Dissecting microbial community structure in sewage treatment plant for pathogens’ detection using metagenomic sequencing technology

Comparative assessment of microbiome and resistome of influent and effluent of sewage treatment plant and common effluent treatment plant located in Delhi, India using shotgun approach

Antimicrobial resistance (AMR) is a significant threat that demands surveillance to identify and analyze trends of the emerging antibiotic resistance genes (ARGs) and potential microbial carriers. The influent of the wastewater treatment plants (WWTPs) reflects the microbes derived from the population and effluent being the source of dissemination of potential pathogenic microbes and AMR. The present study aimed to monitor microbial communities and antibiotic resistance genes in WWTPs employing a whole metagenome shotgun sequencing approach. The samples were collected from a sewage treatment plant (STP) and a common effluent treatment plant (CETP) in Delhi, India. The results showed the influent of STP to be rich in Bifidobacterium, Bacteroides, Escherichia, Arcobacter, and Pseudomonas residents of gut microbiota and known to cause diseases in humans and animals; whereas the CETP sample was abundant in Aeromonas, Escherichia, and Shewanella known to be involved in the degradation of different compounds. Interestingly, the effluent samples from both STPs and CETP were rich in microbial diversity, comprising organic and xenobiotic compound degrading and disease-causing bacteria, indicating the effluent being the source of dissemination of concerning bacteria to the environment. The functional profile at both sites displayed similarity with an abundance of housekeeping function genes as analyzed by Clusters of Orthologous Genes (COG), KEGG Orthology (KO), and subsystem databases. Resistome profiling by MEGARes showed the dominance of ARGs corresponding to beta-lactams having relative abundance ranging from 16% to 34% in all the metagenome datasets, followed by tetracycline (8%-16%), aminoglycosides (7%-9%), multi-drug (5%-9%), and rifampin (3%-9%). Also, AMR genes oxa, ant3-DPRIME, and rpoB, which are of clinical importance were predominantly and most prevalently present in all the samples. The presence of AMR in effluents from both types of treatment plants indicates that wastewater from both sources contributes to the spread of pathogenic bacteria and resistance genes, increasing the environmental AMR burden and therefore requires tertiary treatment before discharge. This work will facilitate further research towards the identification of suitable biomarkers for monitoring antibiotic resistance.

Profiling pathogenic protozoan and their functional pathways in wastewater using 18S rRNA and shotgun metagenomics

Despite extensive research, little is known about the composition of eukaryotic protists in environmental samples. This is due to low parasite concentrations, the complexity of parasite diversity, and a lack of suitable reference databases and standardized protocols. To bridge this knowledge gap, this study used 18S rRNA short amplicon and shotgun metagenomic sequencing approaches to profile protozoan microbial communities as well as their functional pathways in treated and untreated wastewater samples collected from different regions of South Africa. Results demonstrated that protozoan diversity (Shannon index P-value = 0.03) and taxonomic composition (PERMANOVA, P-value = 0.02) was mainly driven by the type of wastewater samples (treated & untreated) and geographic location. However, these WWTPs were also found to contain a core community of protozoan parasites. The untreated wastewater samples revealed a predominant presence of free-living, parasitic, and potentially pathogenic protists typically found in humans and animals, ranging from Alveolata (27 %) phylum (Apicomplexa and Ciliophora) to Excavata (3.88 %) (Discoba and Parasalia) and Amoebozoa (2.84 %) (Entamoeba and Acanthamoeba). Shotgun metagenomics analyses in a subset of the untreated wastewater samples confirmed the presence of public health-importance protozoa, including Cryptosporidium species (3.48 %), Entamoeba hystolitica (6.58 %), Blastocystis hominis (2.91 %), Naegleria gruberi (2.37 %), Toxoplasma gondii (1.98 %), Cyclospora cayetanensis (1.30 %), and Giardia intestinalis (0.31 %). Virulent gene families linked to pathogenic protozoa, such as serine/threonine protein phosphatase and mucin-desulfating sulfatase were identified. Additionally, enriched pathways included thiamine diphosphate biosynthesis III, heme biosynthesis, Methylerythritol 4-Phosphate Pathway, methyl erythritol phosphate (MEP), and pentose phosphate pathways. These findings suggest that protozoan pathogens may possess metabolic and growth potential within WWTPs, posing a severe risk of transmission to humans and animals if inadequately disinfected before release. This study provides a baseline for the future investigation of diverse protozoal communities in wastewater, which are of public health importance.

Bacteriophage-based biosensors for detection of pathogenic microbes in wastewater

Wastewater is discarded from several sources, including industry, livestock, fertilizer application, and municipal waste. If the disposed of wastewater has not been treated and processed before discharge to the environment, pathogenic microorganisms and toxic chemicals are accumulated in the disposal area and transported into the surface waters. The presence of harmful microbes is responsible for thousands of human deaths related to water-born contamination every year. To be able to take the necessary step and quick action against the possible presence of harmful microorganisms and substances, there is a need to improve the effective speed of identification and treatment of these problems. Biosensors are such devices that can give quantitative information within a short period of time. There have been several biosensors developed to measure certain parameters and microorganisms. The discovered biosensors can be utilized for the detection of axenic and mixed microbial strains from the wastewaters. Biosensors can further be developed for specific conditions and environments with an in-depth understanding of microbial organization and interaction within that community. In this regard, bacteriophage-based biosensors have become a possibility to identify specific live bacteria in an infected environment. This paper has investigated the current scenario of microbial community analysis and biosensor development in identifying the presence of pathogenic microorganisms.

