One Health Threat of Treated Wastewater Discharge in Urban Ohio Rivers: Implications for Surface Water and Fish Gut Microbiome and Resistome.

Wastewater treatment plants (WWTPs) are thought to be a major disseminating source of antibiotic resistance (AR) to the environment, establishing a crucial connection between human and environmental resistome. The objectives of this study were to determine how wastewater effluents impact microbiome and resistome of freshwater and fish, and identify potential AR-carrying clinically relevant pathogens in these matrices. We analyzed wastewater influent and effluent from four WWTPs in three metropolitan areas of Ohio, USA via shotgun metagenomic sequencing. We also sequenced river water and fish guts from three reaches (upstream, at the WWTP outfall, and downstream). Notably, we observed a decline in microbiome diversity and AR gene abundance from wastewater to the receiving river. We also found significant differences by reach and trophic level (diet) in beta-diversity of the fish gut microbiomes. SourceTracker revealed that 0.443 and 0.248 more of the of the fish gut microbiome was sourced from wastewater effluent in fish from the outfall and downstream locations, respectively, compared to upstream fish. Additionally, AR bacteria of public health concern were annotated in effluent and river water samples, indicating potential concern for human exposure. In summary, our findings show the continued role of wastewater as a significant AR reservoir and underscores the considerable impact of wastewater discharge on aquatic wildlife, which highlights the One Health nature of this issue.

Urban green waste bulking agent is the major source of antimicrobial resistance genes persisted in home compost, not animal manure.

Urban green waste and food waste are often used as bulking agents to prepare home compost in combination with animal manure in urban horticulture and community gardening. Although it is known that antimicrobial resistance genes (ARGs) persist in home compost, their origins have not been determined. In addition, the factors contributing to ARGs persistence remain unclear. In this study, we aim to (i) characterize the changes in the microbiome and antimicrobial resistome during the composting process of home compost using metagenomics shotgun sequencing, (ii) identify the source of the ARGs persisted in home compost using SourceTracker, and (iii) elucidate the collective effect of compost microbiome and environmental factors, including the physicochemical properties and antibiotics concentration of home compost, in contributing to ARG persistence using Procrustes analysis, co-occurrence network analysis, variation partitioning analysis, and structural equation modeling. SourceTracker analysis indicated that urban green waste bulking agent was the major source of the persisting ARGs in home compost instead of animal manure. Procrustes analysis and co-occurrence network analysis revealed a strong association between microbiome and antimicrobial resistome. Variation partitioning analysis and structural equation modeling suggested that physicochemical properties shaped the antimicrobial resistome directly and indirectly by influencing the microbiome. Our results indicated that the persistence of ARGs in home compost might be due to the succession of microbial species from the urban green waste bulking agent, and the physicochemical properties might have defined the compost environment to shape the microbiome in the compost, thus, in turn, the persisting antimicrobial resistome.

Benchmarking MicrobIEM - a user-friendly tool for decontamination of microbiome sequencing data.

BACKGROUND: Microbiome analysis is becoming a standard component in many scientific studies, but also requires extensive quality control of the 16S rRNA gene sequencing data prior to analysis. In particular, when investigating low-biomass microbial environments such as human skin, contaminants distort the true microbiome sample composition and need to be removed bioinformatically. We introduce MicrobIEM, a novel tool to bioinformatically remove contaminants using negative controls. RESULTS: We benchmarked MicrobIEM against five established decontamination approaches in four 16S rRNA amplicon sequencing datasets: three serially diluted mock communities (108-103 cells, 0.4-80% contamination) with even or staggered taxon compositions and a skin microbiome dataset. Results depended strongly on user-selected algorithm parameters. Overall, sample-based algorithms separated mock and contaminant sequences best in the even mock, whereas control-based algorithms performed better in the two staggered mocks, particularly in low-biomass samples (≤ 106 cells). We show that a correct decontamination benchmarking requires realistic staggered mock communities and unbiased evaluation measures such as Youden's index. In the skin dataset, the Decontam prevalence filter and MicrobIEM's ratio filter effectively reduced common contaminants while keeping skin-associated genera. CONCLUSIONS: MicrobIEM's ratio filter for decontamination performs better or as good as established bioinformatic decontamination tools. In contrast to established tools, MicrobIEM additionally provides interactive plots and supports selecting appropriate filtering parameters via a user-friendly graphical user interface. Therefore, MicrobIEM is the first quality control tool for microbiome experts without coding experience.

