Nonbacterial Microflora in Wastewater Treatment Plants: an Underappreciated Potential Source of Pathogens

Comparative analysis of qPCR and metagenomics for detecting antimicrobial resistance in wastewater: a case study

OBJECTIVE

The World Health Organization (WHO) has declared antimicrobial resistance (AMR) as one of the top threats to global public health. While AMR surveillance of human clinical isolates is well-established in many countries, the increasing threat of AMR has intensified efforts to detect antibiotic resistance genes (ARGs) accurately and sensitively in environmental samples, wastewater, animals, and food. Using five ARGs and the 16S rRNA gene, we compared quantitative PCR (qPCR) and metagenomic sequencing (MGS), two commonly used methods to uncover the wastewater resistome. We compared both methods by evaluating ARG detection through a municipal wastewater treatment chain.

RESULTS

Our results demonstrate that qPCR was more sensitive than MGS, particularly in diluted samples with low ARG concentrations such as oxidation pond water. However, MGS was potentially more specific and has less risk of off-target binding in concentrated samples such as raw sewage. MGS analysis revealed multiple subtypes of each gene which could not be distinguished by qPCR; these subtypes varied across different sample types. Our findings affect the conclusions that can be drawn when comparing different sample types, particularly in terms of inferring removal rates or origins of genes. We conclude that both methods appear suitable to profile the resistome of wastewater and other environmental samples, depending on the research question and type of sample.

Urbanization enhances consumer protist-driven ARGs dissemination in riverine ecosystems

Despite the emergence of antibiotic resistance genes (ARGs) and antibiotic resistant bacteria (ARBs), how biological inter-trophic interactions, modulated by watershed urbanization, shape the resistome remains unexplored. We collected water samples from the highly urbanized (western: 65 % built land, sewage-affected) and lesser-urbanized (northern: 25 % built land, drinking water source) downstream tributaries of the Jiulong River in southeast China over dry and wet seasons. We utilized metagenomic and amplicon (16S and 18S rDNA) sequencing to investigate the relationships among microeukaryotic algae, consumer protists, bacterial communities, and the resistome. Metagenomic results showed that ARG-MGE-carrying contigs (mobile ARGs), rather than ARG-carrying contigs (non-mobile ARGs), exhibited more pronounced discrepancies between tributaries. A higher total abundance of ARGs and a greater number of co-shared ARGs between pathogen and non-pathogen bacteria were observed in the more urbanized western tributary. Structural equation modeling revealed that consumer protist-bacteria and algae-bacteria cohesions predominantly influenced the resistome in the western and northern tributaries, respectively. Additionally, consumer protists had more significant associations (511 out of 634) with bacteria carrying mobile ARGs in western tributary, while algae had more significant associations (73 out of 105) in northern tributary. These results highlight the distinct inter-trophic driving factors of the resistome modulated by watershed urbanization.

Filling the Knowledge Gap Regarding Microbial Occupational Exposure Assessment in Waste Water Treatment Plants: A Scoping Review

BACKGROUND

Wastewater treatment plants (WWTPs) are crucial in the scope of European Commission circular economy implementation. However, bioaerosol production may be a hazard for occupational and public health. A scoping review regarding microbial contamination exposure assessment in WWTPs was performed.

METHODS

This study was performed through PRISMA methodology in PubMed, Scopus and Web of Science.

RESULTS

28 papers were selected for data extraction. The WWTPs' most common sampled sites are the aeration tank (42.86%), sludge dewatering basin (21.43%) and grit chamber. Air sampling is the preferred sampling technique and culture-based methods were the most frequently employed assays. Staphylococcus sp. (21.43%), Bacillus sp. (7.14%), Clostridium sp. (3.57%), Escherichia sp. (7.14%) and Legionella sp. (3.57%) were the most isolated bacteria and Aspergillus sp. (17.86%), Cladosporium sp. (10.71%) and Alternaria sp. (10.71%) dominated the fungal presence.

