Background

One of the toughest challenges facing the world’s supply of clean drinking water is contamination from faeces and soil [1, 2]. Diarrhoeal disease is responsible for 10.5 % of deaths in children of less than five years of age [3–5], having a greater impact than malaria and HIV/AIDS combined [5]. Pathogens of concern include viruses, bacteria and protists [1]. Of the latter pathogen group, human-infective taxa (i.e. species and genotypes/assemblages) of Cryptosporidium and Giardia are highly significant [1, 4–8]. Cryptosporidium and Giardia are unique in that very small numbers of infective stages (oocysts and cysts, respectively) can cause disease in humans [9, 10] and that these stages are resistant to chlorination and other common water treatments [1, 11]. An example of the tremendous impact these parasites can have was demonstrated in 1993, with a major outbreak of cryptosporidiosis in Milwaukee, USA [12], which affected more than 400,000 people and resulted in 100 deaths. This case emphasizes the major public health importance of waterborne diseases and the need for their sustained prevention.

Melbourne (Victoria, Australia; population ~4 million) is one of the few cities in the world that receives largely unfiltered drinking water from protected wilderness catchment areas. The management of Melbourne’s ten main water catchment areas includes restricted access for humans, long water retention times and an intense program of testing and monitoring for pathogens in source water. These catchments represent habitat for native and feral animals, such that the monitoring of zoonotic pathogens is central to management and the prevention of outbreaks of waterborne disease. In 2008, we initiated a program to monitor Cryptosporidium and Giardia in faecal samples from various mammals and birds in the Melbourne’s catchments [13]. To do this, we collected 2,009 fresh faecal samples (from June 2009 to June 2011) and tested them using an established and validated PCR-based mutation scanning-coupled sequencing approach (cf. [14–16]), combined with phylogenetic analyses of loci (SSU and gp60) in the small subunit (SSU) of ribosomal RNA and 60-kDa glycoprotein (gp60) genes to detect and characterise Cryptosporidium, and another locus (tpi) in the triose-phosphate isomerase (tpi) gene to identify and classify Giardia [13]. In total, Cryptosporidium and Giardia were detected in 2.8 and 3.4 % of all 2009 samples tested, respectively, and 35 previously undescribed genotypes were reported [13]. In spite of this relatively low prevalence, the findings from this study emphasized a need for a sustained program.

Therefore, from July 2011 to November 2015, we extended our monitoring program, and genetically characterised Cryptosporidium and Giardia from native and introduced animals in Melbourne’s water catchments, in order to continually assess the prevalence and diversity of Cryptosporidium and Giardia taxa, evaluate their host affiliations, geographical distributions and zoonotic potential, and support catchment management. In the present article, we describe the results from this 4-year study and discuss the findings in a water industry context.

Methods

Melbourne’s catchments

Greater Melbourne sources its municipal drinking water from ten main water catchment reservoirs. Approximately 80 % of Melbourne’s drinking water is drawn from ‘closed’ catchments in the Yarra Ranges (~85 km east of Melbourne), which cover 157,000 hectares of eucalypt forest, with restricted human and domestic animal access, to minimise the risk of waterborne diseases. The remaining 20 % of Melbourne’s water comes from ‘open’ catchments, in which some farming and human activities are permitted. All water undergoes treatment in accordance with national and international guidelines [17, 18]. The nine reservoirs studied here (Fig. 1) are located north and east of Melbourne’s central business district (CBD), are less than 90 km apart and include: Cardinia (CA) 37°47'S, 145°24'E; Greenvale (GV) 37°37'S, 144°54'E; Maroondah (MR) 37°38'S, 145°33'E; O’Shannassy (OS) 37°40'S, 145°48'E; Silvan (SV) 37°50'S, 145°25’E; Tarago (TAR) 37°59'S, 145°55’E; Thompson (TH) 37°47'S, 146°21'E; Upper Yarra (UY) 37°40'S, 145°55'E; and Yan Yean (YY) 37°33'S, 145°08'E. Reservoirs MR, OS, TH and UY are situated in the densely forested Yarra Ranges catchment, whereas YY reservoir is a much smaller catchment north of the CBD and surrounded by residential and grazing land. The remaining reservoirs, including CA, GV and SV, act as storage facilities for the larger catchments and have eucalypt and/or pine forests. TAR is the one ‘open’ water supply catchment, which permits farming in the land surrounding the reservoir. All regions have small areas of grassland adjacent to water reservoirs, and it is here that faecal samples were collected.

