Title: A Simple, Cost-Effective, and Automation-Friendly Direct PCR Approach for Bacterial Community Analysis

Abstract

Bacterial communities in water, soil, and humans play an essential role in environmental ecology and human health. PCR-based amplicon analysis, such as 16S rRNA sequencing, is a fundamental tool for quantifying and studying microbial composition, dynamics, and interactions. However, given the complexity of microbial communities, a substantial number of samples becomes necessary for analyses that parse the factors that determine microbial composition. A common bottleneck in performing these kinds of experiments is genomic DNA (gDNA) extraction, which is time-consuming, expensive, and often biased based on the types of species present. Direct PCR method is a potentially simpler and more accurate alternative to gDNA extraction methods that do not require the intervening purification step. In this study, we evaluated three variations of direct PCR methods using diverse heterogeneous bacterial cultures, including both Gram-positive and Gram-negative species, ZymoBIOMICS microbial community standards, and groundwater. By comparing direct PCR methods with DNeasy Blood and Tissue Kits for microbial isolates and DNeasy PowerSoil Kits for microbial communities, we found that a specific variant of the direct PCR method exhibits an overall efficiency comparable to that of the conventional DNeasy PowerSoil protocol in the circumstances we tested. We also found that the method showed higher efficiencymore » for extracting gDNA from the Gram-negative strains compared to DNeasy Blood and Tissue protocol. This direct PCR method is 1,600 times less expensive ($0.34 for 96 samples) and 10 times simpler (15 min hands-on time for 96 samples) than the DNeasy PowerSoil protocol. The direct PCR method can also be fully automated and is compatible with small-volume samples, thereby permitting scaling of samples and replicates needed to support high-throughput large-scale bacterial community analysis.« less

Authors:

Song, Fangchao ^[1]; Kuehl, Jennifer V. ^[1]; Chandran, Arjun ^[2]; Arkin, Adam P. ^[3]; Glaven, ed., Sarah

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+ Show Author Affiliations

1. Environmental Genomics &, Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
2. Department of Bioengineering, University of California at Berkeley, Berkeley, California, USA
3. Environmental Genomics &, Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA, Department of Bioengineering, University of California at Berkeley, Berkeley, California, USA

Publication Date:

2021-10-26

Research Org.:

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Sponsoring Org.:

USDOE

OSTI Identifier:

1822977

Alternate Identifier(s):

OSTI ID: 1855188

Grant/Contract Number:  

AC02-05CH1123; AC02-05CH11231

Resource Type:

Published Article

Journal Name:

mSystems

Additional Journal Information:

Journal Name: mSystems Journal Volume: 6 Journal Issue: 5; Journal ID: ISSN 2379-5077

Publisher:

American Society for Microbiology

Country of Publication:

United States

Language:

English

Subject:

59 BASIC BIOLOGICAL SCIENCES; 16S rRNA sequencing; microbial communities