Patent Publication Number: US-2007122844-A1

Title: Reduction of redundant protein identification in high throughput proteomics

Description:
CROSS-REFERENCE TO RELATED APPLICATION  
      This application claims priority from U.S. provisional application No. 60/713,373 filed Sep. 2, 2005 and entitled METHOD FOR IDENTIFYING PROTEIN. 
    
    
     FIELD OF THE INVENTION  
      The present invention relates to the field of proteomics. More specifically, the invention relates to the identification of proteins in a protein mixture using peptides and protein databases.  
     BACKGROUND OF THE INVENTION  
      A fundamental goal of proteomics is the systematic simultaneous analysis of large numbers of proteins in biological samples. Automated, high-throughput analyses of complex protein mixtures are presently a matter of routine, made possible by the application of soft-ionization methods to mass spectrometry, and the sequencing of an ever increasing number of genomes. These innovations permit the identification and characterization of proteins with greater sensitivity, shorter analysis times, more consistency in the analysis process, and the flexibility of multiple assays. Global analyses such as these will provide a comprehensive framework within which more traditional, studies directed to individual proteins can be carried out.  
      In shotgun proteomics, protein samples are generally enzymatically digested into smaller peptide fragments to make them amenable to sequence analysis by mass spectrometry [1]. The resulting complex peptide sample is then separated in time, using liquid chromatography (LC), and coupled to a tandem mass spectrometer so that peptides can be detected and selected for fragmentation as they elute.  
      Tandem mass spectrometry uses two mass analyzers. The first mass analyzer selects a single peptide mass from the initial mass spectrum (MS) by filtering out all other masses. The single peptide is then fragmented in a collision cell and the second mass analyzer acquires the resulting fragmentation spectra (MS/MS). Peptides typically fragment along the polypeptide backbone rather than in the side chains. Consequently, the series of ions generated by fragmentation can be used to determine the amino acid sequence of the peptide. Protein database searches find all candidate peptides that match the mass of the parent ion to peptides in silico protein digests, then rank the candidates based on the matching theoretical and experimental fragmentation spectra [2, 3]. Proteins containing the identified peptides are then considered to have been identified. There is growing evidence that the number of MS/MS mass spectra (queries) associated with a protein identification provide a measure of relative protein abundance [4, 5].  
      Unfortunately, identification of proteins in this way yields a redundant list of proteins due to redundancies in peptide identifications, redundant database entries, and gene products that have long stretches of conserved sequence identity. This redundancy must be eliminated to correctly interpret the biological significance of the results or to peptide counts to estimate abundance. A common approach is to group the protein hits on the basis of sequence similarity (e.g. [6]); this is laborious, time-consuming, subjective and is based on derived results (protein sequence) rather than primary data (peptide sequence). Another approach uses a probabilistic analysis to select the proteins with the highest likelihood of being present based on a knowledge of the probability that the individual peptide identifications are correct [7].  
     SUMMARY OF THE INVENTION  
      The present invention provides a simpler, set-based approach to the elimination of redundant protein identifications that yields the minimum number of proteins needed to explain the peptides observed.  
      In a broad embodiment of the invention, there is provided a method for identifying proteins in a mixture of proteins comprising: providing peptides derived from the mixture of proteins; obtaining mass spectra of the peptides to identify the peptides by comparing the mass spectra with spectra of a standardized database; matching the identified peptides with proteins in a database to generate a protein hits (PHs) list, each of the PHs having an associated peptides set; and identifying PHs having an associated peptides set that is included in at least one other PH-associated peptide set; and removing the identified PHs from the list and wherein remaining PHs provides an identification of the one or more proteins.  
      In another embodiment there is provided method as described above further comprising grouping the identified PHs that share a same set of peptides in primary protein groups and wherein each of the primary protein group identifies a non-redundant PH.  
      In another aspect the method can also comprise combining all primary protein groups that share at least one common characteristic among the non-redundant PH to generate secondary protein groups and identifying a non-redundant PH for each of the secondary protein groups based on the characteristic.  
      In another embodiment there is provided a method for reducing redundancy in a protein hits list, comprising: associating a set of peptides with each protein of the protein hits to generate PHs-associated peptide sets; comparing the set PHs-associated peptide sets; identifying PHs having an associated peptides set that is included in at least one other PH-associated peptides set; and removing the identified PHs from the list and wherein remaining PHs provides an identification of the one or more proteins.  
      The invention also provides a device for identifying proteins in a mixture of proteins, the device comprising a data input means for inputting peptide analysis results, a peptide database, a protein database, a first analyzer to identify the peptides, a second analyzer to match the identified peptides with proteins in the protein database to create protein hits (PH) and to create peptide sets associated with PHs, a comparator for comparing PH associated sets of peptide and for eliminating redundancy in PHs, and a display to display identified PH substantially free of redundancy.  
      In another embodiment, the invention also provides a computer readable medium with computer executable instructions for performing a method for identifying proteins comprising matching identified peptides obtained from a protein mixture with proteins in a database to generate protein hits (PH) each of said PHs having an associated peptide set; and eliminating PHs having a peptide set that is included in at least one other PH-associated peptide set thereby producing a set of PHs substantially free of redundancy. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
      Further features and advantages of the present invention will become apparent from the following detailed description, taken in combination with the appended drawings, in which:  
       FIG. 1  is an example of information contained in a protein hits (PH) array;  
       FIG. 2  is a graphic showing proteins hits and their associated peptides for a hypothetical proteomics experiment demonstrating how peptides may be shared among hits in various ways;  
       FIG. 3  is a table array showing the correspondence between PHs and peptides sets from the data of  FIG. 2 ;  
       FIG. 4  is a distribution of the number of proteins (from rat) containing peptides having 6-30 amino acids;  
       FIG. 5  is a table array showing the correspondence between primary protein groups, PHs and PEPTIDEID;  
       FIG. 6  is a flow chart algorithm to group PHs;  
       FIG. 7  is a schematic representation of a result of adjacency analysis showing the connectivity between secondary groups;  
       FIG. 8  is a graphic of PHs and associated peptides in a typical proteomics experiment;  
       FIG. 9  is a graphic showing the results of applying the method of the invention to the data of  FIG. 8 ;  
       FIG. 10  is a graph showing the linkage for secondary grouping for the ABRF sample;  
       FIG. 11  is a schematic representation of the sequences of PHs in a secondary group from  FIG. 10  wherein horizontal bars represent areas of common peptides and stars represent areas of different peptides;  
       FIG. 12  is a graph showing the relative abundance of the 8 proteins in the ABFR sample estimated from the redundant peptide counts compared to knowon values. 
    
