Genomics and molecular epidemiology of Cryptosporidium species

Accepted Manuscript Title: Genomics and molecular epidemiology of Cryptosporidium species Authors: Asis Khan, Jahangheer S. Shaik, Michael E. Grigg PII: DOI: Reference:

S0001-706X(17)30889-6 https://doi.org/10.1016/j.actatropica.2017.10.023 ACTROP 4484

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Acta Tropica

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Please cite this article as: Khan, Asis, Shaik, Jahangheer S., Grigg, Michael E., Genomics and molecular epidemiology of Cryptosporidium species.Acta Tropica https://doi.org/10.1016/j.actatropica.2017.10.023 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Genomics and molecular epidemiology of Cryptosporidium species

Asis Khan1,*, Jahangheer S Shaik1, Michael E. Grigg1

1Laboratory

of Parasitic Diseases, National Institutes of Allergy and Infectious Diseases,

National Institutes of Health, Bethesda, Maryland, USA

*Corresponding

author: Asis Khan

Address: Laboratory of Parasitic Diseases, Building 4, Room B1-06, 4 Memorial Drive, Bethesda, MD 20892 Email: [email protected] Abstract Cryptosporidium is one of the most widespread protozoan parasites that infects domestic and wild animals and is considered the second major cause of diarrhea and death in children after rotavirus. So far, around 20 distinct species are known to cause severe to moderate infections in humans, of which Cryptosporidium hominis and Cryptosporidium parvum are the major causative agents. Currently, ssurRNA and gp60 are used as the optimal markers for differentiating species and subtypes respectively. Over the last decade, diagnostic tools to detect and differentiate Cryptosporidium species at the genotype and subtype level have improved, but our understanding of the zoonotic and anthroponotic transmission potential of each species is less clear, largely because of the paucity of high resolution whole genome sequencing data for the different species. Defining which species possess an anthroponotic vs. zoonotic transmission cycle is critical if we are to limit the spread of disease between animals and humans. Likewise, it is unclear to what extent genetic hybridization impacts disease potential or the emergence of outbreak strains. The development of high resolution genetic markers and whole genome sequencing of different species should provide new insights into these knowledge

gaps. The aim of this review is to outline currently available molecular epidemiology and genomics data for different species of Cryptosporidium.

Key words: Cryptosporidiosis, molecular epidemiology, population genetics, genomics

Cryptosporidiosis Increases in the reporting of diarrheal diseases worldwide, with an estimated 1.3 million deaths globally in 2015, made cryptosporidiosis the fourth leading cause of death among children under the age of 5. Once Cryptosporidium was identified as a causative agent for human infection in 1976 (White, 2010), it was immediately recognized as both a common etiology and a major cause of chronic diarrhea among immunocompromised patients (60,400 deaths). In 2015 it represented approximately 12.1 % (2.8-26.9) of deaths globally among children younger than 5 according to the recent Global Burden of Disease Study (Collaborators, 2017). In the United States alone, Cryptosporidium infects 750,000 people each year and is considered the second major cause of diarrhea and death in children after rotavirus (Kotloff et al., 2013). In sub-Saharan Africa, 93% of the 64,818 reported deaths in 2015 were mainly children under the age of 5 infected with Cryptosporidium. However, in the Mediterranean African countries, the 2010 diarrheal mortality rate in children under five was significantly lower, ranging from 1% (in Liberia) to 12% (in Sudan). It is also possible that the lower rate of infection detected in the Mediterranean African countries reflects either poor surveillance, under diagnosis, or under reporting and poor book keeping. In India, a multicenter study established that the death rate in children below the age of 5 attributable to cryptosporidiosis is about 7.0% (Ajjampur et al., 2010). Poor hygiene as well as malnutrition, and partial or complete lack of immunity are the major reasons for the higher prevalence among children under the age of 5. Interestingly, a cohort study that typed human cryptosporidiosis in England and Wales between 2000 to 2003 revealed a second smaller peak in prevalence which corresponded to adults between ages of 30 and 40, especially women, suggesting that infected children were likely transmitting Cryptosporidium parasites to their parents (Chalmers et al., 2009).

Cryptosporidiosis is also a significant threat to immunocompromised patients and is considered one of the original AIDS-defining illnesses due to its high association with mortality (Colford et al., 1996). The first case of cryptosporidiosis associated with AIDS was reported in a homosexual man in 1982 (Ma and Soave, 1983) and within a year, 50 other cases had been reported (Ma, 1984). The infection among HIV/AIDS patients was so fatal and life threatening that cryptosporidiosis was featured as one of the defining agents of the AIDS syndromes prior to the discovery of the virus (Hunter and Nichols, 2002). However, the introduction of anti-retroviral therapy (HAART) has led to a precipitous drop in the prevalence of cryptosporidiosis in HIV patients over the past two decades. Recently, the emergence of drug-resistant strains of Cryptosporidium has led to increased infection rates in HIV patients (Hunter and Nichols, 2002). In Europe, a prospective long-term study identified 3-4% seroprevalence rates for Cryptosporidium among patients in the later stages of their HIV infection (Pedersen et al., 1996), whereas prevalence rates can be as high as 46% among HIV patients in other parts of the world (Chacin-Bonilla et al., 1992).

Life Cycle of Cryptosporidium The causative agent of cryptosporidiosis has a monoxenous life cycle that completes within the gastrointestinal track of a single host (Bouzid et al., 2013; Current and Garcia, 1991). Infection is initiated by the ingestion of sporulated oocysts, which each contain 4 infectious sporozoites, from either contaminated water or food (Chen et al., 2002; Tzipori and Ward, 2002). Infectious sporozoites are released during the excystation stage in the gastrointestinal tract, they attach to the apical surface of host cells, and through an active invasion mechanism are internalized within the host cell plasmalemma, where they form a parasitophorous vacuole (PV) (Fig. 1). Within the PV, parasites develop into spherical trophozoites, that undergo asexual replication (merogony) to either form a type I meront (contains 8 merozoites) or type II meront (contains 4 merozoites) (Fig. 1). Merozoites within the type II meront undergo gametogony and produce either microgametes or macrogamonts (O'Donoghue, 1995; Tzipori and Griffiths, 1998). Fertilization of macrogamonts by the microgametes leads to the production of zygotes, which, after two asexual divisions develop either a thin-walled oocyst containing only a single layer membrane or a thick-walled oocyst containing two-layered membranes (Fig. 1). The thick-walled oocysts

are environmentally resistant and are released through feces, transmitting the infection from one host to the other, whereas the thin walled oocysts autoinfect the same host to maintain the parasite within the gastrointestinal tract, obviating the necessity for a new oral infection (Tzipori and Ward, 2002). Thus, the ability of the parasites to persist within a single host is quite distinct from its closely related apicomplexan parasites that possess a heteroxenous life cycle. This distinct autoinfection mechanism makes cryptosporidiosis a frequent cause of prolonged acute diarrhea in the general population and is attributed to repeated merogony through asexual replication and the production of these sporulated thin-walled oocysts. This distinct autoinfection mechanism makes cryptosporidiosis a frequent cause of prolonged acute diarrhea in the general population.

