Detection of the clinically persistent, pathogenic yeast spp. Candida auris from hospital and municipal wastewater in Miami-Dade County, Florida

Fluorescence damping as primary interference mechanism of humic acids on qPCR quantification of SARS-CoV-2 in wastewater surveillance

Real-time polymerase chain reaction (qPCR) is a widely used technology for the detection and quantification of nucleic acids in wastewater surveillance. However, the presence of inhibiting and/or interfering substances in wastewater samples, in particular humic acids, can significantly impact the accuracy and reliability of qPCR results. In this study, we investigated the impact of humic acids on qPCR reactions and determined the relative importance of various inhibition/interference mechanisms through spiked experiments and modeling. Our results showed that higher concentrations of humic acids led to increasing threshold cycle (CT) values, which however cannot be adequately described by the polymerase inhibition model and the DNA template complexation model. Further inspection showed that humic acids caused fluorescence damping of the FAM reporter dye, resulting in an overall decrease in fluorescence intensity. Modeling of the fluorescence damping effect showed that the CT values of qPCR reactions can be corrected based on end-point fluorescence reduction. Similar observations and corrections were also achieved when SARS-CoV-2 cDNA was spiked with an actual wastewater sludge cDNA.

Candida auris Diagnostics: Identification and Screening

Candida auris is an emerging yeast species classified as an urgent threat by the Centers for Disease Control and Prevention due to its ability to colonize numerous surfaces, its ability to spread through health care systems, its elevated antifungal resistance, and its high mortality rate. Accurate detection of C auris from patient specimens is crucial for containing, preventing the spread of, and managing patients with C auris. Here, we review currently available diagnostics, current screening guidance, and identify areas where diagnostics could improve.

Novel Workflows for Separate Isolation of Pathogen RNA or DNA from Wastewater: Detection by Innovative and Conventional qPCR

Wastewater-based surveillance (WBS) can provide a wealth of information regarding the health status of communities from measurements of nucleic acids found in wastewater. Processing workflows for WBS typically include sample collection, a primary concentration step, and lysis of the microbes to release nucleic acids, followed by nucleic acid purification and molecular-based quantification. This manuscript provides workflows from beginning to end with an emphasis on filtration-based concentration approaches coupled with specific lysis and nucleic acid extraction processes. Here, two WBS processing approaches are presented, one focusing on RNA-specific pathogens and the other focused on DNA-specific pathogens found within wastewater: 1) The RNA-specific approach, employed for analyzing RNA viruses like severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) couples electronegative filtration of wastewater with the placement of the filter within a lysis buffer followed by direct RNA extraction. 2) The DNA-specific approach, employed for analyzing DNA pathogens like Candida auris, uses size selection membranes during filtration, subsequently followed by a lysis buffer, bead-beating, and DNA extraction. Separate workflows for RNA versus DNA isolations have the advantage of improving the detection of the target pathogen. A novel aspect of the RNA-specific workflow is the direct extraction of nucleic acids from filter lysates, which shows enhanced recoveries, whereas the DNA-specific approach requires bead beating prior to extraction. Novelty is also provided in a new qPCR approach called Volcano 2nd Generation (V2G), which uses a polymerase capable of using RNA as a template, bypassing the reverse transcriptase step normally required for qPCR. Key features • Membrane filtration approaches for concentrating suspended solids from wastewater. After concentration, workflows are optimized for separate recovery of RNA and DNA. • Unique polymerase utilized to perform qPCR analysis, foregoing reverse transcription, for RNA. • Sample products for use with other molecular techniques (e.g., sequencing) as workflow approaches generate high-quality, concentrated nucleic acid extracts with minimal inhibitors. • Validated through COVID-19 surveillance where >1,000 samples of wastewater and >3,000 filter concentrates produced from these samples have been created and analyzed, with published results. This complete protocol was used in: J Biomol Tech (2023), DOI: 10.7171/3fc1f5fe.dfa8d906.