    
     DETAILED DESCRIPTION OF THE INVENTION  
      Protein Identification  
      A. Data Representation  
      Protein identification algorithms operate in three stages. First, experimental fragmentation (ms/ms) mass spectra are matched to theoretical spectra from an in silico digestion of sequences in a protein database. Next, the matches are examined in some way to determine those which are valid. Finally, the proteins containing identified peptides are determined. Irrespective of the tools used, the results may be considered to consist of a set of protein hits PHs, each comprising a protein identifier and the associated set of peptides used to identify it. For example, let us assume that the protein hits are stored as a structure array, PH, having the fields defined in  FIG. 1 . It will be appreciated that the array can contain other information associated with a particular PH such as for example functional information regarding the identified protein, species (taxonomy) from which the protein sequence is derived, number of associated peptides and the like.  
      In practice, the protein hits resulting from the analysis of complex mixtures are found to be quite redundant. This is illustrated in  FIG. 2  which shows the results of a hypothetical experiment in which 13 peptides were identified leading to the generation of 8 protein hits. However, inspection of this plot reveals that only 4 hits ( 1 , 2 , 4 , 5 ) have peptides which occur uniquely. Thus, the peptides for hit  3  are a subset of those for hit  2  while the peptides of hits  6 ,  7  and  8  are also found in hits  4  &amp;  5 . Indeed the peptides of hit  7  are a subject of hit  5  while the same applies to hits  8  and  6 . The data of  FIG. 2  are reproduced in tabular array in  FIG. 3 .  
      Moreover, there are cases where the peptides from one hit are a subset of those identifying another (e.g. hits  3  and  2  in  FIG. 2 ). That is 
 
[PH (i).PEPTIDEID] ⊂ [(PH). PEPTIDEID]
 
      Such hits are redundant since postulating the existence of protein j can explain all of the peptides in both hits i and j. There is no evidence that protein i is present although its existence cannot be ruled out.  
      B. Redundant Peptide Identifications  
      The first source of redundant protein identifications is that a single mass spectrum may be matched to more than one peptide. Search algorithms, such as Mascot™ and Sequest™ [2, 3], identify peptides by matching fragmentation spectra to an in silico digest and evaluating the goodness of fit in some way. There are a number of amino acids whose masses cannot be distinguished by mass spectra data (e.g. isolucine and leucine are structural isomers while lysine and glutamine have the same nominal mass). Consequently, peptides whose sequences differ only by interchanges of such amino acids cannot be distinguished by mass spectra and so will result in redundant peptide identifications. In addition, there may also be cases in which an experimental spectrum matches more than one theoretical spectra well. Examination of a number of data sets from rat liver organelles revealed that approximately 5% of the mass spectra match two or more peptides.  
      C. Redundant Peptide to Protein Mapping  
      A second source of redundant protein identifications is that a particular peptide may occur in more than one protein sequence in the database. This can result from database inconsistencies including redundant entries in the database, partial sequences, and splice variants. It may also arise biologically from proteins that are closely related gene products having long stretches of conserved sequences as occurs in closely related gene products. An in silico analysis of all the tryptic peptides in the NCBI nr database [8] with taxonomy restricted to rat, suggests that only about 15% of peptides occur in more than one protein sequence. However, tandem mass spectrometry only identifies peptides between 6 and: 30 amino acids. These shorter peptides are much less specific and as  FIG. 4  shows, more than 45% of these peptides occur in two or more proteins. The number of redundant peptides can be expected to increase when searches are carried using a wider range of taxonomies.  
      In the present invention there is provided a set-based algorithm that eliminates or reduces redundancy in protein identification. The method can be applied to already established list of PHs or may include the preparation of peptides using enzymatic digestion and mass spectrometry to identify the peptides and the proteins using standardized databases. In one embodiment all PHs that have a peptides set that is included in any other PH are eliminated from the PHs list. The remaining PHs provide an identification of the protein(s) in the mixture of proteins.  
      Protein hits, PHs, that share the same set of peptides can be grouped together to form a protein group PG. For a PG, 
 
