Occurrence of novel human tomato brown rugose fruit virus and conventional microbial source tracking genetic markers in a Hawaiian coupled stream-beach system

Abstract

Fecal contamination of coastal waters threatens human and ecosystem health. Microbial source tracking (MST) methods offer a strategy to identify sources of fecal contamination through the measurement of genetic markers associated with a particular animal host. In this study, we measured fecal indicator bacteria (FIB) and employed MST methods to evaluate the sources of fecal contamination in a coupled stream-beach system in Kailua Bay, Hawai'i where residents adjacent to the shoreline use onsite cesspools for sewage management. In a baseline campaign, we measured enterococci concentrations in surface water samples from the stream and beach (n = 36). Results indicated that the stream contained enterococci in exceedance of the state standard (50% of samples) and therefore represented a potential source of contamination to the coastal ocean. To identify potential fecal sources, five MST genetic markers – three indicative of human feces (HF183/BacR287, CPQ_056, and ToBRFV), one of dog feces (DG3), and one of avian feces (GFD) – were measured alongside enterococci concentrations and environmental parameters (water temperature, salinity, tidal stage, and rainfall) in stream and beach water samples from longitudinal (n = 78) and spatial (n = 25) sampling campaigns. During the two-week longitudinal campaign, detections were observed for the avian marker (78% of samples positive), human marker ToBRFV (40%), and dog marker (10%), while HF183/BacR287 and CPQ_056 were not detected. Marker detection frequency varied by sampling location, with GFD most frequently detected in the stream and ToBRFV most frequently detected at the site adjacent to cesspools. In the spatial campaign, enterococci concentrations significantly decreased along the stream towards the beach (p < 0.001) but similar trends were not observed for MST markers. The occurrence of human, avian, and canine MST genetic markers in this study confirms these are important sources of fecal contamination in the Kailua Bay area. This study is the first to implement the RNA-based ToBRFV digital PCR assay in tropical coastal waters.

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Environmental significance

Fecal indicator bacteria are commonly used to assess the presence of fecal pollution in recreational waters, but they do not provide insight into the source of the pollution. Microbial source tracking methods can be used to identify contributors to fecal pollution to aid in remediation of water bodies. We found that the novel human fecal marker tomato brown rugose fruit virus can be detected in coastal waters alongside more traditionally used markers, and that it may be a useful marker for human fecal pollution from onsite sanitation systems. This marker may be a useful new target for scientists and regulators looking to track human fecal pollution in coastal recreational waters.

1. Introduction

Coastal waters are of vital cultural, economic, and environmental importance.¹ However, point source and nonpoint source pollution threaten coastal waters around the world, which in turn may endanger human and ecosystem health.² Specifically, pathogens from both human and non-human fecal contamination may pose a health risk to coastal water recreators.² An understanding of the occurrence and origin of fecal contamination in an impacted area is critical to beginning to address and ameliorate this issue.

Fecal indicator bacteria (FIB) like enterococci and Escherichia coli are used around the world to assess microbial water quality in recreational waters.³ While the use of enterococci as fecal indicators is widespread, there is disagreement in the literature about whether enterococci and other fecal indicator bacteria like E. coli correlate with pathogen presence or recreator illness, especially in areas where point source human fecal contamination (e.g., from a sewage spill) may not be the dominant contributor to FIB concentrations.^4–8 Enterococci may exist and replicate in beach sands, grasses, and plants unrelated to fecal sources.⁹ Naturalized enterococci have been observed in tropical soils, drawing into question their utility as an indicator for fecal contamination in this setting.¹⁰ Additionally, enterococci are found in the feces of many warm-blooded animals, meaning determination of sources of fecal contamination is not possible with enterococci measurements alone.¹¹ However, it is important to know the origin of fecal contamination in an area to better understand potential public health risks and inform mitigation efforts, especially since human fecal pollution may pose an elevated risk to human health compared to many other animals given equivalent exposures.¹²

Many microbial source tracking (MST) methods rely on the detection of genetic markers that are strongly associated with a particular animal host (e.g., human, canine). Detecting and quantifying MST markers in the environment can offer more targeted identification of fecal contamination sources than information obtained by measuring general fecal indicators like enterococci. MST markers have been used to identify sources of fecal contamination in a broad array of settings.^13,14 Recently, a tomato brown rugose fruit virus (ToBRFV) digital PCR assay was proposed as a novel human-associated fecal source identification marker¹⁵ and has since only been tested in temperate environmental waters in California¹⁵ and Alabama.¹⁶ ToBRFV is a plant virus that has been found in high concentrations in human stool and wastewater and has been found to be sensitive and specific to human stool.¹⁵ While most conventional human-associated fecal markers detect DNA bacterial and viral targets (e.g., Bacteroides HF183,¹⁷ CPQ_056,¹⁸ HumM2 (ref. 19)), the ToBRFV marker is an RNA target. RNA recovery from environmental samples requires different sample filtration, nucleic acid recovery, and amplification protocols compared to DNA targets, making implementation more technically demanding. However, RNA MST markers may more closely mimic the fate and transport of key enteric RNA viruses, such as norovirus, which is reported to be a significant cause of recreational waterborne illness.²⁰

The goal of this study is to identify fecal pollution sources associated with FIB (i.e., enterococci) measurements in a coupled stream-beach system in Hawai'i using RNA-(ToBRFV) and DNA-based MST genetic markers. With several potential sources of fecal contamination in Kailua Bay, including onsite cesspools used by residents adjacent to the field site,²¹ we measured one canine, one avian, and three human fecal markers in the study area. The canine and avian markers, Bacteroides DG3 (ref. 22) and Helicobacter spp. GFD,^23,24 respectively, and two of the human markers, Bacteroides HF183/BacR287 (ref. 25) and crAssphage-like CPQ_056,¹⁸ have previously been applied to contaminated coastal waters to better understand sources of fecal contamination.^26–29Bacteroides HF183 has been applied in Hawaiian waters to track human fecal contamination.^30–35 The present study also applies the novel human MST marker ToBRFV.¹⁵ Because HF183/BacR287, CPQ_056, and ToBRFV may differ in their concentration, persistence, and transport in new contexts, it is valuable to test these markers in parallel to evaluate their performance in this setting.

