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First cross-sectional, molecular epidemiological survey of Cryptosporidium, Giardia and Enterocytozoon in alpaca (Vicugna pacos) in Australia

Parasites & Vectors201811:498

https://doi.org/10.1186/s13071-018-3055-6

  • Received: 28 May 2018
  • Accepted: 10 August 2018
  • Published:

Abstract

Background

Eukaryotic pathogens, including Cryptosporidium, Giardia and Enterocytozoon, have been implicated in neonatal diarrhoea, leading to marked morbidity and mortality in the alpaca (Vicugna pacos) and llama (Lama glama) around the world. Australia has the largest population of alpacas outside of South America, but very little is known about these pathogens in alpaca populations in this country. Here, we undertook the first molecular epidemiological survey of Cryptosporidium, Giardia and Enterocytozoon in V. pacos in Australia.

Methods

A cross-sectional survey of 81 herds, comprising alpacas of 6 weeks to 26 years of age, were sampled from the six Australian states (Queensland, New South Wales, Victoria, South Australia, Tasmania and Western Australia) across the four seasons. PCR-based sequencing was employed, utilising genetic markers in the small subunit of the nuclear ribosomal RNA (SSU) and 60-kilodalton glycoprotein (gp60) genes for Cryptosporidium, triose-phosphate isomerase (tpi) gene for Giardia duodenalis and the internal transcribed spacer region (ITS) for Enterocytozoon bieneusi.

Results

PCR-based analyses of 81 faecal DNA samples representing 1421 alpaca individuals detected Cryptosporidium, Giardia and/or Enterocytozoon on 15 farms in New South Wales, Victoria and South Australia, equating to 18.5% of all samples/herds tested. Cryptosporidium was detected on three (3.7%) farms, G. duodenalis on six (7.4%) and E. bieneusi on eight (9.9%) in two or all of these three states, but not in Queensland, Tasmania or Western Australia. Molecular analyses of selected faecal DNA samples from individual alpacas for Cryptosporidium, Giardia and/or Enterocytozoon consistently showed that alpacas of ≤ 6 months of age harboured these pathogens.

Conclusions

This first molecular investigation of Cryptosporidium, Giardia and Enterocytozoon in alpaca subpopulations in Australia has identified species and genotypes that are of likely importance as primary pathogens of alpacas, particularly young crias, and some genotypes with zoonotic potential. Although the prevalence established here in the alpaca subpopulations studied is low, the present findings suggest that crias are likely reservoirs of infections to susceptible alpacas and/or humans. Future studies should focus on investigating pre-weaned and post-weaned crias, and on exploring transmission patterns to establish what role particular genotypes play in neonatal or perinatal diarrhoea in alpacas and in zoonotic diseases in different states of Australia.

Keywords

  • Alpaca (Vicugna pacos)
  • Australia
  • Cryptosporidium
  • Giardia duodenalis
  • Enterocytozoon bieneusi

Background

Internationally, alpacas (Vicugna pacos), the domesticated form of the South American camelid vicuña (Vicugna vicugna), are prized for their wool and meat [1]. In the 1860s, alpacas and llamas were imported into Australia. However, the camelid industry failed to establish at that time [2]. In the late 1980s, the modern alpaca industry began in Australia, Canada and the USA, with the importation of alpacas from South America (www.alpaca.asn.au). The Australian alpaca fibre market is worth ~ AUD 3.4 million, with an estimated total herd size of 450,000 animals [3]. Commercially farmed alpacas are usually kept in small herds (n ≥ 50), although farms with as many as 5000 animals exist (J. L. Vaughan, unpublished data). Maintaining the health of these herds is of utmost importance to the alpaca industry.

In addition to viruses, bacteria and parasitic helminth infections [46], eukaryotic microbial pathogens of alpaca, including species of Cryptosporidium, Giardia, Eimeria and Enterocytozoon, have been implicated in or inferred to cause neonatal diarrhoea [4, 7], leading to severe morbidity and mortality [4, 812]. Co-infections of Cryptosporidium and Giardia with other pathogens, including viruses, bacteria and other protists, such as Eimeria are common [4, 9, 1115]; such co-infections are recognised to increase the severity and duration of diarrhoea [4, 11]. Young alpacas, or crias, are particularly susceptible to viral and microbial infections, with much infectious disease research being focussed on this age group [911, 13, 16, 17] and few studies involving older animals [1719]. Pathogens, such as Cryptosporidium, Giardia and Enterocytozoon, have the potential to utilise a wide range of hosts, such as humans, wild and domestic animals, as reservoirs for zoonotic transmission [20, 21].

The accurate detection and characterisation of eukaryotic microbes is central to determining their potential infection sources and transmission routes, particularly given that there are at least 37 described species of Cryptosporidium [2224], eight assemblages of Giardia duodenalis [25] and more than 200 genotypes of E. bieneusi [20] to discern. Therefore, the use of molecular (particularly PCR-based) methods has become crucial for any molecular epidemiological investigation [26]. As nothing is currently known about the diversity of such microbes in Australian alpaca herds, the aim here was to undertake the first molecular survey of Cryptosporidium, Giardia and Enterocytozoon in subpopulations of alpacas from 81 farms in six states of Australia.

