Challenges in microbial ecology: building predictive understanding of community function and dynamics
Year: 2016
Type: review
Abstract: The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model-experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.
Source: The ISME Journal
Authors: Stefanie Widder, Rosalind J Allen, Thomas Pfeiffer, Thomas P Curtis, Carsten Wiuf, William T Sloan, Otto X Cordero, Sam P Brown, Babak Momeni, Wenying Shou, Helen Kettle, Harry J Flint, Andreas F Haas, Béatrice Laroche, Jan-Ulrich Kreft, Paul B Rainey, Shiri Freilich, Stefan Schuster, Kim Milferstedt, Jan R van der Meer, Tobias Groβkopf, Jef Huisman, Andrew Free, Cristian Picioreanu, Christopher Quince, Isaac Klapper, Simon Labarthe, Barth F Smets, Harris Wang, Orkun S Soyer
Institutions: University of Vienna, University of Edinburgh, Massey University, Newcastle University, University of Copenhagen, University of Glasgow, Massachusetts Institute of Technology, Centre for Immunity, Infection and Evolution, Boston College, Fred Hutch Cancer Center, Biomathematics and Statistics Scotland, University of Aberdeen, San Diego State University, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, University of Birmingham, Agricultural Research Organization, Friedrich Schiller University Jena, Laboratoire de Biotechnologie de l'Environnement, University of Lausanne, University of Warwick, University of Amsterdam, Delft University of Technology, Temple University, Technical University of Denmark, Columbia University
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,153
Funders: Isaac Newton Institute for Mathematical Sciences, National Centre for the Replacement, Refinement and Reduction of Animals in Research, Lundbeckfonden, Directorate for Biological Sciences, Medical Research Council, Engineering and Physical Sciences Research Council, Biotechnology and Biological Sciences Research Council, Division of Mathematical Sciences, Army Research Office
Awards: Engineering Synthetic Microbial Communities for Biomethane Production, G2524744901, G3424441068, G3493265225, Isaac Newton Institute for Mathematical Sciences, G4495588905, G5128091834, Predicting the acclimatisation of microbial wastewater treatment communities as a function of the environment, random immigration, birth and death, G5713690049, G677550382, G7452299184, G7469976914, Synthetic Biology applications to Water Supply and Remediation, G8173229303
OpenAlex ID: W2295190630