Large-scale comparative phenotypic and genomic analyses reveal ecological preferences of Shewanella species and identify metabolic pathways conserved at the genus level
Large-scale comparative phenotypic and genomic analyses reveal ecological preferences of Shewanella species and identify metabolic pathways conserved at the genus level
Date
2011-04-27
Authors
Rodrigues, Jorge L. M.
Serres, Margrethe H.
Tiedje, James M.
Serres, Margrethe H.
Tiedje, James M.
Linked Authors
Alternative Title
Citable URI
As Published
Date Created
Location
DOI
Related Materials
Replaces
Replaced By
Keywords
Abstract
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.
Description
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.