Toward Forensic Uses of Microbial Source Tracking

Microbial source tracking using molecular and cultivable methods in a tropical mixed-use drinking water source to support water safety plans

Microbial contamination deteriorates source water quality, posing a severe problem for drinking water suppliers worldwide and addressed by the Water Safety Plan framework to ensure high-quality and reliable drinking water. Microbial source tracking (MST) is used to examine different microbial pollution sources via host-specific intestinal markers for humans and different types of animals. However, the application of MST in tropical surface water catchments that provide raw water for drinking water supplies is limited. We analyzed a set of MST markers, namely, three cultivable bacteriophages and four molecular PCR and qPCR assays, together with 17 microbial and physicochemical parameters, to identify fecal pollution from general, human-, swine-, and cattle-specific sources. Seventy-two river water samples at six sampling sites were collected over 12 sampling events during wet and dry seasons. We found persistent fecal contamination via the general fecal marker GenBac3 (100 % detection; 2.10-5.42 log₁₀ copies/100 mL), with humans (crAssphage; 74 % detection; 1.62-3.81 log₁₀ copies/100 mL) and swine (Pig-2-Bac; 25 % detection; 1.92-2.91 log₁₀ copies/100 mL). Higher contamination levels were observed during the wet season (p < 0.05). The conventional PCR screening used for the general and human markers showed 94.4 % and 69.8 % agreement with the respective qPCR results. Specifically, in the studied watershed, coliphage could be a screening parameter for the crAssphage marker (90.6 % and 73.7 % positive and negative predictive values; Spearman's rank correlation coefficient = 0.66; p < 0.001). The likelihood of detecting the crAssphage marker significantly increased when total and fecal coliforms exceeded 20,000 and 4000 MPN/100 mL, respectively, as Thailand Surface Water Quality Standards, with odds ratios and 95 % confidence intervals of 15.75 (4.43-55.98) and 5.65 (1.39-23.05). Our study confirms the potential benefits of incorporating MST monitoring into water safety plans, supporting the use of this approach to ensure high-quality drinking water supplies worldwide.

Strategies for Monitoring Microbial Life in Beach Sand for Protection of Public Health

The 2021 revised guidelines of the World Health Organization recommend monitoring the quality of sand in addition to water at recreational beaches. This review provides background information about the types of beaches, the characteristics of sand, and the microbiological parameters that should be measured. Analytical approaches are described for quantifying fungi and fecal indicator bacteria from beach sand. The review addresses strategies to assess beach sand quality, monitoring approaches, sand remediation, and the proposed way forward for beach sand monitoring programs. In the proposed way forward, recommendations are provided for acceptable levels of fungi given their distribution in the environment. Additional recommendations include evaluating FIB distributions at beaches globally to assess acceptable ranges of FIB levels, similar to those proposed for fungi.

Ecological dynamics imposes fundamental challenges in community-based microbial source tracking

Quantifying the contributions of possible environmental sources ("sources") to a specific microbial community ("sink") is a classical problem in microbiology known as microbial source tracking (MST). Solving the MST problem will not only help us understand how microbial communities were formed, but also have far-reaching applications in pollution control, public health, and forensics. MST methods generally fall into two categories: target-based methods (focusing on the detection of source-specific indicator species or chemicals); and community-based methods (using community structure to measure similarity between sink samples and potential source environments). As next-generation sequencing becomes a standard community-assessment method in microbiology, numerous community-based computational methods, referred to as MST solvers hereafter have been developed and applied to various real datasets to demonstrate their utility across different contexts. Yet, those MST solvers do not consider microbial interactions and priority effects in microbial communities. Here, we revisit the performance of several representative MST solvers. We show compelling evidence that solving the MST problem using existing MST solvers is impractical when ecological dynamics plays a role in community assembly. In particular, we clearly demonstrate that the presence of either microbial interactions or priority effects will render the MST problem mathematically unsolvable for MST solvers. We further analyze data from fecal microbiota transplantation studies, finding that the state-of-the-art MST solvers fail to identify donors for most of the recipients. Finally, we perform community coalescence experiments to demonstrate that the state-of-the-art MST solvers fail to identify the sources for most of the sinks. Our findings suggest that ecological dynamics imposes fundamental challenges in MST. Interpretation of results of existing MST solvers should be done cautiously.

