Subtypes of Cryptosporidium parvum in humans and disease risk.

The 2 main species of Cryptosporidium that infect humans are Cryptosporidium hominis and C. parvum. Here, multilocus fragment analysis of 3 microsatellite loci (ML1, ML2, and gp60) was used to subtype strains from sporadic cases of cryptosporidiosis in Wales and northwest England. Of 72 strains of C. parvum, 63 were typeable at all 3 loci, forming 31 subtypes. These strains formed 3 broad clusters, representing 74.6%, 20.6%, and 4.8% of typeable strains. Of 118 C. hominis strains, 106 were typeable at all 3 loci, forming 9 subtypes; however, 90% belonged to the same subtype. Analysis with epidemiologic data found an association between strains from case-patients who reported contact with farm animals and individual C. parvum microsatellite alleles. The strongest association was with ML1; all strains from case-patients that reported farm animal contact had the same allele (ML1-242). Microsatellite typing of C. parvum provides valuable additional information on the epidemiology of this

Crytosporidium species are intestinal parasites that infect a variety of animals; Cryptosporidium hominis (synonym: Cryptosporidium parvum genotype 1) and C. parvum (synonym: C. parvum genotype 2) are the 2 most commonly identified species that cause disease (cryptosporidiosis) in humans (1,2). The main symptom of cryptosporidiosis is diarrhea, which may be accompanied by dehydration, weight loss, abdominal pain, fever, nausea, and vomiting (3). In England and Wales, [approximately equal to] 5,000 cases are reported annually (4). Disease, although lasting for up to 2 weeks, is usually self-limiting in immunocompetent persons but may be chronic and more severe in immunocom-promised patients (5). Furthermore, C. hominis is associated with increased risk of postinfection symptoms (6).

C. hominis primarily infects humans but has recently been reported to infect a dugong and a lamb, and other animals have been infected experimentally (7). Rare occurrences of low-level natural infection of cattle by C. hominis have also been reported (8). By contrast, C. parvum naturally infects several animal species that serve as reservoirs for zoonotic infection, including cattle, sheep, goats, and deer (7).

Several methods have been described by different research groups to investigate intraspecies variation within the genus Cryptosporidium, including microsatellite sequence analysis (9-12), minisatellite and microsatellite PCR fragment length analysis (13,14), single-strand conformation polymorphism analysis (15), gp60 sequence analysis (16,17), and telomere sequence analysis (18,19). A recent study that used minisatellite and microsatellite fragment analysis identified some C. parvum clones that may not be zoonotic (13,14); this study compared isolates from humans and bovines in a single Scottish county. However, no epidemiologic data were presented on casepatients. In the study described here, we investigated the subtypes of C. parvum and C. hominis and tested the association of subtypes with known epidemiologic factors.

Materials and Methods

Strains

The strains included in this analysis were collected during the case-control study of human cryptosporidiosis in Wales and northwest England (20). This study is to date the only case control-study of risk factors for cryptosporidiosis with species identification of infecting strains. Some 427 case-patients and controls were

surveyed by mail questionnaire. The key findings were that travel abroad and changing diapers of children <5 years of age were associated with risk for C. hominis infections. For C. parvum, touching farm animals was associated with illness but eating raw vegetables and tomatoes was strongly negatively associated with illness.

As part of that study, clinical laboratories were encouraged to send fecal samples positive for Cryptosporidium by microscopy to the UK Cryptosporidium Reference Unit in Swansea. Confirmation that samples were positive by microscopy was performed when required by using a modified Ziehl-Neelsen method as described by Casemore et al. (21). To extract Cryptosporidium DNA from microscopy-positive feces, oocysts were first separated from fecal matter by saturated-salt-solution centrifugation as described by Elwin et al. (22). The oocyst suspension was then incubated at 100[degrees]C for 60 min, digested with proteinase K and lysis buffer, and purified by using QIAamp DNA Mini Kit spin columns (QIA-GEN Ltd, Crawly, UK) as described previously (2). DNA was stored at -20[degrees]C before species determination and subtyping, when appropriate.

