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At least 55 records · Page 3Linked to original sources

Viral, bacterial, and protozoan pathogens and fecal markers in wells supplying groundwater to public water systems in Minnesota, USA

Drinking water supply wells can be contaminated by a broad range of waterborne pathogens. However, groundwater assessments frequently measure microbial indicators or a single pathogen type, which provides a limited characterization of potential health risk. This study assessed contamination of wells by testing for viral, bacterial, and protozoan pathogens and fecal markers. Wells supplying groundwater to community and noncommunity public water systems in Minnesota, USA (n = 145) were sampled every other month over one or two years and tested using 23 qPCR assays. Eighteen genetic targets were detected at least once, and microbiological contamination was widespread (96% of 145 wells, 58% of 964 samples). The sewage-associated microbial indicators HF183 and pepper mild mottle virus were detected frequently. Human or zoonotic pathogens were detected in 70% of wells and 21% of samples by qPCR, with Salmonella and Cryptosporidium detected more often than viruses. Samples positive by qPCR for adenovirus (HAdV), enterovirus, or Salmonella were analyzed by culture and for genotype or serotype. qPCR-positive Giardia and Cryptosporidium samples were analyzed by immunofluorescent assay (IFA), and IFA and qPCR concentrations were correlated. Comparisons of indicator and pathogen occurrence at the time of sampling showed that total coliforms, HF183, and Bacteroidales -like HumM2 had high specificity and negative predictive values but generally low sensitivity and positive predictive values. Pathogen-HF183 ratios in sewage have been used to estimate health risks from HF183 concentrations in surface water, but in our groundwater samples Cryptosporidium oocyst:HF183 and HAdV:HF183 ratios were approximately 10,000 times higher than ratios reported for sewage. qPCR measurements provided a robust characterization of microbiological water quality, but interpretation of qPCR data in a regulatory context is challenging because few studies link qPCR measurements to health risk.

Minnesota↗

Phylogenomic analyses reveal introgression and cryptic speciation in the globally distributed, vector-transmitted pathogen Plasmodium relictum

Establishing species limits is challenging, particularly for pathogens of wildlife. These pathogens can be difficult to sample and culture, and their genome sequencing must often be conducted in the presence of high levels of host DNA. Plasmodium relictum is a mosquito-vectored avian malaria pathogen that is a globally distributed host generalist, comprised of several genetic lineages. We used sequence capture data from 52 P. relictum infections originating from multiple continents to generate a genomic dataset of the pathogen. With this data, we established a robust phylogeny and determined species limits among P. relictum lineages. We generated phylogenomic trees by maximum likelihood and Bayesian methods with multi-species coalescent models and confirmed robustness of the topology by varying the amount of missing data in the analyses. Our results suggest the existence of two cryptic species among the infections we analyzed and provide evidence of genetic introgression between these species. One of the cryptic species, GRW4, devastated the endemic and immunologically naïve avifauna of Hawaii after its introduction to the islands ca. 100 years ago, and so was tested for positive selection in the GRW4 Hawaiian clade. Although we hypothesized it would be released from host selective pressures, we did not find evidence of positive selection in the Hawaiian GRW4 clade, and we discuss possible explanations. Overall, our results underscore the importance of genomic analyses for resolving pathogen species limits and understanding pathogen evolution.

Molecular Phylogenetics and Evolution↗

When environmentally persistent pathogens transform good habitat into ecological traps

Habitat quality plays an important role in the dynamics and stability of wildlife metapopulations. However, the benefits of high-quality habitat may be modulated by the presence of an environmentally persistent pathogen. In some cases, the presence of environmental pathogen reservoirs on high-quality habitat may lead to the creation of ecological traps, wherein host individuals preferentially colonize high-quality habitat, but are then exposed to increased infection risk and disease-induced mortality. We explored this possibility through the development of a stochastic patch occupancy model, where we varied the pathogen’s virulence, transmission rate and environmental persistence as well as the distribution of habitat quality in the host metapopulation. This model suggests that for pathogens with intermediate levels of spread, high-quality habitat can serve as an ecological trap, and can be detrimental to host persistence relative to low-quality habitat. This inversion of the relative roles of high- and low-quality habitat highlights the importance of considering the interaction between spatial structure and pathogen transmission when managing wildlife populations exposed to an environmentally persistent pathogen.