2. Methods

2.1 Sample site characterization

Kailua Bay (Hawai'i, USA) is located on the windward side of the island of O'ahu (Fig. 1). The town and surrounding area are served by two wastewater treatment plants, the Kailua Regional Wastewater Treatment Plant and the Marine Corps Base Hawai'i Wastewater Reclamation Facility which treat 14 and 2 millions of gallons of sewage per day, respectively.^36,37 Both facilities discharge their treated effluent from the same location 1549 m offshore of the Mōkapu Peninsula in Kailua Bay.³⁸ Both plants have exceeded permitted effluent bacterial levels on numerous occasions in the past five years, and in September 2023 the United States Environmental Protection Agency entered into an Administrative Order of Consent (AOC) with the Kailua Regional Wastewater Treatment Plant to repair treatment processes due to continued exceedances of bacterial levels in effluent.³⁹ There is a high density of cesspools in the north end of Kailua Bay (Fig. 1). The north end of Kailua Bay is home to the Kawainui Marsh Wildlife Sanctuary, an important habitat for waterbirds. Kawainui Marsh feeds into the Kawainui stream which flows into the bay. Flow out of the stream is tidally modulated, particularly during dry weather with ocean water flowing into the stream mouth during flood tides, and out during ebb tides. During rain events or other large discharge events (i.e., large ebb tides), stream water may impact the beach shoreline, affecting water clarity and potentially water quality. Parks adjacent to the Kawainui Marsh and the beach adjacent to the stream mouth permit dogs which often roam without leashes. The wastewater treatment plants, cesspools, marsh, and dogs represent potential sources of fecal contamination at the study site.

Fig. 1 Map of sampling sites and cesspools in Kailua, HI, USA. Site A is at the Kawainui marsh upstream of the Kawainui stream, Site B is on the Kawainui stream, and Site C is at Castles Beach. Cesspool data is from the Hawai'i Cesspool Prioritization Tool.²¹ Made in ArcGIS Pro (version 3.3.2). Light Gray Base Map⁸⁶ (credits: Esri, TomTom, Garmin, SafeGraph, FAO, GeoTechnologies, Inc, METI/NASA, USGS, EPA US Census Bureau, USDA, USFWS).

Sampling took place at three sites (Fig. 1). Site A is at the Kawainui Marsh (latitude 21.406607, longitude −157.756101) located at the headwaters of the stream. Site B is near the mouth of the Kawainui Stream (latitude 21.423688, longitude −157.744714), located near a large cluster of cesspools. Recreators on paddleboards, kayaks, and small watercraft were observed at this sampling site. Site C is at Castles Beach (latitude 21.420064, longitude −157.744362) adjacent to the mouth of the stream. Castles Beach is used for recreation including swimming, surfing, and paddleboarding.

2.2 Sampling campaigns

Three sampling campaigns were conducted to investigate FIB and MST marker concentrations across the study area (n = 135 total samples). For all sampling campaigns, water samples were collected from the stream bank or the beach at ankle depth, unless otherwise stated. Sterile 1065 mL Whirl-Pak® bags (Whirl-Pak, Pleasant Prairie, Wisconsin, USA) were triple rinsed with sample water before filling and were immediately placed on ice. Two hundred milliliters of sample water were used for analysis in this study. At the same time of sample collection, water temperature (°C) and salinity (ppt) were measured using a YSI Model 30 probe (YSI, Yellow Springs, OH, USA) placed into the water adjacent to where the sample was collected. The time of sample collection was recorded in local time (Hawai'i Standard Time, HST) and the GPS coordinates of the sample location were recorded using the Save Location GPS mobile application.⁴⁰

In the baseline campaign, 36 water samples were collected from two sites, one on the Kawainui stream (Site B) and one at Castles Beach (Site C) from January to April 2024 to assess the spatial and temporal variation of FIB concentrations in the coupled stream-beach system. Water samples were collected around 6:00 twice each week at each site, just before or just after sunrise.

After the end of baseline campaign, we carried out a higher frequency longitudinal sampling campaign; 78 water samples were collected from sites A, B, and C (n = 26 samples from each site) along the Kawainui stream and in Kailua Bay as shown in Fig. 1. Over a period of two weeks in April and May 2024, water samples were collected twice daily from each site in the morning and evening. Sampling times were constrained to the morning and evening to minimize sample exposure to sunlight, as previous work has shown sunlight exposure decreases fecal indicator bacteria concentrations.^41,42 Specific sampling times were chosen to capture equivalent ebb, flood, and transitional tidal conditions (Fig. 2).

Fig. 2 Graph of tide predictions from Moku o Loe monitoring station (blue line) during the sampling period with sampling times (red points).

To investigate potential spatial trends along the Kawainui Stream, 14 water samples were collected upstream (Site A) to the mouth of the stream on the morning of 4 May 2024 between 6:00 and 8:00 during a transitional tide (ebb until low tide at 6:24 and then flood) (Fig. 3). Samples were taken in the morning to minimize sample exposure to sunlight. At Site A, Site B, and the mouth of the stream three samples were taken in the left, middle, and right of the stream to evaluate lateral variability of FIB and MST paired measurements. GPS coordinates for sampling sites were planned and collected using Google My Maps.⁴³ Five grab samples were also taken over the course of the spatial sampling campaign from potential sources or areas of interest outside of the predefined sampling sites (Fig. 3). These five grab samples include three samples taken from the Maunawili Stream which feeds into the Kawainui Marsh (Stream 1, Stream 2, and Stream 3), one sample taken from the wastewater treatment outfall coordinates at the surface of the ocean (Outfall), and one sample taken from the ocean water in a large mass of seaweed just offshore of the beach (Seaweed).