Culture-Dependent and -Independent Wastewater Surveillance for Multiple Pathogenic Yeasts

Wastewater surveillance is a promising tool to monitor potential outbreaks and determine the disease burden within a community. This system has been extensively used to monitor polio and COVID-19 infection levels, yet few attempts have been made to apply it to monitoring pathogenic yeast. This study aimed to investigate the application of wastewater surveillance for potentially pathogenic yeast in wastewater treatment plant influent. This was done by comparing culture-dependent data with culture-independent data and investigating the fluconazole concentration in wastewater. Additional studies on the growth of isolated strains were conducted. We found that a multiplex PCR system to detect multiple yeasts holds promise as a molecular detection tool for wastewater surveillance. Culture-dependent results indicated that Candida spp. specifically C. krusei and C. glabrata, were most prominent. Growth studies supported that these species grow well in this environment while the less frequently isolated yeasts grew poorly. The data from culture-dependent and independent techniques showed some correlation, with similar species being identified with both, further promoting the use of molecular tools for surveillance. This study highlights the presence of potentially pathogenic yeasts in wastewater, which may indicate the prevalence of these yeasts in the environment or community. This wastewater may also be a potential source of infection for persons encountering it due to poor wastewater management.

A Perspective on Wastewater and Environmental Surveillance as a Public Health Tool for Low- and Middle-Income Countries

Geographical variations in infectious diseases create differences in public health priorities between high- and low-income countries. Low- and middle-income countries (LMICs) face resource constraints that limit adherence to international monitoring standards for wastewater-based epidemiology (WBE). The development of low-cost WBE programs, such as those to detect SARS-CoV-2, offers LMICs a promising tool for monitoring pathogens of local concern. In this work, we summarize important wastewater biomarkers for LMICs and their associated public health challenges, ranging from pathogens causing gastroenteritis to putative markers for plant diseases linked to food safety, as well as antimicrobial resistance. We raise awareness of the great potential of WBE for LMICs and highlight the critical health markers, research needs, and strategies necessary to establish tailored wastewater surveillance programs.

Wastewater Based Measures of COVID-19 and Associations with Children's Absenteeism at Grade Schools

During the COVID-19 pandemic schools closed due to concerns over disease spread resulting in lost learning opportunities. One approach for documenting disease spread includes wastewater (WW) surveillance of the virus that causes COVID-19 (Severe Acute Respiratory Syndrome Coronavirus 2, SARS-CoV-2) and other infectious pathogens. The objective of this study was to evaluate whether wastewater can be used to track children's health at grade schools in an underserved community, which was vulnerable due to limited health-based data and difficulties in implementing mitigation measures. The 18-month study was initiated during January 2022 at 9 grade schools (3 high, 2 middle, and 4 elementary schools) characterized as low income. Children's health was evaluated through absenteeism due to difficulties in attaining representative clinical diagnoses through school-based clinics. Wastewater measurements of SARS-CoV-2 were available weekly through grab sample collection and RNA extraction followed by quantification using qPCR. The average absenteeism rate was 7.1%, ranging from 4.6% to 12.5% per school. Fraction of WW samples positive for SARS-CoV-2 was 38% with SARS-Cov-2 levels ranging from detection limits (100 gc/L) to a maximum of 10.2 million gc/L. When data were aggregated across all schools, a statistically significant association was observed between weekly absenteeism rates and WW SARS-CoV-2 with a one percent increase in the loge WW SARS-CoV-2 associated with a 1.4% increase in student absence (p < 0.05). When evaluating the data by individual school, this association was strongest at schools with enclosed architecture characterized by limited natural ventilation. For schools with limited resources for clinical diagnosis of illnesses, school absenteeism coupled with wastewater-based monitoring should be utilized for assessing overall health of student populations. Strategies to maintain schools open during pandemics should include consideration of school architecture along with appropriate messaging of WW monitoring results to inform administrators and families.