Methods

Collection of faecal samples

Animal ethics approval (AEC no. 1413412.1) was granted by the University of Melbourne to collect faecal samples from Huacaya alpacas of 6 weeks to 26 years of age (mean: 4.8 years; both sexes) from farms in six states of Australia (Fig. 1). In total, 1421 faecal samples were collected rectally from individual alpacas from 81 herds/farms located in Queensland (QLD; n = 113), New South Wales (NSW; n = 473), Victoria (VIC; n = 563), Tasmania (TAS; n = 89), South Australia (SA; n = 117) and Western Australia (WA; n = 66) (Fig. 1). Each herd was sampled on one occasion between January 2016 and July 2017. The 81 herds comprised 9906 animals [mean herd size ± standard error of the mean (SE), was 122 ± 348; range: 13–3000]. The numbers of faecal samples from individual alpacas in each of the 81 herds varied, depending on the number of samples submitted by farmers (mean: 17.5 ± 4.8; range: 5–35). For 59 (72.9%) of the herds studied, at least 20% of the total herd size was sampled (Additional file 1: Table S1), and the average percentage of each herd sampled was 41.7% (range: 0.3–100%). Of the 1421 individual faecal samples collected, 256 were from crias (< 12 months of age), with an average herd comprising 19.9% crias; most samples were collected in the winter months (40.7%), followed by autumn (28.4%), spring (24.7%) and summer (6.2%) (Table 1).
Fig. 1
Fig. 1

Map of Australia showing the locations of alpaca farms/herds studied. Each circle represents one alpaca farm. QLD Queensland , NSW New South Wales , VIC Victoria , TAS Tasmania, SA South Australia and WA Western Australia

Table 1

The numbers of herds (representing 1421 individual alpacas) sampled from 81 farms from six states in Australia (Fig. 1), and the numbers of pooled faecal samples that were test-positive for Cryptosporidium sp., Giardia duodenalis and Enterocytozoon bieneusi using specific PCR-based sequencing tools (top). Molecular results are also presented according to season in which faecal samples were collected (bottom)

 

Alpacas sampled

Pathogens identified by PCR-based sequencing

No. of herds

No. of individuals

Cryptosporidium sp.

G. duodenalis

E. bieneusi

State

 NSW

26

473

1

4

3

 QLD

7

113

0

0

0

 SA

7

117

0

1

2

 TAS

4

89

0

0

0

 VIC

32

563

2

1

3

 WA

5

66

0

0

0

 Total

81

1421

3

6

8

Season

 Spring

23

382

0

3

3

 Summer

20

369

0

0

0

 Autumn

5

89

0

1

0

 Winter

33

581

3

2

5

 Total

81

1421

3

6

8

Abbreviations: NSW New South Wales, QLD Queensland, SA South Australia, TAS Tasmania, VIC Victoria, WA Western Australia

Genomic DNA isolation and molecular analyses

Faecal samples collected from individual alpacas (n = 5 to 35, in most cases) from each of the 81 herds/farms (Additional file 1: Table S1) were subjected to sucrose flotation (Methods 3.1 and 3.2 in [27]). During this procedure, ~ 20% of the final suspensions (step 4 of Method 3.2 in [27]) derived from all individual faecal samples from each of the herds were pooled, resulting in 81 ‘pooled faecal concentrates’ representing the individual farms. Genomic DNA was isolated from 200 μl each of these concentrates using Method 3.3 [27]. This latter method has been shown to eliminate any faecal constituents that might be inhibitory to PCR [28]. As our goal was to investigate the presence of Cryptosporidium, Giardia and Enterocytozoon populations on the farms, and, where possible, to identify respective species, genotypes or assemblages, we thawed all 81 purified faecal genomic DNA samples (same codes/designations as farms) and subjected them to nested PCR-based sequencing. Subsequently, as required, DNA samples from individual faecal samples (represented in the pooled samples) were prepared [27] and subjected to the same PCR-based analyses.

Established nested PCRs were conducted utilising regions in the small subunit of nuclear ribosomal RNA (SSU), the 60-kilodalton glycoprotein (gp60) gene (for Cryptosporidium; [29]) and the triose-phosphate isomerase (tpi) genes, (for G. duodenalis; [29]) as well as the internal transcribed spacer (ITS) of nuclear ribosomal DNA (for E. bieneusi; [30]). For each assay, known test-positive, test-negative and no-template controls were included in every round of every PCR run. No-template (negative) controls were included at all steps, and no-template controls were ‘carried over’ from the primary to the secondary (nested) PCR. Following PCR, amplicons were examined on standard ethidium bromide-stained 1.5% agarose gels using TBE (65 mM Tris-HCl, 27 mM boric acid, 1 mM EDTA, pH 9; Bio-Rad, Hercules, CA, USA) as the buffer and a 100 bp-DNA ladder (Promega, Madison, WI, USA) as a size marker. Aliquots of individual amplicons were treated with ExoSAP-IT (Affymetrix, Santa Clara, CA, USA) and directly sequenced in both directions (BigDye Terminator v.3.1 chemistry, Applied Biosystems, Foster City, CA, USA) using the same primers employed in the (respective) secondary PCR. Forward and reverse sequences were visually inspected, assembled using the program Geneious v.11.1.2 [31] and compared with other sequences in the GenBank database (NCBI) using the blastn program. Sequences were deposited in the GenBank database under  accession numbers MH341585-MH341587 (SSU), MH346121 and MH346122 (gp60), MH346123 and MH346124 (tpi), and MH342036-MH342038 (ITS).

