Skip to main content

First molecular characterization of Cryptosporidium and Giardia from bovines (Bos taurus and Bubalus bubalis) in Sri Lanka: unexpected absence of C. parvum from pre-weaned calves

Abstract

Background

The genetic characterization of Cryptosporidium and Giardia has important implications for investigating their epidemiology and underpins their control. We undertook the first molecular epidemiological survey of domestic bovids in selected regions of Sri Lanka to establish whether they excreted Cryptosporidium and/or Giardia with zoonotic potential.

Methods

Faecal samples were collected from dairy calves (n = 340; Bos taurus; < 3 months of age; weekly sampling for six weeks) and water buffaloes (n = 297; Bubalus bubalis; <6 months and ≥6 months of age; one sampling) from seven different farms in Sri Lanka. Genomic DNAs were extracted from individual faecal samples and then tested for the presence of parasite DNA using a PCR-based mutation scanning-targeted sequencing-phylogenetic approach, employing genetic markers within the small subunit of nuclear ribosomal RNA and 60 kDa glycoprotein genes (designated pSSU and pgp60, respectively) for Cryptosporidium, and within the triose phosphate isomerise (ptpi) gene for Giardia.

Results

Based on pSSU sequence data, C. bovis, C. ryanae and six new genotypes that were genetically similar but not identical to C. andersoni (n = 1), C. bovis (n = 1), C. ryanae (n = 3) and C. suis (n = 1) were recorded in cattle. For pSSU, two other, new genotypes were defined in water buffalo, which were genetically most similar to Cryptosporidium genotypes recorded previously in this host species in other countries including Australia. Consistent with the findings for pSSU, no species or genotypes of Cryptosporidium with zoonotic potential were detected using pgp60. Based on ptpi sequence data, G. duodenalis assemblages A and E were detected in four and 137 samples from cattle, respectively, and assemblage E in two samples from water buffaloes.

Conclusions

The present study showed that C. parvum, the most commonly reported zoonotic species of Cryptosporidium recognised in bovine calves globally, was not detected in any of the samples from pre-weaned calves tested in the present study. However, eight new genotypes were recorded. Future studies of different host species in various regions are required to investigate the molecular epidemiology of cryptosporidiosis and giardiasis in Sri Lanka and neighbouring countries in South Asia.

Background

Cryptosporidium and Giardia are two parasitic protists that mainly infect the gastrointestinal tract and cause enteric disease in humans and various other animals [1, 2]. These protozoa are global in their distribution and adversely impact on human health in both developed and developing countries [3, 4]. Infections are usually transmitted via the faecal-oral route, following direct or indirect contact with infective stages (oocysts or cysts) [2, 3]. Although infections are often self-limiting in immuno-competent individuals [3, 5], they can become severe and chronic in infants, elderly people or immuno-compromised or -suppressed individuals [68]. Key risk factors for cryptosporidiosis and giardiasis of humans include contact with individuals with diarrhoea, swimming in public pools, travel to developing countries and, importantly, direct contact with animals (e.g., [912]).

Cryptosporidiosis and giardiasis can be transmitted from human to human (anthroponotic) or from animal to human (zoonotic) [13]. Ruminants often have been implicated as a major source of human cryptosporidiosis and giardiasis based on the findings of many molecular epidemiological studies (reviewed in [14, 15]). For instance, investigations of outbreaks and case–control studies [1620] have demonstrated that there is a strong link between human cryptosporidiosis/giardiasis and the direct or indirect contact with cattle, particularly pre-weaned calves [15, 21]. To date, seven species (i.e. C. andersoni, C. bovis, C. felis, C. hominis, C. parvum, C. ryanae and C. suis) and two genotypes of Cryptosporidium (i.e. “pig genotype II” and a new “C. suis-like genotype”) have been recorded in cattle [22, 23]. For Giardia duodenalis, assemblage E is the most commonly reported genotype in cattle, followed by assemblages A and B [2426]. An appraisal of the literature shows that the majority of molecular studies of Cryptosporidium and Giardia of cattle and other animals relates mainly to a limited number of countries in the developed world [3, 27], but there is little published information for developing countries, including Sri Lanka. In addition, although there have been numerous studies of cattle (Bos taurus) in many developed regions of the world [27], there have been few investigations of the molecular epidemiology of cryptosporidiosis and giardiasis in related bovids, such as water buffaloes (Bubalus bubalis) [28, 29], which are common domesticated animals in many countries, particularly in Asia.

Although Cryptosporidium and Giardia are known to present clinical problems in humans [3032] and animals [3335] in Sri Lanka, there is no detailed epidemiological information on the species and genotypes/assemblages of these parasites present in humans or any other animals. These knowledge gaps relate to the fact that suitable molecular methods have not yet been used previously to identify and characterise such species and genotypes/assemblages in this country. Therefore, in the present study, we conducted the first molecular epidemiological survey in Sri Lanka to establish whether domestic bovids might harbour Cryptosporidium and/or Giardia with zoonotic potential. We used a PCR-based approach employing genetic markers in the small subunit of ribosomal RNA (SSU), 60 kDa glycoprotein (gp60) genes for Cryptosporidium and in the triose phosphate isomerase (tpi) gene for Giardia, which have been widely used for the genetic characterization of members of these genera [3, 27]; we were particularly focussed on identifying zoonotic genotypes of these protozoa.

Methods

Sample collection

Faecal samples were collected rectally from pre-weaned dairy calves (Bos taurus; < 3 months of age) and water buffaloes (Bubalus bubalis; <6 months and ≥6 months of age) from seven different farms (designated AB, NZ and DY; BR, HA, NK and MR) in Sri Lanka between August 2012 and February 2013. The three dairy cattle farms (AB, NZ and DY) studied were large, intensive farms, located in the highland wet zone (average >2000 mm of annual rainfall and > 900 m altitude), and maintained Ayrshire, Holstein Friesian and Jersey breeds, respectively. Faecal samples were collected weekly for six weeks from these three dairy farms. At the first visit, faeces were collected from 20 pre-weaned calves (1–12 weeks) from each farm, and individual calves were sampled weekly for 6 weeks, providing a total of 340 samples for molecular testing. In addition, a total of 297 faecal samples were collected once from the two different age groups of water buffalo. The four riverine buffalo herds (BR, HA, NK and MR) studied were in two different climatic zones, with an average of 1,750-2,500 and 1,850-5,000 mm of annual rainfall at altitudes of <300 and 300–900 m, respectively.

Cattle and buffaloes were born and raised on the farms studied, and fed whole milk (twice a day) until weaning at 3 months of age. Dairy calves were reared in individual pens, whereas buffalo calves were maintained as groups (n = 3–10) in pens. Therefore, there was no direct contact between calves and adult cattle or buffaloes. Herd management practices on these dairy and water buffalo farms are typical of large-scale, intensive farms in Sri Lanka.

