R-3 Repository :: Browsing by Author "Stadler, Lauren B."

Browsing by Author "Stadler, Lauren B."

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Advancing methods for wastewater disease surveillance of antibiotic resistance and SARS-CoV-2
(2022-09-19) Lou, Esther; Stadler, Lauren B.
Wastewater-based epidemiology (WBE), which involves using biological indicators in sewage to provide information on the overall health of a community, is a powerful tool to monitor public health. WBE offers several advantages that make it complementary to conventional clinical surveillance: it is rapid and resource-efficient, enables broad monitoring of large populations, is able to detect symptomatic and asymptomatic infections, and is not biased by health seeking behavior or access to healthcare resources. Recent studies have shown that WBE is a powerful tool for estimating community-level prevalence of COVID-19 by measuring levels of SARS-CoV-2 RNA in wastewater, and for predicting the prevalence of clinical antibiotic resistance by screening wastewater for antibiotic resistance genes. Furthermore, WBE has enabled global collaboration through national (e.g., National Wastewater Surveillance System (NWSS) on COVID-19) and international (e.g., the Enhanced Gonococcal Antimicrobial Surveillance Program) programs to advance the integration of WBE into public health response. Despite the surge of interest in applying WBE, there are currently no standardized methods for wastewater disease monitoring, including how and when to collect samples, what methods to use for analysis, and how to interpret the data to inform action. Without a more complete understanding of the methodological challenges involved in characterizing target indicators in wastewater samples, our ability to leverage WBE for routine monitoring and international collaboration is limited. This dissertation aims to evaluate the strengths and weaknesses of several current methods used for wastewater monitoring of antimicrobial resistance (AMR) and SARS-CoV-2 and discuss implications of method selection for future WBE work. The research focuses on four objectives, corresponding to the four chapters presented in this dissertation: (1) characterize the impact of wastewater sampling designs (i.e., grab and composite sampling) on the ARG removal rates achieved by a wastewater treatment plant (WWTP), (2) elucidate the fate of different forms of cell-associated and cell-free ARGs in an emerging wastewater treatment process, (3) compare two targeted methods (i.e., RT-ddPCR and targeted amplicon sequencing) for monitoring SARS-CoV-2 mutations in wastewater, and (4) evaluate short- and long-read metagenomics and a targeted method (epicPCR) for tracking ARG host range across a WWTP. Sampling design is critical to the collection of representative samples for WBE and for estimating removal rates of genes across wastewater treatment processes. We compared grab and composite sampling in terms of their effects on removal rates for a suite of genes, including several clinically-relevant ARGs (blaNDM-1, blaOXA-1, MCR-1, MCR-5, MCR-10, and qnrA). We find that the diurnal variation of ARG loading in the WWTP influent and effluent created significantly different instantaneous ARG removal rates among all grab samples collected throughout a day, indicating grab sampling can introduce bias to ARG removal calculations. Overall, using composite samples are more representative for WBE and for assessing removal of ARGs across wastewater treatment processes as compared to grab sampling which may overestimate ARG removal rates. The form of the ARG, specifically whether it is cell-free or cell-associated, is critical to understanding ARG removal across wastewater treatment processes. We found that the fraction of cell-associated ARGs decreased whereas the fraction of cell-free ARGs increased in the treated effluent as the influent organic loading rate was gradually increased. The results indicate that the ARGs in treated effluent can transit between cell-associated and cell-free DNA in response to changing operational conditions, which should be considered to better evaluate the total ARGs in the wastewater treatment system. WBE has been widely applied to track SARS-CoV-2 infections in communities and in some cases to identify circulating variants of concern. There are several different methods that have been applied to screen for variants of concern in wastewater. We compared targeted methods for screening for SARS-CoV-2 variants of concern in wastewater samples. The results demonstrated that RT-ddPCR is more sensitive and should be applied for mutation quantification or variant confirmation in wastewater, whereas detection via targeted amplicon sequencing was influenced by the depth of sequencing, viral load, and mutation concentration. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on targeted amplicon sequencing. We compared targeted and untargeted methods for ARG detection in wastewater. The results demonstrate that despite its significantly lower sequencing depth, long-read sequencing outperforms short-read sequencing with higher sensitivity for detecting ARGs, especially for ARGs associated with mobile genetic elements (MGEs). In addition, long-read sequencing consistently revealed a wider range of ARG hosts compared to short-read sequencing. Nonetheless, the host range detected by long-read sequencing represented only a subset of the host range detected by a targeted method, epicPCR (Emulsion, Paired Isolation, and Concatenation PCR). Taken together, the results have implications for future WBE, particularly in terms of method selection: 1) collect composite samples rather than grab samples to acquire a representative view of the monitoring targets in a population; 2) include different forms of DNA (cell-associated and cell-free) to analyze ARGs because effluent ARGs are present in both forms and can transition between these forms in response to environmental conditions; 3) apply RT-ddPCR for quantitative analysis and early variant detection if targets are known; and 4) use long-read sequencing for routine wastewater AMR surveillance and use epicPCR to obtain a high-resolution host range of clinically relevant ARGs. The findings provided by this research contribute to establishing a scientific consensus on method selection for WBE, thus advancing it as a routine tool for public health surveillance.
Crykey: Rapid identification of SARS-CoV-2 cryptic mutations in wastewater
(Springer Nature, 2024) Liu, Yunxi; Sapoval, Nicolae; Gallego-García, Pilar; Tomás, Laura; Posada, David; Treangen, Todd J.; Stadler, Lauren B.
Wastewater surveillance for SARS-CoV-2 provides early warnings of emerging variants of concerns and can be used to screen for novel cryptic linked-read mutations, which are co-occurring single nucleotide mutations that are rare, or entirely missing, in existing SARS-CoV-2 databases. While previous approaches have focused on specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and investigating their potential origin. We present Crykey, a tool for rapidly identifying rare linked-read mutations across the genome of SARS-CoV-2. We evaluated the utility of Crykey on over 3,000 wastewater and over 22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations in wastewater that represent potential circulating cryptic lineages, serving as a new computational tool for wastewater surveillance of SARS-CoV-2.
Enabling accurate and early detection of recently emerged SARS-CoV-2 variants of concern in wastewater
(Springer Nature, 2023) Sapoval, Nicolae; Liu, Yunxi; Lou, Esther G.; Hopkins, Loren; Ensor, Katherine B.; Schneider, Rebecca; Stadler, Lauren B.; Treangen, Todd J.
As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variant of concerns (VoCs) in communities. In this paper we present QuaID, a novel bioinformatics tool for VoC detection based on quasi-unique mutations. The benefits of QuaID are three-fold: (i) provides up to 3-week earlier VoC detection, (ii) accurate VoC detection (>95% precision on simulated benchmarks), and (iii) leverages all mutational signatures (including insertions & deletions).
Evaluating a gas biosensor for the measurement of conjugative transfer in wastewater communities
(2020-07-17) Rice, Eric W; Stadler, Lauren B.
Antibiotic resistance poses a threat to global public health causing simple infections to become untreatable and lead to potential fatality. Antibiotic resistance genes (ARGs) can be exchanged between microorganisms via horizontal gene transfer (HGT) enabling the rapid dissemination of resistance. HGT of ARGs present on broad host range plasmids (BHRP) can be transferred among phylogenetically distant bacteria. There is a need to characterize the bacteria that transfer BHRPs, as well as the transfer rates of BHRPs to inform antibiotic resistance mitigation strategies. This work is focused on the development and application of an engineered BHRP that reports on HGT by producing a volatile gas after HGT occurs. The project focused on characterizing the performance of this bioreporter in Escherichia coli. Specifically, the Escherichia coli was engineered as a donor of the BHRP reporter and its performance was measured. In addition, the reporter signal was transferred intraspecies to receiver Pseudomonas putida and gas output was characterized across several strains. Gas detection in complex matrices (e.g. wastewater) was also demonstrated. Results indicated that background donor signal, variability of gas production in transconjugant hosts, and gas degradation in activated sludge (AS) are important factors that must be accounted for to deploy the gas reporter in real wastewaters. Future research using targeted single-cell fusion PCR methods can be applied to characterize the hosts of the BHRP in a mixed community. Knowledge of BHRP hosts is critical to evaluate the risk of ARG spread between environmental and clinically-relevant pathogenic bacteria.