Royal Society Open Science↗

Defining an epidemiological landscape that connects movement ecology to pathogen transmission and pace-of-life

Pathogen transmission depends on host density, mobility and contact. These components emerge from host and pathogen movements that themselves arise through interactions with the surrounding environment. The environment, the emergent host and pathogen movements, and the subsequent patterns of density, mobility and contact form an ‘epidemiological landscape’ connecting the environment to specific locations where transmissions occur. Conventionally, the epidemiological landscape has been described in terms of the geographical coordinates where hosts or pathogens are located. We advocate for an alternative approach that relates those locations to attributes of the local environment. Environmental descriptions can strengthen epidemiological forecasts by allowing for predictions even when local geographical data are not available. Environmental predictions are more accessible than ever thanks to new tools from movement ecology, and we introduce a ‘movement-pathogen pace of life’ heuristic to help identify aspects of movement that have the most influence on spatial epidemiology. By linking pathogen transmission directly to the environment, the epidemiological landscape offers an efficient path for using environmental information to inform models describing when and where transmission will occur.

Ecology Letters↗

Increased pathogen exposure of a marine apex predator over three decades

Environmental changes associated with global warming create new opportunities for pathogen and parasite transmission in Arctic wildlife. As an apex predator ranging over large, remote areas, changes in pathogens and parasites in polar bears are a useful indicator of changing transmission dynamics in Arctic ecosystems. We examined prevalence and risk factors associated with exposure to parasites and viral and bacterial pathogens in Chukchi Sea polar bears. Serum antibodies to six pathogens were detected and prevalence increased between 1987–1994 and 2008–2017 for five: Toxoplasma gondii , Neospora caninum , Francisella tularensis , Brucella abortus/suis , and canine distemper virus. Although bears have increased summer land use, this behavior was not associated with increased exposure. Higher prevalence of F. tularensis , C. burnetii , and B. abortus/suis antibodies in females compared to males, however, could be associated with terrestrial denning. Exposure was related to diet for several pathogens indicating increased exposure in the food web. Elevated white blood cell counts suggest a possible immune response to some pathogens. Given that polar bears face multiple stressors in association with climate change and are a subsistence food, further work is warranted to screen for signs of disease.

Alaska↗

Serological assessment of pathogen exposure among desert bighorn sheep in southwestern Arizona

Bighorn sheep ( Ovis canadensis ) are influenced by infectious diseases. Although Mycoplasma ovipneumoniae has been the main focus of bighorn sheep managers since early 2010, other pathogens may also influence bighorn sheep populations. We sampled desert bighorn sheep ( Ovis canadensis mexicana ) captured for a study on the Cabeza Prieta National Wildlife Refuge in southwestern Arizona, USA, 2001–2005, for a suite of pathogens: bluetongue (BT), epizootic hemorrhagic disease (EHD), parainfluenza 3, bovine respiratory syncytial virus, Clamydia , seven Leptospira serovars, bovine herpesvirus 1 (causative agent of infectious bovine rhinotracheitis), bovine viral diarrhea virus, and bovine respiratory syncytial virus. We recorded evidence of exposure to seven of these pathogens, with two Leptospira serovars ( hardjo and bratislava ), five strains of BT, and two strains of EHD detected. Seroprevalence rates of detected pathogens varied between 12–49%. We observed high levels of co-occurrence for EHD and BT. These results highlight that multiple pathogens may influence desert bighorn sheep populations. These data also provide historical context to pathogen exposure for a region where few such data are available.

Arizona↗

Quarantine of Aeromonas salmonicida-harboring ebonyshell mussels (Fusconaia ebena) prevents transmission of the pathogen to brook trout (Salvelinus fontinalis)

