Anthropogenic particle concentrations and fluxes in an urban river are temporally variable and impacted by storm events.

Anthropogenic particles (AP), which include microplastics and other synthetic, semisynthetic, and anthropogenically modified materials, are pollutants of concern in aquatic ecosystems worldwide. Rivers are important conduits and retention sites for AP, and time series data on the movement of these particles in lotic ecosystems are needed to assess the role of rivers in the global AP cycle. Much research assessing AP pollution extrapolates stream loads based on single time point measurements, but lotic ecosystems are highly variable over time (e.g., seasonality and storm events). The accuracy of models describing AP dynamics in rivers is constrained by the limited studies that examine how frequent changes in discharge drive particle retention and transport. This study addressed this knowledge gap by using automated, high-resolution sampling to track AP concentrations and fluxes during multiple storm events in an urban river (Milwaukee River) and comparing these measurements to commonly monitored water quality metrics. AP concentrations and fluxes varied significantly across four storm events, highlighting the temporal variability of AP dynamics. When data from the sampling periods were pooled, there were increases in particle concentration and flux during the early phases of the storms, suggesting that floods may flush AP into the river and/or resuspend particles from the benthic zone. AP flux was closely linked to river discharge, suggesting large loads of AP are delivered downstream during storms. Unexpectedly, AP concentrations were not correlated with other simultaneously measured water quality metrics, including total suspended solids, fecal coliforms, chloride, nitrate, and sulfate, indicating that these metrics cannot be used to estimate AP. These data will contribute to more accurate models of particle dynamics in rivers and global plastic export to oceans. PRACTITIONER POINTS: Anthropogenic particle (AP) concentrations and fluxes in an urban river varied across four storm events. AP concentrations and fluxes were the highest during the early phases of the storms. Storms increased AP transport downstream compared with baseflow. AP concentrations did not correlate with other water quality metrics during storms.

First Report and Characterization of a Plasmid-Encoded blaSFO-1 in a Multi-Drug-Resistant Aeromonas hydrophila Clinical Isolate.

Antibiotic resistance remains one of the most pressing public health issues facing the world today. At the forefront of this battle lies the ever-increasing identification of extended-spectrum beta-lactamases and carbapenemases within human pathogens, conferring resistance towards broad-spectrum and last-resort antimicrobials. This study was prompted due to the identification of a pathogenic Aeromonas hydrophila isolate (strain MAH-4) collected from abdominal fluid, which presented a robust resistance pattern against second-, third-, and fourth-generation cephalosporins, ertapenem, ciprofloxacin, gentamicin, levofloxacin and moxifloxacin, and beta lactam/beta-lactamase inhibitor combinations. Whole genome sequencing was performed and identified a 328 kb plasmid (pMAH4) encoding 10 antibiotic resistance genes, including blaSFO-1, blaTEM-1, and blaOXA-1 of A. hydrophia MAH-4. This is the first report of beta-lactamase SFO-1 within a clinical strain of Aeromonas. Due to the remarkable sequence identity of pMAH4 to plasmids associated with Enterobacterales genera like Klebsiella and the extensive capabilities of Aeromonas for horizontal gene transfer, our identification of a clinical isolate encoding SFO-1 on a plasmid suggests antibiotic resistance gene mobility between Enterobacterales and non-Enterobacterales species.

Impact of corrosion inhibitors on antibiotic resistance, metal resistance, and microbial communities in drinking water.

