Comparison of Sewage and Animal Fecal Microbiomes by Using Oligotyping Reveals Potential Human Fecal Indicators in Multiple Taxonomic Groups

Difference of Microbial Community in the Stream Adjacent to the Mixed Antibiotic Effluent Source

Released antibiotics from source to stream can influence bacterial communities and potentially alter the ecosystem. This research provides a comprehensive examination of the sources, distribution, and bacterial community dynamics associated with varied antibiotic release sources adjacent to the stream. The residual of antibiotics from different sources was determined, and the bacterial community structure was examined to reveal the differences in the bacteria community in the stream. The residual of antibiotics was quantified with liquid chromatography-tandem mass spectrometry (LC-MS/MS), and the Illumina MiSeq platform was utilized to sequence bacterial 16S rRNA genes, providing comprehensive insights into the bacterial community structure in the sediment across five different sites. Results indicated that the presence and distribution of antibiotics were significantly influenced by released sources. In the case of the bacterial community, the Proteobacteria and Firmicutes were the most dominant phyla in the sediment, and especially, the Firmicutes showed higher abundance in sites mostly affected by livestock sources. Additionally, livestock gut bacteria such as Clostridium saudiense, Proteiniclasticum ruminis, and Turicibacter sanguinis were prevalent in antibiotic-contaminated sites adjacent to livestock facilities. Overall, this study provides critical insights into the effect of antibiotic contamination by verifying the relationship between the occurrence of antibiotic residuals and the alteration in the bacterial community in the stream.

Anthropogenic activity remains the main contributor to fecal pollution in managed tropical watersheds as unraveled by PhyloChip microarray-based microbial source tracking

The spread of disease by enteric pathogens associated with fecal contamination is a major concern for the management of urban watersheds. So far, the relative contribution of natural and anthropogenic sources to fecal pollution in managed tropical watersheds remains poorly evaluated. In this study, the microbiomes of water samples collected from managed watersheds in Singapore were elicited using the PhyloChip, a dense 16S rRNA gene-based DNA microarray, and fecal impairment was inferred using a machine-learning classification algorithm (SourceTracker). The predicted contribution of wildlife fecal sources to environmental samples was generally negligible (< 0.01 ± 0.01), indicating a low likelihood of fecal impairment from natural sources. However, sewage showed considerably higher contribution (0.09 ± 0.05) to microbial communities in a subset of watershed samples from canals and rivers, suggesting persistent impairment of certain areas by anthropogenic activity although being managed. Interestingly, the contribution of sewage microbial communities showed decreasing trends from canals/rivers to the connected reservoirs, indicating meaningful auto-mitigation of fecal pollution in canals and rivers. Notably, exclusion of locally derived fecal samples and source categories from the training data set impaired the predictive performance of the classification algorithm despite a high degree of similarity in the phylogenetic composition of microbiomes in biologically similar but geographically distinct sources.

Effective removal of iron, nutrients, micropollutants, and faecal bacteria in constructed wetlands cotreating mine water and sewage treatment plant effluent

Regulators in England and Wales have set new targets under the Environment Act 2021 for freshwater quality by 2038 that include halving the length of rivers polluted by harmful metals from abandoned mines and reducing phosphorus loadings from treated wastewater by 80%. In this context, an intriguing win-win opportunity exists in the removal of iron from abandoned mines and phosphate from small sewage treatment plants by coprecipitation in constructed wetlands (CWs). We investigated such a CW located at Lamesley, Northeast England, which cotreats abandoned coal mine and secondary-treated sewage treatment plant effluents. We assessed the removal of nutrients, heavy metals, organic micropollutants, and faecal coliforms by the CW, and characterized changes in the water bacteriology comprehensively using environmental DNA. The CW effectively removed ammonium-nitrogen, phosphorus, iron, and faecal coliforms by an average of 86, 74, 98, and 75%, respectively, to levels below or insignificantly different from those in the receiving river. The CW also effectively removed micropollutants such as acetaminophen, caffeine, and sulpiride by 70-100%. Molecular microbiology methods showed successful conversion of sewage and mine water microbiomes into a freshwater microbiome. Overall, the CW significantly reduced impacts on the rural water environment with minimal operational requirements.

Microplastics in urban waters and its effects on microbial communities: a critical review

Microplastic (MP) pollution is one of the emerging threats to the water and terrestrial environment, forcing a new environmental challenge due to the growing trend of plastic released into the environment. Synthetic and non-synthetic plastic components can be found in rivers, lakes/reservoirs, oceans, mountains, and even remote areas, such as the Arctic and Antarctic ice sheets. MPs' main challenge is identifying, measuring, and evaluating their impacts on environmental behaviors, such as carbon and nutrient cycles, water and wastewater microbiome, and the associated side effects. However, until now, no standardized methodical protocols have been proposed for comparing the results of studies in different environments, especially in urban water and wastewater. This review briefly discusses MPs' sources, fate, and transport in urban waters and explains methodological uncertainty. The effects of MPs on urban water microbiomes, including urban runoff, sewage wastewater, stagnant water in plumbing networks, etc., are also examined in depth. Furthermore, this study highlights the pathway of MPs and their transport vectors to different parts of ecosystems and human life, particularly through mediating microbial communities, antibiotic-resistant genes, and biogeochemical cycles. Overall, we have briefly highlighted the present research gaps, the lack of appropriate policy for evaluating microplastics and their interactions with urban water microbiomes, and possible future initiatives.

Hormetic effect of 17α-ethynylestradiol on activated sludge microbial community response

Synthetic estrogen analogues are among the most potent estrogenic contaminants in effluents from wastewater treatment plants. Although its effects have been well elucidated in the feminization of male fish and interference with the endocrine systems in humans, it has not been fully explored in the activated sludge (AS) microbiome, particularly EE2 (17α-ethynylestradiol). Therefore, in this study, the bacterial community shift in a 6-day laboratory-scale reactor in environmental (0, 5, 10, and 100 ng/L) and predictive elevated concentrations (5, 10, and 100 mg/L) of EE2 was investigated using culture-based and metagenomics approaches. Results showed significant changes (t-test, all p < 0.05) between initial and final physicochemical parameters (pH, DO, and EC). Although environmental concentrations showed a slight decrease in microbial counts (5.6 × 10⁶ to 4.6 × 10⁶ CFU/ml) after a 24-h incubation for the culturable approach, the predictive elevated concentrations (5 to 100 mg/L) revealed a drastic microbial counts reduction (5.6 × 10⁶ to 8 × 10² CFU/ml). The metagenomic data analysis uncovered that bacterial communities in the control sample were dominated by Proteobacteria, followed by Bacteroidetes and Firmicutes. The taxonomic classification after exposure of microbial communities in various concentrations revealed significant differences in community composition between environmental concentration (Shannon indices between 2.58 to 3.68) and predictive elevated concentrations (Shannon indices between 2.24 and 2.84; t-test, all p < 0.05). The EE2 enriched seven OTUs were Novosphingobium, Cloacibacterium, Stenotrophomonas, Enterobacteriaceae_unclassified, Stenotrophomonas, Enterobacteriaceae_unclassified and Rhodobacteraceae_unclassified. These results were supported by a dehydrogenase activity (DHA) test, which demonstrated less (about 40%) DHA in predictive elevated concentrations than in environmental concentrations. Notwithstanding, these findings suggest that EE2 may possess potent hormetic effect as evidenced by promotion of microbiome richness and dehydrogenase activity of AS in lower EE2 doses.