Fig. 3 (A) Map showing locations where samples were collected during the spatial sampling campaign. (B) Map showing locations where grab samples were collected: the wastewater treatment plant outfall, the seaweed at the beach, and the three samples from Maunawili Stream upstream of Kawainui Marsh.

2.3 Enterococci measurement

Enterococci concentrations (most probable number (MPN) per 100 mL) were measured in all samples immediately within 6 hours of collection using the IDEXX Enterolert assay with the Quanti-Tray/2000 according to manufacturer's instructions (IDEXX, Westbrook, ME, USA). The lower limit of detection for the assay was 10 MPN per 100 mL and the upper limit of detection was 24 196 MPN per 100 mL. To interpret enterococci concentrations, the Hawai'i Department of Health threshold of 130 MPN per 100 mL was used as a comparative threshold.⁴⁴

2.4 Water filtration

For samples collected during the spatial and longitudinal campaigns, bacterial and viral nucleic acids were captured by filtration within 12 hours of sample collection. Water samples were stored at 4 °C prior to filtration. Two hundred milliliters of each water sample was vacuum filtered through 47 mm diameter, 0.45 µm-pore size mixed cellulose ester filters (MilliporeSigma, Burlington, MA, USA) using 100 mL disposable filter funnels (Cytiva, Marlborough, MA, USA). Prior to filtration, water samples were augmented with MgCl₂ to a final concentration of 50 mM to promote viral adsorption to the filter.⁴⁵ Addition of MgCl₂ promotes collection of viruses and nucleic acids onto the filter via electrostatic interactions and does not affect the collection of bacterial targets which occurs via size exclusion.⁴⁵ Once the water completely passed through the filter, the vacuum was released and 0.5 mL of RNAlater Stabilization Solution (Invitrogen, Waltham, MA, USA) was added to the filter, allowed to incubate for 5 minutes, and subsequently the vacuum was applied to allow the solution to pass through the filter. RNAlater Stabilization Solution has been shown to provide protection to both DNA and RNA targets for a wide variety of sample types at a range of temperatures.^42–45 The filter was then removed from the disposable filter funnel using sterilized forceps and placed in a sterile cryotube for transport and storage. Daily field blanks were created by filtering molecular water (Invitrogen, Waltham, MA, USA). Cryotubes were stored at −20 °C for up to two weeks before being shipped overnight on ice to Stanford University. They were then stored at −80 °C for nine weeks until being shipped on dry ice to the Andrew W. Breidenbach Environmental Research Center at the United States Environmental Protection Agency, where they were stored at −80 °C for three months until processing.

2.5 Tide level and rainfall

The time of sample collection was used to determine the tide level relative to mean sea level (MSL) using the Moku o Lo'e monitoring station (1612480) operated by the National Oceanic and Atmospheric Administration. Tidal stage during sample collection was classified as ebb if the tide was falling, flood if rising, and transitional if there was a change in tidal direction during a 2-hour window of sample collection, as defined by Boehm and Weisberg.⁴⁶ Rainfall data were collected every morning at 7:00 using a rain gauge (Mateda, ASIN: B0BXS548G8) next to the Kawainui Stream and reported in centimeters (Fig. 1).

2.6 Nucleic acid extraction

Methods reporting follows EMMI guidelines (Fig. S1).⁴⁷ Nucleic acids were extracted and purified from filters using the AllPrep PowerViral DNA/RNA kit (QIAGEN, Hilden, Germany). Three method blanks were included in each sample extraction batch (10 samples per batch). Before extraction, samples were spiked with a working stock of 0.2 µg mL⁻¹ of salmon sperm DNA (Sigma-Aldrich, St. Louis, MO) and 10 µL of reconstituted bovine coronavirus (BCoV) vaccine as a DNA and RNA extraction control, respectively. To reconstitute the BCoV vaccine, 3 mL of phosphate-buffered saline were added to one vial of Zoetis Calf-Guard bovine rotavirus-coronavirus vaccine (catalog no. 50-218-8570) per the manufacturer instructions. The nucleic acids (both DNA and RNA) were extracted in 100 µL total of eluant. Nucleic acid extracts were stored at 4 °C for <24 hours prior to being used as a template in PCR-based assays.

2.7 qPCR amplification

Four host-associated qPCR assays were selected for qPCR testing indicative of human, avian, and canine fecal sources (Table 1). Primer and probe sequences and thermocycling conditions can be found in Table S1 of the SI. qPCR was used to measure HF183/BacR287, CPQ_056, GFD, DG3, and Sketa22 genetic markers. Each instrument run consisted of samples tested in triplicate, six positive controls [National Institute of Standards and Technology Standard Reference Material® 2917 Level 3 (SRM 2917, Rockville, MD, USA)], six no template controls (NTC), and three method blanks run in triplicate. qPCR reactions were 25 µL, containing 1X TaqMan Environmental Master Mix 2.0 (Thermo Fisher Scientific, Waltham, MA, USA), 0.2 mg per mL bovine serum albumin (Sigma-Aldrich, St. Louis, MO, USA), 1 µM primers, 80 nM 6-carboxyfluorescein (FAM)-labeled probe, and 2 µL neat template. qPCR reactions for the HF183/BacR287 assay had an additional 80 nM VIC-labeled probe that acted as an internal amplification control (IAC). qPCR assays were run on the QuantStudio 6 Flex Real-Time PCR System (Thermo Fisher Scientific, Waltham, MA, USA). The threshold was manually set to 0.03 ΔRn for HF183/BacR287, DG3, and Sketa22, and 0.08 ΔRn for GFD.