Efficacy of cleaning, disinfection, and sterilization modalities for addressing infectious drug-resistant fungi: a review

This is a timely and important review that focuses on the appropriateness of established cleaning, disinfection, and sterilization methods to safely and effectively address infectious fungal drug-resistant pathogens that can potentially contaminate reusable medical devices used in healthcare environment in order to mitigate the risk of patient infection. The release of the World Health Organization (WHO) fungal priority pathogen list (FPPL) in 2022 highlighted the public health crisis of antimicrobial resistance (AMR) in clinically relevant fungal species. Contamination of medical devices with drug-resistant fungal pathogens (including those on the FPPL) in healthcare is a rare event that is more likely to occur due to cross-transmission arising from lapses in hand hygiene practices. Established disinfection and sterilization methods decontaminate fungal pathogens on single-use and reusable medical devices; however, there are assumptions that reusable devices destined for semi-critical use are appropriately cleaned and do not harbour biofilms that may undermine the ability to effectively decontamination these type devices in healthcare. International standards dictate that manufacturer's instructions for use must provide appropriate guidance to healthcare facilities to meet safe reprocessing expectations that include addressing drug-resistant fungal pathogens. Increased environmental monitoring and vigilance surrounding fungal pathogens in healthcare is advised, including adherence to hand hygiene/aseptic practices and appropriate cleaning encompassing the simplification of reusable device features for 'ease-of-reach'. There are emereging opportunities to promote a more integrated multiactor hub approach to addressing these sophisticated challenges, including future use of artificial intelligence and machine learning for improved diagnostics, monitoring/surveillance (such as healthcare and wastewater-based epidemiology), sterility assurance, and device design. There is a knowledge gap surrounding the occurrence and potential persistence of drug-resistant fungal pathogens harboured in biofilms, particularly for ascertaining efficacy of high-level disinfection for semi-critical use devices.

Candida auris: Epidemiology and Antifungal Strategy

Candida auris is a recently emerged fungal pathogen that causes severe infections in healthcare settings around the globe. A feature that distinguishes C. auris from other fungal pathogens is its high capacity to colonize skin, leading to widespread outbreaks in healthcare facilities via patient-to-patient transmission. C. auris can persist on skin or in the surrounding environment for extended periods of time, and it exhibits greater antifungal resistance than other Candida species. These factors pose major obstacles for the prevention and treatment of C. auris infection. Recent reports have identified frequently colonized skin sites, risk factors for developing invasive infection, and patterns of antifungal resistance among C. auris strains, all of which help guide therapeutic options. In this review, we highlight key studies of C. auris epidemiology and antifungal resistance, discussing how these factors influence healthcare-associated transmission and treatment outcomes.

Early Introductions of Candida auris Detected by Wastewater Surveillance, Utah, USA, 2022-2023

Candida auris is considered a nosocomial pathogen of high concern and is currently spreading across the United States. Infection control measures for C. auris focus mainly on healthcare facilities, yet transmission levels may already be significant in the community before outbreaks are detected in healthcare settings. Wastewater-based epidemiology (culture, quantitative PCR, and whole-genome sequencing) can potentially gauge pathogen transmission in the general population and lead to early detection of C. auris before it is detected in clinical cases. To learn more about the sensitivity and limitations of wastewater-based surveillance, we used wastewater-based methods to detect C. auris in a southern Utah jurisdiction with no known clinical cases before and after the documented transfer of colonized patients from bordering Nevada. Our study illustrates the potential of wastewater-based surveillance for being sufficiently sensitive to detect C. auris transmission during the early stages of introduction into a community.

Towards geospatially-resolved public-health surveillance via wastewater sequencing

Wastewater is a geospatially- and temporally-linked microbial fingerprint of a given population, making it a potentially valuable tool for tracking public health across locales and time. Here, we integrate targeted and bulk RNA sequencing (N = 2238 samples) to track the viral, bacterial, and functional content over geospatially distinct areas within Miami Dade County, USA, from 2020-2022. We used targeted amplicon sequencing to track diverse SARS-CoV-2 variants across space and time, and we found a tight correspondence with positive PCR tests from University students and Miami-Dade hospital patients. Additionally, in bulk metatranscriptomic data, we demonstrate that the bacterial content of different wastewater sampling locations serving small population sizes can be used to detect putative, host-derived microorganisms that themselves have known associations with human health and diet. We also detect multiple enteric pathogens (e.g., Norovirus) and characterize viral diversity across sites. Moreover, we observed an enrichment of antimicrobial resistance genes (ARGs) in hospital wastewater; antibiotic-specific ARGs correlated to total prescriptions of those same antibiotics (e.g Ampicillin, Gentamicin). Overall, this effort lays the groundwork for systematic characterization of wastewater that can potentially influence public health decision-making.