New insights into identifying sediment phosphorus sources in river-lake coupled system: A framework for optimizing microbial community fingerprints.

Identifying sediment phosphorus sources in river-lake coupled system is a question in developing preferential control strategies for phosphorus. As sediments adsorbed phosphorus and microbes would be transported with changing hydrodynamic, the phosphorus source-specific microbial community fingerprints shed light on determining the major sediment phosphorus sources. However, the identification of microbial community fingerprints is a challenge because both microbial succession and hydrological characteristics of river-lake systems would affect the stability of fingerprints. Therefore, this study provided a framework for optimizing phosphorus source-specific microbial community fingerprints, and attempted to identify the major sources of sediment phosphorus in river-lake coupled ecosystem. Meiliang Lake is one of the highly eutrophic area in Taihu Lake, where the sediments, bacterial communities, and phosphorus had a close relationship. Through analyzing the connectivity of microbes along water continuum, a microbial fingerprints candidate database was constructed. The phosphorus-related bacterial communities were screened and optimized by comparing the difference of predicted results between upstream and downstream, forming the stable microbial community fingerprints which consisted of Bacteroidia, Bacilli, Clostridia, and other species at the class level. SourceTracker results that based on the optimized phosphorus source-specific microbial community fingerprints indicated that the major sediment phosphorus sources to Meiliang Lake were Liangxi River, Wujingang River, and Donghuandi River, with the relative standard deviations ranging from 2.59% to 27.56%. The accuracy of phosphorus source apportionments was further confirmed based on the composite pollution index and hydrodynamic condition. This study put forward suggestions on how to improve the stability of microbial community fingerprints, and would help to improve the understanding of applying microbial source tracking method to identify the sources of abiotic pollution like sediment phosphorus.

Source identification of phosphorus in the river-lake interconnected system using microbial community fingerprints.

Phosphorus, one of the primary limiting factors for eutrophication, plays a crucial role in the ecology health of aquatic ecosystems. However, understanding phosphorus bioavailability and source contributions in contaminated lake sediments which could help develop effective eutrophication management plans is limited largely due to the lack of appropriate methods in large catchments with a complex arrangement of sources. Based on the significant relationships between sediment, phosphorus and microbial community, source-specific microbial community fingerprints formed by machine-learning classification SourceTracker might shed light on determining dominant phosphorus sources in the river-lake systems in the era of high-throughput sequencing. This study was conducted in Dongting Lake that suffered accelerated eutrophication due to considerable phosphorus input from the inflow-rivers. The results of phosphorus fractionation according to the Standards, Measurements and Testing harmonized procedure indicated that sediments in the central lake had a higher concentration of non-apatite inorganic phosphorus (Mann-Whitney U test), which deserves greater attention on the risk of phosphorus release. The significant relationships between phosphorus fractionations, sediment and bacterial community were established with the spearman correlation and network analysis. SourceTracker analysis indicated that the major inflow-rivers of phosphorus sources to Dongting Lake were the Songzi, Miluo, and Xinqiang Rivers. The effects of sediment diffusion distance on phosphorus source apportionment were further confirmed. Taken together, our results contribute to an improved understanding of phosphorus fractionations and source contributions in the river-lake systems and its potential impact to eutrophication management plans.

Exploring the diversity and role of microbiota during material pretreatment of light-flavor Baijiu.

Baijiu (Chinese liquor) is a type of traditional distilled alcoholic beverage produced through spontaneous solid-state fermentation with sorghum as the primary material. Material processing, including sorghum soaking, steaming and cooling which is carried out in an open environment, is an integral part of Baijiu manufacturing. However, the microbiota involved in material pretreatment and its associate with the alcoholic fermentation is unclear. This research is aimed to exploring the diversity and role of microbiota during material pretreatment of light-flavor Baijiu. Results showed that Cyanobacteria, Epicoccum, and Cladosporium predominated in the sorghum at the beginning of soaking. Lactobacillus and Pichia became the predominant bacterial and fungal genera by the end of soaking. With the dynamics of microbiota, the pH declined sharply and the categories and concentration of volatile flavors such as alcohols, esters, acids, phenols, ketones, and aldehydes increased. Correlation analysis indicated that Lactobacillus and Pichia showed positive correlation with various flavors during soaking. Furthermore, SourceTracker analysis revealed that the microbiota involved during cooling processing was an important source of the Lactobacillus during fermentation of light-flavor Baijiu. This study illustrates the role of microbiota during material pretreatment and the association with alcoholic fermentation, which contributes to reveal the mechanism of Baijiu manufacturing.