Furunculosis, caused by the bacterium Aeromonas salmonicida , was artificially induced in brook trout ( Salvelinus fontinalis ) in an experimental tank. Ebonyshells ( Fusconaia ebena ) were placed to cohabit with these fish to acquire the pathogen through siphoning. After 2 wk of cohabitation, 10 of the mussels were assayed by bacterial culture and all were found to harbor A. salmonicida . The mean cell count from soft tissue homogenates was 1.84 × 10 5 cfu/g, which comprised an average 14.41% of the total bacteria isolated from tissues. From the fluids, a mean of 2.84 × 10 5 A. salmonicida cfu/mL was isolated, which comprised an average of 17.29% of the total bacterial flora. The mussels were removed from the cohabitation tank and distributed equally among five previously disinfected tanks, 35 per tank. The F. ebena in each tank were allowed to depurate A. salmonicida for various durations: 1, 5, 10, 15 or 30 days. After each group had depurated for their assigned time, 10 were assayed for bacteria, tank water was tested, and 20 pathogen-free bioindicator brook trout were added to cohabit with the remaining mussels. Depuration was considered successful if A. salmonicida was not isolated from tank water or the mussels, and there was no infection or mortality to bioindicator fish. After 1 day of depuration, A. salmonicida was not isolated from the soft tissues; however, it was isolated from one of the paired fluids (10% prevalence). The tank water tested positive, and the bioindicator fish became infected and died. From the 5-day depuration group, A. salmonicida was not isolated from soft tissues, but was isolated from three fluids (30%; mean = 1.56 × 10 2 cfu/mL). Tank water from the 5-day group was negative, and there was no mortality among the bioindicator fish. However, A. salmonicida was isolated from 2 of 20 fish at the end of the 14-day observation period. One F. ebena fluid sample was positive for A. salmonicida from the 10-day depuration group, but none of the soft tissue homogenates. The pathogen was not isolated from 10-day tank water, but there was a 30% cumulative mortality to the bioindicator fish. Aeromonas salmonicida was not isolated from any of the soft tissue homogenates, fluids or tank water from the 15 day or 30 day depuration groups, and the bioindicator fish remained pathogen- and disease-free. Study results showed that the F. ebena were harboring a high A. salmonicida cell load going into depuration, but at 15 days and beyond, the pathogen had been depurated to the extent that the mussels did not serve as pathogen vectors.

Journal of Shellfish Research↗

Viral pathogen detection in U.S. game-farm mallard (Anas platyrhynchos) flags spillover risk to wild birds

The threat posed by emerging infectious diseases is a major concern for global public health, animal health and food security, and the role of birds in transmission is increasingly under scrutiny. Each year, millions of mass-reared game-farm birds are released into the wild, presenting a unique and a poorly understood risk to wild and susceptible bird populations, and to human health. In particular, the shedding of enteric pathogens through excrement into bodies of water at shared migratory stop-over sites, and breeding and wintering grounds, could facilitate multi-species long-distance pathogen dispersal and infection of high numbers of naive endemic birds annually. The Mallard ( Anas platyrhynchos ) is the most abundant of all duck species, migratory across much of its range, and an important game species for pen-rearing and release. Major recent population declines along the US Atlantic coast has been attributed to game-farm and wild mallard interbreeding and the introduction maladaptive traits into wild populations. However, pathogen transmission and zoonosis among game-farms Mallard may also impact these populations, as well as wildlife and human health. Here, we screened 16 game-farm Mallard from Wisconsin, United States, for enteric viral pathogens using metatranscriptomic data. Four families of viral pathogens were identified – Picobirnaviridae (Genogroup I), Caliciviridae (Duck Nacovirus ), Picornaviridae (Duck Aalivirus ) and Sedoreoviridae (Duck Rotavirus G). To our knowledge, this is the first report of Aalivirus in the Americas, and the first report of Calicivirus outside domestic chicken and turkey flocks in the United States. Our findings highlight the risk of viral pathogen spillover from peri-domestically reared game birds to naive wild bird populations.

Frontiers Earth Science Journal↗

Challenges and opportunities developing mathematical models of shared pathogens of domestic and wild animals

Diseases that affect both wild and domestic animals can be particularly difficult to prevent, predict, mitigate, and control. Such multi-host diseases can have devastating economic impacts on domestic animal producers and can present significant challenges to wildlife populations, particularly for populations of conservation concern. Few mathematical models exist that capture the complexities of pathogens, yet development of such models would allow us to estimate and compare the potential effectiveness of management actions for mitigating or suppressing disease in wildlife and/or livestock host populations. We conducted a workshop in March 2014 to identify the challenges associated with developing models of pathogen transmission across the wildlife-livestock interface. The development of mathematical models of pathogen transmission at this interface is hampered by the difficulties associated with describing the host-pathogen systems including: 1) the identity of wildlife hosts, their distributions, and movement patterns, 2) the pathogen transmission pathways between wildlife and domestic animals, 3) the effects of the disease and concomitant mitigation efforts on wild and domestic animal populations, and 4) barriers to communication between sectors. To promote the development of mathematical models of transmission at this interface, we recommend further integration of modern quantitative techniques and improvement of communication among wildlife biologists, mathematical modelers, veterinary medicine professionals, producers, and other stakeholders concerned with the consequences of pathogen transmission at this important, yet poorly understood, interface.

