Patterns of variation in diversity of the Mississippi river microbiome over 1,300 kilometers

Spatio-temporal dynamics of bacterial community composition in a Western European watershed, the Meuse River watershed

This study aimed to identify factors influencing bacterial diversity in the Meuse River watershed by analyzing 42 locations sampled in spring and summer 2019, combined with biweekly sampling of one mid-stream location for a year. Bacterial community composition (BCC) was assessed in the small (SF; <5 µm) and large fractions (LF; ≥5 µm,), alongside physico-chemical parameters. LF consistently exhibited greater alpha diversity than SF. During the spatial campaigns, alpha diversity increased downstream in spring with high discharge, and BCC differed significantly between headwaters and the main river. Along this axis, several genera, Flavobacterium, Limnohabitans, and Aquirufa stood out as indicators of good water quality. Rhodoferax, another taxon indicative of good water quality, prevailed in the headwaters and during winter. In contrast, two cyanobacteria genera indicators of poor river quality, Microcystis PCC 7914 and Cyanobium PCC 6307, peaked in summer. BCC in spring and summer temporal samples aligned with spatial ones, while winter and autumn samples had distinct BCC. Finally, season, temperature, and distance from river mouth were the main driving parameters of beta diversity, outweighing the effect of fraction size on the BCC. These findings reinforce the notion that local conditions exert significant influence on bacterial communities in rivers.

Metagenomic Analysis of Surface Waters and Wastewater in the Colombian Andean Highlands: Implications for Health and Disease

Urban water bodies serve as critical reservoirs of microbial diversity, with major implications for public health and environmental quality. This study aimed to characterize the microbial diversity of surface waters and wastewater from the Pasto River in the Colombian Andean Highlands, offering insights that may support water quality monitoring efforts. Sampling was conducted at three river sites and one wastewater location. Standard physicochemical and microbiological analyses were performed, including real-time PCR to detect protozoan pathogens Giardia spp. and Cryptosporidium spp. Metagenomic sequencing provided an in-depth taxonomic and functional profile of microbial communities through two complementary approaches: (i) read-based analysis to identify abundant families and species, both pathogenic and beneficial, and (ii) detection of health-related molecular markers, including antimicrobial resistance markers and virulence factors. Physicochemical analyses showed distinct profiles between wastewater and surface water, with wastewater exhibiting elevated levels of suspended solids (113.6 mg/L), biochemical oxygen demand (BOD, 311.2 mg/L), and chemical oxygen demand (COD, 426.7 mg/L). Real-time PCR detected Giardia spp. DNA in 75% (76/102) of the samples and Cryptosporidium spp. DNA in 94% (96/102) of samples. The metagenomic read-based profiling identified Aeromonas media as a prevalent pathogen and Polaromonas naphthalenivorans as a potential biodegradative agent. The metagenomic assembly produced 270 high-quality genomes, revealing 16 bacterial species (e. g., Acinetobacter johnsonii and Megamonas funiformis) that provided insights into fecal contaminants and native aquatic microbes. Functional profiling further revealed a high prevalence of antimicrobial resistance markers, particularly for tetracyclines, aminoglycosides, and macrolides, with the highest abundance found in wastewater samples. Additionally, virulence factors were notably present in Zoogloea ramigera. The findings underscore the value of metagenomic profiling as a comprehensive tool for water quality monitoring, facilitating the detection of pathogens, beneficial species, and molecular markers indicative of potential health risks. This approach supports continuous monitoring efforts, offering actionable data for water management strategies to safeguard public health and maintain ecological integrity.

A functional microbiome catalogue crowdsourced from North American rivers

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires knowledge of the spatial drivers of river microbiomes. However, understanding of the core microbial processes governing river biogeochemistry is hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we used a community science effort to accelerate the sampling, sequencing and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb profiles the identity, distribution, function and expression of microbial genomes across river surface waters covering 90% of United States watersheds. Specifically, GROWdb encompasses microbial lineages from 27 phyla, including novel members from 10 families and 128 genera, and defines the core river microbiome at the genome level. GROWdb analyses coupled to extensive geospatial information reveals local and regional drivers of microbial community structuring, while also presenting foundational hypotheses about ecosystem function. Building on the previously conceived River Continuum Concept1, we layer on microbial functional trait expression, which suggests that the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures2,3, so that it can be widely accessed across disciplines for watershed predictive modelling and microbiome-based management practices.