Identification of Species or Genotype by PCR--Restriction Fragment Length Polymorphism Analysis (PCR-RFLP)

Cryptosporidium sp. was determined by PCR-RFLP analysis of the Cryptosporidium oocyst wall protein (COWP) and small subunit (SSU) rRNA genes using methods based on those described by Spano et al. (23) and Xiao et al. (24), respectively. For PCR-RFLP analysis of the COWP gene, PCR was carried out by using the forward primer 5'-GTAGATAATGGAAGAGATTGTG-3' and reverse primer 5'-GGACTGAAATACAGGCATTAT CTTG-3' to produce an amplicon of [approximately equal to] 550 bp. The PCR products were digested by using the restriction enzyme RsaI to differentiate between most Cryptosporidium spp.

For nested PCR-RFLP analysis of the SSU rRNA gene, the primary PCR produced fragments of [approximately equal to] 1,325 bp by using the forward primer 5'-TTCTAGAGCTAATA CATGCG-3' and the reverse primer 5'-CCCATTTC CTTCGAAACAGGA-3'. The secondary PCR, which produced fragments of [approximately equal to] 830 bp, used the forward primer 5'-GGAAGGGTTGTATTTATTAGATAAAG-3' and the reverse primer 5'-AAGGAGTAAGGAACAACCTCCA3'. The products of the secondary PCR were digested with SspI and VspI. Digested fragments from SSU rRNA and COWP genes were separated by electrophoresis on 3% agarose gels, visualized by SYBR Green I (Sigma, Gillingham, UK) staining, and images were recorded with a digital imaging system (Alpha Imager, Kodak, Hemel Hempstead, UK).

Confirmation of Species or Genotype by SSU rRNA Gene Sequence Analysis

After PCR-RFLP analysis, unusual species and equivocal samples were confirmed by amplifying a fragment of the SSU rRNA gene and DNA sequencing in both directions. Briefly, amplicons of [approximately equal to] 830 bp were produced from each sample by using the nested primer set described above (23), and an [approximately equal to] 298-bp fragment was sequenced (Genetic Research Instrumentation, Braintree, UK) by using the forward primer 5'-AGTGACAAGAAATAACA ATACAGG3' and the reverse primer 5'-CCTGCTTTAAGCACTCT AATTTTC-3' (25). The forward and reverse sequences of these fragments were then aligned and analyzed with a CEQ 8000 Genetic Analysis System (Beckman Coulter, High Wycombe, UK) to obtain a consensus sequence. This sequence was then compared with all GenBank, EMBL, DDBJ, and PDB sequences by using the National Center for Biotechnology Information BLASTN tool (available from www.ncbi.nlm.nih.gov/BLAST/).

Analysis of C. hominis and C. parvum Subtypes

Subtypes were identified by using a multilocus fragment-size--analysis approach to target 3 microsatellite markers (ML1, ML2, and gp60 [synonymous with gpl5]) as previously described (26). The ML1 fragment was amplified by using the forward primer 5'-CTAAAAATG GTGGAGAATATTC-3' and the reverse primer 5'-CAACA AAATCTATATCCTC-3' (10,11). The ML2 fragment was amplified by using the forward primer 5 '-CAATG TAAGTTTACTTATGATTAT-3' and the reverse primer 5'CGACTATAAAGATGAGAGAAG-3' (11). The gp60 fragment was amplified by using the forward primer 5'-GCCGTTCCACTCAGAGGAAC-3" and the reverse primer 5'-CCACATTACAAATGAAGTGCCGC-3' (13). Reverse primers were supplied that were labeled with Beckman Coulter WellRED D3 dye (Proligo, Paris, France). The 50-[micro]L PCR mixture for each primer set contained PCR buffer (QIAGEN Ltd), 2.5 mmol/L of Mg[Cl.sub.2], 200 [micro]mol/L of each dNTP, 500 nmol/L of each primer, 2.5 U of HotStar Taq DNA polymerase (QIAGEN Ltd), and 5 [micro]L of template DNA. The cycling conditions for each PCR were an initial denaturing step of 15 min at 95[degrees]C, then 40 cycles of 95[degrees]C for 50 s, 50[degrees]C (60[degrees]C for gp60) for 50 s, and 72[degrees]C for 60 s before a final extension of 10 min at 72[degrees]C. The fragment sizes of amplified products were then analyzed with a CEQ 8000 Genetic Analysis System (Beckman Coulter). Allele nomenclature was based on the median fragment size of each natural group rounded to the nearest probable base pair number. The combined results of fragment-size analysis at all 3 markers were used to create a multilocus fragment type for subtypes within C. parvum and C. hominis as described elsewhere (26,27).