Results

Cryptosporidium

Cryptosporidium was detected in three of all 81 samples tested (Table 2):
Table 2

Summary of all pathogen species, genotypes and/or assemblages identified in alpaca herds from 81 farms from six states in Australia (Fig. 1) based on PCR-based sequencing of particular genetic markers. The GenBank accession numbers of respective sequences are listed

Pathogen identified

Farm/herd/sample code

Genetic marker used

Pathogen species/genotype/assemblage identified by PCR-based sequencing

GenBank accession no.

Cryptosporidium sp.

CsNSW26

SSU

Cryptosporidium ubiquitum

MH341585

CsVIC15a

SSU

C. parvum

MH341586

gp60

C. parvum IIaA20G3R1

MH346121

CsVIC25a

SSU

C. cuniculus

MH341587

gp60

C. cuniculus VbA25

MH346122

Giardia duodenalis

CsNSW7

tpi

Giardia duodenalis AI

MH346123

CsNSW9

tpi

G. duodenalis AI

MH346123

CsNSW11

tpi

G. duodenalis E

MH346124

CsNSW21

tpi

G. duodenalis AI

MH346123

CsSA3

tpi

G. duodenalis AI

MH346123

CsVIC27

tpi

G. duodenalis AI

MH346123

Enterocytozoon bieneusi

CsNSW6

ITS

Enterocytozoon bieneusi genotype ALP1

MH342036

CsNSW11

ITS

E. bieneusi genotype ALP3

MH342037

CsNSW20a

ITS

E. bieneusi genotype P

MH342038

CsVIC16

ITS

E. bieneusi genotype ALP1

MH342036

CsVIC22

ITS

E. bieneusi genotype ALP1

MH342036

CsVIC23

ITS

E. bieneusi genotype P

MH342038

CsSA3

ITS

E. bieneusi genotype ALP1

MH342036

CsSA7

ITS

E. bieneusi genotype ALP1

MH342036

aReported from a cria of ≤ 6 months of age

(i) C. ubiquitum was detected in sample CsNSW26. The SSU sequence (814 bp) (GenBank: MH341585) from this sample was identical to the sequence with accession no. JN812216 [17] representing C. ubiquitum from an alpaca from Peru and 52 other sequences originating from humans, other animals or environmental samples.

(ii) C. parvum was detected in the sample from farm CsVIC15. The SSU sequence obtained (785 bp) (GenBank: MH341586) was identical to that with accession no. MF074664 and more than 100 other C. parvum sequences (in the GenBank database) representing human and other animal hosts. The electropherogram revealed multiple peaks at 7 nucleotide sites, suggesting a mixed infection. When samples from individual alpacas (n = 13) from CsVIC15 were individually tested, C. parvum IIaA20G3R1 was identified; the gp60 sequence (309 bp) (GenBank: MH346121) was identical to that of C. parvum IIaA20G3R1 (GenBank: JF727804; [32]).

(iii) C. cuniculus was detected in the sample from farm CsVIC25; the SSU sequence obtained (808 bp) (GenBank: MH341587) was identical to that of C. cuniculus from a rabbit in China (GenBank: HQ397716). When samples from individual alpacas (n = 18) from CsVIC25 were tested individually, C. cuniculus VbA25 was identified in a cria of 3.6 months of age; the gp60 sequence obtained (286 bp) (GenBank: MH356122) was 99% similar to the sequence with accession no. MG516794 from C. cuniculus VbA25 from a rabbit in Australia [22].

Giardia

Giardia duodenalis was detected in six of the 81 samples tested (Table 2):

(i) G. duodenalis assemblage AI was detected in samples CsNSW7, CsNSW9, CsNSW21, CsSA3 and CsVIC27; the five tpi sequences obtained (500 bp; GenBank: MH346123) were identical to those with accession no. KM926546 and 46 other tpi sequences in GenBank.

(ii) G. duodenalis assemblage E was detected in sample CsNSW11; the sequence obtained (500 bp; GenBank: MH346124) was identical to that with accession no. GQ444456 [33] derived from a lamb in Australia.

