Molecular epidemiology of Cryptosporidium in ...

Veterinary Parasitology 193 (2013) 15–24

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Molecular epidemiology of Cryptosporidium in livestock animals and humans in the Ismailia province of Egypt Yosra A. Helmy a,b,∗ , Jürgen Krücken c , Karsten Nöckler d , Georg von Samson-Himmelstjerna c , Karl-H. Zessin b a b c d

Department of Animal Hygiene, Zoonoses and Animal Ethology, Faculty of Veterinary Medicine, Suez Canal University, 41511 Ismailia, Egypt Faculty Panel Veterinary Public Health, Freie Universität Berlin, 14163 Berlin, Germany Institute for Parasitology and Tropical Veterinary Medicine, Freie Universität Berlin, 14163 Berlin, Germany Federal Institute for Risk Assessment (BfR), 12277 Berlin, Germany

a r t i c l e

i n f o

Article history: Received 23 August 2012 Received in revised form 10 December 2012 Accepted 13 December 2012 Keywords: Cryptosporidium Molecular epidemiology Copro-antigen RIDA® QUICK test Zoonosis gp60 PCR-RFLP Egypt

a b s t r a c t The zoonotic potential of Cryptosporidium was studied in one of the most densely populated provinces of Egypt regarding livestock and people. In a representative survey, faecal samples from cattle, buffalo and stool samples from diarrhoeic children (1y–2y

11.8 (10/85) (6.1–19.97)

12.5 (8/64) (6.0–22.4)

(2/21) (1.6–28.1)

25.9 (22/85) (17.4–35.9)

29.7 (19/64) (19.5–41.7)

14.3 (3/21) (3.8–34.1)

>2y

4.3 (7/164) (1.9–8.3)

5.2 (6/115) (2.1–10.5)

2.0 (1/49) (0.1–9.7)

15.9 (26/164) (10.9–22.1)

13.9 (16/115) (8.5–21.2)

20.4 (10/49) (10.9–33.4)

Total

19.5 (157/804) (16.9–22.4)

19.2 (114/593) (16.2–22.6)

20.4 (43/211) (15.4–26.2)

32.3 (260/804) (29.2–35.6)

31.2 (185/593) (27.6–35.0)

35.5 (75/211) (29.3–42.2)

a

95% confidence interval. All Quick test positives and 10% of the Quick test negative samples were analysed by PCR. Prevalences were calculated by extrapolation assuming that the analysed negative samples are representative for all negative samples. b

were identified by BLASTn in the GenBank® nucleotide database. All C. parvum and C. hominis samples identified in the 18S rDNA PCR, regardless if they were positive in the RIDA® QUICK test or not, were subjected to subtyping regarding the gp60 gene. The C. parvum subtypes were named according to (i) the major subtype family identified by BLAST search, (ii) the numbers of repeats of TCA and TCG in the region of trinucleotide repeats, and (iii) according to the number of ACATCA repeats immediately following the trinucleotide repeat region (Sulaiman et al., 2005). 2.5. Statistical analysis Statistical analysis of the epidemiological data and results of the diagnostic was performed using mid-P exact probability tests to analyse the data and differences were considered significant when p-values 3 month to 1 year and >1 year to 2

years. There was no difference in prevalence between sexes (p = 0.05) with 35.9% (118/329; 95%CI = 30.8–41.2) in males (32/83 buffalo and 86/246 cattle) and 29.9% (142/475; 95%CI = 25.9–34.1) in females (43/128 buffalo and 99/347 cattle). In contrast, only 6.7% (11/165) of the human samples were positive for Cryptosporidium (Table 2). 3.2. Results of the PCR Using a nested PCR, all animal samples positive in the RIDA® QUICK test were confirmed to be positive by PCR. However, when a 10% subset of the negative samples (selection by random number tables from the total of non-ordered numbered 647 negative samples) was tested by PCR, 16% (95%CI = 9–25.6) appeared Cryptosporidium positive in the PCR. Extrapolation of these numbers to the whole dataset gives a total prevalence of 32.3% (31.2% in cattle samples and 35.5% in buffalo samples; Table 1). Age-specific prevalence data are presented in Table 1. Furthermore, 29.9% (142/475) and 35.9% (118/329) of total examined females and males were positive, respectively. Only samples positive in both, PCR and RIDA® QUICK test, had a significantly higher prevalence of diarrhoea (60.51%; 95%CI = 52.7–67.82) than animals negative in both tests (26.84%; 95%CI = 23.28–30.72). The difference in occurrence of diarrhoea between animals only positive in PCR but not in the RIDA® QUICK test (32.04; 95%CI = 34.79–41.58) and animals negative in both tests was not significant. Thus the RIDA® QUICK test performed well in terms of detection of clinical cryptosporidiosis although it failed to detect Cryptosporidium in a considerable percentage of the PCR positive samples. In contrast to the animal samples, all human samples were tested for the presence of Cryptosporidium by PCR. An unexpectedly high percentage of 49.1% of human samples were positive for Cryptosporidium by PCR