Corrosion inhibitors, including zinc orthophosphate, sodium orthophosphate, and sodium silicate, are commonly used to prevent the corrosion of drinking water infrastructure. Metals such as zinc are known stressors for antibiotic resistance selection, and phosphates can increase microbial growth in drinking water distribution systems (DWDS). Yet, the influence of corrosion inhibitor type on antimicrobial resistance in DWDS is unknown. Here, we show that sodium silicates can decrease antibiotic resistant bacteria (ARB) and antibiotic-resistance genes (ARGs), while zinc orthophosphate increases ARB and ARGs in source water microbial communities. Based on controlled bench-scale studies, zinc orthophosphate addition significantly increased the abundance of ARB resistant to ciprofloxacin, sulfonamides, trimethoprim, and vancomycin, as well as the genes sul1, qacEΔ1, an indication of resistance to quaternary ammonium compounds, and the integron-integrase gene intI1. In contrast, sodium silicate dosage at 10 mg/L resulted in decreased bacterial growth and antibiotic resistance selection compared to the other corrosion inhibitor additions. Source water collected from the drinking water treatment plant intake pipe resulted in less significant changes in ARB and ARG abundance due to corrosion inhibitor addition compared to source water collected from the pier at the recreational beach. In tandem with the antibiotic resistance shifts, significant microbial community composition changes also occurred. Overall, the corrosion inhibitor sodium silicate resulted in the least selection for antibiotic resistance, which suggests it is the preferred corrosion inhibitor option for minimizing antibiotic resistance proliferation in DWDS. However, the selection of an appropriate corrosion inhibitor must also be appropriate for the water chemistry of the system (e.g., pH, alkalinity) to minimize metal leaching first and foremost and to adhere to the lead and copper rule. IMPORTANCE Antibiotic resistance is a growing public health concern across the globe and was recently labeled the silent pandemic. Scientists aim to identify the source of antibiotic resistance and control points to mitigate the spread of antibiotic resistance. Drinking water is a direct exposure route to humans and contains antibiotic-resistant bacteria and associated resistance genes. Corrosion inhibitors are added to prevent metallic pipes in distribution systems from corroding, and the type of corrosion inhibitor selected could also have implications on antibiotic resistance. Indeed, we found that sodium silicate can minimize selection of antibiotic resistance while phosphate-based corrosion inhibitors can promote antibiotic resistance. These findings indicate that sodium silicate is a preferred corrosion inhibitor choice for mitigation of antibiotic resistance.

One Health and Global Health View of Antimicrobial Susceptibility through the "Eye" of Aeromonas: Systematic Review and Meta-Analysis.

Antimicrobial resistance (AMR) is one of the most pressing public health concerns; therefore, it is imperative to advance our understanding of the factors influencing AMR from Global and One Health perspectives. To address this, Aeromonas populations were identified using 16S rRNA gene libraries among human, agriculture, aquaculture, drinking water, surface water, and wastewater samples, supporting its use as indicator bacteria to study AMR. A systematic review and meta-analysis was then performed from Global and One Health perspectives, including data from 221 articles describing 15 891 isolates from 57 countries. The interconnectedness of different environments was evident as minimal differences were identified between sectors among 21 different antimicrobials. However, resistance to critically important antibiotics (aztreonam and cefepime) was significantly higher among wastewater populations compared with clinical isolates. Additionally, isolates from untreated wastewater typically exhibited increased AMR compared with those from treated wastewater. Furthermore, aquaculture was associated with increased AMR to ciprofloxacin and tetracycline compared with wild-caught seafood. Using the World Health Organization AWaRe classifications, countries with lower consumption of "Access" compared to "Watch" drugs from 2000 to 2015 demonstrated higher AMR levels. The current analysis revealed negative correlations between AMR and anthropogenic factors, such as environmental performance indices and socioeconomic standing. Environmental health and sanitation were two of the environmental factors most strongly correlated with AMR. The current analysis highlights the negative impacts of "Watch" drug overconsumption, anthropogenic activity, absence of wastewater infrastructure, and aquaculture on AMR, thus stressing the need for proper infrastructure and global regulations to combat this growing problem.

An inexpensive, reproducible method to quantify activated sludge foaming potential: Validation through lab-scale studies and year-long full-scale sampling campaign.