Decay of sewage-associated bacterial communities in fresh and marine environmental waters and sediment.

Understanding the microbial quality of recreational waters is critical to effectively managing human health risks. In recent years, the development of new molecular methods has provided scientists with alternatives to the use of culture-based fecal indicator methods for investigating sewage contamination in recreational waters. Before these methods can be formalized into guidelines, however, we must investigate their utility, including strengths and weaknesses in different environmental media. In this study, we investigated the decay of sewage-associated bacterial communities in water and sediment from three recreational areas in Southeast Queensland, Australia. Outdoor mesocosms with water and sediment samples from two marine and one freshwater sites were inoculated with untreated sewage and sampled on days 0, 1, 4, 8, 14, 28, and 50. Amplicon sequencing was performed on the DNA extracted from water and sediment samples, and SourceTracker was used to determine the decay of sewage-associated bacterial communities and how they change following a contamination event. No sewage-associated operational taxonomic units (OTUs) were detected in water and sediment samples after day 4; however, the bacterial communities remained changed from their background measures, prior to sewage amendment. Following untreated sewage inoculation, the mesocosm that had the most diverse starting bacterial community recovered to about 60% of its initial community composition, whereas the least diverse bacterial community only recovered to about 30% of its initial community composition. This suggests that a more diverse bacterial community may play an important role in water quality outcomes after sewage contamination events. Further investigation into potential links between bacterial communities and measures of fecal indicators, pathogens, and microbial source tracking (MST) markers is warranted and may provide insight for recreational water decision-makers.

Metagenomic analysis of microbial communities and antibiotic resistant genes in the Tijuana river, and potential sources.

The Tijuana River is a transborder river that flows northwest across the border from Baja California in Mexico into Southern California before discharging into the Pacific Ocean. The river is frequently contaminated with raw sewage due to inadequate sanitary infrastructure in Tijuana. To assess the type and degree of microbial contamination, water samples were collected monthly from a near-border and an estuarine site from August 2020 until May 2021. A portion of each sample was used for epifluorescent microscopy and DNA was extracted directly from the rest for shotgun metagenomic sequencing. After sequence quality checking and processing, we used the rapid taxonomic identifier tool Kaiju to characterize the microbial diversity of the metagenomes and matched the sequences against the Comprehensive Antibiotic Resistance Database (CARD) to examine antimicrobial resistance genes (ARGs). Bacterial and viral-like particle (VLP) abundance was consistently higher in the near-border samples than in the estuarine samples, while alpha diversity (within sample biodiversity) was higher in estuarine samples. Beta-diversity analysis found clear compositional separation between samples from the two sites, and the near-border samples were more dissimilar to one another than were the estuarine sites. Near-border samples were dominated by fecal-associated bacteria and bacteria associated with sewage sludge, while estuarine sites were dominated by marine bacteria. ARGs were more abundant at the near-border site, but were also readily detectable in the estuarine samples, and the most abundant ARGs had multi-resistance to beta-lactam antibiotics. SourceTracker analysis identified human feces and sewage sludge to be the largest contributors to the near-border samples, while marine waters dominated estuarine samples except for two sewage overflow dates with high fecal contamination. Overall, our research determined human sewage microbes to be common in the Tijuana River, and the prevalence of ARGs confirms the importance of planned infrastructure treatment upgrades for environmental health.

Assessing impacts of municipal wastewater treatment plant upgrades on bacterial hazard contributions to the receiving urban river using SourceTracker.