Isolation of genomic DNA from faecal samples, and PCR amplification

Genomic DNA was isolated from individual faecal samples using the PowerSoil DNA isolation kit (MoBIO, USA) [29], and then frozen at −20°C until molecular testing. Each genomic DNA sample was tested by PCR for Cryptosporidium DNA employing markers (designated pSSU and pgp60) within the small subunit nuclear ribosomal RNA and 60 kDa glycoprotein genes, and for Giardia DNA using a region (ptpi) within the triose phosphate isomerase gene [29, 36]; pgp60 is employed specifically for the detection and assignment of Cryptosporidium species, genotypes or subgenotypes that are infective to humans (cf. [2]). Some genomic DNAs (n = 50) were also tested for inhibition of the enzymatic reaction in PCR using a DNA-spiking approach [37]. In brief, aliquots (2 μl) of individual genomic DNA samples that had been test-negative in PCR were individually spiked with 1 pg of C. parvum DNA and subjected to PCR-based mutation scanning to demonstrate the amplification of a specific product. There was no evidence that samples tested contained constituents inhibitory to PCR.

Mutation scanning-based sequencing and phylogenetic analyses of sequence data

For pSSU amplicons, single-strand conformation polymorphism (SSCP) analysis [38] was carried out as described previously [39]. For ptpi amplicons, restriction endonuclease fingerprinting was employed, using the enzyme Rsa I (Promega) [4042]. Amplicons representing each banding profile were selected and treated with exonuclease I and shrimp alkaline phosphatase (Fermentas), according to the manufacturer’s instructions, and then sequenced in both directions by direct, automated sequencing (BigDye Terminator v.3.1 chemistry, Applied Biosystems, USA), using the same primers employed in secondary PCR. The quality of each sequence was assessed based on the corresponding electropherogram using the program BioEdit [43], and the sequences determined were compared with known reference sequences using the Basic Local Alignment Search Tool (BLAST; http://www.ncbi.nlm.nih.gov/BLAST). Phylogenetic analysis of sequence data was performed using the Bayesian inference (BI) tree building method in MrBayes 3.1.2 [44, 45]. Posterior probabilities (pp) were calculated via 2,000,000 generations, utilizing four simultaneous tree-building chains, with every 100th tree being saved. At this point, the standard deviation of split frequencies was <0.01, and the potential scale reduction factor (PSRF) approached one. A 50% majority rule consensus tree for each analysis was constructed based on the final 75% of trees generated by BI.

Phylogenetic analysis was conducted to assess the relationships of the sequences from the present study to those available from public databases for species or genotypes of Cryptosporidium, and published in the peer-reviewed literature. In brief, species were determined based on 100% sequence homology to known species of Cryptosporidium. Phylogenetic analysis was used to provide unequivocal support for the classification of species and genotypes of Cryptosporidium; new genotypes were designated using sequential numbers, according to a previous study [29]. In addition, statistical analysis of proportional difference was performed using the Fisher’s exact test [46].

Results

Cryptosporidium species/genotypes in cattle

Although pgp60 was not amplified from any of the 340 genomic DNA samples tested, the pSSU region was amplified from 211 (62.1%) of them. SSCP-based analysis of all amplicons revealed eight unique banding profiles. In total, 60 amplicons representing these eight profiles were sequenced (5–10 per profile). No sequence variation was detected among all sequences representing each SSCP profile, such that, ultimately, eight unique pSSU sequences (GenBank accession nos. KF891285-KF891292) were defined. These eight sequences differed by 72-99% upon pairwise comparison. Phylogenetic analysis (Figure 1) of these eight as well as 70 reference sequences (Additional file 1) included for comparative purposes revealed C. bovis (accession no. KF891286), C. ryanae (KF891285) and six new records (genotypes) that were genetically similar (72-99%) but not identical to C. andersoni (n = 1; accession no. KF891291), C. bovis (n = 1; KF891290), C. ryanae (n = 3; KF891287-KF891289) or C. suis (n = 1; KF891292), respectively (see Additional files 2 and 3). In the epidemiological context (Table 1), C. bovis and C. ryanae were detected in 5.6% and 7.4% of all samples only from farm AB, respectively, and the six new Cryptosporidium sequence types (accession nos. KF891287-KF891292) were detected in 0.3-27.6% of samples from farms AB, DY and/or NZ (Table 1).

Figure 1
figure 1

Phylogenetic analysis of p SSU sequence data for Cryptosporidium using Bayesian inference (BI) analysis. The ten distinct pSSU sequences determined in the present study and 36 reference sequences representing Cryptosporidium (accession nos. listed in Additional file 1) were included in the analysis. Eimeria necatrix, E. acervulina, E. brunetti, E. praecox and E. maxima sequences were used as outgroups. Accession numbers of publicly available sequences are indicated at the ends of the branches. Accession numbers linked to sequences determined in the present study are in bold-type; the numbers of samples with particular sequence types are in parentheses. Posterior probabilities (pp) for major nodes are indicated.

Table 1 Cryptosporidium species/genotypes and Giardia duodenalis assemblages detected in faecal samples from dairy cattle from three farms in Sri Lanka

Cryptosporidium species/genotypes in water buffaloes

Although pgp60 was not amplified from any of the 297 genomic DNA samples tested, the pSSU region was amplified from 29 (9.8%) of them. SSCP-based analysis of amplicons revealed three unique banding profiles. In total, nine amplicons representing these three profiles were sequenced. No sequence variation was detected among all three sequences representing each SSCP profile, such that, finally, three unique pSSU sequences (GenBank accession nos. KF891292-KF891294) were defined. These three new sequence types differed by 84-97% upon pairwise comparison. Based on the phylogenetic analysis, two sequence types (accession nos. KF891293 and KF891294) were genetically most similar but not identical to Cryptosporidium genotypes reported previously from water buffaloes (see Figure 1). The other sequence type defined was the same as the pSSU sequence of Cryptosporidium with accession no. KF891292 recorded in cattle in the present study (see section on Cryptosporidium species/genotypes in cattle). In the epidemiological context (Table 1), the Cryptosporidium sequence types with accession nos. KF891293, KF891294 and KF891292 were detected in 2.4% (farms BR, NK and MR), 5.7% (farms HA and MR) and 1.7% (farm MR) of the 297 samples tested, respectively.