Comparison of Yamuna (India) and Mississippi River (United States of America) bacterial communities reveals greater diversity below the Yamunotri Glacier

The Yamuna River in India and the Mississippi River in the United States hold significant commercial, cultural, and ecological importance. This preliminary survey compares the bacterial communities sampled in surface waters at 11 sites (Yamuna headwaters, Mississippi headwaters, Yamuna River Yamunotri Town, Mississippi River at Winona, Tons River, Yamuna River at Paonta Sahib, Yamuna River Delhi-1, Yamuna River Delhi-2, Yamuna River before Sangam, Sangam, Ganga River before Sangam). Bacterial 16S rDNA analyses demonstrate dominance of Proteobacteria and Bacteroidetes phyla. Actinobacteria were also dominant at sites near Sangam in India and sites in Minnesota. A dominance of Epsilonbacteraeota were found in Delhi, India. Principal component analysis (PCA) using unique operational taxonomic units (OTUs) resulted in the identification of 3 groups that included the Yamuna River locations in Delhi (Delhi locations), Yamuna headwaters and Yamuna River at Yamunotri (Yamuna River locations below the Glacier) and Mississippi, Ganga, Tons, and other Yamuna River locations. Diversity indices were significantly higher at the Yamuna River locations below the Glacier (Simpson D = 0.986 and Shannon H = 5.06) as compared (p value <0.001) to the Delhi locations (D = 0.951 and H = 4.23) and as compared (p value < 0.001) to Mississippi, Ganga, Tons, and other Yamuna River locations (D = 0.943 and H = 3.96). To our knowledge, this is the first survey to compare Mississippi and Yamuna River bacterial communities. We demonstrate higher diversity in the bacterial communities below the Yamunotri glacier in India.

Flow cytometric assessments of metabolic activity in bacterial assemblages provide insight into ecosystem condition along the Buffalo National River, Arkansas

The Buffalo National River (BNR), on karst terrain in Arkansas, is considered an extraordinary water resource. Water collected in Spring 2017 along BNR was metagenomically analyzed using 16S rDNA, and for 17 months (5/2017-11/2018), bacterial responses were measured in relation to nutrients sampled along a stretch of BNR near a concentrated animal feed operation (CAFO) on Big Creek. Because cell count and esterase activity can increase proportionally with organic enrichment, they were hypothesized to be elevated near the CAFO. Counts (colony forming units; CFUs) were different among sites for 73 % of the months; Big Creek generated highest CFUs 27 % of the time, with the closest downstream site at 13.3 %. Esterase activity was different among sites 94 % of the time, with Big Creek exhibiting lowest activity 71 % of the time. Over the months, activity was similar across sites at ~70 % active, except at Big Creek (56 %). The α-diversity of BNR microbial consortia near a wastewater treatment plant (WWTP) and the CAFO was related to distance from the WWTP and CAFO. The inverse relationship between high CFUs and low esterase activity at Big Creek (r = -0.71) actuated in vitro exposures of bacteria to organic wastewater contaminants (OWC) previously identified in the watershed. Exponential-phase Escherichia coli (stock strain), Streptococcus suis (avirulent, from swine), and S. dysgalactiae (virulent, from silver carp, Hypophthalmichthys molitrix) were incubated with atrazine, pharmaceuticals (17 α-ethynylestradiol and trenbolone), and antimicrobials (tylosin and butylparaben). Bacteria were differentially responsive. Activity varied with exposure time and OWC type, but not concentration; atrazine decreased it most. Taken together - the metagenomic taxonomic similarities along BNR, slightly higher bacterial growth and lower bacterial esterase at the CAFO, and the lab exposures of bacterial strains showing that OWC altered metabolism - the results indicated that bioactive OWC entering the watershed can strongly influence microbial processes in the aquatic ecosystem.

Inferring microbial community assembly in an urban river basin through geo-multi-omics and phylogenetic bin-based null-model analysis of surface water

Understanding the community assembly process is a central issue in microbial ecology. In this study, we analyzed the community assembly of particle-associated (PA) and free-living (FL) surface water microbiomes in 54 sites from the headstream to the river mouth of an urban river in Japan, the river basin of which has the highest human population density in the country. Analyses were conducted from two perspectives: (1) analysis of deterministic processes considering only environmental factors using a geo-multi-omics dataset and (2) analysis of deterministic and stochastic processes to estimate the contributions of heterogeneous selection (HeS), homogeneous selection (HoS), dispersal limitation (DL), homogenizing dispersal (HD), and drift (DR) as community assembly processes using a phylogenetic bin-based null model. The variation in microbiomes was successfully explained from a deterministic perspective by environmental factors, such as organic matter-related, nitrogen metabolism, and salinity-related parameters, using multivariate statistical analysis, network analysis, and habitat prediction. In addition, we demonstrated the dominance of stochastic processes (DL, HD, and DR) over deterministic processes (HeS and HoS) in community assembly from both deterministic and stochastic perspectives. Our analysis revealed that as the distance between two sites increased, the effect of HoS sharply decreased while the effect of HeS increased, particularly between upstream and estuary sites, indicating that the salinity gradient could potentially enhance the contribution of HeS to community assembly. Our study highlights the importance of both stochastic and deterministic processes in community assembly of PA and FL surface water microbiomes in urban riverine ecosystems.