[PH (i).PEPTIDEID] ⊂ [PG.PEPTIDEID] ∀ i  in PG
 
      In the present description a group defined based on the above definition is referred to as a primary Protein Group or PG 1 .  FIG. 5  provides an example of PG 1 s formed based on the above definition and on the data of  FIGS. 2 and 3 . PG 1   2 , PG 1   4  and PG 1   5  comprise more than one PH. Not all protein hits in a group need have all the peptides associated with the group. Within a group the protein comprising the most peptides (NPEPTIDEID) is identified as the nun-redundant PH (the other peptides being redundant) and is included in the protein list that serves to identify the proteins in a mixture. In other words the redundant PHs are eliminated from the protein list.  
      The algorithm used to define the protein identification group is illustrated in  FIG. 6 . It takes as its input PH, a structure array of redundant protein hits, and generates the output PG 1 , a structure array containing the non redundant protein identification groups.  
      Groups can be defined iteratively by first sorting the protein hits by the number of peptides they each contain. Then all hits defined by sets of peptides contained within the initial set are found and merged into the first group. Hits assigned to a group are eliminated from the list of protein hits and the procedure repeated until all hits have been assigned.  
      Redundancy can be further reduced by performing an adjacency analysis of the primary protein groups. This analysis joins primary protein groups that share at least one peptide among themselves into secondary protein groups. That is to primary protein groups for which the non-redundant PHs share at least one peptide are placed in a secondary protein group. Then the connectivity of each primary protein group within a secondary protein group is established. By connectivity it is meant the number of primary protein groups with which a given primary protein group shares at least one peptide. Referring back to  FIG. 5 , it can be seen that PG 1   3 , PG 1   4  and PG 1   5  share PEP 9  and would therefore be grouped as a secondary protein group. It can further bee seen that the connectivity for PG 1   3 , PG 1   4  and PG 1   5  is 2. That is to say PG 1   3  is connected with the other two groups (PG 1   4  and PG 1   5 ) and similarly for PG 1   4  and PG 1   5 . Secondary grouping with connectivity is shown in  FIG. 7 .  
      The redundant PHs of a secondary protein group can be determined based on the connectivity. Thus for example, the primary protein group having the highest connectivity can be identified as the non-redundant PH of a secondary protein group. All other primary protein group associated non-redundant PHs would be eliminated from the list of PHs.  
      It will be appreciated that proteins that are identified as being redundant using the adjacency analysis are proteins for which the sequences are potentially highly related. For example a same protein obtained from different species, proteins exhibiting allelic variations, proteins in a database with sequencing errors and the like.  
      It will also be appreciated that criteria other than or in addition to peptide sharing among primary protein groups could also be applied in the adjacency analysis. For example, secondary grouping could be based on protein function, protein length and other such protein characteristics.  
      Query Counting  
      There is growing evidence that the number of MS/MS mass spectra (queries) associated with a protein identification are related in some way to the protein abundance [4, 5]. Consequently, the mass spectra information underlying the identification of each group is summarized by counting the associated peptides. Three peptide counts can be determined for each group. Thus, 
          N U  is the number of peptides which occur only in the group     N S  is the number of peptides that are shared with other groups     N P  is the pro-rated number of peptides that combines N U  with N S  weighted by the relative number of unique queries in the associated queries.      It is defined by:  
           N   P     ⁡     (   i   )       =         N   U     ⁡     (   i   )       +         N   S     ⁡     (   i   )       [         N   U     ⁡     (   i   )           ∑     j   =   1       j   =   nhits       ⁢       N   U     ⁡     (   j   )           ]           
       

