Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology

被引:17
作者
Lui, Lauren M. [1 ]
Majumder, Erica L-W [2 ]
Smith, Heidi J. [3 ]
Carlson, Hans K. [1 ]
von Netzer, Frederick [4 ]
Fields, Matthew W. [3 ]
Stahl, David A. [4 ]
Zhou, Jizhong [5 ]
Hazen, Terry C. [6 ]
Baliga, Nitin S. [7 ]
Adams, Paul D. [1 ,8 ]
Arkin, Adam P. [1 ,8 ]
机构
[1] Lawrence Berkeley Natl Lab, Div Environm Genom & Syst Biol, Berkeley, CA 94720 USA
[2] Univ Wisconsin, Dept Bacteriol, Madison, WI 53706 USA
[3] Montana State Univ, Ctr Biofilm Engn, Dept Microbiol & Immunol, Bozeman, MT 59717 USA
[4] Univ Washington, Dept Civil & Environm Engn, Seattle, WA 98195 USA
[5] Univ Oklahoma, Sch Civil Engn & Environm Sci, Inst Environm Genom, Dept Microbiol & Plant Biol, Norman, OK 73019 USA
[6] Univ Tennessee, Dept Civil & Environm Engn, Knoxville, TN USA
[7] Inst Syst Biol, Seattle, WA USA
[8] Univ Calif Berkeley, Dept Bioengn, Berkeley, CA 94720 USA
关键词
reactive transport modeling; metabolic model; species interaction network; systems biology; subsurface microbial ecology;
D O I
10.3389/fmicb.2021.642422
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.
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页数:15
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