The mosquito microbiome includes habitat-specific but rare symbionts

Microbial communities are known to influence mosquito lifestyles by modifying essential metabolic and behavioral processes that affect reproduction, development, immunity, digestion, egg survival, and the ability to transmit pathogens. Many studies have used 16S rRNA gene amplicons to characterize mosquito microbiota and investigate factors that influence host-microbiota dynamics. However, a relatively low taxonomic resolution due to clustering methods based on arbitrary threshold and the overall dominance of Wolbachia or Asaia symbionts obscured the investigation of rare members of mosquito microbiota in previous studies. Here, we used high resolution Shannon entropy-based oligotyping approach to analyze the microbiota of Culex pipiens, Culex quinquefasciatus and Aedes individuals from continental Southern France and overseas Guadeloupe as well as from laboratories with or without antibiotics treatment. Our experimental design that resulted in a series of mosquito samples with a gradient of Wolbachia density and relative abundance along with high-resolution analyses of amplicon sequences enabled the recovery of a robust signal from typically less accessible bacterial taxa. Our data confirm species-specific mosquito-bacteria associations with geography as a primary factor that influences bacterial community structure. But interestingly, they also reveal co-occurring symbiotic bacterial variants within single individuals for both Elizabethkingia and Erwinia genera, distinct and specific Asaia and Chryseobacterium in continental and overseas territories, and a putative rare Wolbachia variant. Overall, our study reveals the presence of previously overlooked microdiversity and multiple closely related symbiotic strains within mosquito individuals with a remarkable habitat-specificity.

INFORMATION CONTENT OF HIGH-ORDER ASSOCIATIONS OF THE HUMAN GUT MICROBIOTA NETWORK

The human gastrointestinal tract is an environment that hosts an ecosystem of microorganisms essential to human health. Vital biological processes emerge from fundamental inter- and intra-species molecular interactions that influence the assembly and composition of the gut microbiota ecology. Here we quantify the complexity of the ecological relationships within the human infant gut microbiota ecosystem as a function of the information contained in the nonlinear associations of a sequence of increasingly-specified maximum entropy representations of the system. Our paradigm frames the ecological state, in terms of the presence or absence of individual microbial ecological units that are identified by amplicon sequence variants (ASV) in the gut microenvironment, as a function of both the ecological states of its neighboring units and, in a departure from standard graphical model representations, the associations among the units within its neighborhood. We characterize the order of the system based on the relative quantity of statistical information encoded by high-order statistical associations of the infant gut microbiota.

Oligotyping and metagenomics reveal distinct Candidatus Accumulibacter communities in side-stream versus conventional full-scale enhanced biological phosphorus removal (EBPR) systems

Candidatus Accumulibacter phosphatis (CAP) and its clade-level micro-diversity has been associated with and implicated in functional differences in phosphorus removal performance in enhanced biological phosphorus removal (EBPR) systems. Side-stream EBPR (S2EBPR) is an emerging process that has been shown to present a suite of advantages over the conventional EBPR design, however, large knowledge gaps remain in terms of its underlying ecological mechanisms. Here, we compared and revealed the higher-resolution differences in microbial ecology of CAP between a full-scale side-stream EBPR configuration and a conventional A2O EBPR process that were operated in parallel and with the same influent feed. Even though the relative abundance of CAP, revealed by 16S rRNA gene amplicon sequencing, was similar in both treatment trains, a clade-level analysis, using combined 16S rRNA-gene based amplicon sequencing and oligotyping analysis and metagenomics analysis, revealed the distinct CAP microdiversity between the S2EBPR and A2O configurations that likely attributed to the improved performance in S2EBPR in comparison to conventional EBPR. Furthermore, genome-resolved metagenomics enabled extraction of three metagenome-assembled genomes (MAGs) belonging to CAP clades IIB (RCAB4-2), IIC (RC14) and II (RC18), from full-scale EBPR sludge for the first time, including a distinct Ca. Accumulibacter clade that is dominant and associated only with the S2EBPR configuration. The results also revealed the temporally increasing predominance of RC14, which belonged to Clade IIC, during the implementation of the S2EBPR configuration. Finally, we also show the existence of previously uncharacterized diversity of clades of CAP, namely the clades IIB and as yet unidentified clade of type II, in full-scale EBPR communities, highlighting the unknown diversity of CAP communities in full-scale EBPR systems.

Biofilm producing indigenous bacteria isolated from municipal sludge and their nutrient removal ability in moving bed biofilm reactor from the wastewater

In the present study, improved moving bed biofilm reactor (MBBR) was applied to enhance the nutrient removal ability of the municipal wastewater. A total of 18 indigenous bacterial isolates were screened from the sewage sludge sample and nitrate reductase, nitrite reductase and hydroxylamine oxidase was analyzed. The strains Pseudomonas aeruginosa NU1 and Acinetobacter calcoaceticus K12 produced 0.87 ± 0.05 U/mg and 0.52 ± 0.12 U/mg hydroxylamine oxidase, 1.023 ± 0.062 U/mg and 1.29 ± 0.07 U/mg nitrite reductase, and 0.789 ± 0.031 U/mg and 1.07 ± 0.13 U/mg nitrate reductase. Nitrogen and phosphate removal improved by the addition of nutrient sources and achieved > 80% removal rate. pH and temperature of the medium also affected nutrient removal and improved removal was achieved at optimum level (p < 0.05). MBBR was designed with R1 (aerobic), R2 and R3 (anoxic) reactors. MBBR reactors removed acceptable level phosphorus removal properties up to 7.2 ± 3.8%, 42.4 ± 4.6%, and 84.2 ± 13.1% in the R1, R2, R3 and R4 reactors, respectively. Denitrification rate showed linear relationship at increasing concentrations nitrogen content in the reactor and denitrification rate was 1.43 g NO₂-N /m²/day at 1.5 g NO₂-N /m²/day. Dehydrogenase activity was assayed in all reactors and maximum amount was detected in the aerobic biofilm reactor. Based on the present findings, MBBRs and the selected bacterial strains are useful for the degradation domestic wastewater with minimum working area.

A weight-of-evidence approach for identifying potential sources of untreated sewage inputs into a complex urbanized catchment

The Hawkesbury-Nepean River (HNR) is the largest catchment in the Sydney region and is undergoing unprecedented population growth. The HNR system receives a mix of anthropogenic inputs such as treated sewage, stormwater and agricultural runoff. Combined, these can diminish the ecological system health and pose potential concerns to human health. Of particular concern are inputs of untreated sewage, that can occur due to a range of different reasons including illegal point source discharges, failure of the sewerage network, and overloading of wastewater treatment plants during storm events. Here, we present findings of an intensive assessment across the HNR catchment where we used a weight-of-evidence (WOE) approach to identify untreated sewage contamination in surface waters against the background of treated effluent and diffuse inputs during post high flow conditions. Total nitrogen and phosphorus concentrations were used to assess treated effluent and diffuse inputs, and microbial analysis, including both culture-based traditional methods for E. coli and enterococci and qPCR analysis of Bacteroides and Lachnospiraceae, were used to assess raw sewage contamination. Despite a background of diffuse inputs from recent high flow events and the influence of treated wastewater, we found no gradient of faecal contamination along the HNR system or its tributaries. We observed two sites with evidence of untreated sewage contamination, where the human markers Bacteroides and Lachnospiraceae qPCR copy numbers were high. The biological and chemical approaches suggested these latter two hotspots originate from an industrial runoff source and possibly from a dry weather sewage leak. Our findings demonstrate the potential of a WOE approach in the assessment of human faecal signal in an urban river that can also pinpoint small sources of contamination as a strategy that can reshape the way monitoring is performed and the chemical end-points chosen to provide pertinent information on the potential risks to aquatic system health.

Measuring Environmental Exposure to Enteric Pathogens in Low-Income Settings: Review and Recommendations of an Interdisciplinary Working Group

Infections with enteric pathogens impose a heavy disease burden, especially among young children in low-income countries. Recent findings from randomized controlled trials of water, sanitation, and hygiene interventions have raised questions about current methods for assessing environmental exposure to enteric pathogens. Approaches for estimating sources and doses of exposure suffer from a number of shortcomings, including reliance on imperfect indicators of fecal contamination instead of actual pathogens and estimating exposure indirectly from imprecise measurements of pathogens in the environment and human interaction therewith. These shortcomings limit the potential for effective surveillance of exposures, identification of important sources and modes of transmission, and evaluation of the effectiveness of interventions. In this review, we summarize current and emerging approaches used to characterize enteric pathogen hazards in different environmental media as well as human interaction with those media (external measures of exposure), and review methods that measure human infection with enteric pathogens as a proxy for past exposure (internal measures of exposure). We draw from lessons learned in other areas of environmental health to highlight how external and internal measures of exposure can be used to more comprehensively assess exposure. We conclude by recommending strategies for advancing enteric pathogen exposure assessments.