Statistical Analysis

Data analysis was carried out by using SPSS 12.0 (SPSS Inc., Chicago, IL, USA). Subclusters were identified by using the SPSS clustering algorithm, a hierarchical algorithm that clusters strains and other clusters together on the basis of their similarity.

[chi square] tests (or Fisher exact test when data were sparse) were used to identify significant trends between C. parvum cluster 1 and C. parvum clusters 2 and 3 combined, with epidemiologic parameters. A final multivariable model was derived by using logistic regression as previously described (20) and including all the different strains of C. parvum; the model was recalculated including only the strains that possessed the ML1--242 allele.

The Hunter-Gaston index of discriminatory power was calculated by using StatsDirect (28). This index was proposed as a measure of the discriminatory power of microbial typing schemes. By using the typing scheme under investigation, it calculates the probability of randomly picking 2 unrelated strains and finding them to be different.

Results

A total of 190 sporadic strains of Cryptosporidium were included in this analysis: 118 were C. hominis, of which 106 were typeable at all 3 microsatellite loci; 72 were C. parvum, of which 63 were typeable at all 3 loci. The distribution of these types is shown in Table 1.

Of the 106 strains of C. hominis typeable at all 3 loci, 95 (90%) were indistinguishable at all 3 loci, having the ML1 allele 233 (ML1-233), ML2-180, and gp60-371. This lack of diversity of C. hominis as demonstrated by these 3 markers did not allow further analysis.

Much greater diversity in allele size at all 3 microsatellite loci was displayed by C. parvum than by C. hominis. The discriminatory power of the 3-loci typing method for C. parvum using the Hunter-Gaston index of discriminatory power was 0.957 (95% confidence interval [CI] 0.9374-0977). For C. hominis, the discriminatory power was 0.197 (95% CI 0.096-0.298).

The online Appendix Figure (available from www.cdc.gov/ncidod/EID/13/ 1/82-appG.htm) shows a 3-dimensional scatterplot of the strains of C. parvum. Considerable variation can be seen in microsatellite length, and 3 broad subclusters are identifiable. Strains belonging to the 2 smaller clusters had the same ML1--227 allele, whereas all strains belonging to the larger cluster had the ML1-242 allele.

We further looked at the association between polymorphisms at the 3 loci and reported case-patient contact with animals. For this analysis, all strains were included, whether or not they were typeable at all 3 loci. Significantly more persons with strains with ML1-242 (22/52, 43%) had touched or handled farm animals than those with ML 1-227 strains (0/14, 0%) (Mann-Whitney U test, p = 0.000 (Figure 1). Similarly, at ML2, significantly more strains with alleles between 223 and 237 (42%, 22/52) were from casepatients who had touched or handled farm animals than were strains with alleles 193 and 197 (0%, 0/13) (Mann-Whitney U test, p = 0.000) (Figure 2). Alleles of gp60 (Figure 3) varied from 311 to 371 bp and peaked at 340 to 341 bp. Case-patients who had contact with farm animals yielded significantly greater product sizes at this locus than those who reported no animal contact before onset of illness (Mann-Whitney U test, p = 0.003).

