Validation of microbial source tracking markers for the attribution of fecal contamination in indoor-household environments of the Peruvian Amazon

Distribution of host-specific Bacteriodales marker genes in water sources of selected rural areas of Vhembe District, South Africa

Access to safe drinking water sources and appropriate sanitation facilities remains a dream in low and middle-income countries including South Africa. This study identified the origin of faecal pollution by using quantitative polymerase chain reaction (qPCR) targeting host-specific Bacteroidales genetic markers to track the distribution of human-specific (BacHum) and animal-specific (cattle-BacCow, chicken-Cytb, pig-Pig-2-Bac, dog-BacCan) markers in water sources used by rural communities of the Vhembe District Municipality (VDM). Results revealed the prevalence of BacHum, BacCow, and BacCan in all surface water sources in Thulamela Local Municipality (TLM) and Collins Chabane Local Municipality (CLM) during wet (100%) and dry seasons (50-75%). Cytb was not detected in untreated spring water in TLM and CLM, and Pig-2-Bac was not detected in untreated hand-dug well water in TLM during both seasons. Household-level analysis detected Cytb (28.8% wet, 17.5% dry), BacHum (34.4% wet, 25% dry for Pig-2-Bac) in stored untreated spring water in CLM, and Cytb (42.9% wet, 28.5% dry) in untreated hand-dug well water in TLM. Despite differences in detection frequencies of host-specific Bacteroidales, the study highlights the public health concern of faecal pollution in rural VDM households.

Validation and application of high-throughput quantitative PCR for the simultaneous detection of microbial source tracking markers in environmental water

No single microbial source tracking (MST) marker can be applied to determine the sources of fecal pollution in all water types. This study aimed to validate a high-throughput quantitative polymerase chain reaction (HT-qPCR) method for the simultaneous detection of multiple MST markers. A total of 26 fecal-source samples that had been previously collected from human sewage (n = 6) and ruminant (n = 3), dog (n = 6), pig (n = 6), chicken (n = 3), and duck (n = 2) feces in the Kathmandu Valley, Nepal, were used to validate 10 host-specific MST markers, i.e., Bacteroidales (BacHum, gyrB, BacR, and Pig2Bac), mitochondrial DNA (mtDNA) (swine, bovine, and Dog-mtDNA), and viral (human adenovirus, porcine adenovirus, and chicken/turkey parvovirus) markers, via HT-qPCR. Only Dog-mtDNA showed 100 % accuracy. All the tested bacterial markers showed a sensitivity of 100 %. Nine of the 10 markers were further used to identify fecal contamination in groundwater sources (n = 54), tanker filling stations (n = 14), drinking water treatment plants (n = 5), and river water samples (n = 6). The human-specific Bacteroidales marker BacHum and ruminant-specific Bacteroidales marker BacR was detected at a high ratio in river water samples (83 % and 100 %, respectively). The results of HT-qPCR were in agreement with the standard qPCR. The comparable performances of HT-qPCR and standard qPCR as well as the successful detection of MST markers in the fecal-source and water samples demonstrated the potential applicability of these markers for detecting fecal contamination sources via HT-qPCR.

Source apportionment based on EEM-PARAFAC combined with microbial tracing model and its implication in complex pollution area, Wujin District, China

Further improving the quality of surface water is becoming more difficult after the control of main point-sources, especially in the complex pollution area with mixed industrial and agricultural productions, whereas the pollution source apportionment might be the key to quantify different pollution sources and developing some effective measures. In this study, a technical framework for source apportionment based on three-dimensional fluorescence and microbial traceability model is developed. Based on screening of the main environmental factors and their spatiotemporal characteristics, potential pollution sources have been tentatively identified. Then, the pollution sources are further tested based on the analysis of fluorescence excitation-emission matrix (EEM) and the similarity of fluorescence components in surface water and potential pollution sources. At the same time, the correlation between microbial species and pollution sources is constructed by analyzing the spatiotemporal characteristics of microbial composition and the response of main species to environmental factors. Therefore, pollution source apportionment is quantified using PCA-APCS-MLR, Fast Expectation-maximization for Microbial Source Tracking (FEAST), and Bayesian community-wide culture-independent microbial source tracking (SourceTracker). PCA-APCS-MLR could not effectively distinguish the contributions of different industrial sources in the complex environment of this study, and the contribution of unknown sources was high (average 39.60%). In contrast, the microbial traceability model can accurately identify the contribution of 7 pollution sources and natural sources, effectively reduce the proportion of unknown sources (average of FEAST is 19.81%, SourceTracker is 16.72%), and show better pollution identification and distribution capabilities. FEAST exhibits a more sensitive potential in source apportionment and shorter calculation time than SourceTracker, thus might be used to guide the precise regional pollution control, especially in the complex pollution environments.

