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MBio. 2016 May 13;7(3). pii: e00714-16. doi: 10.1128/mBio.00714-16.

Toward a Predictive Understanding of Earth's Microbiomes to Address 21st Century Challenges.

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Departments of Microbiology and Medicine, New York University School of Medicine, New York, New York, USA.
The Ecosystems Center, Marine Biological Laboratory, Woods Hole, Massachusetts, USA.
Stanford Center for Biomedical Ethics, Stanford University, Palo Alto, California, USA.
Department of Biology and Howard Hughes Medical Institute, University of North Carolina, Chapel Hill, North Carolina, USA.
Department of Bacteriology, Great Lakes Bioenergy Research Center and Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Biology and the Built Environment Center, University of Oregon, Eugene, Oregon, USA Department of Biology, Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, USA.
Departments of Pediatrics and Computer Science & Engineering, and Center for Microbiome Innovation, University of California San Diego, La Jolla, California, USA.
Biosciences, Lawrence Berkeley National Laboratory, Berkeley, California, USA.
Division of Biostatistics, Gladstone Institutes and Institute for Human Genetics, Institute for Computational Health Science, University of California, San Francisco, California, USA.
Earth and Environmental Sciences, Lawrence Berkeley National Lab, Berkeley, California, USA Department of Environmental Science, Policy and Management, University of California, Berkeley, California, USA


Microorganisms have shaped our planet and its inhabitants for over 3.5 billion years. Humankind has had a profound influence on the biosphere, manifested as global climate and land use changes, and extensive urbanization in response to a growing population. The challenges we face to supply food, energy, and clean water while maintaining and improving the health of our population and ecosystems are significant. Given the extensive influence of microorganisms across our biosphere, we propose that a coordinated, cross-disciplinary effort is required to understand, predict, and harness microbiome function. From the parallelization of gene function testing to precision manipulation of genes, communities, and model ecosystems and development of novel analytical and simulation approaches, we outline strategies to move microbiome research into an era of causality. These efforts will improve prediction of ecosystem response and enable the development of new, responsible, microbiome-based solutions to significant challenges of our time.

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