[FIGURES 1-3 OMITTED]

To test further the association between the ML1-242 polymorphism and contact with animals, the final logistic regression model for C. parvum presented in our earlier article (20) was re-run but included only those strains with the 242-bp allele. The positive association with farm animals and the negative associations with eating raw vegetables all are stronger in the model with just ML1-242 allele strains than in the model containing all C. parvum strains (Table 2).

Each typeable strain was also categorized by local environment, based on postal code of patient's residence. These categories were urban, town or town fringe, village, and hamlet or isolated dwelling. The attack rates per 100,000 population for each of the 2 ML1 types of C. parvum are shown in Table 3. The incidence of ML1-242 strains increased as the home environment became increasingly rural, whereas ML1-227 strains were largely restricted to urban and town environments (Mann-Whitney U test, p = 0.005).

Discussion

At these 3 microsatellite loci, much greater genetic diversity was detected among C. parvum strains than among C. hominis strains. For C. parvum the 3 loci were highly discriminatory (Hunter-Gaston index 0.957), but for C. hominis, they were poorly discriminatory (0.197). These 3 loci by themselves are unlikely to be sufficient for subtyping C. hominis but are adequate for subtyping C. parvum.

Using all 3 loci, the typeability for C. hominis was 90% and for C. parvum 87.5%. The presence of non-typeable strains in any one of the 3 single loci reduced the overall typeability and therefore discriminatory power of the typing method. However, strains that did not type at every locus could still be compared. For example, 70 (96%) strains of C. parvum were typed at the ML1 locus, which improved the power of analyses using just this locus. We are unable to say whether nontyping at a particular locus was because of an unusual allele or because of the sensitivity of the method.

The low diversity of C. hominis is to be expected because it is a species-specific parasite. Hunter and Fraser (29) noted that species adapted to single host species were likely to be less genetically diverse than those with a wider host range, as predicted by the theory of adaptive polymorphism. Greater genetic variation was also found among C. parvum (type 2) than C. hominis (type 1) isolates in a previous study that used minisatellite and microsatellite loci (13). This apparently low genetic diversity among strains of C. hominis might make it difficult to develop discriminatory and reproducible typing methods for C. hominis. However, recent investigation of isolates from global sources at multiple minisatellite and microsatellite loci showed increased polymorphism, particularly over many minisatellite loci (30). On the other hand, the use of only 3 loci gives good discriminatory power for C. parvum.

Using just 3 microsatellite loci, we have shown that 3 major groupings of C. parvum can be found, which supports the similar findings of Mallon et al. (13), who used 7 loci. These researchers reported that the largest cluster contained strains isolated from both humans and animals, while the 2 smaller clusters contained strains isolated only from humans. In our study, all strains isolated from persons reporting contact with animals came from cluster 1, which supports the suggestion of 2 clones of human-adapted strains of C. parvum.

The most intriguing finding was that of an association between strains of C. parvum that may be human-adapted or zoonotic and particular alleles of the microsatellites. While this association included all 3 loci, the strongest association was with alleles at the ML1 locus. This observation was even more dramatic, given that only 2 alleles were found at this locus. None of the case-patients whose strains yielded ML1-227 reported contact with farm animals, while 43% of those whose strains yielded ML1-242 reported such contact. This finding is strengthened by the observation that most of the case-patients yielding cluster 2 or 3 strains were more likely to live in urban areas where the possibilities for animal contact are lower than for those yielding cluster 1 strains. In a related study, all 28 strains isolated from animals were ML1-242, which further supports this hypothesis (27,31).