Cryptosporidium species and host range More than 100 years ago, Ernest Edward Tyzzer first made his observation that gastric glands of a tame, which is a variety of common mice, frequently contained a distinct parasite which he named Cryptosporidium muris (C. muris) (Tyzzer, 1907). After he identified this new genus of parasites, he also identified another new species isolated from the intestines of mice and named it Cryptosporidium parvum (C. parvum) (Tyzzer, 1912). He considered the second parasites as a new species because they produced smaller sized oocysts and the location of infection was only in the small intestine. During much of 1970s and through the 1990s, Cryptosporidium was thought to consist of only two species; one, C. muris, which infects the gastric mucosa of mammals and produces large oocysts, and the other C. parvum, which infects all mammals and produces smaller oocysts (Tzipori et al., 1980). However, as more biological and genetic data for additional genotypes accumulated, the species definition of Cryptosporidium changed to encompass greater than 20 different species, and more than 40 genotypes that cause mammalian infections (Table 1, Fig. 2) (Fayer et al., 2008). All of these distinct species have a nomenclature based on International Code for Zoological Nomenclature (ICZN) rules. These include, but are not limited to, size and morphology of oocysts, molecular characterization including 18S rRNA sequencing, natural and experimental host specificity. It was previously thought that each species of Cryptosporidium possessed a narrow host range and infected only a single host or closely related host species. For example, dogs are almost exclusively infected with only Cryptosporidium canis (C. canis). However it is now apparent that Cryptosporidium has

been isolated from more than 150 distinct host species, and some Cryptosporidium species, for example the cervine genotype Cryptosporidium ubiquitum (C. ubiquitum), possess a very broad range of hosts, including domestic and wild ruminants, rodents, woodchucks, deer, raccoons and humans (Bertolino et al., 2003; Blackburn et al., 2006; Fayer et al., 2010; Feltus et al., 2006; Leoni et al., 2006; Nichols et al., 2006; Ong et al., 2002; Perz and Le Blancq, 2001; Ryan et al., 2005; Ryan et al., 2003a; Soba et al., 2006; Trotz-Williams et al., 2006). Similarly, the best characterized species C. parvum also infects a wide range of hosts including humans, ruminants and cattle younger than 2 months old. With the availability of additional genetic and biological data, it is likely that new species of Cryptosporidium will be described, and follow-up epidemiological studies will be necessary to determine which species are zoonotic (animal to human) from those that are anthroponotic (inter-human or human-to-animal). Cryptosporidium species in animals Cryptosporidium species cause a varying degree of naturally occurring diarrhea in neonatal farm animals including calves, lambs, foals, and piglets (Table 1). C. parvum, Cryptosporidium andersoni (C. andersoni), Cryptosporidium bovis (C. bovis), and Cryptosporidium ryanae (C. ryanae) are the four-major species of Cryptosporidium that are isolated from domestic cattle (Xiao, 2010; Xiao and Feng, 2008). C. parvum is the most common cause of calf diarrhea and is found mostly in pre-weaned calves (Amer et al., 2013). On the other hand, C. bovis and C. ryanae are cattle adapted parasites. C. bovis most commonly infects post weaned calves globally. High prevalence rates of C. bovis infection (70% to 80%) are typically observed in calves between 12 - 14 weeks of age (Santin et al., 2008; Silverlas et al., 2010). Infections with C. ryanae are generally asymptomatic, with infection rates approaching 60% in certain populations in the world (Santin et al., 2008). Unlike other genotypes, C. ryanae has no zoonotic potential. C. andersoni has been isolated from 5% of 1-2 year old dairy heifers and infects primarily the epithelial cells of the abomasum (Lindsay et al., 2000). Although cattle are the primary host, C. andersoni can also infect camels, sheep, goats, gerbils and mice. C. parvum is a common source of infection in young lambs and goats (Geurden et al., 2008; Karanis et al., 2007; Mueller-Doblies et al., 2008; Pritchard et al., 2007; Pritchard et al., 2008; Quilez et al., 2008b) but interestingly it has not been detected in sheep and pigs. Instead C. bovis and Cryptosporidium cervine (C. cervine) genotypes are the common infectious agents in sheep. C.

agni also widely infects sheep and pre-weaned lambs (Barker and Carbonell, 1974). Conversely, C. suis and the Cryptosporidium pig genotype II has only been detected infecting pigs younger than 5 weeks of age in Australia, Norway, N. Ireland, Denmark and Spain (Hamnes et al., 2007; Langkjaer et al., 2007; Suarez-Luengas et al., 2007; Xiao et al., 2006). Another Cryptosporidium species, Cryptosporidium scrofarum (C. scrofarum) has been detected in domestic pigs but has less than a 5% prevalence rate (Garcia-Presedo et al., 2013). C. canis, which was previously recognized exclusively as a canine genotype and is known to infect domestic dogs worldwide (Fayer et al., 2001) is now thought to be zoonotic. For example, it has been isolated from symptomatic children in households with dogs that shed oocysts (Xiao et al., 2007). Cryptosporidium pestis (C. pestis) is considered a zoonotic species with a global distribution and it has been isolated from calves under 2 weeks of age (Santin et al., 2004). Cryptosporidium fayeri (C. fayeri) and Cryptosporidium macropodum (C. macropodum) are commonly detected in Australia infecting marsupials, including kangaroos, wallabies and koalas (Power and Ryan, 2008; Ryan et al., 2008). Asymptomatic domestic cats infected with C. felis have also been documented worldwide (Ballweber et al., 2009; Fayer et al., 2006a). C. felis, which is recognized as a cat-adapted strain, has no zoonotic potential, and this parasite has only been reported in cats.

Cryptosporidium species in humans Two major species of Cryptosporidium, C. hominis and C. parvum, cause significant community outbreaks of diarrheal diseases worldwide in humans (Table 1, Fig. 3B). Several subtypes of C. hominis and C. parvum have been identified based on gp60 sequence analysis, which is the most widely used genetic marker for subtyping Cryptosporidium isolates. C. parvum subtype IIa and IId have been identified in both human and ruminant infections, whereas type IIc has only been isolated from humans (Alves et al., 2003; Quilez et al., 2008a; Quilez et al., 2008b; Xiao and Feng, 2008). Unlike the zoonosis C. parvum, C. hominis does not appear to be anthroponotic and is exclusively isolated from humans. Thus, C. hominis is transmitted humanto-human whereas C. parvum maintains a zoonotic transmission cycle from animals to humans. There are also seasonal and age-related variations in the disease burdens of C. parvum and C. hominis infections (Chalmers et al., 2009; Chalmers et al., 2011). C. hominis is highly prevalent in autumn in the UK and New Zealand, whereas C. parvum is more prevalent during the

