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1. 82 2 10 Giving Compounds additional names e eee eee eese etes nette esee een netten sets eto sesta set en sees seta 82 3 Browsing and opening from SBase 3 1 Opening multiple spectra 4 eere sees eren ee eren eerte neenon senno ta sets tona setas eoep Sasss se p Svoren sten set titros 86 3 2 Removing rename and editing Spectral Base entries eere eee eee reser eese e eene n neenon seen 88 4 Knowledge base 4 1 Creating a Knowledge Base eee eee eee ee eee ee ee eene eene etta netta stone setas setas seta sees setas estos oeno sae 89 4 2 Adding compounds to Knowledge Base manually 4 eeeeeeee eee e eerte ee ettet eene enne enses seen 90 4 3 Reference COMPOUNA Mn 92 4 4 Autofilling the Knowledge Base e sesssesseosseossoossoesoossoossosssosssossssessesssesssossoossoossoossosssosssosssesssesssesseess 93 4 5 Viewing and editing your Knowledge Base eee eee eese etes ee eee ee enne eene ta soto sesto sesta seen seen naso 93 65 5 File structure and acquiring spectral data online XM IF m IOA D R E E M 95 5 2 Downloading raw spectral data sessseesoossoossoossosssosssosssesssesssessocsseossocssossoossoossosesosssoesssessesssesssessoosso 96 6 Using Amix to analyze new NMR spectra 6 1 Placement of the file and setting of Amix cess
2. Select up to 3 files from list 3 files hold erae for multiple selection ft for area selection c 8 salar ref sucrose ldnosey lr cpr 6 5 salar ref sucrose 2dhsqc rr cpr 6 8 salar ref sucrose tocsy rr cpr OK AutoSelect fT 99 RAA Unselect EX E Cancel Screenshot 23 The search results for compound name sucrose with no experiment type given at the bottom of the window To search for Keys check the evaluate keys box and confirm This will lead to 84 a window giving several options Screenshot 24 You can choose not to search by Key by checking the Do not use box You can choose your search Key from a list of all defined Keys by checking the Use existing value or you can use a manual input key by checking the Evaluate range box It is recommended to use the existing Keys ET 7 Fm A a OQ Qf 2283 x R rx A z m se SSR AI un if possible this will AAA D ae il ET allow you to select a Key from the drop down list below Once you have confirmed porem xPgcns Amix will generate a KEY amino acid do not use feno list of all the spectra GEO labeled with this Key Selecting spectra from OK Cancel the list generated functions like selecting spectra from the lists explained above If you manually input the Key using Screenshot 24 The search by
3. T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T 8 0 75 7 0 65 6 0 55 5 0 45 40 35 3 0 25 2 0 15 1 0 0 5 0 0 5 Chemical Shift ppm Figure 13 The NMR spectra of dataset S4 with TO and T5 overlaid on the same spectra TO is shown in blue T5 in red 35 5 4 1 Nucleotides Figures below show the change in order with TO on the bottom selected peaks relating to nucleotides Spectra are overlaid in ascending 80 T0 T5 esp 020 45070 r5 esp 0 15 0 10 4 z ni inosine Inosine amp 0 10 i f 0 05 4 J x Po T 0 05 4 7 N J A E i i NN m PO FA H Pj s J E aa a N z a ee Bod P i 1 5 oh E 2 Koc TN 3 7 uu m N md N 0 054 0 054 zt we E 4 p m 7 0 104 B 23 z 7 3 D E i N a J bia N E yf ES 0 104 3 ais i f a x 1 pas Mi pit NU 3 7 x 7 i V z 3 8205 3220 8216 83 8 350 8 345 8 340 83 8 330 8 325 Chemical Shift ppm Figure 14 The change of Inosine and IMP peaks at 8 23 and 8 22 ppm respectively for dataset SO 5070 T5 esp Normalized Intensity 0 08 4 T T T T TT T T T T T T T T T T 8 560 8 555 8 550 8 545 8 540 8 535 Chemical Shift ppm Figure 16 Change of AMP peak at 8 56 ppm for dataset SO Chemical Shift ppm Figure 15 The change of inosine peak
4. knovlegdge base C data sichacl eax 5 salar KB HICI3 txt Cancel lt Back Next gt containing the Knowledge Base by specifying the file path of the text file or by using the browse function with the indicated arrow on the right side of the text box Screenshot 51 The following window Screenshot 52 requires the specification of the Sbase to be used and what type of spectra to be analyzed Check Preform identification to specify the operation to be done select the correct Screenshot 51 The window of the analysis in which you specify the Knowledge Base to be used is possible to use other 2D spectra Sbase if needed if there only is one Sbase this is not an option Check only the 1D box under the Use which data for identification fields It In the following window Screenshot 53 specify that you wish to use Positional matches for identification This will use this peak range for each compound in the Knowledge Base and compare them to the peaks in the new spectra Continue to the next window and specify that you wish to use Fully automated noise handling for the data of the A standard Perform identification c S salar 2o ms in mixures e g metabolites in body fluids e data If identification is wanted reference in an AMIX spectra base must be provided tained from Bruker Use which data for identification v 41
5. 5 TEn 0 0154 T a iic eas L 0 025 4 0 030 4 0 0384 0043 x 0 045 3 ir wq UN ep p T T T T TOUT T T TS rr E T E 2910 290 2 900 895 2 890 2 885 2 880 2875 2 870 2 865 3 245 Chemical Shift ppm Chemical Shift ppm Figure 24 Change of TMA levels dataset S0 peak at Figure 25 Change of TMAO levels dataset SO peak at 3 26 2 89 ppm ppm 5410 15 esp 10 48410 t5 esp 084 4 3 oo 3 074 4 3 os 3 9571 073 os 4 os 4 o44 os 4 13 044 033 E TMAO j 034 7 024 3 j 024 g g E 1j 4 bd a H 0 1 3 014 8 PUN H E 4 St gil mie go go a me S d j E 014 5 04 3 1 7 4 24 i 921 73 E 4 024 3 034 3 l a 3 i3 k 04 a 0 44 osd A add as P 3 1 M 4 SK 4 3 di 074 E E 0 9 3 N 084 4 ees 4 104 TTTUTUUTPUTTERTTUT ETT RU ETT ETT UT TUE TRE NOAA RADA RTT TU TUTTI RU RTT TTE PUTET yTUT 3 i i a 2 925 2 920 2 915 2 910 2 905 2 900 2 895 2 890 2 885 2 880 2 875 2 870 2 865 2 860 2 3 270 3 250 3245 Chemical Shift ppm Figure 27 Change of TMAO levels dataset S4 peak at 3 26 ppm 39 T Figure 28 The T5 spectra of SO and S4 overlaid with SO on the bottom blue and S4 on top red Shows the final difference of TMA peak at 2 89 ppm pe 1889 2 888 2 887 2 886 2 885 2 884 2 883 2 882 2 881 Chemical Shift ppm Figure 29 On the left T5 spectra of SO and S4 overlaid with SO at the bottom
6. hmp metabolites that would be regarded as either abundant gt 1 uM or relatively rare lt 1 nM Additionally 5 688 protein and DNA sequences are linked to these metabolite entries Each MetaboCard entry contains ktil The Human Metabolome Database HMDB is a freely available electronic database containing detailed information about small molecule metabolites found in the human body It is intended to be used for applications in metabolomics clinical chemistry biomarker discovery and general education The database is designed to contain or link three kinds of data 1 chemical data 2 clinical data and 3 molecular biology biochemistry data The database version 3 6 contains 41 815 metabolite entries including both water soluble and lipid soluble metabolites as well as e than 110 data fields with 2 3 of the information being devoted to chemical clinical data and the other devoted to enzymatic or bi JetaCy emical data Many data fields are hyperlinked to other databases KEGG E Prot and G ik and a variety of structure and pathway viewing appels The HMDB database supports extensive text sequence chemical structure and relational query searches Four additional databases DrugBank T3DB SMPDB and F rugBank contains equivalent information on 1600 drug and drug metabolites T information on 3100 common toxins and environmental pollutants human metabolic and disease pathways while F databases
7. B contains oDB contains equivalent information on 28 000 food components and food additives HMDB Version 3 6 B are also part of the HMDB suite of MPOB contains pathway diagrams for 440 oes a Q Search Tweets V Follow Metabolomics Centre TMIC Computer program developed by TMIC investigators and RCMP to solve arson cases metabolomics u news ualberta ca newsarticles 2 af Metabolomics Centre HMDB is offered to the public as a freely available resource Use and re distribution of the data in whole or in part for commercial purposes requires explicit permission of the authors and explicit acknowledgment of the source material HMDB and the original publication see below We ask that users who download significant portions ofthe database cite the HMDB paper in any resulting publications Please cite 1 Wishart DS Tzur D Knox C et al HMDB the Human Metabolome Database Nucleic Acids Res 2007 Jan 35 Database issue D521 6 17202168 2 Wishart DS Knox C Guo AC et al HMDB a knowledgebase for the human metabolome Nucleic Acids Res 2009 37 Database issue D603 610 1895302 3 Wishart DS Jewison T Guo AC Wilson M Knox C et al HMDB 3 0 The Human Metabolome Database in 2013 Nucleic Acids Res 2013 Jan 1 41 D1 D801 7 3161693 Pi 5 V TMIC rens e fs 5 8 8 Screenshot 44 The Human Metabolom Database home http www hmdb ca eD f each compound both for NMR p
8. Section 3 presented an introduction to the basics of NMR spectroscopy This section briefly outlined the practical uses of NMR spectroscopy and its application in biochemistry for assaying the concentration of metabolites In Section 4 we have discussed the findings that were presented in Section 2 We critically review some of the requirements for objective measurements and evaluated some of the advantages of the use of indices We have further listed some methods which are currently used to monitor the concentration of metabolites Finally NMR spectroscopy was compared to other commonly used techniques Benefits and restrictions of NMR spectroscopy were listed In 4 6 we presented our own database which has been created using Bruker s Amix software This database contains at present reference spectra for 70 different compounds The database was created to test the usability of Brukers Amix software as a tool that allows the streamlining of identification processes of metabolites in a NMR spectra The functionality of the database was discussed in a case study presented in Section 5 We showed some restrictions errors and the need for the further development of Bruker s software Yet the software already now holds the promise for becoming a useful tool for rapid analysis of NMR spectra and further development is recommended In addition to its functionality the database can provide the storage and systematization of NMR reference data Reference
9. 1982 Trimethylamine TMA is a compound formed by the bacterial reduction of TMAO or by the breakdown of choline during the spoilage of fish Hebard 1982 Sikorski 1990 Some fish species such as pelagic fish have the enzymes necessary to reduce TMAO to TMA Hebard 1982 For Atlantic salmon it has been suggested that such enzymes are of bacterial origin Shahidi 2006 Simpson 2012 Studies show that in some cases the bacterial load of fish products correlated pretty well with the amounts of TMA produced Hebard 1982 TMAO may also be catabolised into equimolar amounts of dimethylamine DMA and formalderhyd FA This breakdown requires a TMAO ase enzymes normally only found in fish of the gadiform order Simpson 2012 This breakdown may also occur in the presents of cysteine and a iron or hemoglobin catalyst at temperatures between 22 and 24 degree Celsius TMA is the major product of such a reaction but an appreciable amount of DMA and FA are also formed Hebard 1982 TMA is a important metabolite in the spoilage process of fish products and plays a major role in the degradation of sensory attributes of fish fillets Hebard 1982 TMA and TMAO are odorous volatile compounds Sikorski 1990 TMA especially has a low odor threshold and is described to have a unpleasant fishy odor and a unpalatable taste Waarde 1988 TMA itself does not appear to posses the odor described as fishy Pure TMA odor has been des
10. 2010 Occurrence of biogenic amines and amines degrading bacteria in fish sauce Czech Journal of Food Science 28 5 440 449 53 8 Appendix Appendix I Bacterium found on fish fillets Table 6 A listing of bacteria found in literature related to production of spoilage compounds TMA TMAO produces Enterobacteriaceae TMA Hypoxanthine Acetic acid Dalgaard 2000 Vibrionaceae TMA Hypoxanthine Acetic acid Dalgaard 2000 Shewenalle Putrefaciens TMA Acetic acid Low pH pH 6 Cadaverine Dalgaard 2000 Photobacterium TMA Hypoxanthine Phosphoreum Acetic acid Biogenic amines Dalgaard 2000 Escherichia Coli Dalgaard 2000 MEE Biogenic amine producers Pseudomonas spp Cadaverine Bulushi 2009 other Biogenic amines Dalgaard 2000 Lactic acid bacteria Ammonia Biogenic amines Daldgaard 2000 Ammonia Biogenic Brochothrix amines Dalgaard 2000 thermoshacta Enterococcus faecalis Acetic acid Ammonia Biogenic amines Dalgaard 2000 Morganella morganii Histamine Dalgaard 2000 Proteus mirabilis Histamine Bulushi 2009 Gram negative ae bacteria Psychrobacter Dalgaard 2000 2000 Low pH pH Low pH pH6 55 Appendix II Compounds found in case study and peak assignment AMIX Analytic Profiler version 3 9 14 Table 7 The results of the analysis of SO T5 and S4 T5 using Aurelia Amix software Compound 6 ppm Percent match in Percent match in A
11. 8 580 8 575 8 570 8 565 8 560 85 8 550 8 545 8 540 8 535 amp 5 8 205 8 200 8 195 8190 8 185 8 160 Chemical Shift ppm Figure 20 Change of AMP peak 8 56 ppm dataset S4 Chemical Shift ppm Figure 21 Change in Hx peaks 8 20 and 8 18 ppm for dataset S4 37 240 8 235 8 230 8 225 Chemical Shift ppm Figure 23 T5 spectra of SO and S4 overlaid with SO on the bottom blue and S4 on top red Shows the final difference of Hx peaks at 8 20 and 8 18 ppm Figure 22 T5 spectra of SO and S4 overlaid with SO on the bottom blue and S4 on top red Shows the final difference of Inosine and IMP peaks at 8 23 and 8 22 ppm respectively 8 220 Hx 0 010 4 Normalized Intensity T T T T T T T T T T 8 210 8 205 8 200 8 195 8 190 8 185 8 180 8 175 8 170 8 16 Chemical Shift ppm 38 Normalized Intensity 5 4 TMA TMAO Figures below show the change in selected peaks relating to TMA and TMAO Spectra are overlaid in ascending order with TO on the bottom Chemical Shift ppm Figure 26 Change of TMA levels dataset S4 peak at 2 89 ppm 0 055 45070 T5 esp 080 J S070 Ts esp 0 050 4 oe a oos 050 E TMAO 0 040 4 4 E TMA e y 0 030 4 4 8 E El 0 028 4 i 0 020 4 0 015 4 0010 4 E 3 s 0 005 4 E 1 1 n 4 ee ee f omnes a e 3 z 3 3 0 005 3 EA 00103 ma
12. Histamine cadaverine tyramine and putrescine levels Tyrosine decarboxylase in salmonoid fish increase parallel with the tw Tim Lysine decarboxylase progression of spoilage Bulushi 2009 Lysine sc NNNM Other research has also shown a clear correlation between the increase of Arginine i Agmatine cadaverine and putrescine and the growth mE porineremcass agmatine deiminase of spoilage organisms on fish fillets Citruline Prester 2011 Visciano 2012 Cadaverine N carbamoylputrescine ornithine N carbomyl putresci has been found to be most commonly carabamoyltransferase a aua present in spoiled fish products Bulushi Ornithine Putrescine 2009 Visciano 2012 Also histamine nee levels have been found to be an inadequate Putrescine measure for fish spoilage Bulushi 2009 spermidine synthase It has been proposed to use the Spermidine concentration of biogenic amines to spermine synthase develop a spoilage index for fish products Several such indices formula 1 and 2 Spermine have been produced but none are in Figure 2 The production of specific biogenic amines from amino acids widespread commercial use with intermediates Prester 2011 Formula 1 Amine index AI putrescine cadaverine histamine putrescine cadaverine histamine tyramine tryptamine methylamine spermine spermidine Bulushi 2009 Formula 2 Biogenic Amine Index BAT histamine putrescine cadaverine tyra
13. J Primavera J H Kautsky N Beveridge M C M Clay J Troell M 2000 Effect of aquaculture on world fish supplies Nature 405 1017 1024 Neuhaus D Williamson M 1989 The Nuclear Overhauser Effect in Structural and Conformational Analysis Wiley Weinheim nal A 2007 A review Current analytical methods for the determination of biogenic amines in food Food Chemistry 103 1475 1486 Pan Z Z Raftery D 2007 Comparing and combining NMR spectroscopy and mass spectrometry in metabolomics Analytical and bioanalytical chemistry 387 2 525 527 52 Prester L 2011 Biogenic amines in fish fish products and shellfish a review Food Additives amp Contaminants Part A 28 11 1547 Regenstein J M Schlosser M A Samson A Fey M 1982 Chemical Changes of Trimethylamine Oxide During Fresh and Frozen Storage of Fish In R E F Martin G J Hebard C E Ward D R Eds Chemistry amp Biochemistry of Marine Food Products Connecticut USA AVI Publishing Company Sen D P 2005 Advances in Fish Processing Technology New Delhi Allied Publishers Private Limited Shahidi F 2006 Maximising the Value of Marine By Products Elsevier Science Shumilina E Ciampa A Capozzi F Rustad T Dikiy A 2014 D and 2D NMR studies of metabolic profile of the Atlantic salmon Salmo salar stored at different temperature Department of Biotechnology NTNU Unpublished manuscript Sikors
14. Screenshot 42 EN SE di bmse000028 L Alanine at BMRB mb wisecedu E PBD f i Melabolomishome A L Alanine Synonym Search TuspAstandards Sonko All standards L Alanine bmse000028 data bmse000994 data bmsto00272 theory Wikipedia L Alanine Go Search Wikipedia L Alanine L S Aminopropionic acid ALANINE L L Alanine Propanoic acid 2 amino S L 2 Aminopropionic acid Alaninum Latin S Alanine alpha Aminopropionic acid L alpha Alanine Alanine L alpha Aminopropionic acid Molecular Formula C3H7N O2 Natural Isotopic Abundance Mass 89 0931800000 Mono Isotopic Molecular Masses C12N14 890476784741 C13N14 920577429875 H C12N15 90 0447133673 2 n C13N15 93 0547778807 a CH L Alanine InCHi String InChI 1S C3H7NO2 c1 2 4 3 5 6 h2H 4H2 1H3 H 5 6 12 ImO s1 isomeric SMILES OH JSmol Screenshot 41 Main page for compound alanine on BMRB window containing a table of the assigned chemical shift data for this page is a molecular structure of the compound that you have opened This molecular structure is interactive and can be scrolled to zoom and rotated in 3D also this structure is 97 nonstatic on the webpage and will not move if you scroll down When doing so you will see the displayed spectra with the title indicating which typ eof spectra it 1s Under the title you find specific information for concentration pH and temper
15. Sikorski 1990 This rise is Figure 9 The development of post mortem pH over time raw fillets at storage temperature 0 C shown as solid line and frozen thawed fillets ShOQGL a Jo shown as dotted line Einen 2002 Hultmann in which Atlantic salmon fillets pH rose from 6 18 and 6 30 to 6 20 and 6 32 respectively over a 14 day period Hultmann 2004 2 6 2 Rigor mortis Cause Bonding of muscle proteins due to rise of Ca Effect Stiffening and shortening of fillets followed by a softening Quality Pronounced effect on texture Also implication for loss of color in salmon meat Indicator Used as a sure indicator or freshness The post mortem stiffening and shortening of the fish muscle is known as rigor mortis Rigor mortis is a well studies biological phenomenon as it has a large impact on the quality of red meat Sikorski 1990 It occurs due to a bonding of the myosin heads to the active centers actin filaments in the fish muscle to form a inextensible actomyosine This connection of the major muscle proteins is caused by a change in the regulatory proteins of the fish s cells after death which is in turn induced by a rise in the concentration of Ca ions Sikorski 1990 Tejada 2009 The Ca levels of the fish s muscle cells is governed by calcium pumps imbedded in the sarcoplasmic reticulum These pumps actively pump Ca ions out of the sarcoplasm against it concentrations gradient using ATP as energy source to drive the r
16. They determine the quality of the fillets which is reflected in the eyes of the consumer as the safety nutrition flavor texture odor color and appearance of the fillets see Section 1 3 Monitoring metabolites through chemical analysis is therefore the key to the understanding and the measuring of fillet quality and opens for the possibility to develop a consumer index that objectivley indicates the quality of samples Due to salmon often being seen as an affordable luxury product see Section 1 2 such a measure would be of special interest for the production and sale of high price premium packs of Atlantic salmon fillets An objective chemical based measure for quality would provide a way to verify and mark the quality of premium products The development of an objective measure of quality would also be of interest for the investigation of the quality of farmed salmon against that of the wild one thus providing a standard marker of quality Moreover an objective measure which also is easy to use would minimize loss of fillets due to faulty spoilage analysis and assure the consumer that fish is safe to eat 4 2 Objective measurement indices and freshness indicators The effects of metabolites on fish quality individually and when interacting with each other is not yet well understood In spite of the central role the development of an objective measurement system still requires more research Sikorski 1990 states that numerous ind
17. especially cadaverine in S4 shows a faster progression of spoilage in this dataset It may also suggest the presents and activity of bacteria which produce biogenic amines in the fillets 5 5 5 Others One noteworthy change in the data was the rapid rise of a peak at 1 91 ppm in dataset S4 assigned to acetate see Figure 37 S4 saw a much larger rise in the concentration peak as seen on Figure 38 This suggests other forms of glucogen glucose breakdown and possibly the presence and activity of bacteria producing acetate Some of these are listed in Appendix I 5 5 6 Database analysis As seen in Appendix II the database was used to attempt the detection of 68 metabolites in T5 samples of SO and S4 Appendix II shows the peak information used in the database for each compound and the match percent of each metabolites in each T5 spectra A higher match percent from the database analysis corresponds to a higher likelihood of the presents of each metabolite In this analysis we can clearly see a low match percent for compounds which were detected through manual analysis such as Inosine and TMAO match percent 35 62 49 76 and 27 04 33 57 Inosine TMAO for S0 and S4 respectively It should be noted however that the reference compound DSS set to peak at 0 ppm showed only a 86 25 and a 86 30 percent match As all samples contain DSS as reference the match percent of DSS should be 100 percent With this in mind the low match percent of the other
18. resulted in a loss of sweetness and an increase in bitterness of fish meat Jones 1967 It is also interesting to note the interaction with IMP IMP plays an important role in the quality of fish meat see Section 2 5 2 These interactions with amino acids may play a part in the flavor enhancing activity of IMP and be responsible for some of the loss of quality during the degradation of IMP Table 3 Values for concentration of individual amino acids from Hultmann 2004 flavors and values for flavor threshold from Belitz 2009 Amino Acid 5 Days umol g 14 Days umol g Taste Threshold Taste Quality umol mL b Rd 7 Glutamic acid Asparagine Histidine Serine Arginine Threonine Alanine Tyrosine Methionine Valine Phenylalanine Isoleucine Leucine 2 2 2 Amino acid degradation Occurs By The proteolysis due to endogenous enzyme and bacterial breakdown Produces Aldehydes sulfides mercaptans short chain fatty acids biogenic amines Effects Generation of odorous compounds and the gradual loss of fresh appearance The breakdown of non protein nitrogenous compounds such as amino acids forms substances such as aldehydes sulfides mercaptans short chain fatty acids and biogenic amines Many of these compounds are odorous and responsible for the gradual loss of the fresh appearance of fish They are also partially responsible for the development of spoilage in fish Sikorski 1990 The break
19. t d m m d t m m d d m d d d m m m t m m t dd d m m m m m dd m m t Tyrosine 6 89 7 19 7 20 Aspartate 2 80 3 86 Spermidine 1 61 2 60 61 62 Appendix III A short manual for the creation of a Spectral database and a Knowledge base using the Aurelia Amix software version 3 9 14 and its use for the detection of compounds in 1D NMR spectra 63 64 Table of content 1 Introduction 1 1 Use of Amix Aurelia Spectral Base and Knowledge Base eee e eee etes eee ee eene eerte netta 67 1 2 Installation Of VU e H 67 1 3 Getting Started noL iSo Sso 70 1 4 The Amix Viewer Spoo sesso tesos soosis seess SER e osese 71 2 Spectra Base 2 1 Creating a new Spectral Base eessesssesseossoossoosoossoossoossosesoessosesessseessesssossoossoossosssosssosssosssesssesssessosss 72 2 2 Preparing data eee ette trien eno Ora enean ge pue eoo Cone rna asa sns n srete rocoto eison soseednadsossscscndccevonsses 73 PRUVE Aa E E E E E EIEE A EEN AE EEE 74 PRE ETEEN IAA TULES A A AEE EAA E EA E E E P AE E E A 77 Ded KC er 78 ZO ratos E 79 pMEAWNIITI CE M roso 80 2 8 Attaching Molecular files 4 eee cresce eese e eres eerte eene etna essere se tona setas sten bos Uson s ororun sesta seen naee 81 pe Kd
20. window This can be done by using the Open function in the File drop down menu in the upper left toolbar You then proceed as in the Amix Viewer Section 1 4 Alternatively you simply drag the spectral file into the window The files are usually named 1r for 1D and 2rr for 2D TOCSY and H 13C HSQC and other 2D spectral data which are the common file formats for processed NMR data Screenshot 8 The main Amix Data Preperation window 73 If the spectral directories lack these files the information is most likely not processed yet and has to be processed by another program before inserting these files into the software becomes possible Once the spectra to be processed is loaded to the prepare data window there are several different methods of preparation depending on the spectra type which is loaded into the window 2 3 1D spectra Once the spectra is loaded a good idea is to define a noise level for the spectra in order to eliminate the background noise Go to the Preparation menu in the upper left toolbar and select Define noise level in the drop down menu This will open a window showing several different options for noise level definition Screenshot 9 For 1D spectra it is the simplest to select Define noise level interactively You can also define the noise level by a number yet this is more difficult Once File Config Analysis eparation SS BM 2255 BILD
21. 8 34 ppm for dataset SO 48070 T5 esp 0 020 ois Hx 200 3 Hx L 0 005 4 V H d ee i a ee m 0 005 d 00104 EM E m we Me ae S er uri o 0 020 P ox r 821 8210 820 8200 8 195 3 190 5 165 5 160 8 170 8475 Chemical Shift ppm Figure 17 Change in Hx peaks 8 18 and 8 20 ppm dataset SO 36 Normalized Intensity Normalized Intensity S410 t5 esp Inosine ix 8410 t5 esp 0 15 0 10 4 T asd 3 Inosine P E L j Normalized Intensity Sen f n 7 i X T T T Chemical Shift ppm Figure 18 Change of Inosine and IMP peaks at 8 22 and 8 23 ppm respectively for dataset S4 0 08 4 T 8 215 T T T T 8310 8 305 Chemical Shift ppm Figure 19 The change of inosine peak 8 34ppm for dataset S4 S410 15 esp 0 07 4 0 06 4 0 045 454 t0 t5 esp oos 4 0 040 4 0 04 4 hse Hx j nil Hx 1 0 030 4 0 03 4 4 8 4 0 025 3 T 0 02 4 0 020 4 3 E id AMP T 0 010 4 EP PEL 1 E E 0 005 4 d P i T ee bic 013 3j 13 per 3 4 0024 owi 7 1 0 0104 0034 NES 4 die a 4 4053 7 E c NES pc i 0 043 N PE 0 0254 0 054 f 4 E rd 0 0304 0 06 3 a q rs eem E 4 4 035 3 7 ey 4 0074 E vow j 00453 T T T T T T T T T T T T T T T T
22. Key window under the Open file from Sbase function Evaluate range the input has to be equivalent to the defined Key value not the Key name This will generate a list of all the spectra labeled with this search string It is also possible to search the Sbase using both compound name experiment type and search Keys For this option select name and properties from the window in the Open file from Sbase function Now it is possible to fill in both compound name and experiment type as well as to check the boxes for search Keys and other search parameters This is by far the search function that gives you the most specific sets of data if the Sbase is set up correctly Let us look as an example If you have entered the 1D H TOCSY and 2D H 3C HSQC spectra of all 20 amino acids and used the amino acid names Compound name and 1dnosey tocsy or 2dhsqc as Experiment type depending on the spectra If you have labeled all spectra with the Key name and value amino acid you can use the name and properties search function in different ways Firstly to bring up all spectra of a specific compound such as Alanine enter alanine into the Compound name field enter into the Experiment type and leave the search keys box unchecked Now Amix 85 will generate a list of all spectra under compound alanine and you will see them displayed on the list select the
23. Met E coli or E coli_met 72 You can create as many Sbases as 3 Amix Viewer version 39 14 you wish and it is recommended File Config Analysis Patterns Measure Amix Tools SBGSMM 22 S BIT OM 9 amp 9 Avs 25 x t AGAIEEIBESIE that you create a separate Sbase which is used to test functions In this way you avoid interfering with create new SBASE work on your main Sbase E eee toe ENSURE SBASE directory c data michael nar test 2 2 Preparing data To prepare spectra for the Sbase you select the Prepare data function under the Amix tool menu in the Amix Viewer A new window will appear This is the data preparation window which gives you access to a number of different functions from the regular Amix Screenshot 7 The create new SBase fucntion and the definition of a data Viewer This window can easily be directory for the Sbase identified by Preparation written in the upper left corner Again this manual will only explain the functions that are essential in the present context for a full list of functions Preparation version 39 14 a fees File Config Analysis Patterns Measure Algebra Preparation Helj g P ZA 25 ES T TS QQ AWA SE see the official AMIX Aurelia B ik Seo A EO te LEE ducum Pe cem EEEO manual To prepare a spectra you have to load it into the data preparation
