Predicting ecological roles in the rhizosphere using metabolome and transportome modeling
The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. New algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad’s ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter of plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism’s transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbialmore »
- Argonne National Lab., Argonne, IL (United States). Biosciences Div.; Univ. of Chicago, Chicago, IL (United States). Dept. of Bioengineering.
- Argonne National Lab., Argonne, IL (United States). Biosciences Div.
- Univ. of Chicago, Chicago, IL (United States). Dept. of Bioengineering
- Univ. of Massachusetts, Worcester, MA (United States)
- Publication Date:
- OSTI Identifier:
- Grant/Contract Number:
- Accepted Manuscript
- Journal Name:
- PLoS ONE
- Additional Journal Information:
- Journal Volume: 10; Journal Issue: 9; Journal ID: ISSN 1932-6203
- Public Library of Science
- Research Org:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Org:
- USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
- Country of Publication:
- United States
- 59 BASIC BIOLOGICAL SCIENCES; 54 ENVIRONMENTAL SCIENCES ecological niches; enzyme metabolism; plant genomics; metabolomics; enzymes; rhizosphere; secondary metabolism; genome analysis
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