Phyletic Profiling with Cliques of Orthologs Is Enhanced by Signatures of Paralogy Relationships

Abstract

New microbial genomes are sequenced at a high pace, allowing insight into the genetics of not only cultured microbes, but a wide range of metagenomic collections such as the human microbiome. To understand the deluge of genomic data we face, computational approaches for gene functional annotation are invaluable. We introduce a novel model for computational annotation that refines two established concepts: annotation based on homology and annotation based on phyletic profiling. The phyletic profiling-based model that includes both inferred orthologs and paralogs—homologs separated by a speciation and a duplication event, respectively—provides more annotations at the same average Precision than the model that includes only inferred orthologs. For experimental validation, we selected 38 poorly annotated Escherichia coli genes for which the model assigned one of three GO terms with high confidence: involvement in DNA repair, protein translation, or cell wall synthesis. Results of antibiotic stress survival assays on E. coli knockout mutants showed high agreement with our model's estimates of accuracy: out of 38 predictions obtained at the reported Precision of 60%, we confirmed 25 predictions, indicating that our confidence estimates can be used to make informed decisions on experimental validation. Our work will contribute to making experimental validation of computational predictions more approachable, both in cost and time. Our predictions for 998 prokaryotic genomes include ∼400000 specific annotations with the estimated Precision of 90%, ∼19000 of which are highly specific—e.g. “penicillin binding,” “tRNA aminoacylation for protein translation,” or “pathogenesis”—and are freely available at http://gorbi.irb.hr/.

Combining Shigella Tn-seq data with Gold-standard E. coli Gene Deletion Data Suggests Rare Transitions between Essential and Non-essential Gene Functionality

“…Thus, clones with transposon insertions in these genes are unlikely to survive during library growth under kanamycin selection. A similar explanation likely underlies the fact that we inferred ybaB, ksgA, yebC, and smpB as essential: these four play role in aminoglycoside resistance [30][31][32].…”

Molecular mechanism of mRNA repression in trans by a ProQ‐dependent small RNA

“…Intriguingly, a few ProQ‐associated sRNAs have known or hypothetical roles in DNA pathways: IstR is induced in response to DNA damage (Vogel et al , ); art200 regulates IS200 transposition (Ellis et al , ); IsrB, IsrF, IsrJ, IsrK, and STnc1080 are prophage‐encoded sRNAs with likely roles in lysogeny maintenance (Barquist et al , ; Hershko‐Shalev et al , ; Padalon‐Brauch et al , ); STnc40 is a hypothetical mutT attenuator (Naville & Gautheret, ; Pfeiffer et al , ); and STnc540 and STnc620 overlap the 3′ UTRs of the himA and ssb mRNAs encoding the α‐subunit of the integration host factor and the single‐stranded DNA‐binding protein, respectively (Chao et al , ; Sittka et al , ). Of note, an E. coli proQ mutant has been predicted to be particularly sensitive to DNA‐damaging agents in global screens (Nichols et al , ; Skunca et al , ). In Legionella , the ProQ homologue RocC plays a critical role in controlling competence (Attaiech et al , ; Sexton & Vogel, ).…”

Phylogenetic Profiling: How Much Input Data Is Enough?

“…Various studies looked at aspects of phylogenetic profiling such as the genomes included [ 4 , 5 ], vocabulary used in functional annotation [ 6 ], methods used to find or group homologs [ 7 – 9 ], and methods used to find similar phylogenetic profiles [ 10 ] (see [ 11 ] for a review). For example, looking at the genomes included, one study suggests that reference genomes should be selected from moderately and highly genetically distant organisms, from all three domains of life [ 2 ].…”