Coupling physiochemical adsorption with biodegradation for enhanced removal of microcystin-LR in water.

To innovate the design of water treatment technology for algal toxin removal, this research investigated the mechanisms of cyanotoxin microcystin-LR (MC-LR) removal by a coupled adsorption-biodegradation. Eight types of woody carbonaceous adsorbents with and without Sphingopyxis sp. m6, a MC-LR degrading bacterium, were tested for MC-LR removal in water. All adsorbents showed good adsorption capability, removing 40 % to almost 100 % of the MC-LR (4.5 mg/L) within 48 h in batch experiments. Adding Sphingopyxis sp. m6 continuously promoted MC-LR biological removal, and successfully broke the barrier of adsorption capacity of tested adsorbents, removing >90 % of the MC-LR in most of the coupled adsorption-biodegradation tests, especially for those adsorbents had low physiochemical adsorption capacity. Variance partitioning analysis indicated that mesopore was the dominant contributor to adsorption capacity of MC-LR in pure adsorption treatments, which acted synergistically with electrical conductivity, polarity and total functional groups on the absorbent. Pore structure was the key factor beneficial for the growth of Sphingopyxis sp. m6 (51% contribution) and subsequent MC-LR biological removal rate (80 % contribution). Overall, pinewood-based carbonaceous adsorbents (especially pinewood activated carbon) exhibited the highest adsorption capacity towards MC-LR and provided the most favorable conditions for biological removal of MC-LR, largely because of their high mesopore volume, total functional groups and electric conductivity. The research outcomes not only deepened the quantitative understanding of mechanisms for MC-LR removal by the coupled process, but also provided theoretical basis for future materials' selection and modification during the practical application of coupled process.

Metagenomic Methods for Addressing NASA's Planetary Protection Policy Requirements on Future Missions: A Workshop Report.

Molecular biology methods and technologies have advanced substantially over the past decade. These new molecular methods should be incorporated among the standard tools of planetary protection (PP) and could be validated for incorporation by 2026. To address the feasibility of applying modern molecular techniques to such an application, NASA conducted a technology workshop with private industry partners, academics, and government agency stakeholders, along with NASA staff and contractors. The technical discussions and presentations of the Multi-Mission Metagenomics Technology Development Workshop focused on modernizing and supplementing the current PP assays. The goals of the workshop were to assess the state of metagenomics and other advanced molecular techniques in the context of providing a validated framework to supplement the bacterial endospore-based NASA Standard Assay and to identify knowledge and technology gaps. In particular, workshop participants were tasked with discussing metagenomics as a stand-alone technology to provide rapid and comprehensive analysis of total nucleic acids and viable microorganisms on spacecraft surfaces, thereby allowing for the development of tailored and cost-effective microbial reduction plans for each hardware item on a spacecraft. Workshop participants recommended metagenomics approaches as the only data source that can adequately feed into quantitative microbial risk assessment models for evaluating the risk of forward (exploring extraterrestrial planet) and back (Earth harmful biological) contamination. Participants were unanimous that a metagenomics workflow, in tandem with rapid targeted quantitative (digital) PCR, represents a revolutionary advance over existing methods for the assessment of microbial bioburden on spacecraft surfaces. The workshop highlighted low biomass sampling, reagent contamination, and inconsistent bioinformatics data analysis as key areas for technology development. Finally, it was concluded that implementing metagenomics as an additional workflow for addressing concerns of NASA's robotic mission will represent a dramatic improvement in technology advancement for PP and will benefit future missions where mission success is affected by backward and forward contamination.

Integrating Virus Monitoring Strategies for Safe Non-potable Water Reuse.

Wastewater reclamation and reuse have the potential to supplement water supplies, offering resiliency in times of drought and helping meet increased water demands associated with population growth. Non-potable water reuse represents the largest potential reuse market. Yet economic constraints for new water reuse infrastructure and safety concerns due to microbial water quality, and especially viral pathogen exposure, limit widespread implementation of water reuse. Cost-effective, real-time methods to measure or indicate viral quality of recycled water would do much to instill greater confidence in the practice. This manuscript discusses advancements in monitoring and modeling of viral health risks in the context of water reuse. First, we describe the current wastewater reclamation processes and treatment technologies with an emphasis on virus removal. Second, we review technologies for the measurement of viruses, both culture- and molecular-based, along with their advantages and disadvantages. We introduce promising viral surrogates and specific pathogenic viruses that can serve as indicators of viral risk for water reuse. We suggest metagenomic analyses for viral screening and flow cytometry for quantification of virus-like particles as new approaches to complement more traditional methods. Third, we describe modeling to assess health risks through quantitative microbial risk assessments (QMRAs), the most common strategy to couple data on virus concentrations with human exposure scenarios. We then explore the potential of artificial neural networks (ANNs) to incorporate suites of data from wastewater treatment processes, water quality parameters, and viral surrogates. We recommend ANNs as a means to utilize existing water quality data, alongside new complementary measures of viral quality, to achieve cost-effective strategies to assess risks associated with infectious human viruses in recycled water. Given the review, we conclude that technologies are ready for identifying and implementing viral surrogates for health risk reduction in the next decade. Incorporating modeling with monitoring data would likely result in more robust assessment of water reuse risk.