Enterocytozoon

Enterocytozoon bieneusi was detected in eight of the 81 samples tested (Table 2). Genotype ALP1 was detected in samples CsNSW6, CsVIC16, CsVIC22, CsSA3 and CsSA7; the five sequences obtained (243 bp; GenBank: MH342036) were identical to that with accession no. KC860942 originating from a farmed alpaca in Peru [7]. Genotype ALP3 was detected in sample CsNSW11; the one sequence obtained (243 bp; GenBank: MH342037) was identical to that with accession no. KC860930 derived from a farmed alpaca in Peru [7]. Genotype P was detected in samples CsNSW20 and CsVIC23; the two sequences obtained (243 bp; GenBank: MH342038) were identical to that with accession no. KC860928 originating from farmed alpaca in Peru [7] and accession no. AF267146 from llama (Lama glama) in the Munich Zoo, Germany [34].

Epidemiological considerations

Cryptosporidium sp. was detected three times in pooled samples collected during the winter months; G. duodenalis was detected in the spring (n = 3), autumn (n = 1) and winter (n = 2); E. bieneusi was detected in the spring (n = 3) and winter (n = 5) (Table 1). None of the three pathogens was detected in the summer months. The most intensely sampled states were Victoria and New South Wales, both of which had the highest prevalences of Cryptosporidium, G. duodenalis and E. bieneusi (Tables 1 and 2). None of the three pathogen groups was detected in Queensland, Tasmania or Western Australia. Age data were available for most (n = 1313), but not all alpaca individuals. Although we did not assess the ages of all pathogen-positive individuals, as not all herd pools were examined at an individual level, all five pathogen-positive individuals were ≤ 6 months of age (Table 2). Because the cross-sectional sampling took place over a two-year period during different seasons and across different states, any epidemiological inference should be assessed with caution.

Discussion

This is the first cross-sectional study of three eukaryotic microbes (Cryptosporidium sp., G. duodenalis and E. bieneusi) in alpaca herds in Australia, representing nearly 10,000 animals. In an attempt to efficiently sample herds, we elected to use a “pooling method”, which allowed us to screen animals from 81 farms across six Australian states. A total of 59 (72.9%) of the herds were included in the study, and ≥ 20% of individual herd sizes were sampled. Overall, we detected three species of Cryptosporidium (C. cuniculus, C. parvum and C. ubiquitum), two assemblages of G. duodenalis (AI and E) and three genotypes of E. bieneusi (ALP1, ALP3 and P) in 15 of the 81 herds (representing 1421 individual samples).

Context of the molecular-genetic findings

Historically, C. parvum has been the most frequently recorded species of Cryptosporidium in molecular surveys of alpaca in the USA [35] and the UK [10, 18], and both C. parvum and C. ubiquitum have been detected in Peru [17]. However, the present study is the first report of C. cuniculus from alpacas. All three species of Cryptosporidium found in this study (C. cuniculus, C. parvum and C. ubiquitum) are known to be zoonotic [36], and it is proposed that alpacas acquire the infection from oocysts in their environment which originate from humans, other livestock and/or rabbits. The sequence of the subtype of C. parvum found (i.e. IIaA20G3R1) was a perfect match (over 785 bp) to a sequence derived from a faecal sample from a human from New South Wales [32]. This subtype is recognised as causing zoonotic infections in humans and cattle in Australia [32]. Incidentally, a study by Starkey et al. [35] used PCR to trace the zoonotic transmission of C. parvum from crias to six people on a farm in New York, USA. Notably, one cria that transmitted the infection to a human who did not display signs of disease (diarrhoea), indicating transmission from an alpaca with a subclinical infection [35]. The presence of C. ubiquitum in one of the herds in the present study could have originated from sheep, cattle or other livestock, or humans, as it is often associated with these host groups [37]. Cryptosporidium cuniculus, originally recorded in rabbits, has been found in humans, and there is one report from an eastern grey kangaroo [38]. The detection of C. cuniculus DNA in faecal samples from two alpacas from the same herd may be the result of pseudo-parasitism [39], but the possibility of it being a true infection, especially from two crias (3.6 months of age), cannot be excluded.

Giardia duodenalis is comprised of eight assemblages, with assemblage A being primarily associated with humans, livestock and wild ruminants, and assemblage E being common in livestock and wild ruminants [40]. Assemblages A and E have been typically reported previously in alpacas from Peru (AI, AII and E, [7, 17, 41]), the UK (A and E; [42]) and the USA (A and E; [43, 44]), and these assemblages were represented in the present study. More specifically, sub-assemblage AI was found in five of the 81 herds tested, and is considered to have zoonotic potential as it is predominantly found in humans, but has been recorded in domestic livestock and wild ruminants and occasionally in cats and dogs [40]. Aside from a mouse-derived culture of Giardia originating from an alpaca in Australia [45], this is the first report of G. duodenalis from farmed alpaca in this country.

