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. 2023 Nov 22;48(1):5–13. doi: 10.1007/s12639-023-01634-2

Source tracking of fecal contamination in Asian green mussels (Perna viridis) harvested in Manila Bay, Philippines by molecular detection and genotyping of Cryptosporidium spp.

Mark Raymond A Vejano 1, Laurice Beatrice Raphaelle O dela Peña 1, Windell L Rivera 1,✉
PMCID: PMC10908986  PMID: 38440756

Abstract

Manila Bay, a multipurpose body of water located around Metro Manila, Philippines, is progressively deteriorating because of massive pollution. Reports have shown that the bay and its aquatic resources (i.e., seafood) are contaminated with fecal matter and enteric pathogens, posing a threat to public health and industry. This problem raises the need for a microbial source tracking methodology as a part of the rehabilitation efforts in the bay. Bivalve mollusks cultivated in water can serve as sentinel species to detect fecal pollution and can complement water monitoring. With the use of polymerase chain reaction and DNA sequence analysis, this study detected Cryptosporidium spp. in Asian green mussels (Perna viridis) cultivated and harvested in Manila Bay and sold in Bulungan Seafood Market, Parañaque, Philippines, from 2019 to 2021 with an overall occurrence of 8.77% (n = 57). The analysis of the 18S rDNA segment revealed three genotypes from Cryptosporidium-positive samples, namely, Cryptosporidium sp. rat genotype IV (60%), C. galli (20%), and C. meleagridis (20%). These findings suggest fecal pollution in bivalve cultivation sites coming from sewage, nonpoint, and agricultural sources. The presence of C. meleagridis, the third most common cause of human cryptosporidiosis, in mussels poses a threat to human health. Thus, there is a need to establish routine detection and source tracking of Cryptosporidium spp. in Manila Bay and to educate seafood consumers on food safety.

Keywords: Cryptosporidium, Manila Bay, Microbial source tracking, Perna viridis, Philippines

Introduction

Manila Bay, a semi-enclosed coastal body surrounded by the provinces of Bataan, Pampanga, Bulacan, Metro Manila, and Cavite in the Philippines, is best known for its essential role in numerous industries, including aquaculture (Raña et al. 2017). The bay has a 17,000 km2 watershed with 26 catchment areas and is surrounded by heavy industries, refineries, and a power plant (Jacinto et al. 2006). Because of overpopulation, industrialization, and other anthropogenic activities around and within the area, Manila Bay is considered massively polluted and deteriorating (Mamon et al. 2016). Ecological stresses responsible for the decline in water quality include chemical, heavy metal, and fecal contamination (Jacinto et al. 2006). Reports from the Department of Environment and Natural Resources (DENR) indicate a decline in fecal coliform counts in monitoring areas in the bay from 2020 to 2021. However, the counts still do not conform to safe levels dictated by water quality criteria (DENR 2021).

The presence of fecal coliforms in water reflects the extent of fecal contamination and the presence of some enteric pathogens (Curutiu et al. 2019). One underreported enteric pathogen in the country is Cryptosporidium spp., a protozoan parasite of global importance linked to a diarrheal disease called cryptosporidiosis in humans and animals (Hijjawi et al. 2022). Cryptosporidium is acquired via the fecal–oral route, with contaminated water and food as the most common vehicles of transmission (Shrivastava et al. 2017). The transmission of the pathogen can also be zoonotic and anthroponotic (Fayer 2004).

Cryptosporidium has been the cause of large outbreaks in drinking water sources in the 1990s, requiring health authorities to establish routine monitoring and water quality guidelines (Gururajan et al. 2021). In the Philippines, the pathogen has been detected in lake waters and rivers, as well as aquatic commodities like edible bivalves (dela Peña et al. 2017, 2021; Pagoso and Rivera 2017; Paller et al. 2013), which poses considerable risks for communities dependent on aquatic bodies for food and livelihood.

The consumption of seafood, such as bivalves, is very common in the Philippines. A study by Bolo et al. (2019) determined that consuming at least 21 g of cooked mussels contaminated with at least 0.1% of viable Cryptosporidium is enough to cause a disease in consumers. This finding raises the pressing need to perform microbial source tracking (MST) of fecal contamination in water bodies, especially those used to cultivate seafood. The presence of pathogens in bivalve cultivation sites is especially problematic as these animals are filter feeders and can concentrate contaminants in their tissues (Oliveira et al. 2016).