Molecular characterization of microorganisms with industrial potential for methane production in sludge from Kangemi sewage treatment plant, Nyeri county-Kenya

Microbial consortia under anaerobic conditions are involved in oxidizing organic matter in the sludge to produce methane gas. However, in developing countries like Kenya, these microbes have not been fully identified to target them for the efficient harnessing of biofuel. This study collected wet sludge from two anaerobic digestion lagoons 1 and 2 that were operational during sampling at Kangemi Sewage Treatment Plant, in Nyeri County, Kenya. DNA was extracted from samples using commercially available ZymoBIOMICS™ DNA Miniprep Kit and sequenced using Shotgun metagenomics. Samples were analyzed using MG-RAST software (Project ID: mgp100988), which allowed for identifying microorganisms directly involved in various stages of methanogenesis pathways. The study found hydrogenotrophic methanogens, such as Methanospirillum (32%), Methanobacterium (27%), Methanobrevibacter (27%), and Methanosarcina (32%), being predominant in the lagoon communities, whereas acetoclastic microorganisms such as the Methanoregula (22%) and the acetate oxidazing bacteria such as Clostridia (68%) were the key microbes for that pathway in the sewage digester sludge. Furthermore, Methanothermobacter (18%), Methanosarcina (21%), Methanosaeta (15%), and Methanospirillum (13%) carried out the methylotrophic pathway. In contrast, Methanosarcina (23%),Methanoregula (14%), methanosaeta (13%), and methnanoprevibacter (13%) seemed to play an important role in the final step of methane release. This study concluded that the sludge produced from the Nyeri-Kangemi WWTP harbors microbes with significant potential for biogas production. The study recommends a pilot study to investigate the efficiency of the identified microbes for biogas production.

Potential Exposure to Respiratory and Enteric Bacterial Pathogens among Wastewater Treatment Plant Workers, South Africa

Wastewater handling has been associated with an increased risk of developing adverse health effects, including respiratory and gastrointestinal illnesses. However, there is a paucity of information in the literature, and occupational health risks are not well quantified. Grab influent samples were analysed using Illumina Miseq 16S amplicon sequencing to assess potential worker exposure to bacterial pathogens occurring in five municipal wastewater treatment plants (WWTPs). The most predominant phyla were Bacteroidota, Campilobacterota, Proteobacteria, Firmicutes, and Desulfobacterota, accounting for 85.4% of the total bacterial community. Taxonomic analysis showed a relatively low diversity of bacterial composition of the predominant genera across all WWTPs, indicating a high degree of bacterial community stability in the influent source. Pathogenic bacterial genera of human health concern included Mycobacterium, Coxiella, Escherichia/Shigella, Arcobacter, Acinetobacter, Streptococcus, Treponema, and Aeromonas. Furthermore, WHO-listed inherently resistant opportunistic bacterial genera were identified. These results suggest that WWTP workers may be occupationally exposed to several bacterial genera classified as hazardous biological agents for humans. Therefore, there is a need for comprehensive risk assessments to ascertain the actual risks and health outcomes among WWTP workers and inform effective intervention strategies to reduce worker exposure.

Molecular Diagnostic Tools Applied for Assessing Microbial Water Quality

Microbial water quality is of vital importance for human, animal, and environmental health. Notably, pathogenically contaminated water can result in serious health problems, such as waterborne outbreaks, which have caused huge economic and social losses. In this context, the prompt detection of microbial contamination becomes essential to enable early warning and timely reaction with proper interventions. Recently, molecular diagnostics have been increasingly employed for the rapid and robust assessment of microbial water quality implicated by various microbial pollutants, e.g., waterborne pathogens and antibiotic-resistance genes (ARGs), imposing the most critical health threats to humans and the environment. Continuous technological advances have led to constant improvements and expansions of molecular methods, such as conventional end-point PCR, DNA microarray, real-time quantitative PCR (qPCR), multiplex qPCR (mqPCR), loop-mediated isothermal amplification (LAMP), digital droplet PCR (ddPCR), and high-throughput next-generation DNA sequencing (HT-NGS). These state-of-the-art molecular approaches largely facilitate the surveillance of microbial water quality in diverse aquatic systems and wastewater. This review provides an up-to-date overview of the advancement of the key molecular tools frequently employed for microbial water quality assessment, with future perspectives on their applications.