Cryptosporidium was detected on all four water buffalo farms (Table 2). Samples test-positive for Cryptosporidium were detected in 25 (8.4%) and four (1.3%) of 297 samples from animals in the categories of < 6 months and ≥ 6 months of age, respectively (Table 3). The lowest (2.4%) and highest (17.6%) percentages of samples test-positive for Cryptosporidium were detected on farms NK and HA, respectively, but there was no significant difference in numbers of test-positive samples between the two different climatic regions in which samples were collected. The total number of calves (< 6 months) that were test-positive for Cryptosporidium was significantly lower for water buffaloes than for cattle in the study population (P < 0.001).

Table 2 Cryptosporidium genotypes and Giardia duodenalis assemblage E detected in faecal samples from buffaloes from four farms in Sri Lanka
Table 3 Cryptosporidium genotypes and Giardia duodenalis assemblage E detected in faecal samples collected from two different age groups of water buffaloes in Sri Lanka

Detection of Giardia duodenalis in cattle

All 340 faecal genomic DNA samples were subjected to genetic analysis for Giardia. The ptpi locus was amplified from 141 (41.5%) of these samples. SSCP analysis of all 141 amplicons displayed 16 distinct profiles. The direct sequencing of 60 amplicons representing all 16 profiles defined 16 distinct sequence types (GenBank accession nos. KF891295-KF891310). These 16 sequences differed by 86-99% upon pairwise comparison. All sequences (~530 bp) representing the 16 profiles were compared with publicly available sequences. One of the 16 sequences was identical to the reference sequence (accession number L02120) for G. duodenalis assemblage A. The 15 other sequences were identified as G. duodenalis assemblage E (Table 4). Three of the 15 sequences were identical to G. duodenalis assemblage E sequences with accession nos. JN162349, JN162348 and EF654688, respectively. Twelve other sequences were 99% similar to G. duodenalis assemblage E sequences with GenBank accession nos. JN162349 (n = 5), JN162348 (n = 2), JN162347 (n = 3) and GQ444455 (n = 2). A comprehensive phylogenetic analysis (Figure 2) supported their classification; the 15 and one sequences determined in this study clustered, with strong nodal support (pp = 1.00), with G. duodenalis assemblages E and A, respectively (Figure 2).

Table 4 Fifteen different p tpi sequences representing assemblage E of Giardia duodenalis detected in cattle and buffaloes in Sri Lanka
Figure 2
figure 2

Phylogenetic relationships of p tpi sequences of Giardia duodenalis based on Bayesian inference (BI) analysis. Sixteen sequences determined in the present study, and 41 reference sequences representing G. duodenalis assemblages A to G (accession nos. listed in Additional file 4) were included in the analysis. Sequences representing G. ardeae, G. muris and G. microti were used as outgroups. Accession numbers linked to sequences determined in the present study are in bold-type; the numbers of samples with particular sequence types are in parentheses. Posterior probabilities (pp) are indicated at all major nodes.

These results were then put into an epidemiological context. Giardia was detected molecularly in 141 (22.1%) samples originating from all three cattle farms. Assemblages A and E were identified in four and 137 of these samples. The highest percentage of test-positive samples was detected in cattle on farm AB (51.3%), followed by farms DY (40.8%) and NZ (32.5%). Each cattle farm had 19 calves that were test-positive for Giardia at some stage during the sampling period. Mixed infections of Cryptosporidium and Giardia were detected in 98 (28.8%) of 340 samples. Of 60 cattle from all three farms, 57 had mixed infections of Cryptosporidium and Giardia at least once during the 6-week sampling period. The total number of calves (< 6 months) that were test-positive for Giardia was significantly higher for cattle than for water buffaloes (P < 0.001).

Detection of Giardia duodenalis in water buffalo

All 297 faecal genomic DNA samples were subjected to genetic analysis for Giardia. The ptpi locus was amplified from two (0.7%) of these samples; the two samples were from water buffaloes of < 1 year of age (farms HA and MR: ≥6 months of age on both farms). The two amplicons were sequenced directly and compared with publicly available sequences. The sequences (GenBank accession nos. KF891311 and KF891312) were the same as two reference sequences (accession nos. JN162348 and JN162349) representing G. duodenalis assemblage E (Additional file 4). The two samples test-positive for Giardia also both contained a Cryptosporidium sequence type with accession no. KF891294.

Discussion

This study genetically characterised, for the first time, Cryptosporidium and Giardia from Bos taurus and Bubalus bubalis in Sri Lanka. Cryptosporidium was identified in 62.1% and 9.8% of 340 samples, and Giardia in 41.5% and 0.7% of 279 samples from these two respective bovid hosts. Overall, two Cryptosporidium species (C. bovis and C. ryanae) and eight new genotypes were defined based on their pSSU sequence (n = 5, accession nos. KF891287-KF891291 in cattle; n = 2, KF891293 and KF891294 in water buffalo; and n = 1, KF891292 in both cattle and buffalo). C. bovis and C. ryanae were detected in calves of 10 and 19 days of age, respectively, time points which are relatively consistent with the pre-patent periods reported for these species of Cryptosporidium[47]. Although both C. bovis and C. ryanae (previously called Cryptosporidium “deer-like genotype”) have been widely reported in calves from different countries throughout the world [48, 49], the eight genotypes characterised here are novel. Consistent with the findings for pSSU, no zoonotic species or genotypes of Cryptosporidium were detected using pgp60, in the absence of any evidence of PCR inhibition.

The first new Cryptosporidium genotype represented by accession no. KF891287, which is distinct in pSSU sequence by one nucleotide substitution (G - > C at alignment position 220; Additional file 3) from C. ryanae (accession no. EU410344), was most commonly detected (44.5%) amongst the 211 Cryptosporidium test-positive samples from cattle. This genotype was detected at least once on all three cattle farms studied and at least once during the 6-week sampling period. The second most frequent (28.9%), new Cryptosporidium genotype pertaining to accession no. KF891290 differed in sequence by one nucleotide substitution (G - > C at position 220; Additional file 3) from C. bovis (AY741305) and was also detected on all three cattle farms examined.

The third and fourth new Cryptosporidium genotypes (accession nos. KF891288 and KF891289), which both differed by two nucleotides (insertion of T or A at alignment positions 73 and 74, and a G - > C at position 220; Additional file 3) from C. ryanae, were each recorded in four and five samples, respectively, from farms AB and DY. These two genotypes differed by only one nucleotide (G- > C) from previously reported C. ryanae variants (accession nos. KC778534 and KC778535; [50]).