24. Om amp amp S 7d 2 a6 ix B L7 4k RS BA EE SG asure Algebra Pr you have selected the interactive noise ae 5 Noise level calculation noise level definition definition press c Ok This will level from noise region el interactively y ratio relative to biggest point in original spectrum automatically take you back to the data right noise factor e g 10 ppa 1 ppa 3 5 user defined noise level 16000000 intensity ratio 10 x preparation window neglect solvent from ratio calculation l neglect reference from ratio calculation Now hover your mouse over your 1D spectra a horizontal line across the window should appear This illustrates the threshold for the noise level Move the mouse until the Screenshot 9 The Define noise level function for 1D spectra line reaches the level that you wish to define as noise level and press the left mouse button A smaller window will appear which gives you the threshold number that you have selected using the interactive noise definition By using this number you can recreate the same threshold through the Define noise level by number function Press OK and you have defined the noise as indicated at the horizontal line Screenshot 10 After the definition of a noise level one can remove any peaks which a
25. The amount of post mortem carbohydrates is also dependent on the conditions of capture Sikorski 1990 Fish which have struggled during capture and are fatigued have exhausted their stored energy and thus contain less reserves of glycogen and carbohydrates after death Well fed fish which is killed instantaneously will contain high amounts of glucose glycogen and other carbohydrates Sikorski 1990 glycogen gt maltose glucose UDP glucose ra AN glucose 1 phosphate phosphate Glycogen is catabolised through a ATP hydrolytic and phosphorylase pathways ee ee known as the Embden Meyerhof Parnas lactic acid pathway see Figure 7 Sikorski 1990 This pathway in combination with the Figure 7 The Embden Meyerhof Parnas pathway anaerobic conditions after death results in Sikorski 1990 the accumulation of lactic acid and produces ATP in the fish muscle The accumulation of lactic acid along with the production of inorganic phosphate is one of the primary factors inducing the post mortem drop in pH of fish meat Concentrations of approximately 60 ug lactic acid 17 per 1g of fish muscle results in a 1 unit drop in pH Sikorski 1990 The amount of glycogen in the fish muscle at the moment of death is a important factor determining the quality of the meat Haard 1992 In addition to governing pH level the degradation of glycogen and glucose to ATP affects the onset of rigor mortis Einen 20
26. ability to quantify the concentration of these metabolites but this ability has not been tested for this thesis Our database also contains in addition well organized data on each of the reference compounds including its molecular structure chemical or common names and the 1D H 2D H H TOCSY and 2D PC HSQC NMR spectra The reference data has been organized to be easily browsable for specific spectra of compounds or for groups of compounds which have been given a specific search key For a more detailed introduction to the Amix software and the creation and function of the database see section 5 3 4 and the attached manual Appendix III To use the Amix software seems to be usefull for the analysis of NMR spectra with a number of known metabolites The database developed for this thesis has the ability to detect up to 70 metabolites in new NMR spectra within minutes The database is not bound to samples of Atlantic salmon and can be applied to any NMR spectra It thus allows any type of NMR study Furthermore the database can also be used to quickly acquire all the data for a quality and freshness index based on metabolites Further development of such a database could yield a useful tool for future studies using NMR spectrometry especially on biological samples 31 5 Case Study Detection and analysis of the development of metabolites during storage of Atlantic salmon using NMR spectroscopy To further illustrate the use of NMR spectrosc
27. acid amino acid c 7S salar ref glutamate idnosey ir cpr KEY amino acid amino acid G 78 salar ref glutamine ldnosey lr cpr KEY amino acid amino acid Sbase and its Keys are set c S salar ref glycine ldnosey lr cpr KEY amino acid amino acid c 4S salarz ref histidine ldnosey lr cpr KEY amino ac e 7S salar ref isoleucine ldnosey 1lr cpr KEY amino acid amino acid 5 78 salar ret leucine ldnosey 1r cpr KEY_amino acid aminn acid up correctly this function 8 salar7 ref lysine 1ldnosey lr cpr KEY amino acid amino acid c 4S salar ref methionine 1dnosey lr cpr KEY amino acid amino acid c 7S salar ref phenylalanine ldnosey 1lr cpr KEY amino acid amino acid Hacen is m tae meds pe A anino acid arino acid is a very powerfull search c S salar ref serine ldnosey lr cpr KEY amino acid amino acid le 7S salar ref threonine ldnosey lr cpr KEY amino acid amino acid Z c 7S salar ref tryptophane ldnosey lr cpr KEY amino acid amino acid l 6 48 salar ref7tyrosine ldnosey lr cpr KEY amino acid amino acid tool c S salar ref valine ldnosey lr cpr KEY amino acid amino acid want and confirm amino acid Entire compounds can also AutoSelect Unselect Cancel be opened directly by Screenshot 26 Search result name This is done with the Open compound for x Sbase function also found for experiment type Idnosey and key amino acid under the File menu This will open a simple window wh
28. alanine HMDB28680 Alanyl Alanine Screenshot 45 Search results for alanine on HMDB a alanine is often decreasec with a short biochemical description of its function technical data such as molecular weight and formula and 99 other things like synonyms for the compound This page is extremely useful for further research and to Common Name L Alanine structure OH n My voL sor Pos smes ncr SENET T 25 2 Aminopropanoste 28 2 Aminopropanoic acid oncertrations Links References XML jms aon Aan eer Son et debts ad gym oan ee rcc pcc with several links below creensho glycine is an inhibitory neurotransmitter in the brain http Avww denutntion com AmincAcids gather technical data for each compound To download the molecular structure of B 2 amp f es each compound for use in the Sbase navigate down to the Structure field of Show Metabolites wiih Similar Studures the HMDB site located in the T Serre ie Methabolite Identification section of See its page Here you will see the molecular Netatolite identification structure of the compound displayed 46 Right click the link titled MOL and press Save link as in the resulting menu This will download the mol structure file of the compound to a Screenshot 46 The main page for L Alanine with the structure section visible on the bottom location which you specify this should
29. anserine and carnosine are also active in the buffering capacity of the fish muscle It has been suspected that their function may involve buffering the lactic acid from anaerobic glycolysis Waarde 1988 Anserine and carnosine have also been shown to be active in several enzyme complexes such as fructose 1 6 biphosphotase several ATPase and the 3 phosphate phosphoglycerate kinase complex Waarde 1988 These compounds may also be involved in the mineral metabolism and the intracellular transport of copper Waarde 1988 2 3 1 b Taurine Produced by Not known fully assumed by methionine catabolism possibly cysteine catabolism Functions Mostly unknown implied in a number of biological functions Effect Mostly unknown implied in a serumy astringent and bitter flavor Taurine is the main free amino acid in salmon species Haard 1992 It can be a product of the methionine Cysteine 2 NADH n dd accedit 202 2NAD 2H20 Cysteine sulfinic acid i CO2 Hypotaurine NADH ioe a as Taurine 2NAD H20 Figure 4 Main route of taurine synthesis in higher vertebrates proposed for fish Waarde 1988 catabolism which produces cysteine and further taurine Espe 2010 Also the biosynthesis of taurine from cysteine which is present in higher vertebrates has been under investigation as possible source of taurine see Figure 4 Li 2009 The specifics of taurine synthesis in fish such as intermediates enzymatic acti
30. at the Norwegian University of Science and Technology in Trondheim 1 The ID H experiment Bruker noesygpprld pulse sequence had a following settings 512 transients the recycle delay of 5 s a 90 pulse of 7 8 s 32K data points presaturation power PL9 42 0dB spectral width 12 ppm acquisition time 2 28 s mixing time of 10ms He d The 2D H H TOCSY experiment Bruker mlevphpr pulse sequence had a following setting TPPI phase sensitive mode spectral width 12 ppm in both dimensions a relaxation delay 2 s mixing time 100 ms 4 K data points in F2 and 512 increments in F1 MET The 2D H C HSQC spectrum was registered in the echo antiecho phase selective mode with the following parameters 7 8 us 90 pulse 12 and 200 ppm spectral widths in the proton and carbon 1o 13 dimensions respectively H C coupling constant 145Hz The spectra were calibrated taking the lg and C chemical shifts of TSP signal equal to 0 ppm Each acquired spectrum was processed with TopSpin 3 x Bruker Germany and MestReC 4 9 8 0 Mestreab Research SL Spain by manually adjusting phase and base line and applying a line broadening factor of 0 5 Hz NMR assignment was performed using the published data for the reference standards BMRB HMDB YMDB ECMDB The metabolites chemical shifts in the range between 0 0 ppm and 12 0 ppm were integrated and normalized to the resonance of TSP signal 5 3 4 Databasing After initial assignment th
31. by few bonds This interaction is particularly useful for determining the connectivity between the atoms in the sample Baldus 1996 Kessler 1988 Dipolar couplings depend on the interaction of isotopes through space Dipolar interactions also give rise to the Nuclear Overhauser effect which influences the intensity of the signal Dipolar interactions supply information on the spacial distance between isotopes and are useful for determining the three dimensional structure of molecules Neuhaus 1989 Such interaction between isotopes greatly complicate the procedure of peak assignment from 1D NMR spectra Thus several two dimensional 2D NMR techniques have been developed which are used to correctly detect isotope interactions and clarify any cases of overlapping peaks Using 2D spectra in coherence with the peaks of the 1D spectra can correctly identify chemical groups and compounds Several 2D NMR techniques have been developed which each show specific aspects of isotope interactions and often have to be combined for certain identification of structures and compounds Spectra which are used in this thesis include techniques 1D H 2D H H TOCSY Total Correlation Spectroscopy Cavanagh 1995 and 2D H C HSQC Heteronuclear Single Quantum Coherence Cavanagh 1995 3 4 NMR in biochemistry The most common isotopes used for the study of biological samples with NMR spectroscopy are H PC PN and P Highman 2012 Due to the univer
32. compound should be scaled up accordingly Taking this into account we consider a compound with an 80 percent or above match a certain detection according to the Aurelia Amix software Compounds which were over this match percent were DSS creatine lactic acid acetate in S4 T5 only phosphocreatine fumerate in S4 T5 only and threonine Also the software was unable to analyze several of the key compounds such as TMA and HX This error in the software needs to be corrected in further versions of the software It should also be noted that this software is an automated analysis of 1D NMR spectra only This means that high or low match percentages measured by the software do not correspond to the certain presents or lack of the compound As mentioned in Section 3 3 the use of only 1D NMR spectra is insufficient for the certain 47 identification of compounds Also the use of software is never equivalent to manual analysis as the software cannot detect unforeseen circumstances or mistakes normally easily detected by manual analysis In its current state the database can be used only as an aid for the manual analysis of each spectra Yet with further development such as the ability to analyze 2D spectra or further adding and adjustment of compounds the likelihood of a match in the software being a certain detection of the compound would increase The Aurelia Amix software also contains functionality to quantify detected compounds De
33. etnia seta seta seo se eset veset seta setas eese esee na a 7 Table 4 The major biogenic amines and the amino acids from which they derive Bulushi M 9 Table 5 The experimental setup for the case study eere ee sette etes eene eene en ee en eene esee setas tease tn etas e to aee 34 Table 6 A listing of bacteria found in literature related to production of spoilage compounds 54 Table 7 The results of the analysis of SO T5 and S4 T5 using Aurelia Amix software eere 56 List of Figures Figure 1 The productions of captured and farmed salmon 1950 2002 in metric tons world wide Goldburg Pip X 3 Figure 2 The production of specific biogenic amines from amino acids with intermediates Prester DVI cossvssinn 10 Figure 3 The formation of nitrosamines from various compounds Bulushi 2009 reser 11 NOES eT P 13 Figure 5 The metabolism of TMAO and its derivatives Waarde 1988 eee eee eee eee eene teen nne 14 Figure 6 The chemical structure of some carotenoids in salmon 1 r carotene 2 canthaxanthin 3 astaxanthin 4 astacene Christophersen 089 eerte teen eroe nein ene or
34. in 2010 was 148 million tons of fish representing a commercial value of 217 5 billion USD Of the total production 128 million tons were utilized for human consumption FOA 2012 The production of the fish industry is expected to rise with the increasing population and the rising wealth in some parts of the world Goldburg 2005 This predicted trend is supported by statistical data showing an increase in production from 137 2 million tons in 2006 to 154 millions tons in 2011 and the rise of the average growth rate of the global fish production of 3 2 percent per year in the years 1961 2009 FOA 2012 In addition to human consumption fish and fish based products are also used to produce feed for the aqua and agriculture industry This use is based on the production of fish meal and fish oils and may also utilize waste products or fish which is of low market value The production of feed is estimated to consume approximately 13 of the world s total fish production FOA 2012 The fish production industry can be divided into two primary sectors The first of these is the capture industry which primarily harvests wild fish from the world s oceans or freshwaters The second sector is the aquaculture industry which deals in the raising and husbanding of fish in enclosures for slaughter and later sale Fisheries which capture fish from 2006 2007 2008 2009 2010 2011 the wild produce wild fish which Million tonnes will
35. in Section 2 3 2 reductive enzymes or of cysteine and iron in high concentrations Close to no fall is seen on TMAO peaks of SO yet the production of TMA in this dataset is SO is small in relation to the TMA production in S4 see Figure 28 for comparison of peaks at T5 If such small amounts of TMA are produced by reduction of TMAO they may not display clearly on the peaks of TMAO as concentration changes are low To firmly establish the correlation between fall of TMAO and rise of TMA a quantitative study is needed The production of TMA is clearly related to a loss of the fillet quality The rapid production of TMA in S4 would indicate a clear quality difference between fillets in dataset SO and S4 suggesting that SO fillets are of higher quality after 7 days of storage 5 5 4 Biogenic amines We have chosen not to study all biogenic amines rather we have selected cadaverine and its production from lysine as it was shown that cadaverine best correlate best to the progression of spoilage see Section 2 2 3 Also tyramine and its production from tyrosine was studied since as tyramine is a potential health hazard Attempts to find histamine were made yet no significant concentrations were found Figure 31 shows a small peak at 3 01 ppm in SO which has been assigned to lysine Figure 32 shows the same peak in S4 yet at T3 another peak begins to grow on the slope of the lysine peak This new peak was assigned to cadaverine The growth of the c
36. in the first section of the black screen and the physical address supplied in the second section Screenshot 3 BY Ledetekst Microsoft Windows Ue Copyright lt c gt 200 Mi toke n 6 1 76011 soft Corporation Med enerett iC Users Dorothee gt ipconf ig all Windows IP konfigurasjon HF 38877 hf fak hf ntnu no Hybrid Nei Vertsnaun Primer DNS suffiks Nodet ype IP ruting aktivert WINS Proxy aktivert Nei Sekeliste for DNS suffiks hf fak hf ntnu no Ethernet kort Lokal tilkobling Tilkoblingsspesifikt DNS suff iks Beskrivelse tion Fysisk adresse 88 21 78 6E 78 7R DHCP aktivert o gt da Automatisk konfigura Koblingslokal IPy6 adresse Intel lt R gt 82566DM 2 Gigabit Network Connec Ja fe8 a98c 614 ae35 305 13 Foretrukket gt IPu4 adresse 16 0 0 4 Foretrukket gt Nettverksmaske aa 255 255 255 6 Leieavtale inng tt er 21 april 2614 11 61 30 Leieavtale utleper a z 21 april 2614 12 31 36 Standard gateway 16 6 6 1 DHCP server 16 6 6 1 DHCPv6 IAID 268444016 DHCPu6 klient DUID 88 81 88 81 18 15 2D 15 8080 21 780 6E 78 70 217 13 7 148 217 13 4 24 Aktivert DNS servere NetBIOS over Tcpip Tunnelkort isatap CB96F78079 FD21 43EF RFC9 7604336D6602B Medietilstand Tilkoblingsspesifikt DNS suffiks Beskrivel Medium frakoblet Microsoft ISATAP Adapter Fysisk adresse 66 60 06 60 06 60 06 E
37. its original name and any additional names you have defined Here an example You define a compound under the compound name ATP and add adinosine_triphosphate as alternate name you will receive ATP as search result if the database is searched for ATP or adenosine_triphosphate When activating the Edit compound names function you first have to specify which compound you wish to give alternate names This is done through the window which first appears after activating the function Here insert the original compound name into the field compound and check the correct Sbase in the top checkboxes of the window Amix will then generate a list of all compounds in the Sbase saved under that name Select the one you wish to add a name to and confirm This will generate a window with blank lines titled Alternate names Screenshot 20 add any alternate names you wish your selected compound to have to these lines Now the selected compound will respond to its original name and to all additional names you have defined when they are used as search parameters This function is especially useful for compounds which are abbreviated such as ATP 82 3 Browsing and opening from SBase The functions to browse search or open files from your Sbase are all placed in the File drop down menu on the top left of the Amix Viewer screen The easiest function to use is Sbase Browser this function
38. more rapid in dataset S4 Ongoing development of lactic acid may point to an ongoing breakdown of glucogen and glucose see Section 2 5 1 Based on the high of lactic acid peaks in relation to other metabolites and data from Einen 2002 showing rigor mortis and post mortem pH development both related to the glucogen glucose and the ATP catabolisms see section 2 5 1 to reach their peaks 20h post mortem Figure 9 and 10 we can assume primary production of lactic acid has concluded This assumption correlates well with the time of purchase of our samples The fillets were purchased and first tested 5 days after death of the fish The post mortem pH should have showed a significant drop caused by the change in the concentration of lactic acid This would have a positive impact on the quality of the fillets providing a firm texture as low pH will inhibit enzymes which break down muscular proteins see Section 2 2 High levels and a slow development of lactic acid could also suggests that rigor mortis has set in see Section 2 6 2 5 5 2 Nucleotides As seen on Figures 14 and 16 the concentration of AMP and IMP in dataset SO is rapidly decreasing reaching disappearing values at T4 10 days Also concentrations of ATP are of no significant value starting at TO Seen on Figure 14 16 and 17 shows rising concentrations of inosine and hypoxanthine Hx Concentrations of xanthine and uric acid were not yet of significance at T5 This indicates that
39. of ATP catabolites has on the quality of the product ATP and its catabolites partially are responsible for the drop in post mortem pH and the initiation of rigor mortis Section 2 6 1 and Section 2 6 2 The liberation of phosphate and ammonia during the degradation of ATP is one factor effecting the final pH of fish fillets Sikorski 1990 In addition to this rigor mortis is highly dependent on ATP degradation within the muscle of the fish Due to the positive effect of IMP and the negative effect of Ino and Hx on quality products of the ATP catabolism have been suggested as a measurement for the freshness of fish In addition it has been found that nucleotide degradation correlates well with the shelf life of a wide range of fish species Tejada 2009 Leading to suggestion that ATP catabolism can also be used as an indicator of spoilage 2 5 2 a K value K value Is a index of freshness and quality based on ATP catabolites Early attempts to develop a index of freshness and quality based on ATP catabolites suggested that measurement of Hx concentration would be suitable as a measure for the spoilage of fish It has been shown that the formation and accumulation of Hx and Ino is different in fish species therefore using only Hx as an indicator of freshness may be misleading and using either Ino or Hx may not be an appropriate measure Tejada 2009 Also the K value has been suggested as a measure of fish quality and spoilage based on seve
40. of products still remain a large problem for the world s fishing industry There are indications that approximately 25 percent of the world s food supply might be lost due to microbial spoilage Dalgaard 2000 Also the consumption of spoiled fish products may lead to Scambroid poisoning and other forms of food intoxication as well as ingestion of carcinogenic chemicals such as nitrosamines Bulushi 2009 It therefore 1s important to evaluate the freshness of fish and monitor the biochemical processes which lead to fish spoilage Greater understanding of these processes could also lead to the development of better storage technology for the industry 1 2 Atlantic salmon Salmo Salar Atlantic salmon S salar also known under the names Bay salmon Silver salmon or Black salmon is a fish from the Salmonidea family found in the Northern Atlantic Ocean and in rivers that flow into the Atlantic Atlantic salmon is a migratory fish which is born in fresh water where it undergoes several live cycle changes before it migrates into the ocean in order to do most of its feeding in salt water Sexually mature adults return to their native freshwaters to reproduce The lifecycle stage at which the salmon are ready to migrate to the oceans is known as smolt McCormick 1998 In relation to other fish species Atlantic salmon has been classified as containing medium amounts of fat and high amounts of protein Haard 1992 Atlantic salmon is a fi
41. open a internet browser window which will display the results of the analysis Also check the Detailed checkbox under the Select Report for display section and Report all results in the Discard results from report These two function are used to filter results for unwanted information The results will also be saved to several text and HTML files Specify where Amix should place these files in the Result Path text box It Screenshot 54 The sixth window Here you specify noise handeling is recommended to create a folder under the samples directory to hold these files as several files The next window will display a list of all compounds annotated in your Knowledge Base Here select which compounds you wish Amix to look for in the new spectra to select several compounds hold down the Ctrl key and click each entry to select all entries press AutoSelect After selecting all compounds you wish to scan for in the new spectra E Quantification of pure compounds gt ei Pure compounds can be quantified The quantification is done by taking ratios of integrals with respect to the reference both normalized to the respective number of protons contained in the knowledge base If absolute weights of the reference and samples are provided either in a single text file or in individual files absolute concentrations can be calculated If weights do not yet exist in digital form e
42. open file window After this select the spectra you wish to delete from the generated list and confirm this will delete the spectra permanently The function Rename can also be applied to entire compounds and the spectra within these compounds For this select the Rename compound function under the Spectral Base menu This will give you a window with only the compound name and molecular data as search parameter Enter the compound name which you wish to edit using the molecular data as search parameter is beyond this manual Once you have confirmed the compound name select the compound from a list of compounds that Amix will generate This will lead you to a window with a single text field new compound name enter the new name of the compound here and confirm The Rename compound will apply the new compound name to every spectra defined under the old compound 88 4 Knowledge base A Knowledge base KB is a text file which contains further spectra information of the compounds that are in one of your Sbases This Knowledge Base in cooperation with your Sbase can be used to identify compounds in new NMR spectra and is a fast and powerful tool for analysis It is a fast and powerful tool for analysis For simplicity it is recommended that you create a knowledge base for pure reference compounds not for mixtures of different compounds although this can also be done 4 1 Creating a Knowledge Base A Knowledge
43. open the Aurelia main window Screenshot 6 From the Aurelia window navigate to Options in the top left menu and then to Viewer again in the top left menu this will take you to the Amix Viewer We will be using several Amix windows all of which have different functions If you are Aurelia 3 914 confused which window currently is active check the window name such as Amix Viewer to be found in the left corner of each window T This manual will only guide you through a limited number of functions of the Amix creenshot 5 The Amix and Aurelia software If you are interested in functions which are not described in this Aurelia icons on 70 manual please read the official Amix user manual which can be downloaded from the Aurelia Amix main page 1 4 The Amix Viewer The Amix Viewer is the main window from which we will open all other functions and for our purpose this window is our main hub Several of the main functions can be found under File in the top left corner The functions here can open spectra molecules or database objects from your hard drive Thus the functions most used from the file menu are the opening functions which allow you to browse the directory on your hard drive find a spectra file 3 Amix Viewer version 39 14 Or a com ound and File Config Analysis Patterns Measure Amix Tools n SMM 2725 Sat M amp amp 87 2 362 open it Other functions f y 23080089 are th
44. programs as suggested by Wishart 2008 such as Bruker s Germany Aurelia Amix software to preform analysis 26 Such software will gather a set of reference spectra and data and use this to analyze new spectra for compound patterns Using such software one can quickly in a matter of minuts identify and quantify known compounds in new spectra This is especially useful when working with a number of spectra from known samples and when analyzing them for well known chemicals Once a NMR database of metabolites in Atlantic salmon has been established from one or several NMR spectra or through the detection of metabolites by other analysis methods one can use this database to analyze new salmon samples This detection method can quickly identify and if wanted quantify all known metabolites present in the new salmon sample through one set of 1D and 2D NMR data For a short introduction to the Aurelia Amix software by Bruker used in this thesis see Section 4 6 and for a further introduction into the softwares functionality see Appendix III 4 Discussion 4 1 On the importance of measuring metabolites From our literature review which focused on metabolites in Atlantic salmon Section 2 it became clear that metabolites and their development post mortem are important for the quality of fish products In our review the importance of metabolites was studied with regard to Atlantic salmon fillets which has been the focus of this study
45. quality of the fillets Fillets with a lower post mortem pH show a firmer texture Haard 1992 In tuna low pH values have also been associated to a sour taste and a stringent aftertaste this has not been observed independently for Atlantic salmon Rapid decline of the pH has been correlated to soft texture of the fillets and a poor water holding capacity resulting in soft dry fillets Haard 1992 Also the post mortem enzymatic activity in fish fillets was highest at pH close to neutral or higher Haard 1992 Unwanted proteolytic enzymes in the fish fillets degrade the muscle see Section 2 2 Hultmann measured low activity of these enzymes at pH 6 0 to 6 5 Hultmann 2004 The low activity in acidic environment may explain the firmer texture of fillets at low pH as the breakdown of the muscle would soften the fillets 20 Post mortem pH decline is not a suitable indicator for shelf life of Atlantic salmon The decline of pH is largely correlated with the accumulation of lactic acid and the dephosphorilation of ATP Hence the pH reaches its low value after 20 hours Einen 6 8 2002 and the pH 6 7 decline may only serve 6 6 to indicate very fresh amp 64 fish 6 3 T gig x It is of noteworthy that ae z FN T2 ES US sone idii aye in the late post mortem E p 6 1 Eat stages the pH of fish 6 fillets rises due to a 0 20 40 60 80 100 decomposition of Cold storage time hours nitrogenous compounds