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.

An in silico analysis of acquired antimicrobial resistance genes in Aeromonas plasmids

Sequences of 105 Aeromonas species plasmids were probed for acquired anti-microbial resistance (AMR) genes using a bioinformatics approach. The plasmids showed no positive linear correlation between size and GC content and up to 55 acquired AMR genes were found in 39 (37%) plasmids after in silico screening for resistance against 15 antibiotic drug classes. Overall, potential multiple antibiotic resistance (p-MAR) index ranged from 0.07 to 0.53. Up to 18 plasmids were predicted to mediate multiple drug resistance (MDR). Plasmids pS121-1a (A. salmonicida), pWCX23_1 (A. hydrophila) and pASP-a58 (A. veronii) harboured 18, 15 and 14 AMR genes respectively. The five most occurring drug classes for which AMR genes were detected were aminoglycosides (27%), followed by beta-lactams (17%), sulphonamides (13%), fluoroquinolones (13%), and phenicols (10%). The most prevalent genes were a sulphonamide resistant gene Sul1, the gene aac (6')-Ib-cr (aminoglycoside 6'-N-acetyl transferase type Ib-cr) resistant to aminoglycosides and the blaKPC-2 gene, which encodes carbapenemase-production. Plasmid acquisition of AMR genes was mainly inter-genus rather than intra-genus. Eighteen plasmids showed template or host genes acquired from Pseudomonas monteilii, Salmonella enterica or Escherichia coli. The most occurring antimicrobial resistance determinants (ARDs) were beta-lactamase, followed by aminoglycosides acetyl-transferases, and then efflux pumps. Screening of new isolates in vitro and in vivo is required to ascertain the level of phenotypic expression of colistin and other acquired AMR genes detected.

Ecological and Technical Mechanisms for Cross-Reaction of Human Fecal Indicators with Animal Hosts

Quantitative PCR (qPCR) assays for human/sewage marker genes have demonstrated sporadic positive results in animal feces despite their high specificities to sewage and human feces. It is unclear whether these positive reactions are caused by true occurrences of microorganisms containing the marker gene (i.e., indicator organisms) or nonspecific amplification (false positive). The distribution patterns of human/sewage indicator organisms in animals have not been explored in depth, which is crucial for evaluating a marker gene's true- or false-positive reactions. Here, we analyzed V6 region 16S rRNA gene sequences from 257 animal fecal samples and tested a subset of 184 using qPCR for human/sewage marker genes. Overall, specificities of human/sewage marker genes within sequencing data were 99.6% (BacV6-21), 96.9% (Lachno3), and 96.1% (HF183, indexed by its inferred V6 sequence). Occurrence of some true cross-reactions was associated with atypical compositions of organisms within the genera Blautia or Bacteroides For human/sewage marker qPCR assays, specificities were 96.7% (HF183/Bac287R), 96.2% (BacV6-21), 95.6% (human Bacteroides [HB]), and 94.0% (Lachno3). Select assays duplexed with either Escherichia coli or Enterococcus spp. were also validated. Most of the positive qPCR results in animals were low level and, on average, 2 orders of magnitude lower than the copy numbers of E. coli and Enterococcus spp. The lower specificity in qPCR assays compared to sequencing data was mainly caused by amplification of sequences highly similar to the marker gene and not the occurrence of the exact marker sequence in animal fecal samples.IMPORTANCE Identifying human sources of fecal pollution is critical to remediate sanitation concerns. Large financial investments are required to address these concerns; therefore, a high level of confidence in testing results is needed. Human fecal marker genes validated in this study showed high specificity in both sequencing data and qPCR results. Human marker sequences were rarely found in individual animals, and in most cases, the animals had atypical microbial communities. Sequencing also revealed the presence of closely related organisms that could account for nonspecific amplification in certain assays. Both the true cross-reactions and the nonspecific amplification had low signals well below E. coli or Enterococcus levels and likely would not impact the assay's ability to reliably detect human fecal pollution. No animal source had multiple human/sewage marker genes present; therefore, using a combination of marker genes would increase the confidence of human fecal pollution detection.

Gut carriage of antimicrobial resistance genes among young children in urban Maputo, Mozambique: Associations with enteric pathogen carriage and environmental risk factors

Because poor sanitation is hypothesized as a major direct and indirect pathway of exposure to antimicrobial resistance genes (ARGs), we sought to determine a) the prevalence of and b) environmental risk factors for gut carriage of key ARGs in a pediatric cohort at high risk of enteric infections due to poor water, sanitation, and hygiene (WASH) conditions. We investigated ARGs in stool from young children in crowded, low-income settlements of Maputo, Mozambique, and explored potential associations with concurrent enteric pathogen carriage, diarrhea, and environmental risk factors, including WASH. We collected stool from 120 children <14 months old and tested specimens via quantal, multiplex molecular assays for common bacterial, viral, and protozoan enteric pathogens and 84 ARGs encoding potential resistance to 7 antibiotic classes. We estimated associations between ARG detection (number and diversity detected) and concurrently-measured enteric pathogen carriage, recently-reported diarrhea, and risk factors in the child's living environment. The most commonly-detected ARGs encoded resistance to macrolides, lincosamides, and streptogramins (100% of children); tetracyclines (98%); β-lactams (94%), aminoglycosides (84%); fluoroquinolones (48%); and vancomycin (38%). Neither concurrent diarrhea nor measured environmental (including WASH) conditions were associated with ARG detection in adjusted models. Enteric pathogen carriage and ARG detection were associated: on average, 18% more ARGs were detected in stool from children carrying bacterial pathogens than those without (adjusted risk ratio (RR): 1.18, 95% confidence interval (CI): 1.02, 1.37), with 16% fewer ARGs detected in children carrying parasitic pathogens (protozoans, adjusted RR: 0.84, 95% CI: 0.71, 0.99). We observed gut ARGs conferring potential resistance to a range of antibiotics in this at-risk cohort that had high rates of enteric infection, even among children <14 months-old. Gut ARGs did not appear closely correlated with WASH, though environmental conditions were generally poor. ARG carriage may be associated with concurrent carriage of bacterial enteric pathogens, suggesting indirect linkages to WASH that merit further investigation.

A horizon scan of priorities for coastal marine microbiome research

Research into the microbiomes of natural environments is changing the way ecologists and evolutionary biologists view the importance of microorganisms in ecosystem function. This is particularly relevant in ocean environments, where microorganisms constitute the majority of biomass and control most of the major biogeochemical cycles, including those that regulate Earth's climate. Coastal marine environments provide goods and services that are imperative to human survival and well-being (for example, fisheries and water purification), and emerging evidence indicates that these ecosystem services often depend on complex relationships between communities of microorganisms (the 'microbiome') and the environment or their hosts - termed the 'holobiont'. Understanding of coastal ecosystem function must therefore be framed under the holobiont concept, whereby macroorganisms and their associated microbiomes are considered as a synergistic ecological unit. Here, we evaluate the current state of knowledge on coastal marine microbiome research and identify key questions within this growing research area. Although the list of questions is broad and ambitious, progress in the field is increasing exponentially, and the emergence of large, international collaborative networks and well-executed manipulative experiments are rapidly advancing the field of coastal marine microbiome research.