Meta-analysis of microbial source tracking for the identification of fecal contamination in aquatic environments based on data-mining

Microbial source tracking (MST) technology represents an innovative approach employed to trace fecal contamination in environmental water systems. The performance of primers may be affected by amplification techniques, target primer categories, and regional differences. To investigate the influence of these factors on primer recognition performance, a meta-analysis was conducted on the application of MST in water environments using three databases: Web of Science, Scopus, and PubMed (n = 2291). After data screening, 46 studies were included in the final analysis. The investigation encompassed Polymerase Chain Reaction (PCR)/quantitative PCR (qPCR) methodologies, dye-based (SYBR)/probe-based (TaqMan) techniques, and geographical differences of a human host-specific (HF183) primer and other 21 additional primers. The results indicated that the primers analyzed were capable of differentiating host specificity to a certain degree. Nonetheless, by comparing sensitivity and specificity outcomes, it was observed that virus-based primers exhibited superior specificity and recognition capacity, as well as a stronger correlation with human pathogenicity in water environments compared to bacteria-based primers. This finding highlights an important direction for future advancements. Moreover, within the same category, qPCR did not demonstrate significant benefits over conventional PCR amplification methods. In comparing dye-based and probe-based techniques, it was revealed that the probe-based method's advantage lay primarily in specificity, which may be associated with the increased propensity of dye-based methods to produce false positives. Furthermore, the heterogeneity of the HF183 primer was not detected in China, Canada, and Singapore respectively, indicating a low likelihood of regional differences. The variation among the 21 other primers may be attributable to regional differences, sample sources, detection techniques, or alternative factors. Finally, we identified that economic factors, climatic conditions, and geographical distribution significantly influence primer performance.

Assessment of Microbial Source Tracking Marker and Fecal Indicator Bacteria on Food-Contact Surfaces in School Cafeterias

Food poisoning outbreaks in schools can affect many students, causing physical and psychological damage and time and economic loss. Fecal indicator bacteria (FIB) have been used to monitor the contamination; however, the detection is time-consuming and confirms the contamination from all warm-blooded animals. Microbial source tracking (MST) is a molecular-based detection method that is host specific. This study aimed to evaluate MSTs and FIBs for tracing contamination in the school cafeteria. The average total aerobic count was 0.89 to 3.63 log CFU/100 cm2, and the faucets in the cooking area showed a significantly high aerobic count. The stove valve, faucet, and hand-washer were the most contaminated area, with a concentration of 1.90 to 6.80 log CFU/100 cm2 from the frequent hand contact. Escherichia coli was not detected on any surfaces, and coliform was detected on five surfaces: the sink and faucet in the food preparation area, the faucet in the cooking area, the hand-washer, and the toilet seat in the restroom with 0.33 to 3.64 log CFU/100 cm2. Human-specific crAssphage appeared on a faucet in the food preparation area, while HF183 was not detected. The result indicates that the continuous monitoring of frequent hand-contact areas is recommended to maintain the hygiene condition in the school cafeteria.

Associations among Household Animal Ownership, Infrastructure, and Hygiene Characteristics with Source Attribution of Household Fecal Contamination in Peri-Urban Communities of Iquitos, Peru

Using previously validated microbial source tracking markers, we detected and quantified fecal contamination from avian species and avian exposure, dogs, and humans on household cooking tables and floors. The association among contamination, infrastructure, and socioeconomic covariates was assessed using simple and multiple ordinal logistic regressions. The presence of Campylobacter spp. in surface samples was linked to avian markers. Using molecular methods, animal feces were detected in 75.0% and human feces in 20.2% of 104 households. Floors were more contaminated than tables as detected by the avian marker Av4143, dog marker Bactcan, and human marker Bachum. Wood tables were consistently more contaminated than non-wood surfaces, specifically with the mitochondrial avian markers ND5 and CytB, fecal marker Av4143, and canine marker Bactcan. Final multivariable models with socioeconomic and infrastructure characteristics included as covariates indicate that detection of avian feces and avian exposure was associated with the presence of chickens, maternal age, and length of tenancy, whereas detection of human markers was associated with unimproved water source. Detection of Campylobacter in surface samples was associated with the avian fecal marker Av4143. We highlight the critical need to detect and measure the burden of animal fecal waste when evaluating household water, hygiene, and sanitation interventions, and the possibility of decreasing risk of exposure through the modification of surfaces to permit more effective household disinfection practices. Animals may be a more important source of household fecal contamination than humans in many low-resource settings, although interventions have historically focused almost exclusively on managing human waste.