A functional microbiome catalog crowdsourced from North American rivers

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial processes governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling, sequencing, and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. Specifically, GROWdb encompasses 1,469 microbial species from 27 phyla, including novel lineages from 10 families and 128 genera, and defines the core river microbiome for the first time at genome level. GROWdb analyses coupled to extensive geospatial information revealed local and regional drivers of microbial community structuring, while also presenting a myriad of foundational hypotheses about ecosystem function. Building upon the previously conceived River Continuum Concept 1 , we layer on microbial functional trait expression, which suggests the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures 2, 3 so that it can be widely accessed across disciplines for watershed predictive modeling and microbiome-based management practices.

Local-Scale Damming Impact on the Planktonic Bacterial and Eukaryotic Assemblages in the upper Yangtze River

Dam construction and impoundment cause discontinuities in the natural biophysical gradients in rivers. These discontinuities may alter distinctive habitats and different microbial community assembly mechanisms upstream and downstream of dams, which reflect the potential impacts of damming on riverine aquatic ecosystems. In this study, we investigated the planktonic microbial assemblages of three large dams in the upper Yangtze River by using high-throughput sequencing. The results revealed that the alpha diversity indexes increased downstream of the dams. In addition, more eukaryotic ASVs solely occurred downstream of the dams, which indicated that a large proportion of eukaryotes appeared downstream of the dams. The nonmetric multidimensional scaling analysis indicated that there was no obvious geographic clustering of the planktonic microbial assemblages among the different locations or among the different dams. However, the dam barriers changed dam-related variables (maximum dam height and water level) and local environmental variables (water temperature, DOC, etc.) that could possibly affect the assembly of the planktonic microbial communities that are closest to the dams. A co-occurrence network analysis demonstrated that the keystone taxa of the planktonic bacteria and eukaryotes decreased downstream of the dams. In particular, the keystone taxa of the eukaryotes disappeared downstream of the dams. The robustness analysis indicated that the natural connectivity of the microbial networks decreased more rapidly upstream of the dams, and the downstream eukaryotic network was more stable. In conclusion, damming has a greater impact on planktonic eukaryotes than on bacteria in near-dam areas, and planktonic microbial assemblages were more susceptible to the environmental changes. Our study provides a better understanding of the ecological effects of river damming.

Conditional Forest Models Built Using Metagenomic Data Accurately Predicted Salmonella Contamination in Northeastern Streams

The use of water contaminated with Salmonella for produce production contributes to foodborne disease burden. To reduce human health risks, there is a need for novel, targeted approaches for assessing the pathogen status of agricultural water. We investigated the utility of water microbiome data for predicting Salmonella contamination of streams used to source water for produce production. Grab samples were collected from 60 New York streams in 2018 and tested for Salmonella. Separately, DNA was extracted from the samples and used for Illumina shotgun metagenomic sequencing. Reads were trimmed and used to assign taxonomy with Kraken2. Conditional forest (CF), regularized random forest (RRF), and support vector machine (SVM) models were implemented to predict Salmonella contamination. Model performance was assessed using 10-fold cross-validation repeated 10 times to quantify area under the curve (AUC) and Kappa score. CF models outperformed the other two algorithms based on AUC (0.86, CF; 0.81, RRF; 0.65, SVM) and Kappa score (0.53, CF; 0.41, RRF; 0.12, SVM). The taxa that were most informative for accurately predicting Salmonella contamination based on CF were compared to taxa identified by ALDEx2 as being differentially abundant between Salmonella-positive and -negative samples. CF and differential abundance tests both identified Aeromonas salmonicida (variable importance [VI] = 0.012) and Aeromonas sp. strain CA23 (VI = 0.025) as the two most informative taxa for predicting Salmonella contamination. Our findings suggest that microbiome-based models may provide an alternative to or complement existing water monitoring strategies. Similarly, the informative taxa identified in this study warrant further investigation as potential indicators of Salmonella contamination of agricultural water. IMPORTANCE Understanding the associations between surface water microbiome composition and the presence of foodborne pathogens, such as Salmonella, can facilitate the identification of novel indicators of Salmonella contamination. This study assessed the utility of microbiome data and three machine learning algorithms for predicting Salmonella contamination of Northeastern streams. The research reported here both expanded the knowledge on the microbiome composition of surface waters and identified putative novel indicators (i.e., Aeromonas species) for Salmonella in Northeastern streams. These putative indicators warrant further research to assess whether they are consistent indicators of Salmonella contamination across regions, waterways, and years not represented in the data set used in this study. Validated indicators identified using microbiome data may be used as targets in the development of rapid (e.g., PCR-based) detection assays for the assessment of microbial safety of agricultural surface waters.