The fifth new genotype (accession no. KF891291), which differed in sequence by one nucleotide from C. andersoni, was identified in one sample. Phylogenetic analysis (Figure 1) revealed that the sequence representing this genotype formed a monophyletic group, with five reference sequences representing C. andersoni (pp = 0.88). Although C. andersoni occurs in adult cattle, it has been found occasionally in pre-weaned calves [5155]. The sixth new genotype (accession no. KF891292) was identified in two faecal samples from one calf on one farm (NZ) and five samples isolated from water buffaloes from another farm (MR). This genotype is one nucleotide different from the pSSU sequence of a new Cryptosporidium genotype described previously in cattle in Australia (accession no. KC778530; [50]), Denmark (accession no. DQ182599; [56]), India (accession no. GQ345008; [57]) and the UK (accession no. HQ822134; [58]), and also in water buffaloes in Australia (accession no. KF019204; [29]). Published sequence data for the heat shock protein 70 (hsp 70) and actin genes also supported the validity of this new genotype [58]. Therefore, this genotype might represent a new species, but it remains to be described.

The seventh and eighth new genotypes (represented by accession nos. KF891293 and KF891294) recorded from water buffaloes differed in sequence by a single point mutation (G- > C at position 220; Additional file 3) from genotypes 1 and 2 (accession nos. KF019202 and KF019203) described recently [29] in water buffaloes in Australia, and they were genetically most similar to those represented by accession nos. KF019202, KF019203, AB712388 and JQ002562 [29, 59, 60] in the phylogenetic analysis. These results indicate that these two novel genotypes of Cryptosporidium are buffalo-affiliated, but these genotypes are clearly different from C. ryanae from cattle [47].

Most samples (86.2% of 29) test-positive for Cryptosporidium in water buffaloes were detected in calves of <6 months of age. This result is consistent with previous studies [29, 61, 62], in which the occurrence of Cryptosporidium infection has been reported to be higher in water buffaloes of <6 months than in those of ≥6 months of age. A novel genotype represented by accession no. KF891294 was most frequently detected (58.6%) among Cryptosporidium test-positive samples from water buffaloes. It was also detected more frequently in samples collected from calves of <6 months of age group than those of ≥6 months age group. All of the eight novel genotypes identified here in cattle and buffaloes from Sri Lanka had a unique single-nucleotide (G < − > C) substitution in pSSU (Additional file 3) and appear to be autochthonous to this country.

Surprisingly, C. parvum, the most commonly reported zoonotic species of Cryptosporidium recognised in cattle throughout the world [2, 15, 48], was not detected in the present study in any of the samples collected from calves of 1 week to 3 months of age using a repeated sampling strategy (every week for six weeks). According to epidemiological studies conducted in many countries [16, 52, 55, 6367], C. parvum is most commonly detected in calves of <3 months of age. According to a longitudinal survey conducted by Santín and colleagues [55], C. parvum was detected in 85% of 503 pre-weaned calves, whereas only 1% was associated with post-weaned calves. For this reason, pre-weaned calves are recognised as the major reservoir for human cryptosporidiosis [2]. However, some recent epidemiological studies have reported an abundance of C. bovis infection and a limited presence of C. parvum in calves of 1–60 days of age in China [23, 68, 69], India [68] Nigeria [70] and Sweden [71]. Taken together, the present findings suggest that calves of this age group are not reservoirs for human C. parvum infection in the geographical regions studied here in Sri Lanka. A likely explanation for this unexpected result might relate to sound husbandry practices on farms in Sri Lanka. The three cattle farms studied were well-managed, intensive farms, and pre-weaned calves were kept and fed/watered in individual, elevated wooden calf pens with slatted floors.

G. duodenalis assemblage A was detected in only four samples from calves on one dairy farm (DY), whereas 97% of samples test-positive for Giardia in cattle related to G. duodenalis assemblage E. This result is consistent with the previous studies [50, 7276] reporting that 80-100% of the G. duodenalis isolated from cattle are in assemblage E. This assemblage was detected in calves on all three dairy farms and, at least once, in individual calves during the 6-week period of sampling. The two samples test-positive for Giardia in water buffaloes on farms HA and MR contained G. duodenalis assemblage E, although Giardia was not detected on the other two farms. Previous molecular studies conducted in Australia [29] and Italy [28] have also reported G. duodenalis assemblage E in water buffaloes. These findings support the proposal that cattle and water buffaloes in the geographical areas studied in Sri Lanka are not significant reservoirs for human infection with Giardia.

Both Cryptosporidium and Giardia were detected concurrently in 28.8% of 340 samples from cattle, which is in accordance with previous studies of cattle [7779]. For each genus, the numbers of test-positive samples were higher in cattle than in water buffaloes, which seems to be consistent with a prevalence of up to 100% recorded in studies of dairy calves [22] compared with 9.5-38.3% in water buffalo [28, 29, 61, 8082].

Conclusions

Results of the present study suggest that the epidemiology of bovine cryptosporidiosis and giardiasis in Sri Lanka is distinct from those of other parts of the world. Unique nucleotide substitutions in the pSSU region appear to be specific to Sri Lanka. Expanded studies of domestic and wild bovids in various regions in Sri Lanka are required to test this proposal. The apparent absence of C. parvum from cattle and buffaloes and the low occurrence of G. duodenalis assemblage A in cattle suggest that bovids in the regions studied here have limited significance as reservoirs for human infections. Future work should be focused on large-scale studies to investigate the molecular epidemiology of cryptosporidiosis and giardiasis in a wide range of animals in Sri Lanka and in neighbouring countries in South Asia.

References

  1. Ryan UM, Cacciò SM: Zoonotic potential of Giardia. Int J Parasitol. 2013, 43 (12–13): 943-956.

    Article  CAS  PubMed  Google Scholar 

  2. Jex AR, Chalmers RM, Smith HV, Widmer G, McDonald V, Gasser RB: Cryptosporidiosis. In Oxford Textbook of Zoonoses. Edited by Palmer SR, Soulsby L, Torgerson PR, Brown DWG. 2011, New York: Oxford University Press Inc., (Chapter 46)

    Google Scholar 

  3. Feng Y, Xiao L: Zoonotic potential and molecular epidemiology of Giardia species and giardiasis. Clin Microbiol Rev. 2011, 24 (1): 110-140. 10.1128/CMR.00033-10.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  4. Snelling WJ, Xiao L, Ortega-Pierres G, Lowery CJ, Moore JE, Rao JR, Smyth S, Millar BC, Rooney PJ, Matsuda M, Kenny F, Xu J, Dooley JS: Cryptosporidiosis in developing countries. J Infect Dev Ctries. 2007, 1 (3): 242-256.

    PubMed  Google Scholar 

  5. Chalmers RM, Davies AP: Minireview: clinical cryptosporidiosis. Exp Parasitol. 2010, 124 (1): 138-146. 10.1016/j.exppara.2009.02.003.

    Article  PubMed  Google Scholar 

  6. Hunter PR, Nichols G: Epidemiology and clinical features of Cryptosporidium infection in immunocompromised patients. Clin Microbiol Rev. 2002, 15 (1): 145-154. 10.1128/CMR.15.1.145-154.2002.

