Microbial Remobilisation on Riverbed Sediment Disturbance in Experimental Flumes and a Human-Impacted River: Implication for Water Resource Management and Public Health in Developing Sub-Saharan African Countries

Significant Factors for Modelling Survival of Escherichia coli in Lake Sediments

Currently available numerical models that describe the fecal contamination of aquatic environments using Escherichia coli as an indicator bacterium did not consider its survival in sediments. We conducted a series of comparative experiments to reveal the independent and interactive effects of sediment factors, including temperature, pH, water-extractable total dissolved solids (TDSs), coexisting microbes, and sampling sites, in lake environments on E. coli survival. In experiments, E. coli survival was observed by controlling any two factors at a time. Consequently, the decrease in pH and presence of coexisting microbes enhanced E. coli die-off, whereas the addition of water-extractable TDSs promoted its growth. To select factors to be considered for modelling E. coli survival in sediments, the independent effects of each factor and the interaction effect of the two factors were statistically compared based on their effect sizes (η2). As a result, pH (η2 = 59.5-89.0%) affected E. coli survival most significantly, followed by coexisting microbes (1.7-48.4%). Among the interactions affecting E. coli survival, including pH or coexisting microbes-which had larger independent effects-relatively larger statistically significant interactions were observed between pH and coexisting microbes (31.1%), coexisting microbes and water-extractable TDSs (85.4%), and coexisting microbes and temperature (26.4%).

The escalating threat of human-associated infectious bacteria in surface aquatic resources: Insights into prevalence, antibiotic resistance, survival mechanisms, detection, and prevention strategies

Anthropogenic activities and climate change profoundly impact water quality, leading to a concerning increase in the prevalence and abundance of bacterial pathogens across diverse aquatic environments. This rise has resulted in a growing challenge concerning the safety of water sources, particularly surface waters and marine environments. This comprehensive review delves into the multifaceted challenges presented by bacterial pathogens, emphasizing threads to human health within ground and surface waters, including marine ecosystems. The exploration encompasses the intricate survival mechanisms employed by bacterial pathogens and the proliferation of antimicrobial resistance, largely driven by human-generated antibiotic contamination in aquatic systems. The review further addresses prevalent pathogenic bacteria, elucidating associated risk factors, exploring their eco-physiology, and discussing the production of potent toxins. The spectrum of detection techniques, ranging from conventional to cutting-edge molecular approaches, is thoroughly examined to underscore their significance in identifying and understanding waterborne bacterial pathogens. A critical aspect highlighted in this review is the imperative for real-time monitoring of biomarkers associated with waterborne bacterial pathogens. This monitoring serves as an early warning system, facilitating the swift implementation of action plans to preserve and protect global water resources. In conclusion, this comprehensive review provides fresh insights and perspectives, emphasizing the paramount importance of preserving the quality of aquatic resources to safeguard human health on a global scale.

Investigating Escherichia coli habitat transition from sediments to water in tropical urban lakes

Background

Escherichia coli is a commonly used faecal indicator bacterium to assess the level of faecal contamination in aquatic habitats. However, extensive studies have reported that sediment acts as a natural reservoir of E. coli in the extraintestinal environment. E. coli can be released from the sediment, and this may lead to overestimating the level of faecal contamination during water quality surveillance. Thus, we aimed to investigate the effects of E. coli habitat transition from sediment to water on its abundance in the water column.

Methods

This study enumerated the abundance of E. coli in the water and sediment at five urban lakes in the Kuala Lumpur-Petaling Jaya area, state of Selangor, Malaysia. We developed a novel method for measuring habitat transition rate of sediment E. coli to the water column, and evaluated the effects of habitat transition on E. coli abundance in the water column after accounting for its decay in the water column.

Results

The abundance of E. coli in the sediment ranged from below detection to 12,000 cfu g-1, and was about one order higher than in the water column (1 to 2,300 cfu mL-1). The habitat transition rates ranged from 0.03 to 0.41 h-1. In contrast, the E. coli decay rates ranged from 0.02 to 0.16 h-1. In most cases (>80%), the habitat transition rates were higher than the decay rates in our study.