Investigating microbial indicators of anthropogenic marine pollution by 16S and 18S High-Throughput Sequencing (HTS) library analysis

High-Throughput Sequencing technologies are providing unprecedented inventories of microbial communities in aquatic samples, offering an invaluable tool to estimate the impact of anthropogenic pressure on marine communities. In this case study, the Mediterranean touristic site of Aci Castello (Italy) was investigated by High-Throughput Sequencing of 16S and 18S rRNA genes. The sampling area falls within a Marine Protected Area and, notwithstanding, features an untreated urban wastewater discharge. Seawater samples were collected close to the wastewater output (COL) and at a second station about 400 m further off (PAN), before and after a summer increase in population. Prokaryotic communities clustered according to stations, rather than to seasons. While PAN showed a typical, not impacted, marine microbial composition, COL was consistently enriched in Epsilonproteobacteria and Firmicutes. Protist communities showed a peculiar clustering, as COL at springtime stood alone and was dominated by Ciliophora, while the other samples were enriched in Dinophyta. Analysis of alternative, detectable by High-Throughput Sequencing, microbial indicators, including both faecal- and sewage-associated, allowed uncovering the different sources of pollution in coastal and anthropogenically impacted marine ecosystems, underpinning the relevance of High-Throughput Sequencing-based screening as rapid and precise method for water quality management.

Combined microbial and isotopic signature approach to identify nitrate sources and transformation processes in groundwater

Nitrate (NO₃^-) pollution is a serious problem worldwide. Identification of NO₃^- sources and transformation processes in aquifers is a key step in effectively controlling and mitigating NO₃^- contamination. In this study, hydrochemical, microbial, and dual isotopic approaches were integrated to elucidate the sources and processes influencing NO₃^- contamination in the Pearl River Delta, China. The results showed a severe NO₃^- contamination, with 75% of the samples having NO₃^--N concentrations above the WHO standard of 10 mg L^-1. The δ¹⁵NNO₃^- and δ¹⁸ONO₃^- values and a multivariate statistical analysis of hydrochemical data both revealed that manure and sewage were mainly responsible for NO₃^- contamination. Biological indicators further demonstrated that, manure and sewage had greater impacts on groundwater quality during the rainy season than during the dry season. Based on the significant relationships of δ¹⁵NNO₃^- and δ¹⁸ONO₃^- with the logarithmic NO₃^- concentration (Ln(NO₃^-)), denitrification was confirmed to occur in the discharge zone during the rainy season. Proteobacteria, Bacteroidetes, and Planctomycetes were identified as the dominant phyla, and Dechloromonas, Flavobacterium, and Nitrospira were dominant among the denitrifying bacteria in groundwater. The abundance of denitrifying bacteria had significant positive correlations with δ¹⁵NNO₃^- and NO₂^--N during the rainy season, further confirming the occurrence of denitrification during the rainy season. This study showed that dual isotope techniques combined with microbial data can be a powerful tool for identifying the sources and microbial processes affecting NO₃^- in groundwater. Moreover, the results can provide useful insights for environmental managers to verify groundwater pollution and better apply remediation solutions.

Hotspots of Sequence Variability in Gut Microbial Genes Encoding Pro-Inflammatory Factors Revealed by Oligotyping

The gut microbiota has been implicated in a number of normal and disease biological processes. Recent studies have identified a subset of gut bacterial genes as potentially involved in inflammatory processes. In this work, we explore the sequence variability for some of these bacterial genes using a combination of deep sequencing and oligotyping, a data analysis application that identifies mutational hotspots in short stretches of DNA. The genes for pks island, tcpC and usp, all harbored by certain strains of E. coli and all implicated in inflammation, were amplified by PCR directly from stool samples and subjected to deep amplicon sequencing. For comparison, the same genes were amplified from individual bacterial clones. The amplicons for pks island and tcpC from stool samples showed minimal levels of heterogeneity comparable with the individual clones. The amplicons for usp from stool samples, by contrast, revealed the presence of five distinct oligotypes in two different regions. Of these, the oligotype GT was found to be present in the control uropathogenic clinical isolate and also detected in stool samples from individuals with colorectal cancer (CRC). Mutational hotspots were mapped onto the USP protein, revealing possible substitutions around Leu110, Glu114, and Arg115 in the middle of the pyocin domain (Gln110, Gln114, and Thr115 in most healthy samples), and also Arg218 in the middle of the nuclease domain (His218 in the uropathogenic strain). All of these results suggest that a level of variability within bacterial pro-inflammatory genes could explain differences in bacterial virulence and phenotype.

Microbial Similarity between Students in a Common Dormitory Environment Reveals the Forensic Potential of Individual Microbial Signatures

Humans leave behind a microbial trail, regardless of intention. This may allow for the identification of individuals based on the “microbial signatures” they shed in built environments. In a shared living environment, these trails intersect, and through interaction with common surfaces may become homogenized, potentially confounding our ability to link individuals to their associated microbiota. We sought to understand the factors that influence the mixing of individual signatures and how best to process sequencing data to best tease apart these signatures.

The microbiota of the built environment is an amalgamation of both human and environmental sources. While human sources have been examined within single-family households or in public environments, it is unclear what effect a large number of cohabitating people have on the microbial communities of their shared environment. We sampled the public and private spaces of a college dormitory, disentangling individual microbial signatures and their impact on the microbiota of common spaces. We compared multiple methods for marker gene sequence clustering and found that minimum entropy decomposition (MED) was best able to distinguish between the microbial signatures of different individuals and was able to uncover more discriminative taxa across all taxonomic groups. Further, weighted UniFrac- and random forest-based graph analyses uncovered two distinct spheres of hand- or shoe-associated samples. Using graph-based clustering, we identified spheres of interaction and found that connection between these clusters was enriched for hands, implicating them as a primary means of transmission. In contrast, shoe-associated samples were found to be freely interacting, with individual shoes more connected to each other than to the floors they interact with. Individual interactions were highly dynamic, with groups of samples originating from individuals clustering freely with samples from other individuals, while all floor and shoe samples consistently clustered together.

Characterization of bacterial communities in wastewater with enhanced taxonomic resolution by full-length 16S rRNA sequencing

Wastewater treatment is crucial to environmental hygiene in urban environments. However, wastewater treatment plants (WWTPs) collect chemicals, organic matter, and microorganisms including pathogens and multi-resistant bacteria from various sources which may be potentially released into the environment via WWTP effluent. To better understand microbial dynamics in WWTPs, we characterized and compared the bacterial community of the inflow and effluent of a WWTP in Berlin, Germany using full-length 16S rRNA gene sequences, which allowed for species level determination in many cases and generally resolved bacterial taxa. Significantly distinct bacterial communities were identified in the wastewater inflow and effluent samples. Dominant operational taxonomic units (OTUs) varied both temporally and spatially. Disease associated bacterial groups were efficiently reduced in their relative abundance from the effluent by the WWTP treatment process, except for Legionella and Leptospira species which demonstrated an increase in relative proportion from inflow to effluent. This indicates that WWTPs, while effective against enteric bacteria, may enrich and release other potentially pathogenic bacteria into the environment. The taxonomic resolution of full-length 16S rRNA genes allows for improved characterization of potential pathogenic taxa and other harmful bacteria which is required to reliably assess health risk.

