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Climate change raises an old disease to a new level of public health threat. The causative agent,Vibrio cholerae, native to aquatic ecosystems, is influenced by climate and weather processes. The risk of cholera is elevated in vulnerable populations lacking access to safe water and sanitation infrastructure. Predictive intelligence, employing mathematical algorithms that integrate earth observations and heuristics derived from microbiological, sociological, and weather data, can provide anticipatory decision-making capabilities to reduce the burden of cholera and save human lives. An example offered here is the recent outbreak of cholera in Malawi, predicted in advance by such algorithms. 

Periodical cicadas (Hemiptera:Magicicada) have coevolved with obligate bacteriome-inhabiting microbial symbionts, yet little is known about gut microbial symbiont composition or differences in composition among allochronicMagicicadabroods (year classes) which emerge parapatrically or allopatrically in the eastern United States. Here, 16S rRNA amplicon sequencing was performed to determine gut bacterial community profiles of three periodical broods, including II (Connecticut and Virginia, 2013), VI (North Carolina, 2017), and X (Maryland, 2021, and an early emerging nymph collected in Ohio, 2017). Results showed similarities among all nymphal gut microbiomes and between morphologically distinct 17-yearMagicicada, namelyMagicicada septendecim(Broods II and VI) and 17-yearMagicicada cassini(Brood X) providing evidence of a core microbiome, distinct from the microbiome of burrow soil inhabited by the nymphs. Generally, phylaBacteroidetes[Bacteroidota] (> 50% relative abundance),Actinobacteria[Actinomycetota], orProteobacteria[Pseudomonadota] represented the core.Acidobacteriaand generaCupriavidus,Mesorhizobium, andDelftiawere prevalent in nymphs but less frequent in adults. The primary obligate endosymbiont,Sulcia(Bacteroidetes), was dominant amongst core genera detected.Chryseobacteriumwere common in Broods VI and X.Chitinophaga, Arthrobacter, andRenibacteriumwere common in Brood X, andPedobacterwere common to nymphs of Broods II and VI. Further taxonomic assignment of unclassifiedAlphaproteobacteriasequencing reads allowed for detection of multiple copies of theHodgkinia16S rRNA gene, distinguishable as separate operational taxonomic units present simultaneously. As major emergences of the broods examined here occur at 17-year intervals, this study will provide a valuable comparative baseline in this era of a changing climate.

 

ABSTRACT Wastewater surveillance (WS), when coupled with advanced molecular techniques, offers near real-time monitoring of community-wide transmission of SARS-CoV-2 and allows assessing and mitigating COVID-19 outbreaks, by evaluating the total microbial assemblage in a community. Composite wastewater samples (24 h) were collected weekly from a manhole between December 2020 and November 2021 in Maryland, USA. RT-qPCR results showed concentrations of SARS-CoV-2 RNA recovered from wastewater samples reflected incidence of COVID-19 cases. When a drastic increase in COVID-19 was detected in February 2021, samples were selected for microbiome analysis (DNA metagenomics, RNA metatranscriptomics, and targeted SARS-CoV-2 sequencing). Targeted SARS-CoV-2 sequencing allowed for detection of important genetic mutations, such as spike: K417N, D614G, P681H, T716I, S982A, and D1118H, commonly associated with increased cell entry and reinfection. Microbiome analysis (DNA and RNA) provided important insight with respect to human health-related factors, including detection of pathogens and their virulence/antibiotic resistance genes. Specific microbial species comprising the wastewater microbiome correlated with incidence of SARS-CoV-2 RNA, suggesting potential association with SARS-CoV-2 infection. Climatic conditions, namely, temperature, were related to incidence of COVID-19 and detection of SARS-CoV-2 in wastewater, having been monitored as part of an environmental risk score assessment carried out in this study. In summary, the wastewater microbiome provides useful public health information, and hence, a valuable tool to proactively detect and characterize pathogenic agents circulating in a community. In effect, metagenomics of wastewater can serve as an early warning system for communicable diseases, by providing a larger source of information for health departments and public officials. IMPORTANCE Traditionally, testing for COVID-19 is done by detecting SARS-CoV-2 in samples collected from nasal swabs and/or saliva. However, SARS-CoV-2 can also be detected in feces of infected individuals. Therefore, wastewater samples can be used to test all individuals of a community contributing to the sewage collection system, i.e., the infrastructure, such as gravity pipes, manholes, tanks, lift stations, control structures, and force mains, that collects used water from residential and commercial sources and conveys the flow to a wastewater treatment plant. Here, we profile community wastewater collected from a manhole, detect presence of SARS-CoV-2, identify genetic mutations of SARS-CoV-2, and perform COVID-19 risk score assessment of the study area. Using metagenomics analysis, we also detect other microorganisms (bacteria, fungi, protists, and viruses) present in the samples. Results show that by analyzing all microorganisms present in wastewater, pathogens circulating in a community can provide an early warning for contagious diseases. 