Discussion

Our study provided a possible explanation for the persistence of E. coli in tropical lakes. To the best of our knowledge, this is the first quantitative study on habitat transition of E. coli from sediments to water column.

Assessing the impact of COVID-19 restrictions on the microbial quality of an urban water catchment and the associated probability of waterborne infections

The World Health Organization reported that COVID-19 cases reached 611,421,786 globally by September 23, 2022. Six months after the first reported case, the disease had spread rapidly, reaching pandemic status, leading to numerous preventive measures to curb the spread, including a complete shutdown of many activities worldwide. Such restrictions affected services like waste management, resulting in waste accumulation in many communities and increased water pollution. Therefore, the current study investigated if lockdown impacted surface water microbial quality within an urban water catchment in South Africa. Using quantitative microbial risk assessment, the study further assessed changes in the probability of infection (Pi) with gastrointestinal illnesses from exposure to polluted water in the catchment. Escherichia coli data for 2019, 2020 and 2021 - pre-COVID, lockdown, and post-lockdown periods, respectively - were collected from the area's wastewater treatment management authorities. The Pi was determined using a beta-Poisson model. Mean overall E. coli counts ranged from 2.93 ± 0.16 to 5.30 ± 1.07 Log₁₀ MPN/100 mL. There was an overall statistically significant increase in microbial counts from 2019 to 2021. However, this difference was only accounted for between 2019 and 2021 (p = 0.008); the increase was insignificant between 2019 and 2020, and 2020 and 2021. The Pi revealed a similar trend for incidental ingestion of 100 mL and 1 mL of polluted water. No statistically significant difference was observed between the years based on multiple exposures. Although the overall microbial load and Pi estimated within the catchment exceeded the local and international limits recommended for safe use by humans, especially for drinking and recreation, these were not significantly affected by the COVID-19 restrictions. Nevertheless, these could still represent a health hazard to immunocompromised individuals using such water for personal and household hygiene, especially in informal settlements without access to water and sanitation services.

Using machine learning models to predict the effects of seasonal fluxes on Plesiomonas shigelloides population density

Seasonal variations (SVs) affect the population density (PD), fate, and fitness of pathogens in environmental water resources and the public health impacts. Therefore, this study is aimed at applying machine learning intelligence (MLI) to predict the impacts of SVs on P. shigelloides population density (PDP) in the aquatic milieu. Physicochemical events (PEs) and PDP from three rivers acquired via standard microbiological and instrumental techniques across seasons were fitted to MLI algorithms (linear regression (LR), multiple linear regression (MR), random forest (RF), gradient boosted machine (GBM), neural network (NN), K-nearest neighbour (KNN), boosted regression tree (BRT), extreme gradient boosting (XGB) regression, support vector regression (SVR), decision tree regression (DTR), M5 pruned regression (M5P), artificial neural network (ANN) regression (with one 10-node hidden layer (ANN10), two 6- and 4-node hidden layers (ANN64), and two 5- and 5-node hidden layers (ANN55)), and elastic net regression (ENR)) to assess the implications of the SVs of PEs on aquatic PDP. The results showed that SVs significantly influenced PDP and PEs in the water (p < 0.0001), exhibiting a site-specific pattern. While MLI algorithms predicted PDP with differing absolute flux magnitudes for the contributing variables, DTR predicted the highest PDP value of 1.707 log unit, followed by XGB (1.637 log unit), but XGB (mean-squared-error (MSE) = 0.0025; root-mean-squared-error (RMSE) = 0.0501; R² =0.998; medium absolute deviation (MAD) = 0.0275) outperformed other models in terms of regression metrics. Temperature and total suspended solids (TSS) ranked first and second as significant factors in predicting PDP in 53.3% (8/15) and 40% (6/15), respectively, of the models, based on the RMSE loss after permutations. Additionally, season ranked third among the 7 models, and turbidity (TBS) ranked fourth at 26.7% (4/15), as the primary significant factor for predicting PDP in the aquatic milieu. The results of this investigation demonstrated that MLI predictive modelling techniques can promisingly be exploited to complement the repetitive laboratory-based monitoring of PDP and other pathogens, especially in low-resource settings, in response to seasonal fluxes and can provide insights into the potential public health risks of emerging pathogens and TSS pollution (e.g., nanoparticles and micro- and nanoplastics) in the aquatic milieu. The model outputs provide low-cost and effective early warning information to assist watershed managers and fish farmers in making appropriate decisions about water resource protection, aquaculture management, and sustainable public health protection.