Activated sludge is a conventional treatment process for biochemical oxygen demand (BOD) and total suspended solids (TSS) removal at water resource recovery facilities (WRRFs). Foaming events are a common operational issue in activated sludge and can lead to decreased treatment efficiency, maintenance issues, and potential environmental health risks. Stable foaming events are caused by biological and chemical drivers (i.e., microbes and surfactants) during the aeration process. However, foaming events are difficult to predict and quantify. We present an inexpensive and easy-to-use method that can be applied at WRRFs to quantify foaming potential. Subsequently, the method was applied over a year-long full-scale study while data on microbial community composition and functional parameters associated with foaming potential were collected from activated sludge samples at South Shore Water Reclamation Facility (WRF) (Oak Creek, WI). Results from the development of the foaming potential method using linear alkylbenzene sulfonate (LAS) showed that the method was reproducible (relative standard deviation <20%) and able to capture changes in foam-inducing constituents. Using full-scale activated sludge samples, higher relative abundance values for the following genera were associated with foaming events: Zoogloea, Flavobacterium, Variovorax, and Bdellovibrio. This is the first report that Variovorx and Bdellovibrio relative abundance was correlated with foaming events in activated sludge. Furthermore, the foaming potential positively correlated (ρ = 0.24) with soluble total nitrogen. Characterizing foaming events through frequent sampling and monitoring of specific genera and functional parameters may allow for predictions and preemptive mitigation efforts to avoid negative consequences in the future. PRACTITIONER POINTS: A reproducible method to measure foaming potential in activated sludge is available. Genera Zoogloea, Flavobacterium, Variovorax, and Bdellovibrio correlated with foaming events. A year-long sampling campaign of activated sludge measuring foaming potential and microbial community composition was conducted at South Shore Water Reclamation Facility in Oak Creek, WI. More research at other facilities with this method is needed to understand links between microbes and foaming.

Full-Length 16S rRNA Gene Sequences from Raw Sewage Samples Spanning Geographic and Seasonal Gradients in Conveyance Systems across the United States.

Wastewater microbiome research often relies on sequencing of hypervariable regions of 16S rRNA genes, which are difficult to classify at refined taxonomic levels. Here, we introduce a data set of near-full-length 16S rRNA genes from samples designed to capture known geographic and seasonal variations in municipal wastewater microbial communities.

Guts of the Urban Ecosystem: Microbial Ecology of Sewer Infrastructure.

Microbes have inhabited the oceans and soils for millions of years and are uniquely adapted to their habitat. In contrast, sewer infrastructure in modern cities dates back only ~150 years. Sewer pipes transport human waste and provide a view into public health, but the resident organisms that likely modulate these features are relatively unexplored. Here, we show that the bacterial assemblages sequenced from untreated wastewater in 71 U.S. cities were highly coherent at a fine sequence level, suggesting that urban infrastructure separated by great spatial distances can give rise to strikingly similar communities. Within the overall microbial community structure, temperature had a discernible impact on the distribution patterns of closely related amplicon sequence variants, resulting in warm and cold ecotypes. Two bacterial genera were dominant in most cities regardless of their size or geographic location; on average, Arcobacter accounted for 11% and Acinetobacter 10% of the entire community. Metagenomic analysis of six cities revealed these highly abundant resident organisms carry clinically important antibiotic resistant genes blaCTX-M, blaOXA, and blaTEM. In contrast, human fecal bacteria account for only ~13% of the community; therefore, antibiotic resistance gene inputs from human sources to the sewer system could be comparatively small, which will impact measurement capabilities when monitoring human populations using wastewater. With growing awareness of the metabolic potential of microbes within these vast networks of pipes and the ability to examine the health of human populations, it is timely to increase our understanding of the ecology of these systems. IMPORTANCE Sewer infrastructure is a relatively new habitat comprised of thousands of kilometers of pipes beneath cities. These wastewater conveyance systems contain large reservoirs of microbial biomass with a wide range of metabolic potential and are significant reservoirs of antibiotic resistant organisms; however, we lack an adequate understanding of the ecology or activity of these communities beyond wastewater treatment plants. The striking coherence of the sewer microbiome across the United States demonstrates that the sewer environment is highly selective for a particular microbial community composition. Therefore, results from more in-depth studies or proven engineering controls in one system could be extrapolated more broadly. Understanding the complex ecology of sewer infrastructure is critical for not only improving our ability to treat human waste and increasing the sustainability of our cities but also to create scalable and effective sewage microbial observatories, which are inevitable investments of the future to monitor health in human populations.

