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Applied and Environmental Microbiology, September 2009, p. 5863-5870, Vol. 75, No. 18
0099-2240/09/$08.00+0 doi:10.1128/AEM.00748-09
Copyright © 2009, American Society for Microbiology. All Rights Reserved.
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Laboratoire d'Ecologie Alpine, CNRS UMR 5553, Université de Grenoble, BP 53, F-38041 Grenoble Cedex 09, France,1 Station Alpine J. Fourier CNRS UMS 2925, Université de Grenoble, F-38041 Grenoble, France,2 CSIRO Marine and Atmospheric Research, Canberra, Australia3
Received 2 April 2009/ Accepted 10 July 2009
Understanding how microbial community structure and diversity respond to environmental conditions is one of the main challenges in environmental microbiology. However, there is often confusion between determining the phylogenetic structure of microbial communities and assessing the distribution and diversity of molecular operational taxonomic units (MOTUs) in these communities. This has led to the use of sequence analysis tools such as multiple alignments and hierarchical clustering that are not adapted to the analysis of large and diverse data sets and not always justified for characterization of MOTUs. Here, we developed an approach combining a pairwise alignment algorithm and graph partitioning by using MCL (Markov clustering) in order to generate discrete groups for nuclear large-subunit rRNA gene and internal transcript spacer 1 sequence data sets obtained from a yearly monitoring study of two spatially close but ecologically contrasting alpine soils (namely, early and late snowmelt locations). We compared MCL with a classical single-linkage method (Ccomps) and showed that MCL reduced bias such as the chaining effect. Using MCL, we characterized fungal communities in early and late snowmelt locations. We found contrasting distributions of MOTUs in the two soils, suggesting that there is a high level of habitat filtering in the assembly of alpine soil fungal communities. However, few MOTUs were specific to one location.
Published ahead of print on 17 July 2009.
Supplemental material for this article may be found at http://aem.asm.org/.
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