Fig. 1
figure 1

Map of the Melbourne Water catchment areas from where the 4,256 faecal samples from animals were collected

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Samples and isolation of genomic DNA

A total of 4,256 faecal deposits from Canis familiaris (dog), Vulpes vulpes (fox), Felis catus (cat), Dromaius novaehollandiae (emu), Wallabia bicolor (swamp wallaby), Macropus giganteus (Eastern grey kangaroo), Trichosurus vulpecula (common brushtail possum), Oryctolagus cuniculus (rabbit), Rattus lutreolus (swamp rat), Rattus fuscipes (bush rat) and Vombatus ursinus (common wombat), together with waterbirds, principally the Australian wood duck (Chenonetta jubata), and deer, including Rusa unicolour (sambar), Cervus elaphus (red) and Dama dama (fallow), and samples of unknown host origin were collected from nine locations from July 2011 to November 2015 (see Additional file 1: Table S1). Specifically, samples were collected from CA (n = 718), GV (n = 638), MR (n = 344), OS (n = 622); SV (n = 527), TAR (n = 61), TH (n = 31), UY (n = 714) and YY (n = 601). Scats were identified using a field guide [19], and host identity was confirmed, as required, by PCR-based sequencing of a region of the mitochondrial cytochrome b gene from faecal DNA using a similar approach to that described by Dalen et al. [20]. Genomic DNA was extracted directly from 0.25 g of faeces using the PowerSoil kit (MoBio, USA), according to the manufacturer’s instructions.

Polymerase chain reaction (PCR) amplification of genetic loci

Genomic DNA samples were subjected to nested PCR-based analyses of three loci. For the specific identification of Cryptosporidium, a portion of the SSU gene (~240 bp) was used [13], and genotypic/subgenotypic classification was achieved employing part of the gp60 gene (250–350 bp) [13]. For the genetic characterisation of Giardia (to the level of assemblage), a portion of the tpi gene (~530 bp) was employed [26]. Primary amplification of gp60 utilised the cycling protocol, 94 °C for 5 min (initial denaturation), followed by 35 cycles of 94 °C for 30 s (denaturation), 55 °C for 45 s (annealing) and 72 °C for 1 min (extension), with a final extension of 72 °C for 10 min. For the amplification of gp60, we employed 94 °C for 5 min, followed by 30 cycles of 94 °C for 30 s, 55 °C for 30 s, and 72 °C for 30 s, with a final extension at 72 °C for 10 min.

For some samples, Cryptosporidium was further characterized using a longer region (~850 bp) of the gp60 gene. This region was PCR-amplified using primers AL3531 (forward: 5'-ATA GTC TCC GCT GTA TTC-3') and AL3535 (reverse: 5'-GGA AGG AAC GAT GTA TCT-3'), followed by a nested amplification using primers AL3532 (forward: 5'-TCC GCT GTA TTC TCA GCC-3') and AL3534 (reverse: 5'-GCA GAG GAA CCA GCA TC-3') [27]. For both amplifications, the following cycling protocol was used: 94 °C for 5 min (initial denaturation), followed by 35 cycles of 94 °C for 45 s (denaturation), 50 °C for 45 s (annealing) and 72 °C for 60 s (extension), with a final extension of 72 °C for 10 min.

For Giardia, the tpi locus was amplified using primers AL3543 (forward: 5'-AAA TTA TGC CTG CTC GTC G-3') and AL3546 (reverse: 5'-CAA ACC TTT TCC GCA AAC C-3’), followed by the nested amplification of tpi employing primers AL3544 (forward: 5'-CCC TTC ATC GGT GGT AAC TT-3') and AL3545 (reverse: 5'-GTG GCC ACC ACT CCC GTG CC-3') [21]. For the primary amplification, the cycling protocol was 94 °C for 5 min (initial denaturation), followed by 35 cycles of 94 °C for 45 s (denaturation), 50 °C for 45 s (annealing), and 72 °C for 1 min (extension) and a final extension of 72 °C for 10 min. Secondary amplification of tpi was achieved employing 94 °C for 5 min, followed by 35 cycles of 94 °C for 45 s, 55 °C for 30 s, and 72 °C for 1 min, with a final extension at 72 °C for 10 min.

