Systems biology approaches towards predictive microbial ecology

被引:17
|
作者
Otwell, Anne E. [1 ]
de Lomana, Adrian Lopez Garcia [1 ]
Gibbons, Sean M. [1 ,2 ,3 ]
Orellana, Monica V. [1 ,4 ]
Baliga, Nitin S. [1 ,3 ,5 ,6 ]
机构
[1] Inst Syst Biol, Seattle, WA 98109 USA
[2] Univ Washington, EScience Inst, Seattle, WA 98195 USA
[3] Univ Washington, Mol & Cellular Biol Program, Seattle, WA 98195 USA
[4] Univ Washington, Appl Phys Lab, Polar Sci Ctr, Seattle, WA 98105 USA
[5] Univ Washington, Dept Biol & Microbiol, Seattle, WA 98195 USA
[6] Lawrence Berkeley Natl Lab, Berkeley, CA 94720 USA
基金
美国国家科学基金会;
关键词
NITROUS-OXIDE EMISSIONS; GLOBAL GENE-REGULATION; FJORD SAANICH INLET; N2O EMISSIONS; NITROSOMONAS-EUROPAEA; BIOGEOCHEMICAL MODEL; RESPONSE PATTERNS; TIME-SERIES; SOIL-PH; DENITRIFICATION;
D O I
10.1111/1462-2920.14378
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
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 N2O 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 N2O production and consumption will respond to future environmental conditions.
引用
收藏
页码:4197 / 4209
页数:13
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