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\begin{document}

\title{Screening of Blood Parasites in Australian Wild Deer}



\author[1]{Jose Huaman}%
\author[2]{Carlo Pacioni}%
\author[3]{David Forsyth}%
\author[4]{Anthony Pople}%
\author[5]{Jordan Hampton}%
\author[1]{Karla Helbig}%
\author[1]{Teresa Carvalho}%
\affil[1]{La Trobe University}%
\affil[2]{Arthur Rylah Institute for Environmental Research}%
\affil[3]{NSW Department of Primary Industries}%
\affil[4]{Queensland Department of Agriculture and Fisheries}%
\affil[5]{Ecotone Wildlife}%


\vspace{-1em}



  
  \date{May 05, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Wild animals are natural reservoir hosts for a variety of pathogens, and
such is the case for deer (family Cervidae). Deer were introduced to
Australia 150 years ago for farming and game, but wild deer populations
have expanded considerably in recent years, posing increasing threats to
biodiversity, agriculture and public health. There are few data
currently available on pathogens that Australian wild deer carry or
whether these organisms pose biosecurity threats to humans, wildlife,
livestock or other domestic animals. To address this knowledge gap, we
tested for the presence of seven parasitic genera in 243 blood samples
collected from four wild deer species in eastern Australia. Blood
samples were tested by PCR for the presence of Plasmodium, Trypanosoma,
Babesia, Theileria, Toxoplasma, Sarcocystis and Neospora DNA. No
amplification was obtained for either the 18S rRNA (or the cytochrome b
gene in the case of Plasmodium) of the seven selected parasitic genera,
suggesting that wild deer in eastern Australia currently pose little
risk as vectors of these parasites to livestock and humans. This survey
represents the first molecular study of its type in Australian deer and
provides important baseline information about the health status of these
animals.%
\end{abstract}%



\sloppy


\textbf{Screening of Blood Parasites in Australian Wild Deer}

Running Title: Blood parasites in Australian wild deer

Jose L. Huaman\textsuperscript{1, 2}, Carlo Pacioni\textsuperscript{3,
4}, David M. Forsyth\textsuperscript{5}, Anthony
Pople\textsuperscript{6}, Jordan O. Hampton\textsuperscript{4,7}, Karla
J. Helbig\textsuperscript{2} and Teresa G. Carvalho\textsuperscript{1,
*}

\textsuperscript{1} Molecular Parasitology Laboratory, Department of
Physiology, Anatomy and Microbiology, School of Life Sciences, La Trobe
University, Melbourne, Victoria, Australia.

\textsuperscript{2} Molecular Virology Laboratory, Department of
Physiology, Anatomy and Microbiology, School of Life Sciences, La Trobe
University, Melbourne, Victoria, Australia.

\textsuperscript{3} Arthur Rylah Institute for Environmental Research,
Department of Environment, Land, Water and Planning, Heidelberg,
Victoria, Australia.

\textsuperscript{4} School of Veterinary and Life Sciences, Murdoch
University, South Street, Murdoch, Western Australia, Australia.

\textsuperscript{5} Vertebrate Pest Research Unit, NSW Department of
Primary Industries, Orange, New South Wales, Australia.

\textsuperscript{6} Invasive Plants \& Animals Research, Biosecurity
Queensland, Department of Agriculture and Fisheries, Ecosciences
Precinct, Brisbane, Queensland, Australia.

\textsuperscript{7} Ecotone Wildlife, PO Box 76, Inverloch Victoria,
Australia

* Correspondence: t.carvalho@latrobe.edu.au

\textbf{ORCID ID:}

JLH: 0000-0003-1321-887X

CP: 0000-0001-5115-4120

DMF: 0000-0001-5356-9573

AP:

JOH: 0000-0003-0472-3241

KJH: 0000-0001-6306-2821

TGC: 0000-0002-4947-371X

\textbf{Summary}

Wild animals are natural reservoir hosts for a variety of pathogens, and
such is the case for deer (family Cervidae). Deer were introduced to
Australia 150 years ago for farming and game, but wild deer populations
have expanded considerably in recent years, posing increasing threats to
biodiversity, agriculture and public health. There are few data
currently available on pathogens that Australian wild deer carry or
whether these organisms pose biosecurity threats to humans, wildlife,
livestock or other domestic animals. To address this knowledge gap, we
tested for the presence of seven parasitic genera in 243 blood samples
collected from four wild deer species in eastern Australia. Blood
samples were tested by PCR for the presence of \emph{Plasmodium}
,\emph{Trypanosoma} , \emph{Babesia} , \emph{Theileria} ,
\emph{Toxoplasma} ,\emph{Sarcocystis} and \emph{Neospora} DNA. No
amplification was obtained for either the 18S rRNA (or the cytochrome b
gene in the case of \emph{Plasmodium} ) of the seven selected parasitic
genera, suggesting that wild deer in eastern Australia currently pose
little risk as vectors of these parasites to livestock and humans. This
survey represents the first molecular study of its type in Australian
deer and provides important baseline information about the health status
of these animals.

\textbf{Keywords}

Wildlife disease, surveillance, wild deer, parasites, Australia, 18S
rRNA gene

\subsection*{Introduction}

{\label{introduction}}

The frequency of emerging and re-emerging infectious diseases outbreaks
in wildlife reservoirs has increased during recent decades (Gortazar,
Acevedo, Ruiz-Fons, \& Vicente, 2006), raising new questions about
disease pathogenesis and epidemiology. The increasing role of wildlife
in the emergence of livestock diseases is due to multiple changes
occurring within wildlife and livestock populations, including
encroachment on natural habitats, climate change and alteration of
population demographics. Most notably, alteration of wildlife population
demographics caused by anthropogenic landscape modification or
introduction of non-native species can create new interfaces between
livestock and wildlife, potentially exacerbating processes that favour
pathogen transmission (Gortazar et al., 2015). Importantly, transmission
of an infectious agent at the wildlife/livestock interface may occur
directly through interspecies contact, or indirectly through shared
space or vectors (Gortazar et al., 2006; Miller, Farnsworth, \&
Malmberg, 2013).

Australian livestock species are infected with multiple parasitic
pathogens of economic relevance, such as \emph{Fasciola hepatica}(`liver
fluke'), \emph{Echinococcus granulosus} (`hydatids'),\emph{Theileria
orientalis} , \emph{Babesia bigemina} , \emph{Babesia bovis} and
\emph{Anaplasma marginale} (Bock, deVos, \& Molloy, 2006; Jenkins, 2018;
Thompson, 2018). Further, infection with \emph{Neospora caninum} has
been identified as a major cause of abortion in cattle and
investigations in Queensland have estimated a prevalence of around 20\%
(Reichel, 2000). Other pathogenic genera such as \emph{Trypanosoma}
,\emph{Sarcocystis} and \emph{Toxoplasma} have also been detected in
Australian wildlife species (Munday \& Mason, 1980; Pan et al., 2012;
Thompson, Godfrey, \& Thompson, 2014). These pathogens share a large
diversity and distribution of their intermediate hosts and are prevalent
in domestic animals, thus they constitute a biosecurity concern for
livestock industries (Spratt \& Beveridge, 2018).

Australia's livestock export industry was valued at approximately
AU\$1,780 million for the 2015--16 financial year (Australian Government
Department of Agriculture, 2020b). Although Australia is currently free
from some of the world's most important livestock diseases such as
foot-and-mouth disease and avian influenza H5N1, endemic infectious
agents impact on livestock industries. For instance, the economic losses
produced by \emph{Neospora caninum} in Australian cattle were estimated
at AU\$85 million and AU\$25 million per annum for the dairy and the
beef cattle industries, respectively (Reichel, 2000). Moreover, exotic
diseases constitute a major threat to Australia's livestock industry and
a severe outbreak would considerably impact Australia's production and
access to export markets (Australian Government Department of
Agriculture, 2020a).

Among Australian wildlife capable of carrying pathogens transmissible to
livestock, deer are of substantial concern as they commonly feed on
pasture and crops in agricultural landscapes, achieve high local
population densities, are highly mobile and are susceptible to a wide
range of viral, bacterial and parasitic infections that may affect other
ungulates (Cripps, Pacioni, Scroggie, Woolnough, \& Ramsey, 2019). Deer
were introduced in Australia as game animals in the
mid-19\textsuperscript{th} century and have successfully adapted to the
climate and environmental conditions. In addition to the initial
intentional releases, there are records of numerous animals establishing
wild populations after escaping from deer farms (Davis et al., 2016).
Currently, six non-native deer species have established viable wild
populations in most Australian habitats (excluding the arid interior and
north-west), and most of these species are expanding their distributions
and abundances (Davis et al., 2016; Forsyth, Stamation, \& Woodford,
2016).