Mutation scanning, sequencing and phylogenetic analyses

Single-strand conformation polymorphism (SSCP) analysis was used to scan for sequence variation within and among SSU and gp60 amplicons (e.g. [13, 16]). In brief, 1 μl of each secondary amplicon (< 450 bp) was mixed with 5 μl of DNA sequencing-stop solution (Promega) and 5 μl of H20, heat-denatured at 94 °C/30 min, snap-cooled on a freeze-block (-20 °C) and then subjected to electrophoresis at 74 V at 7.4 °C (constant) for 16 h in a GMA Wide Mini S-2x25 gel in a SEA 2000 rig (Elchrom Scientific AG) using TAE buffer (40 mM Tris base, 20 mM acetic acid, 1.0 mM EDTA, Bio-Rad, USA). A control sample (representing a known genotype) was included on each gel to ensure the reproducibility of profiles representing this sample among gels.

Following SSCP-based analysis, selected amplicons representing each distinct electrophoretic profile and all SSU, gp60 (Cryptosporidium) and tpi (Giardia) amplicons were treated with shrimp alkaline phosphatase and exonuclease I (ThermoFisher, Waltham, USA), according to the manufacturer’s instructions, and then subjected to bi-directional automated sequencing (BigDye® Terminator v.3.1 chemistry, Applied Biosystems, USA) using the same primers employed in the secondary PCR. Sequence quality was verified by comparison with corresponding electropherograms using the program Geneious v.8 [28]. Sequences were aligned using the program MUSCLE [29], and alignments were adjusted manually using the program Mesquite v.2.75 [30]. Sequences were then compared with those available in the GenBank database using BLASTn.

Phylogenetic analysis of sequence data was conducted by Bayesian inference (BI) using Monte Carlo Markov Chain (MCMC) analysis in MrBayes v.3.2.3 [31]. The likelihood parameters set for BI analysis of SSU data were based on the Akaike Information Criteria (AIC) test in jModeltest v.2.1.7 [32]. For SSU (Cryptosporidium) and tpi (Giardia) data, the number of substitutions (Nst) was set at 6, with a gamma-distribution and a proportion of invariable sites. For the separate analyses of gp60 (Cryptosporidium) sequence data, the Nst was set at 6, with an equal rate among sites. Posterior probability (pp) values were calculated by running 2,000,000 generations with four simultaneous tree-building chains. Trees were saved every 100th generation. At the end of each run, the standard deviation of split frequencies was < 0.01, and the potential scale reduction factor approached one. A 50 % majority rule consensus tree for each analysis was constructed based on the final 75 % of trees generated by BI. Analyses were run three times to ensure convergence and insensitivity to priors. Outgroups used in the analyses were Giardia muris for G. duodenalis (tpi), C. hominis for gp60 and C. muris for SSU.

Results

Molecular detection of Cryptosporidium, and taxon identity based on SSU

We conducted mutation scanning and sequence analyses of all amplicons (n = 69) produced from 4,256 (1.62 %) faecal DNA samples and identified them to species and/or genotype of Cryptosporidium. A total of 64 samples were characterised by their SSU sequences; 52 were assigned GenBank accession nos. (KU531647–KU531698; Tables 1 and 2), of which 24 sequences were selected as representatives for phylogenetic analysis (Fig. 2; Additional file 2: Table S4). In total, there were 12 novel sequences (i.e. < 100 % identity with a sequence on GenBank) for SSU. Samples that were test-positive for SSU were assessed according to catchment (Additional file 1: Table S2) and host (Additional file 1: Table S3). Overall, prevalence was assessed by catchment in Table 2.

Table 1 Summary of epidemiological and molecular information pertaining to the pathogen test-positive faecal samples collected from the Melbourne Water catchments (July 2011 to November 2015)
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Table 2 The total numbers of each host sampled in each catchment, as part of the Melbourne Water Corporation sampling program for waterborne pathogens (July 2011 to November 2015), together with the numbers of animals PCR test-positive for species/genotypes of Cryptosporidium (number of test-positive samples)
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Fig. 2
figure 2

Relationships among Cryptosporidium taxa inferred from the phylogenetic analysis of partial small subunit ribosomal RNA gene (SSU) sequence data by Bayesian inference (BI). Posterior probabilities are indicated at all major nodes. Bold-type indicates Cryptosporidium species or genotypes characterized from faecal DNA samples in this study. In parentheses are the numbers of samples representing a particular species, genotype and sequence (GenBank accession numbers indicated). Novel genotypes (*). Scale-bar represents the number of substitutions per site