Table 1 PCR-based assays selected for microbial source tracking analysis

Assay	Type	Platform	Reference
HF183/BacR287	Human-associated bacterial DNA marker	qPCR	25
CPQ_056	Human-associated viral DNA marker		18
GFD	Avian-associated bacterial DNA marker		23 and 24
DG3	Canine-associated bacterial DNA marker		22
Sketa22	DNA control		25
ToBRFV	Human-associated viral RNA marker	dPCR	15
BCoV	RNA control		87

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qPCR calibration curve data was generated using National Institute of Standards and Technology Standard Reference Material 2917 (SRM 2917, Rockville, MD, USA), which has five dilution preparations: Level 1 (10.3 copies per 2 µL), Level 2 (1.11 × 10² copies per 2 µL), Level 3 (1.06 × 10³ copies per 2 µL), Level 4 (1.06 × 10⁴ copies per 2 µL), and Level 5 (1.04 × 10⁵ copies per 2 µL).^48,49 Eight instrument runs were performed for each qPCR assay. Additional information is provided in the SI (Fig. S2). Master calibration curves were generated from the eight calibration runs. qPCR results were classified as non-detect (C_q = 40 for all replicates) or detect (C_q < 40 for at least one replicate). The lower limit of quantification (LLOQ) for qPCR was defined as the 95% credible interval upper-bound from measures of the lowest standard concentration (SRM 2917, Dilution Level 1).

2.8 dPCR amplification

dPCR was used to measure ToBRFV and BCoV genetic markers (Table 1). Each ToBRFV dPCR assay instrument run consisted of unknown samples run in duplicate (due to limited template), a positive control, a NTC, and two method blanks. All dPCR reactions were 40 µL, containing 1X OneStep Advanced Probe Master Mix (QIAGEN, Hilden, Germany), 1X OneStep Advanced Reverse Transcription Mix (QIAGEN, Hilden, Germany), 0.4 µM primers, 0.2 µM probe, 5 µL Enhancer GC (QIAGEN, Hilden, Germany), and 15 µL neat template. For BCoV, 2 µL template was diluted into 13 µL molecular water (Invitrogen, Waltham, MA, USA). dPCR assays were run on the QIAcuity Digital PCR System using the Qiagen OneStep Advanced Probe Kit (QIAGEN, Hilden, Germany) for one-step reverse transcription. Additional dPCR information is provided in the SI.

For dPCR, a 4 nmol Ultramer™ RNA oligo (IDT, Coralville, IA, USA) of the target ToBRFV amplicon was resuspended in 1000 µL of Tris–EDTA buffer and serially diluted to a concentration of 1 × 10² copies per µL for use as a positive control. The limit of detection (LOD) was defined as the lowest concentration of ToBRFV RNA able to be reliably distinguished from the limit of blank (LOB) as defined by Armbruster and Pry.⁵⁰ dPCR results were classified as non-detect (below LOD) or detect (≥LOD). The dPCR limit of quantification (LOQ) was set using a maximum percent coefficient of variation (%CV) of 20% from a precision profile experiment consisting of repeated testing of serial dilutions of the ToBRFV positive control.

2.9 qPCR and dPCR acceptance metrics

All qPCR assay results were evaluated against a series of acceptance criteria that have been previously used in MST studies.^51,52 Briefly, qPCR calibration curve linearity (R²) values must be greater than or equal to 0.980 and amplification efficiency must fall in the range of 0.90 to 1.10.^53,54 For the HF183/BacR287 assay, IAC was used to monitor for amplification inhibition as previously described.⁵⁵ To monitor for suitable IAC proficiency, the standard deviation for the NTC VIC C_q values of the IAC must be less than or equal to 1.16 for each instrument run.⁵⁵ The Sketa22 assay, which served as a sample processing control (SPC), was used to monitor DNA recovery (where samples must not exceed the mean method blank concentration ±1.5C_q for each instrument run). Instrument run specific Sketa22 method blank standard deviations must be less than or equal to 0.62C_q.

To estimate dPCR ToBRFV genetic marker concentrations in a sample, duplicate wells were treated as a single reaction. Positive partitions were converted to concentrations in Excel using the following equation (eqn (1)):

where C is concentration (copies per µL), p_n is the number of negative partitions, p_v is the number of valid partitions, v_c is the cycled volume, v_r is the reaction volume, and v_t is the template volume in the hyperwell. A minimum of 30% of partitions must be valid for a well to be accepted. Manual thresholding was performed using precision profile data to set a master threshold for each dPCR assay used across all instrument runs (see Fig. S3 for example threshold). BCoV was used as a quality control metric as follows: sample BCoV concentrations were accepted if they fell within 0.1× to 10× of the instrument-run specific mean method blank BCoV concentration. Additional details of BCoV performance can be found in the SI.

2.10 Statistical analyses

All statistical analyses were conducted in R version 4.4.2 (ref. 56) using RStudio.⁵⁷

For the longitudinal sampling campaign, Pearson's correlation coefficient tests were performed to test the null hypothesis that the correlation coefficient between enterococci concentration and environmental variables (salinity, water temperature, and rainfall) is not different from 0. The Benjamini–Hochberg correction was applied to adjust for multiple testing for each family of tests.

