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Updated: Jun 20, 2026

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

Using ecological diversity measures with bacterial communities.

Tom C J Hill¹, Kerry A Walsh, James A Harris

¹School of Health and Bioscience, University of East London, Romford Road, Stratford, London E15 4LZ, UK.

FEMS Microbiology Ecology

|September 2, 2009

Summary

This summary is machine-generated.

Assessing bacterial diversity in soils, this study found that the number of analyzed clones and OTU weighting significantly impact diversity measures. Species abundance models proved useful for comparing bacterial communities across different soil conditions.

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Efficient Nucleic Acid Extraction and 16S rRNA Gene Sequencing for Bacterial Community Characterization

Efficient Nucleic Acid Extraction and 16S rRNA Gene Sequencing for Bacterial Community Characterization

Published on: April 14, 2016

Area of Science:

Microbial Ecology
Environmental Microbiology
Bioinformatics

Background:

Ecological diversity measures are widely used but their applicability to highly diverse bacterial communities is often overlooked.
Assessing bacterial diversity is crucial for understanding soil health and environmental impacts.

Purpose of the Study:

To evaluate the suitability of various species richness, evenness, and dominance indices for bacterial communities.
To assess the utility of species abundance models for analyzing bacterial diversity in contaminated and control soils.

Main Methods:

Bacteria were classified into operational taxonomic units (OTUs) using amplified ribosomal DNA restriction analysis.
Diversity indices and species abundance models were applied to bacterial samples from zinc-contaminated and control soils.
Analysis involved 236 clones per soil sample.

Main Results:

Diversity indices reflected reduced bacterial diversity in contaminated soil to varying degrees.
The number of analyzed clones and OTU weighting were critical factors in selecting appropriate diversity measures.
Log series distribution and non-parametric methods like Chao 1 showed promise for extrapolation and richness estimation.
Species abundance models fit the less diverse contaminated soil but not the control soil due to a high number of single-occurrence OTUs.

Conclusions:

Certain diversity indices (e.g., log series alpha, Q statistic, Berger-Parker, Simpson's, Shannon-Wiener) showed utility, with considerations for coverage and accuracy.
Species abundance models are valuable for comparing bacterial community distributions and identifying trends, regardless of sample coverage.
Careful selection of diversity measures, considering sample size and OTU abundance weighting, is essential for accurate bacterial community assessment.