Drug Use Patterns in Wastewater and Socioeconomic and Demographic Indicators

Importance

Measuring drug use behaviors in individuals and across large communities presents substantial challenges, often complicated by socioeconomic and demographic variables.

Objectives

To detect spatial and temporal changes in community drug use by analyzing concentrations of analytes in influent wastewater and exploring their associations with area-based socioeconomic and sociodemographic metrics like the area deprivation index (ADI) and rural-urban commuting area (RUCA) codes.

Design, Setting, and Participants

This longitudinal, cross-sectional wastewater study was performed from May 2022 to April 2023 and included biweekly influent wastewater samples of 39 analytes from 8 sampling locations across 6 wastewater treatment plants in southern Nevada. Statistical analyses were conducted in December 2023.

Main Outcomes and Measures

It was hypothesized that wastewater monitoring of pharmaceuticals and personal care products (PPCPs) and high-risk substances (HRSs) could reveal true spatial and temporal drug use patterns in near-real time. Data collection of samples for PPCPs and HRSs was performed using mass spectrometry. Both ADI and RUCA scores were utilized to characterize neighborhood contexts in the analysis. The false discovery rate (FDR) method was utilized to correct for multiple comparisons (PFDR).

Results

Over the 12-month wastewater monitoring period, 208 samples for PPCPs and HRSs were collected, and analysis revealed an increase in the consumption of HRSs and the seasonal variation in PPCP use in southern Nevada. There was a significant increase in levels of stimulant-associated analytes, such as cocaine (β = 9.17 × 10-4; SE = 1.29 × 10-4; PFDR = 1.40 × 10-10), and opioids or their metabolites, notably norfentanyl (β = 1.48 × 10-4; SE = 1.88 × 10-4; PFDR = 1.66 × 10-12). In contrast, DEET, an active ingredient in mosquito and tick repellents, demonstrated a seasonal use pattern (β = -4.85 × 10-4; SE = 2.09 × 10-4; PFDR = 4.87 × 10-2). Wastewater from more disadvantaged or rural neighborhoods, as assessed through ADI and RUCA scores, was more likely to show a significant positive correlation with HRSs, such as cocaine (β = 0.075; SE = 0.038; P = .05) and norfentanyl (β = 0.004; SE = 0.001; P = 1.64 × 10-5).

Conclusions and Relevance

These findings suggest that wastewater monitoring of PPCPs and HRSs offers a complementary method to existing public health tools, providing timely data for tracking substance use behaviors and use of PPCPs at a population level.

Prospective study of Candida auris nucleic acids in wastewater solids in 190 wastewater treatment plants in the United States suggests widespread occurrence

Candida auris is an emerging, multidrug-resistant fungal pathogen that poses a significant public health threat in healthcare settings. Despite yearly clinical cases rapidly increasing from 77 to 8,131 in the last decade, surveillance data on its distribution and prevalence remain limited. We implemented a novel assay for C. auris detection on a nationwide scale prospectively from September 2023 to March 2024, analyzing a total of 13,842 samples from 190 wastewater treatment plants across 41 U.S. states. Assays were extensively validated through comparison to other known assays and internal controls. Of these 190 wastewater treatment plants, C. auris was detected in the wastewater solids of 65 of them (34.2%) with 1.45% of all samples having detectable levels of C. auris nucleic-acids. Detections varied seasonally, with 2.00% of samples positive in autumn vs 1.01% in winter (P < 0.0001). The frequency of detection in wastewater was significantly associated with states having older populations (P < 0.001), sewersheds containing more hospitals (P < 0.0001), and sewersheds containing more nursing homes (P < 0.001). These associations are in agreement with known C. auris epidemiology. This nationwide study demonstrates the viability of wastewater surveillance for C. auris surveillance and further highlights the value of wastewater surveillance when clinical testing is constrained.

IMPORTANCE

This study highlights the viability of wastewater surveillance when dealing with emerging pathogens. By leveraging an existing framework of wastewater surveillance, we reveal the widespread presence of C. auris in the United States. We further demonstrate that these wastewater detections are consistent with demographic factors relevant to C. auris epidemiology like age and number of hospitals or nursing homes. As C. auris and other pathogens continue to emerge, the low-cost and rapid nature of wastewater surveillance will provide public health officials with the information necessary to enact targeted prevention and control strategies.