Microbiome response in an urban river system is dominated by seasonality over wastewater treatment upgrades

BACKGROUND

Microorganisms such as coliform-forming bacteria are commonly used to assess freshwater quality for drinking and recreational use. However, such organisms do not exist in isolation; they exist within the context of dynamic, interactive microbial communities which vary through space and time. Elucidating spatiotemporal microbial dynamics is imperative for discriminating robust community changes from ephemeral ecological trends, and for improving our overall understanding of the relationship between microbial communities and ecosystem health. We conducted a seven-year (2013-2019) microbial time-series investigation in the Chicago Area Waterways (CAWS): an urban river system which, in 2016, experienced substantial upgrades to disinfection processes at two wastewater reclamation plants (WRPs) that discharge into the CAWS and improved stormwater capture, to improve river water quality and reduce flooding. Using culture-independent and culture-dependent approaches, we compared CAWS microbial ecology before and after the intervention.

RESULTS

Examinations of time-resolved beta distances between WRP-adjacent sites showed that community similarity measures were often consistent with the spatial orientation of site locations to one another and to the WRP outfalls. Fecal coliform results suggested that upgrades reduced coliform-associated bacteria in the effluent and the downstream river community. However, examinations of whole community changes through time suggest that the upgrades did little to affect overall riverine community dynamics, which instead were overwhelmingly driven by yearly patterns consistent with seasonality.

CONCLUSIONS

This study presents a systematic effort to combine 16S rRNA gene amplicon sequencing with traditional culture-based methods to evaluate the influence of treatment innovations and systems upgrades on the microbiome of the Chicago Area Waterway System, representing the longest and most comprehensive characterization of the microbiome of an urban waterway yet attempted. We found that the systems upgrades were successful in improving specific water quality measures immediately downstream of wastewater outflows. Additionally, we found that the implementation of the water quality improvement measures to the river system did not disrupt the overall dynamics of the downstream microbial community, which remained heavily influenced by seasonal trends. Such results emphasize the dynamic nature of microbiomes in open environmental systems such as the CAWS, but also suggest that the seasonal oscillations remain consistent even when perturbed.

Metagenomic mapping of cyanobacteria and potential cyanotoxin producing taxa in large rivers of the United States

Cyanobacteria and cyanotoxin producing cyanobacterial blooms are a trending focus of current research. Many studies focus on bloom events in lentic environments such as lakes or ponds. Comparatively few studies have explored lotic environments and fewer still have examined the cyanobacterial communities and potential cyanotoxin producers during ambient, non-bloom conditions. Here we used a metagenomics-based approach to profile non-bloom microbial communities and cyanobacteria in 12 major U.S. rivers at multiple time points during the summer months of 2019. Our data show that U.S. rivers possess microbial communities that are taxonomically rich, yet largely consistent across geographic location and time. Within these communities, cyanobacteria often comprise significant portions and frequently include multiple species with known cyanotoxin producing strains. We further characterized these potential cyanotoxin producing taxa by deep sequencing amplicons of the microcystin E (mcyE) gene. We found that rivers containing the highest levels of potential cyanotoxin producing cyanobacteria consistently possess taxa with the genetic potential for cyanotoxin production and that, among these taxa, the predominant genus of origin for the mcyE gene is Microcystis. Combined, these data provide a unique perspective on cyanobacteria and potential cyanotoxin producing taxa that exist in large rivers across the U.S. and can be used to better understand the ambient conditions that may precede bloom events in lotic freshwater ecosystems.

HiLi-chip: A high-throughput library construction chip for comprehensive profiling of environmental microbial communities