Veterinary Sciences↗

Glass wool filters for concentrating waterborne viruses and agricultural zoonotic pathogens

The key first step in evaluating pathogen levels in suspected contaminated water is concentration. Concentration methods tend to be specific for a particular pathogen group, for example US Environmental Protection Agency Method 1623 for Giardia and Cryptosporidium1, which means multiple methods are required if the sampling program is targeting more than one pathogen group. Another drawback of current methods is the equipment can be complicated and expensive, for example the VIRADEL method with the 1MDS cartridge filter for concentrating viruses2. In this article we describe how to construct glass wool filters for concentrating waterborne pathogens. After filter elution, the concentrate is amenable to a second concentration step, such as centrifugation, followed by pathogen detection and enumeration by cultural or molecular methods. The filters have several advantages. Construction is easy and the filters can be built to any size for meeting specific sampling requirements. The filter parts are inexpensive, making it possible to collect a large number of samples without severely impacting a project budget. Large sample volumes (100s to 1,000s L) can be concentrated depending on the rate of clogging from sample turbidity. The filters are highly portable and with minimal equipment, such as a pump and flow meter, they can be implemented in the field for sampling finished drinking water, surface water, groundwater, and agricultural runoff. Lastly, glass wool filtration is effective for concentrating a variety of pathogen types so only one method is necessary. Here we report on filter effectiveness in concentrating waterborne human enterovirus, Salmonella enterica, Cryptosporidium parvum, and avian influenza virus.

Journal of Visualized Experiments↗

Estimating occurrence, prevalence, and detection of amphibian pathogens: Insights from occupancy models

Understanding the distribution of pathogens across landscapes and their prevalence within host populations is a common aim of wildlife managers. Despite the need for unbiased estimates of pathogen occurrence and prevalence for planning effective management interventions, many researchers fail to account for imperfect pathogen detection. Instead raw data are often reported, which may lead to ineffective, or even detrimental, management actions. We illustrate the utility of occupancy models for generating unbiased estimates of disease parameters by 1) providing a written tutorial describing how to fit these models in Program PRESENCE and 2) presenting a case study with the pathogen ranavirus. We analyzed ranavirus detection data from a wildlife refuge (Maryland, US) using occupancy modeling, which yields unbiased estimates of pathogen occurrence and prevalence. We found ranavirus prevalence was underestimated by up to 30% if imperfect pathogen detection was ignored. The unbiased estimate of ranavirus prevalence in larval wood frog ( Lithobates sylvaticus ; 0.73) populations was higher than in larval spotted salamander ( Ambystoma maculatum ; 0.56) populations. In addition, the odds of detecting ranavirus in tail samples were 6.7 times higher than detecting ranavirus in liver samples. Therefore, tail samples presented a nonlethal sampling method for ranavirus that may be able to detect early (nonsystemic) infections.

Maryland↗

Risk of invasive waterfowl interaction with poultry production: Understanding potential for avian pathogen transmission via species distribution models

Recent outbreaks of highly pathogenic avian influenza have devastated poultry production across the United States, with more than 77 million birds culled in 2022–2024 alone. Wild waterfowl, including various invasive species, host numerous pathogens, including highly pathogenic avian influenza virus (HPAIV), and have been implicated as catalysts of disease outbreaks among native fauna and domestic birds. In major poultry-producing states like Arkansas, USA, where the poultry sector is responsible for significant economic activity (>$4 billion USD in 2022), understanding the risk of invasive waterfowl interactions with domestic poultry is critical. Here, we assessed the risk of invasive waterfowl-poultry interaction in Arkansas by comparing the density of poultry production sites (chicken houses) to areas of high habitat suitability for two invasive waterfowl species, (Egyptian Goose [ Alopochen aegyptiaca ] and Mute Swan [ Cygnus olor ]), known to host significant pathogens, including avian influenza viruses. The percentage of urban land cover was the most important habitat characteristic for both invasive waterfowl species. At the 95% confidence interval, chicken house densities in areas highly suitable for both species (Egyptian Goose = 0.91 ± 0.11 chicken houses/km 2 ; Mute Swan = 0.61 ± 0.03 chicken houses/km 2 ) were three to five times higher than chicken house densities across the state (0.17 ± 0.01 chicken houses/km 2 ). We show that northwestern and western Arkansas, both areas of high importance for poultry production, are also at high risk of invasive waterfowl presence. Our results suggest that targeted monitoring efforts for waterfowl-poultry contact in these areas could help mitigate the risk of avian pathogen exposure in Arkansas and similar regions with high poultry production.