46. the software system remains promising tool for rapid analysis of unknown spectra for compounds entered into the database Further development of this software seems recommendable Assuming resolution of rigor mortis and given the dissipating levels of IMP we can conclude that the fillets which we studied were not of prime freshness This corresponds well with the time of purchase 5 days post mortem Falling IMP concentration and rising concentration of metabolites such as TMA inosine and cadaverine indicate that the spoilage process of the fillets has begun The suggested levels of IMP and low levels of spoilage metabolites at time of purchase based on samples at TO indicate that the fillets were in a good state of quality at that time The slower degradation of IMP and slower rise of compounds with undesirable properties such as TMA inosine Hx and cadaverine in dataset SO shows that fillets stored at 0 C spoil slower then fillets stored at 4 C 48 6 Conclusion This thesis has presented a literature review focusing on the analysis of metabolites found in fish fillets specifically those of Atlantic salmon S salar Selected metabolites were considered individually or in groups and their effects on the quality and spoilage characteristics of fillets In addition some indices some at present in use some proposed were studied and their efficiency for the measurement of the quality and spoilage of fish fillets were described
47. with the key Amino acid To attach Keys one first has to define a key for the database The defined key can then be selected multiple times from a drop E Preparation version 3 9 14 down menu a E a Patterns Me When attaching a W2SE TtT OMRAN 7g 2 aon xx amp lv xke Br xq DEG key from the Save spectra function Amix will open a window titled edit user key shown in the top left corner This window Screenshot 12 and 13 will give you three options which appear in check boxes on top of the menu If you already have a defined Key which you wish to use select Use C data michael nmr Anserine 10 pdata 1 ir edit user keys c S salar c fusa KEY amino acid do not use use existing value new value anino acid z define new key key name KEY key value OK Cancel LL Screenshot 12 The edit user key window existing value Now the drop down menu below will become usable it contains every Key which you have previously 8 edit user keys c S salar e lolz KEY amino acid C do not use use existing value C new value amino acid amino acid V define new key key name KEY key value OK Cancel I Screenshot 13 The edit user key window with both key dropdown menu and define new key active defined Select the key you want and
48. 02 Section 2 6 2 The catabolism of glycogen and glucose also contributes to a loss of the sweet meaty character flavors found in very fresh fish Sikorski 1990 The catabolism of glycogen in the muscle is a rapid process which considering the change in post mortem pH and onset of rigor mortis seem to complete within 20 hours after death see Figure 9 and 10 Einen 2002 2 5 2 ATP Breakdown By dephosphorylation and deamination Important products IMP inosine hypoxanthine Biochemical effects Effects the post mortem pH and the onset of rigor mortis Effects IMP is associated with quality gives sweet taste and fresh flavor Inosine and hypoxanthine are associated with loss of quality and give bitter flavor Nucleosides 5 phosphate esters are termed nucleotides The most important of these nucleotides is adenosine 5 triphosphate ATP This molecule functions as the carrier of chemical energy in cells and through the breaking of the high energy phosphate bonds power most catalytic reactions in the cell Under normal conditions ATP can be generated through the use of glucose or lipids in the fish cells Post mortem the production and regeneration of ATP from ADP adenosine 5 diphosposphate continues anaerobically until stores of glycogen and free carbohydrates are exhausted Sikorski 1990 After this begins the catabolism of ATP with the stepwise dephosphorilation to AMP Sikorski 1990 and subsequent deamination by endogenous
49. 06e787a vendor info for hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 X 17 46 02 FEATURE XWINPLOT bruker 1s 0 0 28 may 2014 uncounted DB1EB09110D1DC03395F HOSTID 0021706e787a vendor info for X hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 17 46 02 FEATURE TOPSPIN ACQU bruker 1s 0 0 28 may 2014 uncounted 6B4E60717D522FF81823 HOSTID 0021706e787a vendor info for hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 17 46 02 FEATURE NMRSIM bruker 1s 0 0 28 may 2014 uncounted amp 6B6EFOD177C1C049B105 HOSTID 0021706e787a vendor info for hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 X 17 46 02 FEATURE NMRCHECK bruker ls 0 0 28 may 2014 uncounted 8B7E80616D96E4FAA8C4 HOSTID 0021706e787a vendor info for hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 17 46 02 FEATURE NMRGUIDE bruker 1s 0 0 28 may 2014 uncounted BB1E4081350A2B8E6C09 HOSTID 0021706e787a vendor info for X hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 17 46 02 FEATURE AUREMOL2 0 bruker 1s 0 0 28 may 2014 uncounted 7BFE4071A0F4385530D5 HOSTID 0021706e787a vendor info for hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 17 46 02 FEATURE TOPSPIN3 bruker ls 0 0 28 may 2014 uncounted 5BDEO051EE218C8B77F7 HOSTID 0021706e787a vendor info for hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 X 17 46 02 FEATURE AMIX3 0 bruker ls 0 0 28 may 2014 uncounted 9B9EE03158FF45AEA5
50. 1992 Carotenoids in salmon have been traditionally though of as precursors for the synthesis of Vitamin A Newer research suggests they may have a secondary function as anti oxidants Miki 1991 Salmons draw carotenoids from their diet although it has been suggested that salmon have the capability of metabolic intra converting these chemicals Haard 1992 Astaxanthine is the main carotenoid present in wild salmon in farmed salmon both astaxanthine and canthaxanthine accumulate in large amounts Christophersen 1989 Haard 1992 Astaxanthine can usually be found in the fillets of fish in its free form Carotenoids are considered unstable compounds and the exposure to heat or light in addition to oxygen leads to decomposition yet the stability of carotenoids in fish products is stil being Figure 6 The chemical structure of some carotenoids in salmon 1 r carotene 2 canthaxanthin 3 astaxanthin 4 astacene Christophersen 1989 investigated Christophersen 1989 There have been anecdotal reports that salmon fed natural sources of carotenoids have a better flavor then those fed synthetic sources Haard 1992 Yet beyond this astaxanthine and other carotenoids have not been shown to affect the flavor or odor of fish fillets Yet the red coloration they provide is a key factor in the quality assessment of salmonoid species Color and appearance are considered key characteristics for the quality and marketability of fish
51. 40 6 835 Chemical Shift ppm Figure 35 Peaks of tyrosine and tyramine 6 87 and 6 89 ppm from dataset S4 i EE TTT 6 930 Terr T T T TT T TTT TTT 6925 6 920 6 915 6910 6 905 6 900 6 895 6 890 6 885 6 880 6 875 6 870 6 865 6 860 T 6 855 THT TTT TTT 6 850 6845 6 Chemical Shift ppm 42 Figure 36 T5 of SO blue and S4 red overlaid The peaks of tyrosine and tyramine at 6 87 and 6 89 ppm 5 4 4 Others Acetate Z a JA I i JA ua a o l amp PN ax P FOE m ee aa 1 93 1 92 1 91 1 90 1 89 Chemical Shift ppm Figure 37 Change in the peak assigned to acetate at 1 91 ppm from S4 Figure 38 T5 of SO blue and S4 red for acetate peak at 1 91 ppm 5 4 5 Database analysis The Aurelia Amix database created was used to analyze spectra SO T5 and S4 T5 Table of results is presented in Appendix II 43 5 5 Discussion 5 5 1 General Figures 12 and 13 show complete spectra of the salmon fillets with selected peaks labeled Here a large peak at 1 32 ppm and a smaller peak at 4 11 ppm are clearly seen These were assigned to lactic acid The large peaks suggests that there are relatively high concentrations of lactic acid in the fillets There is a small development in both the height and in the difference of height in datasets SO and S4 with the peaks of S4 being slightly higher This suggests a development of lactic acid which is
52. A3 HOSTID 0021706e787a vendor info for hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 17 46 02 FEATURE SBASE 1 1 1 bruker_ls 0 0 28 may 2014 uncounted 9B2EF041040E90CF1D0C HOSTID 0021706e787a vendor info for X hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 17 46 02 FEATURE AURELIA3 0 bruker ls 0 0 28 may 2014 uncounted BB5E50516C4AD337B08E HOSTID 0021706e787a vendor info for hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 17 46 02 Screenshot 4 Content of lincese file Note the first line other lines are license specific and will vary The content of the first lines of the dat text file should look as shown in Screenshot 4 Once you have saved the file as license dat in the correct directory your version of Amix should be licensed and fully activated If for some reason the dat file is not supplied in the e mail or is already existing other license options are given in the how to install the license page on Bruker com https www bruker com fileadmin user upload 3 Service Support MagneticResonance NMR Hovw to install the license pdf 13 Getting Started After the installation of the Amix software package there should be two shortcuts on your desktop or in the directory which you have chosen under the installation The main functionalities described in this manual are in the Amix Viewer The icon titled Amix will directly open the Amix Viewer the other icon will
53. Base requires a specific directory to function which you need to create at Partition name data some name nmr The some name folder of the directory path can be titled anything however it is recommended that the ee e Qv gt Datamaskin OSDisk C data gt michael nmr gt Organiser v Inkluderi bibliotek Delmed Brenn Ny mappe Na Sir Favoritter age d Nedlastinger J Uracil Nylig brukt Ji Valine BB Skrivebord L KB test metabol KB ph7 Z Biblioteker Ssalar KB_H1C13 E Bilder s s salar_kbase 76 elementer gt 9 fl Screenshot 29 The open directory of the Knowledge Base with several Knowledge Base text files that the Knowledge Base will contain If you are working with E coli KB E coli txt This new text file will be the file containing the information of your Knowledge Base The folder nmr is also the easiest place to store the spectra which you want to analyze and all the raw spectral data which you have added to your Sbase This 1s discussed in the section on data analysis and file structure Section 6 3 Analytic Profiler version 39 14 BSBSMM 2273 wt Tom ARR BEB Attention lt lt click right mouse button to get basic infos gt gt directory name is related to the users name such as by name e g C data michael nmr Screenshot 29 In the directory folder titled nmr create a text file The text file can have any
54. D cosy TOCSY I msoc ICHS delta mass 0 lt Back Next Cancel noise level estimation Screenshot 52 The fourth window of the analysis asking you to specify Screenshot 54 the operation and the SBase E Details for spectra matching can be selected by the user 2D identification is done internally under full program control available 1D match options positional matches C match peak lists C match based on sub spectra lt Back e e is 1D Identification is based on spectra comparison techniques Various algorithas Cancel Screenshot 53 The fifth window of the analysis Here select what type of analysis to preform 103 The next window shows options for the quantification of compounds as said this is beyond the scope of this manual In this field do not check Perform 1D NMR quantification and Perform 2D NMR quantification and leave other settings at the default Screenshot 55 P E Noise level estimation WHR noise level handling fully automated noise handling C user defined level by number individual noise calculation user defined noise level po E noise area in 1H spectra 1D NMR left 0 ppa right 0 ppa noise factor 0 e g lt Back Cancel Next specify how the results should be displayed It is recommended to check the Show results in HTML style box Screenshot 56 This will after the analysis
55. DHCP aktivert Nei Automatisk konfigurasjon aktivert Tunnelkort Lokal tilkobling 11 Medietilstand Tilkoblin Medium frakoblet Microsoft Teredo tunnelkort 898 880 8080 880 80 080 88 E8 Nei Ja iC Users Dorothee gt Screenshot 3 The command prompt function used to aquire you computer data in Now you go back to the license dat Windows Note this is a Norwegian version of Windows here Vertsnavn Hostname and file sent by Bruker and open the file in a simple text editor like Fysisk adresse Physical address notepad You see in the first line the word FEATURE Your computer address needs to be attached in this text in front of the word FEATURE 69 At the start of the text document write the following lines SERVER your hostname your hostid physical address 1700 DAEMON bruker is T license Notisblokk Se Fil Rediger Format Vis Hjelp SERVER HF 30077 0021706E787A 1700 DAEMON bruker ls FEATURE TOPSPIN2 bruker ls 0 0 28 may 2014 uncounted EBS8E9011CFB6AEC88531 HOSTID 0021706e787a vendor info for hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 17 46 02 FEATURE TOPSPIN 1D bruker ls 0 0 28 may 2014 uncounted 2B5E8031B47A44EF524D HOSTID 0021706e787a vendor_info for hostid s 0021706e787a ISSUER 782bcbaal031 2014 01 28 17 46 02 FEATURE TOPSPIN 2D bruker ls 0 0 28 may 2014 uncounted 6BFEB02140A9B5912D3F HOSTID 00217
56. Displays total change in TMAO peak at 3 26 ppm Figure 30 On the right the two T5 spectra laid on top of each other Displays total change in TMAO TTTTTTTTTTTTTTTTTTTTTTTT TTTTTTTTTTTTTTTTTTTTT TTTTT TT TTT TT TTTTTT TTTTITTITT TTTTTTTTT TT TTTTTT TT T TTTT TTTTT TTTTTTTTTTTTTT TTTTT TT TT T TT T TT TTTTTT 3261 3260 3259 3256 3257 3256 3255 32 peak at 3 26 ppm 3 260 3259 3258 3 257 3256 3255 3 m ale Chemical Shift ppm 40 303 5 4 3 Biogenic amines The figures below show the change in selected peaks relating to lysine and cadaverine as well as tyrosine and tyramine The spectra are overlaid in ascending order with TO on the bottom 5 4 3 a Lysine and cadaverine 0 015 4 Lysine 1 4 0 010 4 dis easi A Re 3 scum bs gr ae 0 005 4 3 E 3 0 4 5 eS xe i 4 0 005 4 Normalized Intensity T T T T 3 025 3 020 3 015 3 010 3 005 Chemical Shift ppm Figure 31 The peak of lysine at 3 01 dataset SO 0 020 4 0 015 4 L 0 005 4 0 005 4 g Salmo 0 1 T5 esp B seo esp Lysine Cadaverine TTTTTITTUTTUTTTYTTTUTTUTyUTTTY 2 980 2975 2 970 29 Chemical Shift ppm 41 T T T T 3 025 3 020 3 015 3 010 3 005 3 000 2 995 2 990 Chemical Shift ppm Figure 32 Peaks of lysine and cadaverine at 3 01 ppm dataset S4 Figure 33 T5 of SO blue and S4 red overlaid Peaks of lysine and cadave
57. NANCES 1 i 35 i REGION 0 044786 0 066857 0 535185 0 753972 Add compound function SBASE COMPOUND NAME DSS standard MASS 218 320000 TOPOLOGY MATRIX 1 MAX COUPLING 18 000000 COUPLING TOLERANCE 0 400000 MULTIPLET INTENSITY TOL 0 200000 MULITPLET USE INTENSITY TOL 1 The window will contain the information added when the compound was METABOLITE RESONANCES REGION 3 889070 3 835790 propanediol 1 2 4 created in the Knowledge base Edit in these fields REGION 3 560520 3 497140 REGION 3 462670 3 393400 REGION 1 156660 1 096800 MULTIP M NAH SBASE COMPOUND NAME propanediol 1 2 MASS 76 095900 TOPOLOGY MATRIX and Amix will save the changes in your MULTIP M INTENSITY 1 INTENSITY C 0 T1 0 000000 INT F C 1 000000 OUANTIFY 0 IDENTIFY 1 KE MULTIP M NAME propanediol 1 2 propanediol 1 propanediol 1 INTENSITY 1 INTENSITY C 0 T1 MULTIP M NAME propanediol 1 2 propanediol 1 propanediol 1 INTENSITY 1 INTENSITY C 0 T1 MULTIP M NAME propanediol 1 2 propanediol 1 2 propanediol 1 INTENSITY 1 INTENSITY C 0 E propanediol 1 2 INTENSITY 3 INTENSITY C 0 T1 0 000000 INT F C 1 000000 C Knowledge Base when you confirm Screenshot 36 The Knowledge Base in coded format 94 The function Show Knowledge Base in the Knowledge Base drop down menu will show the Knowledge Base text file in coded format Screenshot 36 The content of the Knowledge base can be read from here but it is re
58. NMR peak at that characteristic position with a characteristic intensity To extract atomic molecular or structural information from NMR spectra firstly many peaks on the spectra have to be assigned to which nuclei are generating the signal This can be done by using reference data and databases example Biological Magnetic Resonance Bank BMRB at http www bmrb wisc edu or by using ones own 1D and 2D see Section 3 3 NMR spectra The use of specific NMR standard reference compounds of known concentration allows the determination of concentration of identified compounds This is done by comparing the height of the identified compounds signals to the height of the reference compound s signal 24 Normalized Intensity Salmo TO TS esp TMAO Lactic acid a aa E Ty 0 85 4 0 80 4 Lactic acid 0 7 5 res ATP AMP IMP Inosine Hx gt L 834 i 8 32 Q o J f RE 508 608 t 0 00 L T T T T T T T T T T T T T T T T T T T T T T T T T 10 5 10 0 9 5 9 0 8 0 75 7 0 65 6 0 5 5 5 0 45 40 3 5 3 0 25 2 0 1 5 1 0 0 5 Chemical Shift ppm Figure 11 A 1D NMR spectra from the case study in Section 5 3 2 Using NMR spectra As seen in Figure 11 NMR spectra are not displayed on a scale of Hz as would seem natural The frequency differences in the interaction of nuclei in different magnetic environments is o
59. NTNU Trondheim Norwegian University of Science and Technology Monitoring of metabolites and the spoilage of Atlantic salmon fillets An NMR approach Including a case study on the detection and analysis of metabolites during the storage of Atlantic salmon using NMR spectroscopy Michael Jonathan Beermann Teacher Education with Master of Science Submission date July 2014 Supervisor Oleksandr Dykyy IBT Co supervisor Elena Shumilina Department of Biotechnology Norwegian University of Science and Technology Department of Biotechnology Abstract English This thesis studies metabolites in Atlantic salmon S salar and their effect on the quality and the spoilage of the fish fillets Of special interest is how the concentrations of metabolites can be assayed using NMR spectroscopy and how metabolite concentrations can be used as a measure of quality and spoilage We have conducted a literature review that reflects the current state of knowledge about metabolites and their effect on the quality and spoilage of fish fillets Also some indices that are currently in use or have been proposed for the measurement of metabolite concentrations are presented In our discussion of the literature we suggest to further study metabolites and a combination of indices for the evaluation of quality and the state of spoilage of Atlantic salmon fillets NMR spectroscopy as a method has both advantages and disadvantages for the detection and
60. QC 40 You can use these self defined values in the experiment type field It is essential to use only one naming system for the whole database since these names will be used in search functions In general it is recommended to have a coherent set of rules for compound names and experiment types throughout your database The Amix software is very sensitive to names and directories and only coherent rules will make a search in your database efficient Also not that it is recommended to avoid capital letters and special characters as well as spaces when naming your compounds Special characters may sometimes be used to denote structure or confirmation yet these should be avoided were possible or spelled out in non capital letters In the following I will give an overview over the rules that I have used for naming compounds in my work with Amix 76 2 4 Naming rules No use of capital letters other then in compound abbreviations such as ATP or GABA No space or special characters other then underscore _ comma and hyphens whereby underscore serves to separate words All special characters relating to structure or confirmation such as a and B need to be spelled out Example a alpha and B beta Group position needs to be named at the end of the compound gt Group positioning will be separated from the compound name by a hyphen gt positions are separated from each other by a comm
61. RB FTP Access BMRB Mirror Sites Acvanced Searcn nm ff you have a query you would like to run on the BMRB database please e mail bmrbhelpg bmrb wisc edu Field Value to searchfor Display G Entry ID 7 O00090 PDB s OOTite 6 Author family name The BMRB project Mission statement BMRB Team BMRB HTCondor NMRFAM PDBj BMRB Citing BMRB News Events ISMAR ICMRBS ENC EUROMAR 2014 PANIC Servers hosted at CS Rosetia structure calculation CS Roselia Structures for BMRB entries Data visualization server STARch file conversion Ambiguity code Screenshot 38 The Biological Magnetic Resonence Data Bank homepage http www bmrb wisc edu home on the drop down menu To find the spectra of specific compounds use the search function on BMRB metabolomics home Screenshot 39 By default this page is set to search for compounds by their names but you can also search for compounds by mass structure peak lists or field strength It is usually sufficient and more effective to search for compounds by their names Enter the name of the compound into the search field select Synonym in the field Search for to enable to database to give Sbase Online databases also contain other data such as molecular mol files and peak lists of the compounds spectra to be used in the Knowledge Base The databases used with this manual are the Biological Magnetic Resonance Data Bank ht
62. These files can contain any text which preferably should not be long The files can also be accessed independently from the spectra and can be used to enter information about the experiment or the compound in question These files are not specific to one 3 Preparation version 3 oo ess Hel NMR spectra but are l S S22 SEET 00 4 amp 4 di ga x specific to the CP NP RETE T compounds to which data michael nmr Anserine i0 pdata i ir they are attached Edit the info file for this compound Imm EE Information you want File 7 loaded bytes from c S salar ref test info to enter here is for Enter text here example the functions of the compound experimental parameters such as pH or simply notes on compounds They can be created and edited after the compound has been defined although it is much easier to add them when you save the first spectra To add an info file Screenshot 14 An open info file This file can be used as a simple text document select the Edit compound info file in the Save spectra to Sbase menu This will bring up a text editor window Screenshot 14 into which you can write text Changes to the info file are saved automatically 79 2 7 2D Spectra Working with 2D spectra is a little more challenging than working with 1D spectra Open the Prepare data window and load the spectra into the windo
63. a Confirmation notation needs to be seperated by hyphen gt No capital letters are used in confirmation denomination Other compound prefixes suffixes are marked behind the compound name gt Separated from compound names by hyphen gt Numbers and other markings within the compound name remain Examples of rule application gt p Glucose glucose beta gt p Glucose 1 phosphate glucose 1 phosphate beta gt L Alanine alanine l gt 2 3 Butandiol butandiol 2 3 Once you have selected the proper Sbase and assigned a compound name to your compound as well as a experiment type you can attach Keys or info files to the spectra These options are covered in Section 2 5 If you wish to attach a key or a info file select these options and you will be directed to those functions This can also be done independently later but it is recommended that you do this at this stage since it is easier Otherwise select OK in the window without ticking any of the boxes and you have successfully saved your 1D specter 77 2 5 Keys Keys for specter function as search words They help you to search quickly for specific groups or types of spectra and they represent another level of organization that you can impose on your database Here an example All amino acids may have the key Amino acid In a search function to be explained later Section 3 you can search for all entries
64. adaverine peak from T3 to T5 can be clearly seen on Figure 32 it should be noted however that these peaks are magnified and are small in relation to those of the other metabolites suggesting only a low production of cadaverine Production of biogenic amines in Atlantic salmon has also been suggested to be due to bacteria Section 2 3 2 No significant changes in cadaverine concentration in S0 and only small changes in S4 suggest bacterial infection but also that the infectant is not very active at low temperatures As changes in cadaverine concentration have been correlated to the progression of spoilage the data here shows faster progression of spoilage in fillets exposed to higher temperature Figure 34 shows two peaks in SO at 6 87 and 6 89 ppm assigned to tyrosine The peaks remain close to constant from TO to T5 In dataset S4 seen on Figure 35 we can see the rise of another set of peaks on the 46 slope of the tyrosine peaks starting at T3 these new peaks were assigned to tyramine We can see a steady growth of the new peaks suggesting a steady production of tyramine in dataset S4 Again these peaks are small in relation to other metabolites Comparing the results no significant production of biogenic amines was found in dataset SO were as dataset S4 shows a production of biogenic amines even though their concentrations at T5 is very small based on peak height in relation to other metabolites Yet the production of biogenic amines
65. also be the terminology in this Propuction thesis Statistics suggest that the CP Inland 9 8 10 0 10 2 10 4 11 2 11 5 annual global production of wild fish marine 80 2 80 4 79 5 79 2 77 4 78 9 Total capture 90 0 90 3 89 7 89 6 88 6 90 4 has plateaued at approximately 90 X Aquaculture million tons per year as seen in Table ua 313 334 360 381 m7 443 1 The continuing rise of the world s Mee O Lo NM Total aquaculture 47 3 49 9 52 9 55 7 59 9 63 6 fish production can therefore be TOTAL WORLD FISHERIES 137 3 140 2 142 6 145 3 148 5 154 0 attributed to the increase in the world s Table 1 The total productions of the world s capture and aquaculture aquaculture production also shown in fish production FOA 2012 Table 1 There have been numerous studies comparing aquacultured fish products to wild fish products and a number of ecological problems with modern aquaculture have been detected Goldburg 2005 Naylor 2000 Discussing these problems or comparing fishery products to farmed fish products is beyond the scope of this thesis The increase in farmed fish has led to a large reduction in the price of fish worldwide lowering investments into fishing fleets and fishing efforts Yet because wild fish maintains a niche market there has been no significant decrease in the capture rates of wild fish With the sustained growth and the improvement of distribution channels for the world s fish production storage and spoilage
66. and experiment type and then save the compound Amix will also show you the compression factor used on the spectra by showing for example that the 40MB spectra was compressed to 0 1MB 2 8 Attaching molecular files After creating a compound you may add coordinate files to it which contain molecular information of the compound This is a way to display E Amix Viewer version 39 14 oles SS AM S ws Tl OMARAAWEMEE the molecular structure of the uu 5s VALS 084009 88 compound in the Amix Viewer as you open the files or on the upper left side of your spectra Screenshot 18 To do this you need to import coordinate files which are usually in the format Title mol This can be done from the Amix Viewer Open the Amix Tool drop down menu and navigate down to Spectral Base Here select Import coordinate file this will gives you a new window in which to select the location of the Screenshot 18 The display of molecular coordinate files in the Amix mol file you wish to import Once Viewer you have selected the file you wish to import you need to assign a compound name to in order to be able to attach this molecular file Select ONE compound Amix will look through the Sbase c S salar and return with a list of all r ATP 1 2 1 0 C10H16012N5P3 491 00 compounds which have the given n name Select the one you
67. ange in TMAO levels dataset SO at 3 26 ppm eere eee eee etes eese enses nen natns eta tnan 40 Figure 26 Change in TMA levels dataset S4 at 2 89 ppm 4 eres ee eese esten eese eee te seen tn seta stantis sons tn staat na o 40 Figure 27 Change in TMAO levels dataset S4 at 3 26 ppm eere eee eres eese e enata stesse natuss tuao 40 Figure 28 The T5 spectra of SO and S4 overlaid with SO on the bottom blue and S4 on top red Shows the final difference of TMA at 2 89 ppm Leser esee ee eee ee eene eene cossos seruro sro seta saote ossos sens ease easet osete sete sea ao 41 Figure 29 On the left T5 spectra of SO and S4 overlaid with SO at the bottom Displays total change in TMAO at 3 26 PPI o ence E teneo peso EE vV ores esae E iue oo pue eap e ER Y Suae Von iUe eB eU UNE Ee dea EUR PHP EVE enu e Uer ee EUH Pea dE V ues 41 Figure 30 On the right the two T5 spectra laid on top of each other Displays total change in TMAO at 3 26 uu GI 41 Figure 31 Peak of lysine at 3 01 dataset SO eee eee eee eee ee ee esee ee ee eee enne ens etate stint to etas etas etae s ttes ns eaa 42 Figure 32 Peaks of lysine and cadaverine at 3 01 ppm dataset S4 eere eret 42 Figure 33 T5 of SO blue and S4 red overlaid Peaks of lysine cadaverine 3 01 ppm 42 Figure 34 Peaks of tyrosine 6 87 and 6 89 ppm fro