      Thus the relative abundance of a non-redundant PH can be determined by providing a count of all the queries (peptides) associated with the corresponding primary or secondary protein group.  
      The method of the invention can be implemented in part using computer-based system and methods as would be known to one skilled in the art.  
      The invention also provides a device for identifying proteins in a mixture of proteins, the device comprising a data input means for inputting peptide analysis results, a peptide database, a protein database, a first analyzer to identify the peptides, a second analyzer to match the identified peptides with proteins in the protein database to create protein hits (PH) and to create peptide sets associated with PHs, a comparator for comparing PH associated sets of peptide and for eliminating redundancy in PHs, and a display to display identified PH substantially free of redundancy.  
      In another embodiment, the invention also provides a computer readable medium with computer executable instructions for performing a method for identifying proteins comprising matching identified peptides obtained from a protein mixture with proteins in a database to generate protein hits (PH) each of said PHs having an associated peptide set; and eliminating PHs having a peptide set that is included in at least one other PH-associated peptide set thereby producing a set of PHs substantially free of redundancy.  
     EXAMPLES  
     Example 1  
      We evaluated the algorithm by analyzing a representative data set from an organellar proteomics experiment using methods similar to those described in [4]. The raw data comprised 13,587 tandem mass spectra acquired from 93 bands from a 1 D gel of a sample of rat rough microsome. Mass spectra were first subjected to peak-detection using a commercial product (Mascot Distiller from Matrix Science) and the resulting peak-lists searched against the NCBI nr database [8] with taxonomy limited to rat using a probability-based search engine (Mascot from Matrix Science). A total of 5,685 mass spectra were assigned to peptides with a probability of random hit being less than 5%. There were 3,498 distinct peptide identifications. The search results were loaded into CellMapBase, our relational database for proteomics analysis [9] and analyzed using the method of the invention.  
       FIG. 8  illustrates the distribution of peptides across the protein hits identified from this data set. As in  FIG. 2 , it is evident that there are many shared peptides. Indeed more than a third of the protein hits contain one or more peptides that are shared among at least two hits. The complexity of this plot illustrates the difficulty of attempting to eliminate redundant identifications by manual analysis.  
       FIG. 9  shows the results of applying the grouping algorithm to the data from  FIG. 8 . It is evident that the number of proteins identified (protein groups) is substantially smaller and there are far fewer shared peptides.  
      Table II provides the quantitative support for this information. Grouping decreased the number of proteins identified by more than 40% and increased the number of proteins identified by unique peptides from 512 to 600. Taken together, the percentage of identifications using only unique peptides from 35.2% to 80.1%.  
      This grouping algorithm provides an objective, automated means to eliminate redundancy in protein identifications in high throughput proteomic experiments. However, as  FIG. 9  demonstrates, it does not completely eliminate shared peptides, presumably reflecting the presence of distinct, but closely related proteins. The algorithm also identifies a few groups, (e.g. hits  6  &amp;  8  in  FIG. 2 ) with only shared peptides that cannot be assigned to any protein with confidence.  
     Example 2  
      The Association of Biomolecular Resource Facilities (ABRF) recently circulated two samples containing 8 proteins in different amounts to assist laboratories in evaluating their ability to identify and quantify unknown proteins. This example describes the analysis of these samples using the proteomics pipeline.  
      Analysis Methods  
      The two ABRF samples were resolved on separate 1D-SDS PAGE gel lanes and subjected to standard band slicing, in-gel trypsinization and LC-coupled mass spectrometry. Peak lists were generated using. Mascot Distiller with optimized parameter values. Peptides were identified using Mascot to search the NCBI nr database with taxonomy limited to mammals. Peptides identified in the two samples were used to identify the proteins present and group them, according to the method described above into distinct sets to define the minimal set of proteins necessary to explain the observed peptides.  
      Table 2 shows the 59 protein groups defined by distinct sets of peptides initially identified.  
      Adjacency Analysis (Secondary Grouping)  
      Sets of closely related proteins groups were determined by adjacency analysis to generate secondary protein groups.  FIG. 10  shows a graph of the relations between groups. Five “islands”—sets of groups which share peptides only among themselves—are apparent  
      Related Proteins  
      Each “island” in  FIG. 10  appears to comprise closely related proteins which appear to be variants of the same protein.  FIG. 11  shows the relation among groups in the first island using Group number 627667 as a reference. It is evident that: the proteins contain extensive regions with the same sequences (blue)•sequence difference were minor (yellow), most peptides are shared (red)•different groups were defined by a few peptides (green) corresponding to sequence difference.  
      This confirms that proteins in each island are highly related, probably as a results of sequence redundancy among species.  
      Final Results  
      Groups in each island were collapsed together and grouping repeated. Seven of the 8 most abundant proteins corresponded to those in the ABRF samples. 1 ABRF protein, horseradish peroxidase, was not identified since the search taxonomy was limited to mammals (table 3)  
      Relative Abundance  
      Relative abundance of 6/8 ABRF proteins was estimated from the ratio of spectral counts. Estimates were not possible for: Horseradish peroxidase since this was not identified; Beta Casein which was only identified in Sample I, where it was in the highest abundance.  
      These estimates corresponded to well to relative abundances provided by ABRF.  
      Conclusions  
      Seven of the eight proteins in ABRF sample were identified conclusively. Estimates of their relative abundances in the two samples based on spectral counts agreed well with expected values; Protein identification by data base search is complex if taxonomy is unrestricted.  
     REFERENCES  
     