Development of a proof-of-concept microfluidic portable pathogen analysis system for water quality monitoring.

Waterborne diseases cause millions of deaths worldwide, especially in developing communities. The monitoring and rapid detection of microbial pathogens in water is critical for public health protection. This study reports the development of a proof-of-concept portable pathogen analysis system (PPAS) that can detect bacteria in water with the potential application in a point-of-sample collection setting. A centrifugal microfluidic platform is adopted to integrate bacterial cell lysis in water samples, nucleic acid extraction, and reagent mixing with a droplet digital loop mediated isothermal amplification assay for bacteria quantification onto a single centrifugal disc (CD). Coupled with a portable "CD Driver" capable of automating the assay steps, the CD functions as a single step bacterial detection "lab" without the need to transfer samples from vial-to-vial as in a traditional laboratory. The prototype system can detect Enterococcus faecalis, a common fecal indicator bacterium, in water samples with a single touch of a start button within 1 h and having total hands-on-time being less than 5 min. An add-on bacterial concentration cup prefilled with absorbent polymer beads was designed to integrate with the pathogen CD to improve the downstream quantification sensitivity. All reagents and amplified products are contained within the single-use disc, reducing the opportunity of cross contamination of other samples by the amplification products. This proof-of-concept PPAS lays the foundation for field testing devices in areas needing more accessible water quality monitoring tools and are at higher risk for being exposed to contaminated waters.

16S rRNA gene sequencing data of the human skin microbiome before and after swimming in the ocean.

These data represent the abundance, diversity and predicted function gene profiles of the microbial communities present on human skin before and after swimming in the ocean. The skin microbiome has been shown to provide protection against infection from pathogenic bacteria. It is well-known that exposure to ocean water can cause skin infection, but little is known about how exposure can alter the bacterial communities on the skin. Skin microbiome samples were collected from human participants before and after swimming in the ocean. These data were used to analyze the changes in abundance and diversity of microbial communities on the skin and the changes in the functional profiles of the bacteria, specifically focusing on genes involved in antibiotic resistance and bacterial virulence.

A dose response model for Staphylococcus aureus.

Dose-response models (DRMs) are used to predict the probability of microbial infection when a person is exposed to a given number of pathogens. In this study, we propose a new DRM for Staphylococcus aureus (SA), which causes skin and soft-tissue infections. The current approach to SA dose-response is only partially mechanistic and assumes that individual bacteria do not interact with each other. Our proposed two-compartment (2C) model assumes that bacteria that have not adjusted to the host environment decay. After adjusting to the host, they exhibit logistic/cooperative growth, eventually causing disease. The transition between the adjusted and un-adjusted states is a stochastic process, which the 2C DRM explicitly models to predict response probabilities. By fitting the 2C model to SA pathogenesis data, we show that cooperation between individual SA bacteria is sufficient (and, within the scope of the 2C model, necessary) to characterize the dose-response. This is a departure from the classical single-hit theory of dose-response, where complete independence is assumed between individual pathogens. From a quantitative microbial risk assessment standpoint, the mechanistic basis of the 2C DRM enables transparent modeling of dose-response of antibiotic-resistant SA that has not been possible before. It also enables the modeling of scenarios having multiple/non-instantaneous exposures, with minimal assumptions.

Acquisition of antibiotic resistance genes on human skin after swimming in the ocean.