Biological Invasions↗

Waterfowl recently infected with low pathogenic avian influenza exhibit reduced local movement and delayed migration

Understanding relationships between infection and wildlife movement patterns is important for predicting pathogen spread, especially for multispecies pathogens and those that can spread to humans and domestic animals, such as avian influenza viruses (AIVs). Although infection with low pathogenic AIVs is generally considered asymptomatic in wild birds, prior work has shown that influenza-infected birds occasionally delay migration and/or reduce local movements relative to their uninfected counterparts. However, most observational research to date has focused on a few species in northern Europe; given that influenza viruses are widespread globally and outbreaks of highly pathogenic strains are increasingly common, it is important to explore influenza–movement relationships across more species and regions. Here, we used telemetry data to investigate relationships between influenza infection and movement behavior in 165 individuals from four species of North American waterfowl that overwinter in California, USA. We studied both large-scale migratory and local overwintering movements and found that relationships between influenza infection and movement patterns varied among species. Northern pintails ( Anas acuta ) with antibodies to avian influenza, indicating prior infection, made migratory stopovers that averaged 12 days longer than those with no influenza antibodies. In contrast, greater white-fronted geese ( Anser albifrons ) with antibodies to avian influenza made migratory stopovers that averaged 15 days shorter than those with no antibodies. Canvasbacks ( Aythya valisineria ) that were actively infected with influenza upon capture in the winter delayed spring migration by an average of 28 days relative to birds that were uninfected at the time of capture. At the local scale, northern pintails and canvasbacks that were actively infected with influenza used areas that were 7.6 and 4.9 times smaller than those of uninfected ducks, respectively, during the period of presumed active influenza infection. We found no evidence for an influence of active influenza infection on local movements of mallards ( Anas platyrhynchos ). These results suggest that avian influenza can influence waterfowl movements and illustrate that the relationships between avian influenza infection and wild bird movements are context- and species-dependent. More generally, understanding and predicting the spread of multihost pathogens requires studying multiple taxa across space and time.

Ecosphere↗

Hosts, pathogens and hot ponds: Thermal mean and variability contribute to spatial patterns of chytrid infection

Temperature is a primary driver of heterogeneity in host–pathogen dynamics and understanding how patch-scale temperature affects landscape-scale patterns of pathogen infection is key to effective monitoring and management. In field studies, both temperature variability and mean temperature are often related to infection of ectothermic animals by fungal pathogens, and although these factors vary spatiotemporally, their contributions to infection outcomes are rarely decomposed into spatial and temporal components. We studied how patch-scale thermal conditions (mean and variability) affect infection of eastern newts Notophthalmus viridescens by Batrachochytrium dendrobatidis ( Bd ), with a special focus on disentangling spatial versus temporal contributions of thermal conditions to infection outcomes. We measured in situtemperature and Bd infection across 20 ponds in two years in southeastern Wisconsin, USA to 1) understand thermal mediation of infection and 2) quantify whether seasonal and/or among-site variation in thermal conditions drive heterogeneity in host–pathogen interactions. In our system, thermal mean and variability covaried tightly, necessitating the creation of a single index to capture both components. We found that 1) this index of thermal mean and variability was strongly and nonlinearly related to Bd infection and 2) differences among patches in thermal conditions drove this relationship, highlighting that variation in patch-level conditions can drive heterogenous host–pathogen outcomes across landscapes. Our research collectively reveals insights about the importance of local, patch-level conditions for mediating disease risk at broader scales.

Wisconsin↗

Pathogen transport in groundwater systems: Contrasts with traditional solute transport

Water quality affects many aspects of water availability, from precluding use to societal perceptions of fit-for-purpose. Pathogen source and transport processes are drivers of water quality because they have been responsible for numerous outbreaks resulting in large economic losses due to illness and, in some cases, loss of life. Outbreaks result from very small exposure (e.g., less than 20 viruses) from very strong sources (e.g., trillions of viruses shed by a single infected individual). Thus, unlike solute contaminants, an acute exposure to a very small amount of contaminated water can cause immediate adverse health effects. Similarly, pathogens are larger than solutes. Thus, interactions with surfaces and settling become important even as processes important for solutes such as diffusion become less important. These differences are articulated in “Colloid Filtration Theory”, a separate branch of pore-scale transport. Consequently, understanding pathogen processes requires changes in how groundwater systems are typically characterized, where the focus is on the leading edges of plumes and preferential flow paths, even if such features move only a very small fraction of the aquifer flow. Moreover, the relatively short survival times of pathogens in the subsurface require greater attention to very fast (<10 year) flow paths. By better understanding the differences between pathogen and solute transport mechanisms discussed here, a more encompassing view of water quality and source water protection is attained. With this more holistic view and theoretical understanding, better evaluations can be made regarding drinking water vulnerability and the relation between groundwater and human health.