For the longitudinal sampling campaign, confidence intervals for MST marker detection frequencies were generated using a Wilson score with continuity correction. Chi-square or Fisher's exact (when expected counts were <5) tests were performed to test two null hypotheses: (1) that marker detection frequencies are the same across MST marker type, and (2) for each MST marker, that marker detection frequencies are the same across locations. Post hoc pairwise chi-square tests with Benjamini–Hochberg corrections to adjust for multiple testing were performed to analyze which pairings were significantly different. Kruskal–Wallis tests were also performed to test the null hypothesis that the medians of environmental variables (enterococci concentration, water temperature, and salinity) are equal across locations. Post hoc Dunn's tests with Benjamini–Hochberg corrections for multiple testing were performed to analyze which pairings were significantly different.

Logistic regression was employed to examine the correlation between environmental measurements and MST marker detection. First, univariate analysis was performed to test the null hypothesis that the predictor variable has no relationship to MST marker detection for the following predictor variables: enterococci concentration, tidal stage, rainfall in previous day (binary outcome), water temperature, salinity, sampling site, and time of sampling (morning or evening). Each predictor variable was compared to the dependent variable, detection of the MST marker (binary outcome). Any univariate correlation between a variable and MST marker dataset that had a p-value <0.25 was selected for inclusion in the multivariable logistic regression model. This process was repeated for each MST marker. Multicollinearity was evaluated using the variance inflation factor (VIF) with the car package in R, where any variables with a VIF higher than 5 were removed from the model for severe multicollinearity.⁵⁸ The Benjamini–Hochberg correction was applied for multiple testing for each family of tests in the logistic regression.

For the spatial sampling campaign, linear regression was performed to examine the relationship between the distance along the stream in meters (as measured in ArcGIS Pro version 3.3.2) and enterococci concentration to test the null hypothesis that there is no association between location and enterococci concentration.

3. Results

3.1 qPCR and dPCR performance

For qPCR-based assays, calibration model R² values >0.980 and E ranged from 0.967 to 0.981 (acceptance criteria 0.90–1.10). Only 1.4% (5 of 360) of water samples failed the SPC metric, falling outside the instrument run-specific mean method blank concentration +1.5C_q acceptance threshold, indicating inconsistent DNA recovery. These samples were discarded from the study. The batch-specific standard deviations of Sketa22 method blank C_q values ranged from 0.10 to 0.32 (acceptance criterion ≤0.62), indicating acceptable SPC proficiency. 100% of samples passed IAC proficiency thresholds, indicating no evidence of amplification inhibition. IAC proficiency was acceptable across all instrument runs, where HF183/BacR287 IAC NTC C_q standard deviations ranged from 0.11 to 0.35 (acceptance criterion ≤1.16). LLOQ C_q values for qPCR assays were as follows: 32.9 for HF183/BacR287, 35.3 for CPQ_056, 32.8 for DG3, and 32.3 for GFD. For all qPCR assays (HF183/BacR287, CPQ_056, DG3, and GFD), no amplification was observed in all NTC, method blank, and field blank controls (n = 1068 reactions). Amplification was observed in 284/288 positive controls, with only four positive controls failing due to presumed pipetting error. The LOB for the ToBRFV dPCR assay was calculated to be 0.016 copies per mL sample (2.48 copies per reaction where reaction refers to the data obtained from the two merged wells), the LOD was calculated to be 0.105 copies per mL sample (16.7 copies per reaction), and the LOQ was 1.05 copies per mL sample (169 copies per reaction) using the 20% CV threshold from precision profile experiments. For ToBRFV, all NTC, method blank, and field blank controls were below the limit of detection. All ToBRFV positive controls were positive for the target. All samples fell within 0.1× to 10× of the instrument-run specific mean method blank BCoV concentration (range: 0.16× to 1.59×), indicating acceptable RNA sample processing proficiency.

Genetic marker concentrations were rarely observed within the range of quantification (ROQ) (Table 2): ToBRFV (n = 3), DG3 (n = 1), and GFD, HF183/BacR287, and CPQ_056 (n = 0). As such, statistical analyses focused on detection frequencies for MST genetic marker datasets.

Table 2 Percentage of all samples classified as detected and quantified for each MST marker assay, median copies per mL sample for samples in the range of quantification, and copies per mL sample range, if applicable

Assay	Percent detected	Percent quantified	Median (ROQ) (copies per mL sample)	Range (ROQ) (copies per mL sample)
HF183/BacR287	<1% (1/103)	0% (0/103)	N/A	N/A
CPQ_056	<1% (1/103)	0% (0/103)	N/A	N/A
ToBRFV	34% (35/103)	3% (3/103)	1.7	1.5–7.4
DG3	8% (8/103)	1% (1/103)	3.5	N/A
GFD	82% (84/103)	0% (0/103)	N/A	N/A

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3.2 Baseline campaign results

During the baseline campaign (January to April 2024), a total of 36 samples were collected. Enterococci concentrations exceeded the HDOH regulatory threshold in half of samples from Site B (Kawainui Stream) and one sample at Site C (Castles Beach) (Fig. 4).

Fig. 4 Enterococci concentrations (MPN per 100 mL) measured by the IDEXX Enterolert assay, where 0 represents <10 MPN per 100 mL (below detection). Error bars represent lower and upper 95% confidence limits. The red dashed line is at 130 MPN per 100 mL, the threshold for recreational water as set by the Hawai'i Department of Health.

This sampling campaign informed the site selection of the longitudinal sampling campaign. The marsh at the headwaters of the stream (Site A) was added for the longitudinal sampling campaign as a sampling site due to its position upstream of the stream sampling site (Site B), where consistently high enterococci concentrations were measured during the baseline sampling campaign. Sites B and C were maintained as sampling sites due to frequent (50%) enterococci exceedances at Site B and the recreational importance of Site C.

