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Agilent G1676AA Fiehn GC/MS Metabolomics RTL Library

1. Previous analysis results will be replaced Run Cancel Settings A Help Figure 124 Finally select SAVE to save the analysis settings The settings are saved in the AMDIS32 folder The name of the file is onsite ini Before exiting the dialog it is possible to save the current analysis settings for future reuse Click Save As to invoke the Save Setting As dialog enter a File name and Save in location of your choice and click Save to create your named INI file and to exit from that dialog back to the Analysis Settings dialog If you wish to subsequently reuse the settings in a saved INI file proceed as follows 1 Exit from AMDIS 2 Delete the file onsite ini in the AMDIS32 folder 3 Locate the saved INI file whose values you wish to restore for use in AMDIS 4 Make a copy of it in the AMDIS32 folder and then rename it as onsite ini 5 Restart AMDIS The restored values are now in use It is important to understand that the Analysis Settings dialog reflects the values you last set in it and not always therefore the values used to analyze the data file whose results you are currently examining If you want to see the pertinent values used for the current file use the View gt Auxiliary Information command and select its dialog s Settings tab Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 A single metabolite may be derivatized into several compounds that elute at different retentio
2. 12 Update the method with the new pressure when you are prompted to do so 13 Run a representative sample of metabolites containing the FAMES markers and locking compound using this relocked method on the GC MS system 14 Verify that the retention time of the new run matches the retention time stored in the supplied method RT curve AMDIS RI use An RI is assigned to all compounds in the AMDIS Retention Index Standards file fiehn csl This file contains the 12 FAME compounds used to assign an RI to unknown compounds found in an AMDIS analysis AMDIS uses the RI difference between that calculated from the unknown s RT and that stored in a spectral library to assign a penalty to a spectral match The RT of an unknown compound found in the GC MS ChemStation data files analyzed by AMDIS must be converted to an RI for AMDIS analysis types that assign this RI penalty The AMDIS calculation of an unknown compound s RI is based on the RI of the nearest FAME marker with a higher RT and the nearest FAME marker with a lower RT than the unknown The unknown compound is assigned an RI between these two marker RI values that is proportionate to their RT differences If your method and GC MS system is not identical to those used to create the Agilent Fiehn Library your retention times can be outside an acceptable RT window This would result in an excessive penalty to the match fit moving a potential good match further down the list If thes
3. A value of 0 0 means that the target has been found within the RT window you specified on the Identif tab of the Analysis Settings dialog When the library s expected retention time for 2 amino 1 phenylethanol is compared to the found retention time for it the difference is greater than the Identif tab s RT window and hence a penalty is computed 20 0 in this case The RETENTION penalty is applied to the computed Net match value for the target and reduce the latter s magnitude hence making the component a less favorable hit for the target In this way as a target is found further away from its expected time a larger penalty is applied up to the Maximum penalty value on the Identif tab of the Analysis Settings dialog Agilent Fiehn Metabolomics Library 147 6 148 AMDIS Getting Started Analysis Type RI Calibration Performance If you wish to use retention indices as an additional aid in identifying targets or for checking the performance of the acquisition system AMDIS can use an RI Calibration Data file that holds a correspondence between retention time and retention index The compounds used when creating an RI Calibration Data file are referred to as the retention index standards If compounds are used for performance checking purposes they are referred to as calibration check compounds An RI Calibration Data file has a cal file extension An RI Calibration Data file is used in three of the analysis types
4. Time 6 26 6 48 6 70 6 92 7 14 7 36 7 58 7 79 3 01 8 23 8 45 8 67 8 89 Abundance 27 9 rl Bose 2 ed 1060 pyruvic acid I 7768 epsilon caprolactam E v 250 300 350 400 450 Library Hit 1 2 107689 L lactic acid 6 851 and Extracted spectrum Figure 75 After adjusting the deconvolution parameters The resulting display differs in two respects to the previous display First the header lists 14 targets and 49 components compared previously to 27 and 122 respectively This is because when a deconvolution analysis is run it applies to the current display range only In the first instance the analysis was run when the full chromatogram was being displayed 6 140 AMDIS Getting Started The exact numbers reported for this range depend on the actual retention time range you previously selected by rubber banding Many parameters on the various tabs in the Analysis Settings dialog control deconvolution detection and reporting in AMDIS Fortunately in most cases the default values either work as is or only require minor changes Searching the NIST database From AMDIS you can search the full NIST mass spectral database with a component This capability requires the G1033A NIST Library 1 Click the V above the large peak at 17 6567 min or select it from the retention time list On the Analyze menu click Go to NIST MS Program The NIST MS Search program is invoked and a dialog shows the
5. Analyzing your Data Elns Experiment Creation Wizard Step 9 of 11 x Sample Summary Hovering the mouse over a compound in the graph will reveal the complete identity of the compound A right click mouse action on the graph or the spreadsheet will offer additional display and export options I Export For Recursion Mass Vs RT Compound Frequency Total number of Aligned Compounds 473 Compounds Present 105 123 350 111 102 37118 108 365 1091 364 193 280 212 261 201 Help lt lt Back Next gt gt Einish Cancel Figure 38 Mass vs RT view in the Sample Summary page Step 9 of 11 of the MS Experiment Creation Wizard Step 10 of 11 Normalization Criteria 1 Select the Normalization Algorithm in the Normalization tab e Internal Standard may be applied only to a compound whose frequency equals the number of samples in the experiment are available for selection An internal standard is a compound added to each sample before your GC MS acquisition and used to reduce the abundance variability caused by sample preparation and instrument response Select the compound you want to use for the internal standard from the table that appears after selecting Internal Standard Percentile Shift is an experiment wide normalization that adjusts the abundance of all of the compounds in all of
6. NLM Toxicology Link Chemical Structure Search Chemical Vendors ABI Chem SID 104296390 External ID AC1L1AF SID 117609703 External ID AC1Q74R Achemica SID 162280200 External ID ACMC 1CJK2 AKos Consulting amp Solutions SID 104670273 External ID AKOS000121850 Ambinter SID 118313459 External ID SBB0657 Angene Chemical SID 136430021 External ID AG D 95873 Anward SID 160794969 External ID ANW 274 Biosynth SID 49748376 External ID 0 5000 A Chembase cn SID 162088653 External ID 102212 Chembo SID 162160782 External ID KB 5935C v ChemFxner Chemical Nirectory amp 5 Click the Classification line in the Table of Contents to access links to Substance Categorization Classification Then scroll to the Metabolic Pathways section See Figure 133 204 Agilent Fiehn Metabolomics Library Using CAS and PubChem Numbers 7 Comparative Toxicogenomics Database SID 53787483 External ID D020351 see all 2 Database Vendor 1 record chemicalize org by ChemAxon SID 137002063 External ID 1588 Journal Publishers 3 records Nature Chemical Biology SID 56437667 External ID nchembio 145 comp30 see all 2 Thomson Pharma SID 15297251 External ID 00057572 Metabolic Pathways 5 records BIND SID 841755 External ID 1554 Comparative Toxicogenomics Database SID 53787483 External ID D020351 see all 2 NIH Molecular Libraries 1 record NCGC SID 124955195 Externa
7. On the Library menu click Build One Library In the Build One Library editor that appears click Files and in the next dialog click Load Library Change Files oftype to Calibr amp Stds Library csl and navigate to the AMDIS32 LIB folder Finally click Fiehn csl and Open to load the library into the Build One Library editor Agilent Fiehn Metabolomics Library 153 154 AMDIS Getting Started C AMDIS32 LIB Fiehn CSL Add Rl 800 6 7 8200 min RI CAL 1 Add All Edit Delete d 1 of 14 cp C10 Methyl caprate 10 647 icp C12 Methyl Laurate 13 250 Hide 7 cp C14 Methyl Myristate 15 597 cp C16 Methyl Palmitate 17 723 Sort by Name Files cp C20 Methyl Eicosanoate 21 441 Ees i Exit 3 Help cp C28 Methyl Octacosanoate 27 349 xl Formula C11H2202 Fy Chemical ID 110429 RI 1000 Figure 89 Calibration amp Standards Library dialog Here you can see some of the target compounds that you just successfully located in the RI CALIBRATION d data file The c to the left of the compound name shows that the compound is a calibration check compound and is used as a calibrant in this analysis type A p signifies that a compound is used as a performance check compound Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 If you click Edit you get the Spectrum Editor Calibration Standards Library dialog for the currently highlighted compound and you can see the sor
8. Quadrupole ha CSE seveds Cancel _Deieut Hep Figure 117 184 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Select the Deconv Tab and adjust values as shown below Analysis Settings Figure 118 Deconv Tab in the Analysis Settings dialog box Select the Libraries tab and if the Target Compounds Library is not Fiehn msl select Select New to browse for it Analysis Settings Al Calibration Data Figure 119 Agilent Fiehn Metabolomics Library 185 6 AMDIS Getting Started If the Internal Standards Library is not Fiehn isl select Select New to browse for it Analysis Settings Figure 120 If the Calibration Standards Library is not Fiehn csl select Select New to browse for it Analysis Settings Figure 121 186 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 If the RI Calibration Data is not Fiehn cal select Select New to browse for it Analysis Settings Target Compounds Library Internal Standards Library Calibrati andards Librar Figure 122 Select the QA QC tab and adjust values as shown below f Analysis Settings Figure 123 Agilent Fiehn Metabolomics Library 187 188 AMDIS Getting Started The components of the Agilent Fiehn Library are the recommended libraries for all of the types of analysis x Type of analysis Use RI CalbrData IntemalStd m Intem Std Lib
9. All of the TIC peaks have been detected as Targets 7 The RI Calibration Data file cal that you created is not directly viewable within AMDIS but is a simple text file and can be easily viewed for example using Notepad AMDIS Getting Started 6 B Fiehn cal otepa _____ ee File Edit Format View Help 7 820 800 0 99 417 C8 methyl Caprylate Marker 9 246 900 0 99 436 c9 methyl Perlargonate Marker 641 1000 0 98 439 c10 methyl caprate Marker 245 1200 0 98 459 c12 methyl Laurate Marker 598 1400 0 97 497 c14 methyl Myristate Marker 710 1503 0 84 580 RTL Myristic Acid d27 730 1600 0 98 513 c16 methyl Palmitate Marker 672 1800 0 97 389 c18 methyl Stearate Marker 456 2000 0 96 392 c20 methyl Eicosanoate Marker 96 370 C22 methyl Docosanoate Marker 93 354 c24 methyl Linocerate Marker 96 261 c26 methyl Hexacosanoate Marker 69 325 c28 methyl Triacontanoate Marker 106 2200 635 2400 061 2600 397 2800 OOODODDDDDDDD Figure 88 Ri Calibration Data file listing The pertinent information that it contains per entry is a retention time and the corresponding retention index for example 10 641 and 1000 0 respectively in Figure 88 The retention time is that of a deconvoluted peak and the retention index is taken from the corresponding entry in the Calibration amp Standards Library csl 8 Examine the Calibration amp Standards Library with which you started
10. Items 1 1o0f1 Structure Name Formula DBlinks Oxaloacetate Oxalacetic acid o Oxaloacetic acid HO 3 OH Oxobutanedioic C4H405 42 7 Oo o acid C00036 Oxosuccinic acid keto Oxaloacetate Items 1 1of1 LIGAND KEGG 3 Click on C000036 in the Entry column to display detailed information for the compound See Figure 125 on page 195 194 Agilent Fiehn Metabolomics Library Using CAS and PubChem Numbers Kies COMPOUND C00036 Entry c00036 Compound entry cooose_ Compound o Oxaloacetate Oxalacetic acid Oxaloacetic acid 2 Oxobutanedioic acid Oxosuccinic acid keto Oxaloacetate oO Des oO 0 C00036 Mol file KCF file DB search _Jmol KegDraw R00217 ROO338 ROO339 ROO340 RO0341 ROO342 RO0343 R00344 R00345 ROO346 ROO347 ROO348 ROO350 ROO351 ROO352 R00353 R00354 ROO355 R00357 ROO359 RO0360 ROO361 R00362 R00363 ROO373 ROO400 R00431 ROO477 ROO493 R00695 R00726 R00930 R00931 RO1144 RO1257 RO1447 RO1713 RO1731 RO3735 R05053 ROS758 RO7164 RO7165 R09683 Pathway ko00010 Glycolysis Gluconeogenesis ko00020 Citrate cycle TCA cycle ko00250 Alanine aspartate and glutamate metabolism ko00362 Benzoate degradation ko00620 Pyruvate metabolism ko00630 Glyoxylate and dicarboxylate metabolism ko00680 Methane metabolism ko00710 Carbon fixation in photosynthetic organisms ko00720 Carbon fixation pathways in prokaryotes map01060 Biosynthesis of plant secondary metabolites map0
11. Running AMDIS 116 To simultaneously view AMDIS and its Help window 116 To put AMDIS into an initialized state 116 Confirm Window and Results Window 118 Agilent Fiehn Metabolomics Library Contents To move between windows 118 Confirm Window Appearance 119 Results Window Appearance 126 Analysis Types 128 Tutorials Overview 130 Analysis Type Simple Analysis Type 132 Analysis Type Use Retention Time 141 Analysis Type RI Calibration Performance 148 Analysis Type Use Retention Index Data 156 Analysis Type Use Internal Standards for RI 163 Analysis Type Use RI Calibr Data Internal Std 170 Analysis Type Performance Check for RI 176 Recap 183 Recommended Settings 183 7 Using CAS and PubChem Numbers 191 KEGG LIGAND Database 193 MetaCyc Database 196 ChemSpider Database 199 SciFinder Substance Identifier Database 202 PubChem Compound Database 203 8 Reference Information 207 Definitions 208 Derivatization Instructions 220 References 221 Agilent Fiehn Metabolomics Library 7 Contents 8 Agilent Fiehn Metabolomics Library Agilent G1676AA Agilent Fiehn GC MS Metabolomics RTL Library User Guide e oe o e ee 1 a Introduction Scope and Intended Use 10 Library Content 11 Metabolic Profiling Workflow 15 Er Agilent Technologies 1 Introduction Scope and Intended Use 10 The Agilent Fiehn 2013 GC MS Metabolomics RTL Library is intended to be part of a solution for la
12. C AMDIS32 LIB Fiehn CSL Intern Std Lib CAAMDISSZSUBSFiehn ISL RI Calib Data C AMDIS32 LIB Fiehn cal Previous Ri calibration data will be replaced Cancel Settings Help Figure 84 Analyze GC MS Data dialog on entry RI Calibration Performance The button that was labeled Target Library for a Simple and Use Retention Time analysis is now labeled Calib Stds Lib Agilent Fiehn Metabolomics Library 149 150 AMDIS Getting Started 3 Click Calib Stds Lib to invoke the Analysis Settings dialog and on the Libr tab with Calibration Standards Library highlighted click Select New In the Calibration Standards Library dialog navigate to the AMDIS32 LIB folder select the file Fiehn csl and click Open to return to the Analysis Settings dialog with the full path of the Fiehn csl file shown as the Calibration Standards Library in the lower half of the dialog Click Save to return to the Analyze GC MS Data dialog Click RI Calib Data to invoke the Analysis Settings dialog and on the Libr tab with RI Calibration Data highlighted click Select New Type New cal as the File name Click Open to return to the Analysis Settings dialog with the full path of the New cal file shown as the RI Calibration Data in the lower half of the dialog Click Save to return to the Analyze GC MS Data dialog A new file New cal is created to avoid overwriting the Fiehn cal file Analyze GC MS Data 1 x GC MS Dat
13. Methyl Myristate 15 597 15 596 124 10 7 1400 86 79 C15H3002 1E Cpd 18 RTL Myristi a T 18 RTL Myristic Acid d27 16 727 16 709 60658 4 1503 57 65 C15HD2702 1 Cpd 19 16 723 ral 19 16 723 fl 20 C181 Methvl Palmitate 17 7731 17 778 117 29 0 1600 RSNA C17H3407 137 j Crd 20 IC161 Methyl J Figure 16 Compound List window in the Qualitative Analysis program In the first level of the table you see results for each compound In the second level of the table you see results for each identification technique that you tried The second level shows each of the possible matches for the selected compound You can compare the retention time value RT with the number in brackets at the end of the Name of the match For example for compound 16 the retention time RT of the compound is 13 243 and the retention time shown in the Name is 13 250 The CAS number for the Best match is included in the first level of the table The RT DB column shows the retention index of the match in the library The retention index is used as an index into the RT calibration file Ignore the RT Diff column when you run the Search Unit Mass Library algorithm It shows the difference between the retention time of the compound and the RT DB value for the match The RT DB value is actually a retention index so it is meaningless to subtract the actual retention time and the retention index 14 optional Print a
14. The AMDIS program uses a retention index RI calculated from a compound s actual retention time RT relative to the RT of adjacent FAME markers included in an external calibrated sample Agilent Fiehn Metabolomics Library 47 4 48 Peak Identification Compound Naming in the Agilent Fiehn Library Spectra of chemical derivatives of 669 metabolites have been obtained by individual analyses of GC MS chromatograms In many cases more than one derivative peak per metabolite standard was observed and accordingly the Agilent Fiehn 2013 GC MS Metabolomics RTL Library contains a total of 1 068 mass spectra Since one of the primary ideas of the intended use of the library is to aid communication between analytical chemists and biologists to foster biological interpretations the library naming refrains from using specific chemical structures or the chemical derivatives that are associated with each peak Instead naming refers to commonly used biological names wherever these were available For example the chemical 1 4 diaminobutane which is derivatized using four trimethylsilyl groups to increase volatility is referred to by the name putrescine instead of the chemical name 1 4 N N tetrakis trimethylsilyl diaminobutane Since either way of naming metabolites chemical structure or common biological may lead to confusion the Agilent Fiehn 2013 GC MS Metabolomics RTL Library supports two different database identifiers The CAS number a
15. The Agilent Fiehn Library supports CAS numbers in one field and the name and PubChem number in a combined field A compound identifier is important to pathway analysis as the software needs a means to identify the metabolite to assign it to a pathway Agilent Fiehn Metabolomics Library 19 1 20 Introduction Agilent Fiehn Metabolomics Library z Agilent G1676AA Agilent Fiehn GC MS Metabolomics RTL Library A 2 User Guide amp 8 o o ee 2 at Sample Preparation and Derivatization e r 7 Biological sample extracts 22 e Metabolites 22 Derivatization 22 ae Agilent Technologies 21 2 22 Sample Preparation and Derivatization Biological sample extracts The preparation of optimal extracts from biological samples is very much dependent on the type of matrix analyzed and the class of compound that is of interest for the study The exact procedures have to be carefully examined and are not part of this guide Metabolites Metabolites are generally small molecules and most primary metabolites bear hydrophilic functional groups such as carboxyl hydroxyl or amino groups According to the functional groups these molecules are often classified into amino acids carbohydrates fatty acids and organic acids The presence of a variety of hydrophilic functional groups enables cells to use metabolites for a variety of cellular purposes including transport in the aqueous cellular environment or betwe
16. You have been shown how to view and perform basic interpretation of results and it was mentioned how to print and create reports All of this should give you the confidence to begin serious work with AMDIS The rest of this User Guide is written in the style of a reference document giving full details of all features with little or no reference made to supplied example files However it does cross reference tutorial sections where relevant to enable you to refresh your memory of a technique that you perhaps use only occasionally Recommended Settings The settings that are shown in the following figures are the recommended settings that are used for most analyses These recommendations are best used as a starting point to become familiar with AMDIS The AMDIS online help provides detailed information for each setting Individual data files sample matrices and experimental objectives may require other settings Agilent Fiehn Metabolomics Library 183 6 AMDIS Getting Started Analysis Settings Instument Decon Libraries QAVQC a Use RI Calibration Data x Nonpolar es Figure 116 It is important to note that the recommended settings are extremely prejudiced against prospective targets that do not meet the retention indice requirements 10 RI units Select the Instrument tab and adjust values as shown below Analysis Settings Decon Libraries avac vw iO M o inot z fasene zl
17. e Information Lists e Mass Spectral Display If you wish to adjust the scaling of the Chromatogram Display or Mass Spectral Display areas you can do this interactively After bringing AMDIS to a known state the profile display shows the TIC and the model ion for the selected target or component To show additional ions select the Select M Z item from the Options menu and increase the number of major m z from 1 to 3 Select M z m lon chromatograms Enter m z between 0 and 1999 Chromatogram HERNEENN ame x m Component window Number of major m z OK Cancel Help PER Figure 64 Comments Showing additional ions Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 AMDIS Chromatogram Component Mode L HISTIDINE D File Analyze Mode View Library Options Window Help Il C AMDIS32 DATA HP L HISTIDINE D DATA MS 8 72 1191 15 10 18 29 2149 2468 2787 3106 34 25 37 44 Abundance 9 44 17 6567 18 8953 earic acid 1TMS STD RTL Myristic Acid ar TR FRA Component Purity 53 RI Alflib 3 6 Amount 0 0615 Net 96 Min Abund 1 0 xl Expec RT 20 68 gt 350 400 Figure 65 Confirm window showing the graphical results of an analysis for a component Agilent Fiehn Metabolomics Library 121 AMDIS Getting Started Sg AMDIS Chromatogram Target Mode L HISTIDINE D File Analyze Mode view Library Options Window Help 1 C AMDIS32 DATA
18. 2 See a 11 40 11 60 11 80 12 00 12 20 12 40 12 60 12 80 13 00 13 20 13 40 13 60 13 80 14 00 Time Figure 3 The total ion chromatogram of oxaloacetate detects the derivatized compound at 12 450 minutes retention time The retention index marker methyl laurate elutes at 13 239 min 26 Agilent Fiehn Metabolomics Library Abundance 700000 600000 500000 400000 300000 200000 1 100000 52 0 60 0 m z Sample Preparation and Derivatization 2 73 1 scan 1034 12 449 min 073007 026 D data ms 147 1 98 1 202 1 290 2 119 0 172 0 230 1 261 2 326 9 80 100 120 140 160 180 200 220 240 260 280 300 320 340 Figure4 The electron impact mass spectrum of derivatized oxaloacetate MW 305 The pseudomolecular ion at M 15 is clearly detectable at m z 290 In most trimethylsilylated GC MS spectra the trimethylsilyl fragment is detected as base peak m z 73 whereas m z 147 represents a rearrangement product of trimethylsilyl O dimethylsilyl indicating the presence of at least one hydroxyl group in the compound substructure Derivatization of N Acetylaspartate N acetyl aspartic acid comprises two hydroxyl groups and a secondary amine Carbonyl groups adjacent to heteroatoms such as nitrogen in the case of the N acetyl group or oxygen in the case of ester groups are not electropositive enough to become target of nucleophilic attack by the methoxyamine reagent Therefore the methoxymation step does not alter t
19. 3 740 mi Ee UbSesrch C14 Methyl Myristate 115 597 Cisnno2 7513 753 m0 207 Fient lu Sean 14 569 14 607 min a C LibSearch C16 Methyl Palmitate 17 723 cm ne ne 1600 12350 FiehnL lu Scan 16 665 16 702 min a C LibSearch 16213400 Cholestrol D6 27 548 C27H400601 7152 7152 282254 1721 846 FiehnL ulu Scan 18 354 18 410 min a C LibSearch C8 Methyl Caprylate 7 812 C9H1802 70 85 70 95 800 1 1 5 Fiehn L luli Scan 18 410 18 466 min a LibSearch 18407 4 acetylbutyric acid 1 10 63 C6H1003 682 682 999 96 13022 85 0 Fiehn L ills Scan 10579 18629 ie a e LibSearch 15609 methyl heptadecanoate 18 711 C18H3602 6728 67 28 17026 11731825 Fiehn L am a epee a C LibSearch C18 Methyl Stearate 19 663 CisH3202 6609 6609 1800 12518 FienL Background Spectra La Compounds E D pome eiii ll OAE ikas hod Items ji z ame 2G is a A Ubrary Search Search Resuts x105 IC12 Methyl Laurate 13 250 Scan 12 261 12 298 min 7 Scans a 8 2 7 le 6 5 Search Database Settings Scoring 4 ee al Were Search Accurate Mass Library Aw Use RT match 2 Generate Formulas T 1 Trapezoidal 0 Match Sequences 4 lub 1 Fer Du un 100 150 200 250 300 350 400 450 500 550 Combine Identification Results S ii Im aan q Figure 12 Qualitative Analysis after Search Unit Mass L
20. 48915 Thermo Rockford IL to the methoxyaminated samples The mixture is incubated at 37 C for 30 minutes The derivatized samples are cooled to room temperature before being transferred into GC vials The vials are injected for GC MS analysis under the conditions given in the Acquisition Method section When analyzing multiple samples randomize the injection order to reduce the affects of variable reaction times on statistical analysis Agilent Fiehn Metabolomics Library Acquisition Method Experimental and Instrument Method 3 The following method was used to acquire the retention and spectral data used in the library This GC MS ChemsStation method is also installed in your ChemStation s method directory See GC MS ChemStation files on page 12 Equipment Agilent 6890GC 5975MSD or Agilent 7890A 5975MSD system Inlet Type Mode Initial temp Pressure Split ratio Split flow Total flow Gas saver Saver flow Saver time Gas type Column Split Splitless Split 250 C On 9 02 psi On This pressure is not an absolute setting The actual setting for your system is determined during the RTL procedure The field run RTL acquired pressure is then saved with your method 10 1 11 1 mL min 15 2 mL min On 20 0 mL min 3 00 min Helium Agilent ZORBAX DB5 MS 10m Duragard Capillary Column Part number 122 5532G Santa Clara CA 30 m X 250 um X 0 25 um max temperature 325 C
21. Adda Edi Delete C10 Methyl caprate 10 647 C12 Methyl Laurate 13 250 C14 Methyl Myristate 15 597 C16 Methyl Palmitate 17 723 C18 Methyl Stearate 19 663 C20 Methyl Eicosanoate 21 441 C22 Methyl Docosanoate 23 082 C24 Methyl Linocerate 24 603 C26 Methyl Hexacosanoate 26 023 C28 Methyl Octacosanoate 27 349 zi K 9 595 Figure 104 Internal Standards Library dialog Hide 7 Sor by Name x Here you can see the list of internal standard compounds that you just located in the RI Calibration d data file If you click Edit you get the Spectrum Editor Internal Standards Library dialog for the currently highlighted compound and you can see the sort of information stored for an entry Click Cancel to exit from the dialog and leave the values unchanged Click Exit to return to the Confirm window Agilent Fiehn Metabolomics Library 169 6 170 AMDIS Getting Started Analysis Type Use RI Calibr Data Internal Std The Use RI Calibr Data Internal Std analysis type is equivalent in operation to the Use Retention Index Data analysis type that you have already learned about Therefore to derive maximum benefit you need a Target Compounds Library with retention index RI information stored in it and an RI Calibration Data file An Internal Standards Library is also required but unlike in the Use Internal Standards for RI analysis type you just examined the int
22. ChemSpider Searches v Properties e Experimental data Predicted ACD Labs Predicted EPISuite Predicted ChemAxon Predicted data is generated using the ACD Labs ACD PhysChem Suite for more information see their website ACD LogP 1 821 of Rule of 5 0 Violations ACD LogD pH 5 5 6 53 ACD LogD pH 7 4 6 57 ACDIBCF pH 5 5 1 00 ACDIBCF pH 7 4 1 00 ACD KOC pH 5 5 1 00 ACDI KOC pH 7 4 1 00 H bond acceptors 5 H bond donors 2 Freely Rotating 3 Polar Surface Area 91 67 A Bonds Index of Refraction 1 498 Molar Refractivity 23 739 cm Molar Volume 80 934 cm Polarizability 9 411 104cm Surface Tension 77 2590026855469 dyne cm Density 1 632 g cm Flash Point 174 794 C Enthalpy of 64 358 kJ mol Vaporization Boiling Point 341 931 C at 760 mmHg Vapour Pressure 0 mmHg at 25 C m EJ Figure 130 ChemSpider finds Oxaloacetic acid Agilent Fiehn Metabolomics Library 201 7 202 Using CAS and PubChem Numbers SciFinder Substance Identifier Database SciFinder provides a proprietary substance identifier database The example below shows that a query using the same CAS number searched in our other examples returns approximately 5 054 references Note You must have an account with Chemical Abstracts Service CAS in order to access the SciFinder Substance Identifier database More information is available at CAS https www cas org products scifinder SciFinder Explore Saved Sea
23. Extraction The process of retrieving a deliberate subset of data from a larger data set whereby the subset of the data preserves the meaningful information as opposed to the redundant and less meaningful information Also known as data extraction Family A group of proteins related by structure function or another biological parameter Feature Independent distinct characteristic of a phenomena and data under observation Features are an important part of the identification of patterns pattern recognition within data whether processed by a human or by artificial intelligence such as Agilent MassHunter Workstation and Agilent Mass Profiler Professional In metabolomics analysis a feature is a metabolite and may be individually referred to as a compound molecular feature element or entity during the various steps of the metabolomic data analysis Feature The reduction of data size and complexity through the removal of extraction redundant and non specific data by using the important variables features associated with the data Careful feature extraction yields a Agilent Fiehn Metabolomics Library 211 8 Reference Information Feature selection 212 Filter Filter by flag Function Hypothesis Hypothetical ID Browser Identified compound Independent variable smaller data set that is more easily processed without any compromise in the information quality This is part of the principal component analysis pro
24. HP L HISTIDINE D DATA MS RT 0 001 Figure 66 Time 8 72 1191 1510 1820 2190 2468 2787 3106 3425 374 N nr er aoe 20 targets T 8 72 1191 1510 1820 2199 2468 2787 3106 3425 37 15 10 18 20 2149 2468 27 87 31 06 34 25 37 44 stearic acid 1TMS am Ez RTL Myristic Acid ar Purity 53 RIA 36 Amount 0 0615 Net 96 Min Abund 1 0 xl Expec AT 20 68 xl 250 300 350 400 Library Hit 5281 stearic acid LTMS and Extracted spectrum Chromatogram 122 Display Confirm window showing the graphical results of an analysis for a target The Chromatogram Display area generally shows the TIC chromatogram but may also show one or more mass chromatograms The X axis shows retention time in decimal minutes and the Y axis is a relative abundance percentage scale with the absolute abundance value representing 100 given at the top left of the display for example 241074 in Figure 65 and Figure 66 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 To the right of the abundance value for analyzed data and as appropriate are the numbers of found targets T symbol and components V symbol where the count of components includes the targets Along the top of the chromatogram graphical display area are rows of T and symbols which are dark blue and positioned at the retention times at which these compounds were determined by the deconvolution process The currently selected tar
25. JT Do not show this dialog again Lo ee Figure 22 Startup dialog box Step 2 Create New Project 1 Type a descriptive unique name for your project in Name in the Create New Project dialog box 2 Type information about your project in Notes 3 Click OK x New Project Details Name GC MS Unidentified Notes Data source from AMDIS ok cancel Il Figure 23 Create New Project dialog box Step 3 Experiment Selection 1 Click Create new experiment in the Experiment Selection Dialog dialog box 2 Click OK Elexperiment Selection Dialog x Choose whether you would like to be guided through the creation of a new experiment or if you would like to open an existing experiment from a previous project Choose Experiment Help ca Cancel zT Figure 24 Experiment Selection Dialog dialog box Agilent Fiehn Metabolomics Library Analyzing your Data 5 Step 4 New Experiment A summary table of selections and entries for the New Experiment dialog box is shown in Table 2 on page 82 1 Type a descriptive name for your experiment in Experiment name in the New Experiment dialog box 2 Select Mass Profiler Professional for Analysis Type 3 Select the Experiment type that matches your source data If your data has been process using AMDIS e Select Identified to use AMDIS find data files e Select Unidentified to use AMDIS elute data files e Select Combined Identified Unident
26. Library Analyzing your Data 5 A one hit wonder is a compound that appears in only one sample and is absent from the replicate samples Therefore a one hit wonder compound does not provide any utility for statistical analysis and you want to filter such compounds from your analysis If most of the one hit wonders the number of compounds in the compound frequency table with unit frequency Frequency 1 have a low relative abundance less than 10 and ideally less than 1 your sample data alignment is likely good If the one hit wonders have a high relative abundance i e in the 30 100 column then you may need to improve your sample data alignment See Figure 37 on page 95 4 Click Next IEMS Experiment Creation Wizard Step 9 of 11 xj Sample Summary Hovering the mouse over a compound in the graph will reveal the complete identity of the compound A right click mouse action on the graph or the spreadsheet will offer additional display and export options 7 Export For Recursion Total number of Aligned Compounds 473 Mass sRT Compound Frequency Total Samples 9 No of Compounds a 8 a 8 Sa ae o i 9 8 7 6 5 Frequency Help lt lt Back Next gt gt Einish Cancel Figure 37 Compound Frequency view in the Sample Summary page Step 9 of 11 of the MS Experiment Creation Wizard Agilent Fiehn Metabolomics Library 95 5 96
27. Library 85 5 86 Analyzing your Data EIMS Experiment Creation Wizard Step 1 of 11 x Select Data Source Choose the data sources that will be used for the experiment C MassHunter Quant MassHunter Qual MassHunter ICP MS Chemstation Generic Organism Vitis vinifera X Help Bad Next gt gt Einst Cancel Figure 27_ Select Data Source page Step 1 of 11 of the MS Experiment Creation Wizard Step 2 of 11 Select Data Source 1 Click Select Data Files to display the file selection dialog box Figure 28 2 Select files you want to import into the experiment in the Open dialog box Data processed using the Agilent Fiehn Library results in two output files that can be used for statistical analysis elute data file elu and find compound data file fin The elute file contains a detailed ion and abundance data listing for all of the peaks features found and is imported with Identified and Combined Identified Unidentified experiment types Note The fin files contain some AMDIS parameters that are important to properly importing the unidentified data contained on the elu files When you import elu data files for an Unidentified experiment the fin files must also be located in the same folder in order for the sample files to import properly The find compound file includes all of the information contained in the elute file and additionally contains the Agilent Fiehn Library se
