Background

Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function.

Results

We experimentally annotated the bacterial pathogen Salmonella Typhimurium 14028, using "shotgun" proteomics to accurately uncover the translational landscape and post-translational features. The data provide protein-level experimental validation for approximately half of the predicted protein-coding genes in Salmonella and suggest revisions to several genes that appear to have incorrectly assigned translational start sites, including a potential novel alternate start codon. Additionally, we uncovered 12 non-annotated genes missed by gene prediction programs, as well as evidence suggesting a role for one of these novel ORFs in Salmonella pathogenesis. We also characterized post-translational features in the Salmonella genome, including chemical modifications and proteolytic cleavages. We find that bacteria have a much larger and more complex repertoire of chemical modifications than previously thought including several novel modifications. Our in vivo proteolysis data identified more than 130 signal peptide and N-terminal methionine cleavage events critical for protein function.

Conclusion

This work highlights several ways in which application of proteomics data can improve the quality of genome annotations to facilitate novel biological insights and provides a comprehensive proteome map of Salmonella as a resource for systems analysis.

Importance

Colonies of the cyanobacteria Trichodesmium act as a biological hotspot for the usage and recycling of key resources such as C, N, P, and Fe within an otherwise oligotrophic environment. While Trichodesmium colonies are known to interact and support a unique community of algae and particle-associated microbes, our understanding of the taxa that populate these colonies and the gene functions they encode is still limited. Characterizing the taxa and adaptive strategies that influence consortium physiology and its concomitant biogeochemistry is critical in a future ocean predicted to have increasingly resource-depleted regions.

Fungi play a critical role in the global carbon cycle by degrading plant polysaccharides to small sugars and metabolizing them as carbon and energy sources. We mapped the well-established sugar metabolic network of Aspergillus niger to five taxonomically distant species (Aspergillus nidulans, Penicillium subrubescens, Trichoderma reesei, Phanerochaete chrysosporium and Dichomitus squalens) using an orthology-based approach. The diversity of sugar metabolism correlates well with the taxonomic distance of the fungi. The pathways are highly conserved between the three studied Eurotiomycetes (A. niger, A. nidulans, P. subrubescens). A higher level of diversity was observed between the T. reesei and A. niger, and even more so for the two Basidiomycetes. These results were confirmed by integrative analysis of transcriptome, proteome and metabolome, as well as growth profiles of the fungi growing on the corresponding sugars. In conclusion, the establishment of sugar pathway models in different fungi revealed the diversity of fungal sugar conversion and provided a valuable resource for the community, which would facilitate rational metabolic engineering of these fungi as microbial cell factories.