The present study represents the first molecular investigation of E. bieneusi in farmed alpacas in Australia, in which eight of 81 herds were shown to be test-positive. Prior knowledge of E. bieneusi of alpacas is limited to one study from herds in Peru [7], and two studies in Chinese zoos [46, 47]. A Peruvian study of 126 crias discovered six novel genotypes (ALP1-6) as well as already known genotypes P, Type IV, D and Beb6 [7]. Surveys from captive alpacas kept in two Chinese zoos detected recognised genotypes J, CALTI and Beb6 [46, 47]. Additionally, a survey of captive llamas (Lama glama) in the Munich Zoo, Germany, identified the novel subtype P [34]. Interestingly, only alpaca- (ALP1 and ALP3) and llama-specific genotypes (P) were found in the present study. Although it is unknown whether these genotypes are zoonotic, their phylogenetic position (cf. figure 13 in [7]) suggests that they have zoonotic potential, based on epidemiological information available for other genotypes in the ‘Group 1’ clade [46].

Prevalence

Although we were not able to calculate an overall prevalence for each of the three pathogens, given the design of this study, we were able to calculate prevalence within herds. Cryptosporidium sp., G. duodenalis and E. bieneusi were detected in only 3, 6 and 8 of the 81 alpaca herds, respectively (Table 1). Low herd prevalence can be attributed to a number of factors, including logistics (e.g. project design and pooling of samples), animal husbandry (e.g. herd movement, stocking density, population density during birthing, pasture management and grazing method), environmental factors (e.g. environmental temperature, humidity and rainfall) and, likely the most important factor, age.

This study indicates that young crias are more likely to harbour infection than adults (Table 2). To our knowledge, there are no examples of studies that assess Cryptosporidium, Giardia and/or Enterocytozoon across different age groups. Most published investigations have exclusively examined young crias (few days to several weeks of age) (cf. [16]) for the purpose of detecting pathogens associated with neonatal diarrhoea and with high morbidity [4, 9] or mortality [8, 10, 11]. The average age of the animals sampled here from each herd was 4.8 years; thus, broad sampling across ages is likely to have contributed to low prevalences. The few studies that have examined adult camelids resulted in zero prevalence of Cryptosporidium sp. in a herd of 53 alpaca from Japan [15] and another of 354 llamas in California, the USA [48], which examined both crias and adults. Rulofson et al. [48] also studied G. duodenalis and estimated a prevalence of 3% in crias, but found no infected dams. Another survey, which included adult alpacas, was that of Burton et al. [19] who examined 110 crias and their dams on 14 farms in New York and Pennsylvania, USA. The prevalence of Cryptosporidium was 8% in dams and 7% in crias, and 6.4% in dams and 16.3% in crias for G. duodenalis using direct immunofluorescence assays [19]. Two previous studies of G. duodenalis in 61 and 352 alpacas, respectively, showed that 3.2–26.2% of crias and 1.6–1.8% of dams were infected [41, 43]. Clearly, young crias have been reported to have a higher prevalence of Cryptosporidium sp. and G. duodenalis compared with adults, and cohabitation of crias with their dams during the time of sampling may have led to a higher prevalence in dams in some studies [48], but not in others [19]. The largest study of Cryptosporidium sp. in alpacas [16] examined 5163 randomly selected crias of 1 to 15 days of age from 105 herds throughout Peru and estimated a prevalence of 13% (n = 666). In this latter study, adults were not tested, and the testing was conducted using acid fast staining and microscopy, such that the actual prevalence could have been much higher if samples had been tested by PCR.

The study by López-Urbina et al. [16] is valuable in that it emphasises some of the important risk factors for Cryptosporidium sp. (which are also applicable to G. duodenalis and E. bieneusi), such as accessibility to grazing pastures and overcrowding during birthing. Stocking density was also indicated as a likely factor contributing to an outbreak of Cryptosporidium sp. on a farm in New York [35] and from multiple cases of Cryptosporidium sp. in Oregon, USA [9]. The trend toward increasing stocking densities of alpaca in the UK is also a notable risk factor for Cryptosporidium [18]. Additionally, a study of llamas [48] concluded that keeping animals in small pens or in large groups increases the likelihood of G. duodenalis infection. Larger pastures and/or the division of herds into multiple pens to achieve an acceptable stocking density might reduce the spread of other pathogens as well. The Australian Alpaca Association guidelines on herd density (stocking rate) are 10 dry sheep equivalents per hectare (DSE/ha) in areas with high rainfall, compared with 1.5 DSE/ha in drylands (www.alpaca.asn.au).

Past studies have suggested that a high pathogen prevalence is correlated with wetter seasons, as seen in the Pacific Northwest of the USA [13], and after periods of heavy rainfall in the UK [10], although other studies (cf. [9]) have found no correlation with season and that infection can occur year-round. The present investigation demonstrated that the highest prevalence of all three pathogens was in the winter season, especially when compared with summer (zero prevalence). Typically, the summers are drier than the winters in much of New South Wales and Victoria, where the vast majority of the alpaca herds were sampled in this study. The other factor is alpaca calving time, which, in Australia, is usually about two months in spring, although the timing and duration of the birthing periods can vary among farms (J. L. Vaughan, unpublished data). Crias are usually weaned at an average age of three months, when the Australian summer starts. Ultimately, longitudinal sampling of the same herds across seasons would be advantageous in future studies to understand the contribution of season and climate to pathogen prevalence.