Upgrading municipal wastewater treatment plants (MWTPs) has been implemented in many megacities of China to reduce the discharges of nutrients and other pollutants and improve water quality of highly urbanized rivers. However, the contribution of MWTP discharge to bacterial hazards in the receiving rivers after upgrades has been largely unknown. In this study, high-throughput sequencing and shotgun metagenomics were applied to investigate the changes in the abundance, composition, potential risks, and contributions of bacteria and antibiotic resistance genes (ARGs) from effluent to receiving river after upgrading the third-largest MWTP in China with denitrification biofilters, ultrafiltration, ozonation, and disinfection processes. The annual loadings of total nitrogen and 27 types of pharmaceuticals were reduced by 42.4% ± 13.2% and 46.2% ± 15.4%, respectively. Bacterial biomass decreased from (3.58 ± 0.49) to (1.23 ± 0.27) × 107 16S rRNA gene copies/mL, and identified biomarkers in effluent and downstream shifted due to the adopted processes. Opportunistic pathogen bacteria downstream were also reduced. Although the relative abundance of total ARGs in MWTP effluent increased from 1.10 ± 0.02 to 2.19 ± 0.03 copies/16S rRNA gene after upgrades, that of total and high-risk ARGs downstream showed no significant difference. More importantly, the Bayesian-based SourceTracker method provided valuable insight by revealing that the contributions of MWTP discharge to downstream bacteria (from 44.2% ± 1.5%-31.4% ± 0.9%) and ARGs (from 61.2% ± 5.3%-47.6% ± 4.1%) were significantly reduced following the upgrades, indicating upgrading MWTP showed integrated benefits to the bacterial hazards in the receiving river. This study provides useful information for better control of bacterial hazard risks and operational strategy for the improvement of the urban aquatic ecosystem.

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

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

Persistence of human- and cattle-associated Bacteroidales and mitochondrial DNA markers in freshwater mesocosms.

Accurate identification of the origins of non-point source pollution is essential for the effective control of fecal pollution. Host-associated Bacteroidales and mitochondrial DNA (mtDNA) markers have been developed to identify the sources of human and cattle fecal pollution. However, the differences in persistence between these two types of markers under different environmental conditions are still poorly understood. Here, we conducted mesocosm experiments to investigate the influence of indigenous microbiota and nutrients on the decay of Bacteroidales and mtDNA markers associated with humans and cattle. Raw sewage or cattle feces were inoculated into mesocosms containing natural eutrophic water, sterile eutrophic water or artificial freshwater. The Bacteroidales markers HF183 (human) and CowM3 (cattle) and mtDNA markers HcytB (human) and QMIBo (cattle) were quantified using the quantitative polymerase chain reaction (qPCR) assays. All markers but HF183 decreased the fastest in the presence of indigenous microbiota. Nutrients caused a decrease in the persistence of HF183; however, no significant nutrient effects were observed for HcytB, CowM3, and QMIBo. The time to reach one log reduction (T90) for HF183 and HcytB was similar; CowM3 reached T90 earlier than QMIBo in all the treatments but eutrophic water. E. coli persisted longer than both Bacteroidales and mtDNA markers in the mesocosms regardless of inoculum type. Additionally, 16S rRNA gene amplicon sequencing was used to determine the changes in bacterial communities accompanying the marker decay. Analysis using the SourceTracker software showed that bacterial communities in the mesocosms became more dissimilar to those in the corresponding inoculants over time. Our results indicate that environmental factors are important determinants of genetic markers' persistence, but their impact can vary depending on the genetic markers. The cattle Bacteroidales markers may be more suitable for determining recent fecal contamination than cattle mtDNA.

Uncovering acid resistance genes in lactic acid bacteria and impact of non-viable bacteria on bacterial community during Chinese strong-flavor baijiu fermentation.

Chinese strong-flavor baijiu (CSFB) brewing is a spontaneously solid-state fermentation process for approximately 60 days. Numerous microorganisms grow, die, and spark a series of metabolic reactions during fermentation. In this study, the microbial community and structure between total and viable bacteria in zaopei from the 5- and 20-year pits of CSFB are revealed by amplicon sequencing. Metagenome sequencing was applied to investigate acid resistance genes in Lactobacillus and predict carbohydrate active enzyme in zaopei. Besides, SourceTracker was conducted to expose bacterial sources. Results revealed that there was no significant difference in the bacterial community and structure between the total and viable bacteria; Lactobacillus was the most dominant bacterium in zaopei of two types of pits. Meanwhile, acid resistance genes argR, aspA, ilvE, gshA, DnaK, and cfa were genes that sustained Lactobacillus survival in the late stages of fermentation with high contents of acid and ethanol, and glycosyltransferases were identified as the predominated enzymes during the CSFB fermentation which catalyzed the process of lactic acid generation via Embden-Meyerhof-Parnas pathway and Hexose Monophosphate Pathway. Moreover, the environment contributed most bacteria to zaopei of the 5- and 20-year pits. These findings will provide a deeper understanding of the microbial community structure of viable and total bacteria and the reason for the dominance of Lactobacillus in the later stages of CSFB fermentation.