28. Settings Help Figure 98 Analyze GC MS Data dialog Use Internal Standards for RI The RI Calib Data in the dialog is disabled This type of analysis does not involve the use of an RI Calibration Data file 3 Although retention index values are automatically computed in this analysis type you still need to tell AMDIS exactly how to use them Click Settings and in the Analysis Settings dialog click Identif Now set Minimum match factor to 65 and check Show Standards 164 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Analysis Settings Identif Inst Deconv Libr Q4 QC Scan Sets jes Minimum match factor Multiple identifications per compound IV Show standards I Only reverse search Type of analysis use Internal Standards for AI RI window 20 0 x OOTRI Match factor penalties Level Average 7 20 Maximum penalty fio No Al in library Save ds Cancel Default Help Figure 99 4 We are now ready to perform the analysis Click Save to exit the Analysis Settings dialog and return to the Analyze GC MS Data dialog Click Run to start the analysis Within a few seconds the results are displayed in the usual format Set the Information Lists area to view only the best hits and then examine RI RI lib values for the found targets If the RI RI lib label and value are absent the library entry does not have an RI
29. The filter is specified by typing the minimum percentage and selecting the applicable condition Type 100 in the Retain entities that appear in at least box Click of samples in at least one condition Click OK Review the profile plot and repeat the Re run Filter until you obtain the best results for your experiment Compare the entity summary above each profile plot in Figure 46 on page 104 and Figure 47 the displayed number of entities declined from 261 to 131 Click Next Agilent Fiehn Metabolomics Library Analyzing your Data 5 Asampie c sample Help H lt csack NEESS nen canei Figure 47 Filter by Frequency page of the Analysis Significance Testing and Fold Change Step 4 of 8 workflow CE Filtering Conditions Retain entities that appear in at least 100 0 of all samples of samples in only one condition of samples in at least one condition C of samples within each condition x Cancel Figure 48 Filter Parameters dialog box Step 5 of 8 QC on samples 1 Review your data change the plot view export selected data or export the plot to a file QC on samples provides you with the first view of the data using a Principal Component Analysis PCA PCA allows you to assess the data by viewing a 3D scatter plot of the calculated principal components You want your samples to form discrete groups in the 3D PCA Scores view base
30. Using Agilent GC MS ChemStation The Agilent GC MS ChemStation software supports three ways to use the Agilent Fiehn Library for peak identifications e PBM Quick Search interactive single spectrum search e Library Search Report all hits for every peak e Screen Report examine every compound stored in an RTL screen database to see if any exist in the sample PBM Quick Search A selected spectrum can be searched against a library in the Agilent GC MS ChemStation using PBM Quick Search This ChemStation search benefits from the Agilent Fiehn Library compound naming convention which includes a bracketed RT value as part of the library name See Compound Naming in the Agilent Fiehn Library on page 48 for more details This example assumes the included Fiehn M method is already loaded This method uses the Fiehn L library stored in the Database directory To confirm this library use from the Spectrum menu select Select Library before proceeding 1 Select the peak s scans used for library searching from the TIC by using the mouse The averaged spectra for the selected scans is displayed in the spectrum window In this example a peak at 17 191 minutes retention time was chosen 2 Select PBM Quick Search from the Spectrum menu The PBM Search Results dialog box is shown in Figure 8 The selected spectrum is displayed graphically at the top of the window with the currently selected PBM Search Results dialog box library comp
31. a population so that when the samples are evaluated a value is obtained that more closely approximates the true value Sample A part piece or item that is taken from a specimen and understood as being representative of the larger specimen e g blood sample cell culture body fluid aliquot or population An analysis may be derived from samples taken at a particular geographical location taken at a specific period of time during an experiment or taken before or after a specific treatment A small number of specimens used to represent a whole class or group Agilent Fiehn Metabolomics Library 217 8 218 Reference Information Sample class prediction Specimen Spike Standard Standard deviation State Statistics Subject Survey t Test A workflow used to build a model and classify samples from mass spectrometry data Class prediction is a supervised learning method and involves three steps validation training and prediction The algorithm learns from samples training set with known functional class and builds a prediction model to classify new samples test set of unknown class An individual organism e g a person animal plant or other organism of a class or group that is used as a representative of a whole class or group The specific and quantitative addition of one or more compounds to a sample A chemical or mixture of chemicals selected for use as a basis of comparing the quality of an
32. a repeating molecular group to form a larger molecule Agilent Fiehn Metabolomics Library 215 8 216 Reference Information Pooled sample Principal component Principal component analysis Process Protein Proteomics Quality When the amount of available biological material is very small samples may be combined into a single sample pooled and then split into different aliquots for multiple analyses By pooling the sample sufficient material exists to obtain replicate analyses of each sample where formerly there was insufficient material to obtain replicate analytical results The trade off loss of information about the biological variation that was formerly present in each unique sample is offset by a gain in statistical significance of the results Transformed data into axes or principal components so that the patterns between the axes most closely describe the relationships between the data The first principal component accounts for as much of the variability in the data as possible and each succeeding component accounts for as much of the remaining variability as possible The principal components often may be viewed and interpreted most readily in graphical axes with additional dimensions represented by color and or shape representing the key elements independent variables of the hypothesis This is part of the principal component analysis process employed by Agilent Mass Profiler Professional The mathem
33. ad Stepe alculate from statistical analysis To apply te new p value cutoff rag the p value cut der or hput the new cut cf valse in the textbox You wil not be able to proceed to Group Satis Displaying 96 ouk cf 131 entes satisfying corrected povalu cut off 0 03 4 Fiter By Frequenc An Oneway ANOVA erjaniriHochberg Pall rzon Pano P zoor Poon 7 zooo BI EI 70 ei 5 al i Tl 0 D Compound D D Cor 72 0655 86157 1 94E 15 684 144 88 0025 620225 L ose 1a 2756 12 65 0850 042390 1 93c 05 13 05 88 0035 345850 2536 02 3 588 02 8 0027 293634 5 25E 15 1 72E 13 73 0062 617535 3236 15 141 13 72 0656 76752 2 55E 03 162602 ja8 0927 247314 3 10E 02 4326 02 104 0 42 08995 78 14 74 13 43 0 13 840567 Z 4EE 06 5 70E 08 55 0017 21261 5186 08 112 04 9 0018 16110 4 56E 07 2 11E 06 73 0962 538218 1 30E 02 2 446 02 83 0 53 502094 5 56E 09 LSIE 08 32 0 1 2035444 3 00E 02 4326 02 72 0056 64532 1926 12 1 696 12 155 0839 090385 2 99602 4326 02 91 0095 392240 1578 04 3826 04 99 0 45 95206 3 53E 04 1716 03 73 0867 87475 2 00E 02 3 40E 02 99 0045 945225 2 596 02 3 90E 02 137 0849 324036 3 14612 1516 11 71 0 10 616377 4716 08 1 05E 04 101 0436 84603 8 586 05 1 83E 0ale pyalue cutoff pos Hep lt lt Back _Net gt gt fins cancel Figure 50 Significance Analysis page of the Analysis Significance Testing and Fold Change Step 6 of 8 workflow Step 7 of 8 Fold Change 1 Review the summary plot Fold change is a signe
34. an analysis The three areas of the Results window are e Control Panel e Information Lists e Information Tabs The Control Panel is a series of command buttons that control the operations available in the Results window Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 The Information Lists area has four sections arranged more or less as quadrants The upper left quadrant is a list of retention times for all targets The upper right quadrant is a list of hits identifications from a target library The lower two quadrants provide various details about the target as determined during the deconvolution process When you click a value in either upper quadrant the lower two quadrants and certain of the tabs in the Information Tabs area changes to reflect the chosen retention time or hit The Information Tabs area has a number of selectable tabs The Library and Spectra tabs change to reflect the selection in the Information Lists Other tabs show data that are independent of the particular targets and so do not change as different selections are made Agilent Fiehn Metabolomics Library 127 6 AMDIS Getting Started Analysis Types AMDIS supports several different analysis types for determining whether or not deconvoluted spectra from samples match any of the target compounds targets stored in a referenced target library The analysis type you choose depends to a large extent on the type of data that you are working wit
35. been extracted from the data file but have no match in the library Many of these unidentified components are in the first few minutes of the data file Expand the display to see components in more detail As an example position the mouse pointer at the 25 position of the TIC graphical display area at about 0 00 min While holding down the left mouse button drag the mouse to the bottom of the TIC window at about 8 45 min a rubber band box is displayed as you drag the mouse When you let go of the left mouse button the display expands to make it easier to determine which components remain unidentified Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 BA AMDIS Chromatogram Component Mode L HISTIDINE D File Analyze Mode View Library Options Window Help RN NEN AN 6 26 648 6 70 692 7 14 736 758 7 79 801 8 23 845 8 67 8 89 Model 117 m z xl Weighted 71 Abundance 17 9 Scan 2800 23 495 min 100 150 200 250 300 350 400 450 500 Library Hit 1 2 107689 L lactic acid 6 851 and Extracted spectrum Figure 73 Expanded chromatogram If you make a mistake with the rubber banding you can always right click anywhere in the Chromatogram Display area and then click Unzoom to correct the most recent rubber banding or if appropriate Unzoom All to immediately restore the display to its full range Agilent Fiehn Metabolomics Library 137 138 AMDIS Getting Started Individual components can be selected
36. box Agilent Fiehn Metabolomics Library 65 5 Analyzing your Data EES Method Items gt Library Search Search Results Library selection C MassHunter Librany Fiehn L A Add Library Remove Library Settings Scoring Match factor E Use RT match In this example the Trapezoidal BE se retention time is not Penalty free RT Range 0 sec used Gaussian Standard deviation 6 sec Multiplicative Additive Max RT penalty 20 00 RT Calibration file Figure 11 Library Search tab in the Method Editor window 7 In the Data Navigator window click User Spectra to highlight all of the spectra 8 Click Spectra gt Search Library for Spectra You can also right click the spectrum and click Search Library for Spectra If you highlight more than one spectra all of the highlighted spectra are searched 9 In the Data Navigator window click Scan 12 261 12 298 min 66 Agilent Fiehn Metabolomics Library Analyzing your Data 5 Sort by Data File B FAMES 2COL SPLITO1 D vi ape LibSearc SE oy a C LibSearch C10 Methyl Caprate 10 647 C11H2202 77 97 I lulu Scan 6 875 6 913 min a e LibSearch C9 Methyl Pelargonate 9 248 C10H2002 76 78 76 78 900 1221 846 Fiehn L Bilal Soon 703
37. by either clicking the blue V above them or by clicking their RT value in the Information Lists area The currently selected component is identified by its W changing from blue to red The same selection mechanism and color changes apply when viewing targets T Also as a component or target is selected all of the other information in the Confirm window changes to reflect the new selection The deconvolution process does have a few parameters that can be changed by the user and so let s see where these are On the Analyze menu click Settings and in the Analysis Settings dialog click Deconv to select its tab Analysis Settings Identif Inst Deconv Libr GA QC Scan Sets fi 2 Component width M Omit m z Adjacent peak subtraction One v Resolution Medium Sensitivity Low Y Shape requirements Medium i Save ds Cancel Defaut Help Figure 74 Deconvolution tab of Analysis Settings dialog The Analysis Settings dialog is described in detail in the AMDIS online Help file but for now simply change Sensitivity to Low and click Save A message appears noting that the parameters have changed and asking if you want to reanalyze Click Yes Agilent Fiehn Metabolomics Library 35 AMDIS Chromatogram Component Mode L HISTIDINE D Eile Analyze Mode View Library Options Window Help pl C AMDIS32 DATA HP L HISTIDINE D DATA MS Rescate neo L 1 3
38. conditioned before use following the manufacturer s guidelines Agilent Fiehn Metabolomics Library 35 3 36 Experimental and Instrument Method Oven Initial temp Initial time Ramps Rate 10 00 Post temp Post time Run time Mode Initial flow MSD Transfer Line temperature MS acquisition parameters 60 C 1 00 min Final temp Final time 325 C 10 00 60 C 1 00 min 37 50 min Constant flow 1 1 mL min 290 C Tune the MSD make sure to select atune before each batch of samples run and do not exceed 12 hours between each tune Save the tune parameters as atune u Keep a record of atune parameters to monitor MS performance Tune File atune u Acquisition mode Scan MS information Solventdelay 5 90 min EM offset 188 Scan Parameters Low mass 50 0 High mass 600 0 Agilent Fiehn Metabolomics Library Threshold Sample A D samples MSZones MS quad MS source Agilent Fiehn Metabolomics Library Experimental and Instrument Method 150 Changing the Threshold can improve results depending on the sample matrix 2 4 150 C 250 C 3 37 3 Experimental and Instrument Method GC MS Setup Before analyzing samples for metabolites e Verify Quality Control checks e Re lock the Fiehn M method e Update the AMDIS cal file Re lock the Fiehn M method This procedure changes the Fiehn M method s column pressure so that th
39. detailed below in a fume hood Use clean graduated glass syringes for example Agilent p n 5182 9615 to transfer each component to the vial During each addition step do not allow the syringe to make contact with any material already in the vial Transfer 10 ul of pyridine to the GC vial and cap the vial to prevent evaporation Add 10 ul of the FAMEs d 7 Myristic Acid Mixture to the vial and cap the vial Add 80 ul of MSTFA 1 TMCS to the vial and cap the vial Incubate the vial at 37 C for 30 minutes Upon completion of these steps the FAMEs d27 Myristic Acid Mixture is ready for use in GC MS Derivatized samples should be analyzed within 24 hours One single use vial each of pyridine and MSTFA 1 TMCS is supplied with the kit and may be used in a single derivatization procedure Thereafter use the GC MS grade pyridine and MSTFA 1 TMCS reagents in routine use in your laboratory 220 Agilent Fiehn Metabolomics Library Reference Information 8 References Manuals Application Notes This section consists of citations to Agilent manuals primers application notes presentations product brochures technical overviews training videos and software that help you use Agilent products and perform your metabolomics analyses Agilent MassHunter Workstation Software Qualitative Analysis Familiarization Guide for GC MS Agilent MassHunter Workstation Software Quantitative Analysis Familiarization Guide Agilent G
40. e MSTFA Si j O N l o UN 0 oO Figure 2 Two step derivatization of oxaloacetate by methoxymation and trimethylsilylation for GC MS The result is a more volatile and more stable modified derivative of oxaloacetic acid that is easily detectable by GC MS Methoxyamination always leads to syn and anti forms of the derivatized products but these cannot always be separated into two distinct peaks under the GC MS parameters given in the experimental section For oxaloacetate only one peak is observed at 12 45 minutes retention time in Figure 3 The peak found at 13 239 minutes is an internal retention index marker compound dodecanoic acid methyl ester The molecular mass of oxaloacetate MW 132 increases by 29 Da due to the methoximation R2C N OCH3 replacing R2C O and twice by 72 Da due to the trimethylsilylation Si CH3 3 is 73 Da minus the replaced acidic proton The derivatized oxaloacetate has a molecular mass of 305 Da but its molecular ion is not represented in the spectrum The presence of multiple methyl groups due to trimethylsilylation leads to detection of pseudo molecular ions of M 15 as seen at m z 290 in Figure 4 on page 27 Agilent Fiehn Metabolomics Library 25 2 Sample Preparation and Derivatization Abundance 5000000 4500000 4000000 3500000 3000000 2500000 2000000 1500000 1000000 500000 TIC 073007 026 D data ms 13 239 12 450 a i a a DD T ee ee eee a Saree mr rie
41. may be imported from files or previous experiments Selected files and samples 4 5 lA _01 ELU E A_OL FIN lA _02 ELU S A _02 FIN 8 IA_03 ELU lA_03 FIN B_O1 ELU E B_O1 FIN B_02 ELU B_O2 FIN B B_03 ELU B_03 FIN E c oLeU C_O1 FIN 8 C_02 ELU IC_D2 FIN C_03 ELU C C_03 FIN i Select Samples Remove Help lt lt Back Next gt gt nish Cancel Figure 29 Select Data to Import page Step 2 of 11 of the MS Experiment Creation Wizard Step 5 of 11 Sample Reordering 1 Click one or more samples that you want to reorder A selected sample is highlighted using a background color for the sample row 2 Reorder the samples as you like using the reorder buttons up down and restore as often as necessary 3 Mark the sample names using the Select column that you want to import into your experiment 4 Click Next 88 Agilent Fiehn Metabolomics Library Analyzing your Data 5 EIMS experiment Creation Wizard Step 5 of 11 xj Sample Reordering To re order the samples select the samples and use the appropriate buttons on the right to move samples up or down This sample order will be used throught out the experiment Deselect the samples that need not be imported Sample Name A01 aoz a03 B_D1 kakakku pe B_03 co AIS Selec
42. of the experiment will be exported and can be imported later IV Fiehn Unidentified IV Fiehn Identified IV Fiehn Mixed Cox cov Figure 58 Choose Experiments dialog box 4 Select or create the file folder 5 Type the File name 6 Click Save Elsave Bx Savein Ji Fiehn GCMS Data z tee 601 0 J a02 COET _03 0 AMDIS Files a J 8 01 0 J 802 0 J 8 03 0 J coD E J c_2 D J cos i MPP Files r i Original data a My Documents Computer Ta Filename Fiehn Project Save gt MOUSE Files of type Tar archive tar Cancel Figure 59 Save dialog box 7 Click OK in the Information dialog box that confirms your project was saved Agilent Fiehn Metabolomics Library 113 5 114 Analyzing your Data Functional areas of MPP The main functional areas of the Mass Profiler Professional screen are illustrated in Figure 60 The main Mass Profiler Professional window consists of four parts Menu Bar access to actions that are used for managing your projects experiments pathways and display pane views Toolbar access to buttons for commonly used tasks grouped by project experiment entity statistical plot and sidebar tasks Display Pane organized into functional areas that help you navigate through your project experiments analyses and available operations Status Bar information related to the current view cursor position entity and system me
43. population Thus increasing the sample size greatly improves the accuracy of the sample set in describing the characteristics of the population Replicate sampling Sampling the entire population is not typically feasible because of constraints imposed by time resources and finances On the other hand fewer samples increase the probability of making a false positive or false negative correlation Agilent Fiehn Metabolomics Library 71 5 78 Analyzing your Data System suitability System suitability involves collecting data to provide you with a means to evaluate and compensate for drift and instrumental variations to assure quality results Techniques employed by Agilent and AMDIS software include 1 retention time alignment 2 intensity normalization 3 chromatographic deconvolution and 4 baselining to produce the highest quality results The best results are achieved by maintaining your instrument and using good chromatography Sampling methodology Improved data quality comes from matching the sampling methodology to the experimental design so that replicate data is collected to span the parameter values for each parameter A larger number of samples appropriate to the population under study results in a better answer to your hypothesis An understanding of the methodologies used in sampling and using more than one method of sample collection have a positive impact on the significance of your results Agilent Fiehn
44. publication 5990 6047EN September 1 2010 Agilent Fiehn GC MS Metabolomics RTL Library Agilent publication 5989 8310EN December 5 2008 Agilent METLIN Personal Metabolite Database Agilent publication 5989 7712EN December 31 2007 Agilent Fiehn Metabolomics Library Reference Information 8 Agilent Metabolomics Laboratory The breadth of tools you need for successful metabolomics research Agilent publication 5989 5472EN January 31 2007 BioCyc Pathway Includes BioCyc Pathway Genome databases from the Bioinformatics Genome Research Group at SRI International used under license Databases BIO http www biocyc org Citation based on use of BioCyc Users who publish research results in scientific journals based on use of data from the EcoCyc Pathway Genome database should cite Keseler et al Nucleic Acids Research 39 D583 90 2011 Users who publish research results in scientific journals based on use of data from most other BioCyc Pathway Genome databases should cite Caspi et al Nucleic Acids Research 40 D742 53 2012 In some cases BioCyc Pathway Genome databases are described by other specific publications that can be found by selecting the database and then going to the Summary Statistics pages under the Tools menu The resulting page sometimes contains a citation for that database Agilent Fiehn Metabolomics Library 223 www agilent com Agilent Technologies Inc 2013 First Edition Jul
45. retention time included in the compound name of this library was a correct identification possible The PubChem identifier number is shown circled in orange in Figure 8 Library search report To generate this report from Data Analysis View after doing a manual integration proceed as follows 1 From the Spectrum menu select Library Search Report to display the Library Search Report Options dialog box Library Search Report Options x Style ERIE Destination VW Screen Printer I File Integration Parameter File Browse Spectrum to Use Apex Cancel Help 2 Select Summary to generate a report listing all PBM matches of the current loaded data file to entries in the Fiehn L library This report lists the retention time area Agilent Fiehn Library compound name library compound number and CAS number for each peak s spectral hits required for manual positive identification of all peak matching compounds Select the report destination s Screen Printer or File 4 Select how the peak s spectrum is extracted for searching Agilent Fiehn Metabolomics Library Analyzing your Data 5 The spectrum can be taken from each peak s apex the apex minus the spectrum at the start of the peak the apex minus the background at tune or the peak average 5 Click OK to exit the dialog box and print the report to the selected destination Screen report This is a very useful report for met
46. set to Infinite You are now ready to perform the analysis 158 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Analysis Settings Identif Inst Deconv Libr 4 QC Scan Sets jeo Minimum match factor 7 Multiple identifications per compound 7 Show standards J Only reverse search Type of analysis use Retention Index Data Rl window 20 0 x omni Match factor penalties Level Infinite 20 Maximum penalty fio No Al in library Saves Cancel Defaut Help Figure 93 Settings dialog Use Retention Index Data 4 Click Save to exit the Analysis Settings dialog and return to the Analyze GC MS Data dialog If the selected GC MS data file has previously been analyzed the mes sage Previous analysis results will be replaced appears above the bot tom row of buttons otherwise this area is blank GC MS Data C AMDIS32 DATASHPSL HISTIDINE D Type of analysis use Retention Index Data gt Target Library C AMDIS32 LIB Fiehn MSL Inter Std Lib CAAMDISZZKLIESFiehMIST RI Calib Data C 4MDIS32 LIB Fiehn cal Previous analysis results will be replaced Cancel Settings Help Figure 94 Analyze GC MS Data dialog showing warning Use Retention Index Data Agilent Fiehn Metabolomics Library 159 6 AMDIS Getting Started When first running this example the analysis results file for L HISTIDINE d should not exist In any
47. that are examined in the coming sections This tutorial section illustrates how an RI Calibration Data file is created by analyzing a clean mixture of known composition often a C series or homologous series sample It is a prerequisite of this analysis type that a Calibration amp Standards Library exists A Calibration amp Standards Library has a csl file extension Before following the instructions below ensure that AMDIS is in a known state by following the instructions in Figure To put AMDIS into an initialized state on page 116 There should now be an empty Confirm window displayed Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 1 Click File gt Open and in the Select Data File dialog navigate to the AMDIS32 DATA HP folder select the file RI CALIBRATION d and click Open Select Data File Drives Path j C ENAMDIS32 DATANHP ALK3 D Cal d Calibr d 3 Test d 4 4 ai CARDS5P D 4 4 y Eai002 d Eai008 d t GROB D e L Histidine D ais Mvall26 d Instrument agiert ChemStation D gt Cancel VW Confirm file format Open in New Window Figure 83 AMDIS32 DATA HP folder RI CALIBRATION d 2 Click Analyze gt Analyze GC MS Data to invoke the Analyze GC MS Data dialog and set Type of analysis to RI Calibration Performance x GC MS Data C 4 DIS32 DATASHPSAI CALIBRATION D Type of analysis een Calib Stds Lib Emossa Fences
48. that are located in the folder in which AMDIS is installed Their names are perfom idx perform tDB and perform txt If these files already exist and you know you want to preserve them use standard Windows techniques to rename each of them before running this tutorial and then afterwards delete the newly created files and rename your saved files back to their original names 1 Click File gt Open and in the Select Data File dialog navigate to the AMDIS32 DATA HP folder select the file Rl Calibration d and click Open 2 Click Analyze gt Analyze GC MS Data and in the Analyze GC MS Data dialog set Type of analysis to Performance Check for RI Use the Calib Stds Lib and RI Calib Data buttons to select the Fiehn csl and Fiehn cal files respectively The dialog should now resemble x GC MS Data C 4 DIS32 DATASHPSRI CALIBRATION D Type of analysis Performance Check for RI Calib Stds Lib A C AMDIS32 LIB Fiehn CSL Intern Std Lib CAAMDISSZSUIB Fehn ISL RI Calib Data C AMDIS32 LIB Fiehn cal Previous analysis results will be replaced Cancel Settings Help Figure 109 Analyze GC MS Data dialog Performance Check for RI The Intern Std Lib button in the dialog is disabled This type of analysis does not involve the use of internal standards Agilent Fiehn Metabolomics Library 177 6 AMDIS Getting Started 3 Click Settings and in the Analysis Settings dialog click I
49. the File menu click Print Text Report to invoke the Print Text Report dialog Print Text Report Print Onsite report Print Options Figure 114 Print Text Report dialog If you click Print Options the ensuing dialog s settings allow you some control over the textual items that can be printed and are fully described in online Help Experiment if you wish by using Print but finally return to the Confirm window 9 Itis possible to save most of the results of an analysis in textual format for subsequent examination or simply for historical recording or any other reason On the File menu click Generate Report to invoke the Generate Report dialog Agilent Fiehn Metabolomics Library 181 6 AMDIS Getting Started ON FIN l Famm oo Vv M Include only first nits Sense Cancel __ Hp Figure 115 Generate Report dialog Click Cancel to return to the Confirm window 182 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Recap In this section you were introduced to the most commonly used main window of AMDIS the Confirm window and the other major window was briefly described the Results window You have learned the basics of manipulating the display of the Confirm window and have worked through each analysis type in turn In doing this you have used all of the file types that AMDIS supports and you have been introduced to many of the most significant commands and some parameters
50. the sample through spiking the sample with a known compound or set of compounds that does not interfere with the sample Acronym for automated mass spectral deconvolution and identification system developed by NIST http www amdis net Biologically significant molecules that contain a core carbon positioned between a carboxyl and amine group in addition to an organic substituent Dual carboxyl and amine functionalities facilitate the formation of peptides and proteins Abbreviation for analysis of variance which is a statistical method that simultaneously compares the means between two or more attributes or parameters of a data set ANOVA is used to determine if a statistical difference exists between the means of two or more data sets and thereby prove or disprove the hypothesis See also t Test Another term for an independent variable Referred to as a parameter and is assigned a parameter name during the various steps of the metabolomic data analysis Another term for one of several values within an attribute for which exist correlating samples Referred to as a condition or a parameter value and given an assigned value during the various steps of the metabolomic data analysis A technique used to view and compare data that involves converting the original data values to values that are expressed as changes relative to a calculated statistical value derived from the data The calculated statistical value is referred to as the baselin
51. these are compromised by several co eluting peaks for example forward similarity matches gt 600 c Establish the presence and intensity ratios of qualifier ions at the high m z values which are characteristic for a specific metabolite For example spectra for many oligosaccharides would pass forward similarity thresholds and often also coelute at close retention times but can be easily distinguished using characteristic ions or characteristic ion ratios Agilent Fiehn Metabolomics Library Analyzing your Data 5 Using AMDIS Before using AMDIS for analyzing your biological data perform the following e New AMDIS Users Please read Chapter 6 AMDIS Getting Started if you are not familiar with the AMDIS program e Set Up defaults Before using AMDIS for the first time with the Agilent Fiehn Library it is necessary to set up program defaults Start the AMDIS program and set these defaults as specified in Recommended Settings on page 183 Update the AMDIS cal File This procedure is covered in Update the AMDIS cal file on page 40 and must be run before using AMDIS for an analysis using RI data Agilent Fiehn Metabolomics Library 59 5 Analyzing your Data Data analysis The example that follows is the most common AMDIS analysis used for finding metabolites 1 Run the metabolite sample with the Fiehn M method loaded in the GC MS ChemStation The method might be set to print a report in Che
52. was investigated and compared against available GC MS libraries However some false spectra annotations can still exist Contact Agilent if you find any such false spectra When more than one peak was detected for a single compound usually one peak was more abundant than the compound s other derivatives For N acetylaspartic acid an example of a minor 3TMS derivative peak and a major 2TMS derivative peak are included In the Agilent Fiehn Library the different derivatization products of each metabolite are listed by retention time order See Compound Naming in the Agilent Fiehn Library on page 48 for RT information Identification of a single peak is sufficient to identify this compound in a particular sample Derivatization products are included if peak abundance exceeds 1 intensity of the major compound derivative However we have not included the information of major or minor derivatives in the library The relative ratio of two or more derivatives of a single metabolite sometimes depends on the status of the GC MS instrument The cleanliness of the injector system its geometry the syringe the inertness and type of liner the sample matrix to a lesser extent and the parameters used during the derivatization procedure influences this ratio Examples and precautions to be taken are established in the scientific literature Fiehn O Wohlgemuth G Scholz M Kind T Lee DY Lu Y Moon S Nikolau BJ Quality control for plant me
53. window shows the file s TIC in the upper half Chromatogram Display and the spectrum at the center of the displayed TIC range is shown in the lower half Mass Spectral Display see Figure 63 Confirm window showing unprocessed data on page 119 2 Click Analyze gt Analyze GC MS Data to invoke the Analyze GC MS Data dialog and set Type of analysis to Use Retention Time x GC MS Data C AMDIS32 DATASHPSL HISTIDINE D Type of analysis RSS ee gen Intern Std Lib Al Cali Data Cancel Settings Help Figure 76 Analyze GC MS Data dialog Use Retention Time 3 Click Target Library to invoke the Analysis Settings dialog and on the Libr tab with Target Compounds Library highlighted click Select New In the Target Compounds Library dialog navigate to the AMDIS32 LIB folder select the file Fiehn msl and click Open to return to the Analysis Settings dialog Agilent Fiehn Metabolomics Library 141 142 AMDIS Getting Started 4 Click Save to return to the Analyze GC MS Data dialog x GC MS Data C AMDIS32 DATASHPSL HISTIDINE D Type of analysis RSS Ratan Target Library Emossa enms C AMDIS32 LIB Fiehn MSL Inter Std EB CAAMDISSZSUBSFiehn ISL Ail Calis Data CAAMDISS2ZSUBiFiehn cal Previous analysis results will be replaced Cancel Settings Help Figure 77 Analyze GC MS Data dialog readied Use Retention Time The Intern Std Lib