Conclusions

The present study provides the first baseline data set for Australia on some major eukaryotic pathogens known to affect alpaca globally. A novel host record was C. cuniculus, and novel locality records were made for the other pathogen species and genotypes identified. All of the pathogens characterised molecularly in this study were either known to be zoonotic or have zoonotic potential. Evident from this study was a low overall herd prevalence of Cryptosporidium sp., G. duodenalis and E. bieneusi infections. Future work should focus on pre-weaned and post-weaned crias to establish which of these pathogens play(s) a role in neonatal diarrhoea in Australia, and it would be interesting to examine faecal consistency and body condition scores to establish the clinical impact of infections by these microbes. Longitudinal studies should investigate herd densities, seasonal effects and environmental factors, such as temperature and rainfall, to ensure the health and welfare of Australia’s alpaca herds.

Abbreviations

FEC: 

faecal egg count

gp60

60-kilodalton glycoprotein

ITS

internal transcribed spacer

SSU

small subunit of nuclear ribosomal RNA gene

tpi

triose-phosphate isomerase

Declarations

Acknowledgement

We are grateful to alpaca farmers across Australia who provided samples for this study.

Funding

Research funding from AgriFutures Australia (AJ), the Australian Research Council (grant number LP160101299) and Melbourne Water Corporation (RBG and AVK) are gratefully acknowledged. Harun Rashid was the recipient of scholarships from the University of Melbourne and the AgriFutures Australia. Yan Zhang was the recipient of scholarships from the Chinese Scholarship Council (CSC) and The University of Melbourne.

Availability of data and materials

The data supporting the conclusions of this article are included within the article and its additional file. Nucleotide sequences reported in this paper are available in the GenBank database under accession numbers MH341585-MH341587 (SSU), MH346121 and MH346122 (gp60), MH346123 and MH346124 (tpi), and MH342036-MH342038 (ITS).

Authors’ contributions

Collected samples: HR, JLV, AJ. Analysis and interpretation: HR, YZ, AVK, JLV, AJ and RBG. Wrote the paper: YZ, AVK and RBG. Supervision of project: AVK, AJ and RBG. Grant funding: AJ, JLV, RBG and AVK. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Animal ethics approval (AEC no. 1413412.1) was granted by The University of Melbourne to collect faecal samples from alpacas in Australia.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria, 3010, Australia
(2)
Cria Genesis, PO Box 406, Ocean Grove, Victoria, 3226, Australia

