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Previous Article | Next Article 
Applied and Environmental Microbiology, October 2007, p. 6475-6483, Vol. 73, No. 20
0099-2240/07/$08.00+0 doi:10.1128/AEM.01034-07
Copyright © 2007, American Society for Microbiology. All Rights Reserved.
Kerri A. Alderisio,2
Wenli Yang,1
Lisa A. Blancero,2
William G. Kuhne,2
Christopher A. Nadareski,2
Michael Reid,2 and
Lihua Xiao1*
Division of Parasitic Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia 30341,1 New York City Department of Environmental Protection, Valhalla, New York 105952
Received 9 May 2007/ Accepted 15 August 2007
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ABSTRACT |
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INTRODUCTION |
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In contrast, PCR-based methods have the ability to differentiate Cryptosporidium at the species and genotype level (24). PCR tools also have the capability to assess the human-infective potential and the animal sources of Cryptosporidium oocysts in water, as different animal species are usually infected with different Cryptosporidium species and genotypes, only a few of which are human pathogens (21). Genotyping using PCR-restriction fragment length polymorphism (RFLP) analysis of the small-subunit (SSU) rRNA gene has been used successfully in assessing the source and human-infective potential of Cryptosporidium oocysts found in water (11, 15, 16, 19, 20, 22, 26).
Previous studies conducted by researchers at the Centers for Disease Control and Prevention and the New York City Department of Environmental Protection (NYCDEP) have identified at least 22 Cryptosporidium genotypes in 121 storm water samples from the Ashokan Brook, Malcolm Brook, and the N5 stream of the New York City water supply system (11, 19, 20). Almost all of these Cryptosporidium genotypes belong to those that have not been previously detected in humans or domestic animals. Results of these studies have demonstrated that molecular techniques can complement traditional detection methods by providing information on the source of contamination and human-infective potential of Cryptosporidium oocysts found in water. Several Cryptosporidium spp. were commonly found in these watersheds, including W4 (cervine genotype) from deer, W7 (muskrat genotype I) from muskrats, and the W1 genotype from an unknown animal source. Some genotypes were only found in a particular watershed. Half of the Cryptosporidium genotypes (W1, W3, W5, W6, W12, W15, and W17 to W21) found have not been attributed to known species/groups of animals (11).
In this study, Cryptosporidium spp. in fecal specimens from known wildlife species living in the watershed of the New York City water supply system were detected and genotyped by the same rRNA-based genotyping tool previously used in the analysis of storm water samples (11, 19, 20). The objectives were (i) to assess the role of wildlife in Cryptosporidium contamination in the NYCDEP watershed and to identify the remaining genotypes that could not be tracked to animal sources in the previous studies and (ii) to understand the public health significance of Cryptosporidium spp. from wildlife.
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MATERIALS AND METHODS |
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Samples were collected utilizing a variety of means, including live and lethal trapping, fresh roadkill collections, and fresh fecal collections from bird roosting/feeding/loafing locations. Trap lines were set just prior to sunset and retrieved postdawn using Sherman live traps, lethal snap traps, and body-gripping traps (no. 220 and 330). Sherman traps were set in transect lines along natural or man-made boundaries such as stream corridors, fences, and stone walls, etc. Snap traps were generally placed around NYCDEP facilities. Foot-hold and body-gripping traps, used to trap beaver (Castor Canadensis), were opportunistically placed at NYCDEP-identified nuisance locations on and around the New York City reservoirs. Fish were collected from screen chambers at the reservoir locations.
Roadkill collections were conducted opportunistically during routine surveillance monitoring during predawn, postdusk, and daytime hours. Roadkill mammals were only collected prior to rigor mortis and if specimens were warm to touch, ensuring freshness, and if all viscera remained intact. All avian samples were collected off pavement and grassy surfaces using sterile syringes and plastic forceps. Direct observation of fecal elimination occurred just prior to sampling to ensure species identification and freshness of samples. Fecal samples were collected from roadkill specimens and euthanized mammals either by direct fecal extraction from the anus (externally) or the lower intestinal tract via dissection. All samples were placed in sterile plastic vials, capped, and stored in coolers with ice packs/ice for transport to the laboratory within 48 h of collection.
All specimens were identified to the species level (except Peromyscus), aged, and sexed. Animals sampled included small rodents (mice, shrews, voles, rats, and chipmunks), other rodents and mammals, birds, and fish (Table 1), with most animals being adults. Samples were initially processed in the NYCDEP laboratory, and then pellets were shipped in coolers to the laboratory at the Centers for Disease Control and Prevention for Cryptosporidium detection and genotyping.