springtime in Canada, Ireland and the Netherlands (Budu-Amoako et al., 2012; Wielinga et al., 2008). Although C. hominis and C. parvum are considered the primary agents of human cryptosporidiosis, up to 20 distinct species are known to cause severe to moderate human infections (Table 1) (Ryan et al., 2014; Slapeta, 2013). Diagnosis of Cryptosporidium Waterborne outbreaks caused by Cryptosporidium are common, but it was not until the 1993 Milwaukee outbreak, in which greater than 400,000 people were infected, has there been a concerted effort to document the public health implications of these disease outbreaks. Interestingly, several recent reports have suggested that most Cryptosporidium infections are symptomatic with various degrees of diarrhea characterized by the presence of considerable numbers of oocysts. Morphological determination of cryptosporidiosis has been the cornerstone of routine laboratory diagnosis, particularly in resource-limited health systems. The modified Ziehl-Neelsen technique and wet mount preparation methods are often sufficient to detect most Cryptosporidium species that have high prevalence rates. However, there are several limitations with the microscopic determination approach, especially in the diagnosis of infections harboring small numbers of oocysts in non-epidemic regions. Furthermore, the small size of the oocysts (4 to 6 µm) can readily be confused with other material present in stool samples. While the routine use of sugar flotation to concentrate oocysts and the use of modified acid-fast (MAF) stains followed by microscopic examinations is known to increase sensitivity (54.8%) (Alles et al., 1995), these enrichment procedures are often not sufficient to identify the presence of Cryptosporidium species infecting asymptomatic patients. Moreover, MAF staining is typically only performed upon a physician’s request, or if the technologist detects structures suspicious of Cryptosporidium on the permanent stained smear. To overcome these barriers, antigen specific immunoassays and molecular techniques such as polymerase chain reaction (PCR) have been used more reliably and with higher sensitivity (97 to 100%) and specificity (100%) (Bialek et al., 2002; Morgan et al., 1998). The direct fluorescent-antibody tests (DFA) and enzyme-immunoassays (EISAs) are the two most widely used antigen specific immunoassays. The sensitivity and specificity of the DFA tests have been shown to be 96 to 100% and 99 to 100%, respectively (Garcia and Shimizu, 1997), whereas the sensitivity and the specificity of EISAs are documented to be 94 to 97% and 99 to 100%, respectively (Garcia and Shimizu, 1997).

Molecular characterization of Cryptosporidium Due to the lack of well-defined morphological and biological traits, in addition to inadequate culture methods, the identification and species definition of Cryptosporidium isolates is solely based on molecular assays, which includes PCR-based genotyping, DNA sequencing of PCR products, and qPCR assays using fluorescent probes and melting curve analyses (Feng et al., 2007; Koinari et al., 2013; Mary et al., 2013; Yang et al., 2013). Several genetic markers such as the Small subunit (SSU) rRNA, Cryptosporidium oocyst wall protein (COWP), heat shock protein 70 (hsp 70), and gp60 have been commonly used to characterize the epidemiology and genotypes of Cryptosporidium isolates identified in animal and human infections and contaminating environmental samples. These markers are conserved within each species however, they are polymorphic between different species. The markers are typically amplified from DNA extracts made directly from clinical samples using specific PCR primers followed by Sanger sequencing or restriction fragment length polymorphism analyses (RFLP). Small subunit (SSU) rRNA sequencing-based tools have been routinely used (86% of publications) to genotype Cryptosporidium in environmental (i.e., water, invertebrate sources), wild and domestic animals, as well as human samples. A PCR-RFLP toolkit has been developed in which an 830bp fragment of the SSU rRNA gene is amplified using gene specific primers (5′TTCTAGAGCTAATACATGCG -3′ and 5′- CCCATTTCCTTCGAAACAGGA -3′ for primary PCR and 5′-GGAAGGGTTGTATTTATTAGATAAAG-3′ and 5′-AAGGAGTAAGGAACAACCTCCA-3′ for secondary PCR) followed by either Sanger sequencing (Fig. 2A) (Table 2) or RFLP analysis using SspI and VspI restriction digestion and agarose gel electrophoresis (Xiao et al., 1999a; Xiao et al., 1999b). Multiple copies of the SSU rRNA gene throughout the genome makes this marker significantly more sensitive than single copy genes. However, minor genetic variations have been observed among different copies of the SSU rRNA gene in many Cryptosporidium species and genotypes, therefore new genotypes or species should not be named based on those minor (one or two single nucleotide polymorphisms (SNPs) or insertion/deletion) variations (Abeywardena et al., 2014). The internal transcribed spacer regions (ITS) of ribosomal DNA have also been used to characterize Cryptosporidium DNA directly in clinical samples using the following

gene

specific

YA56F

primers

GGCGCTACTTCATATAATATAATGTTTTTT-3′)

and

YA54R

(forward, (reverse,

5′5′-

GGCGCTAATTTTAACTTAAATTGGTTAAGAAA-3′) to amplify a 230 bp region (pITS-2) of the

ITS-2 region (Chalmers et al., 2005). These sequences can then be used to distinguish a limited number of taxa but are insufficient to resolve all species due to the conserved nature of the sequences across several species (Grinberg et al., 2013; Paparini et al., 2015; Reed et al., 2002). In addition to the SSU rRNA gene, the Cryptosporidium oocyst wall protein (COWP) gene (Pedraza-Diaz et al., 2000; Putignani et al., 1999; Spano et al., 1997) (Fig. 2B) (Table 2) and the 70 kDa heat shock protein (HSP70) gene (Table 2) (Gobet and Toze, 2001; Sulaiman et al., 2000) (Fig. 2D) have also been studied widely and the polymorphisms present in these two genes can be utilized to develop species and strain specific diagnostic tools. The sensitivity of oocyst detection using COWP gene is 85.7% for samples inoculated with 1, 10, and 100 oocysts (Kato et al., 2003). Unfortunately, these two genes are highly polymorphic in nature, so PCR based genotyping tools for these two markers have only been optimized to amplify DNA from C. hominis, C. parvum, and species/genotypes that are closely related to C. parvum, which limits the broad utilization of these primer sets for genotyping Cryptosporidium species commonly found in animals. A few studies have utilized the actin gene for real-time PCR detection of Cryptosporidium (Fig. 2C) (Sulaiman et al., 2002). Although this gene has a significant level of polymorphism necessary to distinguish between the diverse Cryptosporidium species, the sensitivity of this single copy gene marker is low (Table 2). Despite this limitation, a large number of sequences are published in GenBank for this gene, which allows for comparison of sequences between most Cryptosporidium species and genotypes (Fig. 2C).