3.3 Longitudinal sampling campaign environmental measurements and FIB results

Nine ebb tide events, eight flood tide events, and nine transitional events were captured over the course of the longitudinal sampling campaign. Rain events were observed on 50% of the sampling dates (7 of 14 days). Daily precipitation totals ranged from 0.2 to 1.6 cm.

Salinity generally increased from Site A (mean 4.1 ± 1.5 ppt) to Site B (mean 22.2 ± 5.5 ppt) to Site C (mean 34.4 ppt ± 0.4 ppt). Variable salinity measurements at Site B (seen by a large standard deviation) show that the site was tidally impacted, with higher salinity measurements during flood tides and lower salinity measurements during ebb tides (Fig. S4). Salinity was significantly different between all sites (Kruskal–Wallis, p < 0.001; Dunn's test, p < 0.001 for A vs. B and A vs. C and p = 0.001 for B vs. C). Water temperature was the lowest at Site A (mean 23.4 ± 1.7 °C) and the highest at Site B (mean 25.5 ± 1.4 °C), with Site C falling in the middle (mean 24.7 °C ± 1.0 °C). Water temperature was significantly different between Sites A and B and A and C, but not between Sites B and C (Kruskal–Walli, p < 0.001; Dunn's test, p < 0.001 for A versus. B, p = 0.002 for A versus C, p = 0.054 for B versus C). Tide, precipitation, temperature, and salinity data can be found in the SI.

Across sampling sites, we examined spatial variation in environmental measurements. Enterococci concentrations were consistently highest at Site A, with a median concentration of 195 MPN per 100 mL (Fig. 5). Eighty five percent of samples at Site A were above the HDOH threshold of 130 MPN per 100 mL. At Site B, the median enterococci concentration was 36 MPN per 100 mL, with only one sample exceeding the HDOH threshold. Enterococci concentrations were lowest at Site C, with two samples above the LOD (both at 10 MPN per 100 mL) and the rest below. Enterococci concentrations were significantly different between all sites (Kruskal–Wallis, p < 0.001; Dunn's test, p < 0.001 for all pairwise comparisons).

Fig. 5 Enterococci concentrations (MPN per 100 mL) measured by the IDEXX Enterolert assay, where 0 represents <10 MPN per 100 mL (below detection). Error bars represent lower and upper 95% confidence limits. The red dashed line is at 130 MPN per 100 mL, the threshold for recreational water as set by the Hawai'i Department of Health. On the x-axis, an M after the date represents “morning” and an E represents “evening” for time of sampling. Blue background indicates one day antecedent rainfall for the date on the x-axis.

Using data from the longitudinal sampling campaign, we tested the correlation between enterococci concentration and several environmental factors (water temperature, salinity, and antecedent one day rainfall) using Pearson's correlation coefficient for each environmental factor and applying a Benjamini–Hochberg correction for multiple testing. Water temperature (R = −0.34, p = 0.003) and salinity (R = −0.60, p < 0.001) were both significantly and negatively correlated with enterococci concentration, whereas antecedent one day rainfall was significantly and positively correlated with enterococci concentration (R = 0.37, p = 0.001). Water temperature was also significantly correlated with salinity (R = 0.44, p < 0.001).

3.4 Longitudinal sampling campaign MST results

Detection frequencies of MST markers differed by assay and site (Fig. 6). GFD was detected the most frequently across sites (78%), followed by ToBRFV (40%) and DG3 (10%). The difference in detection frequencies across markers was statistically significant (p < 0.001) and was observed in all post hoc pairwise comparisons (ToBRFV versus DG3, ToBRFV versus GFD, and DG3 versus GFD). HF183/BacR287 and CPQ_056 were not detected in samples collected during the longitudinal sampling campaign.

Fig. 6 (A) Detection frequency of MST markers across all sampling sites (n = 78 for each marker). (B) Detection frequency of MST markers separated by sampling site, where A is the marsh site, B is the stream site, and C is the beach site (n = 26 for each site and marker). Error bars represent 95% confidence intervals which were generated using a Wilson score with continuity correction. HF183 refers to the HF183/BacR287 assay and crAssphage refers to the CPQ_056 assay.

Detection frequencies also differed for each marker across sampling sites. While a higher detection frequency of ToBRFV was observed at site B as compared to sites A and C (58% versus 35% and 27%, respectively), no statistically significant difference was found across sites (chi-square test, p = 0.06). DG3 was not detected in samples from Site B, but was detected at Sites A and C. A statistically significant difference was found across sites for DG3 (Fisher's exact test, p = 0.02), and post hoc pairwise testing showed this difference was statistically significant only for Site A versus Site B (p = 0.02). GFD was detected in all samples from Sites A and B, and in 35% of samples from Site C. A statistically significant difference was found for GFD detection across sites (chi-square test, p < 0.001), and post hoc pairwise testing showed this difference was statistically significant for Site A versus Site C (p < 0.001) and Site B versus Site C (p < 0.001).

3.5 Longitudinal sampling correlations between MST, FIB, and environmental measurements

Associations between MST markers and environmental measurements (enterococci concentration, tidal stage, antecedent one day rainfall, water temperature, salinity, sampling site, and time of sampling) were investigated using logistic regression. P-Values for the univariate analysis used to screen variables for inclusion in the logistic regression models are shown in the SI (Table S2). GFD was excluded from the logistic regression analysis because the 100% detection frequency (all below the LOQ) in all samples from Sites A and B make the dataset unsuitable for logistic regression (see SI for details). A significant relationship was observed between rainfall in the previous day and ToBRFV detection (β = 1.49, p = 0.025). No significant relationships were observed between predictors and marker detection for DG3 (Table S3).