This study aimed to determine the occurrence of Cryptosporidium from Asian green mussels (Perna viridis) cultivated and harvested in Manila Bay and sold in Bulungan Seafood Market in Parañaque, Philippines, using polymerase chain reaction (PCR) detection of the 18S rDNA and to source track fecal contamination in these aquatic resources using DNA sequence and phylogenetic analyses.

Materials and methods

Sample collection and processing

Sample collection and processing were adapted from the study of Pagoso and Rivera (2017). Fifty-seven pooled mussel samples were collected from Bulungan Seafood Market in Parañaque, Philippines (Fig. 1), using non-probability purposive sampling from February 2019 to June 2021. Each sample contained 30 g of digestive glands from 20 to 25 adult P. viridis cultivated and harvested from Manila Bay. The extracted digestive glands were homogenized in 5 mL of distilled water and sieved through a double-layered gauze. The oocysts were pelleted by centrifugation at 1000×g at 4 °C for 10 min.

Fig. 1.

Fig. 1

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Map showing Bulungan Seafood Market’s location in Parañaque, Philippines (red pin). The market is close to the Las Piñas–Parañaque Wetland Park, a critical habitat for migratory and local birds, and P. viridis was harvested from Manila Bay. Inset: A portion of the Philippine map showing the approximate location of the sampling site (Maxar 2023)

Oocyst concentration

Oocyst concentration was determined via sucrose flotation adapted from the World Organisation for Animal Health (2018). The pelleted samples were mixed with 20 mL of sucrose solution (specific gravity: 1:18), and the suspension was centrifuged at 1100×g for 5 min. The upper layer and the interphase containing the oocysts were aspirated, pelleted by re-centrifugation, and washed three times with deionized distilled water. The final pellet was suspended in 1 mL of 1 × phosphate-buffered saline solution.

Oocyst wall disruption and DNA extraction

Samples were subjected to eight freeze–thaw cycles to facilitate oocyst wall disruption (Pagoso and Rivera 2017) by freezing the samples in an ethanol bath with dry ice for 5 min and immediately thawing them in a dry heat block set at 95 °C for 1 min. DNA extraction was performed using the PureLink™ Microbiome DNA Purification Kit (Invitrogen, California, USA) following the manufacturer’s instructions, except that the final elution volume was set at 50 μL for a higher DNA concentration. The DNA samples were stored at − 20 °C until further use.

18S rDNA PCR assay

Presumptive detection of Cryptosporidium spp. was conducted using a nested PCR scheme adapted from the study of Nichols et al. (2003) and Nichols et al. (2010) with modifications. The primary PCR run used the primer set WR49F-XR1 targeting a ~ 982-bp segment of the 18S rDNA. The PCR mix consisted of 12.5 μL of 2 × GoTaq® Green Mastermix (Promega Corporation, Wisconsin, USA), 200 nM each of both forward and reverse primers (Macrogen Inc., Seoul, South Korea), bovine serum albumin (Vivantis, Selangor Darul Ehsan, Malaysia) at 400 μg/mL, nuclease-free water, and 2.5 μL of DNA template in a total of 25 μL of reaction volume. The PCR conditions were as follows: initial denaturation at 95 °C for 5 min; 35 cycles of denaturation at 94 °C for 30 s, annealing at 60 °C for 1 min, and extension at 72 °C for 1 min; and a final extension at 72 °C for 10 min. The secondary PCR run used the primer set CPB-DIAGF/R targeting a ~ 435-bp segment of the primary PCR product. The PCR mix composition for the secondary run is the same as that of the primary PCR, except that 3.75 μL of the primary PCR product was used as the DNA template. The PCR conditions were as follows: initial denaturation at 95 °C for 5 min; 35 cycles of denaturation at 94 °C for 30 s, annealing at 61.1 °C for 1 min, and extension at 72 °C for 30 s; and a final extension at 72 °C for 10 min. The PCR assay’s limit of detection was determined by performing serial dilutions of C. meleagridis DNA. DNA concentrations were quantified using a fluorometer. The highest dilution with at least 95% amplification success rate was determined as the limit of detection. The quantity of DNA was converted to an approximate number of oocysts (Coupé et al. 2005).

