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

Aims:  To correlate microbial community composition and water quality changes within wetland cells containing varying plant densities and composition in a free water surface (FWS) constructed wetland. Methods and Results:  Water chemistry was monitored weekly for nitrate, orthophosphate, and suspended solids, at various sites throughout the wetland for 6 months. Treatment ponds with 50% plant cover had about a 96·3% nitrate removal. The average change between the influent and effluent was 50–60% nitrate removal and 40–50% orthophosphate removal. Community profile of total DNA, generated by using denaturing gradient gel electrophoresis (DGGE), was used to determine the major microbial composition associated with the wetland sediment, rhizosphere, and surface water. Bacterial cloned libraries were constructed, and 300 clones were analysed by amplified ribosomal DNA restriction analysis (ARDRA) and grouped into operational taxonomic units (OTUs). A total of 35, 31, and 36 different OTU were obtained from sediment, rhizosphere, and surface water, respectively. The bacterial members within the dominant group of our clone library belonged to unclassified taxa, while the second predominant group consisted of members of the phylum Proteobacteria. The dominant organisms within the class were in the γ, β, and δ classes. Conclusion:  Microbial diversity as determined by Shannon‐Weaver index (H) was higher in the wetland cells with 50% plant density than the 100%. This was in agreement with the most efficient wetland contaminant removal units. Significance and Impact of the Study:  This study provides evidence that wetlands with 50% plant cover may promote the growth of diverse microbial communities that facilitate decomposition of chemical pollutants in surface water, and improve water quality.

Conventional water resources are not sufficient in many regions to meet the needs of growing populations. Due to cyclical weather cycles, drought, and climate change, water stress has increased worldwide including in Southern California, which serves as a model for regions that integrate reuse of wastewater for both potable and non-potable use. The Orange County Water District (OCWD) Advanced Water Purification Facility (AWPF) is a highly engineered system designed to treat and produce up to 100 million gallons per day (MGD) of purified water from a municipal wastewater source for potable reuse. Routine facility microbial water quality analysis is limited to standard indicators at this and similar facilities. Given recent advances in high throughput DNA sequencing techniques, complete microbial profiling of communities in water samples is now possible. By using 16S/18S rRNA gene sequencing, metagenomic and metatranscriptomic sequencing coupled to a highly accurate identification method along with 16S rRNA gene qPCR, we describe a detailed view of the total microbial community throughout the facility. The total bacterial load of the water at stages of the treatment train ranged from 3.02 × 106 copies in source, unchlorinated wastewater feed to 5.49 × 101 copies of 16S rRNA gene/mL after treatment (consisting of microfiltration, reverse osmosis, and ultraviolet/advanced oxidation). Microbial diversity and load decreased by several orders of magnitude after microfiltration and reverse osmosis treatment, falling to almost non-detectable levels that more closely resembled controls of molecular grade laboratory water than the biomass detected in the source water. The presence of antibiotic resistance genes and viruses was also greatly reduced. Overall, system design performance was achieved, and comprehensive microbial community analysis was found to enable a more complete characterization of the water/wastewater microbial signature.

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.