68. are particularly important in species which during their life cycle migrate between fresh and saltwater such as salmon 2 3 1 Amino acid related osmolites As amino acid related osmolites we understand metabolites who s biological function relates to osmoregulation of fish cells and are derived from or structurally closely related to amino acids Some of these metabolites may contain elements of the amino acid backbone in their structure 2 3 1 a Anserine and Carnosine Produced by Histidine catabolism Produced in Liver cell and white muscle of some fish Function Buffering and also active in enzyme complexes Carnosine and especially anserine are major metabolites present in the Salmonidea and the Godoidea family Waarde 1988 Both of these amino acid related compounds are formed from the histidine catabolism by Equation 1 Equation 1 Histidine gt Carnosine gt Anserine Waarde 1988 The enzymes which catalyze this reaction have been detected in the liver of fish and in the white muscle of some fish species Waarde 1988 The levels of anserine in the muscle of fish remain close to constant even if the levels of histidine and carnosine vary Salmon fed with a histidine deficient diet deplete their levels of histidine and carnosine but their levels of anserine remains mostly unchanged Waarde 1988 This has led to the proposal that anserine is a metabolically inert form of the imidazole skeleton Waarde 1988 Both
69. as Alteromonas and Vibrio have been frequently associated with the production of TMA and TMAO in fish fillets Dalgaard 2000 Sikorski 1990 If fish is caught in polluted waters or if the production and storage conditions of the fish products are unacceptable other bacterial species can develop in the fish Many of these are associated with the production of biogenic amines and compounds leading to rapid spoilage Some species found in contaminated fish are S putrefaciens Enterobacteriaceae and Pphosphoreum Dalgaard 2000 Sikorski 1990 23 3 Introduction to NMR spectroscopy Nuclear magnetic resonance NMR spectroscopy is a technique that deals with the interaction between the magnetic moments of atomic nuclei and magnetic fields Kessler 1988 It has since its discovery become the single most widely used technique for elucidation of molecular structure Macomber 1988 NMR is based on the interaction of nuclei subjected to a strong external magnetic field and radiation The interaction can only occur for nuclei with a non zero nuclear spin which arises from an odd number of nucleons protons and neutrons considered separately in the nucleus Due to this fact NMR spectroscopy can only detect nuclei with odd number of nucleons in their nucleus During an NMR experiment interactions of the nucleons in the nuclei with radiation occurs at specific frequencies which are detected and displayed in the NMR spectra 3 1 NMR spec
70. ature for each spectra Screenshot 43 To download the complete set of data for each spectra press the Time domain data at the bottom of each spectra usually named spectra name tar This will begin the download of the datafile 2 bmse000028 L Alanine at BMRB wisc edu L Alanine C3 H7 N O2 L Alanine bmse000028 data bmseo00994 data bmst000272 theory Natural Isotopic formula weight 89 0931800000 View large 3D structure JSmol L Alanine zem Dn amp f Metabolomics home pu BMRB USDA standards Ali standards Synonym Search bmse000028 Data Entry STAR file bmse000028 str Time Domain Data bmse000028 tar l alanine Source Sigma a7627 Solvent 100 D20 Buffer 50 mM sodium phosphate Cytocide 500 uM sodium azide Reference 500 uMDSS Concentration and pH are given with spectrum Spectrometer Bruker DMX 400 MHz Data Source Madison Metabolomics Consortium Qiu Cui lan Lewis Gareth Westler Brendan Hodis Mark E Anderson John L Markley Assigned Chemical Shifts 1D1H Concentration 100 mM pH 74 temperature 298 K click on image for an expanded view Screenshot 42 A data page for L Alanine The parameters of the data are visible Alternatively right click each tar file and press Save link as in the resulting menu This will allow you to specify the download path for each spectra and enable you to directly targ
71. be the molecular structure folder under the compounds directory To view data on HMDB more relating to NMR navigate the compound page down to the spectra section Here select the link titled H NMR Spectra This will open the main page for the compounds NMR spectra Here are images of the compounds NMR spectra and assignment of its peaks Screenshot 47 along with other data such as the assignment of multiplets To download these image files for use go to the Documentation section and select the appropriate link right click the Download file hyperlink on the right to download the files to your computer To view a compressed form of the peak list assigned to the spectra left IN reyes e Human Metsbclere Datakare LH NR mad ca spectaspectre imy one d 112 al Pn amp f HMDB Browse Search Downluads Abou Contac Mstaooites s A search Image Details L Alanine HMDB00161 Nit 1H NMR spectrum 500 MHz in H O 4 o Sample 50 mM at pH 7 0 H c x Zi Referenced to DSS 36 OH 3 Full sH NMR Spectrum PT a j 5 Screenshot 47 The main page containing NMR information for L Alanine on HMDB click the Download file of List of chemical shift value for spectrum under the documentation section this will open the download link in your browser Here you find a table of peaks multiplets and peak types which can be used to manually fill in the peak information
72. bolites by their chemical properties NMR measures them by their isotope content this presents a number of advantages 29 Firstly rather than measuring one or a set of metabolites NMR spectroscopy measures all metabolites with set isotope content Considering the prevalence of H and PC in most metabolites found in fillets of Atlantic salmon and fish in general this is an incredibly powerful analysis tool One measurement of 1D and 2D NMR spectra presents the opportunity to detect from one set of data a large number of metabolites and to quantify these Secondly NMR is a fairly rapid and in use a quite simple analytic tool One set of measurements may require only several hours including sample preparation In this time rather than acquiring data on one or several metabolites the researcher receives a wide specter of chemicals in the fillets Thus even though other methods may be quicker in practice NMR provides a much larger amount of data for the time used NMR is in addition a very sensitive analysis method detecting metabolites at concentrations of the mM to the uM This is a advantage when analyzing fillets for chemicals with a low concentration such as nitrosamines or tracking changes of multiple chemicals over time such as in studies of change in metabolites over storage time Also since the data presented in NMR spectra is so extensive the spectra may be reused and reanalyzed in later research focused on other topics In r
73. breakdown Loss of texture and quality softer fillets more gaping The degradation of proteins into their constituent amino acid has a large impact on the quality of fish fillets The changes observed from the breakdown include softening of the fillets and more gaping Hultmann 2004 Breakdown occurs via proteases which can be classified as exopeptidases which degrade the proteins from their terminals or endopeptidases cleaving the internal bonds at specific points During degradation a protein is first broken into fragments by endopeptidases then degraded from each terminal by exopeptidases Urich 1994 It has been shown that the degradation of structural and muscular proteins in the fish leads to a loss of textural properties which are not considered desirable Hultmann 2004 The changes are usually not visible until after several weeks of storage This has been attributed to the stable actomysine formed during rigor mortis see Section 2 5 2 Hultmann 2004 Most textural changes during the spoilage process of fish are often attributed to protein breakdown Odor and flavor changes during spoilage are attributed to microbes and catabolism of non protein metabolites Hultmann 2004 As Atlantic salmon has been classified as a high protein fish see Section 1 2 it may be particularly affected by the textural changes arising from protein degradation in its spoilage process Studies investigating the content of free amino acids in At
74. cal Paper Rome Food and Agriculture Organization of the United Nations Jones N R 1967 Fish Flavors In H W Shultz E A Day amp L M Libbey Eds Symposium on Foods The Chemistry and Physiology of Flavors Vol 4 Connecticut USA AVI Publishing Company Karovi ov J Kohajdova Z 2005 Biogenic amines in food Chem Pap 59 1 70 79 Kessler H Gehrke M Griesinger C 1988 Two Dimensional NMR Spectroscopy Background and Overview of the Experiments New Analytical Methods 36 Angewandte Chemie International Edition in English 27 4 490 536 Li P Mai K Trushenski J Wu G 2009 New developments in fish amino acid nutrition towards functional and environmentally oriented aquafeeds Amino Acids 37 1 43 53 doi 10 1007 s00726 008 0171 1 McCormick S D Hansen L P Quinn T P Saunders R L 1998 Movement migration and smolting of Atlantic salmon Salmo salar Canadian Journal of Fisheries and Aquatic Sciences 55 S1 77 92 Macomber R S 1998 A complete introduction to modern NMR spectroscopy Wiley New York Miki W 1991 Biological functions and activities of animal carotenoids Pure Applied Chem 63 1 141 146 Mohamed R Livia S S Hassan S Soher E Ahamed Adel E B 2009 Changes in free amino acids and biogenic amines of Egyptian salted fermented fish Feseekh during ripening and storage Food Chemistry 115 635 638 Naylor R L Goldburg
75. case study Lo pe k pe jg Je js qm seo n m Jm Jm seo jo m m m jm js 5 2 3 Chemicals Deuterium oxide D 0 99 9 was purchased from Cambridge Isotope Laboratories Inc Andover MA Sodium 4 4 dimethyl 4 silapentane 1 sulfonate DSS de 98 atom D Trichloroacetic acid TCA 6 1 N and KOH from Sigma Aldrich 5 3 Method 5 3 1 Sample preparation Polar water soluble metabolites were extracted from the sample using trichloroacetic acid TCA at 4 C For this the 25g samples of fish muscle were added to 50 mL of 7 5 TCA and blended with a vertical homogenizer Ultra Turrax Ika The homogenized mixture was then filtered using filter paper Whatman N 4 Little Chalfont UK The pH of the extract was adjusted to pH 7 00 by the use of 9M KOH After this samples were stored at 80 C until the NMR experiment was preformed 5 3 2 NMR sample preparation 1 mL of sample was placed into a Eppendorf microfuge and centrifuged for 5 mins at 14k rpm to remove potassium trichloroacetate precipitate After this 800 uL of the centrifuged liquid was transferred to a standard 5mm NMR tube To this 160 uL of TSP were added to a final concentration of 1mM 33 5 3 3 NMR experiment 1 13 13 ID H ID C 2D TOCSY and C HSQC NMR spectra were taken at 298 K using a Bruker Avance 600 MHz spectrometer equipped with a 5 mm z gradient TXI H C N cryoprobe at the NMR center of the Faculty of Natural Sciences and Technology
76. ch for file option will search your computer for exiting Knowledge Bases Use the Open named file function to find the text file which has been created in the nmr folder Once you check this box the Knowledge Base field will become editable You may also browse your computer by selecting the downward arrow on the right side of the text box Navigate to and select the text file of the Knowledge Base and confirm This text file will remain the default setting for this window so that this process only has to be repeated each time you switch Knowledge Base or when you wish to define a new Knowledge base Once you have confirmed the E Analytic Profiler version 391 Saam 1 2 m 010 amp amp 8 BSR ge optiona average mass knovlegdge base sucrose Next gt Cancel Screenshot 32 Second window of the Add compound to Knowledge Base function 90 Knowledge base you wish to add information to another window appears Screenshot 32 This window will specify the name of your compound and establish its reference to your Sbase The top of this window contains the field Name of compound This will be the name of the compound given internally in the Knowledge Base and can be different from the compounds name in the Sbase but it is recommended to use the same naming system and the same names of compounds for simplicity You will also find checkbox
77. commended to simply use the edit compound function if you need to view the exact content of each entry You can also remove compounds from your Knowledge Base To do this use the Remove compound from Knowledge Base function under the Knowledge Base drop down menu This functions in the same way as the Edit confirm your text file then select the compound you wish to remove from a list of all compounds in the Knowledge Base When you confirm the selected compounds they will be removed from the Knowledge Base Note that you will not have to confirm the removal after selecting compounds from the list but note that after selection deletion is final 5 File structure and acquiring spectral data online The Amix software requires a specific file structure to function You may wish to store the raw spectral data independently of you Sbase for later use This section will show a simple file system for acquiring spectral reference data online from different databases We will also introduce a system which can be used to organize and store this data in relation to the Amix software file requirement 5 1 File structure As mentioned in previous sections Sections 2 1 and 4 1 the best place to store spectral reference data is in the C data some name nmr the file path which already contains your Knowledge Base text files and any spectra you wish to analyze later In the nmr folder it is recommended to create a subfolder for every
78. compound you wish to annotate in your Sbase and then to store all spectral data within this folder This can also be done with experimental data and the results of an analysis as show in Section 4 It is recommended that you decide which type of spectral data you will use for your reference compounds before you begin work on 3 atamaskin OSDisk C data michael nmr gt Cysteine EAE QGOo gt Datamaskin OSDisk C data michael gt Cysteine gt your Sbase After this Organiser v Inkluder i bibliotek Del med v Brenn Ny mappe c m Sa ee in Em define for each different avoritter s TES ads J Nedlastinger d 10 13 04 2014 B 2 Filmappe dataset a code which can E Nylig brukt ds 30 13 04 2014 1 Filmappe A x3 structure 13 am A im s i be used to identify it T Biblioteker amp j Bilder Lets us look at an Screenshot 37 The folder of compound cysteine with subfolders example If I wish to make an Sbase and use ID H 2D H H TOCSY and 2D H C HSQC spectra For this you will have to assign 1D H 10 TOCSY 30 and HSQC 40 First create a folder titled cysteine in the nmr folder on the file path shown above Within the new folder called cysteine you create four more folders titled 107 730 40 and molecular structure When downloading the 1D spectra for Cysteine you have to place them in the folder titled 10 in the cysteine folder You place the other spectra and the molecular stru
79. confirm you choice to attach the Key If you want to use a Key not yet defined check the last box titled new value and after this check the box Define new key below Screenshot 13 Now two fields below should become usable one titled Key name and the other Key value The Key name is the name of the Key which can later be used to quickly select the Key from drop down menus as explained above The Key value is the search parameter which you assign to your spectra When defining this it is 78 important that the Key value follows the same naming rules as the compound name of the spectra Section 2 4 this will make the Key more practical to use User defined Keys can also be added at any time after you have created a spectra For this go to the Amix tool drop down menu and navigate to the Spectral bases drop down menu In the lowest section of the menu you will find Add user defined key When using this function the spectra you wish to add a Key to has to be opened This is done through the Open file function as explained later Section 3 After this the Key definition window appears as explained above At the bottom of the Spectral Bases menu are also functions such as Rename or Remove user defined Keys These functions can be used to edit the Keys which you have created 2 6 Info files An info file is a simple text file that can be attached to compounds for additional information
80. considered sound proof of spoilage in fish and shellfish Biogenic amines are only present in trace amounts in fresh fish and due to their bacterial origin may be used as an indicator of bacterial spoilage Yet practically fish fillets with high concentrations of these chemicals quickly become stale and are easily rejected through sensory evaluation The risk of scombroid poisoning and other food intoxication through high concentrations of amines in fish samples underlines the importance of monitoring their concentrations Other hazardous chemicals such as the carcinogenic nitrosamines may also be present in Atlantic salmon fillets see Section 2 2 4 Even though the presents and production of these chemicals may be circumstantial their production may rapidly exceed the low tolerance limits of 3ug kg Prester 2011 Monitoring systems for these chemicals would provide greater consumer safety No index for the formation of TMA and TMAO has been found in the literature review Yet the importance of these compounds for the quality and spoilage of fish has been reviewed see Section 2 3 2 Limits for the content of TMA in fish fillets has been suggested at 0 001 1 00 mg 100g for prime quality fish and 7 01 mg 100g as upper limit for fish of acceptable quality Measuring the levels of these volatile compounds in Atlantic salmon fillets could lead to a greater understanding of fish odor during spoilage and may allow their use as an indicat
81. cribed to resemble the odor of ammonia It is believed that TMA acquires the fishy odor in interaction with lipids and other compounds found in fish Hebard 1982 TMA has been found in salmon caught in marine environment but not in concentrations exceeding 1mg 100g Also salmon caught in freshwater rivers do not show any presents of TMA in their flesh Hebard 1982 As Atlantic salmon do not produce TMAO reductase necessary for reducing TMAO to TMA and as other enzymes necessary for converting choline to TMA have only been shown to be active in the liver and kidney Waarde 1988 the production of TMA post mortem has been correlated to bacterial spoilage Simpson 2012 No correlation has been found between TMA production or concentration and bacterial count It is assumed that the production of TMA is dependent on the bacterial composition of the fillets and the storage conditions Hebard 1982 Spoilage with rapid production of TMA is quickly detected due to the unpalatable taste and the low odor threshold of the compound Due to the important role of TMA in sensory spoilage of fillets it has been suggested by Waarde 1988 to use TMA as a indicator of freshness Using TMA as a measure it would not be clear if the TMA is formed by bacterial degradation or by autolytic degradation of TMAO or choline Waarde 1988 Devising spoilage indexes based on TMA or on the relation of TMA to sensory spoilage has been attempted One correlation betw
82. ction with spectra visible in the background 34 Confirm this and Amix will extract as much information as possible from the spectra on the screen and add it to the appropriate fields All information should be manually checked for correctness as small errors may occur For Amix to automatically add molecular weight a molecular file needs to be displayed on the window see above how to add molecular files to compounds See Section 2 8 For Amix to add H and or C data the appropriate spectra needs to be displayed on the screen For this to function all the spectra on the screen need to display peaks at the same points H and C seperate If two H spectra display different peaks the Amix software will show an error which states that the spectra on the screen are ambiguous and therefore information could not be extracted In this case information either needs to be entered manually or the spectra need to be equalized Using the auto fill is a very quick and mostly accurate way of adding data to your Knowledge Base 93 4 5 Viewing and editing your Knowledge Base Compounds in the Knowledge Base can be edited and viewed both in code and in content after the entries T Analytic Profiler version 39 14 ere 64 G0 2265 wttTowmaad SEB edit compound DSS_standard propanediol 1 2 alanine beta AHP anserine arginine asparagine choline creatine cysteine diaminopropane 1 3 n glucose alpha glutama
83. cture data in their 95 respective folders under the cysteine compound folder Screenshots 37 This will allow for a quick and easy organization of the downloaded data and for easy storage later This structure will also create an uncompressed database of reference compounds which later can be used to create other Sbases or for data in other experiments Uncompressed spectral data requires a large amount of hard drive space especially when using several types of 2D spectra in your data 5 2 Downloading raw spectral data It is possible to download the raw spectral data of pure compounds for use in the Sbase from free online research databases The spectra of these databases should be processed and are then ready for use in the zysym s BMRB Biclogical Magnetic Resonance mibowscedu uj P E amp f 1 1 1 Member of p Biological Magnetic Resonance Data Bank wip wip BMRB A Repository for Data from NMR Spectroscopy on Proteins Peptides Nucleic Acids and other Biomolecules af d Your one 4 NMR Data Visualizations see more data GST Home About BMRB Search Validation Tools Deposit Data NMR Statistics Visualization options Single entry Two entry Restraints by PDB ID Chem shift histograms Speciroscopists Corner Visualization server Programmers Corner Visualization tutorial videos Metabolomics Educational Outreach NMR Data Formats Links to External Sites Search BM
84. d database tools in combination with NMR ceres 26 4 Discussion 4 1 On the importance of measuring metabolites cec eese ee ee ee eee eene eren enean etas ta sse tn asse tassa see 27 4 2 Objective measurement indices and freshness indicators c eee eee eee ee eerte e eren eerte nete 28 4 3 Objectyve measUte SilevissdsccsenccessesussSeosnnosnadsesccdseancsusevecoscdessedeenscenseesedsssbessscnsoesecedeasesuenscvesedeedssanedennssocese 29 4 4 Current teChmlQuess iscccccsscsssscscesensscsisssccsstescncevaccsuscdsescscesdecssassendstsuusesbbesseossesonccevesesvansosessssesssebvecevadsenad 29 4 5 Use of NMR as measurement tool 4 cesse cete esee eee eene en netta aeta soto esten aset ta eee ta se tones ense seen seen ss enna 30 4 6 Use of NMR software AMIX eee eere eerte eene eene eene vaos oost os6 sss soosoo stooo os Sros S skos tns eo KSS tense tense etas etna se 31 5 Case Study Detection and analysis of the development of metabolites during storage of Atlantic salmon using NMR spectroscopy 5 1 Introduction and background 4 eee eee eee sees eene eee en esten netos setas setas seta sets se tone etos setas sens sene 33 5 2 Experiment and chemicals eee eeee eerie eerte ee eee ee eee seen sten netta setas to sesto asse tn setenta etos seen sesta se taa 33 5 2 1 Purchase and preparation L
85. data included in the database were molecular structure common and alternate compound name and the 1D H 2D H H TOCSY as well as 2D H PC HSQC NMR spectra of most compounds A case study on Atlantic salmon fillets was presented in Section 5 It studied the relative concentration of some select metabolites based on changes in peak heights of NMR spectra Here a progressive degradation and production of several metabolites was found The literature review provided the background as it highlighted the importance of these metabolites to quality and spoilage processes of fish fillets As goals for future work we suggested that the concentration changes of the metabolites should be quantified This also holds for their relation to quality This could be approached both in regard to their final concentration and to their rate of change using subjective methods It has also been proposed that even though NMR spectrometry has restrictions such as cost and the need of dedicated space and trained personal that it can be a useful tool for the further analysis of metabolites since it provides a large amount of data using only a few reading Also such data can be verified in multiple repeated experiments using the same sample 49 NMR would be a useful tool to develop a compiled index of quality and freshness based on the existing indices and other chemicals deemed relevant With NMR such chemicals could be simultaneously assayed and with analysi
86. data must be stored in netCDF format 10 expno COSY 21 expno HSQC lao expno 1D expno TOCSY 30 expno LCMS so expno JRES 400 used for advanced quantification The spectra of the pure compounds are loaded from SBASE match those of the Knovledge base 11 be used for analysis of spectra selected above SBASE experiment type settings 1D 1dnosey cosy eesyss d2o 7 Tocsy tocsy HSOC 2dhsqc Peak fiting needs to know the average lineshape The following single peak is used to determine the lineshape peak position 5 04 ppa Low Cancel Screenshot 48 The Configure Profiler function format the spectral file has To do this go to the Analytical Profiler window in the Amix Viewer Here select Configure Profiler in the Profiler drop down menu This will open a window with settings specifying how to connect compounds from the Sbase and how to locate sample spectra on your computer Screenshot 48 In the top section of this window specify the code you have given your spectra If following the example in Section 5 all directories containing 1D spectra will have code 10 specify 10 in the expno 1D field This will guide the Amix software to the location of the spectra In the fields below specify what you have used as experiment type in your Sbase For example if all 1D 101 spectra used in the Sbase are given experiment typ
87. databases All parameters of these spectra such as pH should be equivalent and as standard as possible The NMR spectra in the Amix software will function as reference for the identification of peaks in new spectra therefore the use of pure compound samples is important when creating spectra 1 2 Installation of Amix The installation of Amix proceeds in two steps First one needs to install the software on a computer then a license agreement for the software has to be obtained The license agreement can be obtained before the installation of the software and may be kept on a different computer than the one on which the Amix software has been installed The Amix package can be downloaded from Bruker s home page www bruker com where one navigates to Service in the top bar selects software downloads from the drop down menu and selects NMR spectography An account has to be registered on the Bruker homepage this is done simply by entering personal information such as name institution and email address into the appropriate fields Bruker will send an email to the registered account to confirm your account One now can log in using the registered username and password 67 This gives access to the download page from which you can select your operating system Windows Linux or Macintosh Note that the Amix software is only available for Windows and Linux Select your platform and in the next window select AURELIA AMIX This
88. degradation of ATP to IMP other indices have been suggested which do not use ATP ADP or AMP Some of these indices include K1 value G value Fr value and P value Some of these indices have been found to better match specific fish species or be more applicable to either farmed or wild fish Tejada 2009 2 6 Post mortem changes The post mortem changes are here considered the overall biochemical changes which occur in the fish fillets after death of the fish 2 6 1 Post mortem pH Cause Glycogen and ATP catabolisms and low buffering capacity of the fillets Effect Low pH Fillets have a firmer texture associated with sour stringent taste in some species High pH Fillets have a softer texture and are dry The post mortem pH of the fish fillets is governed by a number of factors These are the glycogen and ATP catabolisms mentioned above Sections 2 5 1 and 2 5 2 and the inherent buffering capacity of the fish muscle caused by amino acids and other metabolites such as anserine see Sections 2 2 1 and 2 3 Sikorski 1990 Sikorski states that the pH of commercially caught fish is usually not lower then 6 2 Sikorski 1990 other studies placed the pH lower but generally agree with his results showing pH of 6 18 6 32 Hultmann 2004 and pH 6 15 6 30 Einen 2002 It has also been proposed that the rate of the post mortem pH decline is of interest not only the final resting level Haard 1992 The pH has direct effects on the
89. dit store is available Perform 1D NHR quantification Perfora 2D HSQC quantification ype of quantification calculate relative concentrations absolute absolute absolute concentrations concentrations concentrations calculate calculate calculate single weights file weights file at spectrum create new weights file file containing absolute weights C SsUsersNDorotheeZweights Scaling of quantification results to defined reference compound in knowledge base C to temporarily selected compound s in knowledge base 75254 c Q e lt Back Cancel Screenshot 55 The seventh window of analysis Here you select option for quantification Generate Result Display and Report Final results of a compound profiling process can be displayed and reported Reports are stored in different styles to disk Anyone of these can be selected for display iv Show result in HTML style Select Report for display C short detailed Discard results from report C report all results report results only if high match factor C report the N best results per mixture report if high matches in all mixtures for PCA 1 lez 100 discard threshold max number of results per mixture Result path C data michael nar saaple_1 results Save in result path automatically includes mprofile 1dbt txt can be used for PCA macros txt mprofile xmal ca