Visualization and purification of PCR products

PCR products were electrophoresed at 2% agarose gel with SYBR™ Safe DNA Gel Stain (Invitrogen, California, USA) at 280 V for 40 min and viewed under UV transillumination. Band sizes were determined using Hyperladder™ 100 bp molecular ladder (Meridian Bioscience, Ohio, USA). Distinct bands viewed corresponding to the target size of the secondary PCR run were considered presumptively positive (Fig. 2). PCR products with either smears or multiple bands were purified using a band-stab PCR protocol from the study by Bjourson and Cooper (1992).

Fig. 2.

Fig. 2

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Presumptive detection of Cryptosporidium spp. using 18S rDNA PCR amplification. The sample image shows amplicons electrophoresed in 2% agarose gel and viewed under UV transillumination (lane 1: molecular weight ladder, lanes 2–5: presumptive Cryptosporidium spp. 18S rDNA amplicons (~ 435-bp), lane 6: no template control)

Phylogenetic analysis of Cryptosporidium sequences

PCR products were transported to Macrogen Inc. (Seoul, South Korea) for PCR clean-up and bidirectional DNA sequencing. Succeeding DNA analyses were conducted in MEGA X (Kumar et al. 2018). Forward and reverse sequences were aligned and trimmed to create consensus sequences (i.e., OQ080026–OQ080029 and OQ080033). A multiple alignment of consensus test sequences and reference sequences of Cryptosporidium species obtained from the GenBank® database (Benson et al. 2017) was performed to determine the optimal DNA substitution model (i.e., the model with the lowest Bayesian information criterion score). Lastly, genotyping of Cryptosporidium sequences was conducted using maximum likelihood analysis with 1000 bootstrap replicates. The constructed phylogenetic tree was rooted in the outgroup, Eimeria tenella.

Determination of seasonal variation

Fisher’s exact test at a significance level α = 0.05 was implemented in R version 4.2.2 (R Core Team 2022) to determine if there is a seasonal variation in the presence of Cryptosporidium in the samples. Season type (i.e., Type I) is based on the modified Corona classification (Lantican 2001).

Results and discussion

The use of host-specific markers of bacteria (e.g., Bacteroidetes and Bifidobacterium), viruses (e.g., HAdV and PAdV), and protozoa (e.g., Cryptosporidium) has recently been exploited in MST, specifically in a major subcategory called library-independent methods (Ballesté et al. 2010; Bortagaray et al. 2019; Ruecker et al. 2007). A few studies have used Cryptosporidium spp. as a source tracking tool in significant water bodies (dela Pena et al. 2021; Prystajecky et al. 2014).

The study by Prystajecky et al. (2014) in a mixed-use watershed in British Columbia, Canada, highlights the promising potential in MST of Cryptosporidium compared to another globally important protozoa—Giardia duodenalis—because of the former’s narrower but not very strict host specificity. For example, the two species that are the most common cause of human cryptosporidiosis, namely, C. hominis and C. parvum, are known to be anthroponotic and zoonotic, respectively (Beser et al. 2017). C. parvum is observed to have the least host specificity among the species of Cryptosporidium as it has been reported to be isolated in many mammalian hosts. Conversely, the dog-specific C. canis, the cat-specific C. felis, the bird-specific C. meleagridis and C. galli, and the rodent-specific C. muris have also been reported to be able to infect humans (Fayer 2004). Despite the lack of strictly exclusive hosts for these species, their host preference can be used to indicate a high likelihood of contamination from specific hosts or sources.

In the Philippines, source tracking using Cryptosporidium spp. in a water body was conducted in the study by dela Peña et al. (2021). Their study showed that Laguna de Bay, a critical freshwater system in the country, was contaminated with both human- and animal-infective genotypes of Cryptosporidium coming from domestic, agricultural, and nonpoint sources.