STENSL: Microbial Source Tracking with ENvironment SeLection

Microbial source tracking analysis has emerged as a widespread technique for characterizing the properties of complex microbial communities. However, this analysis is currently limited to source environments sampled in a specific study. In order to expand the scope beyond one single study and allow the exploration of source environments using large databases and repositories, such as the Earth Microbiome Project, a source selection procedure is required. Such a procedure will allow differentiating between contributing environments and nuisance ones when the number of potential sources considered is high. Here, we introduce STENSL (microbial Source Tracking with ENvironment SeLection), a machine learning method that extends common microbial source tracking analysis by performing an unsupervised source selection and enabling sparse identification of latent source environments. By incorporating sparsity into the estimation of potential source environments, STENSL improves the accuracy of true source contribution, while significantly reducing the noise introduced by noncontributing ones. We therefore anticipate that source selection will augment microbial source tracking analyses, enabling exploration of multiple source environments from publicly available repositories while maintaining high accuracy of the statistical inference. IMPORTANCE Microbial source tracking is a powerful tool to characterize the properties of complex microbial communities. However, this analysis is currently limited to source environments sampled in a specific study. In many applications there is a clear need to consider source selection over a large array of microbial environments, external to the study. To this end, we developed STENSL (microbial Source Tracking with ENvironment SeLection), an expectation-maximization algorithm with sparsity that enables the identification of contributing sources among a large set of potential microbial environments. With the unprecedented expansion of microbiome data repositories such as the Earth Microbiome Project, recording over 200,000 samples from more than 50 types of categorized environments, STENSL takes the first steps in performing automated source exploration and selection. STENSL is significantly more accurate in identifying the contributing sources as well as the unknown source, even when considering hundreds of potential source environments, settings in which state-of-the-art microbial source tracking methods add considerable error.

Integrated analyses of fecal indicator bacteria, microbial source tracking markers, and pathogens for Southeast Asian beach water quality assessment

The degradation of coastal water quality from fecal pollution poses a health risk to visitors at recreational beaches. Fecal indicator bacteria (FIB) are a proxy for fecal pollution; however the accuracy of their representation of fecal pollution health risks at recreational beaches impacted by non-point sources is disputed due to non-human derivation. This study aimed to investigate the relationship between FIB and a range of culturable and molecular-based microbial source tracking (MST) markers and pathogenic bacteria, and physicochemical parameters and rainfall. Forty-two marine water samples were collected from seven sampling stations during six events at two tourist beaches in Thailand. Both beaches were contaminated with fecal pollution as evident from the GenBac3 marker at 88%-100% detection and up to 8.71 log₁₀ copies/100 mL. The human-specific MST marker human polyomaviruses JC and BK (HPyVs) at up to 4.33 log₁₀ copies/100 mL with 92%-94% positive detection indicated that human sewage was likely the main contamination source. CrAssphage showed lower frequencies and concentrations; its correlations with the FIB group (i.e., total coliforms, fecal coliforms, and enterococci) and GenBac3 diminished its use as a human-specific MST marker for coastal water. Human-specific culturable AIM06 and SR14 bacteriophages and general fecal indicator coliphages also showed less sensitivity than the human-specific molecular assays. The applicability of the GenBac3 endpoint PCR assay as a lower-cost prescreening step prior to the GenBac3 qPCR assay was supported by its 100% positive predictive value, but its limited negative predictive values required subsequent qPCR confirmation. Human enteric adenovirus and Vibrio cholerae were not found in any of the samples. The HPyVs related to Vibrio parahaemolyticus, Vibrio vulnificus, and 5-d rainfall records, all of which were more prevalent and concentrated during the wet season. More monitoring is therefore recommended during wet periods. Temporal differences but no spatial differences were observed, suggesting the need for a sentinel site at each beach for routine monitoring. The exceedance of FIB water quality standards did not indicate increased prevalence or concentrations of the HPyVs or Vibrio spp. pathogen group, so the utility of FIB as an indicator of health risks at tropical beaches maybe challenged. Accurate assessment of fecal pollution by incorporating MST markers could lead to developing a more effective water quality monitoring plan to better protect human health risks in tropical recreational beaches.

Untreated sewage contamination of beach sand from a leaking underground sewage system