54. 08 Add Parameter Esperance Dae Peraneler Hep lt lt Back Next gt gt fins _ canei Figure 43 Experiment Grouping page of the Analysis Significance Testing and Fold Change Step 2 of 8 workflow Step 3 of 8 Filter Flags 1 Review your data change the plot view export selected data or export the plot to a file 2 Click Re run Filter to enter parameters in the Filter Parameters dialog box Figure 45 on page 103 A flag is used to denote the quality of an entity within a sample A flag indicates if the entity was detected in each sample as follows e Present means the entity was detected e Absent means the entity was not detected e Marginal means the signal for the entity was saturated 3 Mark the Present and Marginal check boxes 4 Clear the Absent check box Click at least __ out of X samples have acceptable values and type 2 in the entry box By setting this parameter to a value of two 2 or more one hit wonders are filtered 6 Click OK Agilent Fiehn Metabolomics Library Analyzing your Data 5 This filter removes irreproducible entities from further consideration as you continue your analysis 7 Review the profile plot and repeat the Re run Filter until you obtain the best results for your experiment Compare the entity summary above each profile plot in Figure 44 and Figure 46 on page 104 the displayed number of entities declined fr
55. 1 m Chemical Structure Figure 131 SciFinder returns a comprehensive list of literature reference information Agilent Fiehn Metabolomics Library Using CAS and PubChem Numbers 7 PubChem Compound Database 1 To access this database enter http www ncbi nlm nih gov sites entrez db pccompound into your Internet browser 2 Enter the PubChem ID number 970 into the search for field and click Go One compound was found for this search 3 Click the 3D Conformer tab Pu bo hem PubChem Compound v Compound Limits Advanced search Help ASN 1 XML SDF Oxaloacetic Acid Compound Summary CID 970 ES gt SE Also known as oxalacetic acid Ketosuccinic acid 2 Oxobutanedioic acid Oxosuccinic acid 2 Oxosuceinic acid 2 3 Ketosuccinic acid Oxobutanedioic acid Properties Molecular Formula C4H4Os Molecular Weight 132 07156 InChlKey KHPXUQMNIQBQEV UHFFFAOYSA N Compound ID 970 A dicarboxylic acid ketone that is an important metabolic intermediate of the CITRIC ACID CYCLE It can be converted Molecular Weight 132 07156 g mol to ASPARTIC ACID by ASPARTATE TRANSAMINASE From MeSH BEER e Aa XLogP3 AA 0 6 Table of Contents Show subcontent titles 2D Structure 3D Conformer H Bond Donor 2 Identification ee H Bond Acceptor 5 Related Records Literature Patents BioActivity Data Links Biomolecular Interactions and Pathways This Compound Biological Test Results with Similar Compounds Classifi
56. 1 00 2572359 25 x Foldcenoececf c o gt tas fr 2 cmiiGow sm 5 Help lt Back LNBESE Einsh Cancel Figure 51 Fold Change page of the Analysis Significance Testing and Fold Change Step 7 of 8 workflow Step 8 of 8 ID Browser Identification 1 Click ID Browser Identification to export your entity list to Agilent MassHunter ID Browser ID Browser is started and automatically prompts you to set up your identification method parameters Processing your entities with ID Browser performs the following automatically save the selected entity list into a CEF file open Agilent MassHunter ID Browser and import the saved CEF file for identification Once identification is completed ID Browser returns an identified CEF file This CEF file is imported into the MPP experiment and annotations are automatically updated 108 Agilent Fiehn Metabolomics Library Analyzing your Data 5 2 Select the compounds to identify and mark the identification method for your experiment in the Compound Identification Wizard dialog box Figure 53 on page 110 3 Click Next Enter the path and file name for the Fiehn library in the Spectral library path in the Settings tab Figure 54 on page 110 5 Adjust the remaining parameters in the Settings Scoring and Search Results tabs to complete setting up your identification method 6 Click Finish when you have the method set up for you
57. 1061 Biosynthesis of phenylpropanoids map01062 Biosynthesis of terpenoids and steroids map01063 Biosynthesis of alkaloids derived from shikimate pathway map01064 Biosynthesis of alkaloids derived from ornithine lysine and nicotinic acid map01065 Biosynthesis of alkaloids derived from histidine and purine z muanNniNncc Biannntihnnim nf nlbalaida it Fenm Inaemnnnnin and All links Ontology 1 KEGG BRITE 1 Pathway 6068 KEGG PATHWAY 63 KEGG MODULE 6005 Chemical substance 7 PubChem 1 ChEBI 1 3DMET 1 HMDB 1 KNApSAcK 1 NIKKAJI 1 PDB CCD 1 Chemical reaction 125 KEGG ENZYME 46 KEGG REACTION 44 KEGG RPAIR 35 Gene 18797 KEGG GENES 18797 All databases 24998 Download RDF Figure 125 Detailed information and links displayed in the KEGG Ligand Database Agilent Fiehn Metabolomics Library 7 aM 195 7 Using CAS and PubChem Numbers MetaCyc Database Home Join MetaCyc Mailing List Faster MetaCyc Search Web Services BT 196 METACYC A member of the Blocyc database collection Search Tools Help 1 To access this database enter http metacyc org into your internet browser 2 Enter the CAS number 328 42 7 into the Quick Search field and click Quick Search LOGIN Why Login Create New Account 328 42 7 Searching MetaCyc change organism database Quick Search Gene Search AML METACYC OVERVIEW MetaCyc is a databas
58. 183 0 53 502094 28382028 00 2476 16 00 own 160 0 68 160 ur 172 0 56 64533 44130396 00 25 40 16 00 up 100 0 00 100 dom 155 0 29 890385 4679154 715 51 16 00 om 479 2 26 4 79 ur 91 0 45 392246 458l EF 4 68 sown 3 07 1 62 3 07 ugl 73 0 67 87475 2 15 z111 215 vom 127 0 84 127 ur 199 0 46 945225 7192 02 7 38 16 00 down 4273337 T538 16 00 up 137 0 49 34036 100 0 00 1 00 om 7931035 00 22 33 16 09 ur 101 0 26 84609 1 72 0 79 173 up 271 Lad 271 ugl 73 0862 624332 1 00 0 00 1 00 Town 4305677 00 22 23 16 09 up 63 0643 38536 1880951 14 20 16 00 vom 31200 3 29 16 09 ur 183 0 31 215335 2 75 1 46 2 75 up 173 0 83 178 up isa 0058 807725 2111842 00 21 57 16 00 own Tal Daal 1 99 up 83 065 6 903497 1 00 0 00 1 00 sown 5579768 00 al 16 00 ur 122 085 1 03483 739 50 75 31 16 00 vom 144542 53 17 14 16 00 up 107 0 53 945736 1 00 0 00 1 00 down 5161122 50 22 30 16 00 u BB 0 22 730045 136 0 97 136 up 5 43 2 45 5 48 ur 105 0 26 59428 337805 58 19 68 16 00 Town 560 2 8 5 60 ur 87 0837 278183 74582752 00 722 13 16 00 down 154 0 63 154 dom 57 0 99 58922 334041290 2107 16 00 vom 144 0 53 144 up 1D8 0 48 593435 1 00 0 00 1 00 down 3776331 00 22 19 16 09 ur 23 0043 288424 BEE FA 16 00 sown 27212 93 1474 16 00 ur 121 0 52 615665 1 00 0 00 1 00 sown 55227950 22 12 16 00 u 128 0 39 39477 1 00 0 00 1 00 down 3895820 00 21 89 16 09 up 81 0620 87874 EICHE 72 58 16 00 down 263 65 3 04 16 00 u
59. 32 LIB Fiehn cal 1S C NAMDIS32 LIB Fiehn ISL RT Fl Names 7820 800 0 C8 9246 900 0 C9 10 641 10000 C10 13 245 12000 C12 15 598 14000 C14 16 710 15030 ATL 17 730 16000 C16 19 672 18000 C18 Bi Figure 106 AMDIS Results dialog Standards tab RI calib It is this RT and RI calibration information that is used to predict the RI of a target from its found RT see below If you click IS the same type of information as described previously for the Use Internal Standards for RI analysis type is displayed Similarly click QA QC and scroll down to the bottom of the Results section Both of the internal standards have been found The difference between RT observed and RT expected together with the match value MF an indication of the overall acquisition system is performing Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 x Library Settings Standards GA OC sen Rests saon Identified 13 of 13 R l Internal Standards 1 STD C8 Methyl Caprylate Marker Defined Ri 800 0 RT observed 7 820 min RT expected 7 83 MF 99 2 STD C9 Methyl Perlargonate Marker Defined Rl 900 0 RT observed 9 246 min RT expected 9 26 MF 99 3 STD C10 Methyl caprate Marker Defined RI 1000 0 RT observed 10 641 min RT expected 10 67 MF 98 2 Figure 107 0A QC results showing the internal standards It is important to understand that m
60. 3835AA MassHunter Mass Profiler Professional Quick Start Guide Agilent publication G3835 90009 Revision A November 2012 Agilent G3835AA MassHunter Mass Profiler Professional Familiarization Guide Agilent publication G3835 90010 Revision A November 2012 Agilent G3835AA MassHunter Mass Profiler Professional Application Guide Agilent publication G3835 90011 Revision A November 2012 Agilent Metabolomics Workflow Discovery Workflow Guide Agilent publication 5990 7067EN Revision B October 2012 Agilent Metabolomics Workflow Discovery Workflow Overview Agilent publication 5990 7069EN Revision B October 2012 Agilent Mass Profiler Professional Agilent publication January 2012 Primers Proteomics Biomarker Discovery and Validation Agilent publication 5990 5357EN February 11 2010 Metabolomics Approaches Using Mass Spectrometry Agilent publication 5990 4314EN October 27 2009 Multi omic Analysis with Agilent s GeneSpring 11 5 Analysis Platform Agilent publication 5990 7505EN March 25 2011 An LC MS Metabolomics Discovery Workflow for Malaria Infected Red Blood Cells Using Mass Profiler Professional Software and LC Triple Quadrupole MRM Confirmation Agilent publication 5990 6790EN November 19 2010 Agilent Fiehn Metabolomics Library 221 8 222 Reference Information Presentations Product Brochures Profiling Approach for Biomarker Discovery using an Agilent HPLC Chip Coupled
61. 5 0 m z 50 100 150 200 250 300 350 400 450 Library Hit 1 2 107689 L lactic acid 6 851 and Extracted spectrum Figure 9 AMDIS after performing a Use RI Calibration Data run Agilent Fiehn Metabolomics Library 61 5 62 Analyzing your Data Using a different analytical method Sometimes it is necessary to use an analytical method that is different from the Fiehn M method for GC MS analysis of a metabolite sample If these method differences do not change the compound elution order it is possible to use AMDIS but not GC MS ChemStation to identify the metabolites using the concepts presented in this guide AMDIS allows you to run a procedure to update the retention time assigned to an external marker s RI value The RI for a compound stored in the library is calculated from the retention times of the FAME markers You can run a sample containing the FAME markers using different methods to obtain the correct FAME RT values You then replace the AMDIS Fiehn cal RT values with the values obtained during the FAMEs run on this new method The RIs in the Fiehn cal file are not changed during this update process permitting the library RI relationship to remain Before running this method you must make it an RTL method using the CG MS ChemStation and a sample containing the locking compound You then run a sample containing the FAME markers with this locked method This data file is then used to update the RT times as show
62. 656 C 1938 ricotinami THEN 23 105 73 3 Cod 19 36 846 Tor _ a 3 855 Tp 45 35 855 i a 3 37 278 _Cpd 23 643801 methyl palmtoleste 17_ 543801 mettyl_ C1743202 522 7 a7 37 738 Cod 87 169141 Shydowaunoine 2 18 69141 Hydor CHNO 57 117 Cod 38067 Cod 14 13017 Ncyetohenifomamide _ EZ ai Cod 6 40360 m 4 Figure 55 ID Browser user interface for reviewing the results Agilent Fiehn Metabolomics Library 111 5 Analyzing your Data Stepe Browser Identification Toidentify the Entties that passedthe Fold change cu of vith Browser cick on the IDBrewser Identification button 1 Summary Report 2 Experiment Goupis Identify Entiteswith Dironser _ ID rowser Identification 3 Fiter Flags Compound FC qE Sampie Log FC dR Sam FC Ghd QR Sa Regulation qE S FC 4C Sampie 10g FC dC Samp_ FC G bo CC Sa Reguiation C 4 FherDyFieauenet Co Mety Pelargonate 9 248 1 00 0 00 1 00 down 401570363 00 23 58 16 00 uel 5 QC en samples 18407 4 acetyburyne acc 1 10 63 365907840 00 28 5 16 00 down 1 09 0 07 1 05 ur a unianeanays CO Meti Pelerconate 9 2481 56 84 1 00 0 00 1 00 dow _17367833 00 24 05 16 00 up lnfieanes analysis 18407 4 acennuryric acid 1 10 63 2385019 75 2119 16 00 un 15405 59 1391 16 00 up 7 Fe
63. 9 Q E t x A C 1f SER r Cpd 16 C12 Methyl Laurate 13 250 Compound Spectrum 13 199 13 324 min RI CALIBRATION D 74 1000 143 1000 lu ETC SEI A tes bon T ende eao 5 60 70 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180 185 190 1 210 Counts vs Mass to Charge m z Figure 15 Qualitative Analysis after Search Unit Mass Library on compounds The compounds are shown in the Compound List window You can change which columns are visible in the table when you right click in the title of the table and click Add Remove Columns Agilent Fiehn Metabolomics Library 71 5 Analyzing your Data C12 Methyl Laurate 13 250 13 243 1200 88 85 C13H2602 1 Best W ID Source Y Name Y Formula Y ScoreY Y RT Diff Y Score Lib Y RT DB VY Library Y LibSearch C12 Methyl Laurate 13 250 C13H2602 88 85 1186 757 88 85 1200 Fiehn L Cc LibSearch 16213400 Cholestrol D6 27 5 C27H40D6 55 97 2809 297 55 97 2822 54 Fiehn L C LibSearch C9 Methyl Pelargonate 9 248 C10H2002 54 74 886 757 54 74 300 Fiehn L LibSearch C10 Methyl Caprate 10 647 C11H2202 54 33 986 757 54 33 1000 Fiehn L C LibSearch C8 Methyl Caprylate 7 812 C9H1802 51 74 786 757 51 74 800 Fiehn L Label YW Show Hide Cpd Y Name Ya RT Y CAS Y RT DB Y Score Y Formula YH Start Cpd 17 C14 Methyl T 17 C14
64. 9a Bologna07 citrate synthase Inhibitor Mechanism unknown of phosphoenolpyruvate synthetase Chulavatna73 malate dehydrogenase NAD requiring Yamaguchi73 Comment 3 fumarate reductase Iverson99 2 oxoglutarate decarboxylase Frank07 citrate lyase Helmward89 glutamine synthetase adenylyltransferase Ebner70 Comment 4 isocitrate dehydrogenase kinase Nimmo84 4 oxalocrotonate tautomerase Orii06 glutamate dehydrogenase Kimura77 succinate dehydrogenase Dey97 ATP citrate lyase Kanao01 References Anderson85 Anderson M Scholtz JM Schuster SM 1985 Rat liver 4 hydroxy 2 ketoglutarate aldolase purification and kinetic characterization Arch Biochem Biophys 236 1 82 97 PMID 3966804 Boland77 Boland MJ Benny AG 1977 Enzymes of nitrogen metabolism in legume nodules Purification and properties of NADH dependent glutamate synthase from lupin nodules Eur J Biochem 79 2 355 62 PMID 21790 d na07 Bologna FP Andreo CS Drincovich MF 2007 Escherichia coli malic enzymes two isoforms with substantial differences in kinetic properties metabolic regulation and structure J Bacteriol 189 16 5937 46 PMID 17557829 Bonete96 Bonete MJ Perez Pomares F Ferrer J Camacho ML 1996 NAD glutamate dehydrogenase from Halobacterium halobium inhibition and activation by TCA intermediates and amino acids Biochim Biophys Acta 1996 1289 1 14 24 PMID 8605224 Bol Bu
65. AMDIS and Agilent MassHunter Qualitative Analysis for finding the metabolites in a GC MS data file This manual and useful application notes are also included The files and programs listed in the following sections are installed on your computer in the specified directories Data processed by AMDIS using the Agilent Fiehn Library results in two output files that can be used for statistical analysis elute data file elu and find compound data file fin The elute file contains a detailed ion and abundance data listing for all of the peaks features found by AMDIS The find compound file includes all of the information contained in the elute file and additionally contains the Agilent Fiehn Library search assignment for each peak feature Data files from single quadrupole MSDs mass selective detectors may also be processed using Agilent MassHunter Qualitative Analysis software Qualitative Analysis generates a single output compound exchange format CEF file cef for each data file After you have found the features metabolites in your GC MS data you can perform statistical and integrated biology analyses using Mass Profiler Professional Mass Profiler Professional imports the files created by AMDIS and Qualitative Analysis User guide Its purpose is to guide the user of this library application to successfully identify metabolites using either the Agilent GC MS ChemStation and the NIST AMDIS programs or the Agilent MassHunter Q
66. Agilent G1676AA Fiehn GC MS Metabolomics RTL Library User Guide RE Agilent Technologies Notices Agilent Technologies Inc 2013 No part ofthis manual may be reproduced in any form or by any means including elec tronic storage and retrieval or translation into a foreign language without prior agree ment and written consent from Agilent Technologies Inc as governed by United States and international copyright laws Manual Part Number 61676 90001 Edition Revision A July 2013 Printed in USA Agilent Technologies Inc 5301 Stevens Creek Blvd Santa Clara CA 95051 Microsoft is a U S registered trademark of Microsoft Corporation Software Revision This guide is valid for A 02 xx revisions of the Agilent G1676AA Agilent Fiehn GC MS Metabolomics RTL Library software where xx refers to minor revisions of the software that do not affect the technical accuracy of this guide Warranty The material contained in this docu ment is provided as is and is sub ject to being changed without notice in future editions Further to the max imum extent permitted by applicable law Agilent disclaims all warranties either express or implied with regard to this manual and any information contained herein including but not limited to the implied warranties of merchantability and fitness for a par ticular purpose Agilent shall not be liable for errors or for incidental or consequential damages in c
67. Database Molecular building blocks of life in the chemical space KEGG2 PATHWAY BRITE MODULE LIGAND COMPOUND GLYCAN REACTION RMODUL Enter C G R RP RC numbers Example C00389 C05903 C06562 C08650 C09727 C09762 Chemical Substances and Reactions KEGG LIGAND contains our knowledge on the universe of chemical substances and reactions that are relevant to life It is a composite database consisting of COMPOUND GLYCAN REACTION RPAIR RCLASS and ENZYME databases whose entries are identified by C G R RP RC and EC numbers respectively ENZYME is derived from the IUBMB IUPAC Enzyme Nomenclature but the others are internally developed and maintained Database Identifier Content ee COMPOUND C number Chemical compound structures KEGG COMPOUND GLYCAN G number Glycan structures KEGG GLYCAN REACTION Rnumber Biochemical reactions Bee RPAIR RP number Reactant pair alignments KEBERFAETON RCLASS RC number Reaction class ENZYME EC number Enzyme nomenclature Search LIGAND for co J bfind mode bget mode LIGAND Relational Database primary re en moo aes a mn database w h the KegDraw interface which i is ase for z ES ee en is on publicly a Search COMPOUND Agilent Fiehn Metabolomics Library 193 7 Using CAS and PubChem Numbers This displays a single result in the Compound Data Search Result screen Compound Data Search Result FR Number of entries in a page 20
68. IST database on page 140 A Target Compounds Library has an msl file extension A Target Compounds Library must exist for a simple analysis to run Before following these instructions ensure that AMDIS is in a known state by following the instructions in To put AMDIS into an initialized state on page 116 An empty Confirm window should now be displayed 1 Click File gt Open and in the Select Data File dialog navigate to the AMDIS32 DATA HP folder select the file L HISTIDINE d and click Open The window shows the file s TIC in the upper half Chromatogram Display The spectrum at the center of the displayed TIC range is shown in the lower half Mass Spectral Display See Figure 63 Confirm window showing unprocessed data on page 119 2 Click Analyze gt Analyze GC MS Data to invoke the Analyze GC MS Data dialog Analyze GC MS Data x GC MS Data C AMDIS32 DATA HPSL HISTIDINE D Type ofanabsis Simple iT i C AMDIS32 LIB PESTPLUS MSL Intern Std Lib CAAMDISSZSUIB Fehn ISL Al Calib Data CAAMDIS32UB4Fiehn cal Previous analysis results will be replaced Run Cancel Settings z Help Figure 68 Analyze GC MS Data dialog Simple 132 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 The text box to the right of the GC MS Data button shows the current data file selection and Type of analysis shows Simple 3 Click Target Library to invoke the Analysis
69. Library Delete Keep Figure 62 Delete Results Files dialog box 5 Click Delete and the newly selected file opens 6 Click File gt Open and select the file you originally opened according to the tutorial s instructions Click Open You are now in the correct state for the tutorial Agilent Fiehn Metabolomics Library 117 6 AMDIS Getting Started Confirm Window and Results Window AMDIS offers two user interfaces windows for you to work with The Confirm window is a full functionality window offering a menu bar and one or more child windows for example Figure 65 on page 121 Each child window has a toolbar several graphical areas and a text area The menu bar provides access to the full functionality of AMDIS and the graphical areas permit interactive manipulations and detailed analysis of the results of AMDIS processing The Confirm window is fully described in AMDIS on line Help and is the window of choice for most users The Results window offers a more limited set of functionality than the Confirm window and in particular does not display graphics nor permit library manipulations It can be useful when it is sufficient to simply review the results of AMDIS processing for example Figure 67 on page 126 The Results window is fully described in AMDIS online Help To move between windows e In the Confirm window click File gt Go to Results to go to the Results window e In the Results wi
70. Metabolomics Library Analyzing your Data 5 Create a new project and experiment When you launch MPP you are guided through four sequential dialog boxes Figure 21 to create a new project and experiment to receive your data Step 1 Startup Select the option to create a new project Step 2 Create New Project Enter descriptive information about your project Step 3 Experiment Selection Select the option to create a new experiment as part of your project Step 4 New Experiment Set up the information to store with your experiment and to guide the analysis process Flow Chart of starting your Project and Experiment Step 1 Step 2 Say Step4 Startup Create New Project F penment New Experiment Selection Dialog V Create your experiment Figure 21 Steps to start a new project and an experiment Step 1 Startup 1 Click Create new project in the Startup dialog box after launching MPP If MPP is already open click Project gt Close Project to close and automatically save any open analysis Then click Project gt New Project to begin creating a new project at Step 2 Create New Project 2 Click OK Agilent Fiehn Metabolomics Library 79 5 Analyzing your Data x Welcome to MassProfiler Pro Select what you would like to do From the options below then click on OK to continue Options Open existing project Open recent project Select recent project GC MS Unidentified
71. Professional software please refer to Using Agilent MassHunter Mass Profiler Professional on page 75 Systems biology analysis The goal of any metabolomics study is to make sense of the metabolic differences discovered in the analysis There are many ways to do this One such approach is to use pathway analysis software to visualize and compare currently known metabolite pathways to highlight the relevant metabolites discovered in the statistical analysis process Agilent MassHunter Mass Profiler Professional MPP software is a powerful chemometrics platform designed to exploit the high information content of mass spectra data and can be used in any MS based differential analysis to determine relationships among two or more sample groups and variables MPP also provides advanced statistical analysis and visualization tools for your experiments and is the only platform that provides integrated identification annotation of compounds and integrated pathway analysis for metabolomic and proteomic studies MPP s pathway analysis tools allow you to analyze and compare entity list data collected using different technologies enabling systems biology analyses Agilent Fiehn Metabolomics Library Introduction 1 MPP software supports the export of comma separated variable CSV formatted files that contain analysis results and compound identifiers The compound identifier comes from compound identifications made using the Agilent Fiehn Library
72. Qualitative Analysis program This example shows searching a compound See Search Unit Mass Library on spectra on page 64 for an example showing how to search a spectrum 1 2 Open the RI CALIBRATION d data file Configure the user interface to include GC algorithms Click Configuration gt User Interface Configuration Mark the GC check box and the Unit mass Q QQQ check box and click OK You can press F1 to get help on any dialog box or window In the Method Explorer window click Find Compounds and then click Find by Chromatogram Deconvolution In the Method Editor window review the parameters for this algorithm For GC MS data a value of 100 is a good starting point for the RT window size factor Click Find gt Find Compounds by Chromatogram Deconvolution With default parameters 43 compounds are found In the Data Navigator window click Compounds to highlight all compounds for this data file In the Method Explorer window click Identify Compounds and then click Search Unit Mass Library In the Method Editor window click Add Library and add the Fiehn l library to the Library selection On the Scoring tab mark the Use RT match check box Agilent Fiehn Metabolomics Library Analyzing your Data 5 10 Click the cai button to select the RT Calibration file 11 Select the RI CALIBRATION csv file An RT Calibration file is a CSV file with four values per line Name CAS number Retention index
73. Run The progress bars indicate the processing operations being performed Within a few seconds the Confirm window is redisplayed showing the results of the deconvolution process AMDIS Simple Figure 71 Agilent Fiehn Metabolomics Library Si AMDIS Chromatogram Component Mode L HISTIDINE D File Analyze Mode View Library Options Window Help DI CA AMDIS32 DATA HP L HISTIDINE D DATA MS E 122 components G 6 2108 7 757 glycolic acid 7 04 6 4066 2 7 12665 2 piperidone 1 8 1 6 4166 7 6058 2 aminoethanethiol 6 8682 4 1060 pyruvic acid 6 7 7 0152 x 7768 epsilon caprolactam Ey Component Match Width 3 6 scans a Expec RT 6 85 a ee 117 Purity 96 Net 73 Model 117 m z gt eighted 71 gt Abundance 17 9 Scan 2800 23 495 min 100 50 350 400 450 500 0 mz SD 100 150 200 250 300 Library Hit 1 2 107689 L lactic acid 6 851 and Extracted spectrum Figure 72 The results of a Simple analysis The file s TIC is presented in the Chromatogram Display area and some but not all of the strong peaks have a T mark above them These are the components that have been identified as target compounds in the Agilent Fiehn Target Compounds Library 27 of its 122 entries have been identified 6 136 AMDIS Getting Started There are also a large number of other components as shown by the V symbols without a T above them These are compounds that have
74. SID column E csv txt MH Qual Find By Molecular Feature Extractor MFE MH Qual GC Scan ind by Chromatographic Deconvolution ICP MS dentified by ICP MS software AMDIS elu Components identified by AMDIS that are not identified by an AMDIS target library Generic xls Entries NOT identified by Compound column C Formula xlsx column D CASID column E csv txt Find By Formula FbF MH Qual GC Scan ind by Chromatographic Deconvolution and Library Search ICP MS identified by ICP MS software AMDIS argets and components discovered by AMDIS elu Generic Combination of entries identified by and not identified by Compound column C Formula column D CASID column E Table3 Summary of data sources and file types based on the selection for Experiment Type in the New Experiment dialog box If you selected Analysis Significance Testing and Fold Change or Data Import Wizard for the Workflow type in the New Experiment dialog box the MS Experiment Creation Wizard is automatically started after this step Agilent Fiehn Metabolomics Library 83 5 84 Analyzing your Data Import and organize your data After you set up your project and create an experiment the MS Experiment Creation Wizard Figure 26 immediately guides you through the nine 9 of eleven 11 steps to organize your experiment import your data define your experiment variables and prepare your data for analysis data preparation includes groupin
75. Settings dialog showing the Libr tab Click Select New to specify Fiehn msl the searchable target compounds library Fiehn msl and other supplied libraries are normally installed in AMDIS32 LIB Analysis Settings Identif Instr Deconv Libr asac Scan Sets MS libraries Rl data View Target Compounds Library Internal Standards Library Calibration Standards Library RI Calibration Data Target Compounds Library E AMDIS32 LIBYFIEHN MSL Save ds Cancel Defaut Help Figure 69 Analysis Settings dialog Libraries tab 4 Click Open to return to the Analysis Settings dialog with the full path of the Fiehn msl file shown after Target Compounds Library in the lower half of the dialog 5 Click Save to return to the Analyze GC MS Data dialog Agilent Fiehn Metabolomics Library 133 134 AMDIS Getting Started xi GC MS Data C AMDIS32 DATASHPSL HISTIDINE D Type of analysis z Target Library C AMDIS32 LIB Fiehn MSL Al Galib Data CAAMDISSZSLIBSFiehn C amp L Previous analysis results will be replaced Cancel Settings Help Figure 70 Analyze GC MS Data dialog readied Simple The Intern Std Lib and RI Calib Data buttons in the dialog are disabled A Simple analysis does not involve the use of internal standards nor does it take any account of retention index information You are now ready to perform the Simple analysis Click Run Select
76. T Diff Y Score Lib Y RT DB Y Library Y 7 ICI ie LibSearch C12 Methyl Laurate 13 250 C13H2602 88 85 1186 757 88 85 1200 Fiehr 9 Cpd 17 C14 Methyl Myristate 15 597 C LibSearch 16213400 Cholestrol D6 27 5 C27H40D6_ 55 97 2809 297 55 97 282254 Fiehr 7 Cpd 18 RTL Myristic Acid d27 16 727 Ie LibSearch CS Methyl Pelargonate 9 248 C10H2002 5474 886 757 54 74 900 Fiehr 7 beni EErEE F LibSearch C10 Methyl Caprate 10 647 C11H2202 5433 986 757 54 33 1000 Fiehr V a Methyl Palmitate 17 C LibSearch Methyl Caprylate 7 81 CSH1802 51 74 786 757 51 74 800 Fiehr E V Cpd 21 C18 Methyl Stearate 19 663 Be Lei F Cpd 22 C20 Methyl Eicosanoate 21 441 Label V ShowlHide Cpd Ya Name Ys RT Y CAS Y RT DB Y Score Y Formula Y Sti Ee ee i Cpd 17 C14 Methyl mM 17 C14 Methyl Myristate 15 597 15 596 124 10 7 1400 86 79 C15H3002 BBG er i Arias 124 603 pd SIRT Ne G 18 RTL Myristic Acid d27 16 727 16 709 60658 4_ 1503 57 65 C15HD2702 J Cpd 26 C26 Methyl Hexacosancate 26 023 Ced 19 16723 16 723 m Cd 20 1C161 Methvi Fi I IC 161 Methvl Palmitate 117 7731 17 778 1600 8509 C17H3407 eg 7 eg z 15 ain Cpd 16 C12 Methyl Laurate 13 250 ECC Scan RI CALIBRATION D 1 08 06 04 13 243 02 Cpd 16 C12 Methyl Laurate 13 250 NT BUT BT e e UST BR 32 3s 343536 Counts vs Acquisition Time min 7 8
77. TMS derivative elutes at 14 955 minutes The internal locking compound trimethylsilylated d27 myristate is detected at 16 724 min The retention index marker methyl tetradecanoate is found at 15 618 min Agilent Fiehn Metabolomics Library 29 2 Sample Preparation and Derivatization Abundance 1000000 900000 800000 700000 600000 500000 202 1 400000 300000 3047 200000 100000 i 376 0 417 3 598 0 ana Hr i a a ER m z gt 50 100 150 200 250 300 350 400 450 500 550 600 73 1 158 1 Scan 1415 14 832 min 1008a07 004 D data ms Abundance 78 1 Scan 1435 14 957 min 1008a07 004 D data ms 100000 90000 80000 274 2 70000 60000 50000 40000 30000 20000 10000 306 2 348 2 414 9 447 2 0 7 MASA AAKAA SAARA MAJAS AASA RASAS GABAA m z gt 4 80 120 160 200 240 280 320 360 400 440 147 1 376 2 Figure 7 Upper spectrum 0 0 bistrimethylsilyl N acetyl aspartic acid MW 319 The pseudo molecular ion m z 304 is present Lower spectrum N 0 0 trimethylsilyl N acetyl aspartic acid MW 391 Both the molecular ion at m z 391 and its pseudomolecular ion after methyl loss are detected at m z 376 30 Agilent Fiehn Metabolomics Library Agilent G1676AA Agilent Fiehn GC MS Metabolomics RTL Library User Guide ee 3 Experimental and Instrument Method Experimental 32 Acquisition Method 35 GC MS Setup 38 Quality Control 42 This section specifies the parameters that were used for estab
78. To use these data files with the MassHunter Qualitative Analysis software see Install the Fiehn library to use with MassHunter Qualitative Analysis on page 63 Application Notes The library locates the following application notes in the Program Files x86 Agilent Fiehn Metabolomics RTL Database G1676AA App Notes directory MSD RTL 5968 3433 pdf Description of RTL method creation and maintenance NIST MS_AMDIS pdf Discussion of the algorithms employed by the NIST and AMDIS search programs Backup files for the library All of the files mentioned above are also located in Program Files x86 Agilent Fiehn GCMS Metabolomics RTL Database directory If you need to replace one of the working files in AMDIS or the GC MS ChemStation with an original file delivered with this library copy the file from this location to your working directory Agilent Fiehn Metabolomics Library Metabolic Profiling Workflow Introduction 1 Metabolomics is the systematic study of the small molecule chemicals metabolites used in the biological processes of an organism A study is typically done by looking at the chemical profile of an organism using either nuclear magnetic resonance NMR or mass spectrometry MS for the chemical analysis This study is often referred to as metabolic profiling The metabolome is the collection of all metabolites in a biological organism and the metabolites are the end products of its gene expression Meta
79. Tools gt Options to launch the Configuration Dialog dialog box Then click MS gt GCMS Peak Alignment Parameters to adjust the calculation coefficients 1 Type a value for Retention Time Tolerance min The default value is 0 05 min 2 Type a value for Match Factor The default value is 0 3 and the value can be between 0 and 1 0 denotes completely different spectra while a value of 1 denotes identical spectra 3 Type a value for Delta MZ Low Resolution The default value is 0 2 m z for low resolution spectra For high resolution spectra the default value is 0 005 m z 4 Click Next EIMS Experiment Creation Wizard Step 8 of 11 Alignment Parameters Unidentified compounds from different samples are aligned or grouped together if their retention times are within the specified tolerance window and the mass spectral similarity as determined by a simple dot product calculation above the specified level Retention Time Tolerance min 0 08 Match Factor 0 3 Delta MZ Low Resolution 0 2 p lt lt Back Next gt gt Cancel Figure 36 Alignment Parameters page Step 8 of 11 of the MS Experiment Creation Wizard Step 9 of 11 Sample Summary 1 Clear the Export For Recursion check box 2 Review the table and chart in the Compound Frequency tab 3 Assess the quality of your sample alignment by reviewing the frequency of compounds that appear in only one sample Agilent Fiehn Metabolomics
80. a C 1 DIS32 DATANHPSRI CALIBRATION D Type of analysis RI Calibration Performance Calib Stds Lib B C AMDIS32 LIB Fiehn CSL Intern Std Lib C AMDISS2Z UBSFiehn ISL CAAMDIS32 LIB New CAL Bun Cancel Settings ze Help Figure 85 Analyze GC MS Data dialog readied RI Calibration Performance 5 The Intern Std Lib in the dialog is disabled An RI Calibration Performance analysis does not involve the use of internal standards You are now ready to perform the analysis Click Run A confirmation dialog appears for you to approve the file selections Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Warning System will use file C AMDIS324LIB Fiehn CSL to build new calibration file C AMDIS32 LIB New CAL Figure 86 Confirmation dialog RI Calibration Performance analysis 6 Click OK to proceed Within a few seconds the Confirm window is redisplayed showing the results of the analysis Agilent Fiehn Metabolomics Library 151 Sg AMDIS Chromatogram Target Mode RI CALIBRATION D Eile Analyze Mode View Library Options Window Help DI C AMDIS32 DATA HP RI CALIBRATION D DATA MS Bm Rescate Into I L Abundance 12 targets T oRBaB gt F 8 44 11 32 14 19 17 07 19 94 22 82 25 69 28 57 3144 34 32 37 10 dance 35 3 812 a 132446 5 gt RI 800 0 fue ase 350 400 450 500 550 Figure 87 RI Calibration Performance analysis results