Although the ML2 locus is more variable than the ML1 locus, the 2 loci correlate very closely. This linkage disequilibrium between the 2 loci has already been noted by other researchers (11), although we must emphasize that our results differ from those of Caccio et al. (11), who detected 3 alleles at the ML1 locus (ML1-238, ML1-226, and ML1-220). By sequencing PCR products, these authors also found all 3 alleles in isolates from animals. These discrepancies are not likely to be due to the different methods used for sizing of PCR fragments.

We cannot yet conclude that our findings indicate human-adapted strains of C. parvum exist or if all strains are potentially zoonotic. ML1-227 strains do not appear to be zoonotic in the United Kingdom but have been identified as such by other workers in Italy (11), for example. If such strains are zoonotic in other countries, they likely would have spread into the UK human population through imported foods or during foreign travel and subsequently spread among humans. However, they may not have yet made the transition to UK animals.

Microsatellite fragment analysis of C. parvum would appear to provide a discriminatory and rapid means of distinguishing strains. This technique would be useful in outbreak settings to determine whether outbreaks were due to single or multiple strains and, if the former, may indicate the source of contamination. The microsatellites used in this work would not be discriminatory enough for routine use for C. hominis, although others may prove to be of more value.

Acknowledgments

We thank Kristin Elwin, Anne Thomas, Cathy Bentley, and David Gomez for maintenance of the National Collection of Oocysts and Cryptosporidium species determination, and Guy Robinson for provision of additional subtyping data.

This project was funded by the Department for Food, Environment and Rural Affairs and managed by the Drinking Water Inspectorate.

References

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(11.) Caccio S, Spano F, Pozio E. Large sequence variation at two microsatellite loci among zoonotic (genotype C) isolates of Cryptosporidiumparvum. Int J Parasitol. 2001;31:1082-6.

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(19.) Blasdall SA, Ongerth JE, Ashbolt NJ. Sub-species differentiation among Type 2 bovine C. parvum isolates using a RAPD microsatellite + telomere primer scheme. Proceedings of IWA World Water Congress, Berlin, 2001. London: International Water Association; 2001.

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(22.) Elwin K, Chalmers RM, Roberts R, Guy EC, Casemore DE The modification of a rapid method for the identification of gene-specific polymorphisms in Cryptosporidium parvum, and application to clinical and epidemiological investigations. Appl Environ Microbiol. 2001 ;67:5581-4.

(23.) Spano F, Putignani L, McLauchlin J, Casemore DR Crisanti A. PCR-RFLP analysis of the Cryptosporidium oocyst wall protein (COWP) gene discriminates between C. wrairi and C. parvum, and between C. parvum isolates of human and animal origin. FEMS Microbiol Lett. 1997;150:209-17.

(24.) Xiao L, Singh A, Limor J, Graczyk TK, Gradus S, Lal A. Molecular characterization of Cryptosporidium oocysts in samples of raw surface water and wastewater. Appl Environ Microbiol. 2001;67:1097-101.

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(28.) Hunter PR, Gaston MA. A numerical index of the discriminatory ability of typing systems: an application of Simpson's index of diversity. J Clin Microbiol. 1988;26:2465-6.

(29.) Hunter PR, Fraser CAM. Application of the theory of adaptive polymorphism to the ecology and epidemiology of pathogenic yeasts. Appl Environ Microbiol. 1990;56:2219-22.

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Paul R. Hunter, * Stephen J. Hadfield, ([dagger]) Dawn Wilkinson, * Iain R. Lake, * Florence C.D. Harrison, * and Rachel M. Chalmers ([dagger])

* University of East Anglia, Norwich, United Kingdom; and ([dagger]) National Public Health Service for Wales, Swansea, United Kingdom

Dr Hunter is professor of health protection at the University of East Anglia. His main interests are in the epidemiology of waterborne disease, especially that caused by Cryptosporidium.