Y.A. Helmy et al. / Veterinary Parasitology 193 (2013) 15–24

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Table 2 RIDA® QUICK test and PCR results of Cryptosporidium spp. detection in different age groups and genders of children with 95% confidence intervals. Age group

Quick test

PCR

All animals (%) (Positive/total) (95%CIa )

Female (%)

Male (%)

All animals (%) (Positive/total) (95%CIa )

Female (%)

Male (%)

6 years

8.3 (1/12) (0–34.8)

0 (0/6) (0–39.3)

16.7 (1/6) (0.8–59.1)

25 (3/12) (6.8–54.1)

16.7 (1/6) (0.8–59.1)

33.3 (2/6) (6.0–73.8)

Total

6.7 (11/165) (3.6–11.3)

7.4 (6/81) (3.1–14.8)

5.9 (5/84) (2.2–12.7)

49.1 (81/165) (41.5–56.7)

49.4 (40/81) (38.6–60.2)

48.8 (41/84) (38.3–59.5)

a

95% confidence interval.

(Table 2). The difference was particularly pronounced in the age group between 1.5 and 6 years. Prevalence in children was significantly higher than in the animal samples (p < 0.001) without significant difference between both genders: 49.4% (40/81) of the females and 48.8% (41/84) of the males. In children 1 month to 1.5 years old the agespecific prevalence of 37.3% was significantly lower than the 57.5% observed in children >1.5 years to 6 years of age. 3.3. Cryptosporidium species identification using PCR-RFLP analysis Samples positive with the nested 18S rDNA PCR were further analysed by using SspI, MboII and VspI restriction enzymes. PCR products were sequenced only when RFLP patterns were not completely clear, which occurred particularly with MboII (45 samples). Nucleotide sequences generated for the 18S rDNA gene have been deposited in the GenBank database under accession numbers JX237825JX237828, JX237830- JX237833 and JX298596- JX298604. Among 169 Cryptosporidium spp. positive samples, 111 were identified as C. parvum, 20 as Cryptosporidium ryanae, 7 as C. bovis, 19 as co-infection of C. parvum and C. ryanae, 9 as C. parvum plus C. bovis and 3 as C. parvum plus C. andersoni. Regarding single species infection prevalences of animal isolates (Table 3), C. parvum with 65.7% were significantly more frequently found than C. ryanae with 11.8% (p < 0.001) which itself was more frequent than C. bovis 4.1% (p < 0.01). Moreover mixed infections due to presence of C. parvum plus C. ryanae (11.2%), C. parvum plus C. bovis (5.3%) and C. parvum plus C. andersoni (1.8%) were identified. Notably, the frequency of C. parvum was also higher in young animals than in the older age groups. Among the 12 samples negative for Cryptosporidium in the RIDA® QUICK test but positive in 18S rDNA PCR, there were four C. parvum, four C. bovis, one C. ryanae and three a combination of C. parvum and C. bovis. In marked contrast to the ruminant samples, 60.5%, 38.2% and 1.2% of the examined human samples were

