Large-scale comparative phenotypic and genomic analyses reveal ecological preferences of Shewanella species and identify metabolic pathways conserved at the genus level

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of American Society for Microbiology for personal use, not for redistribution. The definitive version was published in Applied and Environmental Microbiology 77 (2011): 5352-5360, doi:10.1128/AEM.00097-11.The use of comparative genomics among 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 the time. In this study, we provide a high throughput alternative to this limiting step by coupling comparative genomics to 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. A number of previously unknown gene products were predicted to be part 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 within 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, from the 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.The work conducted by the U.S. Department of Energy Joint Genome Institute is supported by the Office of Science of the U.S. Department of Energy under Contract numbers DE-AC02-05CH11231 and DE-FG02-08ER64511