Hydrogeology Journal↗

Evidence for common ancestry among viruses isolated from wild birds in Beringia and highly pathogenic intercontinental reassortant H5N1 and H5N2 influenza A viruses

Highly pathogenic clade 2.3.4.4 H5N8, H5N2, and H5N1 influenza A viruses were first detected in wild, captive, and domestic birds in North America in November&ndash;December 2014. In this study, we used wild waterbird samples collected in Alaska prior to the initial detection of clade 2.3.4.4 H5 influenza A viruses in North America to assess the evidence for: (1) dispersal of highly pathogenic influenza A viruses from East Asia to North America by migratory birds via Alaska and (2) ancestral origins of clade 2.3.4.4 H5 reassortant viruses in Beringia. Although we did not detect highly pathogenic influenza A viruses in our sample collection from western Alaska, we did identify viruses that contained gene segments sharing recent common ancestry with intercontinental reassortant H5N2 and H5N1 viruses. Results of phylogenetic analyses and estimates for times of most recent common ancestry support migratory birds sampled in Beringia as maintaining viral diversity closely related to novel highly pathogenic influenza A virus genotypes detected in North America. Although our results do not elucidate the route by which highly pathogenic influenza A viruses were introduced into North America, genetic evidence is consistent with the hypothesized trans-Beringian route of introduction via migratory birds.

Infection, Genetics and Evolution↗

Ecological and socioeconomic factors associated with the human burden of environmentally mediated pathogens: A global analysis

Background Billions of people living in poverty are at risk of environmentally mediated infectious diseases—that is, pathogens with environmental reservoirs that affect disease persistence and control and where environmental control of pathogens can reduce human risk. The complex ecology of these diseases creates a global health problem not easily solved with medical treatment alone. Methods We quantified the current global disease burden caused by environmentally mediated infectious diseases and used a structural equation model to explore environmental and socioeconomic factors associated with the human burden of environmentally mediated pathogens across all countries. Findings We found that around 80% (455 of 560) of WHO-tracked pathogen species known to infect humans are environmentally mediated, causing about 40% (129 488 of 359 341 disability-adjusted life years) of contemporary infectious disease burden (global loss of 130 million years of healthy life annually). The majority of this environmentally mediated disease burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. We found weak associations between disease burden and biodiversity or agricultural land use at the global scale. In contrast, the proportion of people with rural poor livelihoods in a country was a strong proximate indicator of environmentally mediated infectious disease burden. Political stability and wealth were associated with improved sanitation, better health care, and lower proportions of rural poverty, indirectly resulting in lower burdens of environmentally mediated infections. Rarely, environmentally mediated pathogens can evolve into global pandemics (eg, HIV, COVID-19) affecting even the wealthiest communities. Interpretation The high and uneven burden of environmentally mediated infections highlights the need for innovative social and ecological interventions to complement biomedical advances in the pursuit of global health and sustainability goals. Funding Bill & Melinda Gates Foundation, National Institutes of Health, National Science Foundation, Alfred P. Sloan Foundation, National Institute for Mathematical and Biological Synthesis, Stanford University, and the US Defense Advanced Research Projects Agency.

The Lancet Planetary Health↗

Application of a microfluidic quantitative polymerase chain reaction technique to monitor bacterial pathogens in beach water and complex environmental matrices

Microfluidic quantitative polymerase chain reaction (MFQPCR) and conventional quantitative polymerase chain reaction methods were compared side by side in detecting and quantifying 19 genetic markers associated with Escherichia coli and select bacterial pathogens in algae, beach sand, and water from Lake Michigan. Enteropathogenic E. coli (EPEC), Shiga toxin-producing E. coli , Salmonella spp., Campylobacter jejuni , and Clostridium perfringens were among the pathogens tested. Of the pathogenic markers, eaeA that encodes intimin in EPEC was detected in all sample types: water (5%), detached/floating algae (42%), exposed/stranded algae (43%), sand below exposed algae (27%), and nearshore sand with no algae (22%). Other pathogenic markers, however, were detected sporadically. Despite comparable results from the two methods for the genetic markers tested in this study, the MFQPCR method may be superior, with the advantage of detecting and quantifying multiple pathogens simultaneously in environmental matrices.

Indiana↗