Literature DB >> 29746923

Use of amplicon sequencing to improve sensitivity in PCR-based detection of microbial pathogen in environmental samples.

Prakit Saingam1, Bo Li1, Tao Yan2.   

Abstract

DNA-based molecular detection of microbial pathogens in complex environments is still plagued by sensitivity, specificity and robustness issues. We propose to address these issues by viewing them as inadvertent consequences of requiring specific and adequate amplification (SAA) of target DNA molecules by current PCR methods. Using the invA gene of Salmonella as the model system, we investigated if next generation sequencing (NGS) can be used to directly detect target sequences in false-negative PCR reaction (PCR-NGS) in order to remove the SAA requirement from PCR. False-negative PCR and qPCR reactions were first created using serial dilutions of laboratory-prepared Salmonella genomic DNA and then analyzed directly by NGS. Target invA sequences were detected in all false-negative PCR and qPCR reactions, which lowered the method detection limits near the theoretical minimum of single gene copy detection. The capability of the PCR-NGS approach in correcting false negativity was further tested and confirmed under more environmentally relevant conditions using Salmonella-spiked stream water and sediment samples. Finally, the PCR-NGS approach was applied to ten urban stream water samples and detected invA sequences in eight samples that would be otherwise deemed Salmonella negative. Analysis of the non-target sequences in the false-negative reactions helped to identify primer dime-like short sequences as the main cause of the false negativity. Together, the results demonstrated that the PCR-NGS approach can significantly improve method sensitivity, correct false-negative detections, and enable sequence-based analysis for failure diagnostics in complex environmental samples.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Detection; False negative; Microbial pathogen; Next generation sequencing (NGS); PCR; Salmonella

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Year:  2018        PMID: 29746923     DOI: 10.1016/j.mimet.2018.05.005

Source DB:  PubMed          Journal:  J Microbiol Methods        ISSN: 0167-7012            Impact factor:   2.363


  1 in total

1.  A Quantitative Metagenomic Sequencing Approach for High-Throughput Gene Quantification and Demonstration with Antibiotic Resistance Genes.

Authors:  Bo Li; Xu Li; Tao Yan
Journal:  Appl Environ Microbiol       Date:  2021-07-27       Impact factor: 4.792

  1 in total

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