Numerous pathogens have been detected in various deer species worldwide,
including protozoan parasites with epidemiological relevance to humans
and domestic animals. For example, serological evidence
of\emph{Neospora} and \emph{Toxoplasma} exposure has been detected in
fallow (\emph{Dama dama} ) and red deer (\emph{Cervus elaphus} ) in
Poland (Bien, Moskwa, Bogdaszewski, \& Cabaj, 2012), Italy (Rocchigiani
et al., 2016) and Mexico (De La Torre et al., 2017). Evidence of
piroplasm infection (\emph{Babesia} and \emph{Theileria} ) was reported
in the same two deer species in Europe and China (Garcia-Sanmartin et
al., 2007; Hornok et al., 2017; Li et al., 2014; Tampieri et al., 2008;
Zanet et al., 2014). Also, \emph{Plasmodium} parasites have been
identified in farmed North American white-tailed deer (\emph{Odocoileus
virginianus} ) (Guggisberg, Sayler, Wisely, \& John, 2018) and South
American pampas deer (\emph{Ozotoceros bezoarticus} ) (Asada et al.,
2018).

Limited information is available regarding the overall infection status
of Australian wild deer populations. In particular, serological evidence
is restricted to parasitic helminths, \emph{Leptospira} and some endemic
livestock viruses in red deer (\emph{Cervus elaphus} ) from Queensland
(McKenzie et al., 1985) and rusa deer (\emph{Rusa timorensis} ) from New
South Wales (Moriarty, 2004). Importantly, the prevalence of blood-borne
parasites known to infect deer overseas has not been investigated in
Australian wild deer populations. Therefore, the role that wild deer
might play in the spread of these diseases to livestock remains unclear,
and the transmission of such pathogens to livestock has yet to be
demonstrated in Australia. Addressing this knowledge gap is critical to
anticipating how such pathogens might be transmitted to other animals
(including livestock and humans), and how these diseases may be
controlled. To this end, a molecular survey of parasitic genera
previously detected in Australian livestock (\emph{Theileria}
,\emph{Babesia} and \emph{Neospora} ), and in deer and livestock
overseas (\emph{Trypanosoma} , \emph{Plasmodium} , \emph{Sarcocystis}
and\emph{Toxoplasma} ), was performed in a wide range of deer blood
samples, representing four deer species, collected during 2018 and 2019
across four Australian states and territories.

\textbf{Materials and methods}

Deer blood sample collection

Blood samples were collected by recreational hunters and professional
culling staff from deer populations across eastern Australia (Figure 1).
In most cases the geographic location of collection sites was determined
based on its proximity with livestock dense areas. Samples were mostly
collected during field operations in cold weather months, when most
culling operations occur in Australia. Blood was drawn from the jugular
vein, the heart or the thoracic cavity and collected with and without
anticoagulant (EDTA). Collection tubes (Becton Dickinson, USA) were
inverted to mix and prevent clotting, immediately kept under
refrigerated conditions and transported to the laboratory. Immediately
upon reception, samples were centrifuged for 10 min at 2,000 g. Aliquots
of plasma and blood pellet were stored at -80\selectlanguage{ngerman}°C and -20°C, respectively.

Genomic DNA extraction from blood using a classical phenol-chloroform
method

A small subset of blood samples was randomly selected, and genomic DNA
was extracted using a classical phenol-chloroform extraction, a rapid
and inexpensive liquid-liquid extraction technique (Chacon-Cortes \&
Griffiths, 2014). Briefly, 200 \selectlanguage{greek}μ\selectlanguage{english}l of blood was lysed with 0.15\% saponin
at 4\selectlanguage{ngerman}°C for 10 minutes and centrifuged at 2,800 g for 10 minutes. The
pellet was washed with PBS, resuspended in 700 \selectlanguage{greek}μ\selectlanguage{english}l of Lysis buffer (10 mM
Tris pH 8, 1 mM EDTA pH 8, 0.4 M NaCl and 1\% SDS) and incubated at 37\selectlanguage{ngerman}°C
for 1 hour. A minimum of two phenol-chloroform extractions were
performed by adding 700 \selectlanguage{greek}μ\selectlanguage{english}l of phenol-chloroform-isoamyl alcohol mixture
(cat\#: 77617, Sigma-Aldrich, USA) until the aqueous phase was clear.
The DNA present in the aqueous phase was ethanol-precipitated and
centrifuged at 9,000 g for 3 minutes at 4\selectlanguage{ngerman}°C. The supernatant was
discarded, and the pellet washed with 70\% ethanol. The DNA pellet was
resuspended in TE buffer pH 8 (1 M Tris pH 8 and 0.5 M EDTA pH 8). The
concentration and purity of the extracted genomic DNA samples were
measured with an IMPLEN Nanophotometer (IMPLEN, Germany).