Investigating the contribution and associations of environmental microbes to ecological health and human well-being is in great demand with the goal of One Health proposed. To achieve the goal, there is an urgent need for accurate approaches to obtaining a large amount of high-resolution molecular information from various microbes. In this study, we developed a high-throughput library construction chip (HiLi-Chip) for profiling environmental microbial communities and evaluated its performance. The HiLi-Chip showed high conformity with the conventional Pacbio method in terms of α-diversity, community composition of abundant bacteria (>83%), as well as rare taxa (>84%) and human pathogens detection (>67%), indicating its advantages of accuracy, high-throughput, cost-efficiency, and broad practicability. It is suggested that the optimal strategy of the HiLi-Chip was a 2.4 μL PCR mixture per sample (∼2.4 ng DNA) with a 216-sample × 24-replicate format. We have successfully applied the HiLi-Chip to the Jiulongjiang River and identified 51 potential human bacterial pathogens with a total relative abundance of 0.22%. Additionally, under limited nutrients and similar upstream environments, bacteria tended to impose competitive pressures, resulting in a more connected network at the downstream river confluence (RC). Whereas narrow niche breadth of bacteria and upstream environmental heterogeneity probably promoted niche complementary and environment selection leading to fewer links at RC in the midsection of the river. Core bacteria might represent the entire bacterial community and enhance network stability through synergistic interactions with other core bacteria. Collectively, our results demonstrate that the HiLi-Chip is a robust tool for rapid comprehensive profiling of microbial communities in environmental samples and has significant implications for a profound understanding of environmental microbial interactions.

Biogeographical variation in antimicrobial resistance in rivers is influenced by agriculture and is spread through bacteriophages

Antibiotic resistance is currently an extensive medical challenge worldwide, with global numbers increasing steadily. Recent data have highlighted wastewater treatment plants as a reservoir of resistance genes. The impact of these findings for human health can best be summarized using a One Health concept. However, the molecular mechanisms impacting resistance spread have not been carefully evaluated. Bacterial viruses, that is bacteriophages, have recently been shown to be important mediators of bacterial resistance genes in environmental milieus and are transferrable to human pathogens. Herein, we investigated the biogeographical impact on resistance spread through river-borne bacteriophages using amplicon deep sequencing of the microbiota, absolute quantification of resistance genes using ddPCR, and phage induction capacity within wastewater. Microbial biodiversity of the rivers is significantly affected by river site, surrounding milieu and time of sampling. Furthermore, areas of land associated with agriculture had a significantly higher ability to induce bacteriophages carrying antibiotic resistance genes, indicating their impact on resistance spread. It is imperative that we continue to analyse global antibiotic resistance problem from a One Health perspective to gain novel insights into mechanisms of resistance spread.

Size-Fractionated Microbiome Structure in Subarctic Rivers and a Coastal Plume Across DOC and Salinity Gradients

Little is known about the microbial diversity of rivers that flow across the changing subarctic landscape. Using amplicon sequencing (rRNA and rRNA genes) combined with HPLC pigment analysis and physicochemical measurements, we investigated the diversity of two size fractions of planktonic Bacteria, Archaea and microbial eukaryotes along environmental gradients in the Great Whale River (GWR), Canada. This large subarctic river drains an extensive watershed that includes areas of thawing permafrost, and discharges into southeastern Hudson Bay as an extensive plume that gradually mixes with the coastal marine waters. The microbial communities differed by size-fraction (separated with a 3-μm filter), and clustered into three distinct environmental groups: (1) the GWR sites throughout a 150-km sampling transect; (2) the GWR plume in Hudson Bay; and (3) small rivers that flow through degraded permafrost landscapes. There was a downstream increase in taxonomic richness along the GWR, suggesting that sub-catchment inputs influence microbial community structure in the absence of sharp environmental gradients. Microbial community structure shifted across the salinity gradient within the plume, with changes in taxonomic composition and diversity. Rivers flowing through degraded permafrost had distinct physicochemical and microbiome characteristics, with allochthonous dissolved organic carbon explaining part of the variation in community structure. Finally, our analyses of the core microbiome indicated that while a substantial part of all communities consisted of generalists, most taxa had a more limited environmental range and may therefore be sensitive to ongoing change.

Impact of water quality parameters on geosmin levels and geosmin producers in European recirculating aquaculture systems

AIMS

Geosmin is associated with off-flavour problems in recirculating aquaculture systems (RAS) and represents an economic problem for the aquaculture industry. This study aims at investigating factors influencing the composition of the bacterial microbiota, in particular the presence of geosmin producers and the environmental and farming factors favouring geosmin accumulation.

METHODS AND RESULTS

Several water quality parameters were correlated to the composition of the microbiota with special emphasis on the presence of geosmin producers within 26 different RAS from four European countries. Three novel groups of geosmin-producing bacteria were quantified to identify potential correlations with geosmin concentration.

CONCLUSIONS

The microbiome differed significantly between systems. However, phosphate levels, calcium levels and redox potential correlated to geosmin concentration in the water and the presence of the Actinomycetales geosmin-producers but not with the presence of other groups of geosmin-producing bacteria. Oxygen levels and conductivity were found to negatively correlate with geosmin concentration. A large proportion of the detected geosmin producers represented novel taxonomic groups not previously linked with this activity.

SIGNIFICANCE AND IMPACT OF THE STUDY

These results improve our understanding of the diversity of microbiota in RAS and the water quality parameters favouring the populations of geosmin-producing bacteria and the production of geosmin.