81. abolite analysis using the GC MS ChemsStation It looks at each RTL compound in a screen database provided with the Agilent Fiehn Library to determine if the screen compound exists in the sample If found in the sample it reports the expected retention time and the difference between this time and the RT of the sample It also reports the target ion response and any out of range qualifiers To generate this report from Data Analysis View with the data file and Fiehn M method loaded proceed as follows 1 From the Tools menu select Specify Method Screen Database to check that Database Fiehn scd is the current screen database 2 From the Tools menu select Change Screen Database Parameters Screen Database Update Set Extraction Windows Set Subtraction Method C Set Uncertainty Type Set Uncertainty Range C Make New RT x SCD Set Other via command Cancel Help Use the Screen database Update dialog box to select the parameters to change that are used for peak identification For more information click Help 3 From the Tools menu select Create Screen Results for Current File to create the screener results file 4 From the Tools menu select Generate Print Screen Report for Current File to send the report to a printer or select Generate Screen Report for Current File to display the report in Wordpad A screen results file must exist or the report is not generated Agilent Fiehn Metabolomics L
82. alysis The Agilent Fiehn Library is specifically built for use with an Agilent GC MS system running the included Fiehn method If the method you are using differs from the Fiehn method see To update the AMDIS cal file on page 58 Peak identification GC MS metabolomics analysis produces three dimensional data that is normally displayed as a two dimensional total ion chromatogram TIC The higher abundance ions obscure lower level metabolites To find the lower level metabolites the three dimensional data is matched using either a forward or reverse peak finding approach Forward peak finding first attempts to find all chromatographic peaks in the TIC and then attempts to identify the found peaks to translate chromatographic peaks into identified compounds Reverse peak finding uses a compound library containing spectral and chromatographic information for specific compounds and searches the TIC data for the presence of each of those library compounds Each peak finding approach has its advantages and disadvantages Reverse peak finding is very good at finding library compounds at low levels but only finds compounds in the library Forward peak finding find peaks that are not contained in a library but tends not to find low level compounds false negatives and find nonexistent compounds false positives Agilent Fiehn Metabolomics Library Introduction 1 The Agilent Fiehn Library works with both forward and reverse peak findin
83. alysis Type Simple Analysis Type 132 Analysis Type Use Retention Time 141 Analysis Type RI Calibration Performance 148 Analysis Type Use Retention Index Data 156 Analysis Type Use Internal Standards for RI 163 Analysis Type Use RI Calibr Data Internal Std 170 Analysis Type Performance Check for RI 176 Recap 183 This chapter is written in tutorial style Follow the examples to learn about the capabilities of AMDIS The whole process should take about 30 minutes For the examples in this chapter AMDIS was installed in the root directory of the C drive The actual location of AMDIS is chosen at installation time The default location is C Program Files NISTMS AMDIS_32 RE Agilent Technologies 115 6 AMDIS Getting Started Running AMDIS 116 To run the AMDIS program select the AMDIS icon on your desktop or click Start gt All Programs gt AMDIS32 gt AMDIS_32 If the NISTO5 Mass Spectral Database and Search Algorithm is installed select Start gt All Programs gt NISTMS gt AMDIS instead To simultaneously view AMDIS and its Help window 1 Click Help gt Contents to open the Help window 2 Ensure that AMDIS and its Help window are not minimized 3 Ensure that all other windows are minimized 4 Right click in any unused area in the Windows task bar to bring up its menu and click Tile Windows Vertically The task bar is usually at the bottom of the screen and has the start button at the left To exi
84. alytical results or for use to measure and compensate the precise offset or drift incurred over a set of analyses A measure of variability among a set of data that is equal to the square root of the arithmetic average of the squares of the deviations from the mean A low standard deviation value indicates that the individual data tend to be very close to the mean whereas a high standard deviation indicates that the data is spread out over a larger range of values from the mean A set of circumstances or attributes characterizing a biological organism at a given time A few sample attributes may include temperature time pH nutrition geography stress disease and controlled exposure The mathematical process employed in manipulating numerical data from scientific experiments to derive meaningful information This is part of the principal component analysis process employed by Agilent Mass Profiler Professional A chemical or biological sample taken from a specimen or a whole specimen that undergoes a treatment experiment or an analysis for the purposes of further understanding Collection of samples from less than the entire population in order to estimate the population attributes A statistical test to determine whether the mean of the data differs significantly from that expected if the samples followed a normal distribution in the population The test may also be used to assess statistical significance between the means of two
85. and RI Calib Data buttons in the dialog are disabled A Use Retention Time analysis does not involve the use of internal standards nor does it take any account of retention index information but there are a few analysis parameters that are specific to the Use Retention Time analysis 5 Click Settings and in the Analysis Settings dialog click Identif Agilent Fiehn Metabolomics Library AMDIS Getting Started analysis settings Identif Instr Deconv Libr 4 QC Scan Sets feo Minimum match factor 7 Multiple identifications per compound Show standards J Only reverse search Type of analysis use Retention Time RT window 02 mir Match factor penalties Level Average x 20 Maximum penalty fio No AT in library Saves Cancel Defaut Help Figure 78 Analysis Settings dialog Use Retention Time RT and its associated Match factor penalties are used by this analysis type only These and the other parameters on this tab are fully described in online Help Select the Deconv tab and specify Very High Sensitivity You are now ready to perform the analysis Agilent Fiehn Metabolomics Library 143 6 AMDIS Getting Started Analysis Settings Figure 79 Analysis Settings dialog Deconv sensitivity 6 Click Save to exit the Analysis Settings dialog and return to the Analyze GC MS Data dialog 7 Click Run to start the analysis and within a few seconds the results ar
86. arch assignment for each peak feature and is imported with Unidentified and Combined Identified Unidentified experiment types Data files from single quadrupole MSDs mass selective detectors may also be processed using Agilent MassHunter Qualitative Analysis Qualitative Analysis generates a single output compound exchange format CEF file cef Agilent Fiehn Metabolomics Library Analyzing your Data 5 e The CEF file is imported with Identified Unidentified and Combined Identified Unidentified experiment types 3 Click Open to load the selected files Review the selected files and use Select Data Files or Select Samples to adjust the selected data files based on your experiment and or advanced search parameters 5 Click Next lookin Ji avosries PS JA_OL ELU 0 02 etu q 4 01 FIN C_02 FIN Recent Items A_D2 ELU C_03 ELU 4 02 FIN 0 03 FIN g A_03 ELU UA_Unknown ELU 4 03 FIN UA_Unknown FIN Desktop B_01 ELU UB_Unknown ELU 6 01 FIN UB_Unknown FIN R B_02 ELU UC_Unknown ELU B_02 FIN UC_Unknown FIN My Documents u B_03 ELU T 8 03 FIN O _o1 elu te C_O1 FIN F Ly Filename 5_01 FIN C_02 ELU C_02 FIN C_03 ELU C_03 FIN Open Network Files oftype amprs Combined ELU and FIN X Cancel Figure 28 Data file selection dialog box Agilent Fiehn Metabolomics Library 87 5 Analyzing your Data Select Data to Import Data
87. area is redrawn to fill the whole height of the display area To zoom a rectangular area of the display do a click drag release operation within the display area to rubber band select the area to be magnified When you release the mouse button the selected area is redrawn to fill the whole display area To cancel the effects of a zoom right click anywhere in the relevant display and click Unzoom or if available Unzoom All on the offered menu Agilent Fiehn Metabolomics Library 125 6 126 AMDIS Getting Started Results Window Appearance The Confirm window shows results for targets and components and the Results window only shows information for targets The Results window has three basic areas and is fully described in AMDIS online Help AMDIS Results L HISTIDINE D Mis x C AMDIS32 DATASHPSL HISTIDINE 30 identifications have been made 1531 2 amino 2 methyl 1 3 propanediol 2 3TMS min amp 66868 porphine 1 2TMS 594 L cysteine 1 2TMS minor 11915 benzoylformic acid 2 1 TMS 1MeOx major 6274 L histidine 1 minor 5143 saccharin 1 1TMS 7 11005 myristic acid 1TMS x Confirm Print Load Results Library Spectra Settings Standards Q4 QC S N Options C Library Component Both 53 0 ll en ra Comey eng ee SEHE 5 54 50 75 100 125 150 175 200 225 250 275 30C 55 Figure 67 Results window shows only the non graphical results of
88. as part of the library name See Compound Naming in the Agilent Fiehn Library on page 48 for more details This example uses the Fiehn L library stored in the Library folder 1 Open the FAMES 2COL SPLITO1 d data file Click File gt Open Data File Select this data file and click Open 2 Configure the user interface to include GC algorithms and to include advanced parameters Click Configuration gt User Interface Configuration Mark the GC check box and the Unit mass Q QQQ check box Mark the Show advanced parameters check box and click OK You can press F1 to get help on any dialog box or window 3 Integrate and extract peak spectra from the data file Click Chromatograms gt Integrate and Extract Peak Spectra You can also right click the chromatogram and click Integrate and Extract Peak Spectra You can limit the number of peaks integrated when you mark the Limit by height to the largest check box on the Integrate MS gt Peak Filters tab in the Method Editor window The averaged spectra for each of the integrated peaks is shown in the MS Spectrum Results window In this example the peak with the 12 28 minute retention time was chosen 4 In the Method Explorer window click Identify Compounds and then click Search Unit Mass Library 5 In the Method Editor window click Add Library and add the Fiehn l library to the Library selection 6 In the Method Editor window on the Scoring tab clear the Use RT match check
89. assHunter Qualitative Analysis on page 63 The library locates the following GC MS ChemStation data files in the MSDCHEM 1 DATA directory RI calibration d L Histidine d Contains all retention index standards Example data file containing derivatized L Histidine FAMES 2COL SPLITOl d Example data file containing FAME markers but using a nonstandard method To use these data files with the MassHunter Qualitative Analysis software see Install the Fiehn library to use with MassHunter Qualitative Analysis on page 63 AMDIS files The library locates the following AMDIS files in the AMDIS32 LIB directory Fiehn msl Fiehn_SIM msl Fiehn isl Fiehn cal Fiehn csl Fiehn msp Fiehn cid Agilent Fiehn Metabolomics Library Library file for scan analyses Library file for SIM analyses contains the 4 largest m z for each compound Internal standards file Retention index calibration file Retention index standards file Mass spectral transfer file Compound information file 1 14 Introduction The library locates the following GC MS data files used for the demonstration of the AMDIS program in the AMDIS32 DATA HP directory RI calibration d Contains all retention index standards also contains a small amount of benzoic acid L Histidine d Example data file containing derivatized L Histidine FAMES 2COL SPLITOl d Example data file containing FAME markers but using a nonstandard method
90. atch results area 1721 48 1718 38 3 1 Agilent Fiehn Metabolomics Library 175 6 176 AMDIS Getting Started Analysis Type Performance Check for RI The Performance Check for RI analysis type is used as a check to see how well the acquisition system is performing You do this by first acquiring a clean mixture of known composition containing one or more performance check compounds You then analyze the results using a Calibration amp Standards Library and an RI Calibration Data file both of which was explained in Analysis Type RI Calibration Performance on page 148 A Calibration amp Standards Library has a csl file extension and an RI Calibration Data file has a cal file extension The Calibration amp Standards Library is a list of compounds that can be used in the creation of a RI Calibration Data file as described in Analysis Type RI Calibration Performance on page 148 and or for performance checking purposes First of all the Performance Check for RI analysis type attempts to identify all compounds in the Calibration amp Standards Library using spectral comparisons only and then computes retention index values for the identified targets using the calibration data held in the RI Calibration Data file If you have elected to use RI information using the Analysis Settings dialog for each identified target is compared to its calibration computed RI value with the value held in the RI Calibration Da
91. atical process by which data containing a number of potentially correlated variables is transformed into a data set in relation to a smaller number of variables called principal components which account for the most variability in the data The result of the data transformation leads to the identification of the best explanation of the variance in the data e g identification of the meaningful information Also known as PCA Classification of biological processes Linear chain of amino acids whose amino acid order and three dimensional structure are essential to living organisms Also know as a polypeptide The study of the structure and function of proteins occurring in living organisms Proteins are assemblies of amino acids polypeptides based on information encoded in the genes of an organism and are the main components of the physiological metabolic pathways of the organism A feature attribute and or characteristic element whose presence absence or inability to be properly ascertained due to instrumental factors is factored into whether a sample is or is not representative of the larger specimen Agilent Fiehn Metabolomics Library Reference Information 8 Recursive Reapplying the same algorithm to a subset of a previous result in order to generate an improved result Recursive finding A three step process in the metabolomics workflow that improves the accuracy of finding statistically significant features in sample data fil
92. atisfy a fold change cut off oF 2 0 in a leas one candtion pair are displayed by defaut To apply the new Fold change cut off drag the Fold charge cut off sider or input the new cut off valus in the text box 2 Esperimert Grouping FE Displaying 90 out of 96 entities with fold change cie cf of 2 01n 4 ou c 2 condticn palis with A Sample as the control condo 4 Fiter By Frequency mpound FC qE Sample vs A Sampl FC qC Sample vs A Sampl 4015 70363 00 5 QCen samples 183 0 35 620235 365307840 00 5 Significance Analysis 1 00 1 05 1726763300 2365013 75 15 24118291200 119 2048 198562 768 00 130 241884144 00 1496921 36 1447 459 52 34 3918552 00 2 8 2 1 2550 42 22427 24 10 7822 028 00 1 3 44130396 00 2 00 46791 34 473 I gt 4 6 3 07 2 2 15 27 Bg 192 02 3272037 5 1 00 7581035 00 amp 173 za 1 00 a505677 00 E 18809 5 1 arso 2 27 178 10 311183 00 1 5379768 00 39 50 144542 68 1 00 516112250 1 96 E 37505 52 5 60 4582752 00 154 57 0659 38922 3340412 00 108 0648 582435 1 00 4776321 00 23 0649 388424 139 80 27312 08 121 0 53 015065 1 00 3562373 50 128 0 39 33477 1 00 3825820 00 TA sample IE Sample IC semple 81 0020 87574 6142 86 262 ss 69 0 58 81264 2303918 50 95 58 Tre 148 0053 6071397
93. bolic profiling can give a snapshot of the physiology of that organism Metabolic profiling by GC MS follows a workflow that is graphically represented in Figure 1 Experiment design and sample preparation are very important to the analysis but are outside the discussion of this workflow analysis Metabolic Profiling Workflow Prepare for an Experiment Import and Organize Data Create an Initial Analysis Find Features Advanced Operations Spectral Features Experiment Design amp Data Acquisition Statistical Data Analysis Experiment Design Hypothesis Natural Variability Replicate Sampling System Suitability Sampling Methodology Sample Preparation EIER Statistical Analyses Interpretations o gt Pathways Filtering Class Prediction Additional features Files Qualitative Analysis gt with DA Reprocessor MassHunter Mass Profiler GC MS Professional Chromatogram Deconvolution Figure 1 Metabolic profiling workflow for GC MS data Agilent Fiehn Metabolomics Library Identify Features as Compounds Identification MassHunter ID Browser 15 1 16 Introduction GC MS analysis The metabolite sample is first derivatized to allow volatile compound separation by the GC The derivatized metabolites are then analyzed by the MS Derivatization See Derivatization on page 22 for a detailed discussion of the chemical derivatization used to create the Agilent Fiehn Library Sample an
94. boratories doing metabolomics research using gas chromatography mass spectrometry GC MS The primary purpose of the library is to identify metabolites commonly found in metabolomic studies The library of electron impact EI spectra and retention data of pure chemical standards is built for the identification of compounds in biological matrices It is compiled mainly from a collection of commercially available metabolites that are comprised in a variety of biochemical databases The library intends to aid chemists and biologists in identifying as many metabolites as possible from GC MS metabolite profiling screens This library is for use as a primary entry tool to metabolite profiling by GC MS It is not meant to comprehensively cover any specific part of known metabolic pathways or any specific organism It does include key metabolites from a diverse set of biochemical pathways that are known to be conserved across organisms The metabolites included are structurally diverse and allow detection by GC MS Large and thermolabile metabolites such as acetyl CoA NADH or ATP are excluded The derivatization procedure for most primary metabolites in this library involves drying samples This drying process excludes volatile metabolites such as aroma compounds Agilent Fiehn Metabolomics Library Introduction 1 Library Content The Agilent Fiehn 2013 GC MS Metabolomics RTL Library includes files required by the Agilent GC MS ChemsStation
95. bsent from the replicate samples and does not provide any utility for statistical analysis Entities that are one hit wonders may be filtered using Filter by Flags Carbon based compounds often with biological origin A group of biochemical systems that function together as a whole thereby creating an individual living entity such as an animal plant or microorganism Individual living entities may be multicellular or unicellular See also specimen The probability of obtaining a statistical result that is comparable to or greater in magnitude than the result that was actually observed assuming that the null hypothesis is true The null hypothesis is stated that no Agilent Fiehn Metabolomics Library Reference Information 8 correlation exists between the independent variables and the measurements taken from the samples Rejection of the null hypothesis is typically made when the p value is less than 0 05 or 0 01 A p value of 0 05 or 0 01 may be restated as a 5 or 1 chance of rejecting the null hypothesis when it is true When the null hypothesis is rejected the result is said to be statistically significant meaning that a correlation exists between the independent variables and the measurements as specified in the hypothesis Parameter Another term for an independent variable Referred to as a parameter or parameter name and is assigned a parameter name during the various steps of the metabolomic data analysis See also condition an
96. c acid oxalacetic acid oxalacetate Chemical Formula C4H205 Molecular Weight 130 06 Daltons Monoisotopic Molecular Weight 132 0058732389 Daltons SMILES C C O 0 C 0 C O 0 InChi InChl 1S C4H405 c5 2 4 8 9 1 3 6 7 h1H2 H 6 7 H 8 9 p 2 Unification Links CAS 328 42 7 ChEBI 16452 KEGG C00036 PubChem 164550 Gibbs Energy of Formation kcal mol estimated 193 1 Forsythe97 Reactions known to consume the compound K C4 nhatar mthatir carhan accimilatian cucln MADD AMC hunn E m wmo B 2 Figure 126 Results in the MetaCyc website 3 Scroll down to display detailed information on the compound See Figure 127 on page 198 Agilent Fiehn Metabolomics Library 197 7 Using CAS and PubChem Numbers Activator Mechanism unknown of isocitrate dehydrogenase phosphatase Nimmo84 Enzymes inhibited by oxaloacetate sorted by the type of inhibition are Inhibitor Competitive of isocitrate dehydrogenase Comment 1 4 oxalocitramalate aldolase Hara03 acetylpyruvate hydrolase Davey75 4 oxalocitramalate aldolase Maruyama01 glutamate synthase NADH dependent Boland77 isocitrate dehydrogenase Kanao02 4 hydroxy 2 ketoglutarate aldolase Anderson85 succinate dehydrogenase Burke82 Inhibitor Noncompetitive of 4 carboxy 4 hydroxy 2 oxoadipate aldolase Tack72 glutamate dehydrogenase NAD dependent Bonete96 Comment 2 Inhibitor Allosteric of malate dehydrogenase Sanwal69 Sanwal6
97. calls attention to an operating procedure practice or the like that if not correctly per formed or adhered to could result in personal injury or death Do not proceed beyond a WARNING notice until the indicated condi tions are fully understood and met Agilent Fiehn Metabolomics Library In This Guide Agilent Fiehn Metabolomics Library This guide contains information on the use of the Agilent Fiehn GC MS Metabolomics RTL Library Introduction Describes the scope and intended use of the library the contents of the library including the file names and location on the user s hard drive and a discussion on the workflow of metabolic profiles is examined Sample Preparation and Derivatization Reviews the preparation of the analytical sample starting with a biological extract tagged with internal standards and markers processed to be compatible with GC analysis and ending with a vial of the sample ready for GC MS analysis Experimental and Instrument Method Lists the analytical method to follow when setting up your Agilent GC MS instrument system for successful use of the library Peak Identification Explores how peaks are identified in the library the compound naming convention that allows RT identification and how to run an analysis using the Agilent GC MS ChemStation and AMDIS Analyzing your Data Guides you through the use of Agilent GC MS ChemStation AMDIS Agilent MassHunter Qualitative A
98. case previous analysis results for a sample are always overwritten when a new analysis is performed and so this warning is completely normal as you reanalyze samples with different parameters Click Run to start the analysis Within a few seconds the results are displayed in the format you are now accustomed to 5 Learn a little more about the Information Lists area of the display You previously saw how to control the display of all hits or just the best hits Now you learn how to undock the Information Lists area so that you can conveniently view all of a hit s results information at once without the need to scroll First select the target at retention time 17 6567 minutes Now right click in the upper left hand quadrant of the Information Lists area to launch a 2 entry menu A ee gt 15 8551 oe pie aad 159959 NIST Liwary gt 160075 Undock SASN N EO PIRANA v Match en A Expec AT 1440 A Wich 23 scans 4 Hae be 12 Puriy 44 v v Figure 95 Controlling docking and undocking Click Undock The Information Lists area now becomes a window 160 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 C AMDIS32 DATA HP L HISTIDINE D DATA MS Figure 96 Information Lists area in Undock mode You can now use Windows techniques to drag and expand the window Experiment moving and stretching it Note especially that if you stretch the window at the top edge it increases the relative size of the upp
99. cation with Similar Conformers Chemical and Physical Properties Expand all sub sections Related Compounds Same Connectivity 5 Same Any Tautomers 8 Similar Compounds 25 Similar Conformers 1001 View Related Substances All 174 Same Structure 76 Mixture 98 Identification A R Im Figure 132 PubChem information on Oxaloacetic acid Agilent Fiehn Metabolomics Library 203 7 Using CAS and PubChem Numbers 4 In the Table of Contents click the Identification line and the page scrolls to the Identification section PubChem lists commercial availability of compounds under vendors in the column on the right It also shows chemical properties and out links to metabolic pathways and protein data Identification Depositor Supplied Synonyms oxalacetic acid oxaloacetic acid Ketosuccinic acid 2 Oxobutanedioic acid Oxosuccinic acid 2 Oxosuccinic acid 2 Ketosuccinic acid Oxobutanedioic acid oxaloacetate 328 42 7 see all 69 Compound Information CID 970 Create Date 2004 09 16 Descriptors IUPAC Name 2 oxobutanedioic acid InChi InChi 1S C4H405 c5 2 4 8 9 1 3 6 7 h1H2 H 6 7 H 8 9 InChiKey KHPXUQMNIQBQEV UHFFFAOYSA N Canonical SMILES C C O C 0 O C 0 O Related Records Related Compounds with Annotation a Same Structure 76 Mixture 98 Other Links Protein Structure 20 PubMed 1011 Gene 70 Taxonomy 1
100. cess employed by Agilent Mass Profiler Professional The identification of important or non important variables and the variable relationships in a data set using both analytical and a priori knowledge about the data This is part of the principal component analysis process employed by Agilent Mass Profiler Professional The process of establishing criteria by which entities are removed filtered from further analysis during the metabolomics workflow A flag is a term used to denote a quality of an entity within a sample A flag indicates if the entity was detected in each sample as follows Present means the entity was detected Absent means the entity was not detected and Marginal means the signal for the entity was saturated A classification of compounds based on their biological purpose or activity A proposition made to explain certain facts and tentatively accepted to provide a basis for further investigation A proposed explanation for observable phenomena may or may not be supported by the analytical data Statistical data analysis is performed to quantify the probability that the hypothesis is true Also known as the scientific hypothesis A statement based on involving or having the nature of a hypothesis for the purposes of serving as an example and not necessarily based on an actuality Agilent software that automatically annotates the entity list with the compound names and adds them to any of the various visualization an
101. compound report Click File gt Print gt Compound Report Click the All Results button if you want the report to include all compounds Mark the Print Preview check box and click OK 72 Agilent Fiehn Metabolomics Library Analyzing your Data 5 You can change the results that are included in this report in the method In the Method Explorer window select Reports and then select Analysis Report In the Method Editor window mark the results that you want to include in the report You can also customize the report template See the Report Designer training disk for more information Print Compound Report ff 9 Methoditems gt H eee Compounds 9 Show compound table Sort by Retention time x Sort order Increasing z Exclude details for unidentified compounds Chromatograms E Show user chromatogram s V Show compound chromatogram s E Overlay compound chromatogram s Compound spectrum MS a V Show MS spectrum Y Show MS peak table 7 Show predicted isotope match table Show MS spectrum zoomed in on special peaks Zoom padding 30 0 30 0 mz Overlay predicted isotope distribution Compound spectrum MS MS Show MS MS spectrum Show MS MS peak table Library search results F Show library spectrum A V Show difference spectrum A Figure 17 Report gt Compound Report section in the Method Editor window Export results to Mass Profiler Professional us
102. d pathway analysis tools Chromatographic components that have an assigned exact identity such as compound name and molecular formula based on prior assessment or comparison with a database See also Unidentified Compound An essential element constituent attribute or quality in a data set that is deliberately controlled in an experiment For example a pharmaceutical compound structure and quantity may be controlled as two independent variables while the metabolite profile presents a host of independent small molecule products that make up the dependent variables of a study An Agilent Fiehn Metabolomics Library Reference Information 8 independent variable may be referred to as a parameter and is assigned a parameter name during the various steps of the metabolomic data analysis Inorganic Non carbon and non biological origin compounds such as minerals and compound salts Interpretation Expression of your data in entity lists after grouping your samples applying filters and performing statistical correlation methods When you open an experiment the All Samples interpretation is active You can click on another interpretation to activate it Lipidomics Identification and quantification of cellular lipids from an organism in a specified biological situation The study of lipids is a subset of metabolomics Mass variation Using the mass to charge m z resolution to improve compound identification Compounds with nearly
103. d attribute Parameter value Another term for one of several values within a parameter for which exist correlating samples Parameter value may also be referred to as a condition during the various steps of the metabolomic data analysis See also attribute value Parent The original set of information that is processed by an algorithm to create one or more subsets of information A subset entity list is referred to as the child of a parent entity list Peptide Linear chain of amino acids that is shorter than a protein The length of a peptide is sufficiently short that it is easily made synthetically from the constituent amino acids Peptide bond The covalent bond formed by the reaction of a carboxyl group with an amine group between two molecules e g between amino acids Permutation Any of the total number of subsets that may be formed by the combination of individual parameters among the independent variables For example the number of permutations of A and B in variable in combination with X Y and Z in variable equals six 6 2 x 3 and may be represented as AX AY AZ BX BY and BZ Note that the combinations of parameters within a variable are not relevant such as AB XY XZ and YZ Polarity The condition of an effect as being positive or negative additive or subtractive with respect to some point of reference such as with respect to the concentration of a metabolite Polymer A molecule formed by the covalent bonding of
104. d on their parameter assignments 2 Click Back to make adjustments to prior steps in the workflow to improve the PCA results Agilent Fiehn Metabolomics Library 105 5 Analyzing your Data 3 Click Next 8 IDBrowser certifican C01 c sample c Legend 3DPCA Scores Hep lt lt Back Next gt gt Ensh Cancel Figure 49 QC on samples page of the Analysis Significance Testing and Fold Change Step 5 of 8 workflow Step 6 of 8 Significance Analysis 1 Review the summary plot The statistical analysis is either a T test or an Analysis of Variance ANOVA based on your samples and experiment grouping 2 Move the p value cut off slider or type a value to change the p value cut off value A larger p value passes a larger number of entities The last row of data in the Result Summary spreadsheet shows the number of entities that would be expected to meet the significance analysis by random chance based on the p value specified in each column heading If the number of entities Expected by chance is much smaller than those based on the Corrected p value your entities show significance among the parameter values 3 Click Next 106 Agilent Fiehn Metabolomics Library Analyzing your Data 5
105. d value that describes how much an entity changes from its initial to its final value For example when an entity changes from a value of 60 to a value of 15 the fold change is 4 The quantity experienced a four fold decrease Fold change is the ratio of the final value to the initial value Fold change analysis is used to identify entities with abundance ratios or for example differences between a treatment and a control that are in excess of specified cut off or threshold value Fold change is calculated between the conditions where Condition 1 and another condition Condition 2 are treated as a single group 2 Move the Fold change cut off slider or type a value to change the Fold change cut off The default value is 2 0 A larger cut off value passes a smaller number of entities through to the final results 3 Select a value for the Minimum number of pairs of conditions that must have entities with a fold change greater than the cut off The default value is 1 Agilent Fiehn Metabolomics Library 107 5 Analyzing your Data 4 Select the experiment grouping parameter value that is the Control Group for the fold change calculation Fold Change value per entity Conditionl entity abundance Condition 2 entity abundance where Condition 2 is the control group 5 Click Next An entity list is created in the Experiment Navigator for the entities that satisfy the cut off parameters Steps Fold Change Compounds thet s
106. dentif Now set Minimum match factor to 65 You are now ready to perform the analysis 4 Click Save to exit the Analysis Settings dialog and return to the Analyze GC MS Data dialog Click Run to start the analysis Within a few seconds the results are displayed in the usual format If you undock and expand the Information Lists area and set it to show only best hit data the target list appears as in Figure 110 on page 178 C8 Methyl Caprylate 7 812 C9 Methyl Pelargonate 9 248 C10 Methyl caprate 10 647 C12 Methyl Laurate 13 250 C14 Methyl Myristate 15 597 C16 Methyl Palmitate 17 723 C18 Methyl Stearate 19 663 C20 Methyl Eicosanoate 21 441 C22 Methyl Docosanoate 23 082 C24 Methyl Linocerate 24 603 C26 Methyl Hexacosanoate 26 023 C28 Methyl Octacosanoate 27 349 uncertain pks 0 0 reverse logic 1 0 few peaks 0 0 purity 1 0 high threshold 0 0 scaling 0 0 adjacent peaks 0 0 flagged peaks 0 0 m z 74 S N m z 74 248 8 Area m z 74 35 590 z RT AT lib 0 008 F Figure 110 Information Lists area after Performance Analysis 178 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 5 Examine the Calibration amp Standards Library that you used On the Library menu click Build One Library In the Build One Library editor that appears click Files and in the next dialog click Load Library Change Files of type to Calibr amp Stds Librar