Application of fast expectation-maximization microbial source tracking to discern fecal contamination in rivers exposed to low fecal inputs.

Community-based microbial source tracking (MST) can be used to determine fecal contamination from multiple sources in the aquatic environment. However, there is little scientific information on its application potential in water environmental management. Here, we compared SourceTracker and Fast Expectation-maximization Microbial Source Tracking (FEAST) performances on environmental water bodies exposed to low fecal pollution and evaluated treatment effects of fecal pollution in the watershed utilizing community-based MST. Our results showed that FEAST overall outperformed SourceTracker in sensitivity and stability, and was able to discern multi-source fecal contamination (mainly chicken feces) in ambient water bodies exposed to low fecal inputs. Consistent with our previous PCR/qPCR-based MST assays, FEAST analysis indicates that fecal pollution has been significantly mitigated through comprehensive environmental treatment by the local government. This study suggests that FEAST can be a powerful tool for accurately evaluating the contribution of multi-source fecal contamination in environmental water, facilitating environmental management.

Response of microbial community assembly and succession pattern to abiotic factors during the second round of light-flavor Baijiu fermentation.

The regulation of microbial communities is an important strategy for fermentation management. Dynamic microbiota during the Baijiu fermentation is shaped by a variety of abiotic factors. Therefore, this study aims to investigate the effects of the microbiota of the fermentation starter Daqu on the microbial assembly and the interaction of microbiota succession and abiotic factors during the second round (Ercha) of light-flavor Baijiu fermentation. The results revealed that Streptomyces, Bacillus, Lactobacillus, and Staphylococcus were the dominant bacterial genera in the initial fermentation, while Lactobacillus was dominant during the middle and later stages. Pichia and Saccharomycopsis were the dominant fungal genera during the whole fermentation process. A total of 54 volatile compounds were identified during the fermentation, among which 15 compounds, mainly including ethyl acetate, diethyl azelate, ethyl 2-hydroxyisocaproate, 3-furaldehyde, and ethylidene diacetate, were identified as important flavor metabolites. The SourceTracker software revealed that Daqu contributed 52.3 % of the bacterial community and 38.6 % of the fungal community to the fermentation. Ethanol, moisture, and pH were the major factors regulating the succession of dominant bacteria and fungi during the fermentation. The microbial succession and co-occurrence pattern driven by abiotic factors played a crucial role in shaping flavor profiles. These results provide guidance for controlling the fermentation process by optimizing operational parameters or bioaugmentation with specific microbes.

Industrial-scale aerobic composting of livestock manures with the addition of biochar: Variation of bacterial community and antibiotic resistance genes caused by various composting stages.

The presence of large amounts of antibiotic resistance genes (ARGs) in livestock manures poses an impending, tough safety risk to ecosystems. To investigate more comprehensively the mechanisms of ARGs removal from industrial-scale composting of livestock manure based on biochar addition, we tracked the dynamics of bacterial community and ARGs at various stages of aerobic composting of livestock manures with 10% biochar. There were no significant effects of biochar on the bacterial community and the profiles of ARGs. During aerobic composting, the relative abundance of ARGs and mobile genetic elements (MGEs) showed overall trends of decreasing and then increasing. The key factor driving the dynamics of ARGs was bacterial community composition, and the potential hosts of ARGs were Caldicoprobacter, Tepidimicrobium, Ignatzschineria, Pseudogracilibacillus, Actinomadura, Flavobacterium and Planifilum. The retention of the thermophilic bacteria and the repopulation of the initial bacteria were the dominant reasons for the increase in ARGs at maturation stage. Additionally, among the MGEs, the relative abundance of transposon gene was substantially removed, while the integron genes remained at high relative abundance. Our results highlighted that the suitability of biochar addition to industrial-scale aerobic composting needs to be further explored and that effective measures are needed to prevent the increase of ARGs content on maturation stage.