    Article  PubMed Central  PubMed  Google Scholar 

  7. Petri WA, Miller M, Binder HJ, Levine MM, Dillingham R, Guerrant RL: Enteric infections, diarrhea, and their impact on function and development. J Clin Invest. 2008, 118 (4): 1277-1290. 10.1172/JCI34005.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  8. Tian L, Chen J, Wang T, Cheng G, Steinmann P, Wang F, Cai Y, Yin X, Guo J, Zhou L, Zhou X: Co-infection of HIV and intestinal parasites in rural area of China. Parasit Vectors. 2012, 5 (1): 36-42. 10.1186/1756-3305-5-36.

    Article  PubMed Central  PubMed  Google Scholar 

  9. Robertson B, Sinclair MI, Forbes AB, Veitch M, Kirk M, Cunliffe D, Willis J, Fairley CK: Case–control studies of sporadic cryptosporidiosis in Melbourne and Adelaide, Australia. Epidemiol Infect. 2002, 128 (3): 419-431.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  10. Yoder JS, Beach MJ: Cryptosporidium surveillance and risk factors in the United States. Exp Parasitol. 2010, 124 (1): 31-39. 10.1016/j.exppara.2009.09.020.

    Article  PubMed  Google Scholar 

  11. Abu-Madi MA, Behnke JM, Ismail A, Al-Olaqi N, Al-Zaher K, El-Ibrahim R: Comparison of intestinal parasitic infection in newly arrived and resident workers in Qatar. Parasit Vectors. 2011, 4: 211-211. 10.1186/1756-3305-4-211.

    Article  PubMed Central  PubMed  Google Scholar 

  12. Júlio C, Vilares A, Oleastro M, Ferreira I, Gomes S, Monteiro L, Nunes B, Tenreiro R, Ângelo H:Prevalence and risk factors for Giardia duodenalis infection among children: A case study in Portugal. Parasit Vectors. 2012, 5 (1): 22-29. 10.1186/1756-3305-5-22.

    Article  PubMed Central  PubMed  Google Scholar 

  13. Xiao L, Fayer R: Molecular characterisation of species and genotypes of Cryptosporidium and Giardia and assessment of zoonotic transmission. Int J Parasitol. 2008, 38 (11): 1239-1255. 10.1016/j.ijpara.2008.03.006.

    Article  CAS  PubMed  Google Scholar 

  14. Thompson RCA: Giardia infections. In Oxford Textbook of Zoonoses. Edited by Palmer SR, Soulsby L, Torgerson PR, Brown DWG. 2011, New York: Oxford University Press Inc., (Chapter 45)

    Google Scholar 

  15. Xiao L, Feng Y: Zoonotic cryptosporidiosis. FEMS Immunol Med Microbiol. 2008, 52: 309-323. 10.1111/j.1574-695X.2008.00377.x.

    Article  CAS  PubMed  Google Scholar 

  16. Ng JSY, Eastwood K, Walker B, Durrheim DN, Massey PD, Porigneaux P, Kemp R, McKinnon B, Laurie K, Miller D, Bramley E, Ryan UM: Evidence of Cryptosporidium transmission between cattle and humans in northern New South Wales. Exp Parasitol. 2012, 130 (4): 437-441. 10.1016/j.exppara.2012.01.014.

    Article  PubMed  Google Scholar 

  17. Ashbolt RH, Coleman DJ, Misrachi A, Conti JM, Kirk MD: An outbreak of cryptosporidiosis associated with an animal nursery at a regional fair. Commun Dis Intell. 2003, 27 (2): 244-249.

    Google Scholar 

  18. Hunter PR, Hughes S, Woodhouse S, Syed Q, Verlander NQ, Chalmers RM, Morgan K, Nichols G, Beeching N, Osborn K: Sporadic cryptosporidiosis case–control study with genotyping. Emerg Infect Dis. 2004, 10 (7): 1241-1249. 10.3201/eid1007.030582.

    Article  PubMed Central  PubMed  Google Scholar 

  19. Roy SL, DeLong SM, Stenzel SA, Shiferaw B, Roberts JM, Khalakdina A, Marcus R, Segler SD, Shah DD, Thomas S, Vugia DJ, Zansky SM, Dietz V, Beach MJ: Risk factors for sporadic cryptosporidiosis among immunocompetent persons in the United States from 1999 to 2001. J Clin Microbiol. 2004, 42 (7): 2944-2951. 10.1128/JCM.42.7.2944-2951.2004.

    Article  PubMed Central  PubMed  Google Scholar 

  20. Kiang KM, Scheftel JM, Leano FT, Taylor CM, Belle-Isle PA, Cebelinski EA, Danila R, Smith KE: Recurrent outbreaks of cryptosporidiosis associated with calves among students at an educational farm programme, Minnesota, 2003. Epidemiol Infect. 2006, 134 (4): 878-886. 10.1017/S0950268805005649.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Hunter PR, Thompson RCA: The zoonotic transmission of Giardia and Cryptosporidium. Int J Parasitol. 2005, 35 (11–12): 1181-1190.

    Article  PubMed  Google Scholar 

  22. Trout JM, Santín M: Livestock. Cryptosporidium and Cryptosporidiosis. Edited by: Fayer R, Xiao L. 2008, Boca Raton, Fl: CRC Press, 451-483. 2

    Google Scholar 

  23. Wang R, Wang H, Sun Y, Zhang L, Jian F, Qi M, Ning C, Xiao L: Characteristics of Cryptosporidium transmission in preweaned dairy cattle in Henan, China. J Clin Microbiol. 2011, 49 (3): 1077-1082. 10.1128/JCM.02194-10.

    Article  PubMed Central  PubMed  Google Scholar 

  24. Budu-Amoako E, Greenwood SJ, Dixon BR, Barkema HW, McClure JT: Foodborne illness associated with Cryptosporidium and Giardia from livestock. J Food Prot. 2011, 74 (11): 1944-1955. 10.4315/0362-028X.JFP-11-107.

    Article  PubMed  Google Scholar 

  25. Thompson RCA: The zoonotic significance and molecular epidemiology of Giardia and giardiasis. Vet Parasitol. 2004, 126 (1–2): 15-35.

    Article  PubMed  Google Scholar 

  26. Geurden T, Vercruysse J, Claerebout E: Is Giardia a significant pathogen in production animals?. Exp Parasitol. 2010, 124 (1): 98-106. 10.1016/j.exppara.2009.03.001.