identified as either C. hominis, C. parvum or C. bovis as shown in Table 4. C. hominis was not identified in any of the cattle or buffalo samples. 3.4. Sequencing and subtyping All C. parvum samples for which a nested gp60 PCR product was obtained were sequenced (n = 120). Nucleotide sequences were deposited in the GenBank database under the accession numbers JX237820, JX237821, JX237823, JX237824, and JX298590- JX298595. Nested gp60 PCR was not successful for any of the C. hominis positive samples. Sequence analysis of the gp60 gene of the C. parvum positive samples detected in this study revealed that subtype family IId (81.1%) was significantly more frequently observed than subtype family IIa (18.9%; p < 0.001), with no significant differences between cattle and buffalo or between age groups. For more details see Supplementary Table S1. All C. parvum of subtype family IIa detected from cattle (22.5%) and buffalo (11.4%) belonged to the IIaA15G1R1 subtype, while human infections with subtype family IIa (50%) were found to be due to the subtypes IIaA15G1R1 (n = 2) and IIaA15G2R1 (n = 5) indicating that the latter subtype is significantly more prevalent in the human samples than in the animal samples (p < 0.001). Nearly all C. parvum of subtype family IId detected from cattle (77.5%), buffalo (88.6%) and human (50%) were classified as subtype IIdA20G1. Although this difference in frequency of this subtype in human and animal samples is significant (p < 0.05), it must be emphasised that half of the human C. parvum infections were due to exactly the same subtype as approximately 80% of the animal C. parvum infections. Only one cattle sample belonged to the IIdA19G1 subtype (0.9%). Infections of females (n = 7) with IId (n = 5) were higher than IIa (n = 2), in contrast to infections of males (n = 7) where IIa (n = 5, four of them were infected with IIaA15G2R1 subtype) was higher than IId (n = 2); however, this difference was not significant. There were also no significant differences between infections of male and female buffalo or cattle infected with IIa or IId.

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Table 3 Proportions of Cryptosporidium species determined by restriction fragment length polymorphism within age-groups of cattle and buffalo. Cryptosporidium species

Age groups 1 day–3 month

C. parvum C. ryanae C. bovis C. parvum + C. ryanae C. parvum + C. bovis C. parvum + C. andersoni

Cattle (n = 84) 77.3a 10.7b 2.4b 6.0b 3.6b 0b

Buffalo (n = 34) 70.6a 8.8b 0b 11.8b 8.8b 0b

>3 month–1 year

>1 year–2 years

>2 years

Cattle (n = 20) 50.0a 20.0a 5.0a 20.0a 5.0a 0a

Cattle (n = 11) 27.3a 27.3a 9.1a 9.1a 9.1a 18.1a

Cattle (n = 9) 33.4a 11.1a 11.1a 22.2a 11.1a 11.1a

Buffalo (n = 8) 62.5a 0a 12.5a 25.0a 0a 0a

Buffalo (n = 2) 50.0a 0a 0a 50.0a 0a 0a

All ages Buffalo (n = 1) 0a 0a 100a 0a 0a 0a

(n = 169) 65.7a 11.8b 4.2b 11.2b 5.3b 1.8b

Different superscripts within cattle and buffalo age groups: significant difference at p < 0.05 within species age category.

Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.vetpar.2012.12.015. In contrast to the situation in animals, numbers and probability of human infections with C. parvum IIa or IId were equal. Repeated trials to obtain gp60 sequences from C. hominis samples failed, probably due to low numbers of oocysts and lower sensitivity of the gp60 specific PCR as compared to the 18S rDNA specific PCR.

combinations had comparable frequencies. Between the two water categories C. parvum was significantly more frequently identified (88.5%; 95%CI = 80.5–94.0) in the canal/underground water category than in the tap water category (11.5%; 95%CI = 6.0–19.5). All other species and species combinations occurred at similar proportions in the two water categories. In humans, the two species C. hominis and C. parvum occurred at statistically comparable rates in the “contact” group (56.3% vs. 41.7%; Table 5). In contrast, C. hominis was significantly more prevalent than C. parvum (85.7% vs. 14.3%) in the “no contact” group. The species combination C. parvum/C. bovis was only detected once and in the “contact” category. Between the two categories, proportions of each species and of the species combination were significantly higher (p < 0.05) in the “contact” than in the “no contact” category. A total of four subtypes of C. parvum were determined, of which IIdA20G1 and IIaA15G1R1 occurred in both animals and humans, whereas IIdA19G1 was only detected in animals (n = 1) and IIaA115G2R1 in humans (n = 5). Within the risk factor “source of water”, IIdA20G1 was significantly predominant in the “canal/underground water” category (83.8% vs. 14.3%) and was the only subtype identified in the “tap water” category. In the human risk factor “contact with animals”, all three subtypes, IIaA15G1R1, IIaA20G1 and IIaA15G2R1, occurred in equal rates within the “contact” category, but IIaA15G1R1 and IIaA15G2R1 were absent in the “no contact” category. There were 29 samples collected from children living on farms where samples were also collected from animals. Ten of the human samples were negative for Cryptosporidium spp., ten were positive for C. hominis and nine for C. parvum. In the latter, five were of subtype IIdA20G1 and two were IIaA15G1R1 and in all these cases the same subtype was identified in animals on that particular farm. In contrast, two samples had the subtype IIaA15G2R1 and this subtype