Effect of Environmental Microorganisms on Fermentation Microbial Community of Sauce-Flavor baijiu.

The compositions of the microbial community in fermented grains of Sauce-flavor baijiu produced in different regions have diverse characteristics; however, the reasons for this remain unclear. The present study investigated the contributions of environmental microorganisms to the microbial community as well as the volatile compounds in the fermented grains of Sauce-flavor baijiu produced in the Beijing region using high-throughput sequencing combined with sourcetracker analysis, and compared the differences of environmental microorganism and their roles in the production process of Sauce-flavor baijiu from different regions.The results showed that the environmental microorganisms in the tools were the main contributors of the bacterial and fungal communities in fermented grains during heap fermentation and at the beginning of pit fermentation. At the end of pit fermentation, pit mud was the main environmental source of bacterial community in fermented grains, while tools and Daqu were the main environmental sources of fungal community in fermented grains.Environmental microorganisms thrived on the functional microorganisms in the fermented grains of Sauce-flavor baijiu produced in the Beijing region and thus shaped the profiles of volatile compounds. Environmental microorganisms of Sauce-flavor baijiu in the Guizhou province and the Beijing region differed significantly, which is partially responsible for the distinctive characteristics in the microbial community structure of Sauce-flavor baijiu-fermented grains from different regions.

Storm promotes the dissemination of antibiotic resistome in an urban lagoon through enhancing bio-interactions.

Antibiotic-resistance genes (ARGs) and resistant bacteria (ARB) are abundant in stormwater that could cause serious infections, posing a potential threat to public health. However, there is no inference about how stormwater contributes to ARG profiles as well as the dynamic interplay between ARGs and bacteria via vertical gene transfer (VGT) or horizontal gene transfer (HGT) in urban water ecosystems. In this study, the distribution of ARGs, their host communities, and the source and community assembly process of ARGs were investigated in Yundang Lagoon (China) via high-throughput quantitative PCR, 16S rRNA gene amplicon sequencing, and application of SourceTracker before, after and recovering from an extreme precipitation event (132.1 mm). The abundance of ARGs and mobile genetic elements (MGEs) was the highest one day after precipitation and then decreased 2 days after precipitation and so on. Based on SourceTracker and NMDS analysis, the ARG and bacterial communities in lagoon surface water from one day after precipitation were mainly contributed by the wastewater treatment plant (WWTP) influent and effluent. However, the contribution of WWTP to ARG communities was minor 11 days after the precipitation, suggesting that the storm promoted the ARG levels by introducing the input of ARGs, MGEs, and ARB from point and non-point sources, such as sewer overflow and land-applied manure. Based on a novel microbial network analysis framework, the contribution of positive biological interactions between ARGs and MGEs or bacteria was the highest one day after precipitation, indicating a promoted VGT and HGT for ARG dissemination. The microbial networks deconstructed 11 days after precipitation, suggesting the stormwater practices (e.g., tide gate opening, diversion channels, and pumping) alleviated the spread of ARGs. These results advanced our understanding of the distribution and transport of ARGs associated with their source in urban stormwater runoff.

Tracking microeukaryotic footprint in a peri-urban watershed, China through machine-learning approaches.

Microeukaryotes play a significant role in biogeochemical cycling and can serve as bioindicators of water quality in freshwater ecosystems. However, there is a knowledge gap on how freshwater microeukaryotic communities are assembled, especially that how terrestrial microeukaryotes influence freshwater microeukaryotic assemblages. Here, we used a combination of 18S rRNA gene amplicon sequencing and community-based microbial source tracking (MST) approaches (i.e., SourceTracker and FEAST) to assess the contribution of microeukaryotes from surrounding environments (i.e., soils, river sediments, swine wastewater, influents and effluents of decentralized wastewater treatment plants) to planktonic microeukaryotes in the main channel, tributaries and reservoir of a peri-urban watershed, China in wet and dry seasons. The results indicated that SAR (~ 49% of the total communities), Opithokonta (~ 34%), Archaeplastida (~ 9%), and Amoebozoa (~ 2%) were dominant taxa in the watershed. The community-based MST analysis revealed that sewage effluents (7.96 - 21.84%), influents (2.23 - 13.97%), and river sediments (2.56 - 11.71%) were the major exogenous sources of riverine microeukaryotes. At the spatial scale, the downstream of the watershed (i.e., main channel and tributaries) received higher proportions of exogenous microeukaryotic OTUs compared to the upstream reservoirs, while at the seasonal scale, the sewage effluents and influents contributed higher exogenous microeukaryotes to river water in wet season than in dry season. Moreover, the swine and domestic wastewater led to the presence of Apicomplexa in wet season only, implying rainfall runoff may enhance the spread of parasitic microeukaryotes. Taken together, our study provides novel insights into the immigration patterns of microeukaryotes and their dominant supergroups between terrestrial and riverine habitats.

