Molecular and phylogenetic approaches for assessing sources of Cryptosporidium contamination in water

Ruecker, Norma J.; Matsune, Joanne C.; Wilkes, Graham; Lapen, David R.; Topp, Edward; Edge, Thomas A.; Sensen, Christoph Wilhelm; Xiao, Lihua; Neumann, Norman F.

doi:10.1016/j.watres.2012.06.045

Cited by 54 publications

(50 citation statements)

References 47 publications

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“…Thus, this may also be true in a case of Cryptosporidium especially for the partial sequence of 18S rRNA. In this study, the topology of phylogenetic tree is somehow consistent with the overall topologies of phylogenetic trees from other previous studies in terms of low proportion of branches that were supported with low bootstrap values normally resulting from the unknown sequences like identified 18S rRNA partial sequences from both rivers in this study [25][26][27][28]. In fact, phylogenetic tree construction was used to root novel Cryptosporidium sequences with known species or genotypes based on the genotypic variations of sequence diversity, thereby resulting in non-homologous copies of this gene due to different factors like host adaptation and geographical distribution [30].…”

Section: Discussionsupporting

confidence: 90%

“…In this study, for all five positive samples with C. parvum, the samples might contain sequence polymorphisms at the 18S rRNA gene location as reported in many cases of 18S rRNA partial sequences [31][32][33]. Moreover, it is troublesome to verify either variation of sequences corresponding to species diversity or reflecting non-homologous copies of ribosomal RNA [28,34].…”

Section: Discussionmentioning

confidence: 87%

“…Multiple sequence alignments of similar type of genes evolutionarily has been extensively used to determine the genotypes of Cryptosporidium species with minimal bootstrap values [23,24]. However, previous studies had reported that constructed phylogenetic trees showed a poor interpretation of bootstrap values regarding to the partial sequence of 18S rRNA for Cryptosporidium [24][25][26][27][28]. The percentage of bootstrap value for branching pattern of phylogenetic tree was influenced by the number of species and genotypes [24].…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

First molecular characterization of Cryptosporidium from three different points of two main rivers in Kuantan, Malaysia using 18S rRNA gene nested PCR

Barudin¹,

Isa²,

Othman³

et al. 2017

APJTD

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 87%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

First molecular characterization of Cryptosporidium from three different points of two main rivers in Kuantan, Malaysia using 18S rRNA gene nested PCR

Barudin¹,

Isa²,

Othman³

et al. 2017

APJTD

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“…Traditional microscopy-based detection tools such as U.S. Environmental Protection Agency (EPA) Method 1622/1623 cannot differentiate Cryptosporidium species. Thus, genotyping tools are increasingly used in the assessment of the human-infective potential and source of Cryptosporidium oocysts in source or finished water (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12).…”

mentioning

confidence: 99%

Development and Evaluation of Three Real-Time PCR Assays for Genotyping and Source Tracking Cryptosporidium spp. in Water

Neumann

Ruecker³

et al. 2015

Appl Environ Microbiol

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jThe occurrence of Cryptosporidium oocysts in drinking source water can present a serious public health risk. To rapidly and effectively assess the source and human-infective potential of Cryptosporidium oocysts in water, sensitive detection and correct identification of oocysts to the species level (genotyping) are essential. In this study, we developed three real-time PCR genotyping assays, two targeting the small-subunit (SSU) rRNA gene (18S-LC1 and 18S-LC2 assays) and one targeting the 90-kDa heat shock protein (hsp90) gene (hsp90 assay), and evaluated the sensitivity and Cryptosporidium species detection range of these assays. Using fluorescence resonance energy transfer probes and melt curve analysis, the 18S-LC1 and hsp90 assays could differentiate common human-pathogenic species (C. parvum, C. hominis, and C. meleagridis), while the 18S-LC2 assay was able to differentiate nonpathogenic species (such as C. andersoni) from human-pathogenic ones commonly found in source water. In sensitivity evaluations, the 18S-LC2 and hsp90 genotyping assays could detect as few as 1 Cryptosporidium oocyst per sample. Thus, the 18S-LC2 and hsp90 genotyping assays might be used in environmental monitoring, whereas the 18S-LC1 genotyping assay could be useful for genotyping Cryptosporidium spp. in clinical specimens or wastewater samples. Waterborne Cryptosporidium spp. present a serious threat to human health because of the ubiquitous presence of Cryptosporidium spp. in water and resistance of the oocysts to environmental conditions, various disinfectants, and many treatment practices (1). As watersheds are vulnerable to contamination with both human-pathogenic and nonpathogenic species, sensitive detection of Cryptosporidium oocysts in water and correct identification of oocysts to the species/genotype level are essential for source water management and risk assessment. Traditional microscopy-based detection tools such as U.S. Environmental Protection Agency (EPA) Method 1622/1623 cannot differentiate Cryptosporidium species. Thus, genotyping tools are increasingly used in the assessment of the human-infective potential and source of Cryptosporidium oocysts in source or finished water (2-12).Currently, numerous molecular techniques have been developed for Cryptosporidium detection and genotyping, based mostly on PCR (single-round PCR, nested PCR, real-time PCR, and multiplex PCR, etc.) followed by restriction fragment length polymorphism (RFLP) analysis, DNA sequencing, melt curve analysis, or single-strand conformation polymorphism (SSCP) analysis (13). Among these methods, the real-time PCR technique with melt curve analysis has recently evolved as a sensitive, specific, and time-saving tool for the detection and genotyping of Cryptosporidium spp. in clinical and environmental samples, relying on several gene targets, including the small-subunit (SSU) rRNA, the 70-kDa heat shock protein (hsp70), the Cryptosporidium oocyst wall protein (COWP), the 60-kDa glycoprotein (gp60), and others (14-21). The SSU rRNA gene is the mo...