Taxonomic profiling and functional gene annotation of microbial communities in sediment of river Ganga at Kanpur, India: insights from whole-genome metagenomics study

The perennial river Ganga is recognized as one of India's largest rivers of India, but due to continuous anthropogenic activities, the river's ecosystem is under threat. Next-generation sequencing technology has transformed metagenomics in the exploration of microbiome and their imperative function in diverse aquatic ecosystems. In this study, we have uncovered the structure of community microbiome and their functions in sediments of river Ganga at Kanpur, India, at three polluted stretches through a high-resolution metagenomics approach using Illumina HiSeq 2500. Among the microbes, bacteria dominate more than 82% in the three polluted sediment samples of river Ganga. Pseudomonadota (alpha, beta, and gamma) is the major phylum of bacteria that dominates in three sediment samples. Genes involved in degradation of xenobiotic compounds involving nitrotoluene, benzoate, aminobenzoate, chlorocyclohexane, and chlorobenzene were significantly enriched in the microbiome of polluted stretches. Pathway analysis using KEGG database revealed a higher abundance of genes involved in energy metabolism such as oxidative phosphorylation, nitrogen, methane, sulfur, and carbon fixation pathways in the sediment metagenome data from the river Ganga. A higher abundance of pollutant degrading enzymes like 4-hydroxybenzoate 3-monooxygenase, catalase-peroxidase, and altronate hydrolase in the polluted microbiome indicates their role in degradation of plastics and dyes. Overall, our study has provided bacterial diversity and their dynamics in community structure and function from polluted river microbiome, which is expected to open up better avenues for exploration of novel functional genes/enzymes with potential application in health and bioremediation.

Relationships between extreme flows and microbial contamination in inland recreational swimming areas

Inland recreational swimming sites provide significant social value globally. This study focused on public recreational swimming sites across the Murrumbidgee River and its tributaries in the Australian Capital Territory (ACT) throughout the swimming season (September-April) from 2009 to 2020 to determine whether high intestinal enterococci concentrations could be predicted with flow exceedance and routinely monitored physical and chemical parameters of water quality. Enterococci concentrations were positively correlated with the turbidity associated with high-flow conditions. The predictive accuracy of high enterococci levels during high-flow conditions was good (mean percentage correctly classified, 60%). The prediction of high enterococci levels at low flows was significantly less reliable (mean percentage correctly classified, 12-15%). As the ACT is expected to experience decreases in rainfall overall but increases in extreme rainfall events due to climate change, understanding the drivers of elevated intestinal enterococci under extreme flow conditions remains important from a public health perspective.

Biological Indicators for Fecal Pollution Detection and Source Tracking: A Review

Fecal pollution, commonly detected in untreated or less treated sewage, is associated with health risks (e.g., waterborne diseases and antibiotic resistance dissemination), ecological issues (e.g., release of harmful gases in fecal sludge composting, proliferative bacterial/algal growth due to high nutrient loads) and economy losses (e.g., reduced aqua farm harvesting). Therefore, the discharge of untreated domestic sewage to the environment and its agricultural reuse are growing concerns. The goals of fecal pollution detection include fecal waste source tracking and identifying the presence of pathogens, therefore assessing potential health risks. This review summarizes available biological fecal indicators focusing on host specificity, degree of association with fecal pollution, environmental persistence, and quantification methods in fecal pollution assessment. The development of practical tools is a crucial requirement for the implementation of mitigation strategies that may help confine the types of host-specific pathogens and determine the source control point, such as sourcing fecal wastes from point sources and nonpoint sources. Emerging multidisciplinary bacterial enumeration platforms are also discussed, including individual working mechanisms, applications, advantages, and limitations.