Thirty people (mostly children) experienced an episode of skin rash days after a sand sifting beach operation at Porto Pim Beach in Faial, Azores during June 2019. An environmental and epidemiologic investigation was conducted to identify the cause of the outbreak of skin rash. The epidemiologic investigation found that some of the patients experiencing symptoms had never entered the beach water. During the pollution period and throughout the epidemiologic investigation, faecal indicator bacteria levels (94 CFU/100 ml for intestinal enterococci and 61 CFU/100 ml for Escherichia coli) in water remained under the limits used for the ninety-five percentile calculation of an Excellent coastal and transitional bathing water defined in the Portuguese Legislation (100 CFU/100 ml for intestinal enterococci and 250 CFU/100 ml for Escherichia coli). Thus sand contact was considered as a likely primary exposure route. Sand microbiological analysis for faecal indicator organisms and electron microscopy strongly suggested faecal contamination. Chemical analysis of the sand also revealed a concomitant substance compatible with sodium-hypochlorite as analysed using gas chromatography and subsequently confirmed by free chlorine analysis. Inspection of the toilet facilities and sewage disposal system revealed a leaking sewage distribution box. Collectively, results suggest that the cause of the outbreak was the leaking underground sewage distribution box that serviced the beach toilet facilities (40 m from beach), where sodium-hypochlorite was used for cleaning and disinfection. This sewage then contaminated the surficial sands to which beach goers were exposed. Chlorine being an irritant substance, was believed to have been the cause of the symptoms given the sudden presentation and dissipation of skin rashes. No gastro-intestinal illness was reported during this episode and during the following 30 days. Like water, beach sand should also be monitored for safety, especially for areas serviced by aged infrastructure.

Microbial Indicators of Fecal Pollution: Recent Progress and Challenges in Assessing Water Quality

PURPOSE OF REVIEW

Fecal contamination of water is a major public health concern. This review summarizes recent developments and advancements in water quality indicators of fecal contamination.

RECENT FINDINGS

This review highlights a number of trends. First, fecal indicators continue to be a valuable tool to assess water quality and have expanded to include indicators able to detect sources of fecal contamination in water. Second, molecular methods, particularly PCR-based methods, have advanced considerably in their selected targets and rigor, but have added complexity that may prohibit adoption for routine monitoring activities at this time. Third, risk modeling is beginning to better connect indicators and human health risks, with the accuracy of assessments currently tied to the timing and conditions where risk is measured. Research has advanced although challenges remain for the effective use of both traditional and alternative fecal indicators for risk characterization, source attribution and apportionment, and impact evaluation.

Effect of Quantitative Polymerase Chain Reaction Data Analysis Using Sample Amplification Efficiency on Microbial Source Tracking Assay Performance and Source Attribution

The widely used microbial source tracking (MST) technique, quantitative polymerase chain reaction (qPCR), quantifies host-specific gene abundance in polluted water to identify and prioritize contamination sources. This study characterized the effects of a qPCR data analysis using the sample PCR efficiencies (the LinRegPCR model) on gene abundance and compared them with the standard curve-based method (the mixed model). Five qPCR assays were evaluated: the universal GenBac3, human-specific HF183/BFDrev and CPQ_056, swine-specific Pig-2-Bac, and cattle-specific Bac3qPCR assays. The LinRegPCR model increased the low-copy amplification, especially in the HF183/BFDrev assay, thus lowering the specificity to 0.34. Up to 1.41 log₁₀ copies/g and 0.41 log₁₀ copies/100 mL differences were observed for composite fecal and sewage samples (n = 147) by the LinRegPCR approach, corresponding to an 18.2% increase and 6.4% decrease, respectively. Freshwater samples (n = 48) demonstrated a maximum of 1.95 log₁₀ copies/100 mL difference between the two models. Identical attributing sources by both models were shown in 54.55% of environmental samples; meanwhile, the LinRegPCR approach improved the inability to identify sources by the mixed model in 29.55% of the samples. This study emphasizes the need for a standardized data analysis protocol for qPCR MST assays for interlaboratory consistency and comparability.

Detection of a microbial source tracking marker by isothermal helicase-dependent amplification and a nucleic acid lateral-flow strip test

Over the last decades, various PCR-based methods have been proposed that can identify sources of faecal pollution in environmental waters. These microbial source tracking (MST) methods are powerful tools to manage water quality and support public health risk assessment. However, their application is limited by the lack of specialized equipment and trained personnel in laboratories performing microbiological water quality assessment. Here, we describe a novel molecular method that combines helicase-dependent amplification (HDA) with a strip test for detecting ruminant faecal pollution sources. Unlike quantitative PCR (qPCR), the developed HDA-strip assay only requires a heating block to amplify the ruminant-associated Bacteroidetes 16S rRNA marker (BacR). Following HDA, the reaction mixture can be directly applied onto the test strip, which detects and displays the amplification products by marker-specific hybridization probes via an on-strip colorimetric reaction. The entire assay takes two hours and demands no extensive practical training. Furthermore, the BacR HDA-strip assay achieved comparable results in head-to-head performance tests with the qPCR reference, in which we investigated source-sensitivity and source-specificity, the analytical limit of detection, and the sample limit of detection. Although this approach only yields qualitative results, it can pave a way for future simple-to-use MST screening tools.