References

  1. Leguía G. The epidemiology and economic impact of llama parasites. Parasitol Today. 1991;7:54–6.View ArticlePubMedGoogle Scholar
  2. Mitchell J. Alpacas in colonial Australia: acclimatisation, evolution and empire. J Aust Colonial Hist. 2010;12:55.Google Scholar
  3. RIRDC: Alpaca market assessment 2016. Wagga Wagga, New South Wales, Australia: Rural Industries Research and Development Corporation; 2016. ISBN no. 978-1-74254-934-7.5Google Scholar
  4. Whitehead CE, Anderson DE. Neonatal diarrhea in llamas and alpacas. Small Ruminant Res. 2006;61:207–15.View ArticleGoogle Scholar
  5. Franz S, Wittek T, Joachim A, Hinney B, Dadak AM. Llamas and alpacas in Europe: endoparasites of the digestive tract and their pharmacotherapeutic control. Vet J. 2015;204:255–62.View ArticlePubMedGoogle Scholar
  6. Halsby K, Twomey D, Featherstone C, Foster A, Walsh A, Hewitt K, et al. Zoonotic diseases in South American camelids in England and Wales. Epidemiol Infect. 2017;145:1037–43.View ArticlePubMedGoogle Scholar
  7. Gómez Puerta LA. Caracterización molecular de genotipos de Enterocytozoon bieneusi y ensamblajes de Giardia duodenalis aislados de heces de crías de alpaca (Vicugna pacos). MSc thesis, Universidad Nacionl Mayor de San Marcos, Lima, Peru; 2013; p. 120.Google Scholar
  8. Bidewell C, Cattell J. Cryptosporidiosis in young alpacas. Vet Rec. 1998;142:287.PubMedGoogle Scholar
  9. Waitt LH, Cebra CK, Firshman AM, McKenzie EC, Schlipf JW. Cryptosporidiosis in 20 alpaca crias. J Am Vet Med Assoc. 2008;233:294–8.View ArticlePubMedGoogle Scholar
  10. Wessels J, Wessels M, Featherstone C, Pike R. Cryptosporidiosis in eight-month-old weaned alpacas. Vet Rec. 2013;173:426–7.View ArticlePubMedGoogle Scholar
  11. Rojas M, Manchego A, Rocha CB, Fornells LA, Silva RC, Mendes GS, et al. Outbreak of diarrhea among preweaning alpacas (Vicugna pacos) in the southern Peruvian highland. J Infect Dev Countr. 2016;10:269–74.View ArticleGoogle Scholar
  12. Lucas JR, Morales S, Barrios M, Rodríguez J, Vásquez M, Lira B, et al. Patógenos involucrados en casos fatales de diarrea en crías de alpaca de la Sierra Central del Perú. Rev Invest Vet Peru. 2016;27:169–75.Google Scholar
  13. Cebra CK, Mattson DE, Baker RJ, Sonn RJ, Dearing PL. Potential pathogens in feces from unweaned llamas and alpacas with diarrhea. J Am Vet Med Assoc. 2003;223:1806–8.View ArticlePubMedGoogle Scholar
  14. Bertin F, Squires J, Kritchevsky J, Taylor S. Clinical findings and survival in 56 sick neonatal New World Camelids. J Vet Intern Med. 2015;29:368–74.View ArticlePubMedGoogle Scholar
  15. Hyuga A, Matsumoto J. A survey of gastrointestinal parasites of alpacas (Vicugna pacos) raised in Japan. J Vet Med Sci. 2016;78:719–21.View ArticlePubMedGoogle Scholar
  16. López-Urbina M, González A, Gomez-Puerta L, Romero-Arbizu M, Perales-Camacho R, Rojo-Vázquez F, et al. Prevalence of neonatal cryptosporidiosis in Andean alpacas (Vicugna pacos) in Peru. Open Parasitol J. 2009;3:9–13.View ArticleGoogle Scholar
  17. Gómez-Couso H, Ortega-Mora LM, Aguado-Martínez A, Rosadio-Alcántara R, Maturrano-Hernández L, Luna-Espinoza L, et al. Presence and molecular characterisation of Giardia and Cryptosporidium in alpacas (Vicugna pacos) from Peru. Vet Parasitol. 2012;187:414–20.View ArticlePubMedGoogle Scholar
  18. Twomey D, Barlow A, Bell S, Chalmers R, Elwin K, Giles M, et al. Cryptosporidiosis in two alpaca (Lama pacos) holdings in the South-West of England. Vet J. 2008;175:419–22.View ArticlePubMedGoogle Scholar
  19. Burton AJ, Nydam DV, Mitchell KJ, Bowman DD. Fecal shedding of Cryptosporidium oocysts in healthy alpaca crias and their dams. J Am Vet Med Assoc. 2012;241:496–8.View ArticlePubMedGoogle Scholar
  20. Santín M. Enterocytozoon bieneusi. In: Xiao L, Ryan U, Feng Y, editors. Biology of Foodborne Parasites. Boca Raton, FL, USA: CRC Press; 2015. p. 149–74.Google Scholar
  21. Thompson R, Ash A. Molecular epidemiology of Giardia and Cryptosporidium infections. Infect Genet Evol. 2016;40:315–23.View ArticlePubMedGoogle Scholar
  22. Zahedi A, Monis P, Gofton AW, Oskam CL, Ball A, Bath A, et al. Cryptosporidium species and subtypes in animals inhabiting drinking water catchments in three states across Australia. Water Res. 2018;134:327–40.View ArticlePubMedGoogle Scholar
  23. Čondlová Š, Horčičková M, Sak B, Květoňová D, Hlásková H, Konečný R, et al. Cryptosporidium apodemi sp. n. and Cryptosporidium ditrichi sp. n. (Apicomplexa: Cryptosporidiidae) in Apodemus spp. Eur J Protistol. 2018;63:1–12.View ArticlePubMedGoogle Scholar
  24. Kváč M, Vlnatá G, Ježková J, Horčičková M, Konečný R, Hlásková L, et al. Cryptosporidium occultus sp. n. (Apicomplexa: Cryptosporidiidae) in rats. Eur J Protistol. 2018;63:96–104.View ArticlePubMedGoogle Scholar
  25. Xiao L, Feng Y. Molecular epidemiologic tools for waterborne pathogens Cryptosporidium spp. and Giardia duodenalis. Food Waterborne Parasitol. 2017;8–9:14–32.View ArticleGoogle Scholar
  26. Gasser RB. Molecular tools - advances, opportunities and prospects. Vet Parasitol. 2006;136:69–89.View ArticlePubMedGoogle Scholar