CONCLUSIONS

This study allowed the identification of the following needs: (a) common protocol from the field (sampling campaign) to the lab (assays to employ); (b) standardized contextual information to be retrieved allowing a proper risk control and management; (c) the selection of the most suitable microbial targets to serve as indicators of harmful microbial exposure. Filling these gaps with further studies will help to provide robust science to policy makers and stakeholders.

A broad wastewater screening and clinical data surveillance for virus-related diseases in the metropolitan Detroit area in Michigan

BACKGROUND

Periodic bioinformatics-based screening of wastewater for assessing the diversity of potential human viral pathogens circulating in a given community may help to identify novel or potentially emerging infectious diseases. Any identified contigs related to novel or emerging viruses should be confirmed with targeted wastewater and clinical testing.

RESULTS

During the COVID-19 pandemic, untreated wastewater samples were collected for a 1-year period from the Great Lakes Water Authority Wastewater Treatment Facility in Detroit, MI, USA, and viral population diversity from both centralized interceptor sites and localized neighborhood sewersheds was investigated. Clinical cases of the diseases caused by human viruses were tabulated and compared with data from viral wastewater monitoring. In addition to Betacoronavirus, comparison using assembled contigs against a custom Swiss-Prot human virus database indicated the potential prevalence of other pathogenic virus genera, including: Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Bocaparvovirus, Molluscipoxvirus, Parechovirus, Roseolovirus, Lymphocryptovirus, Alphavirus, Spumavirus, Lentivirus, Deltaretrovirus, Enterovirus, Kobuvirus, Gammaretrovirus, Cardiovirus, Erythroparvovirus, Salivirus, Rubivirus, Orthohepevirus, Cytomegalovirus, Norovirus, and Mamastrovirus. Four nearly complete genomes were recovered from the Astrovirus, Enterovirus, Norovirus and Betapolyomavirus genera and viral species were identified.

CONCLUSIONS

The presented findings in wastewater samples are primarily at the genus level and can serve as a preliminary "screening" tool that may serve as indication to initiate further testing for the confirmation of the presence of species that may be associated with human disease. Integrating innovative environmental microbiology technologies like metagenomic sequencing with viral epidemiology offers a significant opportunity to improve the monitoring of, and predictive intelligence for, pathogenic viruses, using wastewater.

Wastewater-based surveillance of vector-borne pathogens: a cautionary note

Diamond et al. recently identified malaria and dengue as high-priority diseases in wastewater surveillance for climate-change-driven shifts in pathogen dynamics. When employing wastewater surveillance for vector-borne pathogens it is essential to take into account the geographical context, pathogen biology, and the availability of sewage networks for meaningful interventions.

PacBio next-generation sequencing uncovers Apicomplexa diversity in different habitats

The phylum Apicomplexa comprises a large group of intracellular protozoan parasites. These microorganisms are known to infect a variety of vertebrate and invertebrate hosts, leading to significant medical and veterinary conditions such as toxoplasmosis, cryptosporidiosis, theileriosis, and eimeriosis. Despite their importance, comprehensive data on their diversity and distribution, especially in riverine environments, remain scant. To bridge this knowledge gap, we utilized next-generation high-throughput 18S rRNA amplicon sequencing powered by PacBio technology to explore the diversity and composition of the Apicomplexa taxa. Principal component analysis (PCA) and principal coordinate analysis (PCoA) indicated the habitat heterogeneity for the physicochemical parameters and the Apicomplexa community. These results were supported by PERMANOVA (P < 0.001), ANOSIM (P < 0.001), Cluster analysis, and Venn diagram. Dominant genera of Apicomplexa in inlet samples included Gregarina (38.54%), Cryptosporidium (32.29%), and Leidyana (11.90%). In contrast, outlet samples were dominated by Babesia, Cryptosporidium, and Theileria. While surface water samples revealed 16% and 8.33% relative abundance of Toxoplasma and Cryptosporidium, respectively. To our knowledge, the next-generation high throughput sequencing covered a wide range of parasites in Egypt for the first time, which could be useful for legislation of the standards for drinking water and wastewater reuse.