Subtyping of Cryptosporidium species, particularly C. hominis and C. parvum, has been developed and used extensively in Cryptosporidium population genetic studies (Table 2). One of the most widely utilized markers is the 60kDa glycoprotein (gp60) (Table 2) that is proteolytically cleaved into a 15 kDa and 40 kDa protein, most likely by a subtilisin like serine protease, hence gp60 is also known as the GP15/40 marker. gp60 has several tandem repeats of a serine-coding tri-nucleotide TCA, TCG or TCT, in addition to extensive sequence divergence in non-repeat regions (Gatei et al., 2006; Leoni et al., 2007a; Leoni et al., 2007b; Wielinga et al., 2008) that makes this marker the preferred choice for subtyping isolates that cause human infection. Several subtype groups have been identified in each species: 7 subtype groups have been described in C. hominis (Ia–Ig) (Fig. 3A), 12 subtype groups are found in C. parvum, 2 are considered zoonotic (IIa, IId) and 10 are non-zoonotic (IIb, IIc, IIe–IIl) (Fig. 3A), and 6 subtype

groups in Cryptosporidium meleagridis (C. meleagridis) (Abe et al., 2006; Akiyoshi et al., 2006; Glaberman et al., 2001; Meireles et al., 2006; Misic and Abe, 2007; Soba and Logar, 2008) (Fig. 3A). Several subgenotypes have been recognized within each subtype based on the number of tri-nucleotide repeats (Sulaiman et al., 2005). Several other multilocus typing tools have been utilized to increase the resolution of the gp60 typing methodology, including CP47, CP56, Mucin 1, MSC6-7, RPGP, and DZHRGP (Table 2) (Gatei et al., 2007; Gatei et al., 2006). It must be mentioned here that gp60 and other subtyping markers will not amplify the DNA from distantly related species of C. hominis and C. parvum due to the divergent nature of these target loci (Feng et al., 2011; Li et al., 2014). Molecular epidemiology of Cryptosporidium Cryptosporidiosis is the major cause of diarrheal diseases worldwide, particularly in young children presenting with watery diarrhea, abdominal pain, nausea and vomiting. It can present as a life-threatening sequela among malnourished and immunocompromised children. A recent epidemiological study which included over 22,000 infants and children in Africa and Asia, showed that Cryptosporidium was one of the four pathogens responsible for most of the severe diarrhea.

Although it is a significant cause of diarrheal diseases, the total burden of

cryptosporidiosis including persistence and acute infections in different countries, particularly in developing countries is still unknown, due primarily to a lack of proper surveillance. Recently, several molecular diagnostic and typing tools have been developed to detect and differentiate diverse species of Cryptosporidium based on whole genome sequencing of several species. These improved molecular diagnostic tools (as mentioned in the Molecular characterization of Cryptosporidium section above) have not only yielded new insights into the epidemiology of cryptosporidiosis, but also led to the identification of common transmission modes, such as zoonotic or anthroponotic transmission through the fecal-oral route via contaminated food or water (Gatei et al., 2007; Gatei et al., 2006; Leoni et al., 2007a; Leoni et al., 2007b; Wielinga et al., 2008). At least twenty distinct Cryptosporidium species have been identified as the causative agents of cryptosporidiosis in humans thus far (Elwin et al., 2012a; Ng et al., 2012; Ryan et al., 2014; Xiao, 2010). Among these, C. parvum and C. hominis are the most common causative agents for

human infection and are associated with localized outbreaks throughout the world (Xiao and Feng, 2008). C. hominis is the most common pathogenic parasite detected in human samples, particularly in young children below the age of 2 and in women between the ages 15 and 45. It predominately infects the microvillous border of intestinal epithelial cells in immunocompetent as well as immunocompromised hosts (Morgan-Ryan et al., 2002). This species has expanded widely in developing countries including India, Brazil, Pakistan and Peru (Fig. 3B) (Ajjampur et al., 2007; Araujo et al., 2008; Bushen et al., 2007; Cama et al., 2007; Cheun et al., 2007; Cordova Paz Soldan et al., 2006; Gatei et al., 2008; Gatei et al., 2007; Gatei et al., 2006; Hung et al., 2007; Jex and Gasser, 2008; Muthusamy et al., 2006; Park et al., 2006; Samie et al., 2006). In the industrialized nations such as European countries, Australia, and USA, the distribution of C. hominis infection is as widespread as C. parvum infection. Four out of the common 7 subtype families, subtypes Ia, Ib, Id, and Ie account for most of the human cases worldwide. A higher heterogeneity of subtype families of C. hominis has been observed in developing countries than the industrialized nations, with all four subtypes detected in Peru, Malawi, and India. Genetic heterogeneity of the C. hominis subtypes was also observed in Australia, China and South America (Table 3B). Subtype Ib is the major causative agent of diarrhea in immunocompetent people of Europe and USA. This virulent subtype also accounted for most of the outbreaks due to Cryptosporidium infections worldwide. Interestingly, most of the outbreaks in the USA are linked to IbA10G2, which is one of the subtype families of Ib associated with cryptosporidiosis outbreaks in Europe (Fig 3) (Cohen et al., 2006; Glaberman et al., 2002; Leoni et al., 2007a; Leoni et al., 2007b). Similar to C. hominis, the geographic distribution of C. parvum infecting humans varies depending on the geographic area and the surrounding socioeconomic conditions. As mentioned above, in Europe and in New Zealand, C. parvum is as equally distributed as C. hominis, whereas in Middle Eastern countries C. parvum is the dominant species isolated from human cryptosporidiosis patients (Nazemalhosseini-Mojarad et al., 2012; Xiao, 2010; Xiao and Feng, 2008). To characterize the transmission dynamics and zoonotic potential of C. parvum in humans and farm animals, gp60 has been widely utilized to subtype the species. Although there is no direct evidence, it has been postulated that human infections with C. parvum can be either zoonotic or anthroponotic (in this case, inter-human transfer) based on the association of

subtypes found between human and farm animals. Several common bovine IIa and less common IId C. parvum subtypes have also been documented in human cases in North America, Europe and Australia. Two major IIa subtypes IIaA15G2R1 and IIaA18G3R1 are frequently isolated from human cryptosporidiosis cases in Portugal, Slovenia, Netherlands and Northern Ireland and they are the common subtypes identified in calves (Feltus et al., 2006; Jex and Gasser, 2008; Soba and Logar, 2008; Xiao, 2010). Four IId subtypes were detected in HIV patients in Portugal and they were also identified from lambs and calves in the same regions (Alves et al., 2006). Thus, there are several indications that C. parvum can be transmitted zoonotically. Conversely, C. parvum subtype family IIc has only been identified in human cases in the United States, Canada, Portugal, Slovenia, United Kingdom, Ireland, Netherland and Australia and has not been found in animals, which demonstrates the anthroponotic nature of the transmission of this subtype of C. parvum (Alves et al., 2006; Soba and Logar, 2008; Xiao, 2010). Unlike developed countries, in developing countries including India, Malawi, Uganda, and Kenya, unusual C. parvum subtype families such as IIb and IIe are identified infecting humans, and have not been identified in sympatric animals in these regions (Akiyoshi et al., 2006; Cama et al., 2008; Muthusamy et al., 2006). The population genetic structure of C. hominis and C. parvum is somewhat debatable. Several studies have suggested that C. hominis and C. parvum are expanding largely asexually and have clonal population genetic structures (Drumo et al., 2012; Feng et al., 2014; Li et al., 2013; Tanriverdi et al., 2008) whereas others demonstrate a panmictic population structure with frequent recombination among the strains analyzed (De Waele et al., 2013; Herges et al., 2012; Widmer and Sullivan, 2012). In a multi-locus sequence typing study, two subpopulations of IaA28R4 of C. hominis in the United States documented intragenic recombination within the gp60 locus (Feng et al., 2014). It is also thought that genetic recombination was the major driving force for the emergence and expansion of the virulent subtype IaA28R4 which caused two large outbreaks (Feng et al., 2014). Similarly, genetic recombination between epidemic and geographically segregated C. parvum populations in the United States, Canada, United Kingdom and Spain appears to have occurred within a hyper-transmissible IIaA15G2R1 subtype (Feng et al., 2013). Multi-locus sequence typing at the genetic markers gp60, CP56, MSC6-7 and ZPT