Impact of a natural disturbance on the performance and microbial communities in a full-scale constructed wetland for industrial wastewater treatment
(Frontiers Media S.A., 2023) Hollstein, Marielle; Comerford, Mattheau; Uhl, Michael; Abel, Michael; Egan, Scott P.; Stadler, Lauren B.
Constructed Wetlands (CWs) are a cost-effective, versatile and sustainable choice for wastewater treatment. In these environments, microbial communities play a significant role in pollutant removal. However, little is known about how microbial communities in full-scale CWs contribute to maintaining water quality or how their dynamics change in response to pulse disturbances such as fire or freezes. Furthermore, few studies have examined the relationship between CW microbial community structure and performance in full-scale industrial operations. We characterized the water-column and leaf-litter layer microbial communities in a 110-acre free water surface CW that provides tertiary wastewater treatment to a plastics manufacturing plant. The CW’s sampling campaign was conducted over a 12-month period that included Winter Storm Uri, a 100-year freeze event. Analysis of 16S rRNA gene amplicon sequences revealed that the bacterial communities experienced a temporal shift. There was also a shift in microbial community structure between the influent and the first segment of the CW. However, no differences in microbial community structure were observed in the second segment of the CW. There was a negative association between microbial community diversity and chlorophyll a, as well as microbial community diversity and total suspended solids (TSS); demonstrating an increase in microbial biodiversity as water quality improved throughout the CW. Six months after the freeze, CW performance in terms of removal of water quality constituents began to return to former removal trends. Yet, there was still a significant difference in microbial community structure within the CW relative to the previous year. This suggests CW functional resilience despite a shift in microbial community structure in the wetland.
Olivar: towards automated variant aware primer design for multiplex tiled amplicon sequencing of pathogens
(Springer Nature, 2024) Wang, Michael X.; Lou, Esther G.; Sapoval, Nicolae; Kim, Eddie; Kalvapalle, Prashant; Kille, Bryce; Elworth, R. A. Leo; Liu, Yunxi; Fu, Yilei; Stadler, Lauren B.; Treangen, Todd J.; Bioengineering; Civil and Environmental Engineering; Computer Science
Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 15 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly. Here we present Olivar, a first step towards a fully automated, variant-aware design of tiled amplicons for pathogen genomes. Olivar converts each nucleotide of the target genome into a numeric risk score, capturing undesired sequence features that should be avoided. In a direct comparison with PrimalScheme, we show that Olivar has fewer mismatches overlapping with primers and predicted PCR byproducts. We also compare Olivar head-to-head with ARTIC v4.1, the most widely used primer set for SARS-CoV-2 sequencing, and show Olivar yields similar read mapping rates (~90%) and better coverage to the manually designed ARTIC v4.1 amplicons. We also evaluate Olivar on real wastewater samples and found that Olivar has up to 3-fold higher mapping rates while retaining similar coverage. In summary, Olivar automates and accelerates the generation of tiled amplicons, even in situations of high mutation frequency and/or density. Olivar is available online as a web application at https://olivar.rice.edu and can be installed locally as a command line tool with Bioconda. Source code, installation guide, and usage are available at https://github.com/treangenlab/Olivar.
On a Reef Far, Far Away: Anthropogenic Impacts Following Extreme Storms Affect Sponge Health and Bacterial Communities
(Frontiers Media S.A., 2021) Shore, Amanda; Sims, Jordan A.; Grimes, Michael; Howe-Kerr, Lauren I.; Grupstra, Carsten G.B.; Doyle, Shawn M.; Stadler, Lauren B.; Sylvan, Jason B.; Shamberger, Kathryn E.F.; Davies, Sarah W.; Santiago-Vázquez, Lory Z.; Correa, Adrienne M.S.
