Original Article
Subject Category: Microbial population and community ecology
The ISME Journal (2008) 2, 707–715; doi:10.1038/ismej.2008.36; published online 3 April 2008
Characterizing mixed microbial population dynamics using time-series analysis
Pål Trosvik1,2, Knut Rudi2,3, Tormod Næs2,4, Achim Kohler2, Kung-Sik Chan5, Kjetill S Jakobsen1 and Nils C Stenseth1
- 1Department of Biology, Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway
- 2Matforsk AS, Norwegian Food Research Institute, Norway
- 3Department of Natural Sciences, Hedmark University College, Hamar, Norway
- 4Department of Mathematics, University of Oslo, Oslo, Norway
- 5Department of Statistics and Actuarial Sciences, University of Iowa, Iowa City, IA, USA
Correspondence: NC Stenseth, Department of Biology, Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo N-0316, Norway. E-mail: n.c.stenseth@bio.uio.no
Received 22 November 2007; Revised 13 March 2008; Accepted 14 March 2008; Published online 3 April 2008.
Abstract
Due to a general shortage of temporal population data, dynamic structures in microbial communities remain largely unexplored. Knowledge of community dynamics is, however, essential for understanding the mechanisms by which microbes interact. Here, we have used a computational approach for quantification of bacteria in multispecies populations, generating data for time-series modeling. Moreover, we have used online FR-IR spectroscopy to monitor the main metabolic processes. The approach enabled us to provide a functional description of the parameters governing the population dynamics in a three-species model bacterial community, demonstrating density-dependent regulation, interspecies competition and even a case of cooperation between two species. Since the field of microbial ecology has yet to embrace many of the concepts and methods developed for the study of ecology of higher plants and animals, the realization that microbial systems can be analyzed within the same conceptual framework as other ecosystems is of fundamental importance.
Keywords:
bacterial community, GAM, model system, population dynamics, time series, FT-IR
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