has also identified an isolate that exists as a genetic admixture between the zoonotic IIa subtype family and the anthroponotic subtype family IIc (Feng et al., 2014; Feng et al., 2013). There are several other Cryptosporidium species including C. meleagridis, C. canis, and C. felis that have been reported to be associated with human cases, particularly in developing countries (Xiao and Feng, 2008). In England and Wales, 99 cases of C. meleagridis, 22 cases of C. felis and two cases of C. canis have been identified among 13,112 diarrheal cases (Nichols et al., 2006). These species have also been detected to be infecting children in Lima, Peru (Xiao et al., 2001), Bangkok, Thailand (Cama et al., 2007), and Kenya (Gatei et al., 2007; Gatei et al., 2006). C. muris-like oocysts were isolated from two healthy Indonesian girls (Katsumata et al., 2000) as well from AIDS patients in Kenya, Peru (Gatei et al., 2006; Palmer et al., 2003) and India (Muthusamy et al., 2006). Interestingly, C. cervine genotypes are more commonly reported in industrialized countries including Canada, the United Kingdom, and the United States (Blackburn et al., 2006; Feltus et al., 2006; Leoni et al., 2006; Nichols et al., 2006; Ong et al., 2002; Soba et al., 2006). CryptoNet (https://www.cdc.gov/parasites/crypto/cryptonet.html). In 2010, the CDC launched CryptoNet in the United States in order to better understand the complex transmission dynamics of the unique and diverse Cryptosporidium genotypes and subtypes, which are indistinguishable by traditional clinical lab tests. CryptoNet is the first molecular tracking system for Cryptosporidium infections which uses two steps to genotype distinct Cryptosporidium species. First, the diagnostic samples are characterized by a nested PCR-RFLP method using the 18S rRNA gene (Fig. 2A) and secondly, the samples are subtyped based on sequencing of an 800 bp nested PCR fragment from the gp60 gene (Fig. 3A). This multidisciplinary molecular based surveillance system has not only improved the detection and investigation of cryptosporidiosis outbreaks in the United States, but is also identifying new Cryptosporidium species, genotypes, and subtypes that were not previously known to infect humans that can be prioritized for whole genome sequencing. Genome of Cryptosporidium There are several concerns in utilizing few genetic markers to interpret the population genetic structure and to genotype or subtype Cryptosporidium species from human specimens. One major concern is that PCR-based techniques typically amplify only the dominant

Cryptosporidium allele for diagnosis and genotyping of the clinical specimen, potentially missing other species present in mixed strain infections that may impact clinical disease. Another major concern is the false negative rate of the Cryptosporidium subtyping methodology, which was developed based on the genome sequences of C. parvum or C. hominis, and may not capture the true genetic diversity within the genus. Thus, the utilization of species-specific markers that only amplify C. parvum, C. hominis, and closely related species or genotypes, would fail to detect the presence of other, more divergent species potentially present in the clinical samples. To overcome these concerns, there is a need to develop more robust methodologies that will perform genome-wide scans across different species. However, it wasn’t until the first reported case in 1976 (Nime et al., 1976) that cryptosporidiosis was even considered to be a health concern among immunocompromised individuals (Current et al., 1983). Hence, there has been no large-scale effort to generate whole genome sequencing for Cryptosporidium until recently. In the late nineties, a collection of all of the published sequenced data reconstructed ~2.5% of the C. parvum genome (Liu et al., 1999) and this was followed by the first sequencing of a C. parvum cDNA library that provided a low-resolution glimpse of the Cryptosporidium genome. Due to several notorious outbreaks, including the 1993 Milwaukee outbreak, and its significance in HIV infected patients, a consortium of three universities in the U.S. (University of Minnesota, Virginia Commonwealth University and Tufts University) initiated the first whole genome sequencing project for Cryptosporidium. For the whole genome sequencing project, C. parvum type II (IOWA) and C. hominis (TU502) were subjected to Sanger sequencing on oocyst DNA harvested from infected germ free neonatal calves. The Cryptosporidium genome was reported to be ~9.1 Mb in total size (13X genome coverage containing five gaps), and comprised of eight chromosomes ranging from ~0.9 to 1.4 Mb. It possessed ~31% GC content, compared to 19.4% and 52% in Plasmodium and Toxoplasma respectively. More recently, a whole genome sequencing project on C. parvum and C. hominis was undertaken to increase our understanding of the population genetic structure of Cryptosporidium (Abrahamsen et al., 2004; Xu et al., 2004). Intriguingly, analysis of the whole genome sequencing data established that organellar genomes and specific metabolic pathways found in closely related apicomplexan parasites were not present in the Cryptosporidium genomes (Zhu et al., 2000). Cryptosporidium, similar to gregarines (Toso and Omoto, 2007), has lost its apicoplast genome that is found in all other Apicomplexan parasites (Foth and McFadden, 2003; Waller and McFadden, 2005). This

differentiates Cryptosporidium from other closely related apicomplexan parasites such as Toxoplasma and Plasmodium. In addition to the loss of the apicoplast genome, they have lost both mitochondrial and nuclear genes for many of the mitochondrial proteins that are required for several metabolic pathways such as the TCA cycle, oxidative phosphorylation and fatty acid oxidation. Instead, they harbor a degenerate “mitosome”, which is probably the site for Fe-S cluster assembly proteins, and proteins for ubiquinone biosynthesis and coenzyme A generation. Comparative genome analyses have revealed high synteny and 95% to 97% genome similarity between C. parvum and C. hominis (Fig. 4). Detailed analysis of the coding sequences between these two-species indicates that there are 11 additional protein coding sequences that are present in C. hominis that are not present in C. parvum Iowa, whereas 5 protein coding sequences that are only present in C. parvum but not in C. hominis. Of these 11 CDS, nine of them are hypothetical proteins and the remaining two are 40S ribosomal protein S11 and DinB/family X-type DNA polymerase, which could be utilized as the genetic markers to distinguish between C. hominis and C. parvum. Interestingly, despite their close sequence association at a genome wide level, C. parvum and C. hominis possess many distinct phenotypic traits. It has therefore been assumed that the phenotypic differences between the two-parasite species must be the result of subtle sequence divergence, such as single nucleotide polymorphisms and small insertions/deletions. In addition to this sequence divergence, it has been postulated that certain gene expression differences could likewise drive the phenotypic differences. The whole genome sequencing of C. hominis and C. parvum provided for the first time the opportunity to understand intraspecies differences. Whole genome based single nucleotide polymorphism analysis using IOWA strain and TU502 identified ~37,500 SNPs in the protein coding regions and ~8,000 SNPs in the non-coding regions (Fig. 4) (Widmer et al., 2012). Although genome wide interspecies comparison between C. parvum and C. hominis exhibit 97% similarity, intra-species comparison showed almost monomorphic genomes (152 SNPs between C. hominis TU502 and C. hominis UKH1 and 1857 SNPs between C. hominis UdeA01 and C. hominis UKH1) (Widmer et al., 2012). Interestingly, a comparison between the reference zoonotic C. parvum genome (IOWA) with the C. parvum genome representative of the anthroponotic group (TU114) identified 12,000 SNPs (1.4 SNP per kilobase), which is much higher than that for the C. hominis intra-species comparison (Widmer et al., 2012). Monomorphic

