Accounting for Bacterial Overlap Between Raw Water Communities and Contaminating Sources Improves the Accuracy of Signature-Based Microbial Source Tracking

Diverse sources of fecal contamination in macroalgae wrack-affected environment adjacent to river outflow along the Baltic Sea coast

We investigated the dynamics of feces-associated microorganisms in areas with wrack accumulation in the southeastern part of the Baltic Sea. Our study covered single-day (2021 ) and multi-day (2022) observations during the recreational season. We collected water, sand, and wrack samples and assessed the abundance of fecal indicator bacteria (FIB), as well metagenomic analysis was conducted to monitor changes in microbial composition. Based on metagenomic data we identified taxa associated with feces, sewage, and ruminant sources. Human-related fecal pollution based on genetic markers correlated with the presence of Lachnospiraceae, Prevotellaceae and Rickenellacea abundance. Higher abundance and diversity of feces-associated and ruminant-associated taxa and the presence of enteric pathogens were observed when wrack accumulated near the river outflow in 2021, suggesting a potential link with fecal pollution from the river. As a preventive measure, it is recommended to remove the wrack to reduce the risk of exposure to potential enteric pathogens if it is accumulated next to the river outflow.

Marine sediments are identified as an environmental reservoir for Escherichia coli: comparing signature-based and novel amplicon sequencing approaches for microbial source tracking

Viable Escherichia coli were detected in sediments near a point of wastewater discharge in a marine coastal environment in Sweden. Since high concentrations were found in the sediments nearest the pipe, this suggested that treated wastewater effluent was the source of the microbes. In order to examine this hypothesis, different bioinformatics approaches were applied using 16S rRNA gene V3-V4 amplicon sequences from the sediments. Both signature-based source tracking using sequence libraries describing known sources of fecal water pollution (SourceTracker); and, a curated source tracking method, indicated that sediments were contaminated with wastewater. The results from the curated approach were independently confirmed using differential abundance analysis (DESeq2). A number of taxa originating from wastewater were identified which can be used to describe contamination of the sediments, and examine the spread of these specific taxa, even at low relative abundance, along the urban coast. Sequences of phylum Bacteroidetes (such as Bacteroides and Prevotella) and Firmicutes (such as Romboutsia) increased in sediments with higher concentrations of E. coli. In addition, sequences from Trichococcus are proposed as an indicator for treated wastewater. All three source tracking approaches, and the detection of viable E. coli, suggest that urban sediments can be a reservoir for indicator bacteria.

Achieving pan-microbiome biological insights via the dbBact knowledge base

16S rRNA amplicon sequencing provides a relatively inexpensive culture-independent method for studying microbial communities. Although thousands of such studies have examined diverse habitats, it is difficult for researchers to use this vast trove of experiments when interpreting their own findings in a broader context. To bridge this gap, we introduce dbBact - a novel pan-microbiome resource. dbBact combines manually curated information from studies across diverse habitats, creating a collaborative central repository of 16S rRNA amplicon sequence variants (ASVs), which are assigned multiple ontology-based terms. To date dbBact contains information from more than 1000 studies, which include 1500000 associations between 360000 ASVs and 6500 ontology terms. Importantly, dbBact offers a set of computational tools allowing users to easily query their own datasets against the database. To demonstrate how dbBact augments standard microbiome analysis we selected 16 published papers, and reanalyzed their data via dbBact. We uncovered novel inter-host similarities, potential intra-host sources of bacteria, commonalities across different diseases and lower host-specificity in disease-associated bacteria. We also demonstrate the ability to detect environmental sources, reagent-borne contaminants, and identify potential cross-sample contaminations. These analyses demonstrate how combining information across multiple studies and over diverse habitats leads to better understanding of underlying biological processes.

Bacterial composition in Swedish raw drinking water reveals three major interacting ubiquitous metacommunities

BACKGROUND

Surface raw water used as a source for drinking water production is a critical resource, sensitive to contamination. We conducted a study on Swedish raw water sources, aiming to identify mutually co-occurring metacommunities of bacteria, and environmental factors driving such patterns.

METHODS

The water sources were different regarding nutrient composition, water quality, and climate characteristics, and displayed various degrees of anthropogenic impact. Water inlet samples were collected at six drinking water treatment plants over 3 years, totaling 230 samples. The bacterial communities of DNA sequenced samples (n = 175), obtained by 16S metabarcoding, were analyzed using a joint model for taxa abundance.

RESULTS

Two major groups of well-defined metacommunities of microorganisms were identified, in addition to a third, less distinct, and taxonomically more diverse group. These three metacommunities showed various associations to the measured environmental data. Predictions for the well-defined metacommunities revealed differing sets of favored metabolic pathways and life strategies. In one community, taxa with methanogenic metabolism were common, while a second community was dominated by taxa with carbohydrate and lipid-focused metabolism.