SODIUM BICARBONATE REMEDIATION OF ANTHROPOGENIC CONTAMINATION OF WATER AT THE GBNERR IN MISSISSIPPI

Grand Bay National Estuarine Research Reserve (GBNERR) is an important ecosystem in the Mississippi Gulf Coast. The GBNERR may be a potential source for contamination with anthropogenic bacterial pathogens that may play a significant role in the causation of waterborne human diseases. The objective of this study was to evaluate the interaction of physicochemical and microbiological water quality parameters at the GBNERR, determine quantitative levels and establish the potential for remediation of post-contamination of water and seafood by human fecal pollution from anthropogenic sources at the reserve. Water samples were collected aseptically from Bayous Heron, Cumbest, Point Aux Chenes Bay and Bangs Lake (Pine-O-Pine). Physicochemical parameters were determined using standard protocols. Eight bacterial species including Campylobacter were concentrated from water samples by membrane filtration. Water samples were tested for the presence of traditional indicator microorganisms including: heterotrophic (HPC), total coliforms (TC), fecal coliforms (FC) and enterococcus (ENT) in CFU/ml concentrations. Mean values of temperature, specific conductivity, dissolved oxygen and pH were within acceptable levels in comparison to MDEQ, USEPA and the USGS standards during the time of investigation. However, the values of turbidity in Grand Bay water exceeded USEPA recommended levels in several occasions during the investigation. Data from this study indicates significant variability (p < 0.0001) in mean bacteria concentrations between sites. The data also indicates significant impact of Sodium bicarbonate treatment in the remediation of post contamination and survival of pathogens from the GBNERR Bayous Heron, Cumbest and Pine-O-Pine when compared with control findings. The interaction of physicochemical and microbiological parameters of water through external chemical manipulation by Sodium bicarbonate may provide utility in the remediation of post-contamination with anthropogenic pathogens such as E. coli, Enterococci, Campylobacter, Vibrio, Giardia and Cryptosporidium. Presence of high numbers of indicator bacteria suggest public health concerns for oyster and shellfish consumers as well as other water contact activities. Hence, control strategies should be developed and implemented to prevent or remediate any future contamination of the GBNERR waters citing the economic impact of such contamination on shell fish fishing activities at the reserve.

Highly Specific Sewage-Derived Bacteroides Quantitative PCR Assays Target Sewage-Polluted Waters

The identification of sewage contamination in water has primarily relied on the detection of human-associated Bacteroides using markers within the V2 region of the 16S rRNA gene. Despite the establishment of multiple assays that target the HF183 cluster (i.e., Bacteroides dorei) and other Bacteroides organisms (e.g., Bacteroides thetaiota omicron), the potential for more human-associated markers in this genus has not been explored in depth. We examined the Bacteroides population structure in sewage and animal hosts across the V4V5 and V6 hypervariable regions. Using near-full-length cloned sequences, we identified the sequences in the V4V5 and V6 hypervariable regions that are linked to the HF183 marker in the V2 region and found these sequences were present in multiple animals. In addition, the V4V5 and V6 regions contained human fecal marker sequences for organisms that were independent of the HF183 cluster. The most abundant Bacteroides in untreated sewage was not human associated but pipe derived. Two TaqMan quantitative PCR (qPCR) assays targeting the V4V5 and V6 regions of this organism were developed. Validation studies using fecal samples from seven animal hosts (n = 76) and uncontaminated water samples (n = 30) demonstrated the high specificity of the assays for sewage. Freshwater Bacteroides were also identified in uncontaminated water samples, demonstrating that measures of total Bacteroides do not reflect fecal pollution. A comparison of two previously described human Bacteroides assays (HB and HF183/BacR287) in municipal wastewater influent and sewage-contaminated urban water samples revealed identical results, illustrating the assays target the same organism. The detection of sewage-derived Bacteroides provided an independent measure of sewage-impacted waters.IMPORTANCE Bacteroides are major members of the gut microbiota, and host-specific organisms within this genus have been used extensively to gain information on pollution sources. This study provides a broad view of the population structure of Bacteroides within sewage to contextualize the well-studied HF183 marker for a human-associated Bacteroides The study also delineates host-specific sequence patterns across multiple hypervariable regions of the 16S rRNA gene to improve our ability to use sequence data to assess water quality. Here, we demonstrate that regions downstream of the HF183 marker are nonspecific but other potential human-associated markers are present. Furthermore, we show the most abundant Bacteroides in sewage is free living, rather than host associated, and specifically found in sewage. Quantitative PCR assays that target organisms specific to sewer pipes offer measures that are independent of the human microbiome for identifying sewage pollution in water.

CALCIUM OXIDE REMEDIATION OF ANTHROPOGENIC CONTAMINATION OF WATER AT THE GBNERR IN MISSISSIPPI

Grand Bay National Estuarine Research Reserve (GBNERR) is an important ecosystem in the Mississippi Gulf Coast. The GBNERR may be a potential source for contamination with anthropogenic bacterial pathogens that may play a significant role in the causation of waterborne human diseases. The objective of this study was to evaluate the interaction of physicochemical and microbiological water quality parameters at the GBNERR, determine quantitative levels and establish the potential for remediation of post-contamination of water and seafood by human fecal pollution from anthropogenic sources at the reserve. Water samples were collected aseptically from Bayous Heron, Cumbest, Point Aux Chenes Bay and Bangs Lake (Pine-O-Pine). Physicochemical parameters were determined using standard protocols. Eight bacteria/parasitic species including Cryptosporidium were concentrated from water samples by membrane filtration. Water samples were tested for the presence of traditional indicator microorganisms including: heterotrophic (HPC), total coliforms (TC), fecal coliforms (FC) and enterococcus (ENT) in CFU/ml concentrations. Mean values of temperature, specific conductivity, dissolved oxygen and pH were within acceptable levels in comparison to MDEQ, USEPA and the USGS standards during the time of investigation. However, the values of turbidity in Grand Bay water exceeded USEPA recommended levels in several occasions during the investigation. Data from this study indicates significant variability (p < 0.0001) in mean bacteria concentrations between sites. The data also indicates significant impact of Calcium oxide treatment in the remediation of post contamination and survival of pathogens from the GBNERR Bayous Heron, Cumbest and Pine-O-Pine when compared with control findings. The interaction of physicochemical and microbiological parameters of water through external chemical manipulation by Calcium oxide may provide utility in the remediation of post-contamination with anthropogenic pathogens such as E. coli, Enterococci, Campylobacter, Vibrio, Giardia and Cryptosporidium. Presence of high numbers of indicator bacteria suggest public health concerns for oyster and shellfish consumers as well as other water contact activities. Hence, control strategies should be developed and implemented to prevent or remediate any future contamination of the GBNERR waters citing the economic impact of such contamination on shell fish fishing activities on the reserve.

Human-Associated Indicator Bacteria and Human-Specific Viruses in Surface Water: A Spatial Assessment with Implications on Fate and Transport

Hydrologic, seasonal, and spatial variability of sewage contamination was studied at six locations within a watershed upstream from water reclamation facility (WRF) effluent to define relative loadings of sewage from different portions of the watershed. Fecal pollution from human sources was spatially quantified by measuring two human-associated indicator bacteria (HIB) and eight human-specific viruses (HSV) at six stream locations in the Menomonee River watershed in Milwaukee, Wisconsin from April 2009 to March 2011. A custom, automated water sampler, which included HSV filtration, was deployed at each location and provided unattended, flow-weighted, large-volume (30-913 L) sampling. In addition, wastewater influent samples were composited over discrete 7 day periods from the two Milwaukee WRFs. Of the 8 HSV, only 3 were detected, present in up to 38% of the 228 stream samples, while at least 1 HSV was detected in all WRF influent samples. HIB occurred more often with significantly higher concentrations than the HSV in stream and WRF influent samples ( p < 0.05). HSV yield calculations showed a loss from upstream to the most-downstream sub-watershed of the Menomonee River, and in contrast, a positive HIB yield from this same sub-watershed emphasizes the complexity in fate and transport properties between HSV and HIB. This study demonstrates the utility of analyzing multiple HSV and HIB to provide a weight-of-evidence approach for assessment of fecal contamination at the watershed level, provides an assessment of relative loadings for prioritizing areas within a watershed, and demonstrates how loadings of HSV and HIB can be inconsistent, inferring potential differences in fate and transport between the two indicators of human fecal presence.