90. down of amino acids can occur by endogenous enzymes or by bacterial proteolysis The rate of breakdown and the products of non nitrogenous compounds depends on the fish species conditions of storage and the bacterial environment which develops 2 2 3 Biogenic Amines Occurs by Mainly the decarboxylation of amino acids also from amination and transamination of aldehydes and ketones Important Produces Histamine cadaverine putrescine tyramine Effects These compounds have hazardous health effects and their concentration increases parallel with progression of spoilage Biogenic amines BA are non volatile aliphatic alicyclic and heterocyclic organic bases of low molecular weight produced in fish by bacteria through decarboxylation of free amino acids Bulushi 2009 Biogenic amines may also be formed from the amination and transamination of aldehydes and ketones Karovi ov 2005 Biogenic amines have been labeled a hazard due to their toxicological effects causing the dangers arising from the consumption of spoiled fish The most common biogenic amines and their precursors are found in Table 4 Many biogenic amines such as histamine seratonine dopamine and tyramine have powerful physiological effects BA s histamine cadaverine putrescine and i tyramine are also implied as the main causes of food Biogenic amine Precursor EN intoxication due to the ingestion of fish products Aliphatic amines These BA
91. e 10 or 1dnosey specify this in the field titled 1D Also all spectra of one group such as all 1D spectra should be labeled with the same experiment type in Sbase Once you have filled out all fields with the correct data example see Screenshot 48 confirm Now you should be ready to analyze your new spectra Open the Analytical Profiler window from the Amix Viewer The analysis of spectra function is located in the Profile drop down menu as the Profile function at the bottom of the menu This will bring up a window with options for what type of input data you B amp 5UcT2295522 OM RAR 55m Screenshot 49 The window in which you specify you spectra location wish to use for the analysis here check the TOPSPIN data tree option and continue with the next button In the following window Amix requires the exact location of your spectra and its title Screenshot 49 Specify the location of your spectra on your computer using the fields given Using star will leave the field blank and the field will not used this field in the search Given you use C data michael nmr_ enter C into the field titled Partition data into the Data directory field michael into the user name field nmr into the spectroscopy field into the Dataset name field 10 into the Experiment field and into a
92. e SBASE functions which allow you to browse and open files from your Spectral database We describe these functions in Section 2 of this manual To open spectra in the Amix Viewer you can either use the open function or simply drag the spectra file into the Amix Viewer window Screenshot 6 Shows a blank window of the Amix Viewer to display the spectra Once the spectra is open in the main window it is possible to zoom the spectra both vertically and horizontally The manual access to these functions is found on the top bar above the spectral window Screenshot 7 The arrows pointing away from each other allow you to zoom the spectra in the direction indicated by the arrows The arrows with bars on either side return the spectra to its original state When zooming click the arrows and then click and hold your spectra approximately at the point that you wish to make more visible Moving the mouse holding down the left mouse button will zoom the spectra in the direction selected You can also use shortcuts for the zooming function If your mouse has a mouse wheel this will function as a vertical zoom Mouse over the spectra and move the mouse wheel and the spectra will automatically zoom in the vertical direction Horizontal zooming can be done by holding down the left 71 mouse button and highlighting a section of the spectra When you let go of the mouse button the Amix software wi
93. e confirmed the 3 Analytic Profiler version 39 14 o e jus information in the compound 4 M2242 wttomaoa sem name window a new window should come up which will l hi 2 Description of well defined signals of a compound ce zi bd enable you to enter the exact 1H left 1H right 13C bottom 13C top protons shape couplings keep T1 name ppa ppa ppa ppa nuaber S D 7 0 12 1 ident quant ratios s peak information for each ES A o a ip a a C compound Screenshot 33 e 3 GENE DR m Here are separate boxes for a s 3 ppt 05 0 3 aser as left upfield and right 5 A Bo i NN downfield shift of the H sw 0e o UE peak ranges and for the C zwar fo EET reet peak ranges all given in ppm It 1s not required to add both 1 13 Hang C peak Screenshot 33 The third window of the Add compound to Knowledge Base information but one of them function Here you add the peak information of your compound is required to analyze a 91 spectra for peaks The boxes of each field will except input in format of numbers using a period to separate the decimals Screenshot 33 You can also in boxes further to the right specify proton number peaks shape and the names of the peaks in the field furthest to the right It is recommended to enter the peak shape but proton number and name of the specific peak are optio
94. e data was used to create a database of the metabolites found in Atlantic salmon using the Aurelia Amix software version 3 9 14 Bruker Germany For this a database of reference spectra for each metabolite was created Data used included 1D H 2D H H TOCSY and 2D C HSQC spectra Reference spectra were acquired from data published on BMRB Biological Magnetic Resonance Data Bank and HMDB Human Metabolome Database All reference spectra are at pH 7 using DSS as reference compound 34 Normalized Intensity 5 4 Results The complete spectra of SO and 13 below Salm TO TS esp Normalized Intensity ATP AMP IMP Inosine Hx 8 34 JE 8 32 8 23 712 6 09 6 08 Li 4 80 o Jaslu lus FPP PT PY FPP FT PT PPP PP PP PP PP FP FFP PPP PP PP PP PP FPP PP FPP PF FP PP PP PT 5 Juul 0 154 TMAO 22 Lactic acid J Lactic acid 1 33 131 T 0 00 and S4 with TO and T5 shown and selected peaks labeled is seen on Figures 12 Figure 12 The NMR spectra of dataset S0 with TO and T5 overlaid on the same spectra TO is shown in blue T5 in Chemical Shift ppm red Salm4 T0 5 esp TMAO Lactic Acid 10 4 0 9 4 08 4 Lactic acid 07 4 0 6 4 0 5 4 04 4 0 3 j 92 4 AMP Inosine HX li 01 4 leg ge jJ E 3 T 35 i T Ui a 0 1 oad pii u
95. ecce eee ee esee e eese e eee ee enne tense ta stone stans seen seen sees s tasse toss seen setas etna 33 JA purge 34 5 223 Chemicals p L nisse osos 34 M n P 34 5 3 1 Sample preparatiOM NTC 34 5 3 2 NMR sample preparation csscccscscscsscccsccsscesssscecescscscccescccssccsssscecsecesscsscsscsssccesescessscesssesseseseeses 34 5 3 3 NMR experiment e 35 EU ADEE OY K TT aa AAE E 35 M A LIT T L EEE 36 5 4 1 N cleotides 37 54 2 TMA TMA O mr E 40 5 4 3 Biogenic AMINES e M 42 5 4 3 a Lysine and cadaverine 1 eee e ee eese eese eene seen seta neto esst ovos sc Eoss so sistr oro sviso soouss enost 42 5 4 3 b Tyrosine and tyramine eee eee eee ee sees ee enne seen etta netos tones tense etna seta setas stone setas seta sete ne sena 43 MICE RI 44 5 4 5 Database analysis E sisses 6ov psov s osoosu dos t65 Vvo VE 6S v voso EVV oS Soo 5 Osos SSSK Essa so aSa 44 S 5 DISCUSSION EEA EAEE A E 45 DSL ESCE a 1 ME ATE E A E E A T EEEE 45 5 5 2 N clegtid s E 45 5 5 2 TMA TMA O sssvccsesteiascstecvacssenstessassensondsnsceatedsonstasenshacse
96. een TMA concentration and sensory evaluation of fish set TMA levels to 0 001 1 00 mg 100g for grade 1 fish judged to be of prime quality 1 01 7 00 mg 100g of TMA for grade 2 fish of acceptable quality and 7 01 mg 100g or above to fish of unacceptable quality Hebard 1982 Yet due to the variation in TMA and TMAO levels in various fish species and the variation with season and age found it has been concluded that freshness measures based on TMA are too unpredictable and become inaccurate Hebard 1982 The use of DMA and formylalderhyd as measure for spoilage has also been suggested Hebard 1982 Yet this process of DMA and FA formation are only common for fish in the gadoid order Under the right conditions the nonenzymatic endogenous breakdown of TMAO may occur yet this breakdown is to unreliable to provide a measure for freshness 2 4 Anti Oxidants Anti oxidants are here considered metabolites which protect the fish tissue and cells from oxidation by attack from free or bound oxygen radicals 2 4 1 Carotenoids Produced by Ingestion and further intra convertion Functions precoursors to vitamin A and anti oxidants Effect Coloration of salmon meat Salmonoid species accumulate the oxycarotenoid astaxanthine as main carotenoid smaller amounts of canthaxanthin r carotene lutein tunaxanthine and zeaxanthine have been found Christophersen 1989 These metabolites give salmonoids their red flesh pigmentation Haard
97. elation to other methods NMR spectroscopy is a nondestructive method that is the sample is not consumed in the process Once the sample has been analyzed in the spectrometer it may be stored frozen 80 C and reused if required NMR experiments thus can be replicated allowing control measurements to be preformed on samples a long time after the initial measurement A further advantage is that as samples are not consumed during a NMR experiment they can be shared with other institutions promoting replication control and further research on measurements For a NMR spectra taken from Atlantic salmon fillets and an analysis of metabolites represented in spectras see case study Section 5 For a table of the NMR peaks assigned to specific metabolites in Atlantic salmon see Appendix II A restriction of NMR spectrography as a method is that it is expensive The equipment must be stored at a dedicated facility and operated by trained personal Also analysis of spectra requires training or automated software Due to the generation of a strong magnetic field and the cooling required for this operation NMR measurements also require large amounts of electricity which increases the cost In summery NMR spectroscopy is a very powerful tool for the analysis of Atlantic salmon and other fish It requires dedicated facilities and trained personal but it gives access to data representing a wide range of metabolites This is especially useful for monito
98. emoval Sikorski 1990 As ATP is depleted after death of the fish the calcium pumps fail as their energy source is depleted This will result in the accumulation of Ca ions in the sarcoplasm and lead to the formation of actomysine Tejada 2009 In resting muscle the concentration 21 of Ca is usually below 1077M at a concentration of above 10 6 M rigor mortis sets in This is usually caused by a ATP concentration of below 10 M Sikorski 1990 The onset of rigor mortis is usually accompanied by a drop in the pH of the fish fillets as expense of ATP is caused by a buildup of lactic acid 2 N and organic phosphate see Section 12 2 5 and Section 2 5 2 E 10 4 8 The course of rigor mortis in fillets 1 6 which on catch are limp and pliable is that they turn stiff and inelastic as E r a d z T io en pee e aridas a result of the formation of the 29 20 40 60 80 100 inelastic actomyosine Sikorski Cold storage time hours 1990 Tejada 2009 As stiffness of the fish fillets increases it is also Figure 10 The course of rigor mortis in Atlantic salmon fillets measured accompanied by a shortening of the by fillets shortening raw fillets at storage temperature 0 C shown as fillets if the fillets are not attached solid line and frozen thawed fillets shown as dotted line Einen 2002 to the spine Tejada 2009 Einen has shown a shortening of 14 initial length of Atlantic salmon fillets cut before
99. er i laks Selv om NMR spektroskopi har begrensninger sa gir denne metoden store mengder n yaktige data i fa fors k og anbefales til videre bruk i studiet av metabolitter og 1 eventuell utvikling av indekser for kvalitet og bedervelse i fisk For videre understreke denne konklusjonen har vi gjennomf rt et case studium med NMR data fra Shumilina 2014 av fileter av atlantisk laks lagret over tid ved forskjellige temperaturer I denne studien har vi analysert dataene for metabolitter fra litteraturstudiene og trukket konklusjoner om filetenes kvalitet og bedervelse Dedication I hereby wish to thank my coordinators Prof Oleksandr Dykyy and Dr Elena Shumilina for their kindness patience and continued support of my work Without their guidance this thesis would not have been possible I also wish to thank my family for their love support and encouragement Their help was invaluable and their regular encouragements and support helped me to overcome many problems Finally I wish to thank my good friends for their understanding their support and for sometimes not taking no for an answer They consistently reminded me that sometimes rest is as important as work and they ensured that having enough of both was an essential part of writing this thesis Preface The database created for this 30 point master s thesis is available on request and can be acquired from Dr Elena Shumilina or Prof Oleksandr Dykyy at the Norwegian University of Sc
100. ere eee ee eee e esee eee ee enne enne etas tns stone setas setas e ennu 101 66 1 Introduction In this manual we will demonstrate the use of the Amix software by Bruker This software is designed for the analysis and storage of information obtained by NMR spectography The manual explains the use of the Spectral Base Sbase Knowledge Base and the Analytical Profiler This manual uses Amix version 3 9 14 In addition we use the Human Methabolome Datebase www HMDB ca and the Biological Magnetic Resonance Bank http www bmrb wisc edu as a source for sample spectra molecular data peak lists and other information needed to establish the database It should be noted that the Amix software requires very specific input information This means that the software is very sensitive to any change in filename directory paths and to the use of special characters Adding a space behind a filename or a period instead of a comma will give wrong search results A directory path requires a specific format which is dependent on your operating system This will be discussed later in the manual 1 1 Use of Amix Aurelia Spectral Base and Knowledge Base The combination of a Spectral Base and a Knowledge Base in the Amix software allows for the quick analysis of new NMR spectra for any compound that has been annotated For the annotation it is recommended to use NMR spectra of pure compounds which can be from one s own research or from online
101. es titled Type of compound with the choice of Reference compound and Normal compound For adding compounds select normal compound as an option Every Knowledge Base needs a reference compound but this will be covered in the next section There are also several text fields The Compound name in Sbase field has to be filled and is the link which the Knowledge Base creates with your Spectral Base In this field fill the name which the compound has in your Sbase This also requires that you create the entry of the compound in the Sbase before you add it to the Knowledge Base If you for example want to add L Alanine to your Knowledge Base and this compound is titled alanine l in your Sbase then you have to add alanine l in the compound name in Sbase field while you can still use L Alanine in the Name of compound field The comment and html page fields are optional and are used to give extra information on each compound and will not be described in this manual Below these is the average mass field here you can fill in the molecular mass of the compound you are adding This information is not required for simple analysis as discribed in this manual The field below Screenshot 32 shows the Knowledge Base you are attempting to add the compound to this should be preset from the previous window but it is still possible to change into which Knowledge Base you place the compound After you hav
102. et the directory of each compound with the downloaded spectra Also peak lists for the specific spectra are given For this press the View spectra peak list button this will open a separate window with the peak list W bmse000282 Alanine at BMRB b wisc edu r Natural Isotopic formula weight 89 0931800000 View large 3D structure JSmol Alanine Time Domain Data PBD tf i Pom 1H 5 tar 1D 1H 2 0 mM Concentration 2 0 mM pH 7 4 temperature 298 K click on image for an expanded view Screenshot 43 One of the spectra from L Alanine main page on BMRB Download link is highlighted If you wish to download all spectral data for one compound press Time domain data at the very top of the webpage this will download all spectra below The files are downloaded in a rar which is a compressed file format You will require a file compression software to decompressed the files into their original format Some spectra may not contain the Ir 1D or rr 2D spectra in their files This is then unprocessed data and needs to be processed before using it in the Amix software 98 The Human Metabolome Database HMDB is useful to obtain further information on compounds Rather then being able to download the data files for each spectra this webpage contains additional information for me Human Metabolome Database hmdb ca HMDB i
103. ffect of metabolites on the quality and spoilage of fish fillets through a change in the fillet s sensory characteristics or their effect on human health if consumed We shall furthermore report on indices which are currently used or have been proposed for the measurement of freshness based on metabolites Groups of metabolites discussed will be Proteins and amino acids Section 2 2 several key osmolites Section 2 3 carotenoids Section 2 4 1 carbohydrates Section 2 5 1 and ATP Section 2 5 2 Indices introduced will be K value Section 2 5 3 a the BAI and AI Section 2 2 3 We will also discuss some biochemical post mortem changes in the fish fillets resulting from the change in metabolites Here we will include the post mortem pH Section 2 6 1 and rigor mortis Section 2 6 2 In Section 3 we will introduce NMR spectroscopy as a method to detect and quantify metabolites in fish products Here we introduce NMR Section 3 1 and the spectra it produces Section 3 2 and we will briefly cover more advanced methods of NMR spectroscopy 3 3 We will also introduce the practical use of NMR in biochemistry 3 4 including the use of software Section 3 5 Our discussion in Section 4 will deal with some implications of our review in Section 2 We will discuss some requirements for an index of quality and spoilage in fish and the use of several metabolites for such a measurement Sections 4 1 and 4 2 We will also list some common
104. hts of TMA peak at T5 of SO and S4 compared to each other The production of TMA in the fillets is a sure indicator of spoilage progression as TMA has been associated with unpleasant odor and taste see Section 2 3 2 Steady production of TMA as seen in S4 indicates a rapid loss in quality The concentration of TMA produced in SO seems to be low yet at which point TMA induces symptoms of spoilage should be investigated quantitatively The production of TMA in Atlantic salmon has been attributed to bacteria see Section 2 3 2 The production of TMA in both sample indicates a bacterial infection of the fillets The source of this infection could be the 45 fillets contact with the extremities of the fish skin gills guts or infection during processing see Section 2 7 The rapid production of TMA in S4 illustrates the importance of temperature to fish storage If the production of TMA is the result of bacterial infection it also underlines the importance of hygienic processing and handling of fish TMAO concentrations remained mostly constant in dataset S0 as seen on Figure 25 with possibly a small decline at T5 Interestingly the concentration of TMAO in dataset S4 is quickly declining after T3 as seen in Figure 27 Figure 26 shows the TMA concentrations in S4 begin to rise at T3 and seem to rise in correlation with the fall of TMAO concentrations This could be a sign of the reduction of TMAO to TMA Figure 5 by bacteria as suggested
105. i 3 Select from spectra bases c S salar select spectra by name properties keys peaks etc name and properties compound name alloved experiment type 1D 2D allowed compound name pee experiment type ia evaluate keys evaluate peaks evaluate molecule evaluate spectrum title search string in spectrum title string Cancel Screenshot 22 The Open file from Sbase fuction window with the compound name sucrose Likewise if you want to open all spectra with Experiment type ldnosey you need to enter a into the Compound field I dnosey name and into the Experiment type field and confirm This will generate a list of all 1D spectra saved in your Sbase The list of spectra which Amix will display shows the directory path of the spectra in the form c Sbase name ref compound_name experiment_type file_type cpr Screenshot 23 From the path you can see the compound and experiment type this will help you select the right spectra Select the spectra you want and press confirm To select multiple spectra hold the ctrl key and click the spectra The AutoSelect button will automatically select all spectra on the list Using the properties function to search your Sbase will allow you to check one or several boxes W Amix Viewer version 39 14 File f Patter lea Hm 22 tUZASMNOBOSESES
106. icators for freshness and quality have been proposed yet only a few have proven to be useful 27 In our literature review we have introduced several indices proposed for the measure of freshness and quality Some of these indices are in use for specific species of fish were as others are still under evaluation The creation of one objective index is very hard to achieve considering the variety of species and biochemical changes For this reason we can focus research on one species in order to to avoid false generalization The literature review has further shown that mono nucleotides are an important quality factor for the flavor of fish Section 2 5 2 To measure this effect the K value index Section 2 5 3 has been developed This index and the measures of Hx amounts in fish are probably the most useful indicators of freshness Sikorski 1990 Even though this factor is limited by the fact that an increase in K value and Hx is due to endogenous enzymatic degradation and possibly also bacterial degradation in fillets Thus the measure also depends on the bacterial flora and is not always linear with the endogenous enzymatic breakdown Another index shown is the biogenic amines index BIA see Section 2 2 3 This index measures the change in biogenic amines in the fillets usually caused by bacterial decarboxylation and breakdown of amino acids According to Sikorski 1990 the presents of significant quantities of biogenic amines is
107. ich allows you to choose which Sbase you would like to search and a text box for the compound name Enter the compound name you wish to search for and confirm Amix will return with a list of compounds select the compound you want and confirm Amix will then show a list of all the spectra under the compound select the spectra you want to open and confirm to open it 3 1 Opening multiple spect ra Amix has the ability to open multiple spectra at the same time for comparison or other functions To do this first configure how you would like to display multiple spectra Go to the Config drop down menu next to 86 the File menu and select Input options This will give you a list of choices for input Screenshot 27 Checking Put objects into new window will open a separate window of the Amix Viewer for every spectra that you open choosing replace all objects in current window will allow you to open only one spectra at a time replacing the old spectra with the new spectra Choosing add objects to current window of same type will add all spectra to the same window of the Amix Viewer It will also D Ami Viewer version 39 14 overlay spectra of the same File Config Analysis Patterns Measure Amix Tools 4S UM 225 Set Tom AQQ AV x type with multiple colors and SYALS amp I S00 98 place spectra of different types in separate sections of the Viewer Screenshot 28 This
108. ience and Technology NTNU VI Table of contents jo xoMbE E EE XII List of FigUreS PEPEIPC XIII 1 Introduction 1 1 Fish production an overview 4 ceres eee esee eene eene eren eerta netta soto asta sse t tasse tn se tones to ss seen sss en assess etna 1 1 2 Atlantic salmon Salmo Salar ee eee ecce ette eee ette ee eene tena aset eh ese etta sese tease se etae sese eaae se eea sese teta a 2 1 3 Quality spoilage and freshness eee ee esee etes sette eren eene eren setae tn nest tn set tn sette se eos se tones eene seta seen Deae 3 i ennt 5 2 Metabolites pa WB e x es 6 2 2 Proteins Their degradation and amino acid Catabolism eee ee eee ee esee entente seen sten atn nee 6 22 1 AMINO iur M 7 2 2 2 Amino acid degradation eee eee ee tees ee eene eene eee en osoo Koos teos SEs setas ees setas se toss se soovi ososi sena 8 22 3 BiOSEMIC ATIINES mE M 8 2 2 4 Nitrosamines and their formation from biogenic amines eese eese eee ee eere eren ener tn etn nae 11 ZS OSMOMIMES 12 2 3 1 Amino acid related osmolites e sseossossesssesssossoossocssoosoosssossoossosssoesssesseossesssessoossoossoossosssosssosssssssee 12 2 3 1 a An
109. imited The functions are available from the Amix tool drop down menu under the Spectral Base menu The functions at the top of the Spectral Base menu Create new Register and Remove relate to the Sbase in general For example the Remove function here will remove the entire Sbase with all entries The Register function is used to import Sbases from other computers into this Amix software this will be shown later The Remove spectra Rename spectra and Copy spectra functions in the Sbase drop down menu relate to editing your individual spectra Note that it is only possible to remove and rename spectra To edit the information in the spectra after they have been created is not possible When renaming or removing spectra click the appropriate function This will open the same search window which is used by the Open file from Sbase function explained above Section 3 1 Use this window to find the compound you wish to rename or remove by giving search parameters and then select the spectra you want to edit from the list given by Amix After selecting the spectra to be edited during the rename function you will be given a window with Compound name and Experiment type fields that may be edited Make the changes to the name or type in these fields and confirm to save The Remove spectra functions in the same manner You have to find and select the spectra you wish to delete using the
110. is 3 Definition of input handlin IEEE P g m Input options C put object into new window side by side C replace all objects in current window exchange the best option for comparing C add object to current window of same type overlag replace last object in current window replace all several spectra with each other or opening several different K Cancel specter types of one compound for comparison Choosing replace last object in window will lock all spectra Screenshot 27 The Config drop down menu for configuring input to Amix except the last one to be Viewer opened in the Viewer Opening new spectra will only exchange the last spectra to be opened with the new spectra while maintaining the old This is a very useful function for comparing one spectra 8 Amix Viewer version 39 14 e Jt 3 2 2 BIT Om amp amp amp SL 7g S AE xx YALA FT son ae with multiple other spectra The replace all option will replace the new spectra with all other spectra open in Amix This includes spectra in other windows Screenshot 28 Several 1D and one 2D spectra open in Amix Viewer with the add objects to current window of same type setting 87 3 2 Removing rename and editing Spectral Base entries Editing of spectra after they have been entered into the Sbase is l
111. ki Z E 1990 Seafood Resources Nutritional Composition and Preservation Taylor amp Francis Simpson B K Nollet L M L Toldr F Benjakul S Paliyath G Hui Y H 2012 Food Biochemistry and Food Processing Wiley Sveier H Lied E 1998 The effect of feeding regime on growth feed utalisation and weight dispersion in large Atlantic salmon Salmo salar reared in seawater Aquaculture 165 333 345 Tejada M 2009 ATP derived products and K value determination In H O Rehbein J Ed Fishery Products Quality safety and authenticity pp 68 88 New York Blackwell Publishing Ltd Urich K 1994 Comparative Animal Biochemistry Berlin Springer Verlag Visciano P Schirone M Tofalo R Suzzi G 2012 Biogenic amines in raw and processed seafood Frontiers in Microbiology 3 Waarde A V 1988 Biochemistry of non protein nitrogenous compounds in fish including the use of amino acids for anaerobic energy production Comparative Biochemical Physiology 91B 2 207 228 Wishart S D 2008 Metabolomics applications to food science and nutrition research Trends in Food Science amp Technology 19 9 482 493 Young A Morris P C Huntingford F A Sinnott R 2005 The effects of diet feeding regime and catch up growth on flesh quality attributes of large 1 sea winter Atlantic salmon Salmo salar Aquaculture 248 59 73 Zaman M Z Bakar F A Selamat J Bakar J