expansion of other closely related apicomplexan parasites, including Neospora caninum and Plasmodium falciparum, has been observed by whole genome sequences of multiple strains throughout the world, usually driven by a selection sweep [(Miotto et al., 2013); Khan A et al., unpublished data]. Thus, phylogenomic studies using additional intra-specific Cryptosporidium isolates, particularly those from C. hominis should be prioritized in order to understand whether a similar phenomenon in the transmission dynamics and mechanism of host adaptation is occurring for this genus. Single cell sequencing. Due to our inability to culture Cryptosporidium in vitro and the limited use of only a few genetic markers, which cover just a fraction of the Cryptosporidium genome, it is not currently possible to estimate the true extent of polymorphisms present in infected human samples. This obstacle can be overcome by single cell whole genome sequencing technique. Recently, Troell K et.al. (Troell et al., 2016) developed a robust method to generate whole genome sequencing data from sorted individual oocysts for subsequent genome amplification and sequencing. Initially, fluorescence-activated cell sorting (FACS) sorted cells were obtained using fluorescent antibodies that are specific to oocyst surface antigens allowing for single Cryptosporidium oocysts to be purified away from fecal material prior to DNA extraction, single cell genome amplification and shotgun sequencing using an Illumina MiSeq. Ten individual genomes were sequenced and each genome covered from 67% to 95% of the entire reference genome (IOWA). When the 10 individual genomes were combined, the sequence data nearly covered the entire reference genome (98.8%) of Cryptosporidium. Thus, single cell whole genome sequencing offers an impressive potential not only to understand the true extent of genetic variation among the isolates of different infected samples, but also to detect multiple species/subtypes (mixed infection) present within the same host. Lateral gene transfer Gene transfer can occur either by lateral gene transfer from another organism, particularly from prokaryotes, or intracellularly through endosymbiosis among eukaryotes, which can have a significant impact on genome evolution. Unlike other apicomplexan parasites, Cryptosporidium has acquired many laterally transferred genes (Sateriale and Striepen, 2016). A recent study using phylogenomic approaches has identified 31 genes acquired through either endosymbiosis (n = 7) or have a prokaryotic (n = 24) origin (Huang et al., 2004). These laterally transferred

genes acquired during evolution provide tremendous benefit to the parasite biology. For example, to adapt to the anaerobic environment of the host intestines, Cryptosporidium horizontally

acquired

several

genes,

including

alcohol

dehydrogenase

and

lactate

dehydrogenase in order to generate oxidized nicotinamide adenine dinucleotide (NAD). Cryptosporidium has also obtained tryptophan synthase B (TrpB) from a proteobacteria, which allows it to produce tryptophan during tryptophan starvation conditions that occur when proinflammatory cytokines such as interferon gamma (IFN) are upregulated in response to Cryptosporidium infection (Chen et al., 1993a; Chen et al., 1993b; Huang et al., 2004; You and Mead, 1998). Interestingly, Cryptosporidium have lost their ability to synthesize nucleotides de novo, so they are heavily dependent on their host to salvage purines and pyrimidines via two laterally transferred genes, inosine 5′ monophosphate dehydrogenase (IMPDH) and thymidine kinase (TK) that have an ancestral proteobacteria origin (Striepen et al., 2004). Thus, these laterally transferred genes not only influence the adaptation of Cryptosporidium to an anaerobic environment, facilitate the salvage of nucleotides from the infected host, and evade the metabolic restrictions imposed by host immunity, they also introduce genomic heterogeneity into Cryptosporidium. This heterogeneity can now be leveraged to identify species specific markers to understand the origins of Cryptosporidium genetic divergence and recombination in wild isolates that affect host range and outbreak potential. Treatment Cryptosporidium drug discovery. Cryptosporidium is the one of leading causes of infectious diarrhea in malnourished and immunocompromised children, particularly in developing countries. It has been shown previously that the both C. parvum and C. hominis can cause long lasting and often life-threatening sequalae in children. Although Cryptosporidium is a huge challenge in children, there are only a handful of drugs for treatment. The major limitation that hinders the progress in the discovery of new anti-parasitic therapeutic drugs against Cryptosporidium is in large part the result of its distinct metabolism from other apicomplexan parasites, including the absence of an apicoplast genome, the paucity of genetic modification tools available, and until recently, a lack of an animal model system to validate drug efficacy in vivo. Currently, only the Food and Drug Administration (FDA) approved drug nitazoxanide has been utilized widely against Cryptosporidium in children and immunocompetent patients,

however it is considered ineffective in immunocompromised individuals (Imboden et al., 2010). There are several non-FDA approved drugs in the market, including paromomycin, which has lower efficacy than nitazoxanide (Hussien et al., 2013; Vandenberg et al., 2012). Intriguingly, Cryptosporidium is an obligate endosymbiont and contains mitosomes instead of mitochondria, which heavily depend on scavenging nutrients from its host. Thus, Cryptosporidium depends on metabolic pathways that are completely distinct from its host and current drug development pipelines are targeting enzymes utilized in these salvage pathways to design new chemoprophylactic interventions. Specifically, drugs that target metabolic pathways to salvage purines for nucleic acid synthesis via inosine 5’-monophosphate dehydrogenase (IMPDH) (Umejiego et al., 2004) and calcium-dependent protein kinase 1 (CDPK-1) (Murphy et al., 2010; Ojo et al., 2010) are being developed. Caffrey et al. adopted an alternative method to treat Cryptosporidium by utilizing an integral family of enzymes known as clan CA (papain-like) group of cysteine proteases including N-methyl-piperazine-PhehomoPhe-vinylsulfone-phenyl (Caffrey and Steverding, 2009). A collection of 400 compounds from an existing library of the Medicines for Malaria has been screened and has identified 19 compounds with significant efficacy against C. parvum at 6.6 uM (Bessoff et al., 2014). However, with the recent development of genetic transformation and other reverse genetic techniques plus novel animal models has opened the door to develop a drug discovery screening process for cryptosporidiosis (Vinayak et al., 2015). By screening 6,220 compounds against C. parvum cultured in the HCT-8 cell line researchers have identified 154 compounds that produce >60% growth inhibition at 5uM concentration and one of them, pyrazolopyridine KDU731, targets the lipid kinase PI(4)K (Phosphatidylinositol-4OH kinase) (Manjunatha et al., 2017). Oral treatment with pyrazolopyridine KDU731, for example, has been shown to significantly reduce parasite burden in the intestines of immunocompromised mice and neonatal calves. Cryptosporidium vaccines. The inability to culture parasites continuously in vitro is impeding the facile generation of transgenic parasites, coupled with the lack of a robust animal model has hindered vaccine development against Cryptosporidium (Vinayak et al., 2015). In the past, several studies utilized -irradiation treatment of oocysts or sporozoites to attenuate strains that were used to elicit protective responses against C. parvum challenge (Ehigiator et al., 2003; Jenkins et al., 2004; Yu and Park, 2003). Several studies also tried to generate vaccines based on DNA immunization by inducing antigen specific B and T cell responses into various infection