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Sequence analysis.
After being purified using Montage PCR filters (Millipore, Bedford, MA), the secondary PCR products were sequenced directly with secondary PCR primers using an ABI BigDye Terminator v. 3.1 cycle sequencing kit (Applied Biosystems, Foster City, CA) and the manufacturer-suggested procedures. Sequences were read on an ABI3130 genetic analyzer (Applied Biosystems). Sequence accuracy was confirmed by two-directional sequencing and sequencing of at least two PCR products from each positive specimen. Nucleotide sequences obtained were aligned with reference Cryptosporidium sequences using the ClustalX 1.81 package (ftp://ftp-igbmc.u-strasbg.fr/pub/ClustalX/) and the default setting. Phylogenetic analysis was carried out to assess the relationship between parasites in animals and known Cryptosporidium spp. Neighbor-joining trees were constructed using the TreeCon package (http://www.psb.rug.ac.be/bioinformatics/psb/Userman/treeconw.html), based on the evolutionary distances calculated by the Kimura two-parameter model. An SSU rRNA sequence of Eimeria tenella (GenBank accession no. AF026388) was used as the outgroup. The reliability of various clusters was evaluated by the bootstrap method with 1,000 replicates.
Nucleotide sequence accession numbers.
Unique partial SSU rRNA sequences obtained from wildlife during the study were deposited in the GenBank database under accession numbers EF641009 to EF641030, EU096237, and EU096238.
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RESULTS |
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Prevalence of Cryptosporidium genotypes in wildlife.
Cryptosporidium spp. were detected in 111 (20.5%) studied animals (Table 1). Most of the positive animals (101/111) were mammals, with only 10 from birds and none from fish. Within mammals, rodents had the highest prevalence of Cryptosporidium, with a prevalence of 32.8%. Most of the high Cryptosporidium prevalence in rodents was attributable to the high infection rate in the well-sampled deer mice (57/177 or 32.2%), even though high prevalence (37.5%) of Cryptosporidium was also seen in the squirrel family (18/48) (Table 1). The only ruminants studied, the white-tailed deer, had a much lower infection rate (5/59 or 8.5%).
Cryptosporidium genotypes in wildlife.
All PCR products were digested with restriction enzymes SspI and VspI to differentiate Cryptosporidium spp. in wildlife. Multiple banding patterns were seen for both SspI and VspI. The combination of SspI and VspI RFLP identified at least 10 restriction patterns, with most of them not previously seen in humans and domestic animals (data not shown). PCR products of all positive specimens were sequenced at least twice to identify Cryptosporidium genotypes. Altogether, 21 Cryptosporidium genotypes were identified in New York wildlife. They included 11 of the 22 Cryptosporidium genotypes previously found in storm water in the NYCDEP watershed: W1, W3, W4, W5, W7, W9, W13, W15, W16, W17, and W18. Previously, animal sources for six of the Cryptosporidium genotypes in storm water were not known (11, 19): W1 (deer mouse genotype III) from deer mice and eastern gray squirrels; W3 (deer mouse genotype IV) from deer mice; W5 (shrew genotype) from northern short-tailed shrews and one ermine; W15 (vole genotype) from a meadow vole; W17 (chipmunk genotype I) from one chipmunk, eastern gray squirrel, and deer mouse each; and W18 from one ermine. The known animal hosts for four of the storm water genotypes were expanded, with W4 (cervine genotype) seen in three eastern gray squirrels, two eastern chipmunks, two beavers, and one each of the red squirrel, woodchuck, deer mouse, and raccoon. These are in addition to known W4 hosts from previous studies such as deer, sheep, mouflon sheep, blesboks, nyalas, lemurs, and humans. W7 (muskrat genotype I) was seen in four boreal red-backed voles in addition to muskrats, W13 (skunk genotype) was seen in one eastern gray squirrel, river otter, and Virginia opossum each, in addition to skunks and raccoons, and W16 was seen in two meadow voles in addition to muskrats (Table 2). Six established Cryptosporidium genotypes previously not seen in New York City watershed storm water were found in wildlife in this study, including goose genotypes I and II from Canada geese, a deer mouse genotype (renamed deer mouse genotype I in this study) from deer mice, Cryptosporidium parvum in an eastern gray squirrel, Cryptosporidium meleagridis in a deer mouse, and Cryptosporidium muris in an eastern gray squirrel. In addition, four new Cryptosporidium genotypes were found in this study, including the mink genotype in a mink, beaver genotype in a beaver, deer mouse genotype II in deer mice, and chipmunk genotype II in an eastern chipmunk (Table 2).