The quality of bivalve mollusks as commodities reflects the microbiological status of the environment where they were bred. Therefore, these organisms may serve as surrogates for water analyses (Oliveira et al. 2016). These organisms can accumulate biocontaminants over time, which can substitute for the need to process large volumes of water to detect parasites (Palos Ladeiro et al. 2013). Bivalve mollusks are known to filter up to 5 L of water per hour and are currently being explored to be used as biological sentinels of water contamination (US EPA 2022). The concentration of pathogens in these organisms is typical in sites impacted by wastewater discharge and runoffs from agricultural sources (Willis et al. 2014).

Reports from the study of Pagoso and Rivera (2017) and dela Peña et al. (2017) have shown the presence of human-infective species (i.e., C. parvum, C. hominis, and C. meleagridis) in various edible bivalve species from selected locations in Metro Manila and adjacent provinces. Furthermore, the study of Paller et al. (2013) detected Cryptosporidium contamination in pooled Asian clam (Corbicula fluminea) samples from Laguna de Bay at an occurrence of 20%. These indicate the possible risks to consumers of edible bivalves in the Philippines.

This study detected Cryptosporidium from five pooled mussel (P. viridis) samples. Maximum likelihood analysis of 269 nucleotide positions of test and reference DNA sequences revealed two bird-specific genotypes on mussel samples: C. meleagridis and C. galli (Fig. 3). Conversely, three samples that were contaminated with Cryptosporidium spp. clustered with Cryptosporidium sp. rat genotype IV (previously W19 genotype). As shown in Fig. 3 and Table 1, rat genotype IV (60%) is the dominant genotype among the detected oocysts in the mussel samples, followed by C. galli (20%) and C. meleagridis (20%).

Fig. 3.

Fig. 3

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Maximum likelihood (ML) analysis of the 269 nucleotide positions of Cryptosporidium spp. 18S rDNA sequences supported by 1000 bootstrap replications using the Tamura 3-parameter model of DNA substitution with gamma distribution (Tamura 1992) in MEGA X software. Bootstrap values > 50 were considered adequate support for clustering. Test samples are marked with a filled triangle (black triangle), and references from the GenBank® database are provided with their accession numbers. The tree was rooted to the outgroup, Eimeria tenella

Table 1.

Genotypes and possible sources of Cryptosporidium spp. detected in mussel samples

Season Genotypes detected No. of positive samples Possible sources
Dry Cryptosporidium sp. rat genotype IV 3 Sewage, non-point sources (e.g. stormwater)
Wet C. galli 1 Wild birds, agricultural birds
C. meleagridis 1 Wild birds, agricultural birds, sewage
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Determination of genotypes and species of Cryptosporidium aids in determining the possible sources of fecal contamination in bivalve cultivation sites. Table 1 shows that the possible dominant source of fecal pollution in the samples is sewage or nonpoint sources. Rat genotype IV has been reported to occur in sewage and storm waters (Feng et al. 2009; Jiang et al. 2005). Another possible source of contamination in the bay is excreta of avian species as the mussel cultivation sites are close to a critical habitat for migratory and local birds (i.e., Las Piñas–Parañaque Wetland Park). Furthermore, the poles of the stake method of bivalve cultivation (Baylon n.d.) may serve as perching spots for birds, allowing the direct contamination of the cultivation sites with bird excrement. Lastly, several poultry farms are established in the provinces and cities surrounding the bay, which may be a source of bird-specific Cryptosporidium species through contamination of Manila Bay tributaries. Rat genotype IV and C. galli have never been reported in humans (Ryan et al. 2014). Conversely, C. meleagridis is the third most common cause of human cryptosporidiosis globally (Silverlas et al. 2012). C. meleagridis in bivalves poses a health risk to consumers dependent on commodities from Manila Bay, especially because it is common for people to eat these mollusks raw or lightly cooked (Mladineo et al. 2009). Several reports describe the presence of viable Cryptosporidium oocysts in edible mollusks, with values as high as 84% (Gómez-Couso et al. 2003; Graczyk et al. 2007).