Variability of E. coli in streambed sediment and its implication for sediment sampling

E. coli is the number one cause for water quality impairments in rivers and streams in South Dakota and the United States. Stream bottom sediments can be a reservoir for bacteria, including pathogenic organisms and fecal indicator bacteria (FIB), due to the favorable conditions provided by sediments for survival. Despite this, little is known about the variability of E. coli in sediments which should be considered when developing a sampling regime. This study examines the spatial variability of E. coli in sediment across the stream cross-section, the temporal stability of E. coli in sediment samples, and the implications for sediment sampling and processing. Five locations were sampled for sediment E. coli along two tributaries to the Big Sioux River in eastern South Dakota, four along Skunk Creek (Sk1, Sk2, Sk3, and Sk4), and one in Sixmile Creek (SM). In Skunk Creek, site Sk1 has direct cattle access where the other three sites (Sk2, Sk3, and Sk4) are under Seasonal Riparian Area Management (SRAM), a strategy that limits the cattle access to the stream. E. coli concentrations in the sediment ranged from 4 to 997 CFU g^-1 (8.5 × 10² to 2.1 × 10⁵ CFU 100 mL^-1). The highest and lowest E. coli concentrations observed were at sites Sk1 and Sk4, respectively. The E. coli concentration decreased from the upstream cattle crossing site (Sk1) through the downstream SRAM sites. Analyzing the stream cross-section analysis revealed no significant difference in E. coli concentration between the edge and the middle of the stream. Sediment samples can be held up to 24 h after sample collection in refrigerated conditions (37 °F) in the majority of cases (80%) without significant changes in E. coli concentrations. The sample size analysis indicated the spatial variability of E. coli across the stream cross-section is high and a single grab sample may not be able to provide adequate representation of E. coli concentrations in sediment without substantial error. The findings provide insight for designing E. coli monitoring projects and promote the awareness of unconventional sources of microbiological water quality impairment which are often overlooked.

Spatiotemporal Analysis of the Water and Sediment Nile Microbial Community Along an Urban Metropolis

Assessing microbial identity, diversity, and community structure could be a valuable tool for monitoring the impact of xenobiotics and anthropogenic inputs in rivers, especially in urban and industrial settings. Here, we characterize the Nile River microbial community in water and sediments in summer and winter at five locations that span its natural flow through the Cairo metropolis. 16S rRNA gene datasets were analyzed to identify the role played by sample type (sediment versus water), season, and location in shaping the community, as well as to predict functional potential of the Nile River microbiome. Microbial communities were mostly influenced by sampling type (sediments versus water), while seasonal effects were only observed in water samples. Spatial differences did not represent a significant factor in shaping the community in either summer or winter seasons. Proteobacteria was the most abundant phylum in both water and sediment samples, with the order Betaproteobacteriales being the abundant one. Chloroflexi and Bacteroidetes were also prevalent in sediment samples, while Cyanobacteria and Actinobacteria were abundant in water samples. The linear discriminative analysis effect size (LEfSe) identified the cyanobacterial genus Cyanobium PCC-6307 as the main variable between summer and winter water. Sequences representing human and animal potential pathogens, as well as toxin-producing Cyanobacteria, were identified in low abundance within the Nile microbiome. Functionally predicted metabolic pathways predicted the presence of antibiotic biosynthesis, as well as aerobic xenobiotic degradation pathways in the river microbiome.

Long-term agricultural contamination shaped diversity response of sediment microbiome