  27. Roeber F, Jex AR, Gasser RB. A real-time PCR assay for the diagnosis of gastrointestinal nematode infections of small ruminants. In: Cunha M, Inácio J, editors. Veterinary Infection Biology: Molecular Diagnostics and High-throughput Strategies. New York, NY, USA: Springer; 2015. p. 145–52.Google Scholar
  28. Roeber F, Jex AR, Gasser RB. Comparative evaluation of two DNA isolation techniques for PCR-based diagnosis of gastrointestinal nematode infections in sheep. Mol Cell Probes. 2013;27:153–7.View ArticlePubMedGoogle Scholar
  29. Koehler AV, Haydon SR, Jex AR, Gasser RB. Cryptosporidium and Giardia taxa in faecal samples from animals in catchments supplying the city of Melbourne with drinking water (2011 to 2015). Parasit Vectors. 2016;9:315.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Zhang Y, Koehler AV, Wang T, Haydon SR, Gasser RB. First detection and genetic characterisation of Enterocytozoon bieneusi in wild deer in Melbourne's water catchments in Australia. Parasit Vectors. 2018;11:2.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, et al. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics. 2012;28:1647–9.View ArticlePubMedPubMed CentralGoogle Scholar
  32. Waldron LS, Dimeski B, Beggs PJ, Ferrari BC, Power ML. Molecular epidemiology, spatiotemporal analysis, and ecology of sporadic human cryptosporidiosis in Australia. Appl Environ Microbiol. 2011;77:7757–65.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Nolan MJ, Jex AR, Pangasa A, Young ND, Campbell AJ, Stevens M, et al. Analysis of nucleotide variation within the triose-phosphate isomerase gene of Giardia duodenalis from sheep and its zoonotic implications. Electrophoresis. 2010;31:287–98.View ArticlePubMedGoogle Scholar
  34. Dengjel B, Zahler M, Hermanns W, Heinritzi K, Spillmann T, Thomschke A, et al. Zoonotic potential of Enterocytozoon bieneusi. J Clin Microbiol. 2001;39:4495–9.View ArticlePubMedPubMed CentralGoogle Scholar
  35. Starkey SR, Johnson AL, Ziegler PE, Mohammed HO. An outbreak of cryptosporidiosis among alpaca crias and their human caregivers. J Am Vet Med Assoc. 2007;231:1562–7.View ArticlePubMedGoogle Scholar
  36. Zahedi A, Paparini A, Jian F, Robertson I, Ryan U. Public health significance of zoonotic Cryptosporidium species in wildlife: critical insights into better drinking water management. Int J Parasitol Parasites Wildl. 2016;5:88–109.View ArticlePubMedGoogle Scholar
  37. Li N, Xiao L, Alderisio K, Elwin K, Cebelinski E, Chalmers R, Santin M, et al. Subtyping Cryptosporidium ubiquitum, a zoonotic pathogen emerging in humans. Emerg Infect Dis. 2014;20:217–24.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Koehler AV, Whipp MJ, Haydon SR, Gasser RB. Cryptosporidium cuniculus - new records in human and kangaroo in Australia. Parasit Vectors. 2014;7:492.View ArticlePubMedPubMed CentralGoogle Scholar
  39. Bowman DD. Georgis’ Parasitology for Veterinarians. 10th ed. Philadelphia: Saunders/Elsevier; 2013.Google Scholar
  40. Cacciò SM, Lalle M, Svärd SG. Host specificity in the Giardia duodenalis species complex. Infect Genet Evol. 2017;doi: https://doi.org/10.1016/j.meegid.2017.12.001.
  41. Gomez-Puerta LA, Lopez-Urbina MT, Alarcon V, Cama V, Gonzalez AE, Xiao L. Occurrence of Giardia duodenalis assemblages in alpacas in the Andean region. Parasitol Int. 2014;63:31–4.View ArticlePubMedGoogle Scholar
  42. Minetti C, Taweenan W, Hogg R, Featherstone C, Randle N, Latham S, et al. Occurrence and diversity of Giardia duodenalis assemblages in livestock in the UK. Transbound Emerg Dis. 2014:61–7.Google Scholar
  43. Trout JM, Santin M, Fayer R. Detection of Assemblage A, Giardia duodenalis and Eimeria spp. in alpacas on two Maryland farms. Vet Parasitol. 2008;153:203–8.View ArticlePubMedGoogle Scholar
  44. Burton A, Nydam D, Mitchell K, Dearen T, Bowman D, Xiao L. The molecular epidemiology of Giardia shedding in horses and alpacas in New York State. J Vet Intern Med. 2010;24:783.View ArticleGoogle Scholar
  45. Ey PL, Mansouri M, Kulda J, Nohynkova E, Monis PT, Andrews RH, et al. Genetic analysis of Giardia from hoofed farm animals reveals artiodactyl-specific and potentially zoonotic genotypes. J Eukaryot Microbiol. 1997;44:626–35.View ArticlePubMedGoogle Scholar
  46. Li J, Qi M, Chang Y, Wang R, Li T, Dong H, et al. Molecular characterization of Cryptosporidium spp., Giardia duodenalis, and Enterocytozoon bieneusi in captive wildlife at Zhengzhou Zoo, China. J Eukaryot Microbiol. 2015;62:833–9.View ArticlePubMedGoogle Scholar
  47. Li W, Deng L, Yu X, Zhong Z, Wang Q, Liu X, et al. Multilocus genotypes and broad host-range of Enterocytozoon bieneusi in captive wildlife at zoological gardens in China. Parasit Vectors. 2016;9:395.View ArticlePubMedPubMed CentralGoogle Scholar
  48. Rulofson FC, Atwill ER, Holmberg CA. Fecal shedding of Giardia duodenalis, Cryptosporidium parvum, Salmonella organisms, and Escherichia coli O157: H7 from llamas in California. Am J Vet Res. 2001;62:637–42.View ArticlePubMedGoogle Scholar

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