Chronic exposure to high-density polyethylene microplastic through feeding alters the nutrient metabolism of juvenile yellow perch (Perca flavescens).

Microplastics are emergent contaminants threatening aquatic organisms including aquacultured fish. This study investigated the effects of high-density polyethylene (HDPE, 100 to 125 µm) on yellow perch (Perca flavescens) based on integrative evaluation including growth performance, nutritional status, nutrient metabolism, fish health, and gut microbial community. Five test diets (0, 1, 2, 4, or 8 g HDPE/100 g diet) containing 41% protein and 10.5% lipid were fed to juvenile perch (average body weight, 25.9 ± 0.2 g; n = 15) at a feeding rate of 1.5% to 2.0% body weight daily. The feeding trial was conducted in a flow-through water system for 9 wk with 3 tanks per treatment and 15 yellow perch per tank. No mortality or HDPE accumulation in the fish was found in any treatments. Weight gain and condition factor of fish were not significantly impacted by HDPE (P > 0.05). Compared to the control group, fish fed the 8% HDPE diet had significantly decreased levels of protein and ash (P < 0.05). In response to the increasing levels of HDPE exposure, the hepatosomatic index value, hepatocyte size, and liver glycogen level were increased, but lipid content was reduced in the liver tissues. Compared to the control treatment, fish fed the 8% HDPE diet had significant accumulations of total bile acids and different metabolism pathways such as bile acid biosynthesis, pyruvate metabolism, and carnitine synthesis. Significant enterocyte necrosis was documented in the foregut of fish fed the 2% or 8% HDPE diet; and significant cell sloughing was observed in the midgut and hindgut of fish fed the 8% HDPE diet. Fish fed the 2% HDPE diet harbored different microbiota communities compared to the control fish. This study demonstrates that HDPE ranging from 100 to 125 µm in feed can be evacuated by yellow perch with no impact on growth. However, dietary exposure to HDPE decreased whole fish nutrition quality, altered nutrient metabolism and the intestinal histopathology as well as microbiota community of yellow perch. The results indicate that extended exposure may pose a risk to fish health and jeopardize the nutrition quality of aquacultured end product. This hypothesis remains to be investigated further.

Genome Streamlining, Proteorhodopsin, and Organic Nitrogen Metabolism in Freshwater Nitrifiers.