The pollution caused by agricultural production poses a threat to the ecological integrity of river ecosystems, altering the structure and function of river ecosystems. Differences in microbial community structure provide useful information about the impact of agricultural pollution on the biological integrity of ecosystems, but generally convey little information regarding ecosystem functions. In this study, using Illumina MiSeq sequencing technology based on the 16S rRNA gene, river sediment samples associated with four different types of agricultural pollution were comprehensively analyzed. The results show that the total organic carbon (TOC) content was highest at the YZS site (animal husbandry sewage) among the assayed sites, but the species richness and uniformity were lowest at this site, which may have been caused by the high nutrient source of the sewage. Furthermore, in the three YZS samples affected by the long-term discharge of aquaculture tail-water, the unique genus Dechloromonas and the genus Candidatus-Competitor were observed, which are strongly correlated with phosphorus conversion. The formation of network modules may correspond to the coexistence of functional bacteria accustomed to multiple niche combinations under different agricultural pollution conditions in river sediments. According to the PICRUSt functional prediction, the bacterial community in the agricultural polluted river sediment primarily harbored 46 subfunctions, exhibiting richness of functions. Overall, our results provide a more comprehensive understanding of the structure and ecological processes associated with the aggregation of bacterial communities, which is beneficial for the management of river environments.

Fecal indicator bacteria from environmental sources; strategies for identification to improve water quality monitoring

In tropical to temperate environments, fecal indicator bacteria (FIB), such as enterococci and Escherichia coli, can persist and potentially multiply, far removed from their natural reservoir of the animal gut. FIB isolated from environmental reservoirs such as stream sediments, beach sand and vegetation have been termed "naturalized" FIB. In addition, recent research suggests that the intestines of poikilothermic animals such as fish may be colonized by enterococci and E. coli, and therefore, these animals may contribute to FIB concentrations in the aquatic environment. Naturalized FIB that are derived from fecal inputs into the environment, and subsequently adapted to maintain their population within the non-host environment are termed "naturalized enteric FIB". In contrast, an additional theory suggests that some "naturalized" FIB diverged from enteric FIB many millions of years ago and are now normal inhabitants of the environment where they are referred to as "naturalized non-enteric FIB". In the case of the Escherichia genus, the naturalized non-enteric members are identified as E. coli during routine water quality monitoring. An over-estimation of the health risk could result when these naturalized, non-enteric FIB, (that is, not derived from avian or mammalian fecal contamination), contribute to water quality monitoring results. It has been postulated that these environmental FIB belonging to the genera Escherichia and Enterococcus can be differentiated from enteric FIB by genetic methods because they lack some of the genes required for colonization of the host intestine, and have acquired genes that aid survival in the environment. Advances in molecular tools such as next generation sequencing will aid the identification of genes peculiar or "enriched" in particular habitats to discriminate between enteric and environmental FIB. In this appraisal, we have reviewed the research studying "naturalized" FIB, and discussed the techniques for their differentiation from enteric FIB. This differentiation includes the important distinction between enteric FIB derived from fresh and non-recent fecal inputs, and those truly non-enteric environmental microbes, which are currently identified as FIB during routine water quality monitoring. The inclusion of tools for the identification of naturalized FIB (enteric or environmental) would be a valuable resource for future studies assessing water quality.

Changes of Bacterial Communities in Response to Prolonged Hydrodynamic Disturbances in the Eutrophic Water-Sediment Systems

The effects of hydrodynamic disturbances on the bacterial communities in eutrophic aquatic environments remain poorly understood, despite their importance to ecological evaluation and remediation. This study investigated the evolution of bacterial communities in the water-sediment systems under the influence of three typical velocity conditions with the timescale of 5 weeks. The results demonstrated that higher bacterial diversity and notable differences were detected in sediment compared to water using the 16S rRNA gene sequencing. The phyla Firmicutes and γ-Proteobacteria survived better in both water and sediment under stronger water disturbances. Their relative abundance peaked at 36.0%, 33.2% in water and 38.0%, 43.6% in sediment, respectively, while the phylum Actinobacteria in water had the opposite tendency. Its relative abundance grew rapidly in static control (SC) and peaked at 44.8%, and it almost disappeared in disturbance conditions. These phenomena were caused by the proliferation of genus Exiguobacterium (belonging to Firmicutes), Citrobacter, Acinetobacter, Pseudomonas (belonging to γ-Proteobacteria), and hgcI_clade (belonging to Actinobacteria). The nonmetric multidimensional scaling (NMDS) and Venn analysis also revealed significantly different evolutionary trend in the three water-sediment systems. It was most likely caused by the changes of geochemical characteristics (dissolved oxygen (DO) and nutrients). This kind of study can provide helpful information for ecological assessment and remediation strategy in eutrophic aquatic environments.