3.5. Epidemiological investigation Detection frequencies of Cryptosporidium in animal and human samples were analysed for associations with potential risk factors determined for the two sample populations. For animals, only the factor “source of drinking water” (“source of water” in Table 5) did show statistical significant differences (p < 0.05). The Cryptosporidium prevalence in animals watered with canal or underground water was significantly higher (80.2%; 95%CI = 72.2–86.7) than in animals watered with tap water (19.8%; 95%CI = 13.3–27.8). For humans, the risk factors residency (city or village), water source (drinking predominantly tap or underground water) and animal contact (children with regular contact to animals in the household or not) were investigated. Cryptosporidium detections were significantly higher (87.3%; 95%CI = 76.4–94.3) for children who had contact with animals in their household than those who had no contact (12.7%; 95%CI = 5.7–23.6). For the risk factors “residency” and “source of water” no difference in prevalence was detected. Table 5 summarises details of the proportional frequencies of Cryptosporidium spp. and C. parvum subtypes within and between the risk factors. Within both water categories (tap water vs. canal/underground water) analysed as risk factors for animals, C. parvum was significantly the dominant species, while the other species and species

Table 4 Relative frequencies (%) of Cryptosporidium spp. within age groups of diarrhoeic children according to restriction fragment length polymorphism. Cryptosporidium species

C. hominis C. parvum C. parvum + C. bovis

Age groups 1 month–1.5 years (n = 9)

>1.5 years–6 years (n = 69)

>6 years (n = 3)

Total (n = 81)

77.8a 22.2b 0b

60.9a 37.7a 1.4b

0a 100a 0a

60.5a 38.3b 1.2c

Different superscripts within human age groups: significant difference at p < 0.05 within age category.


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Table 5 Associations of proportions of Cryptosporidium spp. and subtypes within (a, b, c) or between (*, **) categories of identified animal and human risk factors. Animals

Humans Risk factor: type of water

Species

C. parvum subtypes

C. parvum C. ryanae C. bovis C. parvum + C. andersoni C. parvum + C. bovis C. parvum + C. ryanae IIdA20G1 IIaA15G1R1 IIaA15G2R1 IIdA19G1

Risk factor: contact with animals

Canal, under-ground water

Tap water

82.8a 5.4b 2.2b 2.2b 4.3b 3.2b 83.8a 14.3b

88.5* 55.6* 50.0* 66.7* 57.1* 50.0* 89.1* 100*

43.5a 17.4a 8.7a 4.3b 13.0a 13.0a 100b 0b

1.5c

100*

0b

Contact

11.5** 44.4* 50.0* 33.3* 42.9* 50.0* 10.9** 0** 38.5a 0**

No contact

C. hominis C. parvum C. parvum + C. bovis

56.3a 41.7a 2.1b

81.8* 95.2* 100*

85.7a 14.3a 0b

18.2** 4.8** 0**

85.7* 100* 0**

100a 0b

14.3* 0**

100*

46.2a 15.4a 0b

Different superscripts (a, b, c) within a category of the risk factor: significant difference at p < 0.05. Different superscripts (*, **) between the categories of the risk factor: significant difference at p < 0.05.

was not identified in animals on the same farm. The overall number of samples positive for Cryptosporidium from farm children was too low to calculate any meaningful statistics.