An Ohio State Scenic River Shows Elevated Antibiotic Resistance Genes, Including Acinetobacter Tetracycline and Macrolide Resistance, Downstream of Wastewater Treatment Plant Effluent

The entry of antibiotic resistance genes (ARGs) into aquatic systems has been documented for large municipal wastewater treatment plants (WWTPs), but there is less study of the impact of smaller plants that are situated on small rural rivers. We sampled water metagenomes for ARGs and taxa composition from the Kokosing River, a small rural river in Knox County, Ohio, which has been designated an Ohio State Scenic River for retention of natural character. Samples were obtained 1.0 km upstream, 120 m downstream, and 6.4 km downstream from the effluent release of the Mount Vernon WWTP. ARGs were identified in metagenomes using ShortBRED markers from the comprehensive antibiotic resistance database (CARD) screened against UniPROT. Through all seasons, the metagenome just downstream of the WWTP effluent showed a substantial elevation of at least 15 different ARGs, including 6 ARGs commonly associated with Acinetobacter baumannii, such as msrE, mphE (macrolide resistance), and tet(39) (tetracycline resistance). The ARGs most prevalent near the effluent pipe persisted 6.4 km downriver. Using metagenomic phylogenetic analysis (MetaPhlAn2) clade-specific marker genes, the taxa distribution near the effluent showed elevation of reads annotated as Acinetobacter species as well as gut-associated taxa, Bacteroides and Firmicutes. The ARG levels and taxa prevalence showed little dependence on seasonal chlorination of the effluent. Nitrogen and phosphorus were elevated near the effluent pipe but had no consistent correlation with ARG levels. We show that in a rural river microbiome, year-round wastewater effluent substantially elevates ARGs, including those associated with multidrug-resistant A. baumannii.

IMPORTANCE Antibiotic resistance is a growing problem worldwide, with frequent transmission between pathogens and environmental organisms. Rural rivers can support high levels of recreational use by people unaware of inputs from treated wastewater, while wastewater treatment plants (WWTPs) can generate a small but significant portion of flow volume into a river surrounded by forest and agriculture. There is little information on the rural impacts of WWTP effluent on the delivery and transport of antibiotic resistance genes. In our study, the river water proximal to wastewater effluent shows evidence for the influx of multidrug-resistant Acinetobacter baumannii, an opportunistic pathogen of concern for hospitals but also widespread in natural environments. Our work highlights the importance of wastewater effluent in management of environmental antibiotic resistance, even in high quality, rural river systems.

Impact of sample collection on prokaryotic and eukaryotic diversity of niche environments of the oil-sand mining impacted Athabasca River

Microbial communities are an important aspect of overall riverine ecology; however, appreciation of the effects of anthropogenic activities on unique riverine microbial niches, and how the collection of these samples affects the observed diversity and community profile is lacking. We analyzed prokaryotic and eukaryotic communities from surface water, biofilm, suspended load niches along a gradient of oil sands-related contamination in the Athabasca River (Alberta, Canada), with suspended load or particle-associated communities collected either via Kenney Sampler or centrifugation manifold. At the level of phyla, different niche communities were highly similar to one another and across locations. However, there were significant differences in the abundance of specific genera amongst different niches and across sampling locations. A generalized linear model revealed that use of the Kenney Sampler resulted in more diverse bacterial and eukaryotic suspended load community than centrifugal collection, though "suspended load" communities collected by any means remained stably diverse across locations. Though there was influence of water quality parameters on community composition, all sampled sites support diverse bacterial and eukaryotic communities regardless of the degree of contamination, highlighting the need to look beyond ecological diversity as means of assessing ecological perturbations, and consider collecting samples from multiple niche environments.

Aquatic Ecosystems of the Anthropocene: Limnology and Microbial Ecology of Mine Pit Lakes

Mine pit lakes ('pit lakes') are new aquatic ecosystems of the Anthropocene. Potentially hundreds of meters deep, these lakes are prominent in the landscape and in the public consciousness. However, the ecology of pit lakes is underrepresented in the literature. The broad goal of this research was to determine the environmental drivers of pelagic microbe assemblages in Australian coal pit lakes. The overall experimental design was four lakes sampled three times, top and bottom, in 2019. Instrument chains were installed in lakes and measurements of in situ water quality and water samples for metals, metalloids, nutrients and microbe assemblage were collected. Lakes were monomictic and the timing of mixing was influenced by high rainfall events. Water quality and microbial assemblages varied significantly across space and time, and most taxa were rare. Lakes were moderately saline and circumneutral; Archeans were not prevalent. Richness also varied by catchment. Microbial assemblages correlated to environmental variables, and no one variable was consistently significant, spatially or temporally. Study lakes were dominated by 'core' taxa exhibiting temporal turnover likely driven by geography, water quality and interspecific competition, and the presence of water chemistry associated with an artificial aquifer likely influenced microbial community composition. Pit lakes are deceptively complex aquatic ecosystems that host equally complex pelagic microbial communities. This research established links between microbial assemblages and environmental variables in pit lakes and determined core communities; the first steps towards developing a monitoring program using microbes.