The skin is a complex organ responsible for protecting the body from physical, chemical and biological insults. The skin microbiome is known to play an important role in protecting the host from skin infections. This study examined the skin microbiome and the changes in antibiotic resistance genes (ARGs), antibiotic biosynthesis genes (ABSGs) and virulence factor genes (VFGs) on human skin before and after swimming in the ocean. Skin microbiome samples were collected from human participants before and after they swam in the ocean, and at 6 h and 24 h post-swim. The samples were analyzed using 16S rRNA gene and shotgun metagenomic sequencing. The results showed that not only is the skin microbiome composition altered after swimming, but the abundance and diversity of ARGs, ABSGs and VFGs on the skin increased post-swim. Overall, there was an increase in total ARGs by 70.6% from before to after swimming. The elevated number of ARGs persisted and continued to increase for at least 6 h post-swim with greater than a 300% increase in comparison with samples collected before ocean swimming. The outcomes of the study support the epidemiological observations of increased risk of skin infections after swimming in the ocean. Cleaning the skin immediately after recreational ocean activities is recommended to reduce the opportunity for infection.

Efficient removal of selenate in water by cationic poly(allyltrimethylammonium) grafted chitosan and biochar composite.

The discovery of cheap and eco-friendly functional materials for the removal of anionic heavy metal ions is still challenging in the treatment of heavy metal-contaminated water. Herein, a new poly(allyltrimethylammonium) grafted chitosan and biochar composite (PATMAC-CTS-BC) was introduced for the removal of selenate (SeO42-) in water. Results suggest that the PATMAC-CTS-BC showed a rapid removal of SeO42- with efficiency of >97% within 10 min and it followed a pseudo-second-order model. High capacity of SeO42- adsorption by the composite was achieved, with maximum value of 98.99 mg g-1 based on Langmuir model, considerably higher than most of reported adsorbents. The thermodynamic results reflected the spontaneous and exothermic nature of SeO42- adsorption onto the composite. The composite could be applied at a wide initial pH range (2-10) with high removal efficiency of SeO42- because of permanent positive charges of quaternary ammonium groups (=N+-). The removal mechanisms of SeO42- were mainly attributed to electrostatic interactions with =N+- and protonated -NH3+ groups, and redox-complexation interactions with -NH2, -NH-, and -OH groups. Besides SeO42-, the hexavalent chromium (Cr2O72-) was considered as example to further demonstrate the anion removal capability of cationic hydrogel-BC composite. The study outcomes open up new opportunities to efficiently remove anionic heavy metal ions (e.g., SeO42- and Cr2O72-) in water using these materials.

Quantifying the risk of indoor drainage system in multi-unit apartment building as a transmission route of SARS-CoV-2.

The COVID-19 pandemic has had a profound impact on human society. The isolation of SARS-CoV-2 from patients' feces on human cell line raised concerns of possible transmission through human feces including exposure to aerosols generated by toilet flushing and through the indoor drainage system. Currently, routes of transmission, other than the close contact droplet transmission, are still not well understood. A quantitative microbial risk assessment was conducted to estimate the health risks associated with two aerosol exposure scenarios: 1) toilet flushing, and 2) faulty connection of a floor drain with the building's main sewer pipe. SARS-CoV-2 data were collected from the emerging literature. The infectivity of the virus in feces was estimated based on a range of assumption between viral genome equivalence and infectious unit. The human exposure dose was calculated using Monte Carlo simulation of viral concentrations in aerosols under each scenario and human breathing rates. The probability of COVID-19 illness was generated using the dose-response model for SARS-CoV-1, a close relative of SARS-CoV-2, that was responsible for the SARS outbreak in 2003. The results indicate the median risks of developing COVID-19 for a single day exposure is 1.11 × 10-10 and 3.52 × 10-11 for toilet flushing and faulty drain scenario, respectively. The worst case scenario predicted the high end of COVID-19 risk for the toilet flushing scenario was 5.78 × 10-4 (at 95th percentile). The infectious viral loads in human feces are the most sensitive input parameter and contribute significantly to model uncertainty.

Can cyanotoxins penetrate human skin during water recreation to cause negative health effects?

Cyanobacteria blooms and associated cyanotoxins pose significant public health risks during water recreation. Oral ingestion is the only recognized route of toxin exposure in water recreation guidelines. This review examines human skin as a barrier for the prevention of cyanotoxin absorption and investigates the likelihood of negative health effects through dermal exposure. Epidemiological studies of health effects from recreational exposure to algal blooms and toxins are summarized to highlight the importance of better understanding the toxicological effect of dermal exposure. The ability of a specific cyanotoxin to penetrate human skin is inferred by its physiochemical properties according to transdermal drug studies. The review identifies a disparity between the human health effects described in algal bloom exposure case studies and the toxicological skin exposure data. Skin penetration by algal toxins is likely and deserves further investigation.