112. lantic salmon during cold storage have found only a small increase in the total content Hultmann 2004 found an increase of total amino acid content in ice stored vacuum packet fillets to rise from 15 2 1 0 umol g to 17 9 1 7 umol g This suggests low activity of exopeptidases as proposed by Hultmann 2004 or the occurrence of a simultaneous catabolism of free amino acids 2 2 1 Amino Acids Effects on quality Important to the overall flavor providing sweetness bitterness and a meaty flavor Interacts with MP and AMP Elimination of glycine Leads to a loss of sweetness and an increase in bitter flavors Amino acids play an important role in the overall flavor of fish products Haard 1992 Sen 2005 In some fish species individual amino acids may be prevalent enough to affect flavor individually For Atlantic salmon Table 3 shows the concentrations of individual amino acids matched with their individual flavor thresholds As seen only the concentration of alanine is above its lower flavor threshold Amino acids rather enhance the overall flavor in combination with other molecules Jones 1967 and have been shown to interact with IMP and AMP nucleotides Specifically glycine valine alanine glutamic acid and particularly methionine have been found to be important in the interaction with mono nucleotides contributing to a sweetness bitterness and a meaty character Jones 1967 Elimination of glycine for example
113. ling by one and two dimensional NMR analysis of complex mixtures Progress in Nuclear Magnetic Resonance Spectroscopy 28 2 161 219 Fan T W M Lane A N 2011 NMR based stable isotope resolved metabolomics in systems biochemistry Journal of Biomolecular NMR 49 3 4 267 280 FOA 2012 The state of the world Fisheries and Aquaculture Fisheries and Aquaculture Department Rome Food and Agriculture organization of the Untied Nations 51 Goldburg R Naylor N 2005 Future seascapes fishing and fish farming Frontiers in Ecology and the Environment 3 21 28 Haard N F 1992 Control of chemical composition and food quality attributes of cultured fish Food Research International 25 289 307 Hebard C E Flick G J Martin R E 1982 Occurrence and Significance of Trimethylamine Oxide and Its Dericatives in Fish and Shellfish In R E F Martin G J Hebard C E Ward D R Ed Chemistry amp Biochemistry of Marine Food Products Connecticut USA AVI Publishing Company Higman V 2012 21 11 2012 Protein NMR A Practical Guide Retrieved 22 06 2014 2014 from http www protein nmr org uk Hultmann L Rustad T 2004 Ice storage of Atlantic Salmon Salmo salar effects on endogenous enzymes and their impact on muscle proteins and texture Food Chemistry 87 31 41 Huss H H 1995 Quality and quality changes in fresh fish Fisheries and Aquaculture Department FAO Fisheries Techni
114. ll remaining fields Screenshot 50 Confirm with the Next button Now Amix will search the specified directory for all files with the title specified and it will return a list of all matching files If you have followed the setup specified above and entered in the Dataset name field the list should contain all spectra added to the database If you wish to search for one spectra specifically add the name of the folder which contains the spectra into the dataset name field For example if you spectra are in the folder titled Sample 1 in the C data name nmr file directory specify Sample 1 in the Dataset name field and Amix will search only for this folder elm Next gt en Screenshot 50 A prefilled window for data location on your computer based on example in manual Once the spectra to be analyzed has been correctly selected the next window of the process requires from you to specify which Knowledge Base should be used in the analysis Here browse and select the text file 3 Analytic Profiler version 3914 E Umoe2es iv x0oe amp uao SEA Analytical profiling of pure compounds in mixtures includes identification and quantification Information about the compounds aust be provided in textual fora kno To create and fill a knowledge base use the available commands in th Knowledge Base pulldown menu wledge base
115. ll zoom into that area To return the spectra back to original the manual buttons still have to be used Access to most other windows is through the Amix Tool drop down menu on the top middle Here the three main functions are the Analytical Profiler the Spectra Base drop down menu and the Prepare data function The Analytical Profiler is what we will later use to create a Knowledge Base of compounds and to identify compounds from a spectra The Spectral Base drop down menu is used to modify information in the Spectral database after the initial entry has been made Here one can edit and rename spectral entries attached molecular files and information files as well as keywords which can be used for search functions The Spectral Base drop down menu also serves to create new and to remove old databases Here you also register imported Spectral Bases from other Amix users into your version of Amix These functions will be explained in detail later in the Spectral Base section Section 2 of this manual Prepare data is the main window used for preparing and entering NMR spectra into the Spectral database 2 Spectral Base SBase The main purpose of Sbase is to organize spectra into groups and to attach data to these spectra or groups of spectra such as molecular data list of peaks on the spectra or information files for groups The program also offers the possibility to effectively search th
116. m dataset SO eee eee eee eeee eene tnane 43 Figure 35 Peaks of tyrosine and tyramine 6 87 and 6 89 ppm from dataset 4 eese 43 Figure 36 T5 of SO blue and S4 red overlaid Peak of tyrosine and tyramine at 6 87 and 6 89 ppm 43 Figure 37 Change in peak assigned to acetate at 1 91 ppm from S4 esee eres esee ee eerte eene ntn ae tntna 44 Figure 38 T5 of SO blue and S4 red for acetate peak at 1 91 ppm eeeeeeeeeeee esee ee ee eee eene tenete nano 44 Figure 39 The K value for SO red and S4 blue Shumilina 2014 ecce eere eee e eterne nnn 46 XII 1 Introduction 1 1 Fish production an overview The Food and Agriculture Organization of the Untied Nations states that fish constitutes an important source of nutritious food and animal protein for much of the world s population FOA 2012 Fish and fish based products represent a rich source of high quality proteins amino acids vitamins and minerals Mohamed 2009 which accounts for 16 6 percent of the world s total intake of animal protein in 2009 FOA 2012 This makes fish and fish products a crucial contribution to the world s wellbeing and prosperity FOA 2012 The consumption of seafood has increased globally This is especially true for countries which traditionally do not consume seafood Prester 2011 The total annual production of the fishery and aquaculture industry
117. mine Prester 2011 Most biogenic amines seemed to have no direct effect on flavor odor or texture of the fish fillets although the presents of bacteria which produce BAs causes fillets to seem stale Sikorski 1990 Histamine has been implicated in a pungent flavor in fish Jones 1967 Other amines such as cadaverine and putrescine are beside their medical effects of interest only as the markers of spoilage not as the causative agents 10 2 2 4 Nitrosamines and their formation from biogenic amines Produced by The reaction between secondary and tertiary amines with nitrite Important products Nitrosopyrrolidine NPYR nitrosopiperidine NPIP nitrosodimethylamine NDMA Effect These compounds have hazardous health effects as they are carceogenic The formation of BAs may lead to the production of carcinogenic nitrosamines These compounds are formed through reactions between secondary and tertiary amines with nitrite present in the fish Bulushi 2009 Prester 2011 Nitrosamine compounds are non detectable in fresh fish Prester 2011 yet may develop through further processing and storage Cadaverine and putrescine have been implicated in nitrosamine formation with chemicals commonly used for coloring flavoring and preservation of fish Bulushi 2009 Prester 2011 Nitrosamines formed from putrescine and cadaverine are nitrosopyrrolidine NPYR and nitrosopiperidine NPIP Prester 2011 Nitrosodimethylami
118. mix software Amix software dataset SO T5 dataset S4 T5 DSS andar E T T Arginine i 42 90 42 70 m t t Asparagine 37 95 26 49 Propanediol 1 2 20 34 40 18 Alanine beta 2 55 21 06 29 19 3 18 i i Methylhistidine 1 56 Taurine 3 25 t 62 19 56 09 3 42 t Proline 27 26 30 77 Creatine 3 03 96 66 96 84 3 92 GABA 1 89 19 48 22 61 2 29 3 02 Ornithine Oxoglutarate 2 42 2 99 Spermine 1 53 1 67 2 68 Anserine N 9 No Serine nN D N Acetate Lactic Acid oo LI nm Tryptophane Phosphocreatine La T 96 66 96 84 3 92 57 a No Citrate 2 66 2 53 Glycogen 51 09 54 09 43 69 41 28 59 01 32 89 E a D glucose 6 20 12 19 77 phospate l 58 oo N N S S S N 2 m m q dd t t dd d d m t tm m brs t m m d m m m dd d a aatgtatcge ATP 8 13 S 25 55 24 08 8 49 S ADP dd 64 87 62 86 dd dd Nicotinic acid Niacinamide Cadaverine 1 35 1 49 2 68 35 62 27 04 1 3 2 11 m 40 85 41 77 diaminopropane 3 11 t Choline S 26 35 26 53 3 51 t 4 05 ddd Ethanol 1 18 t 41 65 54 56 3 66 q 3 14 15 27 01 di 3 0 42 79 57 39 8 Ethanolamine 13 3 81 Uracil 5 80 7 53 Isoleucine Leucine Valine 65 16 59 78 84 14 83 85 38 76 42 59 p 11 88 10 41 14 19 35 60 21 76 14 07 60 Threonine Lysine Methionine Phenylalanine Glutamate Glutamine
119. modern methods of NMR spectroscopy Chemistry amp Biodiversity 2 2 147 177 Bulushi I A Poole S Deeth H C Dykes G A 2009 Biogenic Amines in Fish Roles in Intoxication Spoilage and Nitrosamine Formation A Review Critical Reviews in Food Science and Nutrition 49 4 369 377 Castejon D Villa P Calvo M M Santa Maria G Herraiz M Herrera A 2010 HHHRMAS NMR study of smoked Atlantic salmon Salmo salar Magn Reson Chem 48 693 703 Cavanagh J Fairbrother W J Palmer III A G Skelton N J 1995 Protein NMR spectroscopy principles and practice Academic Press Christophersen A G Knuthsen P Skibsted L H 1989 Determination of carotenoids in salmonoids Zeitschrift f r Lebensmittel Untersuchung und Forschung 188 5 413 418 Dalgaard P 2000 Fresh and Lightly Preserved Seafood In C M D J Man A A Ed Shelf Life Evaluation of Foods pp 110 1139 Gaitherburg Maryland Aspen Publisher Inc Einen O Guerin T Fj ra S O Skjervold P O 2002 Freezing of pre rigor fillets of Atlantic salmon Aquaculture 212 129 140 Espe M Rathore R M Du Z Y Liaset B El Mowafi A 2010 Methionine limitation results in increased hepatic FAS activity higher liver 18 1 to 18 0 fatty acid ratio and hepatic TAG accumulation in Atlantic salmon Salmo salar Amino Acids 39 2 449 460 doi 10 1007 s00726 009 0461 2 Fan T W M 1996 Metabolite profi
120. muscle enzymes into IMP inosine 5 monophosphate The degradation of ATP to IMP is rapid and usually completed 2 days after death of the fish Sikorski 1990 Further degradation involves the breakdown of IMP to inosine Ino hypoxanthine Hx xanthine X and finally into uric acid U see Figure 8 The breakdown of IMP is a slow process and is the rate limiting step of the cycle hence IMP accumulates especially in the NH 2H muscle of the fish Tejada 2009 7 a E ru A m N N In relation to quality it is accepted that TUE in n N N gt LS nobosopoen T A o Hc nucleotides play an important role in the o oct v Si S HO OH H OH HO C flavor of fish Tejada 2009 IMP is the ATP IMP ma most important nucleotide in relation to b 5a quality and gives a pleasant sweet Ribose Ribose 1 Pi eee as 02H20 taste contributing to a fresh flavor pain aer Y JI h 2 J Y This flavor is maintained even as the ud Aii meat is cooked Tejada 2009 The degradation of IMP in the fish Figure 8 The degradation of ATP Huss 1995 muscle is correlated to a loss of typical desirable flavor of fresh fish Sikorski 1990 The resulting compounds Ino and Hx are usually associated 18 with the production of less desirable bitter flavors Tejada 2009 Also the degradation of IMP to Ino and Hx is correlated to bacterial growth Tejada 2009 In addition to the direct effects the presents
121. n be used inside statistics lt Back Cancel e Jer confirm with OK Now Amix will begin to scan the selected spectra for each compound specified in the Knowledge Base and use the annotate peaks in Knowledge Base to match to the peaks in the selected spectra When complete the program will automatically open a HTML file in your Internet browser containing the results of the analysis Every spectra is shown with a separate table The table will always contain the reference compound on top followed by all compounds you specified to be looked for in the spectra The 1D Screenshot 56 The last window of analysis Here you select how you wish to display results 104 match column contains the percent match of the peaks in the Knowledge Base to the new spectra If done correctly a sample will give a over 99 percent match to the spectra in the Knowledge Base if it contains the compound Screenshot 57 a file C data mich esults mprofile html file C data michael nmr sample_1 results mprofile html a c Se P BD amp f AMIX Analytic Profiler version 3 9 14 Created by Dorothee on HF 30077 Fri 2014 04 25 21 05 45 B Calculation Parameter Knowledge base C data michael nmr S salar KB H1C13 txt created Fri 2014 04 25 20 41 48 by Dorothee used SBASE c S salar Underground removal applied filter widht 20 0 Hz region 10 00 0 10 ppm region for offset correction 10 00 9 00 ppm 1D NMR
122. n the level of one to hundreds of a Hz Measuring such changes in Hz is inconvenient and thus a more appropriate measure of chemical shift sign 8 was introduced This scale measures the change in frequency chemical shift in parts per million ppm This scale is not only much more convenient considering the magnitude of the change but also independent of the magnetic field strength used and thus gives a standard scale usable independent of instrumental settings Highman 2012 3 3 Isotope interaction and 2D NMR As presented above NMR spectroscopy results in a spectra displaying the frequencies of all interactions with NMR active isotopes in the sample Even though NMR spectroscopy 1s sensitive enough to differentiate between the chemical shift of isotopes which are similar magnetic and molecular environments are not completely separated Chemical shifts of some signals may overlap and NMR active isotopes may also interact with each other to further complicate NMR spectra This is especially true for spectra of complex mixtures of chemicals or those from large molecules such as proteins The most common types of interactions between nuclei are scalar spin spin couplings J couplings and dipolar couplings Kessler 1988 J couplings are resultant of the interaction of isotopes through chemical bonds and lead to a splitting of the peaks giving rise to a multiplicity of the peaks It occurs only between 25 isotopes which are separated
123. na nea rone nh enhance raa eene Nene Soo ant orae Unna e na csesesdoes 16 Figure 7 The Embden Meyerhof Parnas pathway Sikorski 1990 e cene e eee eee etes eren eren enne tane tnaenos 17 Figure 8 The degradation of ATP Huss 1995 eerie eee eee ee esee esee eee einen ettet ta stint tn etas etas e tasse teste sten eta ao 18 Figure 9 The development of post mortem pH over time raw fillets at storage temperature 0 C shown as solid line and frozen thawed fillets shown as dotted line Einen 2002 c eeeeeeeee ecce eee eren 20 Figure 10 The course of rigor mortis in Atlantic salmon fillets measured by fillets shortening raw fillets at storage temperature 0 C shown as solid line and frozen thawed fillets shown as dotted line Einen 200 A EA E eaput edt Rn ER A tulit teu simui ten neta dE 22 Figure 11 A 1D NMR spectra from the case study in Section 5 eese e eee eerte reset teen tn sta stna tnus 25 Figure 12 The NMR spectra of dataset SO with TO and T5 overlaid on the same spectra TO is shown in blue HESSE GU P 36 Figure 13 The NMR spectra of dataset S4 with TO and T5 overlaid on the same spectra TO is shown in blue DEG 36 Figure 14 The change in Inosine and IMP 8 23 and 8 22 ppm respectively for dataset 37 Figure 15 The change in inosine 8 34ppm for data
124. nal information In addition the text boxes ident and quant are defined The identification check box ident needs to be checked to preform an identification of compounds in a new NMR spectra The quantification quant will enable Amix to preform a quantification operation on identified compounds in new spectra It is not in the scope of this manual therefore it should not be checked The peak information added in this section can be read directly from example spectra or it can be obtained from peak lists online such as on the Human Methabolome Database HMDB How to obtain peak lists online will be shown in a later section Section 5 2 If there is not enough space to enter all the relevant peaks of a spectra then select the most relevant peaks which enable the identification of the compound and enter these The more unique these peaks are to a given compound the higher pro cent match Amix can generate in a random spectra as shown later Section 6 Once all relevant peaks have been entered into this window confirm by pressing next in the bottom right of the window This will save the compound to your Knowledge Base 4 3 Reference compound Every Knowledge Base needs to have a defined reference compound to function The reference compound serves as a reference point for the program and can help as a tool for troubleshooting Also when analyzing new spectra the Amix software will always attempt to identify the reference c
125. ne NDMA is formed from DMA produced by the breakdown of TMAO see Section 2 3 2 and nitrite Bulushi 2009 Little is known about the mechanisms governing the formation of nitrosamines or about the impact of storage conditions on the formation of these compounds Bulushi 2009 The presents of crude impure salts has been implied in affecting the formation of nitrosamines as well as heating of fish fillets Prester 2011 Tolerance limits for these chemicals have been under discussion yet 3 ug kg has been cited as limit Prester 2011 Nitrosamines may not be directly involved in the spoilage of fish yet they play an important role to the TMA Cadaverine Putrescine DMA Piperidine Pyrolidine Bacterial reduction of nitrate salts Nitrite salts ee Impure salts idl Nitrosodimethylamine Nitrosopiperidine Nitrosopyrrolidine Figure 3 The formation of nitrosamines from various compounds Bulushi 2009 quality due to their association to cancer Thus further research regarding the mechanisms of formation and monitoring of nitrosamine is in the interest of researchers consumers producers and health authorities Bulushi 2009 2 3 Osmolites Osmolites are here understood as metabolites which help govern the osmotic balance and pressure within cells These chemicals help fish adjust to changes in their environment s concentration of salt and other chemicals Sikorski 1990 Waarde 1988 Therefore osmolites
126. noise handling automatic Discard results by match 1 0 8 compounds tested 2 discarded Reference compound DSS_ standard Spectrum C data michael nmr Test 10 pdata 1 1r title ZGCPPR mmcd clem D2O opt topspin216 mfjofre 1 A1 101 AMP 49 96 GABA 11 23 inosine 4 57 threonine 100 00 dopamine 5 86 Screenshot 57 A complete analysis with results This example spectra contains threonine as only this gives a over 99 match 105
127. npleasant fishy odor and an unpalatable taste Interacts with Assumed to interact with lipids Trimethylamine N oxide TMAO is a compound primarily found in fish and shellfish of marine origin It is one of the most important osmotically active non protein nitrogenous compounds in many marine species Hebard 1982 Urich 1994 TMAO from freshwater fish is with a few exceptions of negligible concentration Hebard 1982 Regenstein 1982 TMAO has also been suggested to effect the total buffering capacity of the fish muscle yet this would not be of great biological Phospholipids importance as TMAO would only effect the buffering capacity below pH 6 Waarde 1988 Choline Diet TMAO content varies between fish species but also varies with factors O2 NAD H20 such as season size and age of the TEM 8 a Pp fish and environmental conditions to TMA TMAO which the fish is subjected Hebard bu uc dd Sy 1982 It has been demonstrated that DMA FA TMAO in Atlantic salmon is of exogenous origin possibly utilized _ uu Figure 5 The metabolism of TMAO and its derivatives Waarde 1988 from their diet Salmon in their freshwater lifecycle stages contain no significant amounts of TMAO whereas wild marine salmon contain TMAO Hebard 1982 Also young Atlantic salmon raised in a marine environment show some TMAO when fed a diet containing the chemical and show no trace of the chemical when their diet lacks the osmolite Hebard
128. nsumption due to degradation or chemical change The evaluation of the quality and the spoilage or in other words a determination of freshness of salmon is commonly based on several methods of objective sensory evaluation which often uses grade sheets of specifically defined characteristics and trained personal to evaluate the quality of the fish Dalgaard 2000 These methods have a number of limitations such as being expensive and time consuming and difficult to calibrate Dalgaard 2000 thus instrumental assessments are needed to replace or compliment the sensory evaluation Instrumental methods measure microbial chemical biochemical and other changes in the fish to produce a more objective measure of its quality It is important that such methods are convenient to use rapid and inexpensive Dalgaard 2000 One of the most commonly used techniques for measuring several factors of biochemical change within fish is High performance liquid chromatography HPLC Tejada 2009 HPLC is also the instrumental technique which 1s used by the EU to measure levels of potentially hazardous chemicals in fish Prester 2011 1 4 Outline of the thesis In this thesis we will present a review of the scientific literature that focuses on metabolites in Atlantic salmon S salar We are particularly interested in the metabolites biological function and their biochemical and microbial degradation The literature will be studied concerning the e
129. o00236 D Alanine cH up ionore beta Alanine Y bmse000159 Screenshot 40 Search results for alanine on BMRB beta Alanine z The database will give you the best alternatives for your search displayed in a table showing the name of the compound its molecular structure its ID number in the BMRB database and its synonyms Screenshot 40 This table should help you to pick the right compound in relation to confirmation and other factors To select a compound press the entry in the BMRB ID field Clicking the entry will guide you to the main page of the compound seen for alanine in the Screenshot 41 The main page contains general data of the compound its molecular structure and links to other chemical database entries of this compound Also on the top of the page there are several tabs marked with bmrbIDcode data these will contain the spectral datasets If there are several tabs for one compound they represent several datasets and it could be useful to surf through all to determine which is the most suitable Under each dataset tab is the spectra data for the pure compound On top of the page is the technical data for the measurement of the spectra usually containing information on solvent and the buffer used and which instrument has been used to obtain the data Under this is a field labeled Assigned Chemical Shift this will open a new browser compound To the left of the
130. of your Knowledge Base 100 6 Using Amix to analyze new NMR spectra This section will demonstrate how to use the created Spectral Base and Knowledge Base to analyze ID NMR spectra for any number of compounds which are annotated in the Amix system It is important that the spectra to be analyzed exists in the 1r file format 6 1 Placement of the file and setting of Amix To analyze spectra the data of the spectra has to be placed in the directory at the end of the file path C data some name nmr in which you also have located your Knowledge Base text file After following the recommendation of this manual you will have the raw data of all compounds added to the Amix software in this directory Create a new folder for the spectra that will be analyzed The folder can have any title yet it is recommended that the title be easily recognizable such as sample 1 In this new folder create other folders with the same structure as used for the raw data of compounds Place the data you wish to analyze in folders with the identification code that you selected Following the example in Section 5 you will place the 1D H data in the folder titled 10 For Amix to analyze unknown spectra the software first has to be given the location of the spectra and what m 2es et tom 9 9 SEB Analytical Profiler Rulebase be located in different lature for all samples Optional LCMS
131. oilage experienced by the consumer and the actual chemical state of the fish meat Important factors in the consumer experience of fish quality are safety nutrition flavor texture odor color and appearance Dalgaard 2000 Norman 1992 Waarde 1988 Safety refers to the perceived adverse health effects for the consumer of the product Nutrition refers to the perceived beneficial effects of fish consumption Concerning the flavor and odor characteristics it is difficult to characterize good flavors or odors since these factors are highly subjective yet bad flavors and odors are considered those described as rotten and are factors leading to a sensory rejection of the fish Texture 1s considered as the firmness of the fish specifically in fillets so that soft fillets are considered a problem by the fish industry Hultmann 2004 Color and appearance are also subjective yet color may be one of the primary reasons consumers accept fish products of some species Haard 1992 One should also note that the relative importance of any characteristics depends on the specific product and its intended use Haard 1992 This means that there is no one set of desired characteristics as such quality measures depend on preferences consumer attitude and methods of preservation and consumption Haard 1992 Spoilage can also be evaluated at a biochemical level and can be considered as the point at which the product 1s unsafe or unfit for co
132. ompound regardless of what compounds are selected for identification Therefore it is recommended that the reference compound is a simple compound with preferably as few peaks as possible It is best to use a compound with only a main peak at 0 ppm such as DSS standard as reference compound if possible To make a reference compound first prepare and save spectra of the compound you want to be the reference in the Sbase as shown in the sections in Section 2 then follow the procedure for adding this compound to the Knowledge Base also explained in Section 4 2 Yet instead of selecting Normal compound in the checkboxes select Reference compound instead A Knowledge Base can only have a single reference compound If you try to define a new reference compound for a Knowledge Base which already has a defined reference compound you will be questioned if you want to define this as the new reference compound If you accept the reference compound will be switched and the old reference compound will become a normal compound entry One of the advantages of having a reference compound with only a zero peak is that if you analyze new spectra Amix will always find the reference compound as long as the spectra has a peak at Oppm This will show that the software is working and that it is attuned correctly 92 4 4 Auto filling the Knowledge Base It is also possible to use Amix to auto fill information into the Knowledge Base For this func
133. oms such as difficulty breathing and anaphylactic shock Bulushi 2009 Mohamed 2009 Visciano 2012 Strict limitations for the content of histamine in fish products are in place Some species of fish which have naturally high levels of histidine such as the Scombridae Clupeidae Engraulidae Coryfenidae Pomatomidea and Scombresosidae families are routinely monitored for histamine levels Prester 2011 Atlantic salmon which has been stored at abusive temperatures for extended periods of time has been shown to contain 255 mg kg of histamine Visciano 2012 Also Tyramine has adverse health effects Ingestion of tyramine of levels above 1080 mg kg can cause migraine and hypertensive crisis Prester 2011 Biogenic amines putrescine cadaverine spermine and spermidine have been shown to have no adverse health effects Yet the breakdown of these biogenic amines in the human digestive system competes for the same enzymes used to breakdown histamine and tyramine mono and diamine oxidase MAO and DAO Thus they potentiate the toxic effect of the ingestion of both histamine and tyramine It should also be noted 9 that histamine and tyramine are also broken down by the same enzymes they thus potentate each other Prester 2011 In addition to the health effects described above which greatly effect consumer perception of quality it has been suggested to use BAs as an indicator of spoilage It has been found that x Histidine 2
134. ones you wish to open and confirm Screenshot 25 You can also generate a list of 1dnosey spectra from all 20 amino acids This can be done by entering Select ONE file from list 2 files c S salar ref alanine 1ldnosey 1lr cpr KEY amino acid amino acid c S salar ref alanine tocsy rr cpr KEY amino acid amino acid AutoSelect Unselect Cancel into the Compound name field entering Screenshot 25 Search results for compound name alanine Idnosey into the Experiment type field and by checking the Evaluate search key box Continue and you are directed to the User key window here select key amino acid or enter this manually Amix will 8 Amix Viewer version 39 14 atterns Sms tz ot 10 ULVASAGDIEOGESG generate a list of all RAAY ldnosey spectra labelled Be AS RI with amino acid select a compound which you Select ONE file from list 21 files fe 7S salar ref7alanine idnosey ir cpr KEY_amino_acid amino_acid c S salar ref arginine ldnosey 1r cpr KEY amino acid amino acid le S salar 7ref asparagine 1ldnosey lr cpr KEY amino acid amino acid c S salar ref aspartate ldnosey lr cpr KEY amino acid amino acid Screenshot 26 If the le 4S salar ref citrulline l 1dnosey lr cpr KEY amino acid amino acid c S salar ref cysteine ldnosey lr cpr KEY amino