3.6 Spatial sampling campaign results

The spatial sampling campaign consisted of 14 samples collected from Site A to the mouth of the stream during a transitional tidal stage (Fig. 3). At three of the locations (Site A, Site B, and the mouth of the stream), two additional samples were collected near each bank. Sample results show a general decrease in enterococci concentration along the stream from the marsh to the bay (Fig. 7), but this trend was not mirrored by any MST marker. The observed decreasing trend in enterococci concentration with distance along the stream (m) was confirmed to be statistically significant (p < 0.001). Enterococci and MST results showed similar concentrations across lateral samples suggesting limited lateral variation across the stream (Fig. S6). The avian marker GFD was detected in 100% of samples. ToBRFV was detected in two samples, one upstream of the cesspools and one at the mouth of the stream.

Fig. 7 (A) Enterococci concentrations (MPN per 100 mL) measured by the IDEXX Enterolert assay, where 0 represents <10 MPN per 100 mL (below detection) measured down the stream. Error bars represent lower and upper 95% confidence limits. The red dashed line is at 130 MPN per 100 mL, the threshold for recreational water as set by the Hawai'i Department of Health. (B) Heatmap of MST markers measured down the stream for the spatial sampling campaign. Detects are shown in red and nondetects are shown in white. HF183 refers to the HF183/BacR287 assay and crAssphage refers to the CPQ_056 assay.

MST markers and enterococci were detected in some of the five grab samples taken outside of the predefined sampling sites (Table S4). No enterococci or MST marker was detected in samples taken from near the ocean outfall or the seaweed. GFD was detected in all three Maunawili Stream samples. Interestingly, all three human markers (HF183/BacR287, CPQ_056, and ToBRFV) were detected in the third Maunawili Stream sample taken just upstream of the Kawainui Marsh, the only such detection in the study. This sample also exceeded the state enterococci threshold with a concentration of 216 MPN per 100 mL. ToBRFV alone was detected in the first Maunawili Stream sample farthest upstream, and both the first and second stream sample had enterococci concentrations of 41 MPN per 100 mL.

4. Discussion

Findings suggest that the stream in the coupled stream-beach system in Kailua Bay, Hawai'i is a potential source of enterococci and MST markers to the beach. Concentrations of enterococci were consistently elevated in the stream and were lower when the stream water (freshwater) mixed with ocean water along the length of the stream. Sources of enterococci to the stream are likely mostly birds, but evidence suggests that other fecal sources, including dogs and humans, contribute. A study conducted in 2011 found that bacterial pathogens were widespread in Oahu streams and detected Salmonella enterica Typhimurium, Campylobacter, Staphylococcus aureus, and Vibrio spp. pathogens in the stream in this study.⁵⁹ The detection of bird, human, and dog MST markers for fecal contamination coupled with previous evidence of bacterial pathogens in the stream suggests that stream water may pose a health risk to recreators. Although the beach site was generally of excellent water quality during the study, the water quality there is likely to be degraded when the stream discharge impacts the beach. The transport of small stream discharges can be affected by their momentum and density, as well as the oceanographic conditions in the coastal ocean including wind-driven and tidally-driven currents.⁶⁰ In particular, high turbidity and colored waters indicative of stream discharge have been observed at the beach site after large rain events suggesting such conditions can lead to stream discharge impinging on the adjacent shoreline. The Hawai'i Department of Health advises recreators to avoid contact with ocean water at the beach site during “Brown Water Advisories” after large rain events.

We provide evidence of human, dog, and avian contributions to fecal contamination in the stream-beach system. The avian fecal marker (GFD) was detected most frequently in samples, as it was found in 100% of samples taken from the stream. Previous work has suggested that Campylobacter is an important human pathogen in gull and chicken feces.⁶¹ Although data is limited for Hawaiian waterbirds, Campylobacter was detected in 5% of cloacal swabs in a survey of Hawaiian ducks.⁶²Salmonella may also be found in bird feces.^63,64 Both Campylobacter and Salmonella have been found in Oahu streams, including in the stream in this study.⁵⁹ Exposure to Campylobacter or Salmonella from bird feces can present a health risk.

The dog-associated marker DG3 was found in 8% of samples, most of which were from Site A at the marsh, but also from Site C. Site A is adjacent to a park which is frequented by dog walkers, and dogs often run off leash at Site C on the beach. Dog feces have been found to contain a variety of human pathogens including Salmonella, Campylobacter, Cryptosporidium spp., and rotaviruses,⁶⁵ as well as antibiotic-resistant bacteria.⁶⁶ Methods to increase the collection of dog waste (e.g., availability of waste bags, signs reminding dog owners to pick up their waste)^67,68 could potentially reduce inputs of dog feces at the study sites.

The human-associated marker ToBRFV was detected in 34% of samples, indicating that this RNA-based target can be detected on a routine basis in fresh and marine tropical waters. Logistic regression yielded a significant correlation between marker detection and one day antecedent rainfall but not between enterococci or other environmental measurements. A lack of correlation between human MST markers and FIB has been previously observed in the literature.^69–71 In the longitudinal sampling campaign, detection frequencies were highest at Site B which is adjacent to a large number of cesspools (Fig. 1). Previous work has found rainfall is associated with increased fecal pollution from on-site waste management systems,^72–74 suggesting that cesspools may be a source of ToBRFV detections in this study. The cesspools in Kailua Bay have been identified by the Hawai'i Cesspool Prioritization Tool as Priority Level 1: “the greatest potential to impact human health and the environment”.²¹ While the state of Hawai'i has mandated that all cesspools be upgraded by 2050, there are many barriers to achieving this goal (e.g., limited understanding of source and risk of pathogens in water, few studies on longitudinal patterns of fecal contamination, and uncertainty on naturalized indicator concentrations).⁷⁵ This study contributes longitudinal measurements of a new human-associated marker in an area of high importance for cesspools. Sampling wastewater directly from cesspools for ToBRFV and conducting extended sampling in this area may be useful in the future.