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In the following list, we assign individual taxa identified in the present study (based on the sequencing of SSU) to the most closely related species of Cryptosporidium in particular clades based on sequence identity:

  • Members of the C. fayeri clade:

    Six of 74 (8.10 %, catchment MR) samples from wallabies were test-positive for C. fayeri. Two of 287 (0.70 %, YY) and one of 603 (0.17 %, GV) samples from kangaroos were test-positive for Cryptosporidium sp. EGK1 (eastern grey kangaroo type 1), two of which were novel genotypes (GenBank accession nos. KU531656 and KU531666). One of 76 (1.32 %) samples from wallabies from catchment CA was a novel genotype that was similar to C. fayeri (KU531658). One of the 287 (0.35 %) samples from kangaroos from catchment YY was a novel genotype similar to Cryptosporidium sp. kangaroo genotype I (KU531694). For the first time, C. fayeri and C. fayeri-like genotypes were reported from wombats.

  • Members of the C. hominis, C. parvum and C. cuniculus clade:

    One of 536 (0.19 %, UY) and one of 408 (0.25 %, OS) from deer were test-positive for C. hominis. One of 603 (0.17 %) samples from a kangaroo from catchment GV was test-positive for C. parvum. Five of 26 (19.2 %, GV), one of eight (12.5 %, SV) samples and one of 287 (0.35 %, YY) samples from rabbits were test-positive for C. cuniculus.

  • Members of the C. canis clade:

    One of 52 (1.92 %) samples from emus from catchment CA was test-positive for C. canis.

  • Members of the C. suis clade:

    One of 536 (0.19 %) samples from deer from catchment UY was test-positive for the novel C. suis-like genotype (KU531660).

  • Members of the C. ubiquitum clade:

    Two of 408 (0.49 %) and one of 247 (0.40 %) samples from deer from catchments OS and CA, respectively, were test-positive for C. ubiquitum. Two samples from wombats were test-positive for a novel C. ubiquitum-like genotype.

  • Members of the C. macropodum clade:

    Twelve of 603 (1.99 %) and one of 287 (0.35 %) of kangaroos from GV and YY, respectively, were test-positive for C. macropodum. Four of 53 (7.55 %) samples from wallabies from catchment OS were test-positive for C. macropodum-like genotypes, three of which were novel (KU531649, KU531661 and KU531679). One of 168 (0.60 %) samples from wallabies from catchment SV were test-positive for a C. macropodum-like genotype.

  • Members of the Cryptosporidium sp. duck genotype clade:

    Two novel genotypes were identified from three of 55 (5.45 %) samples from waterbirds from catchment UY (KU531654 and KU531689).

  • Members of the C. ryanae clade:

    Two of 536 (0.37 %) and one of 250 (0.40 %) samples from deer were test-positive for Cryptosporidium sp. deer genotype from the catchments UY and YY, respectively. One of 536 (0.19 %, UY), two of 408 (0.49 %, OS), two of 247 (0.81 %, CA) and one of 250 (0.40 %, YY) samples from deer were test-positive for the C. ryanae-like MW4 genotype. Two of 408 (0.49 %) samples from deer from catchment OS were test-positive for the novel genotype C. ryanae-like MW7 (KU531650). Two of 408 (0.49 %, OS) and one of 247 (0.40 %, CA) samples from deer were test-positive for the C. ryanae-like MW2 genotype.

Cryptosporidium subgenotypes based on gp60

All ten samples test-positive in PCR for gp60 (n = 10) were characterised to the level of subgenotype, and seven of them were assigned GenBank accession nos. (KU531699–KU531705). Based on a comparison with reference sequences from GenBank, six unique gp60 sequence types were characterised as C. hominis (genotype Ib - subgenotype IbA10G2), and C. cuniculus (genotype Vb - subgenotype VbA25 and VbA26) (Fig. 3; Table 1 and Additional file 2: Table S5). One of 74 (1.35 %) samples from wallabies from catchment MR was test-positive for C. hominis IbA10G2 (accession no. KJ506839). In addition, Cryptosporidium cuniculus subgenotypes VbA25 and VbA26 were identified in seven samples from rabbits from catchments GV, YY, SV and MR, four of which were novel. Cryptosporidium cuniculus (VbA26) was identified in two samples from kangaroos from catchment YY (cf. [33]).