    Article  PubMed  Google Scholar 

  27. Jex AR, Gasser RB: Genetic richness and diversity in Cryptosporidium hominis and C. parvum reveals major knowledge gaps and a need for the application of "next generation" technologies. Biotechnol Adv. 2010, 28: 17-26. 10.1016/j.biotechadv.2009.08.003.

    Article  PubMed  Google Scholar 

  28. Cacciò SM, Rinaldi L, Cringoli G, Condoleo R, Pozio E: Molecular identification of Cryptosporidium parvum and Giardia duodenalis in the Italian water buffalo (Bubalus bubalis). Vet Parasitol. 2007, 150 (1–2): 146-149.

    Article  PubMed  Google Scholar 

  29. Abeywardena H, Jex AR, von Samson-Himmelstjerna G, Haydon SR, Stevens MA, Gasser RB: First molecular characterisation of Cryptosporidium and Giardia from Bubalus bubalis (water buffalo) in Victoria, Australia. Infect Genet Evol. 2013, 20: 96-102.

    Article  CAS  PubMed  Google Scholar 

  30. Perera J: Cryptosporidium associated childhood diarrhoea in Sri Lanka - a preliminary study. Ceylon Med J. 1988, 33 (3): 101-104.

    CAS  PubMed  Google Scholar 

  31. Perera J, Lucas GN: Cryptosporidiosis-oocyst shedding and infection in household contacts. Ceylon Med J. 1990, 35 (1): 11-14.

    CAS  PubMed  Google Scholar 

  32. Perera J, Jayawardena I, Mendis L, Abeyratne K: Intestinal parasites and diarrhoea in a children’s hospital in Sri Lanka. Ceylon J Med. 1999, 42: 7-12.

    Google Scholar 

  33. Bahirathan M, Weilgama DJ, Wijesundera MKDS: Identification of three species of Eimeria and oocysts of Cryptosporidium from calves in Sri Lanka. Sri Lanka Vet J. 1987, 35: 13-18.

    Google Scholar 

  34. Noordeen F, Rajapakse RPVJ, Faizal AC, Horadagoda NU, Arulkanthan A: Prevalence of Cryptosporidium infection in goats in selected locations in three agroclimatic zones of Sri Lanka. Vet Parasitol. 2000, 93 (2): 95-101. 10.1016/S0304-4017(00)00361-7.

    Article  CAS  PubMed  Google Scholar 

  35. Ekanayake DK, Arulkanthan A, Horadagoda NU, Sanjeevani GK, Kieft R, Gunatilake S, Dittus WP: Prevalence of Cryptosporidium and other enteric parasites among wild non-human primates in Polonnaruwa, Sri Lanka. Am J Trop Med Hyg. 2006, 74 (2): 322-329.

    PubMed  Google Scholar 

  36. Abeywardena H, Jex AR, Nolan MJ, Haydon SR, Stevens MA, McAnulty RW, Gasser RB: Genetic characterisation of Cryptosporidium and Giardia from dairy calves: Discovery of species/genotypes consistent with those found in humans. Infect Genet Evol. 2012, 12: 1984-1993. 10.1016/j.meegid.2012.08.004.

    Article  CAS  PubMed  Google Scholar 

  37. Jiang J, Alderisio KA, Singh A, Xiao L: Development of procedures for direct extraction of Cryptosporidium DNA from water concentrates and for relief of PCR inhibitors. Appl Environ Microbiol. 2005, 71 (3): 1135-1141. 10.1128/AEM.71.3.1135-1141.2005.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  38. Gasser RB, Hu M, Chilton NB, Campbell BE, Jex AR, Otranto D, Cafarchia C, Beveridge I, Zhu XQ: Single-strand conformation polymorphism (SSCP) for the analysis of genetic variation. Nat Protoc. 2006, 1 (6): 3121-3128.

    Article  CAS  PubMed  Google Scholar 

  39. Jex AR, Ryan UM, Ng J, Campbell BE, Xiao L, Stevens M, Gasser RB: Specific and genotypic identification of Cryptosporidium from a broad range of host species by nonisotopic SSCP analysis of nuclear ribosomal DNA. Electrophoresis. 2007, 28 (16): 2818-2825. 10.1002/elps.200600772.

    Article  CAS  PubMed  Google Scholar 

  40. Nolan MJ, Jex AR, Pangasa A, Young ND, Campbell AJ, Stevens M, Gasser RB: Analysis of nucleotide variation within the triose-phosphate isomerase gene of Giardia duodenalis from sheep and its zoonotic implications. Electrophoresis. 2010, 31 (2): 287-298. 10.1002/elps.200900480.

    Article  CAS  PubMed  Google Scholar 

  41. Orita M, Iwahana H, Kanazawa H, Hayashi K, Sekiya T: Detection of polymorphisms of human DNA by gel electrophoresis as single-strand conformation polymorphisms. Proc Natl Acad Sci U S A. 1989, 86 (8): 2766-2770. 10.1073/pnas.86.8.2766.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  42. Zhu XQ, Gasser RB: Single-strand conformation polymorphism (SSCP)-based mutation scanning approaches to fingerprint sequence variation in ribosomal DNA of ascaridoid nematodes. Electrophoresis. 1998, 19 (8–9): 1366-1373.

    Article  CAS  PubMed  Google Scholar 

  43. Hall TA: BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser. 1999, 41: 95-98.

    CAS  Google Scholar 

  44. Ronquist F, Huelsenbeck JP: MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics. 2003, 19 (12): 1572-1574. 10.1093/bioinformatics/btg180.

    Article  CAS  PubMed  Google Scholar 

  45. Huelsenbeck JP, Ronquist F: MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics. 2001, 17 (8): 754-755. 10.1093/bioinformatics/17.8.754.

    Article  CAS  PubMed  Google Scholar 

  46. Petrie A, Watson PF: Statistics for veterinary and animal science. 2013, Oxford: Blackwell Publishing, 3

    Google Scholar 

  47. Fayer R, Santín M, Trout JM: Cryptosporidium ryanae n. sp. (Apicomplexa: Cryptosporidiidae) in cattle (Bos taurus). Vet Parasitol. 2008, 156: 191-198. 10.1016/j.vetpar.2008.05.024.

    Article  PubMed  Google Scholar 

  48. Xiao L: Molecular epidemiology of cryptosporidiosis: an update. Exp Parasitol. 2010, 124 (1): 80-89. 10.1016/j.exppara.2009.03.018.

    Article  CAS  PubMed  Google Scholar 

  49. Santín M: Clinical and subclinical infections with Cryptosporidium in animals. N Z Vet J. 2012, 61 (1): 1-10.

    Article  PubMed  Google Scholar 

  50. Abeywardena H, Jex AR, Firestone SM, McPhee S, Driessen N, Koehler AV, Haydon SR, von Samson-Himmelstjerna G, Stevens MA, Gasser RB: Assessing calves as carriers of Cryptosporidium and Giardia with zoonotic potential on dairy and beef farms within a water catchment area by mutation scanning. Electrophoresis. 2013, 34 (15): 2259-2267. 10.1002/elps.201300146.