Microbial nitrification is a critical process governing nitrogen availability in aquatic systems. Freshwater nitrifiers have received little attention, leaving many unanswered questions about their taxonomic distribution, functional potential, and ecological interactions. Here, we reconstructed genomes to infer the metabolism and ecology of free-living picoplanktonic nitrifiers across the Laurentian Great Lakes, a connected series of five of Earth's largest lakes. Surprisingly, ammonia-oxidizing bacteria (AOB) related to Nitrosospira dominated over ammonia-oxidizing archaea (AOA) at nearly all stations, with distinct ecotypes prevailing in the transparent, oligotrophic upper lakes compared to Lakes Erie and Ontario. Unexpectedly, one ecotype of Nitrosospira encodes proteorhodopsin, which could enhance survival under conditions where ammonia oxidation is inhibited or substrate limited. Nitrite-oxidizing bacteria (NOB) "Candidatus Nitrotoga" and Nitrospira fluctuated in dominance, with the latter prevailing in deeper, less-productive basins. Genome reconstructions reveal highly reduced genomes and features consistent with genome streamlining, along with diverse adaptations to sunlight and oxidative stress and widespread capacity for organic nitrogen use. Our findings expand the known functional diversity of nitrifiers and establish their ecological genomics in large lake ecosystems. By elucidating links between microbial biodiversity and biogeochemical cycling, our work also informs ecosystem models of the Laurentian Great Lakes, a critical freshwater resource experiencing rapid environmental change. IMPORTANCE Microorganisms play critical roles in Earth's nitrogen cycle. In lakes, microorganisms called nitrifiers derive energy from reduced nitrogen compounds. In doing so, they transform nitrogen into a form that can ultimately be lost to the atmosphere by a process called denitrification, which helps mitigate nitrogen pollution from fertilizer runoff and sewage. Despite their importance, freshwater nitrifiers are virtually unexplored. To understand their diversity and function, we reconstructed genomes of freshwater nitrifiers across some of Earth's largest freshwater lakes, the Laurentian Great Lakes. We discovered several new species of nitrifiers specialized for clear low-nutrient waters and distinct species in comparatively turbid Lake Erie. Surprisingly, one species may be able to harness light energy by using a protein called proteorhodopsin, despite the fact that nitrifiers typically live in deep dark water. Our work reveals the unique biodiversity of the Great Lakes and fills key gaps in our knowledge of an important microbial group, the nitrifiers.

Shifts in Vaginal Bacterial Community Composition Are Associated With Vaginal Mesh Exposure.

OBJECTIVE: The objective of this study was to evaluate the relationship between vaginal mesh exposure and vaginal bacterial community composition. METHODS: Vaginal swab samples were collected from 13 women undergoing excision of vaginal mesh with vaginal mesh exposure. Samples were collected at the midvagina, site of exposure, and underneath the vaginal epithelium at the exposure. Control samples were collected vaginally during 15 new patient examinations. For all samples, we extracted genomic DNA and polymerase chain reaction amplified and sequenced the 16S rRNA gene V4 region. We tested for differences in the microbiota among control and exposure samples with PERMANOVA tests of beta diversity measures (Morisita-Horn dissimilarity) and Wilcoxon rank sum tests of Lactobacillus distribution. RESULTS: Vaginal bacterial communities in both control and case groups were divided into 2 primary community types, one characterized by Lactobacillus dominance (>50% of community) and the other by low Lactobacillus and a high diversity of vaginal anaerobes. In 10 of 13 case women, bacterial communities were highly similar between the 3 vaginal sites (adonis R2 = 0.86, P = 0.0099). In the 3 women with community divergence, all 3 were characterized by decreased Lactobacillus abundance at the exposure site. Overall, Lactobacillus abundance was lower at the site of mesh exposure and under the epithelium than in the experimental control (W = 137, P = 0.072, r = 0.41; W = 146, P = 0.025, r = 0.50). Common putative pathogenic mesh colonizing bacteria were common (in 51 of 54 samples), but generally not abundant (median relative abundance = 0.014%). CONCLUSIONS: In vaginal mesh exposure cases, a woman is more likely to have a diverse, non-Lactobacillus-dominant community.

Human Fecal Contamination Corresponds to Changes in the Freshwater Bacterial Communities of a Large River Basin.