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DISCUSSION |
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Of the 21 Cryptosporidium genotypes found in wildlife in the NYCDEP watershed, 19 of them were intestinal. The finding of the only gastric species in this study, C. muris, in only one animal is surprising, especially when one considers the fact that a large number of several species of rodents was sampled. The result is nevertheless in agreement with the previous finding of Cryptosporidium genotypes in storm runoff samples collected from the same watershed, where 20 of the 22 Cryptosporidium genotypes were intestinal (11, 19). One Cryptosporidium genotype previously found in a storm water sample from the watershed, W21, clustered outside the known intestinal and gastric Cryptosporidium species/genotypes, even though a BLAST search of the GenBank database clearly established its identity of Cryptosporidium (11). Interestingly, the chipmunk genotype II found in this study had high sequence homology to the W21 genotype at the 3' and 5' ends of the SSU rRNA gene and formed a cluster together outside the intestinal and gastric Cryptosporidium species/genotypes (Fig. 2). The biological uniqueness of these two Cryptosporidium genotypes warrants further studies.
Results of this study support the previous conclusion that most Cryptosporidium spp. from wildlife are host adapted in nature (25, 27-29). Thus, most Cryptosporidium genotypes in this study were found in a few related animals, such as deer mouse genotypes I, II, and IV (W3) in deer mice, muskrat genotypes I (W7) and II (W16) in muskrats and voles, a deer genotype (W9) in deer, a vole genotype (W15) in voles, chipmunk genotype I (W17) in chipmunks and squirrels, and goose genotypes I and II in Canada geese. Results of phylogenetic analysis also support the suggestion of host adaptation and parasite-host coevolution of Cryptosporidium spp., because some related animal species have related Cryptosporidium genotypes. For example, it was previously shown that (i) opossum genotype I in Virginia opossum (the American marsupial) is related to but distinct from the marsupial genotype I seen in kangaroos and koalas in Australia; (ii) the monkey genotype has only minor sequence differences from C. hominis seen in humans; (iii) the ruminant parasites deer genotypes (in deer), deer-like genotype (in cattle), and Cryptosporidium bovis (in cattle and sheep) are related to each other; and (iv) distinct C. canis genotypes are seen in dogs, coyotes, and foxes (27) (Fig. 2). In this study, the newly found mink genotype is related to the ferret genotype with only minor sequence differences (with 5 bp of substitutions and 3 bp of deletions), and they cluster together in the phylogenetic tree (Fig. 2). Minor differences are present between muskrats and voles in the sequences of muskrat genotype I or II. The C. muris sequence obtained from an eastern gray squirrel had small differences from sequences obtained previously from other rodents and mammals. In some hosts, even though multiple genotypes are present, these Cryptosporidium genotypes are related to each other, such as deer genotypes I and II in deer mice, goose genotypes I and II in Canada geese, and the various squirrel genotypes seen in squirrels in California (Fig. 2).
Whether deer mouse genotypes I and II are two true Cryptosporidium genotypes remains to be determined. Even though there is greater than 1% difference between these two types of sequences, which is above the extent of difference among many established Cryptosporidium species, a few deer mouse genotype I sequences were also seen in animals with deer mouse genotype II. In fact, many PCR products of genotype I were difficult to sequence. It was previously shown that some Cryptosporidium spp. such as C. felis and marsupial genotype I have very different copies of the SSU rRNA gene, which is responsible for the existence of mixed RFLP profiles and difficulties in sequencing some PCR products (23). In this study, the existence of heterogeneous copies of the SSU rRNA gene was also seen in the multiple products in one specimen each of C. parvum, cervine genotype (W4), and muskrat genotype I (W7), even though the sequence differences were all minor. It is possible that at least some of the divergent Cryptosporidium sequences obtained from squirrels in California (2) were from heterogeneous copies of the SSU rRNA gene. In contrast, the goose genotypes I and II were usually seen in different specimens from Canada geese (29).