Ecologically informed microbial biomarkers and accurate classification of mixed and unmixed samples in an extensive cross-study of human body sites

BACKGROUND

The identification of body site-specific microbial biomarkers and their use for classification tasks have promising applications in medicine, microbial ecology, and forensics. Previous studies have characterized site-specific microbiota and shown that sample origin can be accurately predicted by microbial content. However, these studies were usually restricted to single datasets with consistent experimental methods and conditions, as well as comparatively small sample numbers. The effects of study-specific biases and statistical power on classification performance and biomarker identification thus remain poorly understood. Furthermore, reliable detection in mixtures of different body sites or with noise from environmental contamination has rarely been investigated thus far. Finally, the impact of ecological associations between microbes on biomarker discovery was usually not considered in previous work.

RESULTS

Here we present the analysis of one of the largest cross-study sequencing datasets of microbial communities from human body sites (15,082 samples from 57 publicly available studies). We show that training a Random Forest Classifier on this aggregated dataset increases prediction performance for body sites by 35% compared to a single-study classifier. Using simulated datasets, we further demonstrate that the source of different microbial contributions in mixtures of different body sites or with soil can be detected starting at 1% of the total microbial community. We apply a biomarker selection method that excludes indirect environmental associations driven by microbe-microbe associations, yielding a parsimonious set of highly predictive taxa including novel biomarkers and excluding many previously reported taxa. We find a considerable fraction of unclassified biomarkers ("microbial dark matter") and observe that negatively associated taxa have a surprisingly high impact on classification performance. We further detect a significant enrichment of rod-shaped, motile, and sporulating taxa for feces biomarkers, consistent with a highly competitive environment.

CONCLUSIONS

Our machine learning model shows strong body site classification performance, both in single-source samples and mixtures, making it promising for tasks requiring high accuracy, such as forensic applications. We report a core set of ecologically informed biomarkers, inferred across a wide range of experimental protocols and conditions, providing the most concise, general, and least biased overview of body site-associated microbes to date.

Fecal source identification using random forest

BACKGROUND

Clostridiales and Bacteroidales are uniquely adapted to the gut environment and have co-evolved with their hosts resulting in convergent microbiome patterns within mammalian species. As a result, members of Clostridiales and Bacteroidales are particularly suitable for identifying sources of fecal contamination in environmental samples. However, a comprehensive evaluation of their predictive power and development of computational approaches is lacking. Given the global public health concern for waterborne disease, accurate identification of fecal pollution sources is essential for effective risk assessment and management. Here, we use random forest algorithm and 16S rRNA gene amplicon sequences assigned to Clostridiales and Bacteroidales to identify common fecal pollution sources. We benchmarked the accuracy, consistency, and sensitivity of our classification approach using fecal, environmental, and artificial in silico generated samples.

RESULTS

Clostridiales and Bacteroidales classifiers were composed mainly of sequences that displayed differential distributions (host-preferred) among sewage, cow, deer, pig, cat, and dog sources. Each classifier correctly identified human and individual animal sources in approximately 90% of the fecal and environmental samples tested. Misclassifications resulted mostly from false-positive identification of cat and dog fecal signatures in host animals not used to build the classifiers, suggesting characterization of additional animals would improve accuracy. Random forest predictions were highly reproducible, reflecting the consistency of the bacterial signatures within each of the animal and sewage sources. Using in silico generated samples, we could detect fecal bacterial signatures when the source dataset accounted for as little as ~ 0.5% of the assemblage, with ~ 0.04% of the sequences matching the classifiers. Finally, we developed a proxy to estimate proportions among sources, which allowed us to determine which sources contribute the most to observed fecal pollution.

CONCLUSION

Random forest classification with 16S rRNA gene amplicons offers a rapid, sensitive, and accurate solution for identifying host microbial signatures to detect human and animal fecal contamination in environmental samples.

Human-Associated Lachnospiraceae Genetic Markers Improve Detection of Fecal Pollution Sources in Urban Waters

The human microbiome contains many organisms that could potentially be used as indicators of human fecal pollution. Here we report the development of two novel human-associated genetic marker assays that target organisms within the family Lachnospiraceae Next-generation sequencing of the V6 region of the 16S rRNA gene from sewage and animal stool samples identified 40 human-associated marker candidates with a robust signal in sewage and low or no occurrence in samples from nonhuman hosts. Two were chosen for quantitative PCR (qPCR) assay development using longer sequences (the V2 to V9 regions) generated from clone libraries. Validation of these assays with these markers, designated Lachno3 and Lachno12, was performed using fecal samples (n = 55) from cat, dog, pig, cow, deer, and gull sources, and the results were compared with those of established host-associated assays (the Lachno2 marker and two human Bacteroides markers, the HB and HF183/BacR287). Each of the established assays cross-reacted with samples from at least one other animal species, including animals common in urban areas. The Lachno3 and Lachno12 markers were primarily human associated; however, the Lachno12 marker demonstrated low levels of cross-reactivity with samples from select cows and nonspecific amplification with samples from pigs. This limitation may not be problematic when testing urban waters. These novel markers resolved ambiguous results from previous investigations of stormwater-impacted waters, demonstrating their utility. The complexity of the microbiome in humans and animals suggests that no single organism is strictly specific to humans, and the use of multiple complementary markers in combination will provide the highest resolution and specificity for assessing fecal pollution sources.IMPORTANCE Traditional fecal indicator bacteria do not distinguish animal from human fecal pollution, which is necessary to evaluate health risks and mitigate pollution sources. Assessing water in urban areas is challenging, since the water can be impacted by sewage, which has a high likelihood of carrying human pathogens, as well as pet and urban wildlife waste. We demonstrate that the Lachno3 and Lachno12 markers are human associated and highly specific for the detection of human fecal pollution from urban sources, offering reliable identification of fecal pollution sources in urban waters.

High levels of sewage contamination released from urban areas after storm events: A quantitative survey with sewage specific bacterial indicators

BACKGROUND

Past studies have demonstrated an association between waterborne disease and heavy precipitation, and climate change is predicted to increase the frequency of these types of intense storm events in some parts of the United States. In this study, we examined the linkage between rainfall and sewage contamination of urban waterways and quantified the amount of sewage released from a major urban area under different hydrologic conditions to identify conditions that increase human risk of exposure to sewage.

METHODS AND FINDINGS

Rain events and low-flow periods were intensively sampled to quantify loads of sewage based on two genetic markers for human-associated indicator bacteria (human Bacteroides and Lachnospiraceae). Samples were collected at a Lake Michigan estuary and at three river locations immediately upstream. Concentrations of indicators were analyzed using quantitative polymerase chain reaction (qPCR), and loads were calculated from streamflow data collected at each location. Human-associated indicators were found during periods of low flow, and loads increased one to two orders of magnitude during rain events from stormwater discharges contaminated with sewage. Combined sewer overflow (CSO) events increased concentrations and loads of human-associated indicators an order of magnitude greater than heavy rainfall events without CSO influence. Human-associated indicator yields (load per km2 of land per day) were related to the degree of urbanization in each watershed. Contamination in surface waters were at levels above the acceptable risk for recreational use. Further, evidence of sewage exfiltration from pipes threatens drinking water distribution systems and source water. While this study clearly demonstrates widespread sewage contamination released from urban areas, a limitation of this study is understanding human exposure and illness rates, which are dependent on multiple factors, and gaps in our knowledge of the ultimate health outcomes.

CONCLUSIONS

With the prediction of more intense rain events in certain regions due to climate change, sewer overflows and contamination from failing sewer infrastructure may increase, resulting in increases in waterborne pathogen burdens in waterways. These findings quantify hazards in exposure pathways from rain events and illustrate the additional stress that climate change may have on urban water systems. This information could be used to prioritize efforts to invest in failing sewer infrastructure and create appropriate goals to address the health concerns posed by sewage contamination from urban areas.