Capturing and tracing the spatiotemporal variations of planktonic and particle-associated bacteria in an unchlorinated drinking water distribution system.

The aperiodic changes in the quantity and community of planktonic and particle-associated bacteria have hampered the understanding and management of microbiological water quality in drinking water distribution systems. In this study, online sampling was combined with the microbial fingerprint-based SourceTracker2 to capture and trace the spatiotemporal variations in planktonic and particle-associated bacteria in an unchlorinated distribution system. The results showed that spatially, the particle load significantly increased, while in contrast, the quantity of particle-associated bacteria decreased sharply from the treatment plant to the distribution network. Similar to the trend of particle-associated bacterial diversity, the number of observed OTUs first slightly decreased from the treatment plant to the transportation network and then sharply increased from the transportation network to the distribution network. The SourceTracker2 results revealed that the contribution of particle-associated bacteria from the treatment plant decreased along the distribution distance. The spatial results indicate the dominant role of sedimentation of particles from the treatment plant, while the observed increases in particles and the associated bacteria mainly originated from the distribution network, which were confirmed directly by the increased contributions of loose deposits and biofilm. Temporally, the daily peaks of particle-associated bacterial quantity, observed OTU number, and contributions of loose deposits and biofilms were captured during water demand peaks (e.g., 18-21 h). The temporal results reveal clear linkages between the distribution system harboring bacteria (e.g., within loose deposits and biofilms) and the planktonic and particle-associated bacteria flowing through the distribution system, which are dynamically connected and interact. This study highlights that the spatiotemporal variations in planktonic and particle-associated bacteria are valuable and unneglectable for the widely on-going sampling campaigns required by water quality regulations and/or drinking water microbiological studies.

Analysis of Cow-Calf Microbiome Transfer Routes and Microbiome Diversity in the Newborn Holstein Dairy Calf Hindgut.

Hindgut microorganisms in newborn calves play an important role in the development of immunity and metabolism, and optimization of performance. However, knowledge of the extent to which microbiome colonization of the calf intestine is dependent on maternal characteristics is limited. In this study, placenta, umbilical cord, amniotic fluid, colostrum, cow feces, and calf meconium samples were collected from 6 Holstein cow-calf pairs. Microbial composition was analyzed by 16S rRNA gene high-throughput sequencing, and maternal transfer characteristics assessed using SourceTracker based on Gibbs sampling to fit the joint distribution using the mean proportions of each sample with meconium as the "sink" and other sample types as different "sources." Alpha and beta diversity analyses revealed sample type-specific microbiome features: microbial composition of the placenta, umbilical cord, amniotic fluid, colostrum, and calf feces were similar, but differed from cow feces (p < 0.05). Compared with profiles of meconium vs. placenta, meconium vs. umbilical cord, and meconium vs. colostrum, differences between the meconium and amniotic fluid were most obvious. SourceTracker analysis revealed that 23.8 ± 2.21% of the meconium OTUs matched those of umbilical cord samples, followed by the meconium-placenta pair (15.57 ± 2.2%), meconium-colostrum pair (14.4 ± 1.9%), and meconium-amniotic fluid pair (11.2 ± 1.7%). The matching ratio between meconium and cow feces was the smallest (10.5 ± 1%). Overall, our data indicated that the composition of the meconium microflora was similar compared with multiple maternal sites including umbilical cord, placenta, colostrum, and amniotic fluid. The umbilical cord microflora seemed to contribute the most to colonization of the fecal microflora of calves. Bacteria with digestive functions such as cellulose decomposition and rumen fermentation were mainly transmitted during the maternal transfer process.