107. e A term used to refer to statistical techniques named after the Reverend Thomas Bayes ca 1702 1761 Agilent Fiehn Metabolomics Library Reference Information 8 Bayesian The use of statistical reasoning instead of direct facts to calculate the inference probability that a hypothesis may be true Also known as Bayesian statistics Bioinformatics The use of computers statistics and informational techniques to increase the understanding of biological processes Biomarker An organic molecule whose presence and concentration in a biological sample indicates a normal or altered function of higher level biological activity Carbohydrate An organic molecule consisting entirely of carbon hydrogen and oxygen that is important to living organisms CEF file A binary file format called a compound exchange file CEF that is used to exchange data between Agilent software In the metabolomics workflow CEF files are used to share molecular features between MassHunter Qualitative Analysis and Mass Profiler Professional Cell The fundamental unit of an organism consisting of several sets of biochemical functions within an enclosing membrane Animals and plants are made of one or more cells that combine to form tissues and perform living functions Census Collection of a sample from every member of a population Cheminfor The use of computers and informational techniques such as analysis matics classification manipulation storage a
108. e AEB ANS jl Fehn Unidentified 11 SCIMS Uniertiied Fi SG Eperinante Experiment Setup A 1 Fiehn Unidentified EETA Experiment Grouping GesteIrtenprettim 20 Quaity contrat v In Unidentified Samples 5 Su Ineotetatins Be amp GAl Sampler AU Typ arraveraged A Class Prediction x a 3 1 Tre 8 RailteTaterpeetations amp E Flterad on Flags JaczCale P Mitar 5 Fitered by frequency condtions E pastivey nee u Oneway ANOVA 005 3 Fold change gt 2 0 t a ALP networks x Oi Wy Favorites H 2 Utilities 2 3 a0 20 A legal Ge Legend Profle plt Gos2Nermalieh obr ay A Lage TE 2 AOL Log2 A02 Log A 03 Log2 8 01 Log 8 02 Log B 03 Log2 C O1 Log C 02 log C03 Loa cere nel Laurchedoninterpretaton AI Sampe z 151 Diplyng 173 0 selected Taten M Figure 57_ Example view of MPP after creating a new project and experiment 112 Agilent Fiehn Metabolomics Library Analyzing your Data 5 Save your project Save your current analysis as a TAR file for archiving restoration of any future analysis to the current results sharing the data with a collaborator or sharing the data with Agilent customer support 1 Click Project gt Export Project 2 Mark the check box next to the experiments you wish to save 3 Click OK Select experiments to export with the project All the contents
109. e RT of the locking compound run on your GC MS system is exactly the same as its RT on the GC MS system used to analyze metabolites for creating the Fiehn L library 1 Prepare a clean RTL sample using the locking compound 2 Using the GC MS ChemStation load the supplied Agilent method Fiehn M 3 Run the RTL sample prepared in step 1 on your GC MS system 4 From the Data Analysis view select RTLock Setup from the View menu to enter the RTLock view 5 Select Relock Method from the RTLock menu Select Data File for ReLock 2 x Select Data File for ReLock ID Documents and Settings DD EnvDemo ID msdchem 1 G 5973N DO DATA O evaldemo d O FAMES 2COL SPLITO1 D L Histidine D RI calibration D x cocer G EEE 6 Select data file of the RTL sample run in step 3 38 Agilent Fiehn Metabolomics Library Experimental and Instrument Method 3 7 Click and drag using the right click to select the peak used for locking in this data file 8 Perform a cross correlation of the spectrum below 0 8 is not allowed 9 Calculate a suggested pressure based on the retention time of the peak in the selected file the pressure it was collected with and the curve stored in the method 10 Select a peak for locking from the list box 11 Use the input box displayed to confirm or change the retention time in the relock data file
110. e displayed 144 Agilent Fiehn Metabolomics Library SH AMDIS Chromatogram Component Mode L HISTIDINED File Analyze Mode View Library Options Window Help pl C AMDIS32 DATA HP L HISTIDINE D DATA MS Bun Rescate to I LA Abundanc TT TT Tr T 75 50 25 0 Time 19 targets 7 676 components 8 45 1132 14 19 17 07 19 94 22 82 25 69 2857 3144 34 32 37 19 Abundance 5 81 Figure 80 6 8682 7 0152 7965 cyclohexanamine 6 7 9441 2 971 oxalic acid 7 883 v Component Match Width 3 8 scans a eee 6 39 Purity 12 Model 170 m z Scan 70 6 418 min and Extracted spectrum 6 417 min 100 125 150 175 200 225 250 275 300 325 350 Library Hit 7768 epsilon caprolactam 6 388 and Extracted spectrum 125 150 175 200 225 250 275 300 325 350 Use Retention Time analysis results 8 To more easily examine the AMDIS results on the Mode menu click Target Only Now only targets are displayed You can switch back to viewing both by clicking Mode gt Component While viewing targets right click anywhere in the upper right hand quadrant of the Information Lists area and view a 2 entry menu 6 AMDIS Getting Started 2 6 10 Dodecatrien 1 ol 3 7 2 6 10 Dodecatien 1 ol Teti Best Hits Only x gt v AlHts iv Component Match idth 28 scans A Expec AT 1040 a Purty 33 Net 96 Model TIC wv Weighted 3 v Figure 81 Controlling the displayed hits Click B
111. e method differences do not change the compound elution order a new conversion table can be created to assign the correct retention times Agilent Fiehn Metabolomics Library 39 3 40 Experimental and Instrument Method An AMDIS analysis type of RI Calibration Performance is used to create a conversion table of RT to RI values for each of the 12 FAME compounds This conversion table is stored in the RI calibration file cal The Fiehn cal file supplied with this application stores these values for the specific GC MS system used to acquire the data to create the Fiehn libraries msl See Update the AMDIS cal file on page 40 for instructions to create this conversion table file Update the AMDIS cal file This AMDIS analysis procedure integrates the calibration data file d acquired by the GC MS ChemStation and matches the found peaks with the FAME compounds in the provided Calibration Standards Library csl It then takes the RTs of these found FAME markers and matches them to the RI stored in the provided Calibration Standards Library This pairing of RIs with RTs is stored in the RI Calibration file cal overwriting the file s previous matchings 1 Prepare a clean calibration sample containing the 12 FAME markers and the locking compound 2 Using an RTL method run this sample on the GC MS system 3 Copy the resulting FAME calibration data file to the AMDIS32 DATA HP directory 4 Start AMDIS and select Open fr
112. e up 643601 meth peimteleste 17 466 100 0 00 1 00 dow 557376500 2 41 16 00 ur 122 085 1 03485 33 60 z531 16 00 own 1445 42 53 17 14 10 00 up 107 0853 945736 1 00 0 00 100 dow 516112250 22 20 16 00 up 88 0 22 730045 196 637 196 un 54 245 5 48 un 926 nicotnamice 1 11 656 837805 69 39 58 16 00 down 5 50 EEE 5 50 up 643891 methA palrritoleate 17 466 _ 4582752 00 22 13 16 00 down z134 0 63 154 down 265 19 terratracortane 29 185 3340412 00 2187 16 00 down 1 44 053 144 up 108 0048 583435 1 00 0 00 1 00 down 477633100 22 19 16 00 un 5280270 squalene 25 251 43 388 BECK EAE 76 00 dam 27212 aR 1474 16 00 up 7472 N N dimethyi 1 4 phenyieneci 1 00 6 00 1 00 down 456237350 22 12 16 00 up 93 1 naphthalene 18 87 1 00 6 00 1 00 dom _3585820 00 2189 16 00 up 81 0 20 87674 5143 86 1258 16 00 down 263 55 8 4 16 00 up 5280370 squalene 25 251158 81264 2303018 50 2114 16 00 dan 95 58 558 16 00 dom 74721 N N dimeihy 1 4 ohenyanzci 1 00 6 00 1 00 dovn 2872969 25 21 25 16 00 ur 12108469193 1 00 0 00 1 00 down _3630982 50 21 50 16 00 up 163 0 40 933502 1 00 0 00 1 00 dom _ 2928251 25 21 48 16 00 up Help lt lt back not gt gt ssh _ cancer Figure 56 ID Browser page of the Analysis Significance Testing and Fold Change Step 8 of 8 workflow after identification SAF Boet Search view Tools Annatations Windows Hela BB a aa Fees B
113. e 41 Steps performed by the Analysis Significance Testing and Fold Change Wizard Step 1 of 8 Summary Report 1 Review the Summary Report The Summary Report is displayed as a spreadsheet view when you have more than 30 samples 2 Click and right click features on the plot or spreadsheet to review the data change the plot view export selected data or export the plot to a file 3 Click Next Agilent Fiehn Metabolomics Library Analyzing your Data 5 1002 Normalized Abundance Values AOL Log A02 Log2 A03 Log 801 Log2 8 02 Log2 8 03 1092 CO1 1092 C 02 1092 C_08 Logz Figure 42 Summary Report page of the Analysis Significance Testing and Fold Change Step 1 of 8 workflow Step 2 of 8 Experiment Grouping 1 Review your Experiment Grouping 2 Click Add Parameter to define or adjust your experiment grouping Follow the steps in Step 6 of 11 Experiment Grouping on page 89 Note In order to proceed to the next step at least one parameter with two parameter values must be assigned 4 Click Next when you have completed your experiment grouping Agilent Fiehn Metabolomics Library 101 5 102 Analyzing your Data Experi ir Ex im Si Fold change analysis wil be skipped i mor Displaying 9 samples wth 1 experiment paraneter s To change tse the button controis below SDHC BEE Samples Type 2 1
114. e Retention time E GU9 RI CALIBRATION csv Microsoft Excel Tetee 5 Home Insert Page Layout Formulas Data Review View Add Ins a o er u lA Aw FE General UE Conditional Formatting geinetr E Av a a E N 7 33 Format as Table FA Delete m Paste r v x __ Sot amp Find amp F BZU He amp A Dr 5 Cell Styles EiFormat 2r Siehe Select Clipboard m Font G Alignment z Number z Styles Cells Editing A16 bd f B D E F G H J 1 757 glycolic acid 79 14 1 748 27 7 049 2 C8 Methyl Caprylate 111 11 5 800 7 812 3 C10 Methyl Caprate 110 42 9 1000 10 647 4 C12 Methyl Laurate 111 82 0 1200 13 25 5 C14 Methyl Myristate 124 10 7 1400 15 597 6 RTL Myristic Acid d27 60658 41 5 1503 16 727 7 C16 Methyl Palmitate 112 39 0 1600 17 723 8 C18 Methyl Stearate 112 61 8 1800 19 663 9 C20 Methyl Eicosanoate 1120 28 1 2000 21 441 10 C22 Methyl Docosanoate 929 77 1 2200 23 082 11 8343 dioctyl phthalate 117 81 7 2207 29 23 163 12 C24 Methyl Linocerate 2442 49 1 2400 24 603 13 C26 Methyl Hexacosanoate 5802 82 4 2600 26 023 14 C28 Methyl Octacosanoate 55682 92 3 2800 27 349 15 C30 Triacontanoate 629 83 4 3000 28 723 17 M 4 H RI CALIBRATION 5 141 M FE Ready Fixed Decimal Bean 100 ry L Figure 13 Example RT Calibration File Agilent Fiehn Metabolomics Library 69 5 70 Analyzing your Data Searc
115. e each entity to median mean across samples or control samples These options will treat all compounds equally regardless of their intensity Options None z transform Baseline to median z of all samples Baseline to fean z of control samples tne 111 OE Control Samples Help lt lt Back Next gt Einish Cancel Figure 40 Baselining Options page Step 11 of 11 of the MS Experiment Creation Wizard If you chose Data Import Wizard for Workflow type in the New Experiment dialog box you are done creating your experiment and can use the operations available in the Workflow Browser If you chose Analysis Significance Testing and Fold Change for Workflow type in the New Experiment dialog box you are immediately directed to Perform your initial analysis on page 99 98 Agilent Fiehn Metabolomics Library Analyzing your Data 5 Perform your initial analysis The Analysis Significance Testing and Fold Change Wizard guides you through the eight 8 steps to enter parameters and values that improve the quality of your results and produce an initial differential expression for your analysis The steps performed during the Significance Testing and Fold Change Wizard are illustrated in Figure 41 Step 1 Summary Report Displays a summary view of your experiment based on the parameters you provided in the Import Data wizard A profile plot with the samples on the x axi
116. e of nonredundant experimentally elucidated metabolic pathways MetaCyc contains more than 1928 pathways from more than 2263 different organisms more and is curated from the scientific experimental literature more MetaCyc contains pathways involved in both primary pss and secondary der Metabolism as well as associated compounds enzymes and genes more Motivations The goal of MetaCyc is to catalog the universe of metabolism by storing a representative sample of each experimentally elucidated pathway metacyc mission MetaCyc is used in a variety of scientific applications such as providing a reference data set for computationally predicting the metabolic pathways of organisms from their sequenced genomes supporting metabolic engineering helping to compare biochemical networks and serving as an encyclopedia of metabolism scientific applications Recent Publication e The MetaCyc Database of metabolic pathways and enzymes and the BioCyc collection of pathway genome databases Nucleic Acids Research 40 D742 D753 2012 Agilent Fiehn Metabolomics Library Using CAS and PubChem Numbers 7 EN M LOGIN Why Login Create New Account ne ETACYC Quick Search Gene Search A member of the BloCyc database collection ri Fi Searching MetaCyc change organism database Home Search Tools Help Compound A Add to group MetaCyc Compound oxaloacetate Synonyms oxaloacetate keto oxaloacetate oxaloaceti
117. earch Figure 8 on page 55 PubChem identifiers refer to the publicly available and free library of chemical compounds hosted and curated by the U S National Center of Biotechnology Information NCBI www ncbi nlm nih gov pccompound from which links to other NCBI databases can be found such as PubMed scientific literature NCBI s protein 3D database and outlinks to biochemical databases such as the KEGG ligand database PubChem identifiers are linked and could be used in other repositories as well so that users of the Agilent Fiehn Library are enabled to query Internet resources using either the CAS numbers or the PubChem entries An example of use of the PubChem identifier is given in Chapter 7 Using CAS and PubChem Numbers Agilent Fiehn Metabolomics Library 49 4 Peak Identification Metabolite Derivatizations Resulting in Multiple Compounds Often GC MS peak is obtained for a single unique chemical compound As much as possible the spectra included in the Fiehn library refer to actual chemical derivatives of a unique metabolite and not to an unwanted impurity in the commercial standard Because molecular ions are frequently absent in electron impact spectra the correct chemical derivatization status can not always be positively established This method would have been the optimal way to verify that the GC MS spectra were correctly annotated to metabolite names The Fiehn library was manually curated Each individual spectrum
118. en compartments and organs The presence of these functional groups in extracts of biological samples causes a significant rise in boiling points rendering most primary metabolites unsuitable for GC separations Derivatization The hydrophilic functional groups must be derivatized to remove hydrogen bond formations to increase volatility This also reduces interaction with the column phase that can cause tailing peaks poor sensitivity and poor chromatographic separation The Agilent Fiehn 2013 GC MS Metabolomics RTL Library uses a two step derivatization procedure routinely used in most published literature in metabolite profiling by GC MS Trimethylsilylation Trimethylsilylation is used to exchange acidic protons under mild universal and sensitive conditions These protons are present in carboxyl hydroxyl amino imino or sulfuryl groups In rare cases like malonic acid with two carboxyl groups at 1 3 positions hydrogen atoms at the Agilent Fiehn Metabolomics Library Sample Preparation and Derivatization 2 alpha carbon are acidic enough to undergo trimethylsilylation Trimethylsilylation dramatically reduces boiling points improves thermal stability and enhances chromatographic separation of metabolites Trimethylsilyl derivatives also have some disadvantages such as a dominant neutral loss of hydroxytrimethylsilyl under 70 eV electron impact conditions which often leads to very low intensities of the molecular ions In add
119. enough The Use Retention Index Data analysis type first identifies target compounds using spectral comparisons only exactly as in the Simple analysis type Next it uses the actual retention times of the identified targets to compute their retention index values by linear interpolation techniques using the calibration data held in the RI Calibration Data file Only then does it determine what to do with these retention indices If you have elected to use RI information see below for each identified target the software compares its calibration computed RI value with the value held in the Target Compounds Library and adjusts the target s match value according to how good the fit is If you are not using RI information the target match value is not adjusted and the RI information is simply used in reporting the deviation between computed and library RI values It is a prerequisite of this analysis type that a Target Compounds Library and an RI Calibration Data file exist Further the calibration information can only be of any use for compounds in the library that have RI values stored for them Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Before following the instructions below ensure that AMDIS is in a known state by following the instructions in Figure To put AMDIS into an initialized state on page 116 There should now be an empty Confirm window displayed 1 Click File gt Open and in the Select Data Fi
120. er quadrants whereas if you stretch it at the bottom edge it increases the relative size of the lower quadrants If you right click in the lower left quadrant the Component list of information you can view the lower level parameters Within this dialog you can determine which parameters to be displayed and the order in which to display the parameters Agilent Fiehn Metabolomics Library 161 162 AMDIS Getting Started Yiew Options x Width Purit n Model A Component Min Abund 2 in Match Amount Scan Peak Taiing ji al Apply S N total f Base Peak Max Amount zl RI Retention index from observed retention time and prior AI calibration results Figure 97 The Information Lists area is fully explained in the online Help but for now we shall just highlight a few values relating to RI In the Match area L Histidine has an RI RI lib value of 1 4 indicating how close the RI match is This value is the difference in RI between the value computed for this component from the RI Calibration Data file cal and the value held in the Target Compounds Library ms The calculated value is shown in the Component area and is 1593 1 in this case with 1591 7 being the library value If the RI RI lib label and value are absent the library entry does not have an RI value specified The Net value 96 in this case is an overall indicator of the matching process and takes all Corrections into account Fi
121. er and click OK d Clear the In place Translation check box e Click Start Translation Import MSD ChemStation Data Files 3 ee Folder containing Data Fies to Import C Program Files amp 86 Agilent Fiehn Metabolomics RTL Database G1676AA Data Browse Inplace Translation Output Folder C MassHunter Data Browse Successful Data File Name Comment C PROGRAM FILES X86 AGILENT FIEHN METABOLOMICS RTL DATABASE G1676AA DATA FAMES OK ww C PROGRAM FILES X86 AGILENT FIEHN METABOLOMICS RTL DATABASE G1676AA DATA LHIST OK Ea C PROGRAM FILES X86 AGILENT FIEHN METABOLOMICS RTL DATABASE G1676AA DATA RI CAL OK m r MassHunter GC MS Translator B 06 00 1116 10 Apr 2012 Translation session complete Figure 10 Import MSD ChemStation Data Files f Verify that all of the data files were translated If the check box in the Successful column is marked then the translation was successful Search Unit Mass Library on spectra You can use the Search Unit Mass Library algorithm on either a compound or a spectrum in the Agilent MassHunter Qualitative Analysis program This example shows searching a spectrum See Search Unit Mass Library with Retention Time Matching on compounds on page 68 for an example showing how to search a compound Agilent Fiehn Metabolomics Library Analyzing your Data 5 The Agilent Fiehn Library compound naming convention includes a bracketed RT retention time value
122. ernal standards are used only as a functional check of the acquisition system and are not used in predicting target RI values since this is done using the RI Calibration Data file A Target Compounds Library has a msl file extension an RI Calibration Data file has a cal file extension and an Internal Standards Library has a is file extension As in the Use Internal Standards for RI analysis type internal standards are co injected with the sample The Use RI Calibr Data Internal Std analysis type first identifies target and internal standard compounds using spectral comparisons only and then computes retention index values for the identified targets using the calibration data held in the RI Calibration Data file If you have elected to use RI information using the Analysis Settings dialog for each identified target the calibration computed RI value is compared with the value held in the Target Compounds Library and adjusted to the target s match value according to how good the fit is If you are not using RI information the target match value is not adjusted and the RI information is simply used in reporting the deviation between computed and library RI values The deviation between the expected and observed retention times of each internal standard is given in the QA QC report see below for details It is a prerequisite of this analysis type that a Target Compounds Library an RI Calibration Data file and an Internal Standa
123. es Step 1 Find untargeted compounds by molecular feature in MassHunter Qualitative Analysis Step 2 Filter the molecular features in Mass Profiler Professional Step 3 Find targeted compounds by formula in MassHunter Qualitative Analysis Importing the most significant features identified using Mass Profiler Professional back into MassHunter Qualitative Analysis as targeted features improves the accuracy in finding these features from the original sample data files Reduction The process whereby the number of variables in a data set is decreased to improve computation time and information quality For example an extracted ion chromatogram obtained from GC MS and LC MS data files Reduction provides smaller viewable and interpretable data sets by employing feature selection and feature extraction Also know as dimension reduction and data reduction This is part of the principal component analysis process employed by Agilent Mass Profiler Professional Regression Mathematical techniques for analyzing data to identify the relationship analysis between dependent and independent variables present in the data Information is gained from the estimation regression or the sign and proportionality of the effects of the independent variables on the dependent variables This is part of the principal component analysis process employed by Agilent Mass Profiler Professional Also known as regression Replicate Collecting multiple identical samples from
124. es of analysis covered in the tutorials is listed in Table 5 along with the demo data files required to run the analysis yourself Use Retention Time Table5 AMDIS Analysis Type AMDIS analysis type Fiehn use description Required AMDIS files Simple This analysis mode is used to process data files that have Fiehn msl not been acquired using the Fiehn m RTL method or data files acquired without any RI calibration Results from this analysis mode are harder to interpret because there are more false positives that need to be evaluated This mode can be used to locate compounds in the data file that are spectrally and structurally similar to compounds in the library This analysis mode is similar to the Simple analysis mode Fiehn msl but it penalizes potential target hits ifthe target retention time differs from the retention time in the library RI Calibration Performance This analysis mode should be used to periodically update Fiehn msl the RTs of the RI standards The Agilent Fiehn Metabolomics Library is calibrated with fatty acid methyl Fiehn cls esters FAMEs between C8 and C28 New cal created Use Retention Index Data This analysis mode is the preferred mode for analyzing Fiehn msl unknown samples that are acquired with Fiehn m It is important to use Fiehn m as an RTL method where d27 Fiehn cal myristic acid elutes at 16 72 minutes 130 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Table5 AMDIS A
125. est Hits Only to display only the single best hit for each target Now click the target symbols above the TIC chromatogram display or click retention times in the Information Lists area to see just the best hit name of each target displayed with the currently selected one highlighted Further the displayed Component and Match information relates to the selected target 9 To examine the details of the deconvolution and library matching select the UNDOCK menu item of the View menu Once the Information list is detached from the AMDIS window the size of the window can be enlarged to show the detailed match parameters In particular select the component at retention time 9 4429 2 amino l phenylethanol 146 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 C AMDIS32 DATA HP L HISTIDINE D DATAMs 1000 2 amino 1 phenylethanoPy 243 benzoic acid 9 594 13017 N cyclohexylformamide 3 753 glycerol 9 941 66868 porphine 1 10 77 534 L cysteine 1 12 544 pan uncertain pks 0 8 reverse logic 0 8 few peaks 0 0 purity 0 9 high threshold 0 0 scaling 0 0 adjacent peaks 0 0 flagged peaks 0 1 m z 174 S N m z 174 64 5 Area m z 174 34 3 RT AT lib 6 225 E Figure 82 RETENTION correction to Net value For most targets the retention time correction to the Net match factor is 0 0 RETENTION is 0 0 However 2 amino 1 phenylethanol has a value of 20
126. files from your structures from hundreds of concur data sources Watch our introduction video Generate Leads M gt Figure 128 CAS Search in ChemSpider 4 Click the Search button below this field to display compounds found in the search See Figure 129 on page 200 Agilent Fiehn Metabolomics Library 199 7 Using CAS and PubChem Numbers RSC Syntheti l ChemSpider RSC The free chemical database About More Searches Web APIs Help Search term 328 42 7 Found by approved synonym Oxaloacetic acid o ChemSpider ID 945 Molecular Formula C4H405 H Average mass 132 072006 Da Monoisotopic mass 132 005997 Da v Systematic name 2 Oxosuccinic acid gt SMILES and InChis 2D 3D Save Zoom TEE gt Cite this record gt Names and Identifiers gt ChemSpider Searches v Properties Experimental data Predicted ACD Labs Predicted EPlSuite Predicted ChemAxon ea lt gt Figure 129 ChemSpider finds Oxaloacetic acid 5 Click Properties or one of the other heading to see additional information See Figure 130 on page 201 200 Agilent Fiehn Metabolomics Library Using CAS and PubChem Numbers 7 tad Oxaloacetic acid E o ChemSpider ID 945 Molecular Formula C4H405 H H Average mass 132 072006 Da Monoisotopic mass 132 005997 Da v Systematic name 2 Oxosuccinic acid gt SMILES and InChis 2D 3D Save Zoom KERN gt Cite this record gt Names and Identifiers gt
127. fit is Otherwise the target match value is not adjusted and the RI information is simply used in reporting the deviation between computed and library RI values At the completion of every analysis a QA QC report is created that provides information about all of the internal standards that have been found as well as those that were not found It is a prerequisite of this analysis type that a Target Compounds Library and an Internal Standards Library exist Further the internal standards information can only be of any use for compounds in the library that have RI values stored for them Before following the instructions below ensure that AMDIS is in a known state by following the instructions in To put AMDIS into an initialized state on page 116 There should now be an empty Confirm window displayed Agilent Fiehn Metabolomics Library 163 6 AMDIS Getting Started 1 Click File gt Open and in the Select Data File dialog navigate to the AMDIS32 DATA HP folder select the file Rl Calibration d and click Open 2 Click Analyze gt Analyze GC MS Data and in the Analyze GC MS Data dialog set Type of analysis to Use Internal Standards for RI Use Target Library and Intern Std Lib to select the Fiehn msl and Fiehn isl files respectively The dialog should now resemble x Type of analysis Use intemal Standards forRl Intern Std Lib Al Calib Data age Previous analysis results will be replaced Cancel
128. g filtering alignment normalization and baselining Step 1 Select Data Source Select the data source that generated the molecular features you are using for your experiment Step 2 Select Data to Import Select the molecular feature sample files Step 3 and Step 4 are skipped by the MS Experiment Creation Wizard for GC MS data Step 5 Sample Reordering Organize your samples by selecting individual samples and reordering the selection to group the samples based on the independent variables Step 6 Experiment Grouping Define the sample grouping with respect to your independent variables including the replicate structure of your experiment Step 7 Filtering Filter the molecular features by abundance mass range number of ions per feature and charge state Step 8 Alignment Align the features across the samples based on tolerances established by retention time and mass This step is omitted when the experiment type is identified because identified compounds are treated as aligned by identification Step 9 Sample Summary Display a mass versus retention time plot spreadsheet and compound frequency for the distribution of aligned and unaligned entities in the samples Compound Frequency charts provide a quick view into the effectiveness of the alignment of unidentified experiment types The back and next buttons in the wizard let you easily review the effects of different alignment and filter options Step 10 Nor
129. g approaches The NIST software package AMDIS is used for forward peak finding For reverse peak finding you can choose between two algorithms in the Agilent ChemStation software Quant and Screener Metabolite identification Using the Agilent Fiehn Library metabolite identification is accomplished by EI spectral library matching in combination with either retention time or retention index matching EI spectral matching alone is not sufficient for a confident identification in the presence of many biologically important isomers The use of chromatographic retention as an additional identifying parameter results in much higher confidence for EI spectral matching It does not resolve all identification issues such as compound chirality Like most analytical methods the chromatography was developed with a compromise between complete separation and analysis time Statistical analysis Metabolomics studies are comparative studies of biological organisms The comparison can be simple such as the metabolic difference between a cell culture under normal and stressed conditions or a very complex study of metabolic differences of a human population with many variables such as diet age sex race etc In both cases the Agilent Fiehn Library and methodology can be used to investigate metabolic differences Data processed by AMDIS using the Agilent Fiehn Library results in two output files that can be used for statistical analysis elute data file e
130. get or component is signified by its symbol being red The rest of the Confirm window s data relate to this compound You can click any of the symbols to make it the current selection For full details of the Chromatogram Display area see AMDIS online Help Profile Display The Profile Display area generally shows the TIC chromatogram and major characteristic ion s of the deconvoluted compound over the retention time window in which is was determined The y axis is a relative abundance percentage scale with the absolute abundance value representing 100 given at the top left of the display for example 2068 in Figure 66 For full details of the Profile Display area see AMDIS online Help Information Lists The Information Lists area changes somewhat according to whether the currently selected compound is being displayed as a component V or as a target T For a component there are two side by side sections For a target there are four sections arranged more or less as quadrants For full details of the Information Lists area see AMDIS online Help Target The upper left quadrant is a list of retention times for all targets The upper right quadrant is a list of hits identifications from a target library The lower two quadrants provide various details about the target as determined during the deconvolution process Component The left hand section is a list of retention times for all components Agilent Fiehn Metabolomic
131. h Of particular significance is whether or not you are using retention indices and if you are whether you are using internal standard compounds within a sample for their computation or whether you are using an external calibration file holding retention index values Table4 Analysis type Analysis type Description Simple Only mass spectra are used in determining target matches so no use is made of retention time or retention indices Use Retention Time Following a target match determined by mass spectral comparison the compound s retention time is compared against the library value to confirm the match RI Calibration Performance A clean mixture of known composition is acquired and the data used to create an RI Calibration Data file for use by other appropriate analysis types Use Retention Index Data Following a target match determined by mass spectral comparison the compound s RI is computed using an external RI Calibration Data file so that the quality of the match can be further assessed Use Internal Standards for RI Known compounds the internal standards are co injected with the sample Mass spectral matching determines which targets and internal standards are present The retention times of the found internal standards are used to compute retention indices for the targets so that the quality of their match can be further assessed 128 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Table4 Analysi
132. h Libra Library Search Search Results Library selection C MassHunter Library Fiehn L love Down Add Library Remove Library Settings A Scoring Match factor V Use RT match A RT penalty function Trapezoidal RT range L 6 Penalty free RT Range 0 Gaussian Standard deviation 6 RT mismatch penalty type Multiplicative amp Additive Max RT penalty 20 00 RT Calibration file C MassHunter Library RI CALIBRATION csv A Figure 14 Library Search gt Scoring tab in the Method Editor window 12 Click Identify gt Search Library for Compounds 13 Close the Method Editor window In the Data Navigator window highlight Compound 16 Agilent Fiehn Metabolomics Library Analyzing your Data 5 Cpd 11 10 448 Cpd 12 C10 Methyl Caprate 10 647 7 Cpd 13 10 733 Cpd 14 11 325 Ya RT Ya CAS V4 RT DB VY Score Y Formula Y St Cpd 27 C28 Methyl Octacosanoate 27 349 Cpd 28 C30 Methyl Triacontanoate 28 723 Cpd 29 29 357 v 9 9 a Dir Best V ID Source Y Name Y Formula Y Score Y R
133. he molecule The trimethylsilylation step yields two products The first product replaces the protons at both carboxyl groups The second product replaces the two carboxylic group and the less acidic secondary amine Figure 5 Agilent Fiehn Metabolomics Library 27 2 28 Sample Preparation and Derivatization N acetylasparte 2TMS is the more abundant peak whereas the completely derivatized molecule N acetylaspartate 3TMS is detected as a minor peak Figure 6 on page 29 H C 40 gt Figure 5 Molecular structure of N acetyl aspartic acid 1 Indicates the modification of N acetyl aspartic acid at the two carboxyl groups which always occurs instantly and completely 2 Secondary amines are less reactive so that two peaks are detected in GC MS one for the completely derivatized tri TMS molecule and another one for the incompletely derivatized di TMS compound at the two carboxyl groups without replacing the proton at the amine group Agilent Fiehn Metabolomics Library Abundance 9000000 8000000 7000000 6000000 5000000 4000000 3000000 2000000 1000000 14 828 14 955 Sample Preparation and Derivatization 2 TIC 1008a07 004 D data ms 16 724 15 618 L Time gt a u T T 14 00 14 50 15 00 15 50 16 00 16 50 17 00 Figure 6 Total ion chromatogram of derivatized N acetyl aspartic acid The 2x trimethylsilylated molecule forms the major peak at 14 828 min and the 3x
