Influence of Library Composition on SourceTracker Predictions for Community-Based Microbial Source Tracking

Abstract

Community-based microbial source tracking (MST) utilizes high-throughput DNA sequencing to profile and compare the microbial communities in different fecal sources and environmental samples. SourceTracker, a program that compares a library of OTUs from fecal sources (i.e., sources) to those in environmental samples (i.e., sinks) in order to determine sources of fecal contamination, is an emerging tool for community-based MST studies. In this study, we investigated the ability of SourceTracker to determine sources of known fecal contamination in spiked, in situ mesocosms containing different source contributors. We also evaluated how SourceTracker results were impacted by accounting for autochthonous taxa present in the sink environment. While SourceTracker was able to predict most sources present in the in situ mesocosms, fecal source library composition substantially influenced the program’s ability to predict source contributions. Moreover, prediction results were most reliable when the library contained only known sources, autochthonous taxa were accounted for and when source profiles had low intragroup variability. Although SourceTracker struggled to differentiate between sources with similar bacterial community structures, it was able to consistently identify abundant and expected sources, suggesting that the SourceTracker program can be a useful tool for community-based MST studies.

Microbial Source Tracking in the Love Creek Watershed, Delaware (USA)

“…Common MST methods use specific bacterial primers from hosts to measure quantities via quantitative real-time PCR (qPCR) (Brown et al, 2017; Harwood et al, 2014). However, the development of primers for fecal sources of interest may be time consuming and previous research has shown potential issues with specificity and sensitivity of qPCR (Brown et al, 2019; Green et al, 2014; Stewart et al, 2013). The usage of NGS methods to define the microbial community of aquatic and fecal samples using amplicon sequence variant (ASV), which can resolve the difference of sequences to a single nucleotide, increases the power of determining potential fecal contamination sources (Callahan et al, 2017; Unno et al, 2018).…”

“…human, farm animal, bird, to determine sources of fecal contamination in the environment. The most common MST method uses quantitative real-time polymerase chain reaction (qPCR) and primers that target the 16S rRNA genes of host associated bacteria (Brown et al, 2017; Harwood et al, 2014), however, qPCR may suffer from specificity and sensitivity issues (Brown et al, 2019; Green et al, 2014; Stewart et al, 2013). In the last decade, advancements in high-throughput DNA sequencing has led to large-scale microbial community studies.…”

“…SourceTracker is a Bayesian classification program, which provides an estimated percentage of the sequenced microbial community from an environmental samples can be attributed to a specific fecal source (Brown et al, 2019; Knights et al, 2011). SourceTracker uses a Gibbs sampling algorithm to examine the likely prior distribution of OTUs/ASVs within user-defined sources.…”

“…The SourceTracker algorithm has been shown to be more accurate than random forest analysis, or naive Bayesian classification (Knights et al, 2011). SourceTracker has been used to determine contamination sources in the Russian River (Dubinsky et al, 2016), ATM keypads (Bik et al, 2016), recreational beaches in Australia (Ahmed et al, 2015; Brown et al, 2017; Henry et al, 2016; McCarthy et al, 2017), lakes in St. Paul, Minnesota (Brown et al, 2019), and the upper Mississippi River (Staley et al, 2015, 2014).…”

Microbial community dissimilarity for source tracking with application in forensic studies

“…To investigate how RAD may perform in real-world experiments, RAD was applied to an experiment by Brown et al [ 17 ], which simulated wastewater by spiking lake water samples with bacteria from sewage effluent or fecal samples. We considered the scenario where the sources of interest are lake water, sewage effluent, cow fecal matter, and horse fecal matter.…”