Terrestrial runoff can negatively impact marine ecosystems through stressors including excess nutrients, freshwater, sediments, and contaminants. Severe storms, which are increasing with global climate change, generate massive inputs of runoff over short timescales (hours to days); such runoff impacted offshore reefs in the northwest Gulf of Mexico (NW GoM) following severe storms in 2016 and 2017. Several weeks after coastal flooding from these events, NW GoM reef corals, sponges, and other benthic invertebrates ~185 km offshore experienced mortality (2016 only) and/or sub-lethal stress (both years). To assess the impact of storm-derived runoff on reef filter feeders, we characterized the bacterial communities of two sponges, Agelas clathrodes and Xestospongia muta, from offshore reefs during periods of sub-lethal stress and no stress over a three-year period (2016-2018). Sponge-associated and seawater-associated bacterial communities were altered during both flood years. Additionally, we found evidence of wastewater contamination (based on 16S rRNA gene libraries and quantitative PCR) in offshore sponge samples, but not in seawater samples, following these flood years. Signs of wastewater contamination were absent during the no-flood year. We show that flood events from severe storms have the capacity to reach offshore reef ecosystems and impact resident benthic organisms. Such impacts are most readily detected if baseline data on organismal physiology and associated microbiome composition are available. This highlights the need for molecular and microbial time series of benthic organisms in near- and offshore reef ecosystems, and the continued mitigation of stormwater runoff and climate change impacts.
Online trend estimation and detection of trend deviations in sub-sewershed time series of SARS-CoV-2 RNA measured in wastewater
(Springer Nature, 2024) Ensor, Katherine B.; Schedler, Julia C.; Sun, Thomas; Schneider, Rebecca; Mulenga, Anthony; Wu, Jingjing; Stadler, Lauren B.; Hopkins, Loren
Wastewater surveillance has proven a cost-effective key public health tool to understand a wide range of community health diseases and has been a strong source of information on community levels and spread for health departments throughout the SARS- CoV-2 pandemic. Studies spanning the globe demonstrate the strong association between virus levels observed in wastewater and quality clinical case information of the population served by the sewershed. Few of these studies incorporate the temporal dependence present in sampling over time, which can lead to estimation issues which in turn impact conclusions. We contribute to the literature for this important public health science by putting forward time series methods coupled with statistical process control that (1) capture the evolving trend of a disease in the population; (2) separate the uncertainty in the population disease trend from the uncertainty due to sampling and measurement; and (3) support comparison of sub-sewershed population disease dynamics with those of the population represented by the larger downstream treatment plant. Our statistical methods incorporate the fact that measurements are over time, ensuring correct statistical conclusions. We provide a retrospective example of how sub-sewersheds virus levels compare to the upstream wastewater treatment plant virus levels. An on-line algorithm supports real-time statistical assessment of deviations of virus level in a population represented by a sub-sewershed to the virus level in the corresponding larger downstream wastewater treatment plant. This information supports public health decisions by spotlighting segments of the population where outbreaks may be occurring.
Snapshot ARG Removal Rates across Wastewater Treatment Plants Are Not Representative Due to Diurnal Variations
(American Chemical Society, 2023) Lou, Esther G.; Ali, Priyanka; Lu, Karen; Kalvapalle, Prashant; Stadler, Lauren B.
To evaluate the threat of the environmental dissemination of antibiotic resistance associated with wastewater treatment plants (WWTPs), the removal efficiency of antibiotic resistance genes (ARGs) during wastewater treatment needs to be assessed. The sample collection strategy is one factor that is often overlooked in study design and most studies on ARGs in wastewater perform grab sampling. Here, we hypothesized that wastewater sampling (i.e., grab and composite sampling) influences the observed ARG concentrations and calculated removal rates across WWTPs. We compared the removal rates calculated based on the two different sampling methods for several genes, including some clinically relevant ARGs (blaNDM-1, blaOXA-1, MCR-1, MCR-5, MCR-10, and qnrA). We conducted summer and winter 24 h sampling campaigns where grab samples were collected every 2 h from the influent, secondary effluent, and final effluent. The snapshot removal rate of each target gene calculated based on the 12 grab samples fluctuated by 0.5–1.6 log in the winter and 0.9–2.7 log in the summer, indicating diurnal variation. Overall, for each target gene, the removal rates calculated based on 24 h composite samples were approximately equal to the median of the 12 snapshot removal rates. Our study confirms the importance of using composite samples to monitor ARGs in wastewater.