134. ibrary The match with the highest Score is automatically chosen as the Best match In this example C12 Methyl Laureate 13 250 has a Score of 96 04 and is selected as the Best match You can select a different Best match by clicking on the row The number in brackets at the end of the name is the retention time of the entry The RT DB column shows the retention index for this match The retention index does not have a direct correlation with the retention time Instead the retention index is used to look up the retention time in the RT Calibration file The RT Calibration file is used in the Search Unit Mass Library with Retention Time Matching on compounds on page 68 10 optional Print a report Click File gt Print gt Analysis Report Mark the Print Preview check box and click OK Agilent Fiehn Metabolomics Library 67 5 68 Analyzing your Data You can change the results that are included in this report in the method In the Method Explorer window select Reports and then select Analysis Report In the Method Editor window mark the results that you want to include in the report 11 optional Close the data file Click File gt Close Data File Do not save the results Click No in the Do you want to save the results message box Search Unit Mass Library with Retention Time Matching on compounds You can use the Search Unit Mass Library algorithm on either a compound or a spectrum in the Agilent MassHunter
135. ibrary 57 5 58 Analyzing your Data The Screen Report uses an X and in the status column to indicate probable and possible identification respectively The indicates that one or more qualifiers fail Expected RT and delta RT are reported along with the target ion Qualifier ions that are out of range are noted in the Qualifiers Out of Range columns The last column reports the cross correlation with the reference spectrum For probable matches with out of range qualifiers marked use AMDIS to clean up and deconvolute spectra to help identify the compound Search basics When using the Agilent Fiehn Library for metabolite identifications a three tiered identification approach is recommended The PBM Quick Search and Library Search Report use mass spectral similarity but do not support use of retention times as a constraint The correct hit may not be found at the top of the list This it is recommended to review the list and select the correct metabolite using retention time mass spectral similarity and characteristic ions a Use small RT differences between the sample peak RT and the library RT for example allow deviations of lt 0 2 min b Use very high mass spectral similarity thresholds for abundant peaks that are not compromised by coeluting peaks for example forward similarity matches gt 850 but allow lower mass spectral similarity thresholds for low abundant peaks especially when
136. identical and identical chromatographic behavior are deconvoluted by adjusting the m z range for extracting ion chromatograms Mean The numerical result of dividing the sum of the data values by the number of individual data observations Metabolism The chemical reactions and physical processes whereby living organisms convert ingested compounds into other compounds structures energy and waste Metabolite Small organic molecules that are intermediate compounds and products produced as part of metabolism Metabolites are important modulators substrates byproducts and building blocks of many different biological processes In order to distinguish metabolites from lager biological molecules known as macromolecules such as proteins DNA and others metabolites are typically under 1000 Da A metabolite may be individually referred to as a compound molecular feature element or entity during the various steps of the metabolomic data analysis Metabolome The complete set of small molecule metabolites that may be found within a biological sample Small molecules are typically in the range of 50 to 600 Da Agilent Fiehn Metabolomics Library 213 8 Reference Information Metabolomics Metabonomics NLP Normalization Null hypothesis Observation One hit wonder 214 Organic compound Organism p value The process of identification and quantification of all metabolites of an organism in a specified biological situati
137. ified to use both AMDIS data file types If your data has been process using Qualitative Analysis e Select Identified when the compounds have been identified by compound formula and or CAS number e Select Unidentified when the compounds have only been identified by Find by Chromatogram Deconvolution resulting in mass and retention time e Select Combined Identified Unidentified when you are unsure if the data has been identified in full or in part or when MassHunter Qualitative Analysis has been previously used to identify some of the compounds A summary table of data sources and file types based on the selection for Experiment type is shown in Table 3 on page 83 4 Select Analysis Significance Testing and Fold Change for Workflow type Regardless of your personal expertise it is recommended to select the Analysis Significance Testing and Fold Change for the Workflow type to provide you with quality control for your analysis that improves your results 5 Type information about your experiment in Notes 6 Click OK Agilent Fiehn Metabolomics Library 81 5 82 Analyzing your Data Experiment description Enter a name analysis type experiment type and a desired workflow type Analysis will guide you through a statistical significance test and fold change analysis Data Import will guide you through experiment creation only Class Prediction will guide you through the creation and testing of a prediction m
138. ing CEF file After you have created compounds and searched those compounds with the Search Unit Mass Library algorithm you can export those results to a compound exchange format CEF file The Agilent Mass Profiler Professional program can use this CEF file in experiments in a project 1 Create compounds See Search Unit Mass Library with Retention Time Matching on compounds on page 68 2 Click File gt Export gt as CEF The Export CEF Options dialog box opens Agilent Fiehn Metabolomics Library 73 5 Analyzing your Data 3 Click All results 4 Review the other parameters and click OK r List of opened data files RI CALIBRATION D Export contents Only highlighted results All results Export destination One export file per data file At the location of the data file gt At specified directory C MassHunter Data If export file already exists Overwrite existing export file Auto generate new export file name Figure 18 Export CEF Options dialog box Agilent Fiehn Metabolomics Library Analyzing your Data 5 Using Agilent MassHunter Mass Profiler Professional Agilent MassHunter Mass Profiler Professional MPP software is a powerful chemometrics platform designed to exploit the high information content of mass spectra MS data and can be used in any MS based differential analysis to determine relationships among two or more sample groups and variables MPP provides adva
139. ing Workflow 15 GC MS analysis 16 Peak identification 16 Metabolite identification 17 Statistical analysis 17 Systems biology analysis 18 2 Sample Preparation and Derivatization 21 Biological sample extracts 22 Metabolites 22 Derivatization 22 3 Experimental and Instrument Method 31 Experimental 32 Acquisition Method 35 GC MS Setup 38 Quality Control 42 4 Peak Identification 45 Peak Identifications from Metabolite Profiles 46 Agilent Fiehn Metabolomics Library 5 Contents Compound Naming in the Agilent Fiehn Library 48 Metabolite Derivatizations Resulting in Multiple Compounds 50 5 Analyzing your Data 53 Using Agilent GC MS ChemStation 54 PBM Quick Search 54 Library search report 56 Screen report 57 Search basics 58 Using AMDIS 59 Data analysis 60 Using a different analytical method 62 Using Agilent MassHunter Qualitative Analysis 63 Install the Fiehn library to use with MassHunter Qualitative Analysis 63 Search Unit Mass Library on spectra 64 Search Unit Mass Library with Retention Time Matching on compounds 68 Export results to Mass Profiler Professional using CEF file 73 Using Agilent MassHunter Mass Profiler Professional 75 Overview of a metabolomics experiment using MPP 75 Elements to consider in planning your experiment 77 Create a new project and experiment 79 Import and organize your data 84 Perform your initial analysis 99 Save your project 113 Functional areas of MPP 114 AMDIS Getting Started 115
140. ition some compound derivatives prove to be unstable under unsuitable inlet conditions especially select amino acids and amides such as asparagine Primary amines are generally more readily derivatized by trimethylsilylation than secondary amines Primary amines can be completely derivatized modified by only one trimethylsilyl group or left underivatized A complete derivatization involves the exchange of both acidic protons with trimethylsilyl groups A common incomplete derivatization results in the exchange of a single trimethylsilyl group that often is the major derivative peak An underivatized amine is rarely found If more than one amine group is present in a metabolite an even higher number of derivative peaks can potentially be formed Amine groups are the primary reason why the Agilent Fiehn 2013 GC MS Metabolomics RTL Library contains more spectra than metabolites Hydroxyl and carboxyl groups are fully derivatized in all cases Alternatives for trimethylsilylation have been proposed by using tertiary butyldimethylsilyl derivatives or ethyl chloroformate see O Fiehn Extending the breadth of metabolite profiling by gas chromatography coupled to mass spectrometry TrAC Trends Anal Chem 2008 27 261 269 These or other derivatization methods are less universal than trimethylsilylations and are not included in the Fiehn 2013 GC MS Metabolomics RTL Library Methoxyamination Prior to trimethylsilylation ketones and aldeh
141. l ID NCGC00248960 01 Patents 3 records IBM SID 128383593 External ID A176CBC7DE331FD9CDA592160699DF73 SCRIPDB SID 142338819 External ID US06197558 20010306 C00002_3 Thomson Pharma SID 15297251 External ID 00057572 a is P n Golm Metabolome Database GMD Max Planck Institute of Molecular Plant Physiology SID 92298111 External ID F15D7D2F 5E37 4B87 A8D2 824D5097A4DE KEGG SID 3338 External ID C00036 Figure 133 Five links to Metabolic pathways are given by a PubChem Compound search Agilent Fiehn Metabolomics Library 205 7 Using CAS and PubChem Numbers 206 Agilent Fiehn Metabolomics Library Agilent G1676AA Agilent Fiehn GC MS Metabolomics RTL Library User Guide Reference Information Definitions 208 Derivatization Instructions 220 References 221 Er Agilent Technologies 207 8 Reference Information Definitions Alignment AMDIS Amino acid ANOVA Attribute Attribute value 208 Baselining Bayesian This section contains a list of terms and their definitions as used in this workflow Review of the terms and definitions presented in this section helps you understand the Agilent software wizards and the metabolomics workflow Adjustment of the chromatographic retention time of eluting components to improve the correlation among data sets based on the elution of specific component s that are 1 naturally present in each sample or 2 deliberately added to
142. ld change CB Methyi Capryate 17 812 341182912 00 27 85 16 00 down Lig 0 26 119 ur 18407 4 acetybunyic add 1 19 53 128662708 00 27 57 16 00 down 130 0 38 130 up CS Metny Pelargonate 9 248 56 76 241884144 00 27 85 16 00 own 1496921 36 2051 16 00 down CB Methvi Caprvate 17 8121 27 2473 1447459 62 20 47 16 00 un 9734 03 13 25 16 00 un 104 0942 08995 762917552 00 225 93 16 00 dam zae Taal 2 20 up 43 0 13 640567 2 04 1 03 2 04 dovn 121 0 27 121 up 18407 4 acerybuiyic add 1 10 53 3550 42 T132 16 00 up 22427 24 48 16 00 dom 13017 N cytlohex flormarride 9 814 28382028 00 24 76 16 00 dom 1 50 0 58 150 up C9 Methy Pelargonate 9 248 56 64 44130396 00 25 40 16 00 un 1 00 0 0 100 dam 12017 N cyelohewformamide 9 81 45791 54 21551 16 00 down azg 226 4 79 un 18170 benzy thiocyanate 10 958 4 68 223 4 68 down 3 07 1 62 3 07 up C4 Meth Myristate 15 597 2 15 i1 215 dom 127 0 4 127 up 12665 2 piperidone 2 8 723 192 02 738 16 00 down 4273937 15 38 76 00 up 127 0046 224026 100 5 00 dan down 7381035 no 22 03 16 0 up 1010826 84609 1 73 0 79 173 up gt 71 1 44 271 un 118407 4 acetybuiyic add 1 10 53 1 00 6 00 1 00 down 4905677 00 22 23 16 00 up 52803 70 squalene 25 251 1880851 14 20 16 00 dom 313 50 3 16 00 up TCO Methvi Pelargonate 19 2481 31 21 2 75 146 225 un 178 0 83 178 un 5280270 squalene 25 251 58807 3111843 00 2157 16 00 down Lag 9 38 Lo
143. le dialog navigate to the AMDIS32 DATA HP folder select the file L HISTIDINE d and click Open Select Data File Drives Path gt C v ENAMDISS2 DATANHP as Rl calibration D ai ALK3 D ais Test d a Cald a Calibr d 4s CARDSP D 4s Eai002 d 3 3 Eai008 d GROB D Mvall26 d Instrument Agilent ChemStation D gt Cancel IV Confirm file format Open in New Window Figure 91 Select data file dialog L HISTIDINE d 2 Click Analyze gt Analyze GC MS Data and in the Analyze GC MS Data dialog set Type of analysis to Use Retention Index Data Use the Target Library and RI Calib Data to select the Fiehn msl and Fiehn cal files respectively The dialog should now resemble the following Agilent Fiehn Metabolomics Library 157 6 AMDIS Getting Started x Type of analysis RSS eee Intern Std Lib CAAMDISSZ UBSFiehn ISL Cancel Settings Help Figure 92 Analyze GC MS Data dialog Use Retention Index Data The Intern Std Lib in the dialog is disabled This type of analysis does not involve the use of internal standards 3 Although retention index values are automatically computed in this analysis type you still need to tell AMDIS exactly how to use them Click Settings and in the Analysis Settings dialog click Identif Now set Minimum match factor to 60 For later note that the Match factor penalties group has its Maximum penalty value set at 20 and its Level
144. le in their combined form A compound spectrum generated to represent the molecular feature that includes more than one ion isotope or adduct not just M H and is used by Mass Profiler Professional for recursive analysis and ID Browser A metabolite that may be individually referred to as a compound molecular feature element or entity during the various steps of the metabolomic data analysis Another term for one of several values within a parameter for which exist correlating samples Condition may also be referred to as a parameter value during the various steps of the metabolomic data analysis See also attribute value Information in a form suitable for storing and processing by a computer that represent the qualitative or quantitative attributes of a subject Examples include GC MS and LC MS data consisting fundamentally of time ion m z and ion abundance from a chemical sample Conversion of data into meaningful information Computers are employed to enable rapid recording and handling of large amounts of data i e Agilent MassHunter Workstation and Agilent Mass Profiler Professional See reduction The technique of reconstructing individual mass and mass spectral data from co eluting compounds An element in a data set that can only be observed as a result of the influence from the variation of an independent variable For example a pharmaceutical compound structure and quantity may be controlled as two independent va
145. lected sample is highlighted using a background color for the sample row 5 Click Assign Value Eladd ed periment Para xj Grouping of Samples Samples with the same parameter values are treated as replicate samples To assign replicate samples their parameter values select the samples and click on the Assign Values button and enter the value for the group Set the parameter type to numeric to interpret the parameter values as numbers Parameter name hine Variety Parameter type Non Numeric v Parameter Values Assign Value Clear Help ok _ cancer Figure 31 Add Edit Experiment Parameter dialog box 6 Type the value for your first grouping in the Assign Value dialog box 7 Click OK En x Enter a value for the selected samples A Sample Figure 32 Assign Value dialog box 8 Click your replicate Samples that share the same second parameter value in your data 9 Click Assign Value 10 Type the value for your second grouping in the Assign Value dialog box 11 Click OK 12 Review your entries and grouping assignment accuracy in the Add Edit Experiment Parameter dialog box Repeat the Sample selection and Agilent Fiehn Metabolomics Library Analyzing your Data 5 Assign Value steps until all of your samples are assigned a parameter value 13 Click OK when the grouping for this Parameter name is complete Eladg tdit Experiment Parameter xj Grouping of Samples Samples with the same pa
146. lishing the spectra and RT or computed RI for the metabolites included in the Agilent Fiehn 2013 GC MS Metabolomics RTL Library An RT match with the library is necessary when using the Agilent GC MS ChemStation to find metabolites in biological samples The parameters specified in Acquisition Method on page 35 should be faithfully followed in addition to using an RTL method run on the GC MS ChemStation software for acquiring data The AMDIS program s library stores an RI calculated from the actual RT of each metabolite The AMDIS program uses a calibration file to translate RT to RI values If the exact acquisition method presented here was not followed a good match can be obtained as long as the relative retention order of the compounds is the same in both acquisition methods The FAME markers used for calculating retention indices are not required in a sample It is required that a FAME marker calibration sample is run and correctly associated with a sample Once this association is established the FAMEs markers can be left out of each sample The inclusion of FAMEs markers in one of the daily samples can guarantee a correct RI calibration can be performed The RTL locking compound should be included in every sample Examining the locking compound in a data file from an RTL method determines if a re locking needs to be performed Examining the RTs of the FAME markers determines if a ae Agilent Technologies 31 3 32 Experime
147. lite QC standards To check the overall instrument sensitivity as well as the compliance of the injector system it is recommended to inject mixtures of metabolites as quality control QC standards These QC samples are analyzed at a minimum of four different concentrations before and between sequences of biological samples Specifically low and high boiling metabolites have to be present for example pyruvate and raffinose as well as representatives of various metabolite classes aromatic compounds such as benzoic acid carbohydrates such as fructose hydroxyl acids such as malic acid organic phosphates such as glucose 6 phosphate steroids such as cholesterol and a variety of amino acids such as glycine alanine glutamate asparagine and serine Peak shapes sensitivities and peak ratios of these compounds have to be monitored and have to be compliant to lower and upper QC intervention limits Agilent Fiehn Metabolomics Library Experimental and Instrument Method 3 GC maintenance In particular the injector system has to be maintained regularly depending on the type of matrix and number of injections For example liners should be exchanged at least every 40 samples The gold plated seal needs to be changed if too much matrix deposits lead to noncompliant QC conditions After every liner exchange the new liner must be cleaned and deactivated by reagent blank injections Peaks that are generated from the liner deactivation are n
148. lu and find compound data file fin The elute data file contains a list of all of the peaks found including ion and abundance This is a file containing unidentified compounds components The find data file contains a list of all of the compounds found including the compound information and assignments This is a file containing identified compounds targets Agilent Fiehn Metabolomics Library 17 1 18 Introduction The Agilent statistical analysis software package for analyzing GC MS data is called Agilent MassHunter Mass Profiler Professional Mass Profiler Professional imports the files generated using AMDIS The first step in the analysis of multiple data files is to align the found peaks in each data file across all the runs in the study The software determines which peaks in each chromatographic run are the same compound and which are different Compound identification prior to peak alignment makes this task much easier for the identified compounds Identification of compounds using the Agilent Fiehn Library is very helpful in the statistical analysis of data sets Once data from all the GC MS analyses are aligned and normalized a number of interpretation algorithms can be applied to find the metabolite relationships to the problem being studied The use of statistics to analyze complex data sets is outside the scope of this guide For more information on importing GC MS data into the Agilent MassHunter Mass Profiler
149. mStation This example is for AMDIS and you can change the Fiehn M method to omit printing the report 2 At the end of the sample run from GC MS ChemStation s Analysis View select AMDIS from the Spectrum menu to start AMDIS with the sample run data file loaded 3 Select Analyze GC MS Data from the Analyze menu x GC MS Data C msdchem 1SDATA L Histidine D Type of analysis Target Library C ANISTOS AMDIS32 LIB Fiehn MSL Intern Std Lib CANISTOS AMDISS2 LIB Fiehn ISL RI Cali Data C ANISTOSNAMDIS32 LIB Fiehn CAL Use Rl Calibration Data Cancel Settings Help 4 For the Type of Analysis select Use RI Calibration Data If you have followed the instructions in Recommended Settings on page 183 the correct Target Library and RI Calib Data files specified should be as shown above 5 Click Run to analyze the data file See Figure 9 60 Agilent Fiehn Metabolomics Library Analyzing your Data 5 gj AMDIS Chromatogram Component Mode L HISTIDINE D C MSDCHEM 1 DATA L HISTIDINE D DATA MST Fi fE A File Analyze Mode View Library Options Window Help Roses me E 0 Time 838 11 17 13 97 16 76 1956 22 36 25 15 27 95 30 75 33 54 36 34 Abundance 27 9 2 100 75 50 ee RI 677 1 a RT 6 85 Width 3 6 scans Tjee 57 8 Purity 96 Abundance 67333 Scan 14 6 068 min and Extracted spectrum 6 067 min 100 TS 50 2
150. malization Criteria Scale the signal intensity of sample features to a value calculated by the specified algorithm or an external scalar Agilent Fiehn Metabolomics Library Analyzing your Data 5 Step 11 Baselining Options Compare the signal intensity of each sample to a representative value calculated across all of the samples or the control samples Flow Chart of the MS Experiment Creation Wizard Step 6 Experiment Grouping Step 1 Select Data Source Step 9 Sample Summary Step 2 Step 10 Select Data to Step 7 Filterin Normalization Criteria Skip Step 8 for identified experiment Step 8 Alignment unidentifed experiment Steps 3 amp 4 skipped Step 5 Sample Reordering Step 11 Baselining Options V GotoStepp9 Create an initial analysis Import Goto Step6 Figure 26 Steps performed by the MS Experiment Creation Wizard Step 1 of 11 Select Data Source 1 Select the source of your data files The available data source selection depends on the Experiment type you selected in the New Experiment dialog box Figure 25 on page 82 For metabolomics analyses using GC MS data you typically select MassHunter Qual Chemstation or AMDIS 2 Select the Organism represented by your experiment Selecting an Organism is most important when you use the Pathway Analysis features of MPP 3 Click Next Agilent Fiehn Metabolomics
151. mory Workflow Browser List of operations relevant for the experiment organized into sequential groups of operations for the analysis Project Navigator List of the experiments within the current project il il Type er averaged Type Desktop Area Interactive views for selections made in the Experiment Navigator and the Workflow Browser Bi Type tor sveraged Poouncance valves acceale P M AN Experiment Navigator il Type Norr averoped QU Type analyses and favorites within the selected experiment Run Pdi rem fie Export Peceton Model a Legend Color key related to y 7 the current view Status Bar a Pe a Legend Profle pit L092 Norman Information related to the current view lo a 01 and a memory monitor Click the garbage can to reduce memory usage a AOL Log AOZ Log OB Log BON Log B02 Log Al Samples alle een Oecd T U T amor ia Figure 60 The main functional areas of Mass Profiler Professional Agilent Fiehn Metabolomics Library Agilent G1676AA Agilent Fiehn GC MS Metabolomics RTL Library User Guide 6 AMDIS Getting Started Running AMDIS 116 To simultaneously view AMDIS and its Help window 116 To put AMDIS into an initialized state 116 Confirm Window and Results Window 118 Confirm Window Appearance 119 Results Window Appearance 126 Analysis Types 128 Tutorials Overview 130 An
152. n in Update the AMDIS cal file on page 40 This different method could not be used for searches on the GC MS ChemStation where RT is necessary for metabolite confirmation The RT contained in the Fiehn L library or screener file is only valid for the unmodified Fiehn M method Existing data files containing FAME markers If you have data files obtained with an RTL method that is different from the Fiehn M method but using the same FAME markers you can use AMDIS to identify the metabolites using the concepts presented in this guide You first use the data file containing the FAME markers to update the RTs in the Fiehn cal file See Update the AMDIS cal file on page 40 Then run this data file on AMDIS using an Analysis Type of Use RI Calibration Data Agilent Fiehn Metabolomics Library Analyzing your Data 5 Using Agilent MassHunter Qualitative Analysis You can use the Agilent MassHunter Qualitative Analysis software to search either spectra or compounds If you want to export the results to the Agilent Mass Profiler Professional program you first search compounds that you created and then you export a CEF file which contains the information on each of the compounds e Install the Fiehn library to use with MassHunter Qualitative Analysis on page 63 e Search Unit Mass Library on spectra on page 64 e Search Unit Mass Library with Retention Time Matching on compounds on page 68 e Export results t
153. n times Each of the derivatized compounds share the same CAS number For any given search of a data file AMDIS only reports a compound or CAS number once AMDIS reports the derivative that possesses the highest match factor MF It does not report the other derivatives The detection of one of these peaks is necessary and sufficient to claim the identification of this compound in a particular sample The use of the screener version of the library in the ChemStation is more likely to identify and report all of the derivatized compounds Agilent Fiehn Metabolomics Library 189 6 AMDIS Getting Started 190 Agilent Fiehn Metabolomics Library Agilent G1676AA Agilent Fiehn GC MS Metabolomics RTL Library User Guide ee Using CAS and PubChem Numbers KEGG LIGAND Database 193 MetaCyc Database 196 ChemSpider Database 199 SciFinder Substance Identifier Database 202 PubChem Compound Database 203 This section describes how to use CAS entries and PubChem numbers to retrieve supplemental chemical and biochemical information on metabolites The Agilent Fiehn Library contains CAS and PubChem numbers used to identify metabolites in biological samples You can use these numbers to derive biologically relevant information from quantitative and qualitative comparisons It is critical that library searches provide data that can be used to perform biological interpretations Such interpretations can be performed by placing metabolites int
154. nally note that in the Corrections list the RETENTION value is 0 0 Note that the Net match factor is increased over the weighted value of 93 due to the high purity of the component and the reverse search logic Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Analysis Type Use Internal Standards for RI If you have retention index RI information stored in a Target Compounds Library an Internal Standards Library isl can be used to aid the target identification process To take advantage of this it is also necessary that one or more of the internal standard compounds represented by the library are co injected with the sample A Target Compounds Library has a msl file extension and an Internal Standards Library has a isl file extension The Use Internal Standards for RI analysis type first identifies target and internal standard compounds using spectral comparisons only exactly as in the Simple analysis type Next using the known RI values and actual retention times of the internal standards that have been found it computes RI values for all of the identified library targets using linear interpolation techniques Only now does it determine what to do with these retention indices If you have elected to use RI information see below for each identified target it the computed RI value is compared with the value held in the Target Compounds Library and the target s match value is adjusted according to how good the
155. nalysis and Agilent Mass Profiler Professional in performing metabolomics GC MS experiments AMDIS Getting Started Introduces AMDIS and is taken directly from Chapter 2 of the AMDIS online help and is presented here with the author s permission Agilent has found that many AMDIS users who were having trouble with the program s concepts were able to master the program once they became aware of this help Agilent thinks that this material is important enough to repeat it in this manual Using CAS and PubChem Numbers Reviews investigative data found on popular Web sites for identifying metabolites using the CAS and PubChem numbers found in the library Reference Information This chapter consists of definitions derivatization instructions and references The definitions section includes a list of terms and their definitions as used in this workflow The derivatization section contains instructions for derivatizing d 7 myristic acid to update the GC MS retention time locking The references section includes citations to Agilent publications that help you use Agilent products and perform your metabolomics analyses Agilent Fiehn Metabolomics Library Contents Contents 1 Introduction 9 Scope and Intended Use 10 Library Content 11 User guide 11 AMDIS program 12 Agilent Fiehn Library metabolite list 12 GC MS ChemStation files 12 AMDIS files 13 Application Notes 14 Backup files for the library 14 Metabolic Profil
156. nalysis Type continued AMDIS analysis type Fiehn use description Required AMDIS files Use Internal Standards for RI Use RI Calibr Data Internal Std Performance Check for RI This analysis mode is used when one or more of the compounds in the Fiehn isl files are part of the acquired data file This mode can produce superior RI results because the RI standards are acquired at the same time as the target compounds The disadvantage of this mode is that some target compounds coelute with the internal standards This analysis mode uses the CAL file for the RI calculations and uses the internal standards as a functional check of the acquisition system This mode expects the RI standards to be injected with the sample This analysis mode is used to evaluate the performance of the acquisition system This mode expects the RI standards to be injected Fiehn msl Fiehn isl Fiehn msl Fiehn isl Fiehn cal Fiehn csl Fiehn cal Agilent Fiehn Metabolomics Library 131 6 AMDIS Getting Started Analysis Type Simple Analysis Type This example illustrates the most basic operation of AMDIS which is to locate and extract significant spectra from a GC MS data file and then compare them against an AMDIS Target Compounds Library It also describes the interactive ability to search a component s spectrum against the main NIST mass spectral database and any other NIST format libraries see Searching the N
157. nced statistical analysis and visualization tools for GC MS LC MS CE MS ICP MS and NMR data analysis MPP also integrates smoothly with Agilent MassHunter Workstation Spectrum Mill ChemStation and AMDIS software and is the only platform that provides integrated identification annotation of compounds and integrated pathway analysis for metabolomic and proteomic studies This section covers the following features of analyzing your data using MPP e Overview of a metabolomics experiment using MPP on page 75 e Elements to consider in planning your experiment on page 77 e Create a new project and experiment on page 79 e Import and organize your data on page 84 e Perform your initial analysis on page 99 e Save your project on page 113 e Functional areas of MPP on page 114 Overview of a metabolomics experiment using MPP MPP is used to import organize and analyze the data you acquired A metabolic profiling experiment may include the following steps 1 prepare for your experiment 2 acquire your data 3 find the spectral features 4 import and organize your data 5 create your initial analysis 6 identify the features 7 save your project and 8 perform advanced analysis operations Figure 19 on page 76 shows the Agilent tools used in metabolic profiling MPP is used for steps 4 through 8 Agilent Fiehn Metabolomics Library 75 5 Analyzing your Data MPP helps you analyze yo
158. ncluded for each metabolite spectrum is a required part of peak identification routines when using this library Along with electron impact mass spectra the library holds retention times of all the metabolite derivatives The RTL software has been used to generate all the retention times which enables universal retention times as long as the same GC MS method and chromatographic column are used Therefore any user laboratory can reproduce the results by locking the retention times to the mass spectral library Metabolite identification requires using the same GC MS conditions listed in Acquisition Method on page 35 These parameters include using the Agilent ZORBAX DB 5MS column and trimethylsilylated myristic acid d27 as internal standard for RTL Criteria for successful compound identification have been frequently discussed in the scientific literature over the past five decades It is evident today that a single parameter such as a mass spectral similarity threshold is insufficient to correctly confirm the presence of a particular Agilent Fiehn Metabolomics Library Peak Identification 4 compound in a sample The use of an absolute retention time or alternatively a retention index is a necessary part of the identification strategy GC MS data is acquired using a RTL method for retention time repeatability across all compounds in the library The GC MS library stores retention times that are used directly in identifications
159. nd retrieval to analyze and solve problems in the field of chemistry Chemometrics A science employing mathematical and analytical processes to extract information from chemical data sets The processes involve interactive applications of techniques employed in disciplines such as multivariate statistics applied mathematics and computer science to obtain meaningful information from complex data sets Chemometrics is typically used to obtain meaningful information from data derived from chemistry biochemistry and chemical engineering Agilent Mass Profiler Professional is designed to employ chemometrics processes to GC MS and LC MS data sets to obtain useful information Child A subset of information that is created by an algorithm from an original set of information An entity list created using Mass Profiler Professional is a child An original entity list is referred to as the parent of one or more child entity lists Agilent Fiehn Metabolomics Library 209 8 Reference Information Co elution Complex Composite spectrum Compound Condition Data Data processing Data reduction Deconvolution Dependent variable Determinate 210 When compounds elute from a chromatographic column at nominally the same time making the assignment of the observed ions to each compound difficult Class of compounds consisting of more than one protein physically which physically bind each other and are biologically active and stab