Fig. 3
figure 3

Relationships among Cryptosporidium taxa inferred from the phylogenetic analysis of partial 60 kDa glycoprotein gene (gp60) sequence data by Bayesian inference (BI). Posterior probabilities are indicated at all major nodes. Bold-type indicates Cryptosporidium species or genotypes characterized from faecal DNA samples in this study. In parentheses are the numbers of samples representing a particular species, genotype and sequence (GenBank accession numbers indicated). Novel genotypes (*). Scale-bar represents the number of substitutions per site

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Giardia species and assemblages

Sequencing of all tpi amplicons identified 13 of 4,256 (0.31 %) individual faecal samples to contain Giardia representing the genetic assemblage A of G. duodenalis, based on direct sequence comparisons. From the 13 samples, we defined three distinct sequence types for tpi (represented by GenBank accession nos. KU531706–KU531718; Fig. 4; Tables 1 and 3 and Additional file 2: Table S6). Giardia sub-assemblage AI was identified in samples from a rabbit and a deer in catchment TH, a wombat in catchment MR and a kangaroo in catchment SV. The genotype (sequence type) of Giardia from deer identified here was novel. Giardia sub-assemblage AIII was identified in nine samples from deer, including five of 536 (0.93 %, UY), two of 408 (0.49 %, OS) and two of 18 (11.1 %, TAR) samples from three different catchments.

Fig. 4
figure 4

Relationships among Giardia taxa inferred from the phylogenetic analysis of partial triose-phosphate isomerase gene (tpi) sequence data by Bayesian inference (BI). Posterior probabilities are indicated at all major nodes. Bold-type indicates Cryptosporidium species or genotypes characterized from faecal DNA samples in this study. In parentheses are the numbers of samples representing a particular species, genotype and sequence (GenBank accession numbers indicated). Novel genotypes (*). Scale-bar represents the number of substitutions per site

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Table 3 The total numbers of samples from individual host animals for each catchment, as part of the Melbourne Water Corporation sampling program for waterborne pathogens (July 2011 to November 2015), together with the numbers of animals PCR test-positive for species/genotypes of Giardia (number of test-positive samples)
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Discussion

Extending our initial monitoring program [13], the present study provides a unique perspective of the epidemiology of zoonotic protists found in wildlife inhabiting the water catchment areas of a major metropolitan city (Melbourne). Worldwide, there have been very few comprehensive wildlife surveys in catchments or watershed, with a few notable exceptions (e.g. [58]. It is plausible that C. canis (0.02 %) and C. fayeri (0.26 %) might also represent minor risks to humans; C. canis has been detected in humans around the world [76]. All of the three genetic variants of tpi detected herein represented assemblage A; two have been reported previously (e.g. GenBank accession nos. KU531708 and KU531707) (cf. [13]), and one is novel (accession no. KU531709). Since assemblages A and B of G. duodenalis appear to represent the greatest zoonotic risk, given their presence in humans, livestock and companion animals [71, 72, 74, 77], studying genetic variability within/among Giardia isolates is pivotal to inferring the zoonotic potential of distinct genotypes within this genus of parasite.

Conclusions

The present study has provided detailed insights into the taxa of Cryptosporidium and Giardia in animals in key water catchments in Victoria. The genetic analyses indicated that 1.92 % of the 4,256 faecal samples contained Cryptosporidium or Giardia that matched species, genotypes or assemblages with the potential to infect humans. In addition, a number of new sequence records, which did not match any previously published genotypes, were identified. As nothing is known about the zoonotic potential of these new variants of Cryptosporidium and Giardia, future work should establish whether they are found in humans in Australia. Although the focus of the present study was on vast water catchment areas in south-eastern Australia, the research findings and the approach taken have considerable implications for other protected wilderness catchment areas around the world that supply unfiltered drinking water to millions of people.

Abbreviations

AIC, Akaike information criteria; BI, Bayesian inference; gp60, 60 kDa glycoprotein gene; MCMC, Monte Carlo Markov Chain; ORF, open reading frame; pp, posterior probability; SSCP, single-strand confirmation polymorphism; SSU, small subunit of ribosomal RNA; tpi, triose-phosphate isomerase gene