Metagenomic Approach for Identification of the Pathogens Associated with Diarrhea in Stool Specimens

Abstract

The potential to rapidly capture the entire microbial community structure and/or gene content makes metagenomic sequencing an attractive tool for pathogen identification and the detection of resistance/virulence genes in clinical settings. Here, we assessed the consistency between PCR from a diagnostic laboratory, quantitative PCR (qPCR) from a research laboratory, 16S rRNA gene sequencing, and metagenomic shotgun sequencing (MSS) for Clostridium difficile identification in diarrhea stool samples. Twenty-two C. difficile-positive diarrhea samples identified by PCR and qPCR and five C. difficile-negative diarrhea controls were studied. C. difficile was detected in 90.9% of C. difficile-positive samples using 16S rRNA gene sequencing, and C. difficile was detected in 86.3% of C. difficile-positive samples using MSS. CFU inferred from qPCR analysis were positively correlated with the relative abundance of C. difficile from 16S rRNA gene sequencing (r(2) = -0.60) and MSS (r(2) = -0.55). C. difficile was codetected with Clostridium perfringens, norovirus, sapovirus, parechovirus, and anellovirus in 3.7% to 27.3% of the samples. A high load of Candida spp. was found in a symptomatic control sample in which no causative agents for diarrhea were identified in routine clinical testing. Beta-lactamase and tetracycline resistance genes were the most prevalent (25.9%) antibiotic resistance genes in these samples. In summary, the proof-of-concept study demonstrated that next-generation sequencing (NGS) in pathogen detection is moderately correlated with laboratory testing and is advantageous in detecting pathogens without a priori knowledge.