Variably improved microbial source tracking with digital droplet PCR

Jean Pierre Nshimyimana; Mercedes C Cruz; Stefan Wuertz; Janelle R Thompson

doi:10.1016/j.watres.2019.04.056

Variably improved microbial source tracking with digital droplet PCR

Water Res. 2019 Aug 1:159:192-202. doi: 10.1016/j.watres.2019.04.056. Epub 2019 May 6.

Authors

Jean Pierre Nshimyimana¹, Mercedes C Cruz², Stefan Wuertz³, Janelle R Thompson⁴

Affiliations

¹ School of Civil and Environmental Engineering, Nanyang Technological University (NTU), 50 Nanyang Avenue, Singapore, 639798, Singapore; Singapore Centre for Environmental Life Sciences Engineering, NTU, 60 Nanyang Dr., Singapore, 637551, Singapore; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology (MIT), 77 Massachusetts Avenue, Cambridge, MA, 02139, USA.
² Singapore Centre for Environmental Life Sciences Engineering, NTU, 60 Nanyang Dr., Singapore, 637551, Singapore.
³ School of Civil and Environmental Engineering, Nanyang Technological University (NTU), 50 Nanyang Avenue, Singapore, 639798, Singapore; Singapore Centre for Environmental Life Sciences Engineering, NTU, 60 Nanyang Dr., Singapore, 637551, Singapore.
⁴ Department of Civil and Environmental Engineering, Massachusetts Institute of Technology (MIT), 77 Massachusetts Avenue, Cambridge, MA, 02139, USA; Centre for Environmental Sensing and Modeling, Singapore-MIT Alliance for Research and Technology, 1 Create Way, Singapore, 138602, Singapore. Electronic address: jthompson@mit.edu.

PMID: 31096066
DOI: 10.1016/j.watres.2019.04.056

Abstract

This study addressed whether digital droplet PCR (ddPCR) could improve sensitivity and specificity of human-associated Bacteroidales genetic markers, BacHum and B. theta, and their quantification in environmental and fecal composite samples. Human markers were quantified by qPCR and ddPCR platforms obtained from the same manufacturer. A total of 180 samples were evaluated by each platform including human and animal feces, sewage, and environmental water. The sensitivity of ddPCR and qPCR marker assays in sewage and human stool was 0.85-1.00 with marginal reduction in human stool by ddPCR relative to qPCR (<10%). The prevalence and distribution of markers across complex sample types was similar (74-100% agreement) by both platforms with qPCR showing higher sensitivity for markers in environmental and composite samples and ddPCR showing greater reproducibility for marker detection in fecal composites. Determination of BacHum prevalence in fecal samples by ddPCR increased specificity relative to qPCR (from 0.58 to 0.88) and accuracy (from 0.77 to 0.94), while the B. theta assay performed similarly on both platforms (specificity = 0.98). In silico analysis indicated higher specificity of ddPCR for BacHum was not solely attributed to reduced sensitivity relative to qPCR. Marker concentrations measured by ddPCR for all sample types were consistently lower than those measured by qPCR, by a factor of 2.6 ± 2.8 for B. theta and 18.7 ± 10.0 for BacHum. We suggest that differences in assay performance on ddPCR and qPCR platforms may be linked to the characteristics of the assay targets (that is, genes with multiple versus single copies and encoding proteins versus ribosomal RNA) however further work is needed to validate these ideas. We conclude that ddPCR is a suitable tool for microbial source tracking, however, other factors such as cost-effectiveness and assay-specific performance should be considered.

Keywords: Digital droplet PCR; Genetic markers; Microbial source tracking; Quantitative PCR.

MeSH terms

Animals
Bacteroidetes*
Feces
Humans
Real-Time Polymerase Chain Reaction
Reproducibility of Results
Sensitivity and Specificity