model systems (He et al., 2004; Jenkins et al., 1995; Sagodira et al., 1999a; Sagodira et al., 1999b; Tilley et al., 1991). Cp15/60 gene (a sporozoite surface antigen), CpP2, and Cp23 have all been tested in the past for efficacy as a DNA vaccine and shown ~60% reduction in oocyst shedding after challenge in the mouse model. Several immunogenic antigens of C. parvum are immunodominant and require the attachment and invasion of this parasite into host cells. These immunogenic antigens, including Cp15/17, Cp40/15 and Cp23/27 have demonstrated therapeutic efficacy in mouse and animal models and therefore can be utilized as vaccine candidates (Ehigiator et al., 2007; He et al., 2004; Tilley et al., 1991). Identification of these type of immunodominant antigens through more whole genomes and RNA sequencing that facilitates more complete annotations of gene models will be required to identify additional vaccine candidates for Cryptosporidium species. Conclusion Cryptosporidium is the causative agent in >60% of the waterborne protozoan parasitic outbreaks that have been reported worldwide between 2004 and 2010 (Baldursson and Karanis, 2011). To understand the transmission potential and outbreaks due to Cryptosporidium infection, the roles of zoonotic transmission due to intricate association between wild life, domestic animals, and humans and anthroponotic transmission between humans need to be elucidated. Although, several typing and subtyping genetic markers have recently evolved by utilizing very few available whole genome sequences, the significance of zoonotic and anthroponotic transmissions of different Cryptosporidium species are not fully understood, particularly due to lack to diversity of those genetic markers. Only one genetic marker, gp60 has been utilized widely to subtype all major Cryptosporidium species. However, it has been well documented that the current gp60 marker can subtype only C. parvum, C. hominis, C. meleagridis, C. tyzzeri, C. cuniculus, C. fayeri, and C. ubiquitum (Feng et al., 2011; Xiao, 2010) due to high degree of genetic divergence at this locus (Li et al., 2014). Using multilocus genotyping methods that include gp60 (Feng et al., 2014; Feng et al., 2013), Feng et al. have demonstrated the evidences of sexual recombination in wild isolates. Cryptic virulence and potential of zoonotic transmission can evolve though genetic recombination in other eukaryotic pathogens. However, the role of genetic recombination in virulence and zoonotic transmission have not been well documented among Cryptosporidium species. Thus, it is indisputable that improved molecular tools are urgently required to understand the virulence mechanisms and potential of zoonotic transmission

of different Cryptosporidium species. Whole genome sequencing of diverse Cryptosporidium species should be highly encouraged in order to facilitate development of these molecular tools, which will be indispensable towards our understanding of the zoonotic vs. anthroponotic risk of Cryptosporidium.

Conflicts of Interest None.

Acknowledgements The authors are supported by the Intramural Research Program of the National Institute of Allergy and Infectious Diseases (NIAID) at the National Institutes of Health. M.E.G., is a scholar of the Canadian Institute for Advanced Research (CIFAR) Program for Integrated Microbial Biodiversity. The authors thank Patricia Sikorski at NIAID for careful reading of the manuscript and helpful comments.

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Figure legends:

Figure 1. Schematic representation of lifecycle of Cryptosporidium species. After release from oocysts (a), sporozoites enter the lumen of the intestine (b) and form parasitophorous vacuoles (c). Within the PV, parasites convert into trophozoites and undergo asexual replication and form type I meronts (d and e). Type I meronts enter the adjacent host cell and undergo asexual replication to form either additional type I meronts or type II meronts (f). Type II meronts enter the host cells and undergo sexual replication and convert into either microgametes (g) or macrogamonts (h). Zygotes are developed by fertilization of microgametes and macrogamonts (i) and undergo sporogony (j) to generate either thick walled oocysts (k) or thin walled oocysts (l). Thick walled oocysts containing four sporozoites release in fecal samples, are environmentally resistant as they have two layered oocyst walls, and transmit between different hosts where as thin walled oocyst autoinfect and maintain within the same host for long time. [adopted from reference (Bouzid et al., 2013; Current and Garcia, 1991) with permission].

Figure 2. Phylogenetic analysis to understand genetic diversity among different species of Cryptosporidium using 18S ribosomal RNA gene (A), oocyst wall protein (COWP) (B), actin gene (C), and heat shock protein 70 (HSP70) (D). Representative sequences were downloaded from NCBI (https://www.ncbi.nlm.nih.gov/) and aligned using Clustal W/X (Higgins et al., 1996) (Larkin et al., 2007). Accession numbers of each genes are in brackets. Phylogenetic trees were generated using MEGA (Kumar et al., 2001) with 50% majority rule. 1,000 replicates were used to get the bootstrap values, which are indicated at each node as percentage values.

Figure 3.

Molecular epidemiology of C. parvum and C. hominis in human infection. A)

Phylogenetic analysis of subtype families of C. hominis (red) and C. parvum (blue) using 60-kDa glycoprotein (gp60) genes. Accession numbers of each genes are in brackets. Phylogenetic trees were generated using MEGA (Kumar et al., 2001) with 50% majority rule. 1,000 replicates were used to get the bootstrap values, which are indicated at each node as percentage values. B) Relative percentages of prevalence rate of C. hominis and C. parvum in human cryptosporidiosis cases. X-axis represents the different subtypes identified in human cases using mainly gp60 genetic markers. Y-axis indicates countries.

Figure 4. Synteny map of C. parvum and C. hominis. The synteny between the two strains is found using alignment based strategy. The C. parvum reads (https://www.ncbi.nlm.nih.gov/sra: ERR1760143) are aligned to the reference genomes (CparvumIowaII v.32 and ChominisTU502 v.32) (www.toxodb.org) of the two strains respectively. The reads aligned to both the genomes are retained and rest of the reads are filtered out. Synteny map is drawn using C. parvum genome as reference and using the reads that commonly aligned to both the genomes. The outer concentric circle shows the synteny between the two strains (a). The regions not shared by the two strains are represented by white gaps. The color scale indicates the read coverage across the genome with dark red colors indicating high coverage and vice versa. The inner two concentric

circles

show

the

SNP

densities

of

C.

parvum

(b)

and

C.

hominis

(https://www.ncbi.nlm.nih.gov/sra: ERR363534) (c) with respect to C. parvum genome. The regions with high SNP densities are highlighted in red and the rest of the regions are colored green. As can be seen, the SNP densities of both the strains are comparable with overlap of high SNP density regions.