Address for correspondence: Rachel M. Chalmers, UK Cryptosporidium Refercnce Unit, NPHS Microbiology Swansea (Velindre NHS Trust), Singleton Hospital, Sketty, Swansea SA2 8QA, UK; email: [e-mail]

Table 1. Distribution of multilocus fragment types (MLFTs) for
Cryptosporidim strains typeable at all 3 loci

                 No.             ML1      ML2      gp60
Species/MLFT   strains     %    allele   allele   allele

C. hominis
  H1             95      89.6     233      180      371
  H2              3       2.8     239      180      371
  H3              2       1.9     242      180      371
  H4              1       0.9     224      180      371
  H5              1       0.9     233      180      407
  H6              1       0.9     233      180      353
  H7              1       0.9     218      180      371
  H8              1       0.9     218      180      413
  H9              1       0.9     233      180      341
C. parvum
  P1              8      12.7     242      229      341
  P2              5       7.9     242      229      338
  P3              2       3.2     227      193      329
  P4              2       3.2     227      195      338
  P5              6       9.5     242      231      341
  P6              4       6.3     242      233      338
  P7              6       9.5     242      231      338
  P8              3       4.8     242      233      341
  P9              1       1.6     242      225      341
  P10             1       1.6     242      227      338
  P11             1       1.6     242      229      332
  P12             1       1.6     242      229      359
  P13             1       1.6     242      229      347
  P14             1       1.6     242      231      356
  P16             1       1.6     242      231      344
  P17             3       4.8     242      231      347
  P18             1       1.6     242      233      347
  P19             1       1.6     242      235      338
  P20             1       1.6     242      237      341
  P21             1       1.6     242      231      350
  P22             1       1.6     227      193      320
  P23             2       3.2     227      195      326
  P24             1       1.6     227      223      332
  P25             2       3.2     227      197      311
  P26             1       1.6     227      231      341
  P27             1       1.6     227      195      353
  P28             1       1.6     227      193      326
  P29             1       1.6     227      193      329
  P30             1       1.6     227      195      332
  P31             1       1.6     227      229      326
  P32             1       1.6     242      237      338

Table 2. Logistic regression model from case-control study (19) showing
final model from original study and recalculated using only those
strains with the ML1-242 polymorphism as cases *

Cases/variable          Cases, n (%)   Controls, n (%)   Odds ratio

All Cryptosporidium
parvum strains
  Touch or handle any
  farm animals
    Yes                    24 (34)         43 (11)          2.653
    No                        47             348
  Eat tomatoes
    Yes                    24 (36)        249 (50)          0.317
    No                        43             246
  Eat raw vegetables
    Yes                     7 (12)        157 (44)          0.222
    No                        51             196
Only ML1-242 strains
  Touch or handle any
  farm animals
    Yes                    21 (43)         43 (11)          3.810
    No                        28             348
  Eat tomatoes
    Yes                    17 (37)        249 (50)          0.425
    No                        29             246
  Eat raw vegetables
    Yes                     4 (10)        157 (44)          0.141
    No                        37             196

Cases/variable             95% CI      p value

All Cryptosporidium
parvum strains
  Touch or handle any
  farm animals
    Yes                 1.113-6.323     0.028
    No
  Eat tomatoes
    Yes                 0.140-0.719     0.005
    No
  Eat raw vegetables
    Yes                 0.086-0.572     0.001
    No
Only ML1-242 strains
  Touch or handle any
  farm animals
    Yes                 1.444-10.049    0.007
    No
  Eat tomatoes
    Yes                 0.164-1.104     0.079
    No
  Eat raw vegetables
    Yes                 0.042-0.474     0.001
    No

* CI, confidence interval. Also included in the models were age and
Health Authority of residence.

Table 3. Association between subtype number and attack rate
per 100,000 population and residential land use

                            ML1-242             ML1-227
Residential land use   No.   Attack rate   No.   Attack rate

Urban                  16        0.21      10        0.13
Town and fringe        10        1.31       4        0.52
Village                14        2.72       0        0.00
Hamlet and isolated    12        3.60       1        0.30
dwellings