Genomic DNA extraction from blood using a bead-based automated kit

Extraction of genomic DNA from all blood pellet samples with the
bead-based automated kit MagMAX\selectlanguage{english}CORE Nucleic Acid Purification Kit
(ThermoFisher Scientific, Applied Biosystems, USA) was performed
according to the manufacturer's recommendations. Briefly, 200 \selectlanguage{greek}µ\selectlanguage{english}L of
sample was mixed with a bead/Proteinase K mix and a lysis/binding
solution. The mixture was processed using the KingFisher Duo Prime
Purification System (ThermoFisher Scientific, USA). Genomic material was
eluted in 90 \selectlanguage{greek}µ\selectlanguage{english}l of Elution buffer and stored at -20\selectlanguage{ngerman}°C until required.
The concentration and purity of samples were measured with an IMPLEN
Nanophotometer (IMPLEN, Germany).

Molecular detection of parasites by PCR

To generate a positive control for the PCR analysis, genomic DNA
extracted from \emph{in vitro} cultures of various parasites and kindly
provided by collaborators was used: \emph{Trypanosoma brucei}
,\emph{Plasmodium falciparum} , \emph{Neospora caninum} ,
\emph{Sarcocystis gigantea} , \emph{Toxoplasma gondii} , \emph{Babesia
bovis} and\emph{Theileria orientalis} . The negative control consisted
of the PCR mix with nuclease-free water added instead of gDNA. PCR
primers targeting a conserved region of the 18S subunit of the ribosomal
RNA gene (18S rRNA), or the cytochrome b gene in the case
of\emph{Plasmodium} , were obtained from the literature for the seven
parasite genera selected in this study (Table 1 and references therein).

PCR amplification was performed in a 25 \selectlanguage{greek}μ\selectlanguage{english}l reaction mixture containing
1x Green GoTaq Flexi buffer, 2 mM MgCl\textsubscript{2}, 10 mM dNTPs,
0.2 \selectlanguage{greek}μ\selectlanguage{english}M of both forward and reverse primers (Table 1), 0.625 units of
GoTaq G2 DNA polymerase (Promega, USA), and 1 \selectlanguage{greek}μ\selectlanguage{english}l of total genomic DNA
template. The PCR program consisted of an initial denaturation step at
95\selectlanguage{ngerman}ºC for 2 minutes, followed by 35 cycles of denaturation at 95ºC for 45
s, annealing at 55--60ºC for 45 s and extension at 72ºC for 45--90 s,
with a final extension of 5 min at 72ºC (see Table 1). Amplification
occurred in a T100 thermal cycler (BioRad, USA). Amplification products
were visualised by gel electrophoresis, using a 2\% agarose gel,
RedSafe\selectlanguage{english} (iNtRON Biotechnology, Korea), and a high-resolution imaging
system (ChemiDoc\selectlanguage{english} MP Imaging System, Bio-Rad, USA).

Parasite prevalence and statistical analysis

Mean comparisons were made with \emph{t} -tests for two independent
means, with \selectlanguage{greek}α \selectlanguage{english}= 0.05. The maximum possible prevalence of infection,
interpreted as the maximum prevalence (for each pathogen) that could be
present in a population but not observed (i.e. with all tested samples
negative), was calculated with three confidence levels (90, 95 and 99\%)
with an unknown population size using WinEpi 2.0 (Thrusfield, Ortega, de
Blas, Noordhuizen, \& Frankena, 2001).