Potential Environmental Reservoirs of Candida auris: A Systematic Review

Candida auris, a multidrug-resistant yeast, poses significant challenges in healthcare settings worldwide. Understanding its environmental reservoirs is crucial for effective control strategies. This systematic review aimed to review the literature regarding the natural and environmental reservoirs of C. auris. Following the PRISMA guidelines, published studies until October 2023 were searched in three databases: PubMed, Web of Science, and Scopus. Information regarding the origin, sampling procedure, methods for laboratory identification, and antifungal susceptibility was collected and analyzed. Thirty-three studies published between 2016 and 2023 in 15 countries were included and analyzed. C. auris was detected in various environments, including wastewater treatment plants, hospital patient care surfaces, and natural environments such as salt marshes, sand, seawater, estuaries, apples, and dogs. Detection methods varied, with molecular techniques often used alongside culture. Susceptibility profiles revealed resistance patterns. Phylogenetic studies highlight the potential of environmental strains to influence clinical infections. Despite methodological heterogeneity, this review provides valuable information for future research and highlights the need for standardized sampling and detection protocols to mitigate C. auris transmission.

Is Candida auris the first multidrug-resistant fungal zoonosis emerging from climate change?

The emergence and evolutionary path of Candida auris poses an intriguing scientific enigma. Its isolation from a pet dog's oral cavity in Kansas, reported by White et al. (T. C. White, B. D. Esquivel, E. M. Rouse Salcido, A. M. Schweiker, et al., mBio 15:e03080-23, 2024, https://doi.org/10.1128/mbio.03080-23), carries significant implications. This discovery intensifies concerns about its hypothetical capacity for zoonotic transmission, particularly considering the dog's extensive human contact and the absence of secondary animal/human cases in both animals and humans. The findings challenge established notions of C. auris transmissibility and underscore the need for further investigation into the transmission dynamics, especially zooanthroponotic pathways. It raises concerns about its adaptability in different hosts and environments, highlighting potential role of environmental and animal reservoirs in its dissemination. Critical points include the evolving thermal tolerance and the genetic divergence in the isolate. This case exemplifies the necessity for an integrated One Health approach, combining human, animal, and environmental health perspectives, to unravel the complexities of C. auris's emergence and behavior.

Wastewater based surveillance can be used to reduce clinical testing intensity on a university campus

Clinical testing has been a vital part of the response to and suppression of the COVID-19 pandemic; however, testing imposes significant burdens on a population. College students had to contend with clinical testing while simultaneously dealing with health risks and the academic pressures brought on by quarantines, changes to virtual platforms, and other disruptions to daily life. The objective of this study was to analyze whether wastewater surveillance can be used to decrease the intensity of clinical testing while maintaining reliable measurements of diseases incidence on campus. Twelve months of human health and wastewater surveillance data for eight residential buildings on a university campus were analyzed to establish how SARS-CoV-2 levels in the wastewater can be used to minimize clinical testing burden on students. Wastewater SARS-CoV-2 levels were used to create multiple scenarios, each with differing levels of testing intensity, which were compared to the actual testing volumes implemented by the university. We found that scenarios in which testing intensity fluctuations matched rise and falls in SARS-CoV-2 wastewater levels had stronger correlations between SARS-CoV-2 levels and recorded clinical positives. In addition to stronger correlations, most scenarios resulted in overall fewer weekly clinical tests performed. We suggest the use of wastewater surveillance to guide COVID-19 testing as it can significantly increase the efficacy of COVID-19 surveillance while reducing the burden placed on college students during a pandemic. Future efforts should be made to integrate wastewater surveillance into clinical testing strategies implemented on college campuses.