Interestingly, the only ermine specimen examined in the study produced both W5 and W18 sequences in repeated analyses. Because the sequence differences (eight or nine nucleotide changes) between W5 and W18 are restricted to the hypervariable region of the gene (Fig. 1), both types of sequences were found in the same animal, and phylogenetically they clustered together (Fig. 2), it is very possible that W5 and W18 represent sequences from heterogeneous copies of the rRNA gene of the same Cryptosporidium genotype (shrew genotype). Whether W6 is in fact also the shrew genotype (W5) remains to be determined, as it is also phylogenetically related to W5 and W18 and differs from W5 and W18 only in the hypervariable regions of the SSU rRNA gene (Fig. 1 and Fig. 2). It also remains to be determined whether the shrew genotype (of W5 and W18 sequences) is a true parasite of ermines, as its finding in the one ermine could be from an infected rodent ingested by the animal.
As expected, the host specificity of Cryptosporidium spp. is not strict and there are apparent exceptions to the hypothesis of host adaptation. The most noticeable example is the cervine genotype (W4), which was found in this study in multiple species of rodents (beaver, eastern gray squirrel, red squirrel, chipmunk, and woodchuck) as well as in a raccoon. Previously, it was also found in various ruminants (white-tailed deer, sheep, mouflon sheep, blesbok, and nyala) and primates (human and lemur) (Table 2). The generalist nature of the host specificity of the parasite and habitat sharing are probably responsible for the wide occurrence of the cervine genotype in animals. The cervine genotype was the most common and the only year-round Cryptosporidium in storm water in the NYCDEP watershed (11, 19, 20). A few other Cryptosporidium species/genotypes also had more-broad host specificity; the deer mouse genotype III (W1) was found in a few eastern gray squirrels in addition to deer mice, the skunk genotype was found in one striped skunk, one squirrel, one opossum, and one river otter, and C. parvum was found in one eastern gray squirrel. The latter is now generally considered mostly a parasite of ruminants and humans, but it has been found occasionally in a few other species of animals such as horses, mice, raccoons, and dogs (21). Thus in the NYCDEP watershed, interspecies transmission of Cryptosporidium mostly occurs in the cervine genotype.
Among the 21 Cryptosporidium genotypes found in this study, only C. parvum, C. meleagridis, C. muris, cervine (W4), and chipmunk I (W17) genotypes have been found in humans. The former three were each found in only one animal and there were minor SSU rRNA sequence differences in C. parvum and C. muris between eastern gray squirrels and humans (one or two nucleotide changes depending on the copies of the gene for C. parvum, and one nucleotide substitution and four nucleotide insertions/deletions for C. muris). Even though the cervine genotype was commonly seen in many animals and in storm water, this Cryptosporidium sp. has been found in only a few human cases around the world (24). Likewise, the chipmunk genotype I has only been reported in two persons in Wisconsin (7). Thus, wildlife in the NYCDEP watershed is unlikely to be a major contributor of human-pathogenic Cryptosporidium spp. in the source water. A similar conclusion was previously made regarding Cryptosporidium spp. in reptiles and Canada geese and in aquatic mammals in the watershed in Maryland (25, 28, 29). This is in contrast to previous suggestions by others (3, 4, 14). The latter, however, was mostly based on the erroneous assumption that C. parvum commonly infects various species of mammals and on dated nomenclature for Cryptosporidium species and genotypes. Even though most Cryptosporidium genotypes in wildlife in this study were grouped in phylogenetic analysis in the cluster containing Cryptosporidium types infectious to humans, one should not conclude that all genotypes within that cluster are infectious to humans. In fact, there are many species and genotypes within this cluster that have never been found in humans. It is likely that only very subtle genetic differences are required to change host specificity; therefore, genotypes can be very similar yet not infect the same hosts.
Results of this study demonstrate that genotyping tools could provide information on the host specificity and the human-infective potential of Cryptosporidium oocysts in wildlife and on the animal source of contamination in water. Wildlife may contribute to Cryptosporidium contamination in the water but may not have major public health significance because they are generally infected with non-human-pathogenic species and genotypes. Nevertheless, watershed protection programs should attempt to control pathogen inputs from wildlife in addition to anthropogenic and agricultural sources, and more attention should be directed to studying the transport of pathogens from wildlife to water and to monitoring pathogens in watersheds deemed protected or pristine.
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ACKNOWLEDGMENTS |
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We thank Tom Baudanza of NYCDEP and Robert Stranges of HDR, P.C., for sampling support and Don Culjack, Alex Maestri, and Deb Schwarz for technical support.
The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.
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FOOTNOTES |
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Published ahead of print on 24 August 2007.
Present address: Institute for Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai 200025, China.
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