135. opy and to show the metabolic change of chemicals in Atlantic salmon we have preformed a study on the decay of metabolites in Atlantic salmon using data from our lab Shumilina 2014 5 1 Introduction and Background The study of Atlantic salmon meets a high commercial interest by consumers and producers established in Section 1 It should also be noted that fresh samples in Norway are easy to obtain The present case study needs to be read in the light of the literature review in Section 2 Central for our case study are the levels of nucleotides Section 2 5 2 TMA and TMAO Section 2 3 2 lysin and cadaverine as well as tyrosine and tyramine discussed in Section 2 2 3 In Section 2 it became clear that all of these factor are important with regard to quality and spoilage We will also attempt to show the development of rigor mortis Section 2 6 1 We will analyze the change of the metabolites and draw conclusions concerning the samples state of quality and the progression of spoilage In the spectra presented below the heights of the peaks correspond proportionally to the concentration of the chemical in question see Section 3 for further detail on NMR spectroscopy We evaluate the changes of the metabolites concentrations relative to each other over time The quantification of concentration is not within the scope of this study We have also established a NMR database of metabolites in Atlantic salmon The database was created for the
136. or of freshness and quality It would seem that a combination of indices and indicators would be of use KI values used to indicate the endogenous breakdown of metabolites the BAI to indicate the bacterial breakdown of metabolites supplemented by other chemicals such as TMA TMAO for its odor and histamine nitrosamines for their safety aspects 28 An investigation of such a combination is beyond the scope of this study Yet as the advantages of such combined measurements of parameters seems apparent it is surprising that no attempts in this direction have been found in the literature reviewed presented in this thesis 4 3 Objective measure An objective measure based on the content of metabolites and other chemicals would depend greatly on the instrumental methods available Requirements for a index are that it 1s based on a fast method reliable and consistent with sensory assessment Sikorski 1990 If an index were devised it would be of great use if it were applicable to multiple species Sikorski 1990 yet as mentioned above this might make matters more complicated How fast and reliable an index can be measured depends greatly on the analysis and the methods used Important factors for the choice of method are that it is low cost has a short analysis time is simple and finally that it can be used outside that is it is not bound to a laboratory environment Onal 2007 4 4 Current techniques Before we discussed the
137. products such as salmon Haard 1992 Due to this there has been a large demand for astaxanthine by the salmon farming industry Here dietary use of this chemical reaches up to 20000 kg year Christophersen 1989 2 5 Carbohydrates and ATP 2 5 1 Carbohydrates catabolism of glucose and glycogen Breakdown By the Embden Meyerhof Parnas pathway Products Lactic acid and ATP Biochemical effects Effects the post mortem pH and the onset of rigor mortis Effects A loss of sweet meaty character in the fish fillets Glucose is a simple monosaccharide with a six carbon backbone which is the primary energy source for many cells Glucose is in the Crebs cycle degraded to ATP and CO which cells can use to drive their chemical reactions Glucose is stored for later use by cells as glycogen These large rosetta like macromolecules consist of many single glucose units and can be broken down for rapid energy during high activity or starvation Other carbohydrates include monosaccharides ribose and fructose but they are of less biological significance then glucose for the fish s cells The amount of carbohydrates in fish muscle is highly dependent on a number of factors including feed intake and the fish s biological condition Well fed fish will have larger amounts of glycogen stored then starved fish Haard 1992 The amount of carbohydrates in fin fish including salmon is usually less then 1 percent Haard 1992 Sikorski 1990
138. quantification of metabolites Even though NMR has its disadvantages the technique yields large amounts of precise data in a short time and therefore should be used more frequently in metabolite studies and more generally for the development of indices for quality and spoilage of fish To further illustrate the point of this conclusion we present a short case study of Atlantic salmon fillets based on NMR data recorded by Shumilina 2014 We have analyzed this data for some of the metabolites covered in our literature study in order to assess the fillets quality and the state of spoilage Abstract Norwegian I denne oppgaven har vi studert metabolitter i atlantisk laks S salar og deres virkninger pa kvaliteten og bedervelsesprosess i fileter av laksen Vi har spesielt fokusert pa metabolittenes konsentrasjon som mal for kvalitet og bedervelse Vi har gjennomfort en studie av litteratur ang ende var forstaelse av metabolitter i laks og disses effekt pa kvalitet og bedervelsesprosess Vi har ogsa presentert noen indekser som er i bruk eller som har blitt forslatt til bruk som mal for metabolittkonsentrasjon i laks I diskusjonen av litteraturstudiene har vi forsl tt videre studier av metabolitter og kombinasjoner av indekser som blir brukt som mal for kvalitet og bedervelse i atlantisk laks NMR spektroskopi har blitt introdusert og analysert for dens fordeler og begrensninger som metode for identifisere og male konsentrasjonen av metabolitt
139. ral ATP catabolites This value is defined as the percentage of the amount of Ino and Hx to the total amount of ATP related compounds Tejada 2009 and expressed as Formula 3 K value 96 Ino Hx ATP ADP AMP Ino Hx Tejada 2009 From the formula we can see that the K value is expressed in percent A higher percentage of K values indicate a decrease in freshness and a loss of quality Tejada 2009 K value right after capture usually does not exceed 10 percent and increases more rapidly for cold water fish species such as Atlantic salmon than warm water species Sikorski 1990 K value supplies an index which correlates linearly to storage time of fish above freezing temperature and is used as a commercial index especially in Japan Tejada 2009 Maximum values for the sensory rejection and spoilage of Atlantic salmon has been suggested at 70 80 percent K value by Tejada 2009 The K value is also used for fish products with stricter quality requirements K value of 20 percent has been defined as the limit for Japanese raw sashimi grade fish and also has been regarded as the freshness limit for fish Sikorski 1990 Tejada 2009 Formula4 K1 value 96 Ino Hx IMP Ino Hx Formula 5 G value 96 Ino Hx AMP IMP Ino Formula 6 Fr value IMP IMP Ino Hx Formula 7 P value 96 Ino Hx AMP IMP Ino Hx Tejada 2009 Due to the rapid
140. rchive Metabolomics Bulk archives Educational Outreach Data upload NMR Data Formats Data poicy Useful NMR Links Site Map ETP Access Acknowledgments Contact bmrbhelp bmro wise edu f you hav Copyright The Beard of Regents of the Li Last Modified Tuesday 17 Sep 2013 01 Images and chemical information were obtained from PubChem except for the structures from the USDA NMR Database of Lignin and Cell Wall Model Compounds which were produced there Screenshot 39 Metabolomics Home on BMRB 96 you the best possible match to the compound name Select the search for Experimental Entries to show only data which has been completely entered into the database and press the Search button hi BMRB Metabolomics search rb wiscedu find BMRB Metabolomics search 59 Search for Synonym Enter search alanine Experimental entries Theoretical entries Selectthe top 10 matches Exportto tab separated file J 41 matches for alanine displaying 10 or upload batch file Bla gjennom Ingen fil valgt Name Image BMRB ID Synonym Search Search i Gades ignore L Alanine Pa ow bmse000028 Alanine cu Search by structure Search 1D peak lists iL ignore Alanine bmse000282 Alanine Search 2D HSQC lists c M en Solvent and field strength ignore L Alanine Pa ou bmseo00994 Alanine cu ignore D Alanine Na ow bmse
141. rdouasusdectebsevesnccensaacentodadsasdasschsedassacsseaceensonesuaeds 46 5 5 4 Biosenic amines 5 once eret preter eae eno o ore ERE Fe dus CE Va pe e rossi b ee SSRs ssa E SIIS Eev ropov osboot Pe PPS e IURE Eae EUER 47 MIENNE M 48 a CONCIUSION rri 49 VIII 6 Conclusion EE AEN S0 rUlUiDcL m ieta aeaa TE EAEE er EE RESTE E Eiei 51 S Appendix Mee P TEN EEEN oo ETET EE E ERa 54 8 1 Appendix I Table of bacterium found on fish fillets ceres eerte eese creen eerte eene eene etta se tnu 54 8 2 Appendix II Compounds found in case study and peak assignment eere eeee eee eene S6 8 3 Appendix III A short manual for the creation of a Spectral database and a Knowledge base using the Aurelia Amix software version 3 9 14 and its use for the detection of compounds in 1D NMR spectra List of Tables Table 1 The total productions of the world s capture and aquaculture fish production FOA Pp O 1 Table 2 The world production of aquaculture produced diadromous fish broken down by species FOA pp 3 Table 3 Values for concentration of individual amino acids from Hultmann 2004 flavors and values for flavor threshold from Belitz 2009 e eee e eee eee e esee ee ee eene te ette
142. re under the defined noise level Amix will do this by removing all peaks which are wholly under the noise level and by smoothing out the curves 74 of the slopes of the larger peaks To access this function again go to the Preparation drop down menu and this time select Line shape analysis located right under the Define noise level function E Preparation version 39 14 Config Analysis Patterns Mea SBGHEM 22 5 tT om AQQAVEZREE BS te BR He CO OE ES Confirm threshold s Le threshold 4013376 OK Cancel Screenshot 10 The Noise threshold number recived from the Define noise level interactivly function Once selected this function will open a window asking you to confirm the noise level number The number it displays should be the number that you had selected as noise level before Screenshot 10 Confirm by pressing OK and Amix will clean up all the noise below your selected noise level Your spectra is now almost ready to be saved There are a number of functions for editing areas of the spectra which are unwanted such as peaks from water or other solvents You can remove these peaks by using the Delete area function in the Preparation menu This function will allow you to highlight an area on the spectra using your mouse This area will be deleted from the spectra There are also functions such as Remove Po
143. rigor mortis has set in Such shortening may also cause the drip loss of water resulting in dry fillets and a loss of quality Einen 2002 After maximum tension is reached termed completion of rigor the muscle of the fish starts to soften termed resolution of rigor Tejada 2009 This softening is due to autolytic enzyme which degraded the bonds inside the cytoskeleton and causes relaxing of the muscle These autolytic enzymes such as calpains are activated by a continued rise in the concentration of Ca or released from the lysosomes such as cathepsins and activated by the post mortem drop in pH Tejada 2009 These enzymes degrade the proteins of the myofibrils and proteins of the external cytoskeleton leading to a tenderizing of the fish fillets often termed the aging effects Tejada 2009 Rigor stiffness of fish fillets is a sure sign of freshness Sikorski 1990 Rigor mortis in fish usually sets in 1 6 h after death and in Atlantic salmon usually starts in the neck region Einen 2002 Tejada 2009 The intensity of and the time to completion and resolution of the rigor is highly dependent on the stores of glycogen and ATP in the fish which are functions of factors such as age size stress during killing and handling of the fish as well as on season water temperature and other environmental factors effecting the fish Tejada 2009 In relation to quality rigor mortis has a pronounced effect on the texture of the fillets as a na
144. rine at 3 01 ppm 28 Normalized Intensity 0 0005 0 0010 3 0 0015 0 0020 3 5 4 3 b Tyrosine and tyramine Tyrosine Tyramine i 4 3s t0 15 esp TO T5 0 0050 4 0 0060 399 T0 T5 esp 3 0 005 4 0 0045 4 0 0050 4 0 0040 4 0 0045 4 3 3 0 0035 4 0 0040 4 i 3 0 0030 4 0 0035 4 3 0 0020 4 0 0025 4 i Tyrosine i 0 0025 3 0 0020 4 0 0020 3 3 j 0 0015 4 0 0015 4 3 i 0 0010 4 0 0010 4 3 i E B asso amp 0 0005 3 0 0005 3 E 3 E 4 3 o0 o 4j N E a 4 0 0005 4 o 000s 4 2 2003 JJ 3 a 0 0010 4 0 00154 3 0 0020 3 0 00154 0 00254 000204 203 0 00254 0 00354 3 4 0 0030 4 0 0040 3 3 0 00453 p X 0 0035 4 0 0050 3 0 0040 0 00554 AN 0 0045 4 000003 A Eep M S NS 13 3 0 00504 LAPAD AAA MSL MAMMA MAMMA MAMMA MAMMA MAMMA MEAM MAMMA MAMMA 3 6920 6915 6910 6905 6900 6895 6890 6885 6880 6875 6870 6865 6860 6855 6850 6845 6840 683 Chemical Shift ppm Figure 34 Peaks of tyrosine 6 87 and 6 89 ppm from dataset SO 0 0105 4Salmo 0 1 TS esp 0 0100 3 0 0095 3 0 0090 3 0 0085 4 0 0080 3 0 0075 3 0 0070 4 0 0065 3 0 0060 4 0 0055 3 0 0050 4 0 0045 3 0 0040 3 0 0035 3 0 0030 3 0 0025 3 0 0020 3 0 0015 4 0 0010 0 0005 0 dala kao dai AA A Jw Tree e e rT 6930 6925 6920 6915 6910 6905 6 900 6 895 6890 6885 6880 6875 6870 6 865 mme T 6 860 6855 6850 6 845 6 8
145. ring the breakdown of multiple metabolites in fish samples over time and for the development and application of an objective index of quality and freshness based on multiple metabolites NMR would allow these metabolites to be measured in one set of data and it makes measurements replicable 30 4 6 Use of NMR software Amix The use of databasing and analysis software such as Bruker s Amix streamlines the process of analyzing NMR spectra as discuss in Section 3 2 2 Bruker s Amix software requires the creation of a database with reference spectra or data to use in comparison with a new NMR spectra The software can use this reference data to scan NMR spectra for patterns of certain compounds or functional groups and supply the user with a list of its findings The software also allows for quantification of findings if provided with the correct information This gives the user the possibility to rapidly analyze a number of spectra for known metabolites and their concentrations For this thesis we have developed a database using Bruker s Amix software to determine the usability of the software for streamlining the analysis process of metabolites in NMR spectra of Atlantic salmon Our database also contains at the moment reference data for 70 different metabolites found in Atlantic salmon See Section 5 Our database furthermore has the ability to detect these metabolites in new NMR spectra According to Bruker the Amix software also has the
146. ronounced quality loss at a specific points in the degradation process of nucleotides would have to be confirmed subjectively both of these points could be further investigated The changing values of inosine Hx and IMP could also if quantified provide the base for the calculation of the K value for each sample see Section 2 5 2 a such as done by Shumilina 2014 seen on Figure 39 The literature suggests maximum K value between 70 and 80 percent for Atlantic salmon see section 2 5 2 Based on Figure 39 dataset S4 fish stored at 4 C passes these values before T3 7 days dataset SO remains within suggested limits until T4 K Index 95 B x 7 The depleted levels of ATP ADP and AMP 80 a further indicate that rigor mortis of the fish has B 2 set in and possibly resolved see Section 2 6 2 n This would correspond well to the observations ss s of Einen stating that it is common practice in so 1 the fish industry to process fish after resolution of rigor mortis 3 to 5 days after death Einen 35 KdndexO C Kindex 0 C 30 2002 0 2 i M 8 10 12 14 16 Storage days Figure 39 The K value for SO red and S4 blue Shumilina 2014 5 5 3 TMA TMAO Figures 24 and 26 show clearly a production of TMA in SO and S4 S4 Figure 26 shows a quicker production of TMA starting at T3 SO does not produce significant amounts of TMA until T5 and in much lower concentration then S4 Figure 28 shows heig
147. rough the established spectra and defined key words which can be used as search words in the database Another purpose of the program is to compress data NMR spectral data can be big leading to large files especially if you work with 2D spectra storage on the PC can become a problem The Sbase software will compress each spectra to a file size of approximately 0 1MB 2 1 Creating a new Spectral Base You start your work with the Sbase by creating a new Sbase that can contain your spectra This is done from the Amix Viewer by selecting Amix Tools and by navigating down to the Spectral Bases drop down menu From here you select the top option labeled Create new This will enable you to create a new spectral database Once selected the program will require you to define a directory for the new Sbase This is the place on your PC from where the Sbase will be located Choose a directory that is easily accessible for you You always have to specify the entire directory path starting with the partition followed by the name of each subdirectory separated by a backward slash Screenshot 7 The name of your Sbase is important The name of the Sbase in Screenshot 7 is Test The name of an Sbase should be informative and related to the content of the Sbase for easier handling of several Sbases later If a name is ambiguous it will be difficult to tell Sbases apart If you are working with metabolites in E coli a good name may be
148. rstand the development of quality and spoilage of salmon or fish in general detailed investigation of microbial formation would be needed Bacterium have been implicated in the production of compounds in fish products and fillets which lead to off flavor loss in quality and spoilage But it should be underlined that in general it is not yet possible to predict the spoilage microflora and spoilage reactions that become limiting for shelf life of products Dalgaard 2000 Therefore it does not yet seem possible to determine microflora by the metabolites they produce The tissue of live fish 1s sterile warded from bacterial flora by the fish s immune system Sikorski 1990 Thus it should be concluded that bacteria infection of fillets or other fish products are a result of exposure to parts of the fish which are in contact with the environment 1 e skin gills guts or unhygienic conditions during processing Also abusive storage conditions with regard to temperature and environment may result in the growth of microflora and the loss of quality spoilage Especially a number of gram negative bacteria have been implied to induce the spoilage of fish products by producing metabolites with unpleasant properties Dalgaard 2000 Bacteria found on the skin and extremities of fish caught in cold water environments such as Atlantic salmon are mainly Psychrobacter Acinetobacter Alteromonas Psudomonas Flavobacterium and Vibrio Sikorski 1990 Psudomon
149. s are of considerable concern regarding the E E safety of fish products Ayesh 2012 Mohamed Putrescine Omithine arginine 2009 Zaman 2010 Cadaverine Lysine Histamine is a biogenic amine produced by the Spermine Ornithine arginine Lo P s endogenous or bacterial degradation of histidine Spermidine Ornithine arginine Histamine is associated with the medical condition Scombroid poisoning which is the result of ingesting spoiled fish containing high levels of biogenic Tyramine Tyrosine amines Scombroid poisoning is regarded the most common form of intoxication through the ingestion of fish Visciano 2012 The term scombroid is derived from the Scombridae fish family which was Phenylethylamine Phenylalanine Heterocyclic first implicated with this type of intoxication Pe Penge Visciano 2012 Consumption of histamine Tryptamine Tryptophane concentrations between 8 40mg triggers slight symptoms of Scombridea poisoning 40 100mg Table 4 The major biogenic amines and the amino acids from which they derive Bulushi 2009 nal 2007 over 100 mg triggers sever poisoning symptoms Onal 2007 These consist of allergy like symptoms such as rash facial swelling and flushing others symptoms such as dizziness rapid weak pulse triggers intermediate symptoms and consumption of drop in blood pressure difficulty swallowing and thirst nausea vomiting cramps and diarrhea Rare cases show severe sympt
150. s software such as Amix they could be quickly detected and quantified 50 7 Bibliography Ayesh A M Ibraheim M N El Hakim A E Mostafa A H 2012 Exploring the contamination level by biogenic amines in fish samples collected from markets in Thuel Saudi Arabia African Journal of Microbiology Research 6 1158 1164 Balamatsia C C Paleologos M G Savvaidis I N 2006 Correlation between microbial flora sensory changes and biogenic amines formation in fresh chicken meat stored aerobically or under modified atmosphere packaging at 4 C possible role of biogenic amines as spoilage indicators Antonie van Leeuwenhoek 89 9 17 Baldus M Meier B 1996 Total correlation spectroscopy in the solid state The use of scalar couplings to determine the through bond connectivity Journal of Magnetic Resonance Series A 121 1 65 69 Bauze T Blaise A Daumas F Cabanis J C 1995 Determination of biogenic amines and their precursor amino acids in the wines of the Valley du Rhone by high preformance liquid chormatography with precolumn derivatization and flourimoetric detection Journal of Chromatography 707 373 379 Belitz H D Grosch W Schieberle P 2009 Food Chemistry Springer Brey W S 1988 Pulse Methods in 1D amp 2D Liquid Phase NMR Elsevier Science Bross Walch N K hn T Moskau D Zerbe O 2005 Strategies and tools for structure determination of natural products using
151. sal occurrence of protons in organic compounds and the high sensitivity of NMR detecting chemicals at uM mM concentrations NMR has been useful in the study of biological compounds Fan 1996 NMR allows for the specific and simultaneous determination of a number of metabolites while maximizing the chance for detecting unexpected or previously unknown metabolites Fan 1996 Extrapolating data from traditional one dimensional NMR spectra has its limitations due to the overlap of signals Yet using the large number of 2D methods available greatly reduces these problems and provides a unusual versatility to such analysis Fan 1996 In modern biology biotechnology NMR spectroscopy is mainly used to determine the 3D structure of biomolecules study the interactions of molecules study complex bioliquids such as blood or urine food research and NMR metabolic profiling 3 5 Use of NMR software Amix and database tools in combination with NMR Analyzing NMR spectra involves matching reference spectral data to new spectra and the assignment of peaks from the reference data to functional groups in the new spectra Alternatively one can match peak patterns to certain compounds and thus directly identify molecules Yet this would be a tedious process especially in complex biological samples which require the use of 1D and 2D spectra such as in fish samples of Atlantic salmon For this purpose it is very useful to use databasing and analysis
152. se you want Only the demo license is free and then send your license request You will receive an email from Bruker in the course of the next several days after your license request which will contain a text file This c s SES file is your license To install GU d OSDisk C fledm Bruker licenses 5 Sak i licenses p Organiser v Inkluder i bibliotek v Del med v Brenn Ny mappe iz i e the license you first have to Yt Favoritter Navn i Da Type St rrelse create the directory C flexlm 39 Nedlastinger license 4 DAT f B Nylig brukt Bruker licenses in Windows RE Skrivebord ZJ Biblioteker Bilder Dokumenter Screenshot 2 The complete license directory or usr local flexIm Bruker licenses in linux This can be done on the PC by creating a folder on your C drive naming it as shown in Screenshot 2 The name of your license file must be license dat Copy this file into the license directory Now you have to specify which computer you want the license to be effective for You need your computer s hostname and physical address In Windows you find this information by selecting programs from your start menu then select accessories and from here select the command prompt This will open a command window with a black screen Type into that window ipconfig all and press enter From the information that now appears we need the hostname supplied
153. serine and Carnosine Leere eee ee eee eee eren eee en netta se tna stone setas setas etos e stone etna sesta seta seen ne 12 p Mp bo enbeSesedsovadcdeveseuss cvswaseswashendsevensesbbecseoascsacccesss 13 PALACE Yn NUEVE soiree 14 p SNIE ODT E DEEK sods cdeseasessenedesssoasessenuasensecescsednass 16 2 4 1 Carotenoids E M 16 2 5 Carbohydrates and ATP prr EE 17 2 5 1 Carbohydrates catabolism of glucose and glycogen eessesssoessoesocsssessoessssssesssosssossoossoossoosoossoo 17 PE PPAS Hr M 18 2 5 2 0 erii eCTC 19 2 6 Post mortem CHANGES lt csiscesccencesesssosecsosvessensd cennecesesesessootessessssesasdsensdovessesecosouaccosaasdvosesetescosesconcsceuscesess 20 PX iiu eer 20 PAPA du g tos 21 2 7 Microbes Their products and their relation to quality and spoilage eere 23 VII 3 Introduction to NMR spectrography Re AA DE ES LE An 1 e M Q 24 3 2 Using NMR ITem M pos oor SSeS 25 3 3 Isotope interaction and 2D NMR scccsccssssccscccscccescecescceesssccsccsesccessccessscessscsessecssscessscessseseesossssesees 25 3 4 intenti NETT T 26 3 5 Use of NMR software Amix an
154. set SO eerie ee eee eee esee sees eese tn atenta tnsen 37 Figure 16 Change in AMP 8 56 ppm for dataset SO eee eee eres estes ense ee sento enata stato sense tas tnsnse 37 Figure 17 Change in Hx peaks 8 18 and 8 20 ppm dataset SO ceres eere eese tenete tenta anne 37 Figure 18 Change in Inosine and IMP 8 22 and 8 23 ppm respectively for dataset S4 38 Figure 19 The change in inosine 8 34ppm for dataset S4 eee eee e e eee eee eee ense sess tn aeta sta snsen 38 Figure 20 Change in AMP 8 56 ppm dataset S4 eere e eee eee ee eese nete senses sensn sense ta sens tn sense tasa sns en aen 38 Figure 21 Change in Hx peaks 8 20 and 8 18 ppm for dataset S4 sssesesossesesossesossossesesossesoeeososossossesesossesose 38 Figure 22 T5 spectra of SO and S4 overlaid with SO on the bottom blue and S4 on top red Shows the final difference of Inosine and IMP at 8 23 and 8 22 ppm respectively eeeeee ee ee esee eee ee ee eene tn atn use 39 Figure 23 T5 spectra of SO and S4 overlaid with SO on the bottom blue and S4 on top red Shows the final difference of Hx at 8 20 and 8 18 ppm 4e eee ee eee ee ee esee eese ene eene tne ta ettet east ta sepas ease test testes oae 39 Figure 24 Change in TMA levels dataset SO at 2 89 ppm 4 erase ee etes tester eee ee seen tenen stantis sone tn stu sena ta 40 Figure 25 Ch
155. sh species which is heavily fished and produced for commercial sale In 2011 its production was at 1 7 million tons representing a total value of approximately 9 7 billion USD FOA 2012 The fish s production is highly reliant on the aquaculture industry as it is nearly extinct in the wild Goldburg 2005 and the development of Atlantic salmon aquaculture has been seen as one of the successes the aquaculture industry Aquaculture of Atlantic salmon originated in Norway in the 1970s and has since increased massively from 776 thousand tons in 1988 to two million tons in 2001 inducing a quadrupling in the production of salmon between 1992 and 2002 as shown on Figure 1 Farmed salmon represented 68 percent of the total salmon production in 2002 and now makes up 60 percent of fresh and frozen salmon sold on the market Goldburg 2005 Due to the sharp rise in the production of farmed Atlantic salmon and its availability on the market the price of S salar fell by 61 percent between 1988 and 2002 illustrating the economic impact l Atlantic samon of the aquaculture industry Due to this fall Milkfish en in market price Atlantic salmon is Eels NENNEN considered an affordable luxury fish Coho silver salmon WIN product Other salmonids m Barramundi Asian sea bass Will As already mentioned wild Atlantic salmon Sturgeons i x Other diadromous fishes occupies a niche market due to the debate 0 0 0 4 0 8 12 1 6 of the heal
156. shown in Screenshot 17 Use the Line shape analysis function also Stm 2255 1 tv T 94 amp QA S 7 2 a5 2o x B amp ULT dk oS BrX x6 E DE GS in the dropdown menu As with the 1D spectra the noise level number Noise level calculation o toja noise level definition a n fae tne e m rit e NUN from the previous window should be define noise level interactively intensity ratio relative to biggest point in original spectrum Cis ies x auto filled with your defined noise left 2 ppa level Yet if this is not the case you right 1 ppa 120 ppa bottom ss 10 spe o o can also enter the noise level noise factor e g 10 2 88 o user defined noise level DIENEN 9 manually Amix will now mu 10 Ie s d x c E a automatically smooth out any peaks neglect reference from ratio calculation which are under this defined noise Lok Cancel o level You can again use the Delete area or Keep area function in the Screenshot 17 The define noise level by number by number function Number which is pasted from Screenshot 16 is highlighted Preparation drop down menu to 80 clean out any peaks from water or other solvents which are not wanted in the spectra Once you have completed removing all unwanted information from the spectra repeat the saving procedure of 1D spectra by selecting the Save to spectral base function Section 2 3 Here you enter the compound name