Standardizing data reporting in the research community to enhance the utility of open data for SARS-CoV-2 wastewater surveillance
(Royal Society of Chemistry, 2021) McClary-Gutierrez, Jill S.; Aanderud, Zachary T.; Al-faliti, Mitham; Duvallet, Claire; Gonzalez, Raul; Guzman, Joe; Holm, Rochelle H.; Jahne, Michael A.; Kantor, Rose S.; Katsivelis, Panagis; Kuhn, Katrin Gaardbo; Langan, Laura M.; Mansfeldt, Cresten; McLellan, Sandra L.; Grijalva, Lorelay M. Mendoza; Murnane, Kevin S.; Naughton, Colleen C.; Packman, Aaron I.; Paraskevopoulos, Sotirios; Radniecki, Tyler S.; Roman, Fernando A.; Shrestha, Abhilasha; Stadler, Lauren B.; Steele, Joshua A.; Swalla, Brian M.; Vikesland, Peter; Wartell, Brian; Wilusz, Carol J.; Wong, Judith Chui Ching; Boehm, Alexandria B.; Halden, Rolf U.; Bibby, Kyle; Vela, Jeseth Delgado
SARS-CoV-2 RNA detection in wastewater is being rapidly developed and adopted as a public health monitoring tool worldwide. With wastewater surveillance programs being implemented across many different scales and by many different stakeholders, it is critical that data collected and shared are accompanied by an appropriate minimal amount of meta-information to enable meaningful interpretation and use of this new information source and intercomparison across datasets. While some databases are being developed for specific surveillance programs locally, regionally, nationally, and internationally, common globally-adopted data standards have not yet been established within the research community. Establishing such standards will require national and international consensus on what meta-information should accompany SARS-CoV-2 wastewater measurements. To establish a recommendation on minimum information to accompany reporting of SARS-CoV-2 occurrence in wastewater for the research community, the United States National Science Foundation (NSF) Research Coordination Network on Wastewater Surveillance for SARS-CoV-2 hosted a workshop in February 2021 with participants from academia, government agencies, private companies, wastewater utilities, public health laboratories, and research institutes. This report presents the primary two outcomes of the workshop: (i) a recommendation on the set of minimum meta-information that is needed to confidently interpret wastewater SARS-CoV-2 data, and (ii) insights from workshop discussions on how to improve standardization of data reporting.
Translating New Synthetic Biology Advances for Biosensing Into the Earth and Environmental Sciences
(Frontiers, 2021) Del Valle, Ilenne; Fulk, Emily M.; Kalvapalle, Prashant; Silberg, Jonathan J.; Masiello, Caroline A.; Stadler, Lauren B.; Bioengineering; Biosciences; Chemical and Biomolecular Engineering; Chemistry; Civil and Environmental Engineering
The rapid diversification of synthetic biology tools holds promise in making some classically hard-to-solve environmental problems tractable. Here we review longstanding problems in the Earth and environmental sciences that could be addressed using engineered microbes as micron-scale sensors (biosensors). Biosensors can offer new perspectives on open questions, including understanding microbial behaviors in heterogeneous matrices like soils, sediments, and wastewater systems, tracking cryptic element cycling in the Earth system and establishing the dynamics of microbe-microbe, microbe-plant, and microbe-material interactions. Before these new tools can reach their potential, however, a suite of biological parts and microbial chassis appropriate for environmental conditions must be developed by the synthetic biology community. This includes diversifying sensing modules to obtain information relevant to environmental questions, creating output signals that allow dynamic reporting from hard-to-image environmental materials, and tuning these sensors so that they reliably function long enough to be useful for environmental studies. Finally, ethical questions related to the use of synthetic biosensors in environmental applications are discussed.