Out of the three human-associated markers included in this study, we report frequent detections of ToBRFV but only detected HF183/BacR287 and CPQ_056 (along with ToBRFV) in one sample. This could be due to a variety of factors. First, dPCR was used to measure ToBRFV while qPCR was employed to quantify HF183/BacR287 and CPQ_056 because the assays chosen were optimized to their respective platforms. Due to a difference in template volumes between dPCR and qPCR (15 µL versus 2 µL) combined with an increase in precision for detection of rare targets from partitioning and reduced background noise,⁷⁶ a higher sensitivity with dPCR is expected. This may result in a difference in detection frequency if targets exist in similar concentrations in the environment. Additionally, HF183/BacR287 and CPQ_056 are both DNA targets, whereas ToBRFV is an RNA target. This chemical distinction may result in a difference in detection of the target, or in a difference of fate and transport in the environment. Evidence suggests that ToBRFV is highly persistent in tap water, with RNA detectable after 15 weeks.⁷⁷ However, no studies to date have examined ToBRFV persistence in environmental waters, making it difficult to compare persistence to other human-associated markers. Similarly, there is limited data on the concentration of ToBRFV in wastewater, with two groups reporting wastewater concentrations ranging from 3.5 to 8 log₁₀ copies per L in Louisiana and Nevada, USA respectively^78,79 and one group reporting 10.5 log₁₀ copies per g of wastewater solids in California, USA.¹⁵ In comparison, the log₁₀ mean of HF183 in wastewater in the USA was 8.2 log₁₀ copies per L,⁸⁰ and CPQ_056 has been reported to range from 8.2 to 10.3 log₁₀ copies per L.⁸¹ Despite limited information on ToBRFV persistence and concentration in wastewater, existing work suggests that ToBRFV may be highly persistent in the environment and/or may occur at similar or higher concentrations compared to HF183 and CPQ_056.

In this study, there was a significant and positive correlation between enterococci concentrations and one day antecedent rainfall and between ToBRFV detection and one day antecedent rainfall, but there was not a significant correlation between enterococci concentrations and the detection of the human- or dog-associated markers This suggests that enterococci may be originating from more than one source. Conversely, the GFD marker was detected in all samples with enterococci concentrations greater than 10 MPN per 100 mL. This observation is supported by previous work that showed waterfowl feces are a source of enterococci.⁸² Naturalized enterococci populations in sand or vegetation may also be contributing to enterococci concentrations.¹¹

There are several limitations to this study. First, we did not evaluate the presence of the human-associated marker ToBRFV in Hawaiian wastewater, human feces, or other local animal feces. However, ToBRFV has been detected in wastewater from the mainland United States as well as from countries and climates around the world including Mexico,⁸³ Spain,⁸⁴ and Thailand,⁸⁵ providing evidence for the global distribution of ToBRFV in wastewater. MST data only represented two weeks of time, and our sampling did not capture any large rain events (greater than 1.6 cm in 24 hours). Finally, most samples in this study fell below the ROQ, limiting quantification of marker concentrations and subsequent statistical analyses. The use of dPCR for all assays or larger sample volumes may result in a greater number of samples falling within the ROQ, allowing for more quantitative comparisons of marker concentrations.

Future studies should explore the presence and quantification of ToBRFV across diverse geographic locations, especially in countries where the virus is endemic to evaluate further its utility as an MST marker. Additionally, more information on the persistence of ToBRFV in the environment, especially in aquatic environments where MST is commonly employed, would be valuable in helping to interpret detections. The measurement of human pathogens in the study area alongside their indicators would be useful to evaluate the best performing marker for the study area and better inform health risks to recreators. Finally, further work on the identification and selection of a stable and consistent RNA control is important in the quality assurance and control of molecular data.

5. Conclusions

In this study, ToBRFV was successfully employed as a novel human-associated fecal contamination marker for coastal recreational waters, indicating it can be detected in coastal and tropical freshwaters. The three sampling campaigns found enterococci in the stream of a coupled beach-stream system in Kailua Bay, Hawaii and detected bird-, human-, and dog-associated MST markers of fecal contamination in the system. Human-associated marker ToBRFV was detected most frequently at a site adjacent to homes that use cesspools, suggesting that ToBRFV may be able to detect potential human fecal contamination from onsite waste management systems. Future work should measure ToBRFV in cesspools and surrounding areas to further evaluate its utility. The occurrence of cultivated enterococci and MST genetic markers in the stream indicates that the stream may be a source of fecal contamination to the beach.

Conflicts of interest

There are no conflicts to declare.

Data availability

Datasets for this manuscript can be found in the Stanford Digital Repository (https://purl.stanford.edu/dg145fy0414).

Supplementary information (SI) is available. See DOI: https://doi.org/10.1039/d5em00373c.

Acknowledgements

The authors would like to thank Patie Boehm, Alissa Rogers, Jenny Lum, and Levani Lipton for their help in sampling, field logistics, and community involvement. The graphical abstract was created in BioRender (created in BioRender. Zulli A. (2025) https://BioRender.com/p8raefo). SAL was supported by a U.S. National Science Foundation Graduate Research fellowship no. DGE-1656518 and NSF INTERN supplement 2415705. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation. Information has been subjected to U.S. EPA peer and administrative review and has been approved for external publication. Any opinions expressed in this paper are those of the authors and do not necessarily reflect the official positions and policies of the U.S. EPA. Any mention of trade names or commercial products does not constitute endorsement or recommendation for use.

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