Microbial water quality is generally monitored by culturable fecal indicator bacteria (FIB), which are intended to signal human health risk due to fecal pollution. However, FIB have limited utility in most urbanized watersheds as they do not discriminate among fecal pollution sources, tend to make up a small fraction of the total microbial community, and do not inform on pollution impacts on the native ecosystem. To move beyond these limitations, we assessed entire bacterial communities and investigated how bacterial diversity relates to traditional ecological and human health-relevant water quality indicators throughout the Milwaukee River Basin. Samples were collected from 16 sites on 5 days during the summer, including both wet and dry weather events, and were processed by 16S rRNA gene amplicon sequencing. Historical water quality at each sampling location, as opposed to upstream land use, was associated significantly with bacterial community alpha diversity. Source partitioning the sequence data was important for determining water quality relationships. Sewage-associated bacterial sequences were detected in all samples, and the relative abundance of sewage sequences was strongly associated with the human Bacteroides fecal marker. From this relationship, we developed a preliminary threshold for human sewage pollution when using bacterial community sequence data. Certain abundant freshwater bacterial sequences were also associated with human fecal pollution, suggesting their possible utility in water quality monitoring. This study sheds light on how bacterial community analysis can be used to supplement current water quality monitoring techniques to better understand interactions between ecological water quality and human health indicators. IMPORTANCE Surface waters in highly developed mixed-use watersheds are frequently impacted by a wide variety of pollutants, leading to a range of impairments that must be monitored and remediated. With advancing technologies, microbial community sequencing may soon become a feasible method for routine evaluation of the ecological quality and human health risk of a water body. In this study, we partnered with a local citizen science organization to evaluate the utility of microbial community sequencing for identifying pollution sources and ecological impairments in a large mixed-use watershed. We show that changes in microbial community diversity and composition are indicative of both long-term ecological impairments and short-term fecal pollution impacts. By source partitioning the sequence data, we also estimate a threshold target for human sewage pollution, which may be useful as a starting point for future development of sequencing-based water quality monitoring techniques.

Urban wastewater bacterial communities assemble into seasonal steady states.

BACKGROUND: Microorganisms in urban sanitary sewers exhibit community properties that suggest sewers are a novel ecosystem. Sewer microorganisms present both an opportunity as a control point for wastewater treatment and a risk to human health. If treatment processes are to be improved and health risks quantified, then it is necessary to understand microbial distributions and dynamics within this community. Here, we use 16S rRNA gene sequencing to characterize raw influent wastewater bacterial communities in a 5-year time series from two wastewater treatment plants in Milwaukee, WI; influent wastewater from 77 treatment plants across the USA; and wastewater in 12 Milwaukee residential sewers. RESULTS: In Milwaukee, we find that in transit from residences to treatment plants, the human bacterial component of wastewater decreases in proportion and exhibits stochastic temporal variation. In contrast, the resident sewer community increases in abundance during transit and cycles seasonally according to changes in wastewater temperature. The result is a bacterial community that assembles into two distinct community states each year according to the extremes in wastewater temperature. Wastewater bacterial communities from other northern US cities follow temporal trends that mirror those in Milwaukee, but southern US cities have distinct community compositions and differ in their seasonal patterns. CONCLUSIONS: Our findings provide evidence that environmental conditions associated with seasonal change and climatic differences related to geography predictably structure the bacterial communities residing in below-ground sewer pipes. Video abstract.

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.

Microbial communities of the Laurentian Great Lakes reflect connectivity and local biogeochemistry.

The Laurentian Great Lakes are a vast, interconnected freshwater system spanning strong physicochemical gradients, thus constituting a powerful natural laboratory for addressing fundamental questions about microbial ecology and evolution. We present a comparative analysis of pelagic microbial communities across all five Laurentian Great Lakes, focusing on Bacterial and Archaeal picoplankton characterized via 16S rRNA amplicon sequencing. We collected samples throughout the water column from the major basins of each lake in spring and summer over 2 years. Two oligotypes, classified as LD12 (Alphaproteobacteria) and acI-B1 (Actinobacteria), were among the most abundant in every sample. At the same time, microbial communities showed distinct patterns with depth during summer stratification. Deep hypolimnion samples were frequently dominated by a Chloroflexi oligotype that reached up to 19% relative abundance. Stratified surface communities differed between the colder, less productive upper lakes (Superior, Michigan, Huron) and warmer, more productive lower lakes (Erie, Ontario), in part due to an Actinobacteria oligotype (acI-C2) that averaged 7.7% of sequences in the lower lakes but <0.2% in the upper lakes. Together, our findings suggest that both hydrologic connectivity and local selective pressures shape microbial communities in the Great Lakes and establish a framework for future investigations.