Cryptosporidium spp. was detected in pooled bivalve samples with a total occurrence of 8.77%. Cryptosporidium oocysts may be present in negative samples in quantities lower than the limit of detection of the nested PCR assay employed in this study (Table 2). Multiple studies using a variety of methods demonstrate the presence of these parasites in bivalve species, with detection rates as low as 12% and as high as 33.3% (Gómez-Couso et al. 2006; Melo et al. 2006; Miller et al. 2005; Srisuphanunt et al. 2009). The differences in detection rates and identified species are a result of a complex interplay of the extent of contamination, climate, pollution sources, water flow, and efficiency of detection methods, among other factors.

Table 2.

Occurrence of Cryptosporidium spp. in mussel samples

Season No. of positive samplesa Sample size (n) Occurrence in mussels (%)
Dry 3 36 8.33
Wet 2 21 9.52
Total 5 57 8.77
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aThe detection limit of the assay is approximately 103 oocysts

Comparison of the seasonal occurrence of Cryptosporidium spp. (Table 2) showed that occurrence is higher during the wet season (9.52%) compared to the dry season (8.33%). This difference may be explained by the higher precipitation amount in the wet season, which can lead to the washing off of the contaminants from land areas such as farms toward bodies of water (Aguirre et al. 2016; Li et al. 2006; Miller et al. 2005). This can be problematic as Manila Bay is connected to river tributaries that may be heavily contaminated with domestic and agricultural wastes, especially during rainy days. However, this observed seasonal variation was not supported by statistical significance in Fisher’s exact test (P = 1.0000).

This study provides additional baseline information on the use of Cryptosporidium spp. as a tool for source-tracking fecal contamination in water in the Philippines and the possible complementation of mussel quality monitoring to existing water quality guidelines. A limitation of the study is the small sample size used; it is recommended to increase the sample size and explore other concentration methods, markers, and detection assays that will increase post-processing yield and detection limits for future studies. Furthermore, the use of quantitative methods (e.g., real-time PCR) may be useful in assessing the risk posed by the presence of Cryptosporidium oocysts in seafood.

Conclusion

This study detected Cryptosporidium spp. in mussel samples collected from Bulungan Seafood Market in Parañaque, Philippines, with an overall occurrence of 8.77%. The predominant genotype observed was Cryptosporidium sp. rat genotype IV (60%), followed by C. galli (20%) and C. meleagridis (20%), suggesting possible contamination from sewage, nonpoint, and agricultural sources. The presence of C. meleagridis, a common Cryptosporidium species in humans, in mussels poses a threat to the seafood industry and public health in the area.

The results on the possible sources of Cryptosporidium spp. in mussels cultivated in Manila Bay can be used by local government units in regulating waste discharge (i.e., better sewage and farm manure management) in pursuit of rehabilitating the bay. As these pathogenic protozoa are present in these aquatic commodities, there is a need to educate consumers in the proper preparation and cooking of seafood to inactivate enteric pathogens, thereby lessening the risk of acquiring waterborne diseases. There is also a need to establish routine monitoring (e.g., detection, genotyping, and source tracking) of Cryptosporidium spp. in water by environmental agencies. It is also recommended that the potential of using bivalves in determining the extent of environmental water contamination in the Philippines should be further studied.

Acknowledgements

We thank the following people and agency for their technical support: Kristin Elwin, Guy Robinson, Rance Derrick Pavon, Kevin Labrador, Mae Ashley Nacario, Chembie Almazar, and the management of the Las Piñas-Parañaque Wetland Park of the Department of Environment and Natural Resources, Philippines.

Author contributions

All authors were involved in the study’s conception and design. WLR is the principal investigator of the study. Sample collection was done by MRAV and LBROdP, while sample processing and laboratory analyses were performed by MRAV. All authors contributed to the analyses of results, manuscript writing, and manuscript revision.

Funding

This study was financially supported by the Office of the Vice Chancellor for Research and Development of the University of the Philippines Diliman (Project No. 191928).

Data availability

The DNA sequences used for phylogenetic analysis in this study are accessible in the GenBank® database.

Declarations

Conflict of interest

The authors have no relevant financial or non-financial interests to disclose.

Ethics approval

Not applicable.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The DNA sequences used for phylogenetic analysis in this study are accessible in the GenBank® database.

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