         
          [1] R. Aebersold and M. Mann, “Mass spectrometry-based proteomics,” Nature, vol. 422, pp. 198-207, 2003.  
          [2] D. N. Perkins, D. J. Pappin, D. M. Creasy, and J. S. Cottrell, “Probability-based protein identification by searching sequence databases using mass spectrometry data,” Electrophoresis, vol. 20, pp. 3551-67, 1999.  
          [3] J. Eng, A. McCormack, and J. R. I. Yates, “An approach to correlate tandem mass spectral data of peptides with amino acid sequences in protein data base,”J. Am. Soc. Mass Spectrom., vol. 5, pp. 976-989, 1994.  
          [4] F. Blondeau, B. Ritter, P. D. Allaire, S. Wasiak, M. Girard, N. K. Hussain, A. Angers, V. Legendre-Guillemin, L. Roy, D. Boismenu, R. E. Kearney, A. W. Bell, J. J. Bergeron, and P. S. McPherson, “Tandem MS analysis of brain clathrin-coated vesicles reveals their critical involvement in synaptic vesicle recycling,” Proc Natl Acad Sci USA, vol. 101, pp. 3833-8, 2004.  
          [5] H. Liu, R. G. Sadygov, and J. R. Yates, 3rd, “A model for random sampling and estimation of relative protein abundance in shotgun proteomics,” Anal Chem, vol. 76, pp. 4193-201, 2004.  
          [6] L. J. Foster, C. L. De Hoog, and M. Mann, “Unbiased quantitative proteomics of lipid rafts reveals high specificity for signaling factors,” Proc Natl Acad Sci USA, vol. 100, pp. 5813-8, 2003.  
          [7] A. I. Nesvizhskii, A. Keller, E. Kolker, and R. Aebersold, “A statistical model for identifying proteins by tandem mass spectrometry,” Anal Chem, vol. 75, pp. 4646-58, 2003.  
          [8] D. A. Benson, I. Karsch-Mizrachi, D. J. Lipman, J. Ostell, and D. L. Wheeler, “GenBank,” Nucleic Acids Res, vol. 33, pp. D34-8, 2005.  
          [9] Z. Bencsath-Makkai, A. Bell, J. Bergeron, D. Boismenu, M. Harrison, W. R. J. Funnell, C. Mounier, J. Paiement, L. Roy, and R. E. Kearney, “CellMapBase—An Information System Supporting High Throughput Proteomics for the Cell Map Project,” presented at Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Cancun, Mexico, 2003.  
       
    
      All references cited herein are incorporated by reference.  
      While the invention has been described in connection with specific embodiments thereof, it will be understood that it is capable of further modifications and this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosures as come within known or customary practice within the art to which the invention pertains and as may be applied to the essential features herein before set forth, and as follows in the scope of the appended claims.  
               TABLE I                          RESULTS OF ELIMINATING REDUNDANT       IDENTIFICATIONS                             Protein Hits   Protein, Groups                                             Total number   1,449   824           Number with no shared   512   660           peptide           Percentage with no   35.2   80.1           shared peptides                      
 
     
       
         
           
               
             
               
                 TABLE II 
               
             
            
               
                   
               
               
                   
               
               
                 Protein Groups identified for the two ABRF samples. 
               
               
                 Prorated queries is the number of spectra associated with each group. 
               
               
                 Protein Groups for the ABRF Sample 
               
            
           
           
               
               
               
               
               
               
               
            
               
                   
                   
                   
                   
                   
                 PERCENT 
                 PRORATED 
               
               
                   
                 CLUSTERID 
                 REFERENCE 
                 DESCRIPTION 
                 SPECIES 
                 COVERAGE 
                 QUERIES 
               
               
                   
                   
               
            
           
           
               
               
               
               
               
               
               
            
               
                 1 
                 626780 
                 Q362R2 
                 ALB protein 
                 
                   Bos taurus 
                 
                 62.4 
                 325.9 
               
               
                 2 
                 625784 
                 P80025 
                 Lactoperoxidase precursor LPO 
                 
                   Bos taurus 
                 
                 45.6 
                 206.0 
               
               
                 3 
                 626785 
                 76365302 
                 hypothetical protein LOC531682 [ Bos taurus ] 
                 
                   Bos taurus 
                 
                 49.1 
                 119.0 
               
               
                 4 
                 626803 
                 6P00751 
                 Trypsin precursor 
                 pig 
                 46.4 
                 116.0 
               
               
                 5 
                 626781 
                 2P02769 
                 Serum albumin precursor 
                 cow 
                 55.6 
                 101.5 
               
               
                 8 
                 626787 
                 P00915 
                 Carbonic anhydrase 1 Carbonic anhydrase I Carbonat 
                 