When the fourth water and digital revolution encountered COVID-19.

The ongoing COVID-19 pandemic is, undeniably, a substantial shock to our civilization which has revealed the value of public services that relate to public health. Ensuring a safe and reliable water supply and maintaining water sanitation has become ever more critical during the pandemic. For this reason, researchers and practitioners have promptly investigated the impact associated with the spread of SARS-CoV-2 on water treatment processes, focusing specifically on water disinfection. However, the COVID-19 pandemic impacts multiple aspects of the urban water sector besides those related to the engineering processes, including sanitary, economic, and social consequences which can have significant effects in the near future. Furthermore, this outbreak appears at a time when the water sector was already experiencing a fourth revolution, transitioning toward the digitalisation of the sector, which redefines the Water-Human-Data Nexus. In this contribution, a product of collaboration between academics and practitioners from water utilities, we delve into the multiple impacts that the pandemic is currently causing and their possible consequences in the future. We show how the digitalisation of the water sector can provide useful approaches and tools to help address the impact of the pandemic. We expect this discussion to contribute not only to current challenges, but also to the conceptualization of new projects and the broader task of ameliorating climate change.

Mitigation of biofouling in agricultural water distribution systems with nanobubbles.

Biofouling poses considerable technical challenges to agricultural irrigation systems. Controlling biofouling with strong chemical biocides is not only expensive and sometimes ineffective, but also contributes to environmental pollution. This study investigated the application of nanobubbles (NBs) on minimizing biofouling in agricultural irrigation water pipelines. Treatment performances were assessed using low concentration bubbles (LCB) and high concentration bubbles (HCB) together with a negative control (CK: no-NBs). 16 s rRNA gene sequencing and X-ray diffraction were used to characterize the microbial community and mineral compositions of biofilms in water emitters. Results demonstrated that NBs effectively mitigated biofouling through reducing fixed-biomass by 31.3-52.1%. A significantly different microbial composition was found in the biofilm community with reduced biodiversity. Molecular ecological network analysis revealed that NBs were detrimental to the mutualistic interactions among microbial species - destabilizing the network complexity and size, which was expressed as decreasing in extracellular polymers and biofilm biomass. Furthermore, NBs significantly decreased the deposition of carbonate, silicate, phosphate, and quartz on the pipe surfaces, leading to reductions of total content of minerals in biofilms. Therefore, this study demonstrated that NBs treatment could be an effective, and eco-friendly solution for biofouling control in agricultural water distribution systems.

Assessing the water quality impacts of two Category-5 hurricanes on St. Thomas, Virgin Islands.

Managing waterborne and water-related diseases is one of the most critical factors in the aftermath of hurricane-induced natural disasters. The goal of the study was to identify water-quality impairments in order to set the priorities for post-hurricane relief and to guide future decisions on disaster preparation and relief administration. Field investigations were carried out on St. Thomas, U.S. Virgin Islands as soon as the disaster area became accessible after the back-to-back hurricane strikes by Irma and Maria in 2017. Water samples were collected from individual household rain cisterns, the coastal ocean, and street-surface runoffs for microbial concentration. The microbial community structure and the occurrence of potential human pathogens were investigated in samples using next generation sequencing. Loop mediated isothermal amplification was employed to detect fecal indicator bacteria, Enterococcus faecalis. The results showed both fecal indicator bacteria and Legionella genetic markers were prevalent but were low in concentration in the water samples. Among the 22 cistern samples, 86% were positive for Legionella and 82% for Escherichia-Shigella. Enterococcus faecalis was detected in over 68% of the rain cisterns and in 60% of the coastal waters (n = 20). Microbial community composition in coastal water samples was significantly different from cistern water and runoff water. Although identification at bacterial genus level is not direct evidence of human pathogens, our results suggest cistern water quality needs more organized attention for protection of human health, and that preparation and prevention measures should be taken before natural disasters strike.

A dose response model for quantifying the infection risk of antibiotic-resistant bacteria.

