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.

Summary: Vibrio spp . thrive in warm water and moderate salinity, and they are associated with aquatic invertebrates, notably crustaceans and zooplankton. At least 12 Vibrio spp. are known to cause infection in humans, and Vibrio cholerae is well documented as the etiological agent of pandemic cholera. Pathogenic non‐cholera Vibrio spp ., e.g., Vibrio parahaemolyticus and Vibrio vulnificus , cause gastroenteritis, septicemia, and other extra‐intestinal infections. Incidence of vibriosis is rising globally, with evidence that anthropogenic factors, primarily emissions of carbon dioxide associated with atmospheric warming and more frequent and intense heatwaves, significantly influence environmental parameters, e.g., temperature, salinity, and nutrients, all of which can enhance growth of Vibrio spp . in aquatic ecosystems. It is not possible to eliminate Vibrio spp ., as they are autochthonous to the aquatic environment and many play a critical role in carbon and nitrogen cycling. Risk prediction models provide an early warning that is essential for safeguarding public health. This is especially important for regions of the world vulnerable to infrastructure instability, including lack of ‘water, sanitation, and hygiene’ (WASH), and a less resilient infrastructure that is vulnerable to natural calamity, e.g., hurricanes, floods, and earthquakes, and/or social disruption and civil unrest, arising from war, coups, political crisis, and economic recession. Incorporating environmental, social, and behavioural parameters into such models allows improved prediction, particularly of cholera epidemics. We have reported that damage to WASH infrastructure, coupled with elevated air temperatures and followed by above average rainfall, promotes exposure of a population to contaminated water and increases the risk of an outbreak of cholera. Interestingly, global predictive risk models successful for cholera have the potential, with modification, to predict diseases caused by other clinically relevant Vibrio spp . In the research reported here, the focus was on environmental parameters associated with incidence and distribution of clinically relevant Vibrio spp . and their role in disease transmission. In addition, molecular methods designed for detection and enumeration proved useful for predictive modelling and are described, namely in the context of prediction of environmental conditions favourable to Vibrio spp ., hence human health risk.

The genus Vibrio includes pathogenic species that are naturally occurring in marine and estuarine environments globally. Routine monitoring for Vibrio species and environmental parameters influencing their incidence is critical to provide a warning system for the public when the risk of infection is high.

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.

The microbiological content of drinking water traditionally is determined by employing culture-dependent methods that are unable to detect all microorganisms, especially those that are not culturable. High-throughput sequencing now makes it possible to determine the microbiome of drinking water. Thus, the natural microbiota of water and water distribution systems can now be determined more accurately and analyzed in significantly greater detail, providing comprehensive understanding of the microbial community of drinking water applicable to public health. In this study, shotgun metagenomic analysis was performed to determine the microbiological content of drinking water and to provide a preliminary assessment of tap, drinking fountain, sparkling natural mineral, and non-mineral bottled water. Predominant bacterial species detected were members of the phyla Actinobacteria and Proteobacteria, notably the genera Alishewanella, Salmonella, and Propionibacterium in non-carbonated non-mineral bottled water, Methyloversatilis and Methylibium in sparkling natural mineral water, and Mycobacterium and Afipia in tap and drinking fountain water. Fecal indicator bacteria, i.e., Escherichia coli or enterococci, were not detected in any samples examined in this study. Bacteriophages and DNA encoding a few virulence-associated factors were detected but determined to be present only at low abundance. Antibiotic resistance markers were detected only at abundance values below our threshold of confidence. DNA of opportunistic plant and animal pathogens was identified in some samples and these included bacteria (Mycobacterium spp.), protozoa (Acanthamoeba mauritaniensis and Acanthamoeba palestinensis), and fungi (Melampsora pinitorqua and Chryosporium queenslandicum). Archaeal DNA (Candidatus Nitrosoarchaeum) was detected only in sparkling natural mineral water. This preliminary study reports the complete microbiome (bacteria, viruses, fungi, and protists) of selected types of drinking water employing whole-genome high-throughput sequencing and bioinformatics. Investigation into activity and function of the organisms detected is in progress.

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.