Climate variables influence the occurrence, growth, and distribution of Vibrio cholerae in the aquatic environment. Together with socio-economic factors, these variables affect the incidence and intensity of cholera outbreaks. The current pandemic of cholera began in the 1960s, and millions of cholera cases are reported each year globally. Hence, cholera remains a significant health challenge, notably where human vulnerability intersects with changes in hydrological and environmental processes. Cholera outbreaks may be epidemic or endemic, the mode of which is governed by trigger and transmission components that control the outbreak and spread of the disease, respectively. Traditional cholera risk assessment models, namely compartmental susceptible-exposed-infected-recovered (SEIR) type models, have been used to determine the predictive spread of cholera through the fecal–oral route in human populations. However, these models often fail to capture modes of infection via indirect routes, such as pathogen movement in the environment and heterogeneities relevant to disease transmission. Conversely, other models that rely solely on variability of selected environmental factors (i.e., examine only triggers) have accomplished real-time outbreak prediction but fail to capture the transmission of cholera within impacted populations. Since the mode of cholera outbreaks can transition from epidemic to endemic, a comprehensive transmission model is needed to achieve timely and reliable prediction with respect to quantitative environmental risk. Here, we discuss progression of the trigger module associated with both epidemic and endemic cholera, in the context of the autochthonous aquatic nature of the causative agent of cholera, V. cholerae, as well as disease prediction. 

Microorganisms are ubiquitous in the biosphere, playing a crucial role in both biogeochemistry of the planet and human health. However, identifying these microorganisms and defining their function are challenging. Widely used approaches in comparative metagenomics, 16S amplicon sequencing and whole genome shotgun sequencing (WGS), have provided access to DNA sequencing analysis to identify microorganisms and evaluate diversity and abundance in various environments. However, advances in parallel high-throughput DNA sequencing in the past decade have introduced major hurdles, namely standardization of methods, data storage, reproducible interoperability of results, and data sharing. The National Ecological Observatory Network (NEON), established by the National Science Foundation, enables all researchers to address queries on a regional to continental scale around a variety of environmental challenges and provide high-quality, integrated, and standardized data from field sites across the U.S. As the amount of metagenomic data continues to grow, standardized procedures that allow results across projects to be assessed and compared is becoming increasingly important in the field of metagenomics. We demonstrate the feasibility of using publicly available NEON soil metagenomic sequencing datasets in combination with open access Metagenomics Rapid Annotation using the Subsystem Technology (MG-RAST) server to illustrate advantages of WGS compared to 16S amplicon sequencing. Four WGS and four 16S amplicon sequence datasets, from surface soil samples prepared by NEON investigators, were selected for comparison, using standardized protocols collected at the same locations in Colorado between April-July 2014. The dominant bacterial phyla detected across samples agreed between sequencing methodologies. However, WGS yielded greater microbial resolution, increased accuracy, and allowed identification of more genera of bacteria, archaea, viruses, and eukaryota, and putative functional genes that would have gone undetected using 16S amplicon sequencing. NEON open data will be useful for future studies characterizing and quantifying complex ecological processes associated with changing aquatic and terrestrial ecosystems. 

Microbial contamination of recreation waters is a major concern globally, with pollutants originating from many sources, including human and other animal wastes often introduced during storm events. Fecal contamination is traditionally monitored by employing culture methods targeting fecal indicator bacteria (FIB), namely E . coli and enterococci, which provides only limited information of a few microbial taxa and no information on their sources. Host-associated qPCR and metagenomic DNA sequencing are complementary methods for FIB monitoring that can provide enhanced understanding of microbial communities and sources of fecal pollution. Whole metagenome sequencing (WMS), quantitative real-time PCR (qPCR), and culture-based FIB tests were performed in an urban watershed before and after a rainfall event to determine the feasibility and application of employing a multi-assay approach for examining microbial content of ambient source waters. Cultivated E . coli and enterococci enumeration confirmed presence of fecal contamination in all samples exceeding local single sample recreational water quality thresholds ( E . coli , 410 MPN/100 mL; enterococci, 107 MPN/100 mL) following a rainfall. Test results obtained with qPCR showed concentrations of E . coli , enterococci, and human-associated genetic markers increased after rainfall by 1.52-, 1.26-, and 1.11-fold log 10 copies per 100 mL, respectively. Taxonomic analysis of the surface water microbiome and detection of antibiotic resistance genes, general FIB, and human-associated microorganisms were also employed. Results showed that fecal contamination from multiple sources (human, avian, dog, and ruminant), as well as FIB, enteric microorganisms, and antibiotic resistance genes increased demonstrably after a storm event. In summary, the addition of qPCR and WMS to traditional surrogate techniques may provide enhanced characterization and improved understanding of microbial pollution sources in ambient waters.