Quantifying the human health risk of microbial infection helps inform regulatory policies concerning pathogens, and the associated public health measures. Estimating the infection risk requires knowledge of the probability of a person being infected by a given quantity of pathogens, and this relationship is modeled using pathogen specific dose response models (DRMs). However, risk quantification for antibiotic-resistant bacteria (ARB) has been hindered by the absence of suitable DRMs for ARB. A new approach to DRMs is introduced to capture ARB and antibiotic-susceptible bacteria (ASB) dynamics as a stochastic simple death (SD) process. By bridging SD with data from bench experiments, we demonstrate methods to (1) account for the effect of antibiotic concentrations and horizontal gene transfer on risk; (2) compute total risk for samples containing multiple bacterial types (e.g., ASB, ARB); and (3) predict if illness is treatable with antibiotics. We present a case study of exposure to a mixed population of Gentamicin-susceptible and resistant Escherichia coli and predict the health outcomes for varying Gentamicin concentrations. Thus, this research establishes a new framework to quantify the risk posed by ARB and antibiotics.

Alterations of the human skin microbiome after ocean water exposure.

Skin is the body's first line of defense against invading microorganisms. The skin microbiome has been shown to provide immunity against exogenous bacterial colonization. Recreational water exposures may alter the skin microbiome and potentially induce skin infections. This study explored the link between ocean water exposures and the human skin microbiome. Skin microbiome samples were collected, using swabs, from human participants' calves before and after they swam in the ocean, and at 6 hour and 24 hour post-swim. Genomic analysis showed that skin microbiomes were different among individuals before swimming. But after swimming, microbial communities were no longer different, which was demonstrated by a decrease in inter-sample diversity. Taxonomic analysis showed that ocean bacteria, including potential pathogens, replaced the native skin bacteria and remained on the skin for at least 24 hour post-swim. This research provides insight into the relationship between the human skin microbiome and the environment.

Storm runoff differentially influences the nutrient concentrations and microbial contamination at two distinct beaches in northern China.

With the escalating coastal development and loss of vegetated landscape, the volume of storm runoff increases significantly in Chinese coastal cities. To protect human health and valuable recreational resources, it is necessary to develop a quantitative understanding of coastal pollution. Here we studied the influence of storm runoff on the nutrients and microbial pathogens at two popular bathing beaches in northern China. Dongshan Beach, located near the mouth of an urban river, is influenced by non-point source pollution while Tiger-Rock Beach, a coastal beach, is primarily influenced by a point source from a storm drain outfall. Storm runoff significantly (P < 0.001) decreased the salinity and Chl a post-storm at both the beaches, but only reduced the concentration of dissolved inorganic N at Tiger-Rock Beach. Escherichia coli decreased by 68.7% at Dongshan Beach, possibly due to the dilution effect of the stormflow, contradicting the notion of elevated fecal contamination in coastal beaches from storm runoff. Vibrio parahaemolyticus increased at both beaches post-storm, by 155.7% at Dongshan Beach and 136.7% at Tiger-Rock Beach. Regardless of storm impact, both E. coli and V. parahaemolyticus were much higher at Dongshan Beach than that at Tiger-Rock, suggesting the influence of different surrounding topographies. Lastly, the statistical models developed based on the environmental and microbial parameters regression showed predictive power (adjusted R2 > 0.5) to estimate the concentration of E. coli at Dongshan Beach and V. parahaemolyticus at Tiger-Rock Beach. Overall, the results suggest the unique role of the individual beaches in attenuating the effect of rainfall on the concentration of microbial pathogens in bathing water quality and provide unique predictive models for recreational water management and public health protection.

Application of unstructured kinetic models to predict microcystin biodegradation: Towards a practical approach for drinking water treatment.

Biological drinking water treatment technologies offer a cost-effective and sustainable approach to mitigate microcystin (MC) toxins from harmful algal blooms. To effectively engineer these systems, an improved predictive understanding of the bacteria degrading these toxins is required. This study reports an initial comparison of several unstructured kinetic models to describe MC microbial metabolism by isolated degrading populations. Experimental data was acquired from the literature describing both MC removal and cell growth kinetics when MC was utilized as the primary carbon and energy source. A novel model-data calibration approach melding global single-objective, multi-objective, and Bayesian optimization in addition to a fully Bayesian approach to model selection and hypothesis testing were applied to identify and compare parameter and predictive uncertainties associated with each model structure. The results indicated that models incorporating mechanisms of enzyme-MC saturation, affinity, and cooperative binding interactions of a theoretical single, rate limiting reaction accurately and reliably predicted MC degradation and bacterial growth kinetics. Diverse growth characteristics were observed among MC degraders, including moderate to high maximum specific growth rates, very low to substantial affinities for MC, high yield of new biomass, and varying degrees of cooperative enzyme-MC binding. Model predictions suggest that low specific growth rates and MC removal rates of degraders are expected in practice, as MC concentrations in the environment are well below saturating levels for optimal growth. Overall, this study represents an initial step towards the development of a practical and comprehensive kinetic model to describe MC biodegradation in the environment.