Fig. 1

Fig. 2 A

B

C

D

Fig. 3 B

Subtypes

C. hominis

Countries C. parvum

Subtypes

A

Countries

Fig. 4

a b c

Table 1. Species of Cryptosporidium Species

Host

Site of infection

Reference

Cryptosporidium andersoni

Cattle, sheep, Bactrian camel, gerbil, multimammate mouse, wood partridge

Abomasum

(Lindsay 2000)

Cryptosporidium agni

Lambs

Intestine

Cryptosporidium baileyi

Chicken, duck, Bobwhite quail

Cryptosporidium bovis

Domestic cattle

Cloaca, bursa, trachea Small intestine

(Barker and Carbonell, 1974) (Current et al., 1986) (Fayer et al., 2006b)

Cryptosporidium canis

Dog, fox, coyote Tortoises

Small intestine Small Intestine

(Fayer et al., 2001) (Traversa, 2010)

Cryptosporidium fayeri Cryptosporidium cuniculus

red kangaroo Kangaroo, rabbits and humans

Small intestine Intestine

Cryptosporidium felis Cryptosporidium fragile Cryptosporidium galli Cryptosporidium hominis

Cat, cattle Black-spined toad Chicken Primates, cattle, sheep, pig, dugong

Small intestine Stomach Proventriculus Small intestine

Cryptosporidium macropodum

Grey kangaroo

Small intestine

Cryptosporidium meleagridis

Turkey, chicken, Bobwhite quail, dog, deer mouse Gilthead seabream, European seabass

Small intestine

(Ryan et al., 2008) (Inman and Takeuchi, 1979) (M, 1979) (Jirku et al., 2008) (Ryan et al., 2003b) (Morgan-Ryan et al., 2002) (Power and Ryan, 2008) (Slavin, 1955)

Mouse, hamster, squirrel, Siberian chipmunk, wood mouse, bank vole, rock hyrax, Bactrian camel, mountain goat, cat, coyote, ringed seal, bilby, cynomolgus monkey, tawny frogmouth Calf, lamb, horse, alpaca, dog, mouse, raccoon dog, eastern squirrel Bovine Cattle Turbot

Stomach

(Alvarez-Pellitero and Sitja-Bobadilla, 2002) (Tyzzer, 1907)

Small intestine

(Tyzzer, 1912)

Small intestine Small intestine Intestine stomach) Intestine

(Slapeta, 2006) (Fayer et al., 2008) (Alvarez-Pellitero et al., 2004) (Kvac et al., 2013)

et

al.,

Cryptosporidium ducismarci

Cryptosporidium molnari

Cryptosporidium muris

Cryptosporidium parvum Cryptosporidium pestis Cryptosporidium ryanae Cryptosporidium scophthalmi Cryptosporidium scrofarum

Stomach and intestine

(and

domestic pigs Cryptosporidium serpentis Cryptosporidium suis

Corn snake, rat snake, Madagascar boa Pig, cattle

Cryptosporidium varanii

Emerald monitor

Cryptosporidium viatorum

(Levine, 1980) (Ryan et al., 2004)

Human

Stomach Small and large intestine Stomach and Small intestine Small intestine

Cryptosporidium ubiquitum

Deer, Sheep, Goat, squirrel, mouse

Intestine

(Fayer et al., 2010)

Cryptosporidium wrairi

Guinea pig

Small intestine

Cryptosporidium tyzzeri

Domestic mice

Small intestine

(Vetterling et al., 1971) (Ren et al., 2012)

(Pavlásek I., 1995) (Elwin et al., 2012b)

Table 2. Genetic markers and Nested PCR primers used for multi locus genotyping of Cryptosporidium species. Gene

Nature of polymorphism

Primers

Primer Sequences (5’ to 3’)

SSU rRNA

Multicopy gene and SNPs

F1 R1 F2 R2 F1 R1 F2 R2 F1 R1 F2 R2 F1 R1 F2 R2 F1 R1 F2 R2 F1 R1 F2 R2 F1 R1 F2 R2 F1 R1 F2 R2 F1 R1 F2 R2 F1 R1 F2 R2 F1 R1 F2 R2

TTCTAGAGCTAATACATGCG CCCATTTCCTTCGAAACAGGA GGAAGGGTTGTATTTATTAGATAAAG AAGGAGTAAGGAACAACCTCCA ACTCTATGAAGGTATTGATT TTAGTCGACCTCTTCAACAGTTGG CAGTTGCCATCAGTAGAG CAACAGTTGGACCATTAGATCC GGAAGAGATTGTGTTGC GCAGGAGCTACATATAG GTGTTCAATCAGACACAG C CTG TAT ATC CTG GTG GGC AGA C ATG(A/G)G(A/T)GAAGAAG(A/T)A(A/G)(C/T)(A/T)CAAGC AGAA(G/A)CA(C/T)TTTCTGTG(T/G)ACAAT CAAGC(A/T)TT(G/A)GTTGTTGA(T/C)AA TTTCTGTG(T/G)ACAAT(A/T)(G/C)(A/T)TGG ATAGTCTCCGCTGTATTC GGAAGGAACGATGTATCT TCCGCTGTATTCTCAGCC GCAGAGGAACCAGCATC GCTTAGATTCTGATATGGATC TAT AGCTTACTGGTCCTGTATCAGTT ACCCCAGAAGGCGGACCAAGGTT GTATCGTGGCGTTCTGAATTATCAA CTCACAGAGTTAAAAATCACTT GAACGCAAATATTAAGAAAAATTGAG TTGGCAATGTTGTCTTTTTCCA ATATGTAATCTGGCGCCAAAG ACTGATGTGTCAAGTGGCAATC TTACAGTTATGAGTTGCTGGT TTGATGATTCAGAATCATCTGACT GTGAGTTCTTCTTCATCTGTATAG ATTGAACAAACGCCGCAAATGTACA CGATTATCTCAATATTGGCTGTTATTGC GCTATTTGCTATCGTCTCACATAACT CTACTGAATCTGATCTTGCATCAAGT AAAGGTAACTCAATTGCTAAAGAT TCTTCCTCT TTCTGGCTTTCAGTATT AGATCATATAGTGACACCTGATCAA CCACTGAATCTTCTTTATTGTCAA TGGTTGAGGTTGAAGGCCCAT CATTTCAGCTATTTTAGCTCAACC CATTAATCTTTTAGCAAGAGTAGCTGA AATGCGTTATGCCTTAAAGCTGG

HSP70

COWP

Actin

Gp60

CP47

CP56

Mucin1

MSC6-7

RPGR

DZHRGP

Minisatellites12 bp repeats and SNPs SNPs

SNPs

MicrosatellitesTCA, TCG, TCT repeats and SNPs MicrosatellitesTAA, TGA/TAG SNPs

Minisatellites63 bp repeats and SNPs Minisatellites15 bp and SNPs Minisatellite-18 bp

Minisatellite-30 bp

Annealing temperature (C) 55

Size (bp)

Reference

1325

(Xiao et al., 1999a)

1030 1100

(Sulaiman et al., 2001)

312422

(Kato et al., 2003)

1066

(Sulaiman et al., 2002)

800850

(Alves et al., 2003)

380500

(Gatei et al., 2007)

660750

(Gatei et al., 2007)

650900

(Gatei et al., 2007)

545564

(Gatei et al., 2007)

358376

(Gatei et al., 2006)

574610

(Gatei et al., 2006)

55 55 45 45 58 50 45 50 50 43 55 50 50 58 55 55 55 55 55 55 58