Journal of Proteome Research ARTICLE Figure 6. Venn diagram of numbers of antigens with categorized enriching features. Enriching features are classiﬁed into three categories: (1) COGs- UMNO, for proteins assigned to one or more of these four COGs; (2) Computational predictions with enriching features, for proteins predicted to have one or more of the following features, that is, TMHMM = 1, SignalP > 0.7, pSort Outermembrane, pSort Periplasmic, or pI < 5, and (3) Protein expression as detected by peptide presence in Mass Spectrometry. Separately shown are numbers of antigens with enriching features, including all such 1128 antigens on chip, 99 serodominant, and 30 serodiagnostic antigens. Numbers of antigens having more than one category of enriching features are also presented in the overlapping region of such categories. Table 2. Enrichment Summary for Antigens with Categorized Enriching Featuresa whole genome (3046 on chip) cross-reactive (89 total) serodiagnostic (33 total) enriching features predicted % of total predicted % of total predicted % of total COGs-U, M, N, O 338 11% 27 30% 10 30% Computationally Predicted 696 23% 47 53% 20 61% Mass Spectrometry Positive (MS+) 356 12% 21 24% 20 61% COGs + Predicted 919 30% 60 67% 22 67% COGs + Predicted + MS+ 1128 37% 69 78% 30 91% Predicted + MS+ 925 30% 58 65% 29 88% a Enriching features are classiﬁed into three categories: (1) COGs-UMNO, for proteins assigned to one or more of these four COGs; (2) Computational predictions with enriching features, for proteins predicted to have one or more of the following features, i.e., TMHMM = 1, SignalP > 0.7, pSort Outermembrane, pSort Periplasmic, or pI < 5; and (3) Protein expression as detected by mass spectrometry. Numbers of overlapping antigens for two or three categories are shown in Figure 6. were printed on our proteome chip. Not surprisingly, expression was a signiﬁcant enriching feature with 5.2-fold enrichment among serodiagnostic antigens (p-value 1.87 10 11), and 2.9- fold in serodominant antigens (p-value 5.28 10 11) (Table 1). Interestingly, the fold enrichment was directly proportional to the number of peptides detected (Figure 5C). There was 8.4- fold enrichment of serodiagnostic antigens in proteins detected with more than 1 peptide (p-value 3.56 10 12), 16.2- fold in pro- teins detected with 5 or more peptides (p-value 1.30 10 7), 23.1- fold enrichment in proteins detected with 7 or more peptides (p-value 1.90 10 5), and 20.5-fold enrichment in proteins detected with 9 or more peptides (p-value 3.91 10 3). Conversely, proteins that were not identiﬁed by MS were signif- icantly underrepresented at 0.4-fold among the serodiagnostic and 0.8-fold among serodominant antigens. The data suggests that protein expression level is an important factor contributing to antigenicity of protein antigens. This was also supported by data in other experimental systems from diﬀerent research groups.55 There are a total of 10 enriching features that fall into 3 categories: (i) functionally annotated COGs U, M, N and O, (ii) computationally predicted features (TMHMM = 1, SignalP > 0.7, pSort Outermembrane, pSort Periplasmic, and pI < 5), and (iii) MS evidence of expression. The Venn diagrams summarize the number of enriched proteins found in each of these 3 categories, showing overlap among the proteins found in each category (Figure 6). There are 338 proteins in the enriched COG categories, 696 computationally predicted proteins, and 356 proteins that were positive by MS (Table 2). Accounting for the overlap between categories, 1128 proteins in all enriched categories represented 37% of the proteome. The microarray results empirically identiﬁed 33 serodiagnostic antigens and 89 cross-reactive antigens. COGs accounted for 30% of the sero- diagnostic hits, the computationally predicted features accounted for 61% of the hits, and MS positive proteins contained 61% of the hits. All together the three categories account for 37% of the proteome and include 91% of the serodiagnostic antigens. But there is only 1 unique serodiagnostic COG antigen that is not represented in either the computationally predicted or MS+ categories (BMEI1060, Table S1, Supporting Information). So by combining the pool of computationally predicted and MS+ proteins representing 30% of the proteome, 88% of the sero- diagnostic antigens can be predicted. 4820 dx.doi.org/10.1021/pr200619r |J. Proteome Res. 2011, 10, 4813–4824