Connectivity of bacterial assemblages along the Loa River in the Atacama Desert, Chile

The Loa River is the only perennial artery that crosses the Atacama Desert in northern Chile. It plays an important role in the ecological and economic development of the most water-stressed region, revealing the impact of the mining industry, which exacerbate regional water shortages for many organisms and ecological processes. Despite this, the river system has remained understudied. To our knowledge, this study provides the first effort to attempt to compare the microbial communities at spatial scale along the Loa River, as well as investigate the physicochemical factors that could modulate this important biological component that still remains largely unexplored. The analysis of the spatial bacterial distribution and their interconnections in the water column and sediment samples from eight sites located in three sections along the river catchment (upper, middle and lower) was conducted using 16S rRNA gene-based Illumina MiSeq sequencing. Among a total of 543 ASVs identified at the family level, over 40.5% were cosmopolitan in the river and distributed within a preference pattern by the sediment substrate with 162 unique ASVs, while only 87 were specific to the column water. Bacterial diversity gradually decreased from the headwaters, where the upper section had the largest number of unique families. Distinct groupings of bacterial communities often associated with anthropogenic disturbance, including Burkholderiaceae and Flavobacteriaceae families were predominant in the less-impacted upstream section. Members of the Arcobacteraceae and Marinomonadaceae were prominent in the agriculturally and mining-impacted middle sector while Rhodobacteraceae and Coxiellaceae were most abundant families in downstream sites. Such shifts in the community structure were also related to the influence of salinity, chlorophyll, dissolved oxygen and redox potential. Network analyses corroborated the strong connectivity and modular structure of bacterial communities across this desert river, shedding light on taxonomic relatedness of co-occurring species and highlighting the need for planning the integral conservation of this basin.

The Composition of Microbial Communities in Six Streams, and Its Association With Environmental Conditions, and Foodborne Pathogen Isolation

Surface water used for produce production is a potential source of pre-harvest contamination with foodborne pathogens. Decisions on how to mitigate food safety risks associated with pre-harvest water use currently rely on generic Escherichia coli-based water quality tests, although multiple studies have suggested that E. coli levels are not a suitable indicator of the food safety risks under all relevant environmental conditions. Hence, improved understanding of spatiotemporal variability in surface water microbiota composition is needed to facilitate identification of alternative or supplementary indicators that co-occur with pathogens. To this end, we aimed to characterize the composition of bacterial and fungal communities in the sediment and water fractions of 68 agricultural water samples collected from six New York streams. We investigated potential associations between the composition of microbial communities, environmental factors and Salmonella and/or Listeria monocytogenes isolation. We found significantly different composition of fungal and bacterial communities among sampled streams and among water fractions of collected samples. This indicates that geography and the amount of sediment in a collected water sample may affect its microbial composition, which was further supported by identified associations between the flow rate, turbidity, pH and conductivity, and microbial community composition. Lastly, we identified specific microbial families that were weakly associated with the presence of Salmonella or Listeria monocytogenes, however, further studies on samples from additional streams are needed to assess whether identified families may be used as indicators of pathogen presence.

Timescales of variation in diversity and production of bacterioplankton assemblages in the Lower Mississippi River

Rivers are characterized by rapid and continuous one-way directional fluxes of flowing, aqueous habitat, chemicals, suspended particles, and resident plankton. Therefore, at any particular location in such systems there is the potential for continuous, and possibly abrupt, changes in diversity and metabolic activities of suspended biota. As microorganisms are the principal catalysts of organic matter degradation and nutrient cycling in rivers, examination of their assemblage dynamics is fundamental to understanding system-level biogeochemical patterns and processes. However, there is little known of the dynamics of microbial assemblage composition or production of large rivers along a time interval gradient. We quantified variation in alpha and beta diversity and production of particle-associated and free-living bacterioplankton assemblages collected at a single site on the Lower Mississippi River (LMR), the final segment of the largest river system in North America. Samples were collected at timescales ranging from days to weeks to months up to a year. For both alpha and beta diversity, there were similar patterns of temporal variation in particle-associated and free-living assemblages. Alpha diversity, while always higher on particles, varied as much at a daily as at a monthly timescale. Beta diversity, in contrast, gradually increased with time interval of sampling, peaking between samples collected 180 days apart, before gradually declining between samples collected up to one year apart. The primary environmental driver of the temporal pattern in beta diversity was temperature, followed by dissolved nitrogen and chlorophyll a concentrations. Particle-associated bacterial production corresponded strongly to temperature, while free-living production was much lower and constant over time. We conclude that particle-associated and free-living bacterioplankton assemblages of the LMR vary in richness, composition, and production at distinct timescales in response to differing sets of environmental factors. This is the first temporal longitudinal study of microbial assemblage structure and dynamics in the LMR.

