Systems biology approaches towards predictive microbial ecology
Abstract
Summary Through complex interspecies interactions, microbial processes drive nutrient cycling and biogeochemistry. However, we still struggle to predict specifically which organisms, communities and biotic and abiotic processes are determining ecosystem function and how environmental changes will alter their roles and stability. While the tools to create such a predictive microbial ecology capability exist, cross‐disciplinary integration of high‐resolution field measurements, detailed laboratory studies and computation is essential. In this perspective, we emphasize the importance of pursuing a multiscale, systems approach to iteratively link ecological processes measured in the field to testable hypotheses that drive high‐throughput laboratory experimentation. Mechanistic understanding of microbial processes gained in controlled lab systems will lead to the development of theory that can be tested back in the field. Using N 2 O production as an example, we review the current status of field and laboratory research and layout a plausible path to the kind of integration that is needed to enable prediction of how N‐cycling microbial communities will respond to environmental changes. We advocate for the development of realistic and predictive gene regulatory network models for environmental responses that extend from single‐cell resolution to ecosystems, which is essential to understand how microbial communities involved in N 2more »
- Authors:
-
- Institute for Systems Biology, Seattle, WA (United States)
- Institute for Systems Biology, Seattle, WA (United States);Univ. of Washington, Seattle, WA (United States)
- Institute for Systems Biology, Seattle, WA (United States);Univ. of Washington, Seattle, WA (United States) ; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1777943
- Alternate Identifier(s):
- OSTI ID: 1478266
- Grant/Contract Number:
- AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Environmental Microbiology
- Additional Journal Information:
- Journal Volume: 20; Journal Issue: 12; Journal ID: ISSN 1462-2912
- Publisher:
- Wiley
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES
Citation Formats
Otwell, Anne E., López García de Lomana, Adrián, Gibbons, Sean M., Orellana, Mónica V., and Baliga, Nitin S. Systems biology approaches towards predictive microbial ecology. United States: N. p., 2018.
Web. doi:10.1111/1462-2920.14378.
Otwell, Anne E., López García de Lomana, Adrián, Gibbons, Sean M., Orellana, Mónica V., & Baliga, Nitin S. Systems biology approaches towards predictive microbial ecology. United States. https://doi.org/10.1111/1462-2920.14378
Otwell, Anne E., López García de Lomana, Adrián, Gibbons, Sean M., Orellana, Mónica V., and Baliga, Nitin S. Fri .
"Systems biology approaches towards predictive microbial ecology". United States. https://doi.org/10.1111/1462-2920.14378. https://www.osti.gov/servlets/purl/1777943.
@article{osti_1777943,
title = {Systems biology approaches towards predictive microbial ecology},
author = {Otwell, Anne E. and López García de Lomana, Adrián and Gibbons, Sean M. and Orellana, Mónica V. and Baliga, Nitin S.},
abstractNote = {Summary Through complex interspecies interactions, microbial processes drive nutrient cycling and biogeochemistry. However, we still struggle to predict specifically which organisms, communities and biotic and abiotic processes are determining ecosystem function and how environmental changes will alter their roles and stability. While the tools to create such a predictive microbial ecology capability exist, cross‐disciplinary integration of high‐resolution field measurements, detailed laboratory studies and computation is essential. In this perspective, we emphasize the importance of pursuing a multiscale, systems approach to iteratively link ecological processes measured in the field to testable hypotheses that drive high‐throughput laboratory experimentation. Mechanistic understanding of microbial processes gained in controlled lab systems will lead to the development of theory that can be tested back in the field. Using N 2 O production as an example, we review the current status of field and laboratory research and layout a plausible path to the kind of integration that is needed to enable prediction of how N‐cycling microbial communities will respond to environmental changes. We advocate for the development of realistic and predictive gene regulatory network models for environmental responses that extend from single‐cell resolution to ecosystems, which is essential to understand how microbial communities involved in N 2 O production and consumption will respond to future environmental conditions.},
doi = {10.1111/1462-2920.14378},
journal = {Environmental Microbiology},
number = 12,
volume = 20,
place = {United States},
year = {Fri Oct 19 00:00:00 EDT 2018},
month = {Fri Oct 19 00:00:00 EDT 2018}
}
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