\textbf{Results}

Host information and statistics

During the sampling period, 243 wild deer blood samples were collected
from four wild deer species (fallow, rusa, sambar (\emph{Rusa unicolor}
) and chital (\emph{Axis axis} ) deer) across eastern states and
territories of mainland Australia (Figure 1). Most samples (69\%) were
collected in June -- October (i.e. winter and spring). Among the four
deer species included in this study, two accounted for more than 83\% of
the samples: fallow deer (57\%), and rusa deer (26\%). Of note, 69\% of
the specimens were collected in the state of New South Wales (Figure 1).
Similar numbers of females (\emph{n} = 120) and males (\emph{n} = 116)
were sampled, with no sex information available for seven animals.
Individuals were classified in three age categories based on
morphological characteristics including body size, tooth wear, and
antler growth: fawn (\textless{} 1 year), yearling (1 to \textless{} 2
years) and adult ([?] 2 years). Most samples were from adults (\emph{n} =
149), followed by yearlings (\emph{n} = 74) and fawns (\emph{n} = 13),
with age information unavailable for seven animals.

Qualitative analysis of the gDNA samples

Considering the high volume of blood samples processed in this study, we
undertook a small-scale comparison to identify the most time-cost
efficient DNA extraction method that would provide optimal DNA quality.
Ten blood samples were randomly selected, and genomic DNA was extracted
using a bead-based method (MagMAXCORE Nucleic Acid Purification Kit)
and a classical phenol-chloroform extraction method. Sample quality
(i.e. concentration and purity) was assessed by spectrophotometry.

Analysis of the gDNA samples extracted with the phenol-chloroform method
determined a mean DNA concentration of 215.3 ng/\selectlanguage{greek}μ\selectlanguage{english}l (SD = 35.2, range =
156 -- 286), a A260/A230 ratio of 1.7 (SD = 0.098, range = 1.49 -- 1.80)
and a A260/A280 ratio of 1.45 (SD = 0.02, range = 1.42 -- 1.48). On the
other hand, the mean DNA concentration obtained with the MagMAXCORE
extraction kit was lower (\emph{p =} 0.0007) (mean 80.4 ng/\selectlanguage{greek}μ\selectlanguage{english}l, SD =
81.2, range = 28 -- 283), although, these samples presented similar
(\emph{p} = 0.4) A260/A230 ratio (mean 1.7, SD = 0.04, range = 1.64 --
1.76) but a higher (\emph{p} \textless{}0.0001) A260/A280 ratio with a
mean of 1.9 (SD = 0.08, range = 1.77 -- 2.00). Therefore, the DNA purity
with MagMAX extraction method was deemed more consistent and superior
when compared to the phenol-chloroform method. Subsequently, MagMAXCORE
was used to extract genomic DNA from all the 243 blood samples included
in this study.

Pathogen PCR amplification analysis

Conserved primers identified in the literature (see Table 1) were used
to amplify the 18S subunit of the ribosomal RNA gene (18S rRNA) of
\emph{Trypanosoma brucei} ,\emph{Neospora caninum} , \emph{Sarcocystis
gigantea} , \emph{Toxoplasma gondii} , \emph{Babesia bovis} and
\emph{Theileria orientalis} (Franco, Romero, Ferrari, Schnittger, \&
Florin-Christensen, 2018; Thompson et al., 2013; Yang et al.,
2014)\emph{.} In the case of \emph{Plasmodium falciparum} , cytochrome b
primers (Schaer et al., 2013) were used. Purified genomic DNA of these
seven pathogens was obtained from \emph{in vitro} cultures and used to
validate the 18S rRNA/cytochrome b primers and PCR amplification
conditions. In this study, PCR conditions were slightly modified as
indicated in Table 1. PCR amplification of the positive controls
resulted in amplicons of the expected size for the seven parasites
investigated (Figure 2).

The 243 genomic DNA samples were subject to PCR amplification with the
four primer pairs and PCR conditions indicated in Table 1. Positive
controls shown in Figure 2 were used in each PCR round. Overall, the PCR
analysis did not amplify the 18S rRNA or the cytochrome b gene of the
seven selected parasites in any of the 243 samples, while the same genes
were successfully amplified in the positive controls within the same
experiment. Despite our best efforts to obtain larger numbers of whole
blood samples from Queensland (\emph{n} = 4), we could only access
additional serum samples of chital deer from this state (\emph{n} =
105). Genomic DNA was extracted from a subset of these serum samples
(\emph{n} = 50) and the PCR screen for the seven parasite genera was
performed (same conditions as indicated in Table 1). No amplicons were
obtained for any of the 50 serum samples and these are not discussed
further.