CONCLUSION

The identification of ubiquitous persistent co-occurring bacterial metacommunities in freshwater habitats could potentially facilitate microbial source tracking analysis of contamination issues in freshwater sources.

Tracking bacterial pollution at a marine wastewater outfall site - A case study from Norway

Coastal marine environments are increasingly affected by anthropogenic impacts, such as the release of sewage at outfall sites and agricultural run-off. Fecal pollution introduced to the sea through these activities poses risks of spreading microbial diseases and disseminating antibiotic resistant bacteria and their genes. The study area of this research, Bore beach, is situated between two such point sources, an outfall site where treated sewage is released 1 km off the coast and a stream that carries run-off from an agricultural area to the northern end of the beach. In order to investigate whether and to what extent fecal contamination from the sewage outfall reached the beach, we used microbial source tracking, based on whole community analysis. Samples were collected from sea water at varying distances from the sewage outfall site and along the beach, as well as from the sewage effluent and the stream. Amplicon sequencing of 16S rRNA genes from all the collected samples was carried out at two time points (June and September). In addition, the seawater at the sewage outfall site and the sewage effluent were subject to shotgun metagenomics. To estimate the contribution of the sewage effluent and the stream to the microbial communities at Bore beach, we employed SourceTracker2, a program that uses a Bayesian algorithm to perform such quantification. The SourceTracker2 results suggested that the sewage effluent is likely to spread fecal contamination towards the beach to a greater extent than anticipated based on the prevailing sea current. The estimated mixing proportions of sewage at the near-beach site (P4) were 0.22 and 0.035% in June and September, respectively. This was somewhat below that stream's contribution in June (0.028%) and 10-fold higher than the stream's contribution in September (0.004%). Our analysis identified a sewage signal in all the tested seawater samples.

Microbial Interactions - Underexplored Links Between Public Health Relevant Bacteria and Protozoa in Coastal Environments

The co-existence of bacteria and protozoa in aquatic environments has led to the evolution of predation defense mechanisms by the bacteria. Some of the predation-resistant bacteria (PRB) are also pathogenic to humans and other mammals. The links between PRB and protozoa in natural aquatic systems are poorly known, but they are important in predicting outbreaks and determining the long-term consequences of a contamination event. To elucidate co-occurrence patterns between PRB (16S rRNA) and bacterivorous protozoa (18S rRNA), we performed a field study in a coastal area in the northern Baltic Sea. Interactions between bacteria and protozoa were explored by using two complementary statistical tools. We found co-occurrence patterns between specific PRB and protozoa, such as Legionella and Ciliophora, and we also found that the interactions are genotype-specific as, for example, Rickettsia. The PRB sequence diversity was larger in bays and freshwater inlets compared to offshore sites, indicating local adaptions. Considering the PRB diversity in the freshwater in combination with the large spring floods in the area, freshwater influxes should be considered a potential source of PRB in the coastal northern Baltic Sea. These findings are relevant for the knowledge of survival and dispersal of potential pathogens in the environment.

Use of metagenomic microbial source tracking to investigate the source of a foodborne outbreak of cryptosporidiosis

Cryptosporidium is a protozoan parasite of global public health importance that causes gastroenteritis in a variety of vertebrate hosts, with many human outbreaks reported yearly, often from ingestion of contaminated water or food. Despite the major public health implications, little is typically known about sources of contamination of disease outbreaks caused by Cryptosporidium. Here, we study a national foodborne outbreak resulted from infection with Cryptosporidium parvum via romaine lettuce, with the main goal to trace the source of the parasite. To do so, we combined traditional outbreak investigation methods with molecular detection and characterization methods (i.e. PCR based typing, amplicon and shotgun sequencing) of romaine lettuce samples collected at the same farm from which the contaminated food was produced. Using 18S rRNA typing, we detected C. parvum in two out of three lettuce samples, which was supported by detections in the metagenome analysis. Microbial source tracking analysis of the lettuce samples suggested sewage water as a likely source of the contamination, albeit with some uncertainty. In addition, the high degree of overlap in bacterial species content with a public human gut microbial database corroborated the source tracking results. The combination of traditional and molecular based methods applied here is a promising tool for future source tracking investigations of food- and waterborne outbreaks of Cryptosporidium spp. and can help to control and mitigate contamination risks.

eDNA profiling of mammals, birds, and fish of surface waters by mitochondrial metagenomics: application for source tracking of fecal contamination in surface waters