ACETIC ACID REMEDIATION OF ANTHROPOGENIC CONTAMINATION OF WATER AT THE GBNERR IN MISSISSIPPI

Grand Bay National Estuarine Research Reserve (GBNERR) is an important ecosystem in the Mississippi Gulf Coast. The GBNERR may be a potential source for contamination with anthropogenic bacterial pathogens that may play a significant role in the causation of waterborne human diseases. The objective of this study was to evaluate the interaction of physicochemical and microbiological water quality parameters at the GBNERR to determine quantitative levels and establish the potential for remediation of post-contamination of water and seafood by human fecal pollution from anthropogenic sources at the reserve. Water samples were collected aseptically from Bayous Heron, Cumbest, Point Aux Chenes Bay and Bangs Lake (Pine-O-Pine). Physicochemical parameters were determined using standard protocols. Eight bacterial species including Campylobacter were concentrated from water samples by membrane filtration. Water samples were tested for the presence of traditional indicator microorganisms including: heterotrophic (HPC), total coliforms (TC), fecal coliforms (FC), and enterococcus (ENT) in CFU/ml concentrations. Mean values of temperature, specific conductivity, dissolved oxygen, and pH were within acceptable levels in comparison to MDEQ, USEPA, and the USGS standards during the time of investigation. However, the values of turbidity in Grand Bay water exceeded USEPA recommended levels in several occasions during the investigation. Data from this study indicates significant variability (p < 0.0001) in mean bacteria concentrations between sites. The data also indicates significant impact of acetic acid treatment in the remediation of post contamination and survival of pathogens from the GBNERR Bayous Heron, Cumbest, and Pine-O-Pine when compared with control findings. The interaction of physicochemical and microbiological parameters of water through external chemical manipulation by acetic acid may provide utility in the remediation of post-contamination with anthropogenic pathogens such as E. coli, Enterococci, Campylobacter, Vibrio, Giardia, and Cryptosporidium. Presence of high numbers of indicator bacteria suggests public health concerns for oyster and shellfish consumers as well as other water contact activities. Hence, control strategies should be developed and implemented to prevent or remediate any future contamination of the GBNERR waters citing the economic impact of such contamination on shellfish fishing activities on the reserve.

Toward Forensic Uses of Microbial Source Tracking

The science of microbial source tracking has allowed researchers and watershed managers to go beyond general indicators of fecal pollution in water such as coliforms and enterococci, and to move toward an understanding of specific contributors to water quality issues. The premise of microbial source tracking is that characteristics of microorganisms that are strongly associated with particular host species can be used to trace fecal pollution to particular animal species (including humans) or groups, e.g., ruminants or birds. Microbial source tracking methods are practiced largely in the realm of research, and none are approved for regulatory uses on a federal level. Their application in the conventional sense of forensics, i.e., to investigate a crime, has been limited, but as some of these methods become standardized and recognized in a regulatory context, they will doubtless play a larger role in applications such as total maximum daily load assessment, investigations of sewage spills, and contamination from agricultural practices.

Sewage loading and microbial risk in urban waters of the Great Lakes

Despite modern sewer system infrastructure, the release of sewage from deteriorating pipes and sewer overflows is a major water pollution problem in US cities, particularly in coastal watersheds that are highly developed with large human populations. We quantified fecal pollution sources and loads entering Lake Michigan from a large watershed of mixed land use using host-associated indicators. Wastewater treatment plant influent had stable concentrations of human Bacteroides and human Lachnospiraceae with geometric mean concentrations of 2.77 × 10⁷ and 5.94 × 10⁷ copy number (by quantitative PCR) per 100 ml, respectively. Human-associated indicator levels were four orders of magnitude higher than norovirus concentrations, suggesting that these human-associated bacteria could be sensitive indicators of pathogen risk. Norovirus concentrations in these same samples were used in calculations for quantitative microbial risk assessment. Assuming a typical recreational exposure to untreated sewage in water, concentrations of 7,800 copy number of human Bacteroides per 100 mL or 14,000 copy number of human Lachnospiraceae per 100 mL corresponded to an illness risk of 0.03. These levels were exceeded in estuarine waters during storm events with greater than 5 cm of rainfall. Following overflows from combined sewer systems (which must accommodate both sewage and stormwater), concentrations were 10-fold higher than under rainfall conditions. Automated high frequency sampling allowed for loads of human-associated markers to be determined, which could then be related back to equivalent volumes of untreated sewage that were released. Evidence of sewage contamination decreased as ruminant-associated indicators increased approximately one day post-storm, demonstrating the delayed impact of upstream agricultural sources on the estuary. These results demonstrate that urban areas are a diffuse source of sewage contamination to urban waters and that storm-driven release of sewage, particularly when sewage overflows occur, creates a serious though transient human health risk.

A human fecal contamination score for ranking recreational sites using the HF183/BacR287 quantitative real-time PCR method

Human fecal pollution of recreational waters remains a public health concern worldwide. As a result, there is a growing interest in the application of human-associated fecal source identification quantitative real-time PCR (qPCR) technologies for water quality research and management. However, there are currently no standardized approaches for field implementation and interpretation of qPCR data. In this study, a standardized HF183/BacR287 qPCR method was combined with a water sampling strategy and a novel Bayesian weighted average approach to establish a human fecal contamination score (HFS) that can be used to prioritize sampling sites for remediation based on measured human waste levels. The HFS was then used to investigate 975 study design scenarios utilizing different combinations of sites with varying sampling intensities (daily to once per week) and number of qPCR replicates per sample (2-14 replicates). Findings demonstrate that site prioritization with HFS is feasible and that both sampling intensity and number of qPCR replicates influence reliability of HFS estimates. The novel data analysis strategy presented here provides a prescribed approach for the implementation and interpretation of human-associated HF183/BacR287 qPCR data with the goal of site prioritization based on human fecal pollution levels. In addition, information is provided for future users to customize study designs for optimal HFS performance.

Microbial communities as biosensors for monitoring urban environments

The BE microbiome is a naturally embedded biosensor in urban infrastructure that can be used to monitor environmental quality and human activity. There are many potential opportunities for leveraging BE microbial communities to guide urban design and public health policy.

Are Oligotypes Meaningful Ecological and Phylogenetic Units? A Case Study of Microcystis in Freshwater Lakes

Oligotyping is a computational method used to increase the resolution of marker gene microbiome studies. Although oligotyping can distinguish highly similar sequence variants, the resulting units are not necessarily phylogenetically and ecologically informative due to limitations of the selected marker gene. In this perspective, we examine how oligotyping data is interpreted in recent literature, and we illustrate some of the method’s constraints with a case study of the harmful bloom-forming cyanobacterium Microcystis. We identified three Microcystis oligotypes from a western Lake Erie bacterial community 16S rRNA gene (V4 region) survey that had previously clustered into one OTU. We found the same three oligotypes and two additional sequence variants in 46 Microcystis cultures isolated from Michigan inland lakes spanning a trophic gradient. In Lake Erie, shifts in Microcystis oligotypes corresponded to spatial nutrient gradients and temporal transitions in bloom toxicity. In the cultures, Microcystis oligotypes showed preferential distributions for different trophic states, but genomic data revealed that the oligotypes identified in Lake Erie did not correspond to toxin gene presence. Thus, oligotypes could not be used for inferring toxic ecotypes. Most strikingly, Microcystis oligotypes were not monophyletic. Our study supports the utility of oligotyping for distinguishing sequence types along certain ecological features, while it stresses that 16S rRNA gene sequence types may not reflect ecologically or phylogenetically cohesive populations. Therefore, we recommend that studies employing oligotyping or related tools consider these caveats during data interpretation.