Component Microenvironments and System Biogeography Structure Microorganism Distributions in Recirculating Aquaculture and Aquaponic Systems.

Flowthrough and pond aquaculture system microbiome management practices aim to mitigate fish disease and stress. However, the operational success of recirculating aquaculture systems (RAS) depends directly on system microbial community activities. In RAS, each component environment is engineered for a specific microbial niche for waste management, as the water continuously flowing through the system must be processed before returning to the rearing tank. In this study, we compared waste management component microbiomes (rearing tank water, pH correction tank, solid-waste clarifier, biofilter, and degassing tower) within a commercial-scale freshwater RAS by high-throughput 16S rRNA gene sequencing. To assess consistency among freshwater RAS microbiomes, we also compared the microbial community compositions of six aquaculture and aquaponic farms. Community assemblages reflected site and source water relationships, and the presence of a hydroponic subsystem was a major community determinant. In contrast to the facility-specific community composition, some sequence variants, mainly classified into Flavobacterium, Cetobacterium, the family Sphingomonadaceae, and nitrifying guilds of ammonia-oxidizing archaea and Nitrospira, were common across all facilities. The findings of this study suggest that, independently of system design, core taxa exist across RAS rearing similar fish species but that system design informs the individual aquatic microbiome assemblages. Future RAS design would benefit from understanding the roles of these core taxa and then capitalizing on their activities to further reduce system waste/added operational controls.IMPORTANCE Recirculating aquaculture systems (RAS) are agroecosystems for intensive on-land cultivation of products of fisheries. Practitioners that incorporate edible plant production into RAS refer to these facilities as aquaponic systems (AP). RAS have the potential to offset declining production levels of wild global fisheries while reducing waste and product distance to market, but system optimization is needed to reduce costs. Both RAS and AP rely on microbial consortia for maintaining water quality and promoting fish/plant health, but little is known about the microorganisms actually present. This lack of knowledge prevents optimization of designs and operational controls to target the growth of beneficial microbial species or consortia. The significance of our research is in identifying the common microorganisms that inhabit production RAS and AP and the operational factors that influence which microorganisms colonize and become abundant. Identifying these organisms is a first step toward advanced control of microbial activities that improve reproducibility and reduce costs.

The flux and impact of wastewater infrastructure microorganisms on human and ecosystem health.

Wastewater infrastructure is designed, in part, to remove microorganisms. However, many microorganisms are able to colonize infrastructure and resist treatment, resulting in an enormous flux of microorganisms to urban adjacent waters. These urban-associated microorganisms are discharged through three primary routes 1) failing infrastructure, 2) stormwater, and 3) treated wastewater effluent. Bacterial load estimates indicate failing infrastructure should be considered an equivalent source of microbial pollution as the other routes, but overall discharges are not well parameterized. More sophisticated methods, such as machine learning algorithms and microbiome characterization, are now used to track urban-derived microorganisms, including targets beyond fecal indicators, but development of methods to quantify the impact of these microbes/genes on human and ecosystem health is needed.

Reevaluating the Salty Divide: Phylogenetic Specificity of Transitions between Marine and Freshwater Systems.

