The recent abundance of genome sequence data has brought an urgent need for systematic proteomics to decipher the encoded protein networks that dictate cellular function. To date, generation of large-scale protein-protein interaction maps has relied on the yeast two-hybrid system, which detects binary interactions through activation of reporter gene expression. With the advent of ultrasensitive mass spectrometric protein identification methods, it is feasible to identify directly protein complexes on a proteome-wide scale. Here we report, using the budding yeast Saccharomyces cerevisiae as a test case, an example of this approach, which we term high-throughput mass spectrometric protein complex identification (HMS-PCI). Beginning with 10% of predicted yeast proteins as baits, we detected 3,617 associated proteins covering 25% of the yeast proteome. Numerous protein complexes were identified, including many new interactions in various signalling pathways and in the DNA damage response. Comparison of the HMS-PCI data set with interactions reported in the literature revealed an average threefold higher success rate in detection of known complexes compared with large-scale two-hybrid studies. Given the high degree of connectivity observed in this study, even partial HMS-PCI coverage of complex proteomes, including that of humans, should allow comprehensive identification of cellular networks.

Mapping protein-protein interactions is an invaluable tool for understanding protein function. Here, we report the first large-scale study of protein-protein interactions in human cells using a mass spectrometry-based approach. The study maps protein interactions for 338 bait proteins that were selected based on known or suspected disease and functional associations. Large-scale immunoprecipitation of Flag-tagged versions of these proteins followed by LC-ESI-MS/MS analysis resulted in the identification of 24 540 potential protein interactions. False positives and redundant hits were filtered out using empirical criteria and a calculated interaction confidence score, producing a data set of 6463 interactions between 2235 distinct proteins. This data set was further cross-validated using previously published and predicted human protein interactions. In-depth mining of the data set shows that it represents a valuable source of novel protein-protein interactions with relevance to human diseases. In addition, via our preliminary analysis, we report many novel protein interactions and pathway associations.

Intestinal microbial dysbiosis is associated with Crohn's disease (CD). However, the mechanisms leading to the chronic mucosal inflammation that characterizes this disease remain unclear. In this report, we use systems-level approaches to study the interactions between the gut microbiota and host in new-onset paediatric patients to evaluate causality and mechanisms of disease. We report an altered host proteome in CD patients indicative of impaired mitochondrial functions. In particular, mitochondrial proteins implicated in H2S detoxification are downregulated, while the relative abundance of H2S microbial producers is increased. Network correlation analysis reveals that Atopobium parvulum controls the central hub of H2S producers. A. parvulum induces pancolitis in colitis-susceptible interleukin-10-deficient mice and this phenotype requires the presence of the intestinal microbiota. Administrating the H2S scavenger bismuth mitigates A. parvulum-induced colitis in vivo. This study reveals that host–microbiota interactions are disturbed in CD and thus provides mechanistic insights into CD pathogenesis.

An evaluation of the proteolytic labeling and quantification of proteins for diagnostic purposes using trypsin and 18O-enriched H2O is presented. We demonstrate that comparative or relative quantitation can be performed effectively with this approach. We have developed a protocol that allows the conservation of the labeled peptides in natural abundance water without fear of back-exchange providing that pH is sufficiently low to quench the catalytic activity of trypsin, but not so low as to promote chemical back-exchange. Because the labeling efficiency depends on the nature of the peptide, a simple linear relationship between the relative 16O/18O digest buffer mixture content (x) and labeling efficiency (y) does not exist; rather it follows a probability based y = x(2) relationship. As such, the extent of peptide labeling using 16O/18O digest buffer mixture ratios may deviate significantly from that expected based on a linear relationship. The evaluation of the relative Ziptip efficiency indicated a loss in sample recovery as the peptide concentration was reduced using normal conditions, suggesting that there is a limit below which there are diminishing returns. In addition, the adsorptive losses due to Speedvac dry down and recovery indicated modest (20%) losses that may vary widely (0-50%) from peptide to peptide. The in-solution digestion efficiency of standard protein mixtures as a function of concentration revealed a linear decrease with decreasing concentration. This is consistent with enzyme kinetic effects and emphasizes a potential quantitation error that could arise when evaluating differential expression based on peptide detection. The results from our studies demonstrate the power of 18O labeling as an optimization tool for proteomics process development.

Alterations in gut microbiota have been implicated in the pathogenesis of inflammatory bowel disease (IBD), however factors that mediate the host–microbiota interactions remain largely unknown. Here we collected mucosal-luminal interface samples from a pediatric IBD inception cohort and characterized both the human and microbiota proteins using metaproteomics. We show that microbial proteins related to oxidative stress responses are upregulated in IBD cases compared to controls. In particular, we demonstrate that the expression of human proteins related to oxidative antimicrobial activities is increased in IBD cases and correlates with the alteration of microbial functions. Additionally, we reveal that many of these human proteins are present and show altered abundance in isolated free extracellular vesicles (EVs). Therefore, our study suggests that the alteration of intestinal EV proteomes is associated with the aberrant host–microbiota interactions in IBD.