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“…Recently, intensive efforts have been made to examine source waters destined for potable consumption, as well as wastewaters intended for reuse, using genotyping assays and, to a lesser extent, infectivity assays (9)(10)(11)(12)(13). The information from these assays provides an indication of the risk to of human health (13).…”

mentioning

confidence: 99%

Integrated Cryptosporidium Assay To Determine Oocyst Density, Infectivity, and Genotype for Risk Assessment of Source and Reuse Water

King

Fanok

Phillips

et al. 2015

Appl Environ Microbiol

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Cryptosporidium continues to be problematic for the water industry, with risk assessments often indicating that treatment barriers may fail under extreme conditions. However, risk analyses have historically used oocyst densities and not considered either oocyst infectivity or species/genotype, which can result in an overestimation of risk if the oocysts are not human infective. We describe an integrated assay for determining oocyst density, infectivity, and genotype from a single-sample concentrate, an important advance that overcomes the need for processing multiple-grab samples or splitting sample concentrates for separate analyses. The assay incorporates an oocyst recovery control and is compatible with standard primary concentration techniques. Oocysts were purified from primary concentrates using immunomagnetic separation prior to processing by an infectivity assay. Plate-based cell culture was used to detect infectious foci, with a monolayer washing protocol developed to allow recovery and enumeration of oocysts. A simple DNA extraction protocol was developed to allow typing of any wells containing infectious Cryptosporidium. Water samples from a variety of source water and wastewater matrices, including a semirural catchment, wastewater, an aquifer recharge site, and storm water, were analyzed using the assay. Results demonstrate that the assay can reliably determine oocyst densities, infectivity, and genotype from single-grab samples for a variety of water matrices and emphasize the varying nature of Cryptosporidium risk extant throughout source waters and wastewaters. This assay should therefore enable a more comprehensive understanding of Cryptosporidium risk for different water sources, assisting in the selection of appropriate risk mitigation measures.C ryptosporidium is ubiquitous in source waters and wastewaters, presenting a treatment challenge on account of its small size, resistance to chlorine disinfection, and the absence of more easily measured surrogates to allow treatment performance validation (1, 2). These characteristics make Cryptosporidium problematic for the water industry, and the ever-present threat from this pathogen requires sound characterization and management of risks, including validation and monitoring of critical control points (3-5). Removal of Cryptosporidium by treatment processes can be highly variable (6), so validation and monitoring of individual processes are important to ensure appropriate performance. Even for validated systems, treatment failure is possible under highly adverse conditions, and management of this risk may require significant capital expenditure to provide sufficient risk mitigation for extreme events. However, risk assessments frequently utilize historical monitoring data based on total oocyst numbers, not considering either oocyst infectivity or species/genotype, resulting in possible overestimation of risk.Of the greater than 26 species or genotypes of Cryptosporidium that might be detected in the environment, only C. parvum and C. hominis common...

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Molecular and phylogenetic approaches for assessing sources of Cryptosporidium contamination in water

Cited by 54 publications

References 47 publications

First molecular characterization of Cryptosporidium from three different points of two main rivers in Kuantan, Malaysia using 18S rRNA gene nested PCR

First molecular characterization of Cryptosporidium from three different points of two main rivers in Kuantan, Malaysia using 18S rRNA gene nested PCR

Development and Evaluation of Three Real-Time PCR Assays for Genotyping and Source Tracking Cryptosporidium spp. in Water

Integrated Cryptosporidium Assay To Determine Oocyst Density, Infectivity, and Genotype for Risk Assessment of Source and Reuse Water

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