Knowing the composition of animals present in aquatic ecosystems can tell us about the anthropic pressures on these environments. One of these pressures is the occurrence of fecal contamination. However, this contamination can originate from more than one animal species in areas where urban and agricultural activities overlap. Mitochondrial DNA (mtDNA) has become the standard barcoding tool to identify the presence of animal species in environment. Amplicon-sequencing metagenomics is a powerful approach to derive the animal profile in an environment. However, PCR primers targeting mtDNA of a broad range of animals are highly degenerate or generate short DNA fragments that could cause ambiguous affiliation. Here we report the development of a new set of primers targeting the mitochondrial 16S ribosomal RNA genes of a broad range of terrestrial and aquatic animals, which include mammals, birds, and fishes. These primers successfully amplified mtDNA from environmental DNA (eDNA) extracted from surface waters. Sequencing the resulting amplicons revealed the presence of mammals and birds that may contribute in fecal contamination of surface water. In one of the river samples high in fecal indicator bacteria, human and bovine mtDNA accounted for 40.5% and 4.1% of the sequences, respectively, suggesting fecal contamination by these two animals. These findings indicate that our PCR primers coupled with amplicon-sequencing metagenomics contribute in profiling the animal diversity in the surface waters and its surrounding. This approach could be a valuable tool to identify simultaneously the potential contribution of various animals as sources of fecal contamination in surface waters.

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.

FORENSIC: an Online Platform for Fecal Source Identification

Sewage overflows, agricultural runoff, and stormwater discharges introduce fecal pollution into surface waters. Distinguishing these sources is critical for evaluating water quality and formulating remediation strategies. With the falling costs of sequencing, microbial community-based water quality assessment tools are under development. However, their application is limited by the need to build reference libraries, which requires extensive sampling of sources and bioinformatic expertise. Here, we introduce FORest Enteric Source IdentifiCation (FORENSIC; https://forensic.sfs.uwm.edu/), an online, library-independent source tracking platform based on random forest classification and 16S rRNA gene amplicon sequences to identify in environmental samples common fecal contamination sources, including humans, domestic pets, and agricultural animals. FORENSIC relies on a broad reference signature database of Bacteroidales and Clostridiales, two predominant bacterial groups that have coevolved with their hosts. As a result, these groups demonstrate cohesive and reliable assemblage patterns within mammalian species or among species sharing the same diet/physiology. We created a scalable and extensible platform that we tested for global applicability using samples collected in distant geographic locations. This Web application offers a fast and intuitive approach for fecal source identification, particularly in sewage-contaminated waters.IMPORTANCE FORENSIC is an online platform to identify sources of fecal pollution without the need to create reference libraries. FORENSIC is based on the ability of random forest classification to extract cohesive source microbial signatures to create classifiers despite individual variability and to detect the signatures in environmental samples. We primarily focused on defining sewage signals, which are associated with a high human health risk in polluted waters. To test for fecal contamination sources, the platform only requires paired-end reads targeting the V4 or V6 regions of the 16S rRNA gene. We demonstrated that we could use V4V5 reads trimmed to the V4 positions to generate the reference signature. The systematic workflow we describe to create and validate the signatures could be applied to many disciplines. With the increasing gap between advancing technology and practical applications, this platform makes sequence-based water quality assessments accessible to the public health and water resource communities.

Airborne microbial biodiversity and seasonality in Northern and Southern Sweden

Microorganisms are essential constituents of ecosystems. To improve our understanding of how various factors shape microbial diversity and composition in nature it is important to study how microorganisms vary in space and time. Factors shaping microbial communities in ground level air have been surveyed in a limited number of studies, indicating that geographic location, season and local climate influence the microbial communities. However, few have surveyed more than one location, at high latitude or continuously over more than a year. We surveyed the airborne microbial communities over two full consecutive years in Kiruna, in the Arctic boreal zone, and Ljungbyhed, in the Southern nemoral zone of Sweden, by using a unique collection of archived air filters. We mapped both geographic and seasonal differences in bacterial and fungal communities and evaluated environmental factors that may contribute to these differences and found that location, season and weather influence the airborne communities. Location had stronger influence on the bacterial community composition compared to season, while location and season had equal influence on the fungal community composition. However, the airborne bacterial and fungal diversity showed overall the same trend over the seasons, regardless of location, with a peak during the warmer parts of the year, except for the fungal seasonal trend in Ljungbyhed, which fluctuated more within season. Interestingly, the diversity and evenness of the airborne communities were generally lower in Ljungbyhed. In addition, both bacterial and fungal communities varied significantly within and between locations, where orders like Rhizobiales, Rhodospirillales and Agaricales dominated in Kiruna, whereas Bacillales, Clostridiales and Sordariales dominated in Ljungbyhed. These differences are a likely reflection of the landscape surrounding the sampling sites where the landscape in Ljungbyhed is more homogenous and predominantly characterized by artificial and agricultural surroundings. Our results further indicate that local landscape, as well as seasonal variation, shapes microbial communities in air.