Parasite prevalence and confidence intervals

The maximum possible prevalence of infection represents the maximum
prevalence (for each parasite) that can be estimated considering the
total number of samples analysed for each deer species. The maximum
possible prevalence of infection ranged from 1.7\% to 11.4\%, except for
chital deer where it ranged from 43.8\% to 68.4\% (Table 2).

\textbf{Discussion}

This study assessed, for the first time, the prevalence of seven
parasite genera in four different wild deer species across Australia. A
total of 243 blood samples were analysed by PCR and the presence
of\emph{Trypanosoma} , \emph{Plasmodium} , \emph{Neospora}
,\emph{Sarcocystis} , \emph{Toxoplasma} , \emph{Babesia}
and\emph{Theileria} was not detected. These findings provide a wide
perspective of the current disease status of the four deer species
investigated (rusa, sambar, chital and fallow deer), which is important
information given that deer coexist and closely interact with humans,
domestic animals and other wildlife species.

Although the limited knowledge of parasitic infections in Australian
wild deer populations is restricted to helminths (McKenzie et al., 1985;
Moriarty, 2004), reports from other countries (Cripps et al., 2019)
indicate that the deer species tested in our study are susceptible to
the pathogens screened in this survey. Interestingly, experimental
infection of white-tailed deer with \emph{Babesia bovis} (Ueti, Olafson,
Freeman, Johnson, \& Scoles, 2015), a pathogenic parasite in cattle and
endemic in Australia (Bock et al., 2006), was reported unsuccessful.
This finding raises the question about the epidemiological role of
specific wild deer species in the maintenance of pathogens in livestock
populations.

\emph{Theileria} , \emph{Babesia} and \emph{Neospora} are endemic
parasites in livestock in the geographical areas covered in our study
and with particularly high prevalence in Queensland (Bock et al., 2006;
Reichel, 2000). Babesiosis is a well-documented disease of cattle and
endemic areas have been reported in northern Australia (Queensland,
Western Australia and Northern Territory) (Bock et al., 2006). Bovine
theileriosis currently occurs throughout coastal New South Wales and
Victoria, Queensland and some isolated parts of South Australia and
Western Australia (Jenkins, 2018). The prevalence of \emph{Neospora
caninum} , identified as a major cause of infectious abortion in
Australian cattle, was estimated to be around 20\% in one study
(Reichel, 2000). It is therefore conceivable that wild deer might carry
some of these parasites. However, the low number of samples collected in
Queensland in this study, 1.6\% (4/243), decreases the probability of
detecting infected animals despite the high prevalence of the parasite
in livestock species in this region.

Reports of Australian wildlife infections with
\emph{Plasmodium}parasites are limited and restricted to Leadbeater's
possum (\emph{Gymnobelideus leadbeateri} ) (Scheelings, McLaren,
Tatarczuch, \& Slocombe, 2016), birds (Grim, McCutchan, Sullivan, \&
Cranfield, 2008; Spratt \& Beveridge, 2018) and reptiles (Spratt \&
Beveridge, 2018; Telford, 1979). In contrast, \emph{Trypanosoma} ,
\emph{Sarcocystis} and\emph{Toxoplasma} have been widely identified in
Australian wildlife (Spratt \& Beveridge, 2018). For instance,
\emph{Trypanosoma} has been detected in indigenous mammalian fauna
living in the same Australian regions targeted in this study. In total,
eight native species of\emph{Trypanosoma} have been described and exotic
trypanosomes have been identified from introduced mammals (Thompson et
al., 2014). In Australia, wild deer coexist with livestock but are also
sympatric with other wildlife species. Thus, considering the diversity
and distribution of intermediate hosts for pathogens such as
trypanosomes, wild deer constitute an obvious biosecurity concern. Our
study has found no evidence of trypanosome infections in the blood of
Australian wild deer, nor of the other six parasites tested, which may
be dependent on several factors, including season of the sampling, low
parasitaemia at the time of blood collection and fluctuation of
parasitaemia during the parasite's life cycle.

One of the limitations of this study is that samples analysed were
mostly collected during the