4. Discussion Although previous studies regarding molecular epidemiology of cryptosporidiosis have been performed in Egypt (Abd El Kader et al., 2012; Amer et al., 2010a,b,c) and the middle east (Hijjawi et al., 2010; Sulaiman et al., 2005), this is to our knowledge the first systematic and representative, although not random, approach to estimate parasite prevalence and genotype distribution using sensitive molecular tools in both, humans and animals, to allow detection of zoonotic transmission and identify risk factors for infection. The prevalence of Cryptosporidium spp. in animal samples was 19.5% when using the RIDA® QUICK test and 32.2% when using PCR. The higher sensitivity of PCR compared to the RIDA® QUICK test in this study is in agreement with other results (Agnamey et al., 2011; Goni et al., 2012; Regnath et al., 2006; Weitzel et al., 2006). The RIDA® QUICK test is licensed for the detection of C. parvum in humans. Among the twelve animal samples negative for Cryptosporidium in the RIDA® QUICK test but positive in PCR 11 contained C. parvum or a combination of C. parvum and a second Cryptosporidium species. Moreover, among the 11 human samples positive in the RIDA® QUICK test, three were identified as C. hominis by PCR-RFLP. This suggests that the negative results are not due to a general inability of the RIDA® QUICK test to detect species other than C. parvum. Ca. 60% of the RIDA® QUICK positive animals showed diarrhoea, while animals with a positive PCR result but negative RIDA® QUICK result only showed diarrhoea in 30% of the cases, which was not significantly different from the Cryptosporidium negative animals (28%). So its performance is apparently related to the severity of the disease. The RIDA® QUICK test thus apparently works sufficiently well to screen clinical diarrhoeic animals for Cryptosporidium but

may fail to detect subclinical cases that might be important from an epidemiological point of view. A 32.2% prevalence of Cryptosporidium spp. detected by PCR in predominantly smallholder farm animals in this study is similar to the ones detected with similar molecular methods in some larger farms in another region of Egypt (Amer et al., 2010c). Due to the superior sensitivity of the PCR to traditional microscopic methods, a higher prevalence for the current study area was reported than in other studies (Abou-Eisha, 1994; Abou-Eisha et al., 2000). There were no significantly different prevalences in cattle compared to buffalo which is in agreement to studies performed in India and Pakistan (Nasir et al., 2009; Singh et al., 2006). The prevalence of Cryptosporidium spp. in calves did follow the known pattern of negative correlation with increasing age (Nasir et al., 2009; Singh et al., 2006), with 42.9% prevalence of Cryptosporidium spp. in the calves being significantly higher than in growing or adult cattle (15.9%). The total Cryptosporidium prevalence in children in our study area was 49.1% when using PCR for detection. Lower results for Cryptosporidium prevalence in humans in the same area detected in previous studies were based on microscopic detection only and either refer to older children (Abou-Eisha et al., 2000) or to adults (Abou-Eisha, 1994). In 19 studies carried out in immuno-competent individuals of various ages in several areas of Egypt, the prevalence of cryptosporidiosis varied between 0% and 47% (Abd El Kader et al., 2012). Compared to the farm animals, the prevalence of human infection was significantly higher in the children study cohort (49.1% in children vs. 32.3% in animals). One reason explaining this difference might be the fact that the human sample originated from diarrhoeic children only while only 60.5% were diarrhoeic animal samples. In the present study a similar principal age pattern for Cryptosporidium infections (mostly in children younger than 5 years) as in other developing countries was observed (Bern et al., 2000; Bhattacharya et al., 1997; Gatei et al., 2006; Newman et al., 1999). Surprisingly though, diarrhoeic children below 1.5 years of age were found to be

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less often infected than children between 1.5 and 6 years (when they enter primary school). One probable explanation is that breastfeeding children are less exposed to Cryptosporidium (Abdel-Messih et al., 2005; Bhattacharya et al., 1997). When children start eating normal food and are playing in the streets, poor hygienic conditions might lead to higher infection rates. Results of the PCR-RFLP and sequence analysis of the 18S rDNA gene identified C. parvum as the most dominant Cryptosporidium species in animals, followed by C. ryanae and C. bovis, with presence of mixed infections of C. parvum with one of the two other species and with C. andersoni in some cases. C. parvum was predominantly isolated from calves