Modelling the effects of physicochemical variables and anthropogenic activities as ecological drivers of Plesiomonas shigelloides distribution and freshwaters quality

Spatio-temporal distribution of pathogens in freshwater is driven by environmental variables (EVs), natural, and human-induced activities and the spread of infections and disease outbreaks are triggered significantly by these processes. The role of EVs and anthropogenic activities on the distribution of Plesiomonas shigelloides is not well understood; hence this study aimed at modelling the effects of EVs and anthropogenic gradients on the densities of Plesiomonas in freshwaters and freshwater quality. Three freshwaters were sampled from February to December 2017. The EVs and Plesiomonas densities of the freshwaters were determined using standard techniques, while partial least square path modelling and correlation analysis were performed on the data collected. Factors underpinning the quality of the freshwaters were identified through principal component analysis (PCA). Most EVs fell within the bounds of recommended permissible limits except turbidity, TSS, salinity and TDS. Results revealed a significant increase of Plesiomonas densities with an increase in the magnitude of path coefficients and intensities of anthropogenic activities along the freshwaters. The distribution of Plesiomonas correlated with temperature (r = 0.69, p < 0.01), TSS (r = 0.30, p < 0.01), TBS (r = 0.28, p < 0.01), and BOD (r = 0.39, p < 0.01). Similarly, a significant correlation existed between conductivity and TDS (r = 0.97, p < 0.01) and salinity (r = 0.99, p < 0.01). Network analysis of EVs identified three closed networks essential for freshwaters quality and Plesiomonas distribution with nodes of variables under synergistic latent influences. Overall, PCA identified four drivers of the freshwater quality and in part, Plesiomonas density; namely, nutrient loading; thermal and organic pollutions, aesthetic pollution, and pH modulators. Higher component score indicated a greater impact of nutrient loading on the freshwater quality. The study concluded that Plesiomonas distribution is largely shaped by anthropogenic gradients and EVs in rivers, and these may play a major role in its dissemination along freshwater milieus.

Evaluating the influence of climate change on the fate and transport of fecal coliform bacteria using the modified SWAT model

Fecal coliform bacteria (FCB) contamination of natural waters is a serious public health issue. Therefore, understanding and anticipating the fate and transport of FCB are important for reducing the risk of contracting diseases. The objective of this study was to analyze the impacts of climate change on the fate and transport of FCB. We modified both the soil and the in-stream bacteria modules in the soil and water assessment tool (SWAT) model and verified the prediction accuracy of seasonal variability of FCB loads using observations. Forty bias-correcting GCM-RCM projections were applied in the modified SWAT model to examine various future climate conditions at the end of this century (2076-2100). Lastly, we also compared the variability of FCB loads under current and future weather conditions using multi-model ensemble simulations (MMES). The modified SWAT model yielded a satisfactory performance with regard to the seasonal variability of FCB amounts in the soil and FCB loading to water bodies. The modified SWAT model presented substantial proliferation of FCB in the soil (30.1%-147.5%) due to an increase in temperature (25.1%). Also, increase in precipitation (53.3%) led to an increase in FCB loads (96.0%-115.5%) from the soil to water body. In the in-stream environment, resuspension from the stream bed was the dominant process affecting the amount of FCB in stream. Therefore, the final FCB loads increased by 71.2% because of the growing peak channel velocity and volume of water used due to an increase in precipitation. Based on the results of MMES, we concluded that the level of FCB would increase simultaneously in the soil as well as in stream by the end of this century. This study will aid in understanding the future variability of FCB loads as well as in preparing an effective management plan for FCB levels in natural waters.