157. sitive or Remove Negative which will delete all positive or all negative peaks from your spectra The Keep area function will ask you to highlight an area which should not to be deleted the rest of the spectra will be deleted After removing all areas which are not relevant the spectra can be saved to Sbase To do this select the Save to spectral base function in the Preparation drop down menu A window will appear which will allow you to define the compound and the experiment type this spectra should be saved to Screenshot 11 75 Spectra are saved under a compound name If two spectra are saved with the same compound name they will belong to the E Preparation version 3 9 14 oles same category SSM 22S TT OM AQAA AAEN LE amp lov he doo KOEN it SN oe If you choose a compound name which Amix does not know yet it will create a i l T Select from spectra bases egre compound with 61 5 salar compound name test this name experiment type 1dnoset Lox _ Cancel The experiment type is important since it separates the spectra in the subcategories It is recommended to Ss Se eae are VISA five aa use experiment types such as Screenshot 11 The Save to spectral base function 2dhsqc or 1dnosey in this field or to define a system number for each experiment type such as 1D H 10 and all 2DHS
158. t 1 Select the execution file the file with the exe extension third from the top Aurelia Amix if working in Windows this should automatically start the download of the Amix software package The other links on this page are a collections of manuals Readme files and a sample database of NMR spectra Sbase Here is a direct link to the Amix download page for Windows http www bruker com service support upgrades software downloads nmr pc pc amixaurelia html Once the download is completed the next step is to install the software package This should be done by clicking on download and then by following the instructions that appear on your screen The install will place two shortcuts on your Desktop or in a directory of your choice The shortcuts will allow direct access to the main Aurelia window and the Amix Viewer The Amix Viewer is the interface where most of the practical work will be done Before one can begin using the software fully the license agreement has to be installed It can be acquired on Bruker s NMR software license request page found at https www bruker com nmr license requests html On this page you again have to register with your name institution and email address Verify that your email address is given correctly as Bruker will mail your license to this address On the webpage there is also a 68 form concerning different licenses for different programs Please select the type of licen
159. te glycogen glycine histidine inosine isoleucine lactic_acid leucine lysine naltose methionine NAD niacinamide phenylalanine proline putrescine polyamine serine succinic acid taurine threonine trimethylamine oxide tryptophane tyrosine uracil OK AutoSelect Unselect Cancel Screenshot 35 The list of all compounds in Knowledge Base given by the Edit compound in Knowledge Base function are made To edit compounds in the Knowledge Base go to Profiler drop down menu in the Analytical Profiler and further on to the Knowledge Base drop down menu Here select the Edit compound in Knowledge Base function This will direct you to a window which confirms which Knowledge Base you wish to edit This is equal to the window used to confirm the Knowledge Base during the Add compound function Select the text file containing your Knowledge Base as done before and confirm Now Amix will show a list of all the compounds in Analytic Profiler version 3 9 14 the Knowledge base SSMM22 5 tot Oomaaas T E3 RB Screenshot 35 Select the compound you wish to edit and confirm again This s tite Knowledge base VERSION E unknown ill b x h USER Dorothee HOST HF 30077 wi ring up t e same type X DATE Fri 2014 04 25 20 41 48 FILE C NdataNmichael nmr S salar KB H1C13 txt of windows used in the REFERENCE DSS standard RESO
160. techniques used to measure metabolites and discuss the benefits and restrictions of NMR spectroscopy to other techniques Sections 4 5 and 4 6 We will also introduce a database of metabolites created in Bruker s Germany Aurelia Amix software for use in this thesis Section 4 6 In Section 5 to exemplify the use of NMR we will present a short case study This study is based on data recorded in our lab Shumilina 2014 and will focus on the development of several key metabolites in the muscle fillets of Atlantic salmon stored at different temperatures over a 14 days period Here we have chosen to study the development of nucleotides TMA TMAO and some biogenic amines Section 5 4 We have analyzed the results in relation to their implications for the quality and spoilage of the sample Section 5 5 2 Metabolites 2 1 On metabolites A metabolite is a low molecular weight molecule present in or excreted by cells or bacteria in the fish meat In the following we will discuss proteins and their degradation to amino acids biogenic amines some osmolites including anserine carnosine and taurine trimethylamine and trimethylamineoxide carotenoids carbonhydrates and nucleotides Above each paragraph we will list key facts regarding each metabolite in order to provide a quick insight into important qualities or functions 2 2 Proteins Their degradation and amino acid concentration Breakdown Due to proteases Effect of
161. th impacts of farmed salmon Million tonnes Yet it cannot be said that wild salmon is Table 2 The world production of aquaculture produced diadromous fish broken down by species FOA 2012 entirely wild Due to escaped salmon from aquaculture farms and supplementing of wild salmon by commercial hatcheries a number of genetically inferior salmon breed with wild salmon and reduce the total fitness of the offspring The biochemistry of this interbreeding has not been completely studied yet the adverse ecological effects have been well documented Goldburg 2005 2000 In this thesis we will deal with the evaluation of the quality and spoilage of Atlantic salmon specifically T We will focus on the chemical processes of spoilage 1000 4 and on the effect such chemistry has on quality characteristics and consumer health Even though some results may be transferable to other species of fish it should be noted that many authors point to 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 the biochemical differences between fish species Onal 2007 Visciano 2012 therefore the results of Figure 1 The world production of captured and farmed salmon 1950 2002 in metric tons this study should be considered thoroughly when Goldburg 2005 applying to other fish species than Atlantic salmon ME Capture Farmed 1 3 Quality spoilage and freshness Quality A factor of safety nutrition flavor text
162. the cyclic breakdown of nucleotides is ongoing and halfway to completion in dataset SO see Figure 8 Section 2 5 2 S4 shows a more rapid progress of degradation It can be clearly seen on Figure 18 and 20 that concentrations of IMP and AMP in this dataset approaches exhaustion already at T3 The concentration of inosine in S4 on Figure 18 and 19 can be seen to rise rapidly and reach a maximum at T4 after which it drops This can be correlated to the production of Hx which begins to rise rapidly after T4 in S4 as seen on Figure 21 At T4 it would seem that the breakdown of inosine to Hx has overtaken its production from IMP possibly due to the exhaustion of IMP Nucleotides and their catabolism have a large impact on the quality of fish fillets High concentrations of IMP are associated with good quality and desirable flavors whereas inosine and Hx are associated with bad quality and undesirable flavors see Section 2 5 2 44 The gradual loss of IMP and the resulting production of inosine and Hx clearly shows the loss in quality of the meat during storage Faster loss of IMP and production of inosine and Hx seen in 4 shows the impact of temperature on quality loss The point at which IMP is rapidly lost T4 and T3 for SO and S4 respectively could be considered pivot points in the loss of fillet quality Also the point at which the inosine breakdown to Hx out paces the production T4 on S4 could indicate a rapid loss in quality A p
163. tion open the Analytical profiler from the Amix Viewer Now use the Open or browse functions in the File drop own menu in the Analytical profiler to open all available spectra and the molecular structure of a compound you have defined in your Sbase in the Analytical Profiler window Make sure you have your window configured to Add objects to current window of same type so that the spectra open in the same window See Section 3 1 Once all information on the s48M 220s wtT om aaa SEB J compound is open on the betasidnosey iz ref alanine beca 2dnsqe 2rr r ref alanine beta cocsy 2zr i Amix Analytical Profiler b window go to Profiler in the top left and select Add goose compound to knowledge base Once you have n of well defined signals of a compound EXE g Bp nni er a OE secu ib 7 N defined which knowledge 2 59718 2 40181 36 8459 35 5568 2 w g V 2 r o 2 21883 02346 9297 3 4794 Hs N base you wish to add this o e o lo a x r jo D D D D e ma r e compound to you will be lo lo lo lo a x gt r r r lo 5 mm asked if Amix should use o o o o a x r jo o io e r p the information on the lt eck West cancer Meie screen to automatically fill Screenshot 34 A prefilled window of the Add compound to Knowledge Base in sists sniaiaae fun
164. title but it 1s recommended that the title relates to the information the text file might be titled Screenshot 30 The Analytical Profier main window 89 After creating the text file we can begin to add information to it from the Amix software To do so go to Amix tools in the Amix Viewer window here select the Analytical profiler function This will open a new window titled Analytical Profiler Screenshot 30 which is the main window for working with your Knowledge Base and for analyze spectra 4 2 Adding compounds to the Knowledge Base manually To add compounds to the text file which is your Knowledge Base select the Profile drop down menu in the Analytical Profiler and navigate down to the Knowledge Base drop down menu It contains all the T Analytic Profiler version 39 14 S480 2265 ETTORRA SER open named file C search for file knowlegdge base Emmm start scorch in M OK Cancel Screenshot 31 The Load knowledge base window from the Add compound to Knowledge Base function commands which create and edit your Knowledge base From here select the Add compound to Knowledge base function This will open a window asking you to specify the location of your Knowledge Base text file Screenshot 31 The dialog window Open named file will allow you to browse your computer and specify an existing text file The Sear
165. to specifically search for one or a set of spectra in your Sbase using either name experiment type properties such as Keys or any combination of these Once you select this function you will see a window on your screen in which you can specify which Sbase you wish to search and your search parameter Screenshot 22 Here you have to select which set of parameters to use in the check boxes on top Searching for compounds by Name will allow you to enter compound name and experiment type as search parameters Searching by Properties will allow you to search for spectra by Keys or for other defined data such as peaks molecular data or titles only search by Key is in the scope of this manual The Sbase can also be searched for a combination of properties and names this is the most specific search option If you choose to search compounds by Name the fields 83 Compound name and Experiment type may be used If you want to disregard one field as search parameter fill this field with star Note that leaving the field blank will not disregard the field as a search parameter For example you want to open all spectra with the compound name sucrose enter sucrose into Compound name and into the Experiment type field Amix will now search Sbase for all spectra 3 Amix Viewer version 39 14 EI 22 SYALAL Aeon ea fet f RAA Ald S48 2 H
166. tp www bmrb wisc edu and the Human Metabolome Database http www hmdb ca Screenshots 38 and 44 To use the Biological Magnetic Resonance Data Bank bmrb go to the link above then to the menu bar on the left side of the webpage select metabolomic and navigate to Methabolomics Less zs sli Metabolomics E ed AL PD A 3 5 Member of Biological Magnetic Resonance Data Bank PORA m SPDB A Repository for Data from NMR Spectroscopy on Proteins Peptides Nucleic Acids and other Biomolecules i Search BMRB Metabolomics e Search for Synonym Ho o Metabolomics data hosted at BMRB d c Enter search a Experimental entries Theoretical entries Witremetabolomice Y All compourds hosted at BMRB A Selectthetoo 1 matches Cell wall compounds from the USDA NMR on database of lignin and cel wall mode or upload batch fle compounds Bla giennom Ingen fi valgt Pathways of metabolism Search Seach False standards Metabolic profiles of 47 marine bacteria Search by mass Search Other Metabolomics resources at BMRB Validation Tools Search by structure TN NMR peaks query Deposit Data Search 1D peak lists Molecular mass calculator NMR Statistics Find formula molecule by mass Spectroscopists Corne Search 2D HSQC lists Heuristically determined formula by mass Metabolomics websites Pee GOTT Solvent and field strength Metabolomics database csv a
167. tra The frequencies at which nucleons and radiation interact are recorded and using mathematical operations such as Fourier transformations turned into corresponding signals on a frequency scale and displayed as peaks on the NMR spectra Kessler 1988 See Figure 11 At which positions of certain peaks in the NMR spectra such interactions occur is based on a number of factors Some of these are instrumental such as the strength of the magnet used others are dependent on the nuclei s identity and magnetic environment Nuclei with different identities such as hydrogen H and carbon PC will interact at vastly different frequencies Also not all hydrogens will interact with radiation at equal frequencies The frequency of interaction and hence the peak on the NMR spectra is dependent on the nuclei s magnetic and molecular environment This environment is a function of the nuclei s surroundings with respect to other nuclei Different magnetic environments will cause nuclei of equal identity to interact with radiation at slightly different frequencies This effect is harnessed by NMR spectroscopy to identify the nuclei s environment Nuclei in specific magnetic environments will consistently generate peaks on NMR spectra at specific frequencies where the height of the peak is proportional to the number of nuclei generating the signal As an example protons H in a methyl group environment will interact with a specific frequency and generate a
168. tural function of the tensing and relaxing of the muscle Also the breakdown of the cytoskeleton may lead to gaping or flaking of the fillets especially during intense rigor Sikorski 1990 Rigor mortis has also been implied in the loss of color of salmon meat Einen 2002 Yet rigor mortis is mostly associated with signs of freshness and a pre rigor or rigor state of the fillets indicated an impeccable freshness of the fillets Sikorski 1990 22 2 7 Microbes Their products and their relation to quality and spoilage Effects Bacterial flora produce many metabolites directly effecting the quality and shelf life Cause Infection occur on processing post mortem Bacterial microbes in and on fish products such as fillets are not metabolites and thus will only be dealt with shortly in this study Bacteria produce many of the metabolites and chemicals found to be responsible for fish quality and spoilage and are thus an important factor in determining fish quality Castell et al states that Bacterial counts are valueless as a measure of the degree of spoilage of fresh fillets Dalgaard 2000 It has also been stated that microflora contributes partly to the gradual loss of taste substances and ultimately to spoilage due to partial proteolysis and accumulation of unpleasant metabolites Sikorski 1990 A table with some important bacterial strains and metabolites which they produce can be found in Appendix I To fully unde
169. ure odor color and appearance Spoilage The point at which the consumer rejects the product based on the appearance texture flavor or odor Freshness Freshness is taken to be the opposite of spoilage indicating that the fish is of good quality A major objective of the fish industry is to produce a high quality product at minimal cost Sveier 1998 Therefore the assessment of quality is an important factor in the production and sale of fishery products Also the assessment of the spoilage of fish products is of interest to the fishery and aquaculture industry in relation to consumer health Fish product s shelf life here understood as the time in storage until the sensory and or biochemical properties indicate spoilage can be short and variable due to a number of environmental and chemical factors Dalgaard 2000 Determination of shelf life is of importance for creating processing and distributing conditions that prevent the product s rejection by the consumer Also determination of shelf life is crucial to establish whether the product is in compliance with guidelines for handling and the purchase agreement promised the consumer Dalgaard 2000 A clear indication of quality concerning fish and the extent of its shelf life 1s thus of interest to the producer and the consumer Therefore it is important to define how quality and spoilage of products is assessed in the fish industry Here we will differentiate between quality and sp
170. urposes and for other analysis methods such as Mass Spectrometry To find compounds in the online database use the search field at the top of the database Screenshot 44 Set the search parameter on the side of the text field to Metabolite and type the compound name into text field This will generate a list of best matches to your search If this search function is insufficient to locate the compound use the advanced search function The list of compounds Screenshot 45 search example alanine will display the compound name in the middle the hmdbID number to the left and the structure of the compound to the right Click the hmdbID number of the compound on the left side to access its page This will bring you to the main page of the compound This page contains information about the compound n Human Metabolome Database Search R hmdb ca ii 1 HMDB se arch mioads About Contact Us Searching metabolites for alanine returned 123 results Displaying metabolites 1 25 of 123 in total Filter metabolites by status Expected but not quantified Detected but not quantified Detected and quantified Filter by biofluid Pe BD f Metabolites Q Search Other Fluids Saliva Cerebrospinal Fluid Urine Blood HMDB00 16 L Alanine 1 12 B Tr r a HMDB01310 D Alanine Match t HMDB3705 Ethiin Matched syn thylsulfinyl L Alanine th nyl L alanine thylsulfinyl
171. use in this study and future studies See Section 4 6 or Appendix III for an introduction to the software we used The results of this study are presented in the results Section 5 4 5 5 2 Experiment and chemicals The initial preparation NMR measurement and initial assignment of peaks were preformed by Shumilina 2014 A short summery of the preparation protocol for the NMR samples is seen below 5 2 1 Purchase and preparation Two Atlantic salmon Salmo salar from the same batch were bought from the same supplier Leroy located in Trondheim Norway 5 days after slaughter of the fish These samples were brought to the laboratory at the Department of Biotechnology Norwegian University of Science and Technology NTNU about an hour after purchase and promptly stored The fillets were cut into samples 25g pieces of muscle and stored on ice at a temperature of 4 C 32 5 2 2 Experiment To correctly show the development of metabolites post mortem samples were analyzed over a period of time The fillets were divided into two sets the first set stored on ice 0 C here labeled SO the second set stored at 4 C Here labeled S4 The first sample was analyzed at the day of purchase 5 days after death of the fish here labeled TO Further samples were stored and analyzed 2 T1 4 T2 7 T3 10 T4 and 14 T5 days after purchase For an overview over the experimental parameters see Table 5 Table 5 The experimental setup for the
172. use of NMR spectroscopy as a tool we will list some other common techniques used to measure metabolites here we will disregard methods which detect metabolites by their effect on fillets such as texture or color Current analytical methods for the direct measurement of metabolites in fish are Thin layer chromatography TLC gas chromatography GC mass spectrometric methods MS capillary electrophoretic methods CE and high performance liquid chromatography HPLC Onal 2007 Tejada 2009 also lists colorimetric methods multi electrode enzyme sensors and chemiluminescence CL flow injection analysis FIA These methods have been analyzed for their benefits and restrictions mostly with regard to the time taken for preforming an analysis A multi electrode enzyme sensory methods requires 5 minutes for one assay including time for preparation Tejada 2009 HPLC is a one of the most commonly used methods to assay metabolites especially in regard to K value Tejada 2009 and biogenic amines Onal 2007 HPLC has an analysis time of 20 minutes low cost ease of use and this method can be applied outside a laboratory Onal 2007 It should be noted that most methods above detect one or one set of metabolites in a given sample and usually consume the sample in the analysis process 4 5 Use of NMR as measurement tool Use of NMR spectroscopy presents a new opportunity for the measurement of metabolites Rather than measuring meta
173. veloping this functionality would be of real improvement for the use of this softwares use with NMR experiments In this section we have demonstrated that the database can analyze new unknown spectra rapidly If the database is developed to the point at which the possibility of a erroneous detection is deemed within acceptable limits and possibly if the software is given the functionality to quantify these compounds the Aurelia Amix software could provide a powerful tool for the rapid analysis of spectra for known compounds 5 6 Conclusion for the case study This case study is based on two datasets of Atlantic salmon fillets stored at different temperatures We could show a difference in the rate of breakdown between these fillets for several metabolites Nucleotides degrade slower and that TMA rises slower in samples stored at lower temperature The rise in biogenic amines and the increase in TMA possibly correlated with a drop in TMAO could indicate an infection of spoilage bacteria The relative rise in concentration of these metabolites suggests that these microbes are more active at higher temperatures Slow rising lactic acid and low concentrations of ATP ADP and AMP suggest that rigor mortis is resolved and that the fillets have a relatively low pH In use of the newly developed Aurelia Amix database showed some errors in the database and a low match percent for several compound which were detected through manual analysis Yet
174. vity as well as regulation are still not fully known Li 2009 Also the metabolic fate of taurine is still unknown Yet it is believed that taurine is not oxidized as no tissue in fish has the capacity to oxidize taurine Waarde 1988 Taurine could be excreted intact by live fish with its post mortem fate still under investigation The biological function of taurine is also still under intense investigation Taurine has been implied to play roles in fat digestion anti oxidative defense and cellular osmoregulation Li 2009 As a structural analog to GABA Taurine may be active as an inhibitor of neural impulses In relation to the quality of fish fillets little is known of taurine s role It has been described to have a serumy somewhat astringent slightly bitter taste Jones 1967 Otherwise the function of this major metabolic constituent of Atlantic salmon is unknown As an amino acid this substance may contributed to the overall flavor of the meat in cooperation with mono nucleotides as is the case with other amino acids see Section 2 2 1 2 3 2 TMAO and TMA Synthesized from TMAO is synthesized from choline in some fish in salmon mainly of exogenous origin TMA is synthesized by endogenous enzymes from TMAO in some fish bacterial origin suggested in salmon Breakdown May produce dimethylamine DMA and formalderhyd FA Function Osmolites Effect Loss of sensory quality in fish fillets producing an u
175. w This is done just as with 1D spectra Section 2 2 j I and Section 2 3 except that the filename of 2D spectra is usually 2rr i Once the spectra is loaded the noise has to be eliminated Yet this cannot be done interactively as with 1D spectra The Define noise level by number function has to be used and the noise Screenshot 15 Function icon level has to be found Using the zooming function scroll into the spectra as much as needed to SS m22 SE ETT ORAA Y E za x x make all important peaks go ys 4k gp o we MX OBB visible After this press 2 Contour levels nmr Anserine 30 pdata 1 2rr o baka define redefine contour AUG UU level on the top middle of PI ae eee a 0 120 0 the toolbar Screenshot 15 S 1B 1 do as W 14 0 A window will appear 7 0 is o 8 Lj 16 0 1 1 See o o showing the current noise Eco 2 TN definition level of the spectra asa le 2 Positive ramp l 5 on your screen Copy the Rap bs 1 o r Saooth contours number which is shown on highlighted in Screenshot 16 frs cut Eggs After this open the Define z noise level function in the Preparation drop down VM EM Screenshot 16 The define redefine contour level function window Number to menu Select the define pe copied is highlighted noise level by number option and paste the number for the noise level into the field below as
176. will direct you to a page gt LER www bruker com DL SE untitled foldery Apple Google Maps YouTube Wikipedia News Popular 7 um z E Downloads fo Windows Home Service Support amp Upgrades Software Downloads NMR PC PC Amix Aurelia AURELIA AMIX 3 9 14 for Windows NT 2000 XP Win 7 There are 4 files W Readme file for Aurelia Amix 3 9 14 2 29 kb This file contains general installation notes Please read it first 2012 d Aurelia Amix 3 9 14 13 99 mb This self extractable file contains an Aurelia Amix installation License information An AURELIA 3 0 license is needed to run Aurelia including the viewer An AMIX 3 0 license is needed to run Amix including the viewer With an AMIX_VIEWER 3 0 license the viewer can be used With an SBASE 1 1 1 license the sample spectra base can be used Free demo licenses can be obtained by filling out the license form Supply the host ID of the machine on which the demo license should be installed including help files and release letter but without the software manuals d Readme file for SpectraBase 1 1 2 2 66 kb March 2012 d SpectraBase 1 1 2 4 32 mb This is a collection of about 650 1D and 2D NMR spectra in compressed and encrypted format The data may be used by the Amix Tools 2012 Screenshot 1 The AURELIA AMIX main download page accessed on 21 05 2014 containing several download links Screensho
177. will open a window on the left side of your Amix viewer which amp s c Jt z3 Ami Viewer version 3914 ole allows you to manually fE c S salar Ze 22S BIT 09 AQAA 8 Za E z ges SY AA4 c e0R aa8 browse your Sbase ZGCPPR mmcd clem D20 opt topspin216 mfjpfre 1 H9 193 eqs pin sa Firstly you will see a c S salar ref civrulline 1 1dnosey 1r 7 aspartate ATP 2 butendicl 23 2 choline 758 sei i 9 citrulline ose HMDB00904 list of all Spectral Bases that have C g J registered in the Amix o software Click the database you wish to browse and a drop inar d window with a list of 7 glucose alpha 7 glucose beta all compounds defined will appear Click any of the compounds to view a list of all Screenshot 21 The Amix Viewer window with the SBase Browser open on the side spectra molecular and with open drop down menu info files currently defined Screenshot 21 Clicking these files will open them in the Amix Viewer This method of manually opening compounds is very comfortable but it is not efficient for large Sbases or for opening groups of specific spectra Another method for opening spectra or compounds from your Sbase is to use the Open file from Sbase or the Open compound from Sbase functions found under the File drop down menu Open file from Sbase will allow you
178. wish to AutoSelect Unselect Cancel attach the file to Screenshots 19 E d and confirm The molecular file is now attached to the compound Screenshot 19 The compound selecting when adding a coordinate file and can be opened from the Sbase browser as explained later Section 5 81 2 9 Other Other information such as lists of peaks in the spectra pH ranges of the experiments and larger amounts of molecular data can be attached to each spectra This however is beyond the scope of this manual If this type of information is of interest please see the official Amix Aurelia user manual 2 10 Giving Compounds additional names The function Edit compound names under the Spectral Base drop down menu in Amix tools can be used to give your compound multiple names Compounds with multiple names will still show under their EE E Amix Viewer version 39 14 EUUCCULUORUE normis fuus Patterns Mea ATP lemon adenosine triphosphate given name when you browse your Sbase e um as explained later Section 3 but when 2 5m 2 2 sg UDYASAOIBSEO a i y E c S salar ref arginine HM psa ett ate ee aaa A ee imc e Screenshot 20 The Alternate names window Cancel O opt tt inine 1di rer searching for compounds by name the compound will respond with

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