The source and fate of Mycobacterium tuberculosis complex in wastewater and possible routes of transmission

BACKGROUND

The Mycobacterium tuberculosis complex (MTBC) consists of causative agents of both human and animal tuberculosis and is responsible for over 10 million annual infections globally. Infections occur mainly through airborne transmission, however, there are possible indirect transmissions through a faecal-oral route which is poorly reported. This faecal-oral transmission could be through the occurrence of the microbe in environments such as wastewater. This manuscript, therefore, reviews the source and fate of MTBC in the wastewater environment, including the current methods in use and the possible risks of infections.

RESULTS

The reviewed literature indicates that about 20% of patients with pulmonary TB may have extra-pulmonary manifestations such as GITB, resulting in shedding in feaces and urine. This could potentially be the reason for the detection of MTBC in wastewater. MTBC concentrations of up to 5.5 × 105 (±3.9 × 105) copies/L of untreated wastewater have been reported. Studies have indicated that wastewater may provide these bacteria with the required nutrients for their growth and could potentially result in environmental transmission. However, 98.6 (± 2.7) %, removal during wastewater treatment, through physical-chemical decantation (primary treatment) and biofiltration (secondary treatment) has been reported. Despite these reports, several studies observed the presence of MTBC in treated wastewater via both culture-dependent and molecular techniques.

CONCLUSION

The detection of viable MTBC cells in either treated or untreated wastewater, highlights the potential risks of infection for wastewater workers and communities close to these wastewater treatment plants. The generation of aerosols during wastewater treatment could be the main route of transmission. Additionally, direct exposure to the wastewater containing MTBC could potentially contribute to indirect transmissions which may lead to pulmonary or extra-pulmonary infections. This calls for the implementation of risk reduction measures aimed at protecting the exposed populations.

Analysis of pharmaceuticals, hormones and bacterial communities in a municipal wastewater treatment plant - Comparison of parallel full-scale membrane bioreactor and activated sludge systems

In this study, the occurrence of pharmaceuticals, hormones and bacterial community structures was studied at a wastewater treatment plant in Finland having two different parallel treatment lines: conventional activated sludge (CAS) treatment with a sedimentation stage, and a membrane bioreactor (MBR). Influent and effluents were sampled seven times over a period of one year. The bacterial communities of the influent samples showed a high degree of similarity, except for the February sample which had substantially lower diversity. There was significant fluctuation in the species richness and diversity of the effluent samples, although both effluents showed a similar trend. A marked decrease in diversity was observed in effluents collected between August and November. The initiation of nitrogen removal as a result of an increase in temperature could explain the changes in microbial community structures. In overall terms, suspended solids, bacteria and total organic matter (COD and BOD) were removed to a greater extent using the MBR, while higher Tot-N, Tot-P and nitrate removal rates were achieved using the CAS treatment. Estrone (E1) concentrations were also consistently at a lower level in the MBR effluents (<0.1-0.68 ng/l) compared to the CAS effluents (1.1-12 ng/l). Due to the high variation in the concentrations of pharmaceuticals, no clear superiority of either process could be demonstrated with certainty. The study highlights the importance of long-term sampling campaigns to detect variations effectively.

Data Analytics for Environmental Science and Engineering Research

The advent of new data acquisition and handling techniques has opened the door to alternative and more comprehensive approaches to environmental monitoring that will improve our capacity to understand and manage environmental systems. Researchers have recently begun using machine learning (ML) techniques to analyze complex environmental systems and their associated data. Herein, we provide an overview of data analytics frameworks suitable for various Environmental Science and Engineering (ESE) research applications. We present current applications of ML algorithms within the ESE domain using three representative case studies: (1) Metagenomic data analysis for characterizing and tracking antimicrobial resistance in the environment; (2) Nontarget analysis for environmental pollutant profiling; and (3) Detection of anomalies in continuous data generated by engineered water systems. We conclude by proposing a path to advance incorporation of data analytics approaches in ESE research and application.

Analysis of Microbial Communities and Pathogen Detection in Domestic Sewage Using Metagenomic Sequencing

Wastewater contains diverse microbes, and regular microbiological screening at wastewater treatment plants is essential for monitoring the wastewater treatment and protecting environmental health. In this study, a metagenomic approach was used to characterize the microbial communities in the influent and effluent of a conventional domestic sewage treatment plant in the metropolitan city of Jeddah. Bacteria were the prevalent type of microbe in both the influent and effluent, whereas archaea and viruses were each detected at <1% abundance. Greater diversity was observed in effluent bacterial populations compared with influent, despite containing similar major taxa. These taxa consisted primarily of Proteobacteria, followed by Bacteroidetes and Firmicutes. Metagenomic analysis provided broad profiles of 87 pathogenic/opportunistic bacteria belonging to 47 distinct genera in the domestic sewage samples, with most having <1% abundance. The archaea community included 20 methanogenic genera. The virus-associated sequences were classified mainly into the families Myoviridae, Siphoviridae, and Podoviridae. Genes related to resistance to antibiotics and toxic compounds, gram-negative cell wall components, and flagellar motility in prokaryotes identified in metagenomes from both types of samples. This study provides a comprehensive understanding of microbial communities in influent and effluent samples of a conventional domestic sewage treatment plant and suggests that metagenomic analysis is a feasible approach for microbiological monitoring of wastewater treatment.