Explicit Characterization of Spatial Heterogeneity Based on Water Quality, Sediment Contamination, and Ichthyofauna in a Riverine-to-Coastal Zone

Our study aims to identify the spatial characteristics of water quality and sediment conditions in relation to fisheries resources, since the productivity of fisheries resources is closely related to the ambient conditions of the resource areas. We collected water quality samples and sediment contaminants from twenty-one sites at Gwangyang Bay, Korea, in the summer of 2018. Our study sites covered the area from the Seomjin River estuary to the inner and outer bays. To spatially characterize physicochemical features of Gwangyang Bay, we used Self-Organizing Map (SOM), which is known as a robust and powerful tool of unsupervised neural networks for pattern recognition. The present environmental conditions of Gwangyang Bay were spatially characterized according to four different attributes of water quality and sediment contamination. From the results, we put emphasis on several interesting points: (i) the SOM manifests the dominant physicochemical attributes of each geographical zone associated with the patterns of water quality and sediment contamination; (ii) fish populations appear to be closely associated with their food sources (e.g., shrimps and crabs) as well as the ambient physicochemical conditions; and (iii) in the context of public health and ecosystem services, the SOM result can potentially offer guidance for fish consumption associated with sediment heavy metal contamination. The present study may have limitations in representing general features of Gwangyang Bay, given the inability of snapshot data to characterize a complex ecosystem. In this regard, consistent sampling and investigation are needed to capture spatial variation and to delineate the temporal dynamics of water quality, sediment contamination, and fish populations. However, the SOM application is helpful and useful as a first approximation of an environmental assessment for the effective management of fisheries resources.

Metagenomic analysis of the bacterial communities and their functional profiles in water and sediments of the Apies River, South Africa, as a function of land use

Water quality is an important public health issue given that the presence of pathogenic organisms in such waters can adversely affect human and animal health. Despite the numerous studies conducted to assess the quality of environmental waters in many countries, limited efforts have been put on investigating the microbial quality of the sediments in developing countries and how this relates to different land uses. The present study evaluated the bacterial diversity in water and sediments in a highly used South African river to find out how the different land uses influenced the bacterial diversity, and to verify the human diseases functional classes of the bacterial populations. Samples were collected on river stretches influenced by an informal, a peri-urban and a rural settlement. Genomic DNA was extracted from water and sediment samples and sequenced on an Illumina® MiSeq platform targeting the 16S rRNA gene variable region V3-V4 from the genomic DNA. Metagenomic data analysis revealed that there was a great diversity in the microbial populations associated with the different land uses, with the informal settlement having the most considerable influence on the bacterial diversity in the water and sediments of the Apies River. The Proteobacteria (69.8%), Cyanobacteria (4.3%), Bacteroidetes (2.7%), and Actinobacteria (2.7%) were the most abundant phyla; the Alphaproteobacteria, Betaproteobacteria and Anaerolineae were the most recorded classes. Also, the sediments had a greater diversity and abundance in bacterial population than the water column. The functional profiles of the bacterial populations revealed an association with many human diseases including cancer pathways. Further studies that would isolate these potentially pathogenic organisms in the aquatic environment are therefore needed as this would help in protecting the lives of communities using such rivers, especially against emerging bacterial pathogens.

Factors affecting the dissipation of pharmaceuticals in freshwater sediments

Degradation is one of the key processes governing the impact of pharmaceuticals in the aquatic environment. Most studies on the degradation of pharmaceuticals have focused on soil and sludge, with fewer exploring persistence in aquatic sediments. We investigated the dissipation of 6 pharmaceuticals from different therapeutic classes in a range of sediment types. Dissipation of each pharmaceutical was found to follow first-order exponential decay. Half-lives in the sediments ranged from 9.5 (atenolol) to 78.8 (amitriptyline) d. Under sterile conditions, the persistence of pharmaceuticals was considerably longer. Stepwise multiple linear regression analysis was performed to explore the relationships between half-lives of the pharmaceuticals, sediment physicochemical properties, and sorption coefficients for the compounds. Sediment clay, silt, and organic carbon content and microbial activity were the predominant factors related to the degradation rates of diltiazem, cimetidine, and ranitidine. Regression analysis failed to highlight a key property which may be responsible for observed differences in the degradation of the other pharmaceuticals. The present results suggest that the degradation rate of pharmaceuticals in sediments is determined by different factors and processes and does not exclusively depend on a single sediment parameter. Environ Toxicol Chem 2018;37:829-838. © 2017 SETAC.