Metagenomic insights to understand transient influence of Yamuna River on taxonomic and functional aspects of bacterial and archaeal communities of River Ganges

River confluences are interesting ecosystems to investigate for their microbial community structure and functional potentials. River Ganges is one of the most important and holy river of India with great mythological history and religious significance. The Yamuna River meets Ganges at the Prayagraj (formerly known as Allahabad), India to form a unique confluence. The influence of Yamuna River on taxonomic and functional aspects of microbiome at this confluence and its downstream, remains unexplored. To unveil this dearth, whole metagenome sequencing of the microbial (bacterial and archaeal) community from the sediment samples of December 2017 sampling expedition was executed using high throughput MinION technology. Results revealed differences in the relative abundance of bacterial and archaeal communities across the confluence. Grouped by the confluence, a higher abundance of Proteobacteria and lower abundance of Bacteroidetes and Firmicutes was observed for Yamuna River (G15Y) and at immediate downstream of confluence of Ganges (G15DS), as compared to the upstream, confluence, and farther downstream of confluence. A similar trend was observed for archaeal communities with a higher abundance of Euryarchaeota in G15Y and G15DS, indicating Yamuna River's influence. Functional gene(s) analysis revealed the influence of Yamuna River on xenobiotic degradation, resistance to toxic compounds, and antibiotic resistance interceded by the autochthonous microbes at the confluence and succeeding downstream locations. Overall, similar taxonomic and functional profiles of microbial communities before confluence (upstream of Ganges) and farther downstream of confluence, suggested a transient influence of Yamuna River. Our study is significant since it may be foundational basis to understand impact of Yamuna River and also rare event of mass bathing on the microbiome of River Ganges. Further investigation would be required to understand, the underlying cause behind the restoration of microbial profiles post-confluence farther zone, to unravel the rejuvenation aspects of this unique ecosystem.

Bacterial community composition shaped by water chemistry and geographic distance in an anthropogenically disturbed river

'Core bacterial communities', bacterial species that are found consistently throughout a river continuum, have previously been identified. However, variations in core and non-core bacterial community structure, as well as the relationships between these communities and water chemistry or geographic distance have not been well studied. Here, we sampled in the entire course of the Le'an River, China, and explored the bacterial community composition at each site using Illumina high-throughput sequencing. The proportion of sequence reads assigned to the core community was ~95% in the upper and middle reaches, gradually decreasing below 90% in the lower reaches. Both the Chao1 richness index and the Shannon diversity index of the bacterial communities were significantly higher in the wet season than in the dry season, and both indices increased slightly from upstream to downstream. The variation in the non-core community was more aggregated from upstream to downstream in the wet season than in the dry season, while the aggregation of the core community was similar between the dry season and the wet season. The proportion of typical freshwater bacterial was significantly higher in the core community than in the non-core community. NO₃^--N was the subset of water chemistry parameters that best explained bacterial community dissimilarities, while 'river length' was the subset of geographic distance parameters that best explained bacterial community dissimilarities. Water chemistry parameters explained more of the variations in the bacterial communities than did geographic distance, especially in the dry season. However, the correlation between water chemistry and bacteria was primarily due to collective allochthonous input (mass effects), not because of any nutritious or toxic effects on bacterial growth competition (species sorting). The greater influence of the mass effects, as compared to species sorting, on bacterial community structure was due to the allochthonous input of bacteria from anthropogenic sources.

PKS-NRPS Enzymology and Structural Biology: Considerations in Protein Production

The structural diversity and complexity of marine natural products have made them a rich and productive source of new bioactive molecules for drug development. The identification of these new compounds has led to extensive study of the protein constituents of the biosynthetic pathways from the producing microbes. Essential processes in the dissection of biosynthesis have been the elucidation of catalytic functions and the determination of 3D structures for enzymes of the polyketide synthases and nonribosomal peptide synthetases that carry out individual reactions. The size and complexity of these proteins present numerous difficulties in the process of going from gene to structure. Here, we review the problems that may be encountered at the various steps of this process and discuss some of the solutions devised in our and other labs for the cloning, production, purification, and structure solution of complex proteins using Escherichia coli as a heterologous host.