Distribution and Differential Survival of Traditional and Alternative Indicators of Fecal Pollution at Freshwater Beaches

Alternative indicators have been developed that can be used to identify host sources of fecal pollution, yet little is known about how their distribution and fate compare to traditional indicators. Escherichia coli and enterococci were widely distributed at the six beaches studied and were detected in almost 95% of water samples (n = 422) and 100% of sand samples (n = 400). Berm sand contained the largest amount of E. coli (P < 0.01), whereas levels of enterococci were highest in the backshore (P < 0.01). E. coli and enterococci were the lowest in water, using a weight-to-volume comparison. The gull-associated Catellicoccus marimammalium (Gull2) marker was found in over 80% of water samples, regardless of E. coli levels, and in 25% of sand samples. Human-associated Bacteroides (HB) and Lachnospiraceae (Lachno2) were detected in only 2.4% of water samples collected under baseflow and post-rain conditions but produced a robust signal after a combined sewage overflow, despite low E. coli concentrations. Burdens of E. coli and enterococci in water and sand were disproportionately high in relation to alternative indicators when comparing environmental samples to source material. In microcosm studies, Gull2, HB, and Lachno2 quantitative PCR (qPCR) signals were reduced twice as quickly as those from E. coli and enterococci and approximately 20% faster than signals from culturable E. coli High concentrations of alternative indicators in source material illustrated their high sensitivity for the identification of fecal sources; however, differential survival and the potential for long-term persistence of traditional fecal indicators complicate the use of alternative indicator data to account for the levels of E. coli and enterococci in environmental samples.

IMPORTANCE

E. coli and enterococci are general indicators of fecal pollution and may persist in beach sand, making their use problematic for many applications. This study demonstrates that gull fecal pollution is widespread at Great Lakes beaches, whereas human and ruminant contamination is evident only after major rain events. An exploration of sand as a reservoir for indicators found that E. coli was ubiquitous, while gull host markers were detected in only 25% of samples. In situ sand beach microcosms provided decay rate constants for E. coli and enterococci relative to alternative indicators, which establish comparative benchmarks that would be helpful to distinguish recent from past pollution. Overall, alternative indicators are useful for identifying sources and assessing potentially high health risk contamination events; however, beach managers should be cautious in attempting to directly link their detection to the levels of E. coli or enterococci.

Unusual sub-genus associations of faecal Prevotella and Bacteroides with specific dietary patterns

BACKGROUND

Diet has a recognized effect in shaping gut microbiota. Many studies link an increase in Prevotella to high-fibre diet, while Bacteroides abundance is usually associated with the consumption of animal fat and protein-rich diets. Nevertheless, closely related species and strains may harbour different genetic pools; therefore, further studies should aim to understand whether species of the same genus are consistently linked to dietary patterns or equally responsive to diet variations. Here, we used oligotyping of 16S rRNA gene sequencing data to exploit the diversity within Prevotella and Bacteroides genera in faecal samples of omnivore and non-omnivore subjects from a previously studied cohort.

RESULTS

A great heterogeneity was found in oligotype composition. Nevertheless, different oligotypes within the same genus showed distinctive correlation patterns with dietary components and metabolome. We found that some Prevotella oligotypes are significantly associated with the plant-based diet but some are associated with animal-based nutrients, and the same applies to Bacteroides. Therefore, an indiscriminate association of Bacteroidetes genera with specific dietary patterns may lead to an oversimplified vision that does not take into account sub-genus diversity and the different possible responses to dietary components.

CONCLUSIONS

We demonstrated that Prevotella and Bacteroides oligotypes show distinctive correlation patterns with dietary components and metabolome. These results substantiate a current oversimplification of diet-dependent microbe-host associations and highlighted that sub-genus differences must be taken into account when planning gut microbiota modulation for health benefits.

Quantification of human-associated fecal indicators reveal sewage from urban watersheds as a source of pollution to Lake Michigan

Sewage contamination of urban waterways from sewer overflows and failing infrastructure is a major environmental and public health concern. Fecal coliforms (FC) are commonly employed as fecal indicator bacteria, but do not distinguish between human and non-human sources of fecal contamination. Human Bacteroides and human Lachnospiraceae, two genetic markers for human-associated indicator bacteria, were used to identify sewage signals in two urban rivers and the estuary that drains to Lake Michigan. Grab samples were collected from the rivers throughout 2012 and 2013 and hourly samples were collected in the estuary across the hydrograph during summer 2013. Human Bacteroides and human Lachnospiraceae were highly correlated with each other in river samples (Pearson's r = 0.86), with average concentrations at most sites elevated during wet weather. These human indicators were found during baseflow, indicating that sewage contamination is chronic in these waterways. FC are used for determining total maximum daily loads (TMDLs) in management plans; however, FC concentrations alone failed to prioritize river reaches with potential health risks. While 84% of samples with >1000 CFU/100 ml FC had sewage contamination, 52% of samples with moderate (200-1000 CFU/100 ml) and 46% of samples with low (<200 CFU/100 ml) FC levels also had evidence of human sewage. Load calculations in the in the Milwaukee estuary revealed storm-driven sewage contamination varied greatly among events and was highest during an event with a short duration of intense rain. This work demonstrates urban areas have unrecognized sewage inputs that may not be adequately prioritized for remediation by the TMDL process. Further analysis using these approaches could determine relationships between land use, storm characteristics, and other factors that drive sewage contamination in urban waterways.

Data Acceptance Criteria for Standardized Human-Associated Fecal Source Identification Quantitative Real-Time PCR Methods

There is growing interest in the application of human-associated fecal source identification quantitative real-time PCR (qPCR) technologies for water quality management. The transition from a research tool to a standardized protocol requires a high degree of confidence in data quality across laboratories. Data quality is typically determined through a series of specifications that ensure good experimental practice and the absence of bias in the results due to DNA isolation and amplification interferences. However, there is currently a lack of consensus on how best to evaluate and interpret human fecal source identification qPCR experiments. This is, in part, due to the lack of standardized protocols and information on interlaboratory variability under conditions for data acceptance. The aim of this study is to provide users and reviewers with a complete series of conditions for data acceptance derived from a multiple laboratory data set using standardized procedures. To establish these benchmarks, data from HF183/BacR287 and HumM2 human-associated qPCR methods were generated across 14 laboratories. Each laboratory followed a standardized protocol utilizing the same lot of reference DNA materials, DNA isolation kits, amplification reagents, and test samples to generate comparable data. After removal of outliers, a nested analysis of variance (ANOVA) was used to establish proficiency metrics that include lab-to-lab, replicate testing within a lab, and random error for amplification inhibition and sample processing controls. Other data acceptance measurements included extraneous DNA contamination assessments (no-template and extraction blank controls) and calibration model performance (correlation coefficient, amplification efficiency, and lower limit of quantification). To demonstrate the implementation of the proposed standardized protocols and data acceptance criteria, comparable data from two additional laboratories were reviewed. The data acceptance criteria proposed in this study should help scientists, managers, reviewers, and the public evaluate the technical quality of future findings against an established benchmark.

The microbiome of urban waters

More than 50% of the world's population lives in urban centers. As collection basins for landscape activity, urban waters are an interface between human activity and the natural environment. The microbiome of urban waters could provide insight into the impacts of pollution, the presence of human health risks, or the potential for long-term consequences for these ecosystems and the people who depend upon them. An integral part of the urban water cycle is sewer infrastructure. Thousands of miles of pipes line cities as part of wastewater and stormwater systems. As stormwater and sewage are released into natural waterways, traces of human and animal microbiomes reflect the sources and magnitude of fecal pollution and indicate the presence of pollutants, such as nutrients, pathogens, and chemicals. Non-fecal organisms are also released as part of these systems. Runoff from impervious surfaces delivers microbes from soils, plants and the built environment to stormwater systems. Further, urban sewer infrastructure contains its own unique microbial community seemingly adapted to this relatively new artificial habitat. High microbial densities are conveyed via pipes to waterways, and these organisms can be found as an urban microbial signature imprinted on the natural community of rivers and urban coastal waters. The potential consequences of mass releases of non-indigenous microorganisms into natural waters include creation of reservoirs for emerging human pathogens, altered nutrient flows into aquatic food webs, and increased genetic exchange between two distinct gene pools. This review highlights the recent characterization of the microbiome of urban sewer and stormwater infrastructure and its connection to and potential impact upon freshwater systems.