BactQuant: an enhanced broad-coverage bacterial quantitative real-time PCR assay

BactQuant:一种增强型广覆盖细菌定量实时 PCR 检测方法

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作者:Cindy M Liu, Maliha Aziz, Sergey Kachur, Po-Ren Hsueh, Yu-Tsung Huang, Paul Keim, Lance B Price

Background

Bacterial load quantification is a critical component of bacterial community analysis, but a culture-independent method capable of detecting and quantifying diverse bacteria is needed. Based on our analysis of a diverse collection of 16 S rRNA gene sequences, we designed a broad-coverage quantitative real-time PCR (qPCR) assay--BactQuant--for quantifying 16 S rRNA gene copy number and estimating bacterial load. We further utilized in silico evaluation to complement laboratory-based qPCR characterization to validate BactQuant.

Conclusions

The BactQuant assay offers significantly broader coverage than a previously reported universal bacterial quantification assay BactQuant in vitro performance was better than the in silico predictions.

Methods

The aligned core set of 4,938 16 S rRNA gene sequences in the Greengenes database were analyzed for assay design. Cloned plasmid standards were generated and quantified using a qPCR-based approach. Coverage analysis was performed computationally using >670,000 sequences and further evaluated following the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines.

Results

A bacterial TaqMan® qPCR assay targeting a 466 bp region in V3-V4 was designed. Coverage analysis showed that 91% of the phyla, 96% of the genera, and >80% of the 89,537 species analyzed contained at least one perfect sequence match to the BactQuant assay. Of the 106 bacterial species evaluated, amplification efficiencies ranged from 81 to 120%, with r2-value of >0.99, including species with sequence mismatches. Inter- and intra-run coefficient of variance was <3% and <16% for Ct and copy number, respectively. Conclusions: The BactQuant assay offers significantly broader coverage than a previously reported universal bacterial quantification assay BactQuant in vitro performance was better than the in silico predictions.

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