QT-AMP: Quanti-Tray-based amplicon sequencing for simultaneous quantification and identification of enterococci for microbial source tracking

Abstract

ABSTRACTEnterococcus is ubiquitous in human feces and has been adopted as a useful indicator of human fecal pollution in water. Although regular enterococci monitoring only examines their numbers, identification of human-specific Enterococcus species or genotypes could help in the discrimination of human fecal contamination from other environmental sources. We documented a new approach to characterize enterococci using an amplicon sequencing platform from Quanti Trays after following the counting of most probable numbers (MPN) of enterococci. We named this method as QT-AMP (Quanti-Tray-based amplicon sequencing). We tested surface water samples collected from three rivers in southwest Florida. We detected 11 Enterococcus species from 45 samples in 1.1 million sequence reads. The method detected three rare species and eight cosmopolitan species (Enterococcus faecalis, E.faecium, E. casseliflavus, E. hirae, E. mundtii, E. gallinarum, E. avium, and E. durans) which have been commonly documented in various enterococci isolation studies. It is likely that the approximate detection level of QT-AMP is four orders of magnitude higher than regular 16S rRNA gene amplicon sequencing. QT-AMP revealed that a majority of Enterolert positive signals are actually the mixture of both enterococci and other facultative aerobes and anaerobes. QT-AMP may have the potential to monitor not only enterococci but also other pathogenic bacteria commonly found in natural environments. This QT-AMP could be a powerful tool to streamline the quantification and identification of enterococci and allows us to do more accurate and efficient microbial source tracking in various water management projects and human health risk assessment.HighlightsA selected primer set (27f-519r) can differentiate over 50 Enterococcus species and is suitable for Illumina amplicon sequencing.The median of the relative contribution of enterococci reads among total sequencing reads was 82.7% and ranged between 0% and 100%.Enterolert signals are most likely the mixture of enterococci and other facultative aerobes and anaerobes.We identified eight cosmopolitan enterococci species and three rare species.The median of the relative contribution of non-enterococci reads among total sequencing reads was 17.3%, respectively, and ranged between 0% and 100%.