                   Homo sapiens 
                 
                 65.4 
                 46.0 
               
               
                 7 
                 626812 
                 P11839 
                 Beta-casein precursor 
                 
                   Ovis aries 
                 
                 15.8 
                 14.0 
               
               
                 8 
                 626796 
                 11P02768 
                 Serum albumin precursor 
                 human 
                 7.4 
                 7.3 
               
               
                 9 
                 626801 
                 Q6B32D 
                 Serum albumin 
                 
                   Elephas maximus 
                 
                 4.3 
                 7.2 
               
               
                 10 
                 626805 
                 IP100717764.1 
                 SWISS-PROT:P30922 ENSEMBL:ENS8BTAP000000   
                 
                   Bos taurus 
                 
                 17.4 
                 5.0 
               
               
                 11 
                 626809 
                 4P13645 
                 Keratin, type I cytoskeletal 10 
                 human 
                 8.8 
                 3.0 
               
               
                 12 
                 626815 
                 753 
                 seminal RNase (aa 47-124) [ Bos taurus ] 
                 
                   Bos taurus 
                 
                 35.9 
                 3.0 
               
               
                 13 
                 626819 
                 3P04264 
                 Keratin, type II cytoskeletal 1 
                 human 
                 3.4 
                 3.0 
               
               
                 14 
                 626826 
                 1P33049 
                 Alpha-S2 casein precursor 
                 goat 
                 4.9 
                 3.0 
               
               
                 15 
                 626806 
                 Q3T101 
                 Hypothetical protein 
                 
                   Bos taurus 
                 
                 14.5 
                 2.0 
               
               
                 16 
                 626813 
                 Q8WVP4 
                 Quiescin Q6, isoform b 
                 
                   Homo sapiens 
                 
                 4.1 
                 2.0 
               
               
                 17 
                 626816 
                 UPI00001FE219 
                 thrombospondin 1 precursor 
                 
                   Homo sapiens 
                 
                 2.1 
                 2.0 
               
               
                 18 
                 626817 
                 539969 
                 lysozyme homolog AT-2, bone - rat (fragments) 
                 
                   Rattus norvegicus 
                 
                 100.0 
                 2.0 
               
               
                 19 
                 626818 
                 IPI00718529.1 
                 TREMBL:Q2KJ32 ENSEMBL:ENSBTAP0000001064   
                 
                   Bos taurus 
                 
                 6.8 
                 2.0 
               
               
                 20 
                 626821 
                 Q9N273 
                 Kappa-casein 
                 
                   Bos indicus 
                 
                 11.3 
                 1.0 
               
               
                 21 
                 626822 
                 UPI0000112E69 
                 Carbonic Anhydrase II 
                 
                   Homo sapiens 
                 
                 4.7 
                 1.0 
               
               
                 22 
                 626824 
                 1P10760 
                 Adenosythornocysteinase 
                 Norway rat 
                 3.0 
                 1.0 
               
               
                 23 
                 626825 
                 UPI00001104E7 
                 Angiogenin 
                 
                   Bos taurus 
                 
                 7.2 
                 1.0 
               
               
                 24 
                 626827 
                 73970109 
                 PREDICTED: similar to 3-hydroxyanthranilate 3,4-dio   
                 
                   Canis familiaris 
                 
                 4.0 
                 1.0 
               
               
                 25 
                 626828 
                 Q9N212 
                 Protein C inhibitor precursor Serine 
                 
                   Bos taurus 
                 
                 6.2 
                 1.0 
               
               
                   
                   
                   
                 (Or cysteine) prot   
               
               
                 26 
                 626829 
                 818028 
                 phosphorylase (aa 760-840) [ Rattus norvegicus ] 
                 
                   Rattus norvegicus 
                 
                 11.3 
                 1.0 
               
               
                 27 
                 626776 
                 2P00489 
                 Glycogen phosphorylase, muscle form 
                 rabbit 
                 52.8 
                 0.0 
               
               
                 28 
                 626777 
                 UPI0000110764 
                 Glycogen Phosphorylase, Muscle Form 
                 
                   O. cuniculue 
                 
                 52.9 
                 0.0 
               
               
                 29 
                 628778 
                 223003 
                 phosphorylase b, glycogen 
                 
                   O. cuniculue 
                 
                 50.9 
                 0.0 
               
               
                 30 
                 626779 
                 P02769 
                 Serum albumin precursor Allergen  Bos  d 6 BSA 
                 
                   Bos taurus 
                 
                 65.9 
                 0.0 
               
               
                 31 
                 626782 
                 NP_001009192.1 
                 muscle glycogen phosphorylase [ Ovis aries ] 
                 unidentified 
                 38.4 
                 0.0 
               
               
                 32 
                 626783 
                 UPI00004BCE81 
                 unknown 
                 
                   Canis familiaris 
                 
                 37.3 
                 0.0 
               
               
                 33 
                 626786 
                 P14639 
                 Serum albumin precursor 
                 