A dynamic transport model for quantification of norovirus internalization in lettuce from irrigation water and associated health risk.

Food production using recycled wastewater offers a sustainable way forward in light of limited freshwater resources. However, concerns of food safety should be addressed to protect public health. To this end, we developed a dynamic transport model to track norovirus from the irrigation water to the root and shoot of lettuce during the growth period. These processes were embodied in a system of ordinary differential equations that also incorporated plant growth, transpiration rate, viral attachment and detachment to culture media, viral decay, and plant barrier effects. Model parameters were either obtained from the literature or through fitting the model to experimental data from a study reporting human norovirus transport in hydroponically grown lettuce. The results showed that lettuce grown hydroponically resulted in a higher risk than lettuce grown in soil. In both cases, the risk predicted failed to meet the risk benchmarks established by the U.S. EPA and WHO. Viral attachment to growth media, such as the soil particles, was an important mechanism for risk reduction. A sensitivity analysis revealed that harvesting time and irrigation time are important factors influencing the viral loads in lettuce. Hence, this pathogen transport model provides a framework for investigating the effects of time and other factors on disease burdens from water reuse in agriculture, underscoring the utility of a dynamic model. In the absence of a routine monitoring of contaminants in the recycled irrigation water and food crops, a quantitative risk assessment based on objective scientific knowledge is the best approach to guide the policy decisions on water reuse practices.

Quantitative microbial risk assessment of Greywater on-site reuse.

Recycle domestic greywater for on-site non-potable uses can lessen the demand on potable water and the burden on wastewater treatment plants. However, lack of studies to assess health risk associated with such practices has hindered their popularity. A Quantitative Microbial Risk Assessment was conducted to estimate the public health risks for two greywater reuse scenarios: toilet flushing and food-crop irrigation. Household greywater quality from three sources (bathroom, laundry and kitchen) was analyzed. Mathematical exposure rates of different scenarios were established based on human behavior using Monte-Carlo simulation. The results showed that, greywater from all three household sources could be safely used for toilet flushing after a simple treatment of microfiltration. The median range of annual infection risk was 8.8 × 10-15-8.3 × 10-11 per-person-per-year (pppy); and the median range of disease burden was 7.6 × 10-19-7.3 × 10-15 disability-adjusted life years (DALYs) pppy. In food-crop irrigation scenario, the annual infection risks and disease burdens of treated greywater from bathroom and laundry (2.8 × 10-8, 4.9 × 10-8 pppy; 2.3 × 10-12-4.2 × 10-12 DALYs pppy) were within the acceptable levels of U.S. EPA annual infection risk (≤10-4 pppy) and WHO disease burden (≤10-6 DALYs pppy) benchmarks, while kitchen greywater was not suitable for food-crop irrigation (4.9 × 10-6 pppy; 4.3 × 10-10 DALYs pppy) based on these benchmarks. The model uncertainties were discussed, which suggests that a more accurate risk estimation requires improvements on data collection and model refinement.

Shifts in dissolved organic matter and microbial community composition are associated with enhanced removal of fecal pollutants in urban stormwater wetlands.

Constructed stormwater wetlands provide a host of ecosystem services, including potentially pathogen removal. We present results from a multi-wetland study that integrates across weather, chemical, microbiological and engineering design variables in order to identify patterns of microbial contaminant removal from inlet to outlet within wetlands and key drivers of those patterns. One or more microbial contaminants were detected at the inlet of each stormwater wetland (Escherichia coli and Enterococcus > Bacteroides HF183 > adenovirus). Bacteroides HF183 and adenovirus concentrations declined from inlet to outlet at all wetlands. However, co-removal of pathogens and fecal indicator bacteria only occurred at wetlands where microbial assemblages at the inlet (dominated by Proteobacteria and Bacteriodetes) were largely displaced by indigenous autotrophic microbial communities at the outlet (dominated by Cyanobacteria). Microbial community transitions (characterized using pyrosequencing) were well approximated by a combination of two rapid indicators: (1) fluorescent dissolved organic matter, and (2) chlorophyll a or phaeophytin a fluorescence. Within-wetland treatment of fecal markers and indicators was not strongly correlated with the catchment-to-wetland area ratio, but was diminished in older wetlands, which may point to a need for more frequent maintenance.