Visualization of ribosomal RNA operon copy number distribution

Rastogi, Rajat; Wu, Martin; Dasgupta, Indrani; Fox, George E.

doi:10.1186/1471-2180-9-208

Cited by 55 publications

(38 citation statements)

References 14 publications

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“…The expected variability was calculated from the consensus models (c). (28,42). Currently, it is common practice to describe the composition of a microbial community using 16S gene composition rather than cell composition.…”

Section: Downloaded Frommentioning

confidence: 99%

Diversity of 16S rRNA Genes within Individual Prokaryotic Genomes

Pei

Oberdorf²,

Nossa³

et al. 2010

Appl Environ Microbiol

241

181

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Analysis of intragenomic variation of 16S rRNA genes is a unique approach to examining the concept of ribosomal constraints on rRNA genes; the degree of variation is an important parameter to consider for estimation of the diversity of a complex microbiome in the recently initiated Human Microbiome Project (http://nihroadmap.nih.gov/hmp). The current GenBank database has a collection of 883 prokaryotic genomes representing 568 unique species, of which 425 species contained 2 to 15 copies of 16S rRNA genes per genome (2.22 ؎ 0.81). Sequence diversity among the 16S rRNA genes in a genome was found in 235 species (from 0.06% to 20.38%; 0.55% ؎ 1.46%). Compared with the 16S rRNA-based threshold for operational definition of species (1 to 1.3% diversity), the diversity was borderline (between 1% and 1.3%) in 10 species and >1.3% in 14 species. The diversified 16S rRNA genes in Haloarcula marismortui (diversity, 5.63%) and Thermoanaerobacter tengcongensis (6.70%) were highly conserved at the 2°structure level, while the diversified gene in B. afzelii (20.38%) appears to be a pseudogene. The diversified genes in the remaining 21 species were also conserved, except for a truncated 16S rRNA gene in "Candidatus Protochlamydia amoebophila." Thus, this survey of intragenomic diversity of 16S rRNA genes provides strong evidence supporting the theory of ribosomal constraint. Taxonomic classification using the 16S rRNA-based operational threshold could misclassify a number of species into more than one species, leading to an overestimation of the diversity of a complex microbiome. This phenomenon is especially seen in 7 bacterial species associated with the human microbiome or diseases.

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Section: Downloaded Frommentioning

confidence: 99%

Diversity of 16S rRNA Genes within Individual Prokaryotic Genomes

Pei

Oberdorf²,

Nossa³

et al. 2010

Appl Environ Microbiol

241

181

View full text Add to dashboard Cite

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“…By contrast, more complex traits such as oxygenic photosynthesis or sulfate reduction involve many more genes and show phylogenetic conservation at much deeper taxonomic levels (80% and 92.2% mean 16S rRNA sequence identity, respectively; Martiny et al, 2012). Other traits not directly related to resource use, such as rRNA operon copy number (Rastogi et al, 2009) and host adaptation (Ettema and Andersson, 2009), may also be conserved at deeper taxonomic levels.…”

Section: Discussionmentioning

confidence: 99%

Microdiversity of extracellular enzyme genes among sequenced prokaryotic genomes

2013

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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 b-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 enzymeproducing 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.

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“…3). With the assumption that soil bacteria possess on average 5 rrn rDNA operons (Rastogi et al, 2009), we found that bacteria abundance estimated by 16S rRNA gene abundance (1.17 Â 10 9 AE 1.38 Â 10 8 genome-equivalent g À1 dry soil for grasslands and 6.7 Â 10 8 AE 1.24 Â 10 8 genomeequivalent g À1 dry soil for crop fields) was approximately as much as double that estimation by FCM counts (6.69 Â 10 8 AE 2.52 Â 10 8 cells g À1 dry soil for grasslands and 4.73 Â 10 8 AE 9.38 Â 10 7 cells g À1 dry soil for crop fields) (Table 3).…”

Section: Other Bacterial Descriptorsmentioning

confidence: 99%