                   Ovis aries 
                 
                 24.4 
                 0.0 
               
               
                 34 
                 626788 
                 Q91X12 
                 Mutant catalase 
                 
                   Mus musculus 
                 
                 21.3 
                 0.0 
               
               
                 35 
                 626789 
                 NP_999466.1 
                 catalase [ Sus scrofa ] 
                 unidentified 
                 19.3 
                 0.0 
               
               
                 36 
                 626790 
                 1P04040 
                 Catalase 
                 human 
                 16.9 
                 0.0 
               
               
                 37 
                 626791 
                 NP_001002964.1 
                 Catalase [ Canis familiaris ] 
                 unidentified 
                 16.1 
                 0.0 
               
               
                 38 
                 626792 
                 Q3UZE7 
                 8 days embryo whole body cDNA, RIKEN full-length 4 
                 
                   Mus musculus 
                 
                 18.4 
                 0.0 
               
               
                 39 
                 626793 
                 Q7YSG3 
                 Serum albumin precursor Allergen Fel d 2 
                 
                   Felis catus 
                 
                 9.2 
                 0.0 
               
               
                 40 
                 626794 
                 1P11216 
                 Glycogen phosphorylase, brain form 
                 human 
                 9.8 
                 0.0 
               
               
                 41 
                 626795 
                 P00661 
                 Ribonuclease pancreatic RNase 1 RNase A 
                 
                   Capra hircus 
                 
                 76.6 
                 0.0 
               
               
                 42 
                 626796 
                 P00656 
                 Ribonuclease pancreatic RNase 1 RNase A 
                 
                   Bison bison 
                 
                 76.6 
                 0.0 
               
               
                 43 
                 626797 
                 P07848 
                 Ribonuclease pancreatic RNase 1 RNase A 
                 
                   Gazella thomsonii 
                 
                 76.6 
                 0.0 
               
               
                 44 
                 626799 
                 2P49822 
                 Serum albumin precursor 
                 dog 
                 7.2 
                 0.0 
               
               
                 46 
                 626800 
                 73966878 
                 PREDICTED: similar to Lactoperoxidase precursor (LI 
                 
                   Canis familiaris 
                 
                 8.4 
                 0.0 
               
               
                 46 
                 626802 
                 Q6R461 
                 Lactoperoxidase 
                 
                   M. auratus 
                 
                 6.1 
                 0.0 
               
               
                 47 
                 626804 
                 29P00556 
                 Ribonuclease pancreatic precursor 
                 cow 
                 45.2 
                 0.0 
               
               
                 48 
                 626806 
                 Q91WA0 
                 Lactoperoxidase 
                 
                   Mus musculus 
                 
                 5.1 
                 0.0 
               
               
                 49 
                 626807 
                 P22079 
                 Lactoperoxidase precursor LPO Salivary peroxidase Σ 
                 
                   Homo sapiens 
                 
                 4.8 
                 0.0 
               
               
                 50 
                 626810 
                 P07849 
                 Ribonuclease pancreatic RNase 1 RNase A 
                 
                   B. tragocamelus 
                 
                 50.8 
                 0.0 
               
               
                 51 
                 626811 
                 P00558 
                 Ribonuclease pancreatic RNase 1 RNase A 
                 
                   Tragelaphus oryx 
                 
                 50.8 
                 0.0 
               
               
                 52 
                 626814 
                 2P07724 
                 Serum albumin precursor 
                 house mouse 
                 6.5 
                 0.0 
               
               
                 53 
                 626820 
                 76713340 
                 PREDICTED: similar to immunoglobulin lambda-like p 
                 
                   Bos taurus 
                 
                 18.5 
                 0.0 
               
               
                 54 
                 626823 
                 248147 
                 beta-casein A2 variant [cattle, Peptide Partial, 46 aa, 
                 
                   Bos taurus 
                 
                 41.3 
                 0.0 
               
               
                 55 
                 626830 
                 UPI00005070E3 
                 PREDICTED: similar to stabilin-2 
                 
                   Rattus norvegicus 
                 
                 0.5 
                 0.0 
               
               
                 58 
                 626831 
                 76615216 
                 PREDICTED: similar to Resin precursor, partial (Bos 
                 
                   Bos taurus 
                 
                 0.5 
                 0.0 
               
               
                 57 
                 626832 
                 P00762 
                 Anionic trypsin-1 precursor Anionic trypsin I Pretrypsi 
                 
                   Rattus norvegicus 
                 
                 8.1 
                 0.0 
               
               
                 58 
                 626833 
                 NP_032499.1 
                 keratin complex 2, basic, gene 1 [ Mus musculus ] 
                 unidentified 
                 1.9 
                 0.0 
               
               
                 59 
                 626834 
                 Q8BLW1 
                 Adult male aorta and vein cDNA, RIKEN full-length en 
                 