160. nd the PubChem identifier help you find further information on these compounds on the Internet These identifier values are an important feature of the library to help you gain knowledge about the chemical and biological properties and relevance of detected GC MS peaks CAS numbers The Chemical Abstracts Service CAS index is a chemical database and a division of the American Chemical Society ACS CAS numbers can be copied from the NIST Search results and used either to gather biochemical information from freely available Web resources such as ChemSpider www chemspider com or publicly supported and curated databases such as KEGG www genome jp kegg or MetaCyc www metacyc org Examples using these databases with CAS identifiers are given in Chapter 7 Using CAS and PubChem Numbers In addition to such pathway links CAS entry numbers can be used in conjunction with the SciFinder database https scifinder cas org scifinder which is accessible for a fee The SciFinder database contains chemical information on compounds and specifically the chemistry of metabolites Agilent Fiehn Metabolomics Library Peak Identification 4 PubChem identifiers The Agilent Fiehn 2013 GC MS Metabolomics RTL Library supports PubChem identifiers The library includes them for every spectral entry which is given in brackets ahead of the metabolite name Therefore the PubChem numbers can be retrieved either from AMDIS or from an Agilent PBM Quick S
161. ndow click Confirm to go to the Confirm window Starting AMDIS from the GC MS ChemStation or the Windows Start menu always starts in the Confirm window 118 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Confirm Window Appearance The Confirm window has two basic appearances according to whether or not it is showing the results of an analysis When results are being shown the contents of the Confirm window are also regulated using the Mode command See the AMDIS online Help for more information When a new data file is initially opened and does not have previously kept results the Confirm window has two areas consisting of a Chromatogram Display and a Mass Spectral Display as shown in Figure 63 3 AMDIS Chromatogram Manual Mode L HISTIDINE D File Analyze Mode view Library Options Window Help C AMDIS32 DATA HP L HISTIDINE D DATA MS Ben Regeae Io lMerustOe Decow J Abundance 0 001 100 75 50 25 Ems HUT a PES Dorn a Te Pn a a ee Time 920 12 95 16 70 20 45 2420 27 96 31 71 35 46 Abundance 24 6 Scan 229 7 413 min and Manually Extracted spectrum _ 100 150 200 250 300 350 400 450 500 550 Figure 63 Confirm window showing unprocessed data When a data file has been analyzed or a file is opened with previously kept results the Confirm window has four basic areas e Chromatogram Display Profile Display Agilent Fiehn Metabolomics Library 119 120 AMDIS Getting Started
162. normally distributed data sets See also ANOVA Agilent Fiehn Metabolomics Library Reference Information 8 Unidentified Chromatographic components that are only uniquely denoted by their compound mass and retention times and which have not been assigned an exact identity such as compound name and molecular formula Unidentified compounds are typically produced by feature finding and deconvolution algorithms See also Identified Compound Variable An element in a data set that assumes changing values e g values that are not constant over the entire data set The two types of variables are independent and dependent Volume The area of the extracted compound chromatogram ECC The ECC is formed from the sum of the individual ion abundances within the compound spectrum at each retention time in the specified time window The compound volume generated by MFE is used by Mass Profiler Professional to make quantitative comparisons Wizard A sequence of dialog boxes presented by Mass Profiler Professional that guides you through well defined steps to enter information organize data and perform analyses Agilent Fiehn Metabolomics Library 219 8 Reference Information Derivatization Instructions Derivatization of d7 myristic acid is required before using this material for GC MS retention time locking 3 4 In a V bottom GC vial e g Agilent p n 5184 3554 with screw cap Agilent p n 5182 0723 assemble the derivatization reaction
163. ntal and Instrument Method retention index calibration needs to be performed The retention time or RI is a very important part of the analysis This measurement is used in combination with the EI spectra to identify a metabolite Experimental Internal standard RTL locking compound Myristic acid d27 Product 366889 Sigma Aldrich St Louis MO A stock solution of 3 mg mL is prepared in the solvent mixture water methanol isopropanol 2 5 2 v v v RT of the locking standard is 16 752 minutes Retention index markers Fatty acid methyl esters FAME Sigma Aldrich St Louis MO Cg Co Co Cy Cs Cig Cig Co9 Coo Coq Cog Cog and C30 linear chain length are dissolved in chloroform at concentrations of 5 mg mL Cg C16 and 2 5 mg mL Cjg Cao The inclusion of these markers in a sample chromatogram can be used as a QC check If identical chromatographic conditions as those employed to generate the Agilent Fiehn Library were used the RT values match The Agilent Fiehn GC MS Metabolomics Standards Kit p n 5182 0723 contains the RTL locking compounds and the FAMES Table 1 FAME markers Name Concentration RT min Methyl caprylateCg 100 pg mL 7 812 Methyl perlargonate Cg 100 pg mL 9 248 Methyl caprateC 100 pg mL 10 647 Methyl laurate C42 100 pg mL 13 25 Methyl myristate C44 100 pg mL 15 597 Methyl palmitate C46 100 pg mL 17 723 Methyl stearate Cy 50 pg mL 19 663 Agilent Fiehn Metabolomics Library Experimen
164. ny parameters as you like but only the first two parameters will be used for analysis in the guided workflow Other parameters can be used in the advanced analysis You can also edit and re order parameters and parameter values here Displaying 9 sample s with 1 experiment parameter s To change use the button controls below ht Bae Samples A Sample A Sample lA Sample B Sample B Sample B Sample __ C Sample C Sample C Sample Add Parameter Edit Parameter Delete Parameter Help lt lt Back Next gt gt Einish Cancel Figure 34 Experiment Grouping page Step 6 of 11 of the MS Experiment Creation Wizard Step 7 of 11 Filtering 1 Mark an Abundance filtering option e Minimum absolute abundance limits the data that is imported to absolute abundances greater than the specified value The abundance counts can be between 1 and 1 000 000 000 Limit to the largest limits the number of compounds that imported for each sample file to the number specified The compounds are selected starting with the highest abundance value in descending order The number of compounds can be between 1 and 99 Minimum Relative Abundance filters out the compounds in a sample file that have a relative abundance less than the value specified with respect to the most abundant compounds in the file The relative abundance is calculated by dividing abundance value for each comp
165. o Mass Profiler Professional using CEF file on page 73 Install the Fiehn library to use with MassHunter Qualitative Analysis When you install the Fiehn library and you have MassHunter Qualitative Analysis installed the library is automatically placed in the Program Files x86 Agilent Fiehn Metabolomics RTL Database G1676AA folder The library needs to be copied to the MassHunter Library folder The data files need to be translated and copied to the MassHunter Data folder 1 Copy the library from Program Files x86 Agilent Fiehn Metabolomics RTL Database G1676AA GCMS Libraries Fiehn L to the MassHunter Library folder The Qualitative Analysis program cannot use the library if it is in the Program Files x86 folder 2 Translate the GC MSD data files which are in the Program Files x86 Agilent Data folder and put the files in the MassHunter Data folder You need to install the translator program first which is available on the GC MS Supplemental Software disk a Double click the GC MSD Translator icon Agilent Fiehn Metabolomics Library 63 5 64 Analyzing your Data b Select the Folder containing Data Files to Import Click Browse In the Browse For Folder dialog box navigate to the C Program Files x 86 Agilent Agilent Fiehn GCMS Metabolomics RTL Database G1676AA Data folder and click OK c Select the Output Folder Click Browse In the Browse For Folder dialog box navigate to the MassHunter Data fold
166. o chemical and biochemical context notably by mapping to biochemical pathways but also by comparing physicochemical properties or scientific literature CAS entries do not necessarily support unique records for each chemical structure because CAS lists multiple identifiers for different versions of chemicals e g sodium or potassium salts of anions of organic acids The Fiehn library uses best possible numbers to refer to CAS entries and in addition Internet resources often recognize different CAS numbers as variants of a unique metabolite Contact Agilent if you find inadequate annotation of metabolites with either PubChem or CAS entries ae Agilent Technologies 191 7 192 Using CAS and PubChem Numbers The examples that follow use oxaloacetate with a CAS 328 42 7 and a PubChem 970 These examples demonstrate how these compound identifiers are used to query biochemical and chemical databases Resulting information ranges from lists of synonym names to structural chemical and biochemical data and comprises both calculated properties as well as links to other external databases Agilent Fiehn Metabolomics Library Using CAS and PubChem Numbers 7 KEGG LIGAND Database 1 To access this database enter http www genome jp ligand into your internet browser 2 Scroll down to Search Compound and select DBlinks from the dropdown list Enter 328 42 7 in the adjacent text box for the CAS number and click Go KEGG LIGAND
167. odel using imported training data Experiment name Fiehn Unidentified Analysistype Mass Profiler Professional Experiment type ne Workflow type Analysis Significance Testing and Fold Change Data source from AMDIS Experiment notes el Lo _ em Figure 25 New Experiment dialog box DielgBosFil_ VourGhoices common Edit field to describe this experiment Analysis type Mass Profiler Professional Mass Profiler Professional must be selected lt other choices depending on Order IDs gt Experiment type Unidentified lt see the next table for more information gt Identified Combined Identified Unidentified Workflow type Analysis Significance Testing and Fold Change Analysis Significance Testing and Fold Change is Class Prediction Build and Test Model recommended to provide qauality control and Data Import Wizard improve your results Edit field to enter other experimental notes Table 2 Summary of selections and entries in the New Experiment dialog box Agilent Fiehn Metabolomics Library Analyzing your Data 5 Experiment Type Data Source Fle Types Comments Identified MH Quant TCompounds identified by MassHunter Quantitative Analysis Chemstation fin Compounds identified by Chemstation Quantification or Screener processes AMDIS fin__ Compound identified by an AMDIS target library Generic xls Entries identified by Compound column C Formula column D xlsx CA
168. om 473 to 261 when one hit wonders were removed 8 Click Next Steps Filter Flags rege Normalized Intensity Values sample Esap samote Tee Game Figure 44 Filter Flags page of the Analysis Significance Testing and Fold Change Step 3 of 8 workflow before filtering one hit wonders lFilter Parameters xi Acceptable Flags IV Present 1 Marginal I absent Retain Entities in which C atleast 100 0 of the values in any 1 out of 3 conditions have acceptable values atleast 2 out of 9 samples have acceptable values a con Figure 45 Filter Parameters dialog box Agilent Fiehn Metabolomics Library 103 5 104 Analyzing your Data Filter Flags tensity Normalized im A sample E sampile c sample Hep lt lt Back Next gt gt fins Cancel Figure 46 Filter Flags page of the Analysis Significance Testing and Fold Change Step 3 of 8 workflow after filtering one hit wonders Step 4 of 8 Filter by Frequency 1 ao A w Review your data change the plot view export selected data or export the plot to a file Click Re run Filter to enter parameters in the Filter Parameters dialog box Figure 48 on page 105 Filter Frequency allows you to filter the input data based upon the frequency with which any compound appears in each sample in the experiment
169. om the File menu Navigate to the AMDIS32 DATA HP directory and select the GC MS ChemStation data file used for the FAME calibration run 5 Select GC MS Data from the Analyze menu 6 Change the Type of Analysis to RI Calibration Performance xi GC MS Data C HP FAMES HP5MS 2COL SPLITO1 D Type of analysis RI Calibration Performance x Calib Stds Lib a C AMDIS32 LIB Fiehn CSL ntem 5 je CAMDISS2 UIBSFiehn ISL RI Calib Data C AMDIS32 LIB Fiehn CAL Previous Rl calibration data will be replaced Cancel Settings Help Agilent Fiehn Metabolomics Library Experimental and Instrument Method 3 7 Change the Calib Stds Lib to the supplied Fiehn csl file 8 Change the RI Calib Data to Fiehn cal This file is overwritten in this analysis You can use a new file name if you wish to keep the original supplied file x cc a Type of analysis RI Calibration Perfomance Calib Stds Lib 3j Intern Std Lib CAMDISSZ UIB Fiehn ISL RI Calib Data C AMDIS32 DATASHP MyNew cal Previous AI calibration data will be replaced Cancel Settings Help 9 Click Runto update the RI Calibration Data file 10 Click the Info button above the chromatogram and click the Standards tab AMDIS Results FAMES 2COL SPLITO1 D x Library Settings Standards gavgc sm RI galib C NISTOS AMDIS32 LIB Fiehn CAl RT Al Name
170. on The study of the metabolites of an organism presents a chemical fingerprint of the organism under the specific situation See metabonomics for the study of the change in the metabolites in response to externalities The metabolic response to externalities such as drugs environmental factors and disease The study of metabonomics by the medical community may lead to more efficient drug discovery and to individualized patient treatment Meaningful information learned from the metabolite response can be used for clinical diagnostics or for understanding the onset and progression of human diseases See metabolomic for the identification and quantitation of metabolites Natural Language Processing NLP algorithm that extracts information from published literature A technique used to adjust the ion intensity of mass spectral data from an absolute value based on the signal measured at the detector to a relative intensity of 0 to 100 percent based on the signal of either 1 the ion of the greatest intensity or 2 a specific ion in the mass spectrum The default position taken by the hypothesis that no effect or correlation of the independent variables exists with respect to the measurements taken from the samples Data acquired in an attempt to understand causality where no ability exists to 1 control how subjects are sampled and or 2 control the exposure each sample group receives An entity that appears in only one sample is a
171. onnec tion with the furnishing use or per formance of this document or of any information contained herein Should Agilent and the user have a separate written agreement with warranty terms covering the material in this document that conflict with these terms the warranty terms in the sep arate agreement shall control Technology Licenses The hardware and or software described in this document are furnished under a license and may be used or copied only in accor dance with the terms of such license Restricted Rights Legend U S Government Restricted Rights Soft ware and technical data rights granted to the federal government include only those rights customarily provided to end user cus tomers Agilent provides this customary commercial license in Software and techni cal data pursuant to FAR 12 211 Technical Data and 12 212 Computer Software and for the Department of Defense DFARS 252 227 7015 Technical Data Commercial Items and DFARS 227 7202 3 Rights in Commercial Computer Software or Com puter Software Documentation Safety Notices CAUTION A CAUTION notice denotes a haz ard It calls attention to an operat ing procedure practice or the like that if not correctly performed or adhered to could result in damage to the product or loss of important data Do not proceed beyond a CAUTION notice until the indicated conditions are fully understood and met A WARNING notice denotes a hazard It
172. ore calculation 7 Click Next Elms Experiment Creation Wizard Step 7 of 11 E x Filtering Filtering during the data import process may be used to reject low intensity data or restrict the range of data After data is imported there are several filtering options that may be applied Filter by Frequency Abundance Variability Flags and Annotation For AMDIS experiments Number of ions filter is Number of Model ions Abundance filtering IV Minimum absolute abundance 10000 counts I Limit to the largest compounds JT Minimum relative abundance Retention time filtering Mass filtering IV Use all available data Min RT 6 78 0 78 1 0 0 Number of ions gt p Charge states All charge states permitted Number of ions required gt 3 Multiple charge states requirec Multiple charge Compound Quality Score Fier Minimum Quality Score 25 ei Help lt lt Back Next gt gt Einish Cancel Figure 35 Filtering page Step 7 of 11 of the MS Experiment Creation Wizard Agilent Fiehn Metabolomics Library 93 5 94 Analyzing your Data Step 8 of 11 Alignment Parameters This step is applicable for Unidentified experiment types Identified compounds are treated as aligned by identification and this step is omitted The formula for performing the alignment is described in section 3 2 7 Alignment Parameters Step 8 of 11 in the Mass Profiler Professional User Manual Click
173. ot considered genuine reagent peaks but represent dirt from various chemical sources Agilent Fiehn Metabolomics Library 43 3 Experimental and Instrument Method 44 Agilent Fiehn Metabolomics Library Agilent G1676AA Agilent Fiehn GC MS Metabolomics RTL Library User Guide e eo o e ee 4 a Peak Identification Peak Identifications from Metabolite Profiles 46 Compound Naming in the Agilent Fiehn Library 48 Metabolite Derivatizations Resulting in Multiple Compounds 50 Er Agilent Technologies 45 4 46 Peak Identification Peak Identifications from Metabolite Profiles Identifying isomers Metabolites come in many isomeric forms For example there are eight D aldohexoses of which D glucose is certainly the most well known metabolite However D mannose and D galactose frequently occur at low concentrations in biological samples The presence of allose altrose gulose idose and talose also cannot be excluded without further knowledge of the sample Electron impact mass spectra of the derivatized products of these metabolite isomers are virtually identical The correct identification of the metabolite isomer requires the use of retention time as the qualifying factor The use of retention information is one of the primary features of the Agilent Fiehn Library Retention time matching All library spectra have been acquired using the Agilent retention time locking RTL feature The retention time i
174. ound hit graphically displayed directly below 54 Agilent Fiehn Metabolomics Library Analyzing your Data 5 3 Move the selection in the PBM Search Results dialog box through the various hits by clicking them As you select each hit the graphic display s lower spectrum is replaced with the selected hit s spectrum The first entry listed is the one that has the most probable spectral match This is not sufficient to positively identify a hit You need to further confirm a library spectral match with retention time File Method Chromatogram Spectrum Calibrate Quantitate Tools View Toolbars Help ETTET EEC T EEEE Window 26 27 117 133 169173 189204 231244 282 291 a20 b36as0384a76390404 433 100 150 U 553 MoL sorbose 2 17 235 231244 262277291 320 B36350384376390 420432 448 466 Figure 8 Identification of sorbose 2 by mass spectral similarity and RT comparison using the PBM Quick Search 4 From the PBM Search Results dialog box of similar spectra use the displayed bracketed RT values shown circled in red in Figure 8 to make a correct identification of the compound Agilent Fiehn Metabolomics Library 55 5 56 Analyzing your Data The correct identification is sorbose 2 since its retention time of 17 235 minutes matches that of the selected peak Other ketohexoses and ketopentoses with almost identical spectra such as the first PBM hit lyxose do not have close RT matches Only by using the
175. ound in a sample by the abundance value of compound with the largest abundance in the same sample The percentage can be between 1 and 100 For GC MS datasets the Minimum Relative Abundance filtering is performed on identified and unidentified compounds separately 2 Mark Use all available data or enter the retention time range for the compounds to import for Retention time filtering Agilent Fiehn Metabolomics Library Analyzing your Data 5 3 Mark Use all available data or enter the mass range for the compounds to import for Mass filtering 4 Enter the minimum number of model ions required in order for a compound to be imported in Number of ions required gt For AMDIS data the default is five 5 5 Select the applicable Charge states parameter allowed for your experiment This parameter is not available for AMDIS data sets 6 Enter the Minimum Quality Score for the Compound Quality Score Filter Compounds with a quality score less than the value specified are filtered out The quality score value can be between 1 and 100 This parameter is only available for AMDIS experiments Quality Score a MO b SNR c Log10 abundance MO is the number of model ions and SNR is the signal to noise ratio The coefficients a b and c are 1 by default Click Tools gt Options to launch the Configuration Dialog dialog box Then click MS gt AMDIS Compound Quality Score Parameters to adjust the weighting coefficients used by the quality sc
176. progress of the search of the selected component s spectrum this can take up to a minute or two when first invoked The component is identified as Oleic Acid a component of the analyzed oil As noted earlier the Agilent Fiehn Library reports compounds as metabolites L Histidine whereas the NIST Search program correctly identifies the metabolite that has been analyzed as a trimethylsilyl TMS derivative The exact library result here and elsewhere depend on the installed libraries and the search parameters currently set in the NIST MS Search program The result here occurs when using default search parameters and searching the Main and Replib libraries From the MS Search program use the ALT TAB key or the Windows task bar to get back to AMDIS Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Analysis Type Use Retention Time If you wish to use retention times as an additional aid in identifying targets AMDIS can use those stored in a Target Compounds Library It is a prerequisite of this type that a Target Compounds Library exists Before following the instructions below ensure that AMDIS is in a known state by following the instructions in To put AMDIS into an initialized state on page 116 There should now be an empty Confirm window displayed 1 Click File gt Open and in the Select Data File dialog navigate to the AMDIS32 DATA HP folder select the file L HISTIDINE d and click Open As normal the
177. r 169 0 58 81264 3303918 5 21 14 16 00 down 95 58 5 58 16 00 dom 142 0 52 697197 1 00 0 00 1 00 sown 3572069 25 21 35 16 00 ur 121 0 46 9153 1 09 0 00 1 00 sown 364099250 21 80 16 09 ur 169 0 45 933502 1 00 0 00 1 00 down 292828125 21 48 16 09 FEB Help lt cBack eres Ensh Cancel Figure 52 ID Browser page of the Analysis Significance Testing and Fold Change Step 8 of 8 workflow before identification Agilent Fiehn Metabolomics Library 109 5 Analyzing your Data compound Identification Wizard Figure 53 Compound Identification Wizard dialog box compound Figure 54 Compound Identification Wizard dialog box method 7 Review and make adjustments to the entity identifications as necessary using the ID Browser interface Figure 55 on page 111 8 Click Save and Return to export your entity list back to your experiment in MPP You are automatically returned to the MPP user interface 9 Review your identified entity list in the ID Browser Identification results The molecular formula now replaces the mass and retention time for identified entities in the compound column Figure 56 on page 112 10 Click Finish when you have completed the ID Browser Identification 110 Agilent Fiehn Metabolomics Library Analyzing your Data 5 The Analysis Significance Testing and Fold Change workflow is now complete and you are immediately returned to the main MPP interface similar to tha
178. r experiment ID Browser automatically begins identifying your entities and shows a progress bar E Steps 1DBrowser Identification To identify the Enties that passed the fold change cut off with IDBrowser click cn the IDBrowser Identification button 2 Esperinerk roupng Identify Entities wth IDBranser _ TOBrowset Tdertfcation 3 Fiter Flags Compound FC qR Sample vs Log FC qe Sampte FC bs qR Sampl_ Regulation qR Sa FC 4C Sample vs Lag FC C Samp FC abs dC Samp Regulation QC Sa 4 FiterBy Frequency 73 0 56 86157 1 00 0 00 1 00 down 401570368 00 28 58 16 09 up 5 QC en samples 83 0 39 020235 305907840 00 28 45 16 00 com 105 0 07 1 05 ur estans anayas 90 58 842386 1 00 0 00 1 00 down 173576380 24 05 16 00 up BB 0635 545956 2385019 75 2119 16 00 up 15405 69 13 51 16 00 ur 7 Fold chan 8B 0 27 293624 241182912 00 27 85 16 00 own 120 026 119 ur 73 0 62 617535 198662 768 00 27 57 16 00 down 130 0 58 130 u 173 0 56 6783 241384 144 00 27 85 16 00 down 149682138 2051 16 00 dom 83 0 27 247214 1447459 52 20 47 16 00 up 973403 13 25 16 00 ur 104 094208005 63318852 00 25 02 16 00 own En 148 2 80 ur 142 0 13 810567 2 04 1 03 2 04 sown 121 027 121 ur 73 0062 535318 2550 42 11 32 16 00 up 22427 24 1445 16 09 dow
179. rameter values are treated as replicate samples To assign replicate samples their parameter values select the samples and click on the Assign Values button and enter the value for the group Set the parameter type to numeric to interpret the parameter values as numbers Parameter name hine Variety Parameter type Non Numeric x Samples Parameter Values A_O1 A Sample A_02 A Sample A_03 A Sample B01 B Sample B_02 B Sample B_03 B Sample c_o C Sample c_02 C Sample c03 C Sample Help ok cancel Figure 33 Add Edit Experiment Parameter dialog box 14 Repeat Add Parameter if your data has more than one independent variable e Click Add Parameter e Repeat the Sample selection and Assign Value steps until all of your samples are assigned a parameter value for the new Parameter name 15 Click the Save experiment parameters to file button Jal to save your experiment parameters and parameter values to a file Saving your experiment parameters to a file saves time when you create multiple experiments 16 Click Next when you have assigned a parameter name type and value to all of your data Agilent Fiehn Metabolomics Library 91 5 92 Analyzing your Data Elns Experiment Creation Wizard Step 6 of 11 xi Experiment Grouping Experiment parameters define the grouping or replicate structure of your experiment Enter experiment parameters by clicking on the Add Parameter button You may enter as ma
180. rate 10 647 RT 10 647 RF 1 000 1200 C12 Methyl Laurate 13 250 RT 13 25 RF 1 000 1400 C14 Methyl Myristate 15 597 RT 15 597 RF 1 000 1600 C16 Methyl Palmitate 17 723 RT 17 723 RF 1 000 1800 C18 Methyl Stearate 19 663 RT 19 663 RF 1 000 2000 C20 Methyl Eicosanoate 21 441 RT 21 441 RF 1 000 xl Figure 102 AMDIS Results dialog Standards tab The RI calib button is disabled The RI Calibration information is only available when an RI Calibration Data file cal has been used in an analysis briefly examined in the next tutorial section Agilent Fiehn Metabolomics Library 167 168 AMDIS Getting Started Now click QA QC to view the QA QC Results report and scroll down to the bottom of the report This report indicates the retention index standards that have been found and those that were missed xi Library Settings Standards QA OC sen Results Performance Defined RI 2200 0 RT observed 23 106 min RT expected 23 08 MF 97 10 STD C24 Methyl Linocerate 24 603 Defined RI 2400 0 RT observed 24 635 min RT expected 24 60 MF 97 11 STD C26 Methyl Hexacosanoate 26 023 Defined RI 2600 0 RT observed 26 061 min RT expected 26 02 MF 96 12 STD C28 Methyl Octacosanoate 27 349 Defined RI 2800 0 RT observed 27 394 min RT expected 27 35 MF 69 Figure 103 AMDIS Results QA QC report Information about the internal standa
181. rches Sciplanner SUBSTANCES SUBSTANCE IDENTIFIER REFERENCES Research Topic SAVED ANSWER SETS Author Name You have no saved answer 328 42 7 sets Company Name Document Identifier Learn how to Create Saved Answer Sets Journal Patent Import Tags Enter one per ine KEEP ME POSTED SUBSTANCES You have no profiles Chemical Structure phen Learn how to Markush Create Keep Me Posted Molecular Formula E Substance Identifier 1 REACTIONS Reaction Structure Preferences sarnder men EEE SciFinder Explore v Saved Searches SciPlanner Save Print Export Substance Identifier 328 42 7 gt substances 1 m Get Get Get Commercial 2 Send to SUBSTANCES B References 4 Reactions amp Sources xK x SciPlanner Gr ee Sort by CASRegsty Number Answers per Page 15 Vew MM MI M E 0of1 Substance Selected Analyze by Substance Role x E 1 Substance Detail Analytical Study 1 328 42 7 Refine by 50 N Biological Study 1 5054 lt References erie sions s Isotope Containing SSS Reactions o Tia Metal Containing Formation II is lt Commercial Sources Commercial Availability Nonpreparative 1 HO2C C CH2 CO2H 2 Regulatory Information Property Availability Miscellaneous 1 4405 gt Property Value Sd Butanedioic acid 2 oxo Reference Availability Beounence 4 en Atom Attachment EEE Experimental Properties Preparation
182. rds Library exist Further the calibration information can only be of any use for compounds in the target library that have RI values stored for them For the purpose of this example suitable files are provided Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Before following the instructions below ensure that AMDIS is in a known state by following the instructions in To put AMDIS into an initialized state on page 116 There should now be an empty Confirm window displayed 1 Click File gt Open and in the Select Data File dialog navigate to the AMDIS32 DATA HP folder select the file Rl Calibration d and click Open 2 Click Analyze gt Analyze GC MS Data and in the Analyze GC MS Data dialog set Type of analysis to Use RI Calibr Data Internal Standard Use Target Library Intern Std Lib and RI Calib Data to select the Fiehn msl FIEHN isl and Fiehn cal files respectively The dialog should now resemble x GC MS Data C 1 DIS324DATANHPSAI CALIBRATION D Type of analysis RSS craic ke Target Library Emsa enms C AMDIS32 LIB Fiehn MSL Intern Std Lib CAAMDISS UIBFichn ISL C AMDIS32 LIB Fiehn ISL RI Calib Data C AMDIS32 LIB Fiehn cal Cancel Settings H Help Figure 105 Analyze GC MS Data dialog Use RI Calibr Data Internal Std 3 Although retention index values are automatically computed in this analysis type you still need to tell AMDIS exac
183. rds that have been found is presented If any of the internal standards have not been found a separate list of those would also be presented The Performance button is described later see Analysis Type Performance Check for RI on page 176 The Settings tab presents important parameter values used for the most recent analysis and the S N tab provides various information relating to the signal to noise analysis performed on the data file It is important to understand that much of the information presented in the AMDIS Results dialog relates to the analysis results currently being examined As such these values are not necessarily those that would be used for a new analysis as analysis settings may have been modified in the Analysis Settings dialog The exception is that the library information is taken from the current state of the library which in general may have been edited since the analysis Click Done to close the dialog 6 Take a quick look at the Internal Standards Library On the Library menu click Build One Library In the Build One Library editor that appears click Files and in the next dialog click Load Library Change Files of type to Internal Std Library isl and navigate to the AMDIS32 LIB folder Finally click FIEHN isl and Open to load the library into the Build One Library editor Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 C AMDIS32 LIB Fiehn ISL Add 95952 min AIGAL
184. riables while the metabolite profile presents a host of small molecule products that make up the dependent variables of a study Having exact and definite limits on an analytical result that provide a conclusive degree of correlation of the subject to the specimen Agilent Fiehn Metabolomics Library Reference Information 8 Element A metabolite that may be individually referred to as a compound molecular feature element or entity during the various steps of the metabolomic data analysis Endogenous Pertaining to cause development or origination from within an organism Entity A metabolite that may be individually referred to as a compound molecular feature element or entity during the various steps of the metabolomic data analysis Entity List The compounds that meet the requirements specified by each experiment performed on your data Entity lists are viewed in the Experiment Navigator Enzyme Proteins acting as biocatalysts in a metabolomic reaction These entities are particularly important in depicting a biochemical network Experiment Data acquired in an attempt to understand causality where tests or analyses are defined and performed on an organism to discover something that is not yet known to demonstrate as proof of something that is known or to find out whether something is effective Externality A quality attribute or state that originates and or is established independently from the specimen under evaluation
185. riment consists of the analysis of a set of replicate samples collected over a range of well defined parameters treatments and or exposures known as independent variables including parameter controls representing minimal or normal perturbations control samples The results from the changes observed in the samples are designed to provide an answer to your hypothesis The hypothesis may be proved or disproved by analyzing the correlation of the independent variables on the resulting expression of a large number of dependent variables the features compounds that are measured in your samples The results must be significant beyond natural variability After you obtain your samples acquire your data and find the features in your sample data MPP takes you through data extraction processing and statistical analysis so that you can prove or disprove your hypothesis The hypothesis The hypothesis is the question that is answered by your analysis For example the question may be a statement that proposes a possible correlation or cause and effect between a set of independent variables and the resulting features in your data Natural variability It is important to understand how any one sample in your data represents the population as a whole Because of natural variability and the uncertainties associated with both the measurement and the population no assurance exists that any single sample from a population represents the mean of the