Marine and freshwater microbial communities are phylogenetically distinct, and transitions between habitat types are thought to be infrequent. We compared the phylogenetic diversity of marine and freshwater microorganisms and identified specific lineages exhibiting notably high or low similarity between marine and freshwater ecosystems using a meta-analysis of 16S rRNA gene tag-sequencing data sets. As expected, marine and freshwater microbial communities differed in the relative abundance of major phyla and contained habitat-specific lineages. At the same time, and contrary to expectations, many shared taxa were observed in both habitats. Based on several metrics, we found that Gammaproteobacteria, Alphaproteobacteria, Bacteroidetes, and Betaproteobacteria contained the highest number of closely related marine and freshwater sequences, suggesting comparatively recent habitat transitions in these groups. Using the abundant alphaproteobacterial group SAR11 as an example, we found evidence that new lineages, beyond the recognized LD12 clade, are detected in freshwater at low but reproducible abundances; this evidence extends beyond the 16S rRNA locus to core genes throughout the genome. Our results suggest that shared taxa are numerous, but tend to occur sporadically and at low relative abundance in one habitat type, leading to an underestimation of transition frequency between marine and freshwater habitats. Rare taxa with abundances near or below detection, including lineages that appear to have crossed the salty divide relatively recently, may possess adaptations enabling them to exploit opportunities for niche expansion when environments are disturbed or conditions change. IMPORTANCE The distribution of microbial diversity across environments yields insight into processes that create and maintain this diversity as well as potential to infer how communities will respond to future environmental changes. We integrated data sets from dozens of freshwater lake and marine samples to compare diversity across open water habitats differing in salinity. Our novel combination of sequence-based approaches revealed lineages that likely experienced a recent transition across habitat types. These taxa are promising targets for studying physiological constraints on salinity tolerance. Our findings contribute to understanding the ecological and evolutionary controls on microbial distributions, and open up new questions regarding the plasticity and adaptability of particular lineages.

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.

TaxAss: Leveraging a Custom Freshwater Database Achieves Fine-Scale Taxonomic Resolution.

Taxonomy assignment of freshwater microbial communities is limited by the minimally curated phylogenies used for large taxonomy databases. Here we introduce TaxAss, a taxonomy assignment workflow that classifies 16S rRNA gene amplicon data using two taxonomy reference databases: a large comprehensive database and a small ecosystem-specific database rigorously curated by scientists within a field. We applied TaxAss to five different freshwater data sets using the comprehensive SILVA database and the freshwater-specific FreshTrain database. TaxAss increased the percentage of the data set classified compared to using only SILVA, especially at fine-resolution family to species taxon levels, while across the freshwater test data sets classifications increased by as much as 11 to 40% of total reads. A similar increase in classifications was not observed in a control mouse gut data set, which was not expected to contain freshwater bacteria. TaxAss also maintained taxonomic richness compared to using only the FreshTrain across all taxon levels from phylum to species. Without TaxAss, most organisms not represented in the FreshTrain were unclassified, but at fine taxon levels, incorrect classifications became significant. We validated TaxAss using simulated amplicon data derived from full-length clone libraries and found that 96 to 99% of test sequences were correctly classified at fine resolution. TaxAss splits a data set's sequences into two groups based on their percent identity to reference sequences in the ecosystem-specific database. Sequences with high similarity to sequences in the ecosystem-specific database are classified using that database, and the others are classified using the comprehensive database. TaxAss is free and open source and is available at https://www.github.com/McMahonLab/TaxAssIMPORTANCE Microbial communities drive ecosystem processes, but microbial community composition analyses using 16S rRNA gene amplicon data sets are limited by the lack of fine-resolution taxonomy classifications. Coarse taxonomic groupings at the phylum, class, and order levels lump ecologically distinct organisms together. To avoid this, many researchers define operational taxonomic units (OTUs) based on clustered sequences, sequence variants, or unique sequences. These fine-resolution groupings are more ecologically relevant, but OTU definitions are data set dependent and cannot be compared between data sets. Microbial ecologists studying freshwater have curated a small, ecosystem-specific taxonomy database to provide consistent and up-to-date terminology. We created TaxAss, a workflow that leverages this database to assign taxonomy. We found that TaxAss improves fine-resolution taxonomic classifications (family, genus, and species). Fine taxonomic groupings are more ecologically relevant, so they provide an alternative to OTU-based analyses that is consistent and comparable between data sets.