                   Mus musculus 
                 
                 1.0 
                 0.0 
               
               
                   
               
            
           
         
       
     
     
       
         
           
               
             
               
                 TABLE III 
               
             
            
               
                   
               
               
                   
               
               
                 Protein groups and spectral counts after highly similar 
               
               
                 groups are collapsed together. Proteins matching the ABRF 
               
               
                 samples are indicated with an asterix 
               
               
                 Final Protein List 
               
            
           
           
               
               
               
               
               
               
            
               
                   
                   
                 TOTAL 
                 SAMPLE 1 
                 SAMPLE 2 
                   
               
               
                 CMBSEQID 
                 DESCRIPTION 
                 QUERIES 
                 QUERIES 
                 QUERIES 
                 RATIO 
               
               
                   
               
            
           
           
               
               
               
               
               
               
            
               
                   21478 
                 Serum albumin precursor Allergen  Bos  d 6 BSA 
                 497 
                 257 
                 240 
                 0.9 
               
               
                   69613 
                 Lactoperoxidase precursor LPO 
                 206 
                 104 
                 104 
                 1.0 
               
               
                   258 
                 Glycogen phosphorylase, muscle form 
                 178 
                 2 
                 174 
                 87.0 
               
               
                   3320409 
                 Catalase 
                 119 
                 93 
                 26 
                 0.3 
               
               
                 19160 
                 Trypsin precursor 
                 116 
                 58 
                 58 
                 1.0 
               
               
                   87406 
                 Cartonic anhydrase 
                 46 
                 17 
                 29 
                 1.7 
               
               
                   41849 
                 Ribonuclease pancreatic RNase 1 RNase A 
                 26 
                 10 
                 16 
                 1.6 
               
               
                   196 
                 Beta-casein precursor 
                 12 
                 12 
                 0 
                 0.0 
               
               
                 3384430 
                 SWISS-PROT:P30922: similar to chitinase 3-like 1 isoform 2 
                 5 
                 2 
                 3 
                 1.5 
               
               
                 69653 
                 Keratin, type I cytoskeletal 10 
                 3 
                 0 
                 3 
               
               
                 10504 
                 Alpha-S2 casein precursor 
                 3 
                 3 
                 0 
               
               
                 3323085 
                 Hypothetical protein 
                 2 
                 2 
                 0 
               
               
                 3200175 
                 Hypothetical protein 
                 2 
                 2 
                 0 
               
               
                 130837 
                 lysozyme homolog AT-2, bone - rat (fragments) 
                 2 
                 2 
                 0 
               
               
                 90453 
                 Keratin, type II cytoskeletal 1 
                 2 
                 0 
                 2 
               
               
                 16617 
                 thrombospondin 1 precursor 
                 2 
                 0 
                 2 
               
               
                 3465 
                 Quiescin Q6, isoform b 
                 2 
                 0 
                 2 
               
               
                 3280346 
                 PREDICTED: similar to 3-hydroxyanthranilate 3,4-dioxygenase (3-HAO) 
                 1 
                 1 
                 0 
               
               
                 148437 
                 Angiogenin 
                 1 
                 0 
                 1 
               
               
                 105809 
                 phosphorytase (aa 760-840) 
                 1 
                 0 
                 1 
               
               
                 54409 
                 S-Adenosythomocysteine Hydrolase 
                 1 
                 1 
                 0 
               
               
                 39122 
                 Protein C inhibitor precursor Serine (Or cysteine) proteinase inhibitor 
                 1 
                 0 
                 1 
               
               
                 19180 
                 Carbonic Anhydrase II 
                 1 
                 0 
                 1 
               
               
                 483 
                 Kappa-casein 
                 1 
                 1 
                 0 
               
               
                 3368768 
                 Similar to immunoglobulin lambda-like polypeptide 1 precursor 
                 0 
                 0 
                 0 
               
            
           
           
               
               
            
               
                   
                 (Immunoglobulin-related 14.1 protein) 
               
            
           
           
               
               
               
               
               
            
               
                 3361675 
                 TREMBL:Q6Q144 REFSEQ:XP_618382 PREDICTED: similar to Reefin 
                 0 
                 0 
                 0 
               
            
           
           
               
               
            
               
                   
                 precursor, partial 
               
            
           
           
               
               
               
               
               
            
               
                 2734641 
                 PREDICTED: similar to stabilin-2 
                 0 
                 0 
                 0 
               
               
                 242220 
                 Adult male aorta and vein cDNA, RIKEN full-length enriched library 
                 0 
                 0 
                 0 
               
               
                 79094 
                 beta-casein A2 variant [ 
                 0 
                 0 
                 0 
               
               
                 75054 
                 Anionic trypsin-1 precursor Anionic trypsin I Pretrypsinogen I 
                 0 
                 0 
                 0 
               
               
                 37492 
                 keratin complex 2, basic, gene 1 [ Mus musculus ] 
                 0 
                 0 
                 0