title: Large-scale comparative phenotypic and genomic analyses reveal ecological preferences of shewanella species and identify metabolic pathways conserved at the genus level.
abstract: The use of comparative genomics for the study of different microbiological species has increased substantially as sequence technologies become more affordable. However, efforts to fully link a genotype to its phenotype remain limited to the development of one mutant at a time. In this study, we provided a high-throughput alternative to this limiting step by coupling comparative genomics to the use of phenotype arrays for five sequenced Shewanella strains. Positive phenotypes were obtained for 441 nutrients (C, N, P, and S sources), with N-based compounds being the most utilized for all strains. Many genes and pathways predicted by genome analyses were confirmed with the comparative phenotype assay, and three degradation pathways believed to be missing in Shewanella were confirmed as missing. A number of previously unknown gene products were predicted to be parts of pathways or to have a function, expanding the number of gene targets for future genetic analyses. Ecologically, the comparative high-throughput phenotype analysis provided insights into niche specialization among the five different strains. For example, Shewanella amazonensis strain SB2B, isolated from the Amazon River delta, was capable of utilizing 60 C compounds, whereas Shewanella sp. strain W3-18-1, isolated from deep marine sediment, utilized only 25 of them. In spite of the large number of nutrient sources yielding positive results, our study indicated that except for the N sources, they were not sufficiently informative to predict growth phenotypes from increasing evolutionary distances. Our results indicate the importance of phenotypic evaluation for confirming genome predictions. This strategy will accelerate the functional discovery of genes and provide an ecological framework for microbial genome sequencing projects.
authors.affiliation: University of Texas, Arlington, Department of Biology, 501 S. Nedderman Drive, Arlington, TX 76019, USA. Jorge@uta.edu
authors.forename: Jorge L M
authors.initials: JL
authors.lastname: Rodrigues
authors.forename: Margrethe H
authors.initials: MH
authors.lastname: Serres
authors.forename: James M
authors.initials: JM
authors.lastname: Tiedje
mesh_terms: D001483:Base Sequence; D002244:Carbon / Q000378:metabolism; D004269:DNA, Bacterial / Q000145:classification / Q000235:genetics; D004275:DNA, Ribosomal / Q000145:classification / Q000235:genetics; D017753:Ecosystem; D004734:Energy Metabolism / Q000235:genetics / Q000502:physiology*; D023281:Genomics; D005838:Genotype; D053858:Metabolic Networks and Pathways / Q000235:genetics / Q000502:physiology*; D009584:Nitrogen / Q000378:metabolism; D010641:Phenotype; D010758:Phosphorus / Q000378:metabolism; D010802:Phylogeny; D012336:RNA, Ribosomal, 16S / Q000145:classification / Q000235:genetics; D017422:Sequence Analysis, DNA; D020592:Shewanella / Q000235:genetics / Q000378:metabolism*; D013455:Sulfur / Q000378:metabolism
chemical_list: D004269:DNA, Bacterial; D004275:DNA, Ribosomal; D012336:RNA, Ribosomal, 16S; D010758:Phosphorus; D013455:Sulfur; D002244:Carbon; D009584:Nitrogen