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ISME J. 2013 Jun;7(6):1187-99. doi: 10.1038/ismej.2012.176. Epub 2013 Jan 10.

Microdiversity of extracellular enzyme genes among sequenced prokaryotic genomes.

Author information

1
Department of Ecology and Evolutionary Biology, University of California Irvine, CA 92697, USA. amy.zimmerman@uci.edu

Abstract

Understanding the relationship between prokaryotic traits and phylogeny is important for predicting and modeling ecological processes. Microbial extracellular enzymes have a pivotal role in nutrient cycling and the decomposition of organic matter, yet little is known about the phylogenetic distribution of genes encoding these enzymes. In this study, we analyzed 3058 annotated prokaryotic genomes to determine which taxa have the genetic potential to produce alkaline phosphatase, chitinase and β-N-acetyl-glucosaminidase enzymes. We then evaluated the relationship between the genetic potential for enzyme production and 16S rRNA phylogeny using the consenTRAIT algorithm, which calculated the phylogenetic depth and corresponding 16S rRNA sequence identity of clades of potential enzyme producers. Nearly half (49.2%) of the genomes analyzed were found to be capable of extracellular enzyme production, and these were non-randomly distributed across most prokaryotic phyla. On average, clades of potential enzyme-producing organisms had a maximum phylogenetic depth of 0.008004-0.009780, though individual clades varied broadly in both size and depth. These values correspond to a minimum 16S rRNA sequence identity of 98.04-98.40%. The distribution pattern we found is an indication of microdiversity, the occurrence of ecologically or physiologically distinct populations within phylogenetically related groups. Additionally, we found positive correlations among the genes encoding different extracellular enzymes. Our results suggest that the capacity to produce extracellular enzymes varies at relatively fine-scale phylogenetic resolution. This variation is consistent with other traits that require a small number of genes and provides insight into the relationship between taxonomy and traits that may be useful for predicting ecological function.

PMID:
23303371
PMCID:
PMC3660669
DOI:
10.1038/ismej.2012.176
[Indexed for MEDLINE]
Free PMC Article

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