research articles Lin et al. Figure 4. Relationship between fractionation effect and Cys-peptide abundance in (A) yeast and (B) RKO cell proteins. Layout of plots is as for Figure 2, except that IEF subfractions 4, 5, and 6 (A) or IEF subfractions 4, 5, 6, and 7 (B) were substituted for the E fraction in IBB fractionated samples. RKO proteomes, even though the abundance of Met-peptides approximates that of Cys-peptides in the database. Next, we directly evaluated the fractionation effect. Our triplicate IEF-LC-MS/MS analyses of yeast peptides (100 µ g) from the G fractions yielded 58094 conﬁdently identiﬁed spectra, whereas only 20443 were found in the E fraction (Figure 2). This suggested an apparently lower complexity of the E fraction relative to the G fraction. Analysis of the lower complexity E fraction could yield identiﬁcations not seen in the more complex G mixture. To model the fractionation effect, we reanalyzed both the entire G fraction and also selected IEF fractions 4, 5 and 6, which together yielded 19 042 identiﬁed spectrasthis is close to the total of 20 443 conﬁdently identiﬁed spectra found in the E fraction. If a fractionation effect contributed to enrichment, we would ﬁnd a signiﬁcant number of proteins with higher spectral counts in the sample assembled from the IEF 4, 5, and 6 subfractions than in the entire G fraction. However, analysis of the data (Figure 4A) indicated that only 9 yeast proteins were found to be slightly enriched (i.e., positive log2 (G4,5,7/G) values). This is in contrast to the much more dramatic effect of IBB captures842 cysteine- containing proteins were found to be enriched in the IBB- selected E fraction, which represented the same number of spectra (see Figure 2B). We repeated this experiment in yeast by selecting either IEF fractions 3, 8, and 9 or fractions 1, 2, 7, and 10 from the G fraction, whose summed spectral counts were 18 360 and 20 548, respectively, were also close to the 20 443 spectra represented by the IBB-captured E fraction. Again, these selected subsets of the G fraction showed no enrichment as a result of IBB capture (data not shown). The same analysis with the RKO proteome selected fractions 4, 5, 6, and 7 from the global sample identiﬁed 24 563 spectra, which is close to the 22 828 spectra found in the E fraction from RKO cells following IBB capture. No enrichment of peptides in the selected fraction was detected as a result of IBB capture (Figure 4B). These data conﬁrm that the enrichment detected as a result of IBB capture was due to the chemoselective enrichment of Cys-peptides in the E fraction, rather than to a simple fractionation effect that reduced the complexity of the E fraction. Impact of Chemoselective Cys-Peptide Capture on Detection of Low Abundance Proteins. Gygi et al.4 demon- strated that Cys-peptide enrichment with an ICAT reagent combined with strong cation exchange fractionation of peptides 5468 Journal of Proteome Research Vol. 9, No. 10, 2010 and LC-MS/MS expanded coverage of the yeast proteome. The combination of ICAT and multidimensional LC-MS/MS ap- proach increased the detection of lower abundance yeast proteins, as estimated by codon bias values, which provide an indirect measure of abundance.44,45 Since that work, a major advance in the ﬁeld was the publication of direct measurements of yeast protein abundance by a quantitative TAP tag ap- proach.43 Of the 3025 yeast proteins we detected, 2088 (69%) were annotated for expression level in the yeast TAP tag data set. These proteins were allocated into bins based on TAP tag copy number and the log2 (E/G) values were plotted (Figure 5). The mean log2 (E/G) value for each bin was inversely proportional to expression copy number. ANOVA analyses indicated signiﬁ- cant differences between log2 (E/G) values for proteins at different abundance levels (p < 0.001). Only 1 (1.3%) protein was enriched in the highest copy number (>105) group, whereas 181 (40%) were enriched in the lowest abundance level group (<102). As noted above, this analysis demonstrates that Cys-peptide enrichment is greatest for lower abundance proteins, but does not indicate the degree to which enrichment increases the identiﬁcation of lower abundance proteins. Figure 6 provides a Venn diagrammatic representation of the identiﬁcation overlaps between the E and G fractions for yeast proteins as a function of abundance. The E fraction contained no unique identiﬁcations at the highest abundance level (>105 copies/cell). However, at lower copy numbers, the numbers of unique identiﬁcations in the E fraction expanded dramatically. In the intermediate copy number bins (104-105 copies/cell and 103-104 copies/cell), the E fraction accounted for 1.6 and 9.9% of the identiﬁcations, respectively. At the lowest copy number level (0-103 copies/cell), the E fraction accounted for 86.4% of the identiﬁcations. Spectral count data provide a measure of relative protein abundance40-42 and have been shown to correlate with TAP tag copy number in yeast27 and we observed the same correlation in our data set for the yeast G fraction (Figure S6, Supporting Information). Accordingly, we allocated the identi- ﬁed yeast proteins into bins based on protein spectral counts (Figure 7). As in the analysis based on TAP tag copy numbers, the mean log2 (E/G) for each spectral count bin was inversely proportional to protein abundance. Only 16/594 proteins (2.7%) in the highest spectral count bin were enriched by IBB capture,