Spatial and Temporal Drug Usage Patterns in Wastewater Correlate with Socioeconomic and Demographic Indicators in Southern Nevada

Evaluating drug use within populations in the United States poses significant challenges due to various social, ethical, and legal constraints, often impeding the collection of accurate and timely data. Here, we aimed to overcome these barriers by conducting a comprehensive analysis of drug consumption trends and measuring their association with socioeconomic and demographic factors. From May 2022 to April 2023, we analyzed 208 wastewater samples from eight sampling locations across six wastewater treatment plants in Southern Nevada, covering a population of 2.4 million residents with 50 million annual tourists. Using bi-weekly influent wastewater samples, we employed mass spectrometry to detect 39 analytes, including pharmaceuticals and personal care products (PPCPs) and high risk substances (HRS). Our results revealed a significant increase over time in the level of stimulants such as cocaine (pFDR=1.40×10-10) and opioids, particularly norfentanyl (pFDR =1.66×10-12), while PPCPs exhibited seasonal variation such as peak usage of DEET, an active ingredient in insect repellents, during the summer (pFDR =0.05). Wastewater from socioeconomically disadvantaged or rural areas, as determined by Area Deprivation Index (ADI) and Rural-Urban Commuting Area Codes (RUCA) scores, demonstrated distinct overall usage patterns, such as higher usage/concentration of HRS, including cocaine (p=0.05) and norfentanyl (p=1.64×10-5). Our approach offers a near real-time, comprehensive tool to assess drug consumption and personal care product usage at a community level, linking wastewater patterns to socioeconomic and demographic factors. This approach has the potential to significantly enhance public health monitoring strategies in the United States.

Wastewater surveillance of high risk substances in Southern Nevada: Sucralose normalization to translate data for potential public health action

The COVID-19 pandemic highlighted the value of wastewater surveillance in providing unbiased assessments of incidence/prevalence for infectious disease targets, ultimately leading to the development of local, state, and national programs across the United States. To address the growing epidemic of drug abuse, there have been calls to extend these programs to high risk substances (HRS) and metabolites, while leveraging the experience gained during the pandemic and from ongoing efforts in other countries. This study further advances the science of wastewater surveillance for HRS by (1) highlighting analytical and sewer transport considerations, (2) proposing sucralose normalization to adjust for varying human urine/fecal load and confounded population estimates (e.g., high tourism areas), and (3) characterizing temporal and geographic trends in HRS use. This one-year study across eight sewersheds in Southern Nevada (208 total samples) monitored concentrations of 17 pharmaceuticals and personal care products (PPCPs) and 22 HRS and metabolites, including natural, semi-synthetic, and synthetic opioids. The data indicated a ∼200 % increase in heroin and methamphetamine use since 2010, a stark increase in fentanyl consumption beginning in October 2022, and statistically significant differences in HRS consumption patterns between sewersheds and on certain dates. Notably, the latter outcome highlights the potential for wastewater surveillance data to be strategically translated into public health action to reduce and/or more rapidly respond to overdoses.

Expanding a Wastewater-Based Surveillance Methodology for DNA Isolation from a Workflow Optimized for SARS-CoV-2 RNA Quantification

Wastewater-based surveillance (WBS) is a noninvasive, epidemiological strategy for assessing the spread of COVID-19 in communities. This strategy was based upon wastewater RNA measurements of the viral target, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The utility of WBS for assessing the spread of COVID-19 has motivated research to measure targets beyond SARS-CoV-2, including pathogens containing DNA. The objective of this study was to establish the necessary steps for isolating DNA from wastewater by modifying a long-standing RNA-specific extraction workflow optimized for SARS-CoV-2 detection. Modifications were made to the sample concentration process and included an evaluation of bead bashing prior to the extraction of either DNA or RNA. Results showed that bead bashing reduced detection of RNA from wastewater but improved recovery of DNA as assessed by quantitative polymerase chain reaction (qPCR). Bead bashing is therefore not recommended for the quantification of RNA viruses using qPCR. Whereas for Mycobacterium bacterial DNA isolation, bead bashing was necessary for improving qPCR quantification. Overall, we recommend 2 separate workflows, one for RNA viruses that does not include bead bashing and one for other microbes that use bead bashing for DNA isolation. The experimentation done here shows that current-standing WBS program methodologies optimized for SARS-CoV-2 need to be modified and reoptimized to allow for alternative pathogens to be readily detected and monitored, expanding its utility as a tool for public health assessment.