Global Functional Atlas of Escherichia coli Encompassing Previously Uncharacterized Proteins

Hu, Pingzhao; Janga, Sarath Chandra; Babu, Mohan; Díaz-Mejía, J. Javier; Butland, Gareth; Yang, Wenhong; Pogoutse, Oxana; Guo, Xinghua; Phanse, Sadhna; Wong, Patrick; Chandran, Shamanta; Christopoulos, Constantine; Nazarians-Armavil, Anaies; Nasseri, Negin Karimi; Musso, Gabriel; Ali, Mehrab; Nazemof, Nazila; Eroukova, Veronika; Golshani, Ashkan; Paccanaro, Alberto; Greenblatt, Jack; Moreno–Hagelsieb, Gabriel; Emili, Andrew

doi:10.1371/journal.pbio.1000096

Cited by 347 publications

(486 citation statements)

References 95 publications

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“…This reveals a considerable complementarity between the different methods: if methods are applied individually, some gene functions may be predicted highly accurately while the others not at all. A combination of genome sequence-based predictors is able to reach across many different GO functions, consistent with the success of past approaches that integrate across large-scale experimental data sources (Troyanskaya et al, 2003;Lee et al, 2004;Lanckriet et al, 2004;von Mering et al, 2005;Hu et al, 2009;Lee et al, 2010).…”

Section: Extensive Complementarity Between Afp Methodssupporting

confidence: 73%

“…This was made evident in the analyses of gene/protein functional association networks, constructed using various sources of large-scale data. Integrating the individual networks resulted in gene modules that were more functionally consistent (Lee et al, 2004;von Mering et al, 2005) and could thus more accurately predict gene function (Troyanskaya et al, 2003;Hu et al, 2009) or phenotypic effects of gene perturbation (Lee et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Extensive complementarity between gene function prediction methods

2016

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Motivation: The number of sequenced genomes rises steadily, but we still lack the knowledge about the biological roles of many genes. Automatic function prediction (AFP) is thus a necessity. We hypothesize that AFP approaches which draw on distinct genome features may be useful for predicting different types of gene functions, motivating a systematic analysis of the benefits gained by obtaining and integrating such predictions. Results: Our pipeline amalgamates 5,133,543 genes from 2,071 genomes in a single massive analysis that evaluates five established genomic AFP methodologies. While 1,227 Gene Ontology terms yielded reliable predictions, the majority of these functions were accessible to only one or two of the methods. Moreover, different methods tend to assign a GO term to non-overlapping sets of genes. Thus, inferences made by diverse AFP methods display a striking complementary, both gene-wise and function-wise. Because of this, a viable integration strategy is to simply rely on a single mostconfident prediction per gene/function, instead of enforcing agreement across multiple AFP methods. Using an information-theoretic approach, we estimate that current databases contain 29.2 bits/gene of known E. coli gene functions. This can be increased by up to 5.5 bits/gene using individual AFP methods, or by 11 additional bits/gene upon integration, thereby providing a highly-ranking predictor on the CAFA2 community benchmark. Availability of more sequenced genomes boosts the predictive accuracy of AFP approaches and also the benefit from integrating them.

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Section: Extensive Complementarity Between Afp Methodssupporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Extensive complementarity between gene function prediction methods

2016

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“…These functions rely more-or-less directly on Rho cooperating with various endogenous factors. Notably, Rho binds to transcription factors NusA and NusG (Li et al, 1993;Schmidt & Chamberlin, 1984), antitermination factor YaeO (Pichoff et al, 1998) and riboregulation factor Hfq (Rabhi et al, 2011b), and co-purifies with a host of other factors (Butland et al, 2005;Hu et al, 2009) that vary with growth conditions to include, for instance, RNA degradosome components PNPase and RNase E (Tuckerman et al, 2011). At present, the extent to which these various roles and interactions are conserved throughout the bacterial kingdom remains largely uncertain.…”

Section: Introductionmentioning

confidence: 99%

Phyletic distribution and conservation of the bacterial transcription termination factor Rho

2013

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Transcription termination factor Rho is a ring-shaped, ATP-dependent molecular motor that targets hundreds of transcription units in Escherichia coli. Interest in Rho was renewed recently on the realization that this essential factor is involved in multiple interactions and cellular processes that protect the E. coli genome and regulate its expression on a global scale. Yet it is currently unknown if (and how) Rho-dependent mechanisms are conserved throughout the bacterial kingdom. Here, we mined public databases to assess the distribution, expression and structural conservation of Rho across bacterial phyla. We found that rho is present in more than 90 % of sequenced bacterial genomes, although Cyanobacteria, Mollicutes and a fraction of Firmicutes are totally devoid of rho. Genomes lacking rho tend to be small and AT-rich and often belong to species with parasitic/symbiotic lifestyles (such as Mollicutes). By contrast, large GCrich genomes, such as those of Actinobacteria, often contain rho duplicates and/or encode Rho proteins that bear insertion domains of unknown function(s). Notwithstanding, most Rho sequences across taxa contain canonical RNA-binding and ATP hydrolysis signature motifs, a feature suggestive of largely conserved mechanism(s) of action. Mutations that impair binding of bicyclomycin are present in~5 % of rho sequences, implying that species from diverse ecosystems have developed resistance against this natural antibiotic. Altogether, these findings assert that Rho function is widespread among bacteria and suggest that it plays a particularly relevant role in the expression of complex genomes and/or bacterial adaptation to changing environments.

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“…Furthermore, a few other studies (22)(23)(24)(25) systematically identified protein complexes and their compositions in bacteria.…”

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confidence: 99%

A Second-generation Protein–Protein Interaction Network of Helicobacter pylori

Häuser

Céol

Rajagopala

et al. 2014

Molecular & Cellular Proteomics

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Helicobacter pylori infections cause gastric ulcers and play a major role in the development of gastric cancer. In 2001, the first protein interactome was published for this species, revealing over 1500 binary protein interactions resulting from 261 yeast two-hybrid screens. Here we roughly double the number of previously published interactions using an ORFeome-based, proteome-wide yeast two-hybrid screening strategy. We identified a total of 1515 protein-protein interactions, of which 1461 are new. The integration of all the interactions reported in H. pylori results in 3004 unique interactions that connect about 70% of its proteome. Excluding interactions of promiscuous proteins we derived from our new data a core network consisting of 908 interactions. We compared our data set to several other bacterial interactomes and experimentally benchmarked the conservation of interactions using 365 protein pairs (interologs) of E. coli of which one third turned out to be conserved in both species. Molecular &

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Global Functional Atlas of Escherichia coli Encompassing Previously Uncharacterized Proteins

Cited by 347 publications

References 95 publications

Extensive complementarity between gene function prediction methods

Extensive complementarity between gene function prediction methods

Phyletic distribution and conservation of the bacterial transcription termination factor Rho

A Second-generation Protein–Protein Interaction Network of Helicobacter pylori

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