Identification of Bisphenol A-Assimilating Microorganisms in Mixed Microbial Communities Using 13C-DNA Stable Isotope Probing.

A wide range of trace organic contaminants (TOrCs), including the endocrine-disrupting compound bisphenol A (BPA), are subject to microbial transformations during biological wastewater treatment. However, relatively little is known about the identity of organisms capable of assimilating emerging contaminants. Here, 13C-DNA stable isotope probing (DNA-SIP) was used to investigate biodegradation and assimilation of BPA by mixed microbial communities collected from two full-scale wastewater treatment plant bioreactors in New York City and subsequently enriched under two BPA exposure conditions. The four enrichment modes (two reactors with two initial BPA concentrations) resulted in four distinct communities with different BPA degradation rates. On the basis of DNA-SIP, bacteria related to Sphingobium spp. were dominant in the assimilation of BPA or its metabolites. Variovorax spp. and Pusillimonas spp. also assimilated BPA or its metabolites. Our results highlight that microbial communities originating from wastewater treatment facilities harbor the potential for addressing not only human-derived carbon but also BPA, a complex anthropogenic TOrC. While previous studies focus on microbial biodegradation of BPA, this study uniquely determines the "active" fraction of microorganisms engaged in assimilation of BPA-derived carbon. Ultimately, information on both biodegradation and assimilation can facilitate better design and operation of engineered treatment processes to achieve BPA removal.

Assessment of Commonly Measured Wastewater Parameters to Estimate Sewershed Populations for Use in Wastewater-Based Epidemiology: Insights into Population Dynamics in New York City during the COVID-19 Pandemic.

Understanding per capita rates of disease incidence or prevalence from wastewater surveillance data requires an estimate of the population contributing to wastewater samples, given that populations in large urban areas are dynamic, especially if major events, such as the onset of the COVID-19 pandemic, cause large population shifts. To assess whether commonly measured wastewater parameters can be used to estimate sewershed populations, we used wastewater data collected from New York City's (NYC) 14 wastewater treatment facilities to evaluate the relationship between influent loads of four wastewater parameters-ammonia, total Kjeldahl nitrogen, total suspended solids, and five-day carbonaceous biochemical oxygen demand-and census-based population estimates of the corresponding sewersheds during 2019, when populations were assumed to be relatively stable. Ammonia mass load had the most consistent relationship with sewershed population, regardless of wet weather contributions to NYC's predominantly combined sewer system. Changes in ammonia loads due to COVID-19 restrictions enacted in March 2020 generally reflected population shifts in sewersheds serving areas of Manhattan and Brooklyn, for which previous studies report decreased commuter mobility and residential populations. Our findings highlight the utility of ammonia mass load in influent wastewater as a population indicator to normalize wastewater-based epidemiology data and track sewershed population dynamics.

Looking Forward: The Role of Academic Researchers in Building Sustainable Wastewater Surveillance Programs.

BACKGROUND: In just over 2 years, tracking the COVID-19 pandemic through wastewater surveillance advanced from early reports of successful SARS-CoV-2 RNA detection in untreated wastewater to implementation of programs in at least 60 countries. Early wastewater monitoring efforts primarily originated in research laboratories and are now transitioning into more formal surveillance programs run in commercial and public health laboratories. A major challenge in this progression has been to simultaneously optimize methods and build scientific consensus while implementing surveillance programs, particularly during the rapidly changing landscape of the pandemic. Translating wastewater surveillance results for effective use by public health agencies also remains a key objective for the field. OBJECTIVES: We examined the evolution of wastewater surveillance to identify model collaborations and effective partnerships that have created rapid and sustained success. We propose needed areas of research and key roles academic researchers can play in the framework of wastewater surveillance to aid in the transition from early monitoring efforts to more formalized programs within the public health system. DISCUSSION: Although wastewater surveillance has rapidly developed as a useful public health tool for tracking COVID-19, there remain technical challenges and open scientific questions that academic researchers are equipped to address. This includes validating methodology and backfilling important knowledge gaps, such as fate and transport of surveillance targets and epidemiological links to wastewater concentrations. Our experience in initiating and implementing wastewater surveillance programs in the United States has allowed us to reflect on key barriers and draw useful lessons on how to promote synergy between different areas of expertise. As wastewater surveillance programs are formalized, the working relationships developed between academic researchers, commercial and public health laboratories, and data users should promote knowledge co-development. We believe active involvement of academic researchers will contribute to building robust surveillance programs that will ultimately provide new insights into population health. https://doi.org/10.1289/EHP11519.

Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917.

Surface water quality quantitative polymerase chain reaction (qPCR) technologies are expanding from a subject of research to routine environmental and public health laboratory testing. Readily available, reliable reference material is needed to interpret qPCR measurements, particularly across laboratories. Standard Reference Material® 2917 (NIST SRM® 2917) is a DNA plasmid construct that functions with multiple water quality qPCR assays allowing for estimation of total fecal pollution and identification of key fecal sources. This study investigates SRM 2917 interlaboratory performance based on repeated measures of 12 qPCR assays by 14 laboratories (n = 1008 instrument runs). Using a Bayesian approach, single-instrument run data are combined to generate assay-specific global calibration models allowing for characterization of within- and between-lab variability. Comparable data sets generated by two additional laboratories are used to assess new SRM 2917 data acceptance metrics. SRM 2917 allows for reproducible single-instrument run calibration models across laboratories, regardless of qPCR assay. In addition, global models offer multiple data acceptance metric options that future users can employ to minimize variability, improve comparability of data across laboratories, and increase confidence in qPCR measurements.