BactQuant: An enhanced broad-coverage bacterial quantitative real-time PCR assay
1 Division of Pathogen Genomics, Translational Genomics Research Institute, 3051 W. Shamrell Blvd., Suite 106, Flagstaff, AZ 86001, USA
2 Center for Microbial Genetics and Genomics, Applied Research & Development Building,, Northern Arizona University, 1298 S. Knoles Drive, Flagstaff, AZ, 86011, USA
3 Departments of Laboratory Medicine and Internal Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei, Taiwan
4 Department of Internal Medicine, Far Eastern Memorial Hospital, No.21, Nanya S. Rd., New Taipei City, Taiwan
5 Current Address: Ross University School of Medicine, 630 US Highway 1, North Brunswick, NJ, 08902, USA
Citation and License
BMC Microbiology 2012, 12:56 doi:10.1186/1471-2180-12-56Published: 17 April 2012
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.
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.
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.
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.