186. rke82 Burke JJ Siedow JN Moreland DE 1982 Succinate Dehydrogenase A Partial Purification from Mung Bean ocotyls and Soybean Cotyledons Plant Physiol 70 6 1577 1581 PMID 16662722 Chulavatna73 Chulavatnatol M Atkinson DE 1973 Phosphoenolovruvate svnthetase from Escherichia coli Effects of adenvlate enerey wl i m gt Figure 127 MetaCyc also lists references to activation or inhibition of enzymes 198 Agilent Fiehn Metabolomics Library Using CAS and PubChem Numbers 7 ChemSpider Database 1 To access this database enter http www chemspider com into your internet browser 2 Click on Search under the ChemSpider logo to display the search box 3 Enter the CAS number 328 42 7 into the search field ChemSpider RSC About More Searches Web APIs Help Simple search Structure search Advanced search 328 42 7 Systematic names Synonyms Trade Registry SMILES InChi names numbers 1 2 AIBN Aspirin 7732 18 5 O C OCC InChl 1 CH4 h1H4 dihydroxybenzene c What is ChemSpider Search by chemical names Search by chemical structure Find important data ChemSpider is a free chemical systematic names Create structure based Literature references structure database providing Synonyms queries Physical properties fast text and structure search Trade names Draw structures inthe web Interactive spectra access to over 28 milion Database identifiers page Chemical suppliers Use structure
187. rmalization Criteria page Step 10 of 11 of the MS Experiment Creation Wizard Step 11 of 11 Baselining Options 1 Select the baselining Option e Select None if only a few features in the samples exist e Select Z Transform if the data sets are very dense i e with data where very few instances of compounds are absent from any sample such as a quantitation data set from recursion e Select Baseline to of all samples to reduce the effect of very abundant and very weak compound features on later statistical analyses The abundance for each compound is normalized to its selected statistical abundance across all of the samples Agilent Fiehn Metabolomics Library 97 5 Analyzing your Data e Select Baseline to ___ of control samples to weight the compound features to a known value that is considered to be normal in the population while reducing the effect of large and small compound features The abundance for each compound is normalized to its selected statistical abundance across just the samples selected as the control samples When you use this baselining option you must select the samples that are the control samples from the table 2 Click Finish x Baselining Options There are Four baseline options None This option will treat compounds with large intensities as more significant than compounds with lesser intensities Z Transform This option should be used when comparing data from different sources Baselin
188. s 6 894 800 0 C8 3 720 1000 0 C10 12 281 1200 0 C12 14 590 1400 0 C14 16 684 1600 0 C16 18 596 1800 0 C18 20 352 2000 0 C20 21 972 2200 0 The results of the updated RI Calibration Data file are shown Examine the results to determine if all 12 FAME compounds were detected and show the new RTs 11 Click Done then exit AMDIS It is important to use the appropriate RI calibration file that corresponds to the FAMEs markers included in the analytical method If multiple calibration files are maintained it is critical to use the correct cal file Agilent Fiehn Metabolomics Library 41 Experimental and Instrument Method Quality Control Tune the MSD daily Tune the mass spectrometer daily before starting an analysis Follow the procedures in the Agilent user manual Perfluorotributylamine PFTBA is the tune compound lon source cleanliness The repeller values and the m z 502 abundance must be checked to ensure that the ion source is clean Air and water limits It is recommend that air m z 28 and water m z 18 abundances be below 5 of base peak base peak m z 69 Derivatization reagent blank Each analysis sequence must be preceded by a derivatization reagent method blank to check for reaction products Reaction products found are caused by equipment contamination or impurities in the reagents This test confirms the purity and conformity of reagents as supplied by the chemical vendors Metabo
189. s The samples are presented by grouping and the current Principal Component Analysis PCA PCA calculates all the possible principal components and visually represents them in a 3D scatter plot The scores shown by the axes scales are used Agilent Fiehn Metabolomics Library 99 5 100 Analyzing your Data to check data quality The scatter plot shows one point per sample colored coded by the experiment grouping Replicates within a group should cluster together and be separated from samples in other groups Step 6 Significance Analysis The entities are filtered based on their p values calculated from a statistical analysis The statistical analysis performed depends on the samples and experiment grouping Step 7 Fold Change Compounds are further filtered based on their abundance ratios or differences between a treatment and a control that are greater than a specified cut off or threshold value Step 8 ID Browser Identification You have the option to import your final entity list directly into ID Browser for identification Flow Chart of the Analysis Significance Testing and Fold Change Wizard Filter by Frequency Fold Change Skip Step 8 for identified lt a experiment Step 2 l Step 8 Experiment Quality Control on ID Browser I 1 Grouping Samples Identification I Step 6 a Significance Save your project and Analysis perform advanced analysis operations from the Workflow Browser Goto Step7 J Figur
190. s 0A 0C sn Beate Batanane ___ RI Height Width Taing Match on Methyl caprate 10 ee 10 641 1000 0 439 3 6 1 00 C12 Methyl Laurate 13 250 J1 13 245 1200 0 459 3 8 1 00 C14 Methyl Myristate 15 597 1I 15 598 1400 0 497 3 8 0 90 C16 Methyl Palmitate 17 723 J1 17 730 1600 0 513 3 8 0 90 13 06 Apr 24 2008 13 06 Apr 24 2008 13 06 Apr 24 2008 13 06 Apr 24 2008 vl File Figure 112 AMDIS Results dialog Performance Check This example has only one set of performance data recorded As this analysis is repeated over time the data build up until many more lines of data are acquired for each compound By observing the reported RT RI Height Width Tailing and Match data you can spot a gradual change over time or a sudden larger change of one or more of these values Click Done to exit 7 Print or save the results On the File menu click Print Spectra to invoke the Print Spectra dialog Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Print Spectra x IV lon chromatogram IV Profile VW Scan IV Extracted spectrum IV Library spectrum 7 Print all targets 17 Print only best hits Cancel Help Figure 113 Print Spectra dialog The settings allow you some control over the graphical items that are printed and are fully described by clicking on Help Experiment if you wish by using Print but finally return to the Confirm window 8 On
191. s Library 123 6 124 AMDIS Getting Started Mass Spectral Display Changing the display range The right hand section provides various details about the component as determined during the deconvolution process You can click an RT value and all areas of the whole display changes to reflect the chosen component You can click a value in either upper section and all areas of the display change to reflect the chosen retention time or hit The Mass Spectral Display area changes according to whether the currently selected compound is being displayed as a target T or as a component V The X axis shows m z values Mass spectral peaks are displayed rounded to integer m z For a component there is one Mass Spectral Display showing the raw original spectrum overlaid with the extracted spectrum resulting from the deconvolution process Ions from the raw spectrum are shown in black and those from the extracted spectrum in white Note that for clarity they are slightly offset from each other along the x axis The Y axis is a relative abundance percentage scale with the absolute abundance value representing 100 given at the top left of the display for example 195 in Figure 65 For a target there are two Mass Spectral Displays The upper display shows the same information as just described for a component The lower display is similar but shows a library hit black ions overlaid with the extracted spectrum white ions Again
192. s and normalized abundance values on the y axis is displayed If the number of samples is more than 30 the data is represented by a spreadsheet view instead of a profile plot Step 2 Experiment Grouping Independent variables and the attribute values of the independent variables must be specified to define grouping of the samples An independent variable is referred to as a parameter name The attribute values within an independent variable are referred to as parameter values Samples with the same parameter values within a parameter name are treated as replicates Step 3 Filter Flags The compounds created during the experiment creation are now referred to as entities The entities are filtered removed from further analysis based on their presence across samples and parameter values now referred to as a condition It is recommended to process your data through at least through this step The Filter Flags step is used to require that an entity must be present in at least two samples in your data This requirement removes entities referred to as one hit wonders A one hit wonder is an entity that appears in only one sample is absent from the replicate samples and does not provide any utility for statistical analysis Step 4 Filter by Frequency Entities are further filtered based on their frequency of presence in specified samples and conditions This filter removes irreproducible entities Step 5 Quality Control on Sample
193. s is the second reason why more than one peak can be detected per metabolite in many instances of the metabolite library The examples below illustrate step by step how derivatization leads to modifications of the molecular structure and hence to improved stability for GC MS screening Derivatization of oxaloacetic acid Oxaloacetic acid is a dicarboxylic acid member of the citric acid cycle TCA or Krebs cycle with an alpha carbonyl keto group The methoxyamination reaction step replaces the oxygen atom of the carbonyl group by methoxyamine N OCH3 The second derivatization step silylation using N methyl N trimethylsilylation MSTFA introduces trimethylsilyl groups to the two carboxyl groups replacing both acidic hydrogens as shown in Figure 2 The reactions have to be carried out with polar aprotic basic solvents Pyridine is normally used as the solvent to capture protons and increase the nucleophilicity of methoxyamine The use of dimethyl formamide as the solvent has also been reported Agents other than MSTFA can be used for trimethylsilylation such as bis trimethylsilyDtrifluoroacetamide BSTFA or variants that include trimethylchlorosilane as a further catalyst Agilent Fiehn Metabolomics Library Sample Preparation and Derivatization 2 Step I Methoxyamination to protect carbonyl groups OH LO OH OH no H N HO No oo Oo 0 O N O N N and pa o oO F F l oor FOOT si Si OH o oO HO x e Ss a A i i
194. s type continued Analysis type Description Use RI Calibr Data Internal Std Performance Check for RI Internal standards are co injected with the sample but target matching is determined as for the Use Retention Index Data type and does not take any account of the internal standard retention times The internal standards are simply used for reporting purposes and permit you to check that the acquisition system is functioning correctly A clean mixture of known composition is acquired and the data for performance check compounds are recorded and reported so that you can determine how well the acquisition system is performing Agilent Fiehn Metabolomics Library 129 6 AMDIS Getting Started Tutorials Overview AMDIS can run seven different types of analysis and includes a tutorial to demonstrate of each of these analyses Each tutorial describes any prerequisites the operational flow and some post analysis options relevant to the particular analysis type Each tutorial uses demo data files and mainly uses default settings of AMDIS parameters Throughout the tutorials related topic are occasionally briefly introduced Although each tutorial section is self contained it is recommended that you initially go through them in order because they do to a certain extent lead from one to the other If later you want to simply refresh your memory on one section go to it directly A summary of the seven different typ
195. t All Unselect All Help lt lt Back Next gt gt Einish Cancel Figure 30 Sample Reordering page Step 5 of 11 of the MS Experiment Creation Wizard Step 6 of 11 Experiment Grouping 1 Click Add Parameter You can click the Load experiment parameters from file button gt to apply a previously saved experiment grouping T If you use a previously saved experiment grouping you can skip the remaining steps and click Next 2 Type a name for your Parameter name in the Add Edit Experiment Parameter dialog box An independent variable is an essential element constituent attribute or quality in a data set that is deliberately controlled in your experiment An independent variable is referred to as a parameter and is assigned a parameter name The attribute values within an independent variable are referred to as parameter values Samples with the same parameter value are treated as replicates 3 Select the Parameter type for your grouping e Select Non Numeric if the grouping is not a quantitative value e Select Numeric if the grouping value is quantitative or a value that reflects a degree of proportionality among the samples with respect to an independent variable A numeric parameter type allows some data plots in MPP to be scaled by the parameter values Agilent Fiehn Metabolomics Library 89 5 90 Analyzing your Data 4 Click your replicate Samples that share the same first parameter value in your data A se
196. t from this mode 5 Right click in any unused area in the Windows task bar and click Undo Tile To put AMDIS into an initialized state To ensure that the examples in this chapter can be easily followed AMDIS must be in an initialized state state following installation 1 Close the AMDIS program 2 Delete the onsite ini file located in the AMDIS32 folder 3 Run AMDIS and select Agilent Files in the Set Default Instrument dialog Figure 61 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Set Default Instrument Please select default format of your GC MS data Agilent MS Engine Files Bruker Files Finnigan GCO Files Finnigan INCOS Files Finnigan ITDS Files INFICON Files Me E You can also change this later in the Settings dialog OK Details gt gt Figure 61 Set Default Instrument At this point all of the AMDIS parameters are set at default values If result files already exist for the tutorial data files the results you see can differ slightly from the examples To start in a clean state do the next steps 4 When you are told to open a file click File gt Open and select any other file Click Open The Delete Result Files dialog appears Figure 62 Delete Result Files for RI CALIBRATION D x AMDIS generates two files containing results for each analysis of a GC MS data file Would you like to delete these files now Select Keep if you are searching NIST
197. t of information stored for an entry Click Cancel to exit from the dialog and leave the values unchanged Spectrum Editor Calibration Standards Library Name a 0 Methyl caprate 10 647 Chemical ID 110423 Formula C11H2202 AT 10 547 RI frooo Ref lon 74 Real conc fi 0 RF fi 000 Comments i O00 Marker 1056 RT 10 647 Mw 186 16 Q Mz Abundance Replace Add Delete C10 Methyl caprate 10 647 Figure 90 Spectrum editor Agilent Fiehn Metabolomics Library 155 6 156 AMDIS Getting Started Analysis Type Use Retention Index Data If you have retention index RI information stored in a Target Compounds Library an RI Calibration Data file can be used as an additional quality check on the results determined by the standard AMDIS spectral comparison process A Target Compounds Library has a msl file extension and an RI Calibration Data file has a cal file extension The RI Calibration Data file is created as you just saw using the RI Calibration Performance analysis type see Analysis Type RI Calibration Performance on page 148 In the Use Retention Index Data analysis type the RI Calibration Data file is acting as an external calibration file In practice you only need to create a new one of these when the chromatographic conditions you are using have changed significantly such that the correlation between retention time and retention index in the calibration file is no longer accurate
198. t shown in Figure 57 on page 112 Elasitent Massttunter 1D Browser 6 05 00 EE Ele Edt view Identification Method Configuration Help 397 Run wird lu 4 8 me Save and Return Spectral Difference Results Cpd 34 931 naphthalene 8 87 C10H8 39385 x RMS Peaks One Compound Spectrum 39 385 min x ive 2ziQk we mz Abund Abund Nom z Sat Species taz 102 Cpa 34 1931 naphthalene 8 87 C10H8 39 385 Compound Spectrum 33385 min a a E E67 T 7 3 T E 33 T a 3 T 70 azo 100 130 Fa 7 T z 2 T E 123 T E T 09 EG T 39 50 630 770 mo 1020 n30 ToT EEA 7 m 67 33 T 13 73 T m T T 931 naphthalene 887 C10H8 Scan Fiehn L TA 3 T 2 q T 15 5 T 12 72 T 127 EE T 12 ES T D 0 7 60 D i En 1 Counts vs Massto Charge m z i all MS Spectum Resuits _Spechal Diference Resuis Cpd 34 931 naphthalene 87 CIOHB 39 385 mo Compound List x pd Y RT 7 Label Name Fomda Y Score v Mase v Masp _ Avg Mara 2 3562 Cpd2 118407 4 acelybutyie acid 1 10 _ 18407 cet ceH1003 5276 68 a E 3778 _Cpd 65 643001 methyi pamaoleate 17 1643801 methi C1743202 5775 a 7a 3205 _Cpd 70 643001 meihpaim oleste 17_ 1843801 methyl C17H3202 Er m Ej 3534 Cpd 28 936 ricotinamde 1 T1
199. ta file and adjustment is made to the target s match value according to how good the fit is If you are not using RI information the target match value is not adjusted and the RI information is simply used in reporting the deviation between computed and library RI values Finally any performance check compounds that have been identified have their data added to the Performance Log file This file can be inspected at any time and by examining the details of the information it is possible to detect any gradual or sudden deterioration in the acquisition system that might indicate the need for remedial action or in some cases simply the creation of a new RI Calibration Data file It is a prerequisite of this analysis type that a Calibration amp Standards Library and an RI Calibration Data file exist Further the Calibration amp Standards Library should have at least one compound identified as a performance check compound For the purpose of this example suitable files are provided Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Before following the instructions below ensure that AMDIS is in a known state by following the instructions in To put AMDIS into an initialized state on page 116 There should now be an empty Confirm window displayed Since this tutorial illustrates the Performance Log it would also be beneficial to start with that in a known state The Performance Log is actually a collection of 3 files
200. tabolomics Reporting MSI compliant studies Plant Journal 2008 53 691 704 Peak abundance information are not included in the peak names A library user might be interested in a different intensity ratio for a metabolite s derivatives than was detected when establishing the library 50 Agilent Fiehn Metabolomics Library Peak Identification 4 Make sure you establish constant peak ratios between metabolite derivatives when using their GC MS profiles for quantitative purposes for their particular biological samples In many cases the monitoring of both high and low abundance derivatives is done to watch for a peak ratio change over the course of an analytical sequence Usually only the major peaks are used for statistical assessments and biological interpretations When these metabolite derivative s peak ratios change across samples of a specific biological study serious concerns arise over the validity of quantitative results After determining the cause of the derivative ratio changes the analysis must be repeated Agilent Fiehn Metabolomics Library 51 4 Peak Identification 52 Agilent Fiehn Metabolomics Library Agilent G1676AA Agilent Fiehn GC MS Metabolomics RTL Library User Guide 5 Analyzing your Data Using Agilent GC MS ChemStation 54 Using AMDIS 59 Using Agilent MassHunter Qualitative Analysis 63 Using Agilent MassHunter Mass Profiler Professional 75 Er Agilent Technologies 53 5 Analyzing your Data
201. tal and Instrument Method 3 Table 1 FAME markers continued Name Concentration RT min Methyl eicosanoate C39 50 pg mL 21 441 Methyl docosanoate Cy 50 pg mL 23 082 Methyl linocerate CH 50 pg mL 24 603 Methyl hexacosanoate Cy 50 pg mL 26 023 Methyl octacosanoate Cy 50 pg mL 27 349 Methyl triacontanoate Cap 50 pg mL 28 723 Derivatization Key points to consider e Thoroughly dry metabolite samples before derivation Reagents are not compatible with water or protic solvents e Use enough reagent to completely derivatize all metabolites e Derivatized samples have a 24 hour shelf life Before doing a large study conduct a test to determine the maximum sample size that is completely derivatized with the recommended protocol Preparing the biological extract An aliquot of 5 uL of myristic acid d27 stock solution is added to the biological extracts The sample is then evaporated to dryness and 2 uL of the FAME RI marker solution is added to the dried extracts Methoxyamination Add 10 uL of a 40 mg mL solution of methoxyamine hydrochloride Product 67546 Sigma Aldrich St Louis MO in pyridine Product TS 27530 Thermo Rockford IL This mixture is gently shaken at 30 C for 90 minutes Agilent Fiehn Metabolomics Library 33 3 34 Experimental and Instrument Method Trimethylsilylation Add 90 uL of N Methyl N trimethylsilyltrifluoroacetamide with 1 Trimethylchlorosilane MSTFA 1 TMCS Product
202. they are slightly offset for visual clarity Since library spectra are only stored with relative ion abundances no absolute abundance value representing 100 is given at the top left of this display For full details of the Mass Spectral Display area see AMDIS online Help Often the Chromatogram Display is very crowded with target and component symbols overlapping To see the detail of the chromatogram s and to easily choose by clicking it a specific target or component symbol it is necessary to first zoom magnify the display Similarly you can zoom the Mass Spectral Display to see greater detail By using the click drag release technique the display can be zoomed individually in either the X direction or the Y direction or in both directions simultaneously Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 Click drag release is as follows First click and hold the left mouse button at one end of the desired linear range or one corner of the desired rectangular area Now drag the mouse pointer to the opposite end or corner of the desired selection Finally release the mouse button To zoom in the X direction do a click drag release operation just below the X axis When you release the mouse button the selected area is redrawn to fill the whole width of the display area To zoom in the Y direction do a click drag release operation just to the left of the Y axis When you release the mouse button the selected
203. tly how to use them Click Settings and in the Analysis Settings dialog click Identif Now set Minimum match factor to 65 We are now ready to perform the analysis 4 Click Save to exit the Analysis Settings dialog and return to the Analyze GC MS Data dialog Click Run to start the analysis Within a few seconds the results are displayed in the usual format Set the Information Lists area to view only the best hits of the targets and then examine RI RI lib values for the found targets Agilent Fiehn Metabolomics Library 171 172 AMDIS Getting Started If the RI RI lib label and value are absent the library entry does not have an RI value specified If you check the value for the Methyl Palmitate internal standard you can see that it is no longer exactly 0 and so is unlike the previous Use Internal Standards for RI analysis method where it was exactly 0 This time the internal standards are being treated more or less the same as normal targets and in this case are subject to the normal RI computation from the RI Calibration Data file and RI adjustments A discussion on this in more detail follows but first click Info to display the AMDIS Results dialog and then click Standards to display RI calib data This is a list of all compounds in the RI Calibration Data file and shows their stored RT RI and Names information AMDIS Results RI CALIBRATION D d xj Library Settings Standards gavac sn Al calib C AMDIS
204. ualitative Analysis software Then you can use the Agilent Mass Profiler Professional program with results from either AMDIS or Agilent MassHunter Qualitative Analysis software The user is shown how to use the library set up the GC MS system for retention time repeatability and run metabolite Agilent Fiehn Metabolomics Library 11 1 Introduction identification reports using these programs This user guide is installed in the Program Files x86 Agilent Fiehn GEMS Metabolomics RTL Database App Notes directory on the application CD AMDIS program The AMDIS program is installed in the Program Files x86 AMDIS32 directory unless you change the default directory during the installation procedure Agilent Fiehn Library metabolite list A listing of the metabolites contained in the library files is included on the CD application disk in the Program Files x86 Agilent Fiehn GCMS Metabolomics RTL Database App Notes directory GC MS ChemStation files The library locates the following GC MS ChemStation method file in the MSDCHEM 1 Methods directory Fiehn m ChemStation RTL Chromatographic Method The library locates the following GC MS ChemStation files in the Database directory Fiehn l ChemStation PBM Library Fiehn scd ChemStation screener file 12 Agilent Fiehn Metabolomics Library Introduction 1 To use this library with the MassHunter Qualitative Analysis software see Install the Fiehn library to use with M
205. uch of the information presented in the AMDIS Results dialog relates to the analysis results currently being examined As such these values are not necessarily those that would be used for a new analysis as analysis settings may have been modified in the Analysis Settings dialog The exception is that the library information is taken from the current state of the library which in general may have been edited since the analysis 5 Examine how the RI Calibration Data files RT and RI information are used Click Done to exit from the AMDIS Results dialog and then select Palmitic acid in the undocked Information Lists area the results look similar to Agilent Fiehn Metabolomics Library 173 174 AMDIS Getting Started C AMDIS32 DATA HP RI CALIBRATION D DATAME SE Figure 108 Results for Palmitic acid The RT of palmitic acid is 18 9013 and so the RI Calibration Data file is examined for the closest RT value below this and the closest above in this case 17 730 and 19 672 see Figure 106 AMDIS Results dialog Standards tab RI calib on page 172 These two values and their cor responding RI values 1600 and 1800 are used to predict the RI of pal mitic acid by simple interpolation yielding RI 1721 48 The difference Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 between the computed RI value for Palmitic acid and its value in the Target Compounds Library 1718 38 is presented as RI RI lib in the M
206. ur metabolomics data through the use of sequential dialog boxes and wizards The sequential tasks performed using MPP are shown in Figure 20 on page 76 Metabolic Profiling Workflow Prepare for an Import and Organize Data Experiment Create an Initial Analysis Identify Features Experiment Design Find Features amp Data Acquisition Advanced Operations as Compounds Spectral Features Statistical Data Analysis Identification Experiment Design Hypothesis Natural Variability Replicate Sampling System Suitability Sampling Methodology Statistical Analyses Interpretations Pathways Filtering Class Prediction Additional features Sample Preparation MassHunter M ass Profiler MassHunter GC MS Qualitative Analysis m gt eoms aha Professional ID Browser Figure 19 The steps involved in a metabolic profiling experiment using Mass Profiler Professional Setupa Do Significance project and an Testing and experiment Fold Change Y Import data files into the experiment Order and Save your group the project and data files experiment s Filter align and normalize Export your the sample project data Figure 20 Overview of the wizards that help you use MPP 76 Agilent Fiehn Metabolomics Library Analyzing your Data 5 Elements to consider in planning your experiment This section helps you understand an experiment and steps you can take to improve your results before analyzing your data with MPP An expe
207. value specified Methyl Palmitate found at 17 7296 minutes has a value of 0 and is a perfect match Agilent Fiehn Metabolomics Library 165 6 AMDIS Getting Started C AMDIS32 DATA HP RI CALIBRATIONDIDATA MSAN Figure 100 5 Examine the QA QC report that was mentioned earlier and review the AMDIS Results dialog Click Info found near the top left of the Confirm window to display the AMDIS Results dialog 166 Agilent Fiehn Metabolomics Library AMDIS Getting Started 6 AMDIS Results RI CALIBRATION D xj Library Settings Standards QA QC s n 1054 spectra in C AMDIS32 LIB Fiehn MSL View 243 benzoic acid 9 594 Formula C7H602 RI 924 69 Class Figure 101 AMDIS Results dialog Library tab When it appears the dialog presents the Library tab and shows information from the Target Compounds Library for the currently selected target Benzoic Acid in our example Note the textual header giving the name of the Target Compounds Library and saying how many spectra there are in it Click Standards to display a tab listing pertinent non spectral information about all of the internal standards in the Internal Standards Library AMDIS Results RI CALIBRATION D x Library Settings Standards aavac sn Al cali 1S C AMDIS32 LIB Fiehn ISL RI Names C8 Methyl Caprylate 7 812 RT 7 812 RF 1 000 900 C9 Methyl Pelargonate 9 248 RT 9 248 RF 1 000 1000 C10 Methyl cap
208. with an Accurate Mass Q TOF LC MS Agilent publication 5990 4404EN October 20 2009 Metabolite Identification in Blood Plasma Using GC MS and the Agilent Fiehn GC MS Metabolomics RTL Library Agilent publication 5990 3638EN April 1 2009 Metabolomic Profiling of Bacterial Leaf Blight in Rice Agilent publication 5989 6234EN February 14 2007 Advances in Instrumentation and Software for Metabolomics Research Agilent publication n a September 18 2012 Multi omics Analysis Software for Targeted Identification of Key Biological Pathways Agilent publication n a May 3 2012 Metabolomics LCMS Approach to Identifying Red Wines according to their variety and Investigating Malaria infected red blood cells Agilent publication n a November 3 2010 Small Molecule Metabolomics Agilent publication n a November 3 2010 Presentation Metabolome Analysis from Sample Prep through Data Analysis Agilent publication n a November 3 2010 Emerging Insights Agilent Solutions for Metabolomics Agilent publication 5990 6048EN April 30 2012 Agilent Mass Profiler Professional Software Discover the Difference in your Data Agilent publication 5990 4164EN April 27 2012 Pathways to Insight Integrated Biology at Agilent Agilent publication 5991 0222EN March 30 2012 Confidently Better Bioinformatics Solutions Agilent publication 5990 9905EN February 2 2012 Integrated Biology from Agilent The Future is Emerging Agilent
209. y csl and navigate to the AMDIS32 LIB folder Finally click Fiehn csl and Open to load the library into the Build One Library editor Select Sort by RI and examine the full list of compounds by scrolling C AMDIS32 DATA HP RI CALIBRATION D DATAD C8 Methyl Caprylate 7 812 C9 Methyl Pelargonate 9 248 C10 Methyl caprate 10 647 C12 Methyl Laurate 13 250 C14 Methyl Myristate 15 597 C16 Methyl Palmitate 17 723 C18 Methyl Stearate 19 663 C20 Methyl Eicosanoate 21 441 C22 Methyl Docosanoate 23 082 C24 Methyl Linocerate 24 603 C26 Methyl Hexacosanoate 26 023 C28 Methyl Octacosanoate 27 349 RETENTION n a uncertain pks 0 0 reverse logic 1 0 few peaks 0 0 purity 1 0 high threshold 0 0 scaling 0 0 adjacent peaks 0 0 flagged peaks 0 0 m z 74 S N m z 74 248 8 Area m z 74 35 590 z RT RT lib 0 008 z Figure 111 Calibration amp Standards Library Performance Check The compound entries that are flagged with cp or p are the performance check compounds and in this case you can see that there are a total of 14 Click Exit to leave the dialog Agilent Fiehn Metabolomics Library 179 180 AMDIS Getting Started 6 Click Info to display the AMDIS Results dialog and then click QA QC followed by Performance to display data for the performance check compounds that have been found AMDIS Results RI CALIBRATION D x Library Settings Standard
210. y 2013 G1676 90001 RE Agilent Technologies
211. ydes are protected by derivatization to methoxyamino groups methoxyamination Two reasons underscore the rationale behind this derivatization For one alpha keto acids tend to undergo chemical loss of carboxyl groups as carbon dioxide if the keto group is left unprotected Since many metabolites comprise alpha keto acid groups such as 2 oxoglutarate and pyruvate derivatization is a precautionary step for quantitative metabolite profiling More importantly many carbohydrates are present in cyclic and in open Agilent Fiehn Metabolomics Library 23 2 24 Sample Preparation and Derivatization chain linear form using the keto or aldehyde group as a center for forming hemiketals or hemiacetals with the carbohydrate hydroxyl groups The anomeric hydroxyl groups can then be present in alpha or beta position Each of the various forms would lead to different peaks in gas chromatography However without protection of the keto or aldehyde groups the ratio of the different peaks cannot be controlled making quantifications extremely challenging Cyclizations are inhibited when the carbonyl groups are methoximated leading to two distinct peaks in GC MS in most instances The two peaks are the syn and the anti form of the methoxyamine group due to the inhibition of rotation across the carbon nitrogen double bond The ratio of syn and anti form is stable for each metabolite and is only dependent on the internal energy of the molecule Thi
212. your samples by the abundance value that represents the entered percentile The abundance for the percentile entered is subtracted from the abundance of each entity The Percentile Shift value can be between 0 and 100 A value of 50 represents the median abundance Agilent Fiehn Metabolomics Library Analyzing your Data 5 e Quantile normalization is a method of normalization that makes the distribution of abundance values of all samples in an experiment identical After normalization all statistical parameters for each sample i e mean median and percentile are identical Quantile normalization reduces variance between samples e None does not perform any normalization The abundance values are transformed to a logs scale 2 Mark Use External Scalar in the External Scalar tab If you use an external scalar enter the value to scale each sample file in the Scale to Value column The Normalization options can be applied alone or in conjunction with External Scalar When both are selected then External Scalar is applied first followed by the chosen Normalization option 3 Click Next EIMS Experiment Creation Wizard Step 10 of 11 E xj Normalization Criteria The compounds associated with each sample may be normalized to an internal standard percentile shift quantile and or an external scalar Normalization External Scalar Normalization Algorithm None v lt lt Back a Enish Cancel Figure 39 No

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