    Article  CAS  PubMed  Google Scholar 

  51. Kváč M, Hromadová N, Květoňová D, Rost M, Sak B: Molecular characterization of Cryptosporidium spp. in pre-weaned dairy calves in the Czech Republic: absence of C. ryanae and management-associated distribution of C. andersoni, C. bovis and C. parvum subtypes. Vet Parasitol. 2011, 177 (3–4): 378-382.

    PubMed  Google Scholar 

  52. Kváč M, Kouba M, Vitovec J: Age-related and housing-dependence of Cryptosporidium infection of calves from dairy and beef herds in South Bohemia, Czech Republic. Vet Parasitol. 2006, 137 (3–4): 202-209.

    PubMed  Google Scholar 

  53. Keshavarz A, Haghighi A, Athari A, Kazemi B, Abadi A, Mojarad EN: Prevalence and molecular characterization of bovine Cryptosporidium in Qazvin province, Iran. Vet Parasitol. 2009, 160 (3–4): 316-318.

    Article  CAS  PubMed  Google Scholar 

  54. Muhid A, Robertson I, Ng J, Ryan UM: Prevalence of and management factors contributing to Cryptosporidium sp. infection in pre-weaned and post-weaned calves in Johor, Malaysia. Exp Parasitol. 2011, 127 (2): 534-538. 10.1016/j.exppara.2010.10.015.

    Article  PubMed  Google Scholar 

  55. Santín M, Trout JM, Xiao L, Zhou L, Greiner E, Fayer R: Prevalence and age-related variation of Cryptosporidium species and genotypes in dairy calves. Vet Parasitol. 2004, 122 (2): 103-117. 10.1016/j.vetpar.2004.03.020.

    Article  PubMed  Google Scholar 

  56. Langkjaer RB, Vigre H, Enemark HL, Maddox-Hyttel C: Molecular and phylogenetic characterization of Cryptosporidium and Giardia from pigs and cattle in Denmark. Parasitology. 2007, 134 (Pt 3): 339-350.

    Article  CAS  PubMed  Google Scholar 

  57. Khan SM, Debnath C, Pramanik AK, Xiao L, Nozaki T, Ganguly S: Molecular characterization and assessment of zoonotic transmission of Cryptosporidium from dairy cattle in West Bengal, India. Vet Parasitol. 2010, 171 (1–2): 41-47.

    Article  CAS  PubMed  Google Scholar 

  58. Robinson G, Chalmers RM, Stapleton C, Palmer SR, Watkins J, Francis C, Kay D: A whole water catchment approach to investigating the origin and distribution of Cryptosporidium species. J Appl Microbiol. 2011, 111 (3): 717-730. 10.1111/j.1365-2672.2011.05068.x.

    Article  CAS  PubMed  Google Scholar 

  59. Amer S, Zidan S, Feng Y, Adamu H, Li N: Identity and public health potential of Cryptosporidium spp. in water buffalo calves in Egypt. Vet Parasitol. 2013, 191 (1–2): 123-127.

    Article  PubMed  Google Scholar 

  60. Venu R, Latha BR, Basith SA, Raj GD, Sreekumar C, Raman M: Molecular prevalence of Cryptosporidium spp. in dairy calves in Southern states of India. Vet Parasitol. 2012, 188 (1–2): 19-24.

    Article  CAS  PubMed  Google Scholar 

  61. Mallinath RHK, Chikkachowdappa PG, Gowda AKJ, D'Souza PE: Studies on the prevalence of cryptosporidiosis in bovines in organized dairy farms in and around Bangalore, South India. Vet Arhiv. 2009, 5: 461-

    Google Scholar 

  62. Nasir A, Avais M, Khan MS, Ahmad N: Prevalence of Cryptosporidium parvum infection in Lahore (Pakistan) and its association with diarrhea in dairy calves. Int J Agr Biol. 2009, 11 (2): 221-224.

    Google Scholar 

  63. Fayer R, Santín M, Trout JM, Greiner E: Prevalence of species and genotypes of Cryptosporidium found in 1-2-year-old dairy cattle in the eastern United States. Vet Parasitol. 2006, 135 (2): 105-112. 10.1016/j.vetpar.2005.08.003.

    Article  PubMed  Google Scholar 

  64. Trotz-Williams LA, Martin DS, Gatei W, Cama V, Peregrine AS, Martin SW, Nydam DV, Jamieson F, Xiao L: Genotype and subtype analyses of Cryptosporidium isolates from dairy calves and humans in Ontario. Parasitol Res. 2006, 99 (4): 346-352. 10.1007/s00436-006-0157-4.

    Article  CAS  PubMed  Google Scholar 

  65. Thompson HP, Dooley JS, Kenny J, McCoy M, Lowery CJ, Moore JE, Xiao L: Genotypes and subtypes of Cryptosporidium spp. in neonatal calves in Northern Ireland. Parasitol Res. 2007, 100 (3): 619-624.

    Article  PubMed  Google Scholar 

  66. Amer S, Zidan S, Adamu H, Ye J, Roellig D, Xiao L, Feng Y: Prevalence and characterization of Cryptosporidium spp. in dairy cattle in Nile River delta provinces, Egypt. Exp Parasitol. 2013, 135 (3): 518-523. 10.1016/j.exppara.2013.09.002.

    Article  PubMed  Google Scholar 

  67. Geurden T, Berkvens D, Martens C, Casaert S, Vercruysse J, Claerebout E: Molecular epidemiology with subtype analysis of Cryptosporidium in calves in Belgium. Parasitology. 2007, 134 (14): 1981-1987.

    Article  CAS  PubMed  Google Scholar 

  68. Feng Y, Ortega Y, He G, Das P, Xu M, Zhang X, Fayer R, Gatei W, Cama V, Xiao L: Wide geographic distribution of Cryptosporidium bovis and the deer-like genotype in bovines. Vet Parasitol. 2007, 144 (1–2): 1-9.

    Article  PubMed  Google Scholar 

  69. Zhang W, Wang R, Yang FK, Zhang L, Cao J, Zhang X, Ling H, Liu A, Shen Y: Distribution and genetic characterizations of Cryptosporidium spp. in pre-weaned dairy calves in Northeastern China's Heilongjiang Province. PLoS ONE. 2013, 8 (1): 1-6.

