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Evidence from GC-TRFLP that bacterial communities in soil are lognormally distributed.

Doroghazi JR, Buckley DH - PLoS ONE (2008)

Bottom Line: As a result, few microbial systems have been sampled with sufficient depth to generate reliable estimates of the community SAD.We also show that TRFLP analysis, in contrast to GC-TRFLP, is not able to effectively distinguish between competing SAD models.Our analysis supports use of the lognormal as the distribution for studying the SAD of bacterial communities as for plant and animal communities.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology, Cornell University, Ithaca, New York, United States of America.

ABSTRACT
The Species Abundance Distribution (SAD) is a fundamental property of ecological communities and the form and formation of SADs have been examined for a wide range of communities including those of microorganisms. Progress in understanding microbial SADs, however, has been limited by the remarkable diversity and vast size of microbial communities. As a result, few microbial systems have been sampled with sufficient depth to generate reliable estimates of the community SAD. We have used a novel approach to characterize the SAD of bacterial communities by coupling genomic DNA fractionation with analysis of terminal restriction fragment length polymorphisms (GC-TRFLP). Examination of a soil microbial community through GC-TRFLP revealed 731 bacterial operational taxonomic units (OTUs) that followed a lognormal distribution. To recover the same 731 OTUs through analysis of DNA sequence data is estimated to require analysis of 86,264 16S rRNA sequences. The approach is examined and validated through construction and analysis of simulated microbial communities in silico. Additional simulations performed to assess the potential effects of PCR bias show that biased amplification can cause a community whose distribution follows a power-law function to appear lognormally distributed. We also show that TRFLP analysis, in contrast to GC-TRFLP, is not able to effectively distinguish between competing SAD models. Our analysis supports use of the lognormal as the distribution for studying the SAD of bacterial communities as for plant and animal communities.

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TRFLP data for soil and the distributions that provided the best fit to this data.Goodness-of-fit measurements are given in Table 3.
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pone-0002910-g006: TRFLP data for soil and the distributions that provided the best fit to this data.Goodness-of-fit measurements are given in Table 3.

Mentions: The lognormal distribution was found to provide the best fitting estimate to the GC-TRFLP data from soil (Table 2, Figure 5). The K-S test could not reject the hypothesis that the lognormal estimate and the GC-TRFLP data were from the same distribution (p-value 0.657). In contrast, the K-S test rejected all other distributions tested (Table 2). As expected, data derived from TRFLP analysis had less ability to exclude potential distributions than GC-TRFLP (Figure 6). From the TRFLP data we could reject the geometric distribution and narrowly rejected Fisher's distribution, but could not distinguish between the power and lognormal distributions (Table 3).


Evidence from GC-TRFLP that bacterial communities in soil are lognormally distributed.

Doroghazi JR, Buckley DH - PLoS ONE (2008)

TRFLP data for soil and the distributions that provided the best fit to this data.Goodness-of-fit measurements are given in Table 3.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2483420&req=5

pone-0002910-g006: TRFLP data for soil and the distributions that provided the best fit to this data.Goodness-of-fit measurements are given in Table 3.
Mentions: The lognormal distribution was found to provide the best fitting estimate to the GC-TRFLP data from soil (Table 2, Figure 5). The K-S test could not reject the hypothesis that the lognormal estimate and the GC-TRFLP data were from the same distribution (p-value 0.657). In contrast, the K-S test rejected all other distributions tested (Table 2). As expected, data derived from TRFLP analysis had less ability to exclude potential distributions than GC-TRFLP (Figure 6). From the TRFLP data we could reject the geometric distribution and narrowly rejected Fisher's distribution, but could not distinguish between the power and lognormal distributions (Table 3).

Bottom Line: As a result, few microbial systems have been sampled with sufficient depth to generate reliable estimates of the community SAD.We also show that TRFLP analysis, in contrast to GC-TRFLP, is not able to effectively distinguish between competing SAD models.Our analysis supports use of the lognormal as the distribution for studying the SAD of bacterial communities as for plant and animal communities.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology, Cornell University, Ithaca, New York, United States of America.

ABSTRACT
The Species Abundance Distribution (SAD) is a fundamental property of ecological communities and the form and formation of SADs have been examined for a wide range of communities including those of microorganisms. Progress in understanding microbial SADs, however, has been limited by the remarkable diversity and vast size of microbial communities. As a result, few microbial systems have been sampled with sufficient depth to generate reliable estimates of the community SAD. We have used a novel approach to characterize the SAD of bacterial communities by coupling genomic DNA fractionation with analysis of terminal restriction fragment length polymorphisms (GC-TRFLP). Examination of a soil microbial community through GC-TRFLP revealed 731 bacterial operational taxonomic units (OTUs) that followed a lognormal distribution. To recover the same 731 OTUs through analysis of DNA sequence data is estimated to require analysis of 86,264 16S rRNA sequences. The approach is examined and validated through construction and analysis of simulated microbial communities in silico. Additional simulations performed to assess the potential effects of PCR bias show that biased amplification can cause a community whose distribution follows a power-law function to appear lognormally distributed. We also show that TRFLP analysis, in contrast to GC-TRFLP, is not able to effectively distinguish between competing SAD models. Our analysis supports use of the lognormal as the distribution for studying the SAD of bacterial communities as for plant and animal communities.

Show MeSH