Using synthetic biology to record information in DNA and RNA within wastewater microbes and communities
(2023-08-02) Kalvapalle, Prashant Bharadwaj; Stadler, Lauren B.; Silberg, Jonathan J.
Microorganisms form the bedrock of key ecological processes that make the Earth habitable. Microbial communities regulate carbon and nitrogen cycles, influencing greenhouse gas concentrations and agricultural productivity. As such, understanding these microbial processes is critical to address climate change and food security and to advance sustainable practices. Microbial communities within wastewater are also critical to public health, such as through the exchange of genetic material, which can result in more virulent pathogens, and resistance to known antibiotic treatments. Engineered microbial sensors can be developed to gather information and understand the influence of physicochemical conditions of the environment. To date, the majority of biosensors developed rely on fluorescent outputs, which are challenging to apply in environmental matrices that are opaque, and contain autofluorescent particles or microbes. In addition, few biosensors have been applied over timescales relevant to ecological processes, and there is a need for biosensors that function over week-long timescales in situ. In this thesis, I describe biosensors that record signals by modifying DNA and RNA, which are designed to monitor chemical exposures and gene exchange within natural environments, respectively. I benchmark the performance of these sensor systems within undomesticated, wastewater microbes. I demonstrate that the DNA biosensor can record analog information about the exposure to a sugar arabinose and microbial communication molecule 3-oxo-C12-homoserine lactone. I describe strategies that can be used to allow these DNA memory biosensors to record information during 9 day incubations. Additionally, I demonstrate that a new type of RNA memory sensor is able to function in a wide variety of wastewater taxa, which writes information in 16S ribosomal RNA. In the first proof-of-concept experiments, I show this sensor can record information in more than 100 microbes in parallel. Together, the tools extend the tools available to environmental microbiologists for detecting microbial processes in complex environments, leading to insights of environmental and public health importance. The longer duration DNA biosensor will be useful for studying the bioavailability of chemicals in situ, while the community distributed RNA memory sensor will be useful for identifying the taxonomic range of gene transfer recipients in a high-throughput manner.
Wastewater surveillance of SARS-CoV-2 and influenza in preK-12 schools shows school, community, and citywide infections
(Elsevier, 2023) Wolken, Madeline; Sun, Thomas; McCall, Camille; Schneider, Rebecca; Caton, Kelsey; Hundley, Courtney; Hopkins, Loren; Ensor, Katherine; Domakonda, Kaavya; Prashant, Kalvapalle; Persse, David; Williams, Stephen; Stadler, Lauren B.
Wastewater surveillance is a passive and efficient way to monitor the spread of infectious diseases in large populations and high transmission areas such as preK-12 schools. Infections caused by respiratory viruses in school-aged children are likely underreported, particularly because many children may be asymptomatic or mildly symptomatic. Wastewater monitoring of SARS-CoV-2 has been studied extensively and primarily by sampling at centralized wastewater treatment plants, and there are limited studies on SARS-CoV-2 in preK-12 school wastewater. Similarly, wastewater detections of influenza have only been reported in wastewater treatment plant and university manhole samples. Here, we present the results of a 17-month wastewater monitoring program for SARS-CoV-2 (n = 2176 samples) and influenza A and B (n = 1217 samples) in 51 preK-12 schools. We show that school wastewater concentrations of SARS-CoV-2 RNA were strongly associated with COVID-19 cases in schools and community positivity rates, and that influenza detections in school wastewater were significantly associated with citywide influenza diagnosis rates. Results were communicated back to schools and local communities to enable mitigation strategies to stop the spread, and direct resources such as testing and vaccination clinics. This study demonstrates that school wastewater surveillance is reflective of local infections at several population levels and plays a crucial role in the detection and mitigation of outbreaks.

Browsing by Author "Stadler, Lauren B."

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