    CAS  Google Scholar 

  70. Maikai BV, Umoh JU, Kwaga JK, Lawal IA, Maikai VA, Cama V, Xiao L: Molecular characterization of Cryptosporidium spp. in native breeds of cattle in Kaduna State, Nigeria. Vet Parasitol. 2011, 178 (3–4): 241-245.

    Article  CAS  PubMed  Google Scholar 

  71. Silverlås C, Näslund K, Björkman C, Mattsson JG: Molecular characterisation of Cryptosporidium isolates from Swedish dairy cattle in relation to age, diarrhoea and region. Vet Parasitol. 2010, 169 (3–4): 289-295.

    Article  PubMed  Google Scholar 

  72. Becher KA, Robertson ID, Fraser DM, Palmer DG, Thompson RCA: Molecular epidemiology of Giardia and Cryptosporidium infections in dairy calves originating from three sources in Western Australia. Vet Parasitol. 2004, 123 (1–2): 1-9.

    Article  CAS  PubMed  Google Scholar 

  73. Ng J, Yang R, McCarthy S, Gordon C, Hijjawi N, Ryan UM: Molecular characterization of Cryptosporidium and Giardia in pre-weaned calves in Western Australia and New South Wales. Vet Parasitol. 2011, 176 (2–3): 145-150.

    Article  CAS  PubMed  Google Scholar 

  74. Appelbee AJ, Frederick LM, Heitman TL, Olson ME: Prevalence and genotyping of Giardia duodenalis from beef calves in Alberta, Canada. Vet Parasitol. 2003, 112 (4): 289-294. 10.1016/S0304-4017(02)00422-3.

    Article  CAS  PubMed  Google Scholar 

  75. Trout JM, Santín M, Greiner E, Fayer R: Prevalence of Giardia duodenalis genotypes in pre-weaned dairy calves. Vet Parasitol. 2004, 124 (3–4): 179-186.

    Article  PubMed  Google Scholar 

  76. Trout JM, Santín M, Greiner EC, Fayer R: Prevalence and genotypes of Giardia duodenalis in 1–2 year old dairy cattle. Vet Parasitol. 2006, 140 (3–4): 217-222.

    Article  PubMed  Google Scholar 

  77. Fayer R, Santín M, Macarisin D: Detection of concurrent infection of dairy cattle with Blastocystis, Cryptosporidium, Giardia, and Enterocytozoon by molecular and microscopic methods. Parasitol Res. 2012, 111 (3): 1349-1355. 10.1007/s00436-012-2971-1.

    Article  PubMed  Google Scholar 

  78. Cardona GA, Carabin H, Goni P, Arriola L, Robinson G, Fernandez-Crespo JC, Clavel A, Chalmers RM, Carmena D: Identification and molecular characterization of Cryptosporidium and Giardia in children and cattle populations from the province of Alava, North of Spain. Sci Total Environ. 2011, 412–413: 101-108.

    Article  PubMed  Google Scholar 

  79. Hamnes IS, Gjerde B, Robertson L: Prevalence of Giardia and Cryptosporidium in dairy calves in three areas of Norway. Vet Parasitol. 2006, 140 (3–4): 204-216.

    Article  PubMed  Google Scholar 

  80. Bhat SA, Juyal PD, Singla LD: Prevalence of cryptosporidiosis in neonatal buffalo calves in Ludhiana District of Punjab, India. Asian J Anim Vet Adv. 2012, 7: 512-520. 10.3923/ajava.2012.512.520.

    Article  CAS  Google Scholar 

  81. Feng Y, Raj Karna S, Dearen TK, Singh DK, Adhikari LN, Shrestha A, Xiao L: Common occurrence of a unique Cryptosporidium ryanae variant in zebu cattle and water buffaloes in the buffer zone of the Chitwan National Park Nepal. Vet Parasitol. 2012, 185 (2–4): 309-314.

    Article  PubMed  Google Scholar 

  82. El-Khodery SA, Osman SA: Cryptosporidiosis in buffalo calves (Bubalus bubalis): prevalence and potential risk factors. Trop Anim Health Prod. 2008, 40 (6): 419-426. 10.1007/s11250-007-9113-2.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Funding support from the Australian Research Council (ARC), Melbourne Water Corporation (MWC), National Health and Medical Research Council (NHMRC) and the Alexander von Humboldt Foundation is gratefully acknowledged.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Robin B Gasser.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

HA carried out molecular laboratory work, data analysis, interpretation and drafting of the manuscript. KU collected samples. AVK assisted with the phylogenetic analyses. HA, RBG and ARJ wrote the manuscript with critical input from RPVJR and other authors. RBG and ARJ conceived the project and attracted the funding. All authors read and approved the final version of the manuscript.

Electronic supplementary material

13071_2014_1230_MOESM1_ESM.doc

Additional file 1: Summary of salient information ( Cryptosporidium species/genotypes, host/environmental source, country, GenBank accession nos. of sequences and associated references) pertaining to the SSU sequences used in the phylogenetic analysis of p SSU data (see Figure 1).(DOC 298 KB)

13071_2014_1230_MOESM2_ESM.doc

Additional file 2: Pairwise comparison of nucleotide sequence differences in the small subunit of nuclear ribosomal RNA (p SSU ) among Cryptosporidium species or genotypes representing reference sequences (GenBank accession nos. EU410344, AY741305, EU245042, EF489038, EU331243 and AB712384) and those from bovids studied herein (bold-type).(DOC 51 KB)

13071_2014_1230_MOESM3_ESM.doc

Additional file 3: An alignment of known reference sequences representing a part of the small subunit of nuclear ribosomal RNA (p SSU ) of Cryptosporidium species or genotypes (GenBank accession nos. EU410344, AY741305, EU245042, EF489038, EU331243 and AB712384) with homologous sequences derived from Cryptosporidium from bovids in the present study. A dot denotes a nucleotide that is identical to that in the top sequence; a dash represents a gap. (DOC 3 MB)

13071_2014_1230_MOESM4_ESM.doc

Additional file 4: Summary of salient information ( Giardia species/assemblages, host origins, country, accession nos. of sequences and associated references) pertaining to the tpi sequences used in the phylogenetic analysis of p tpi data (see Figure 2).(DOC 170 KB)

Authors’ original submitted files for images

Below are the links to the authors’ original submitted files for images.

Authors’ original file for figure 1

Authors’ original file for figure 2

Rights and permissions

Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( https://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Cite this article

Abeywardena, H., Jex, A.R., Koehler, A.V. et al. First molecular characterization of Cryptosporidium and Giardia from bovines (Bos taurus and Bubalus bubalis) in Sri Lanka: unexpected absence of C. parvum from pre-weaned calves. Parasites Vectors 7, 75 (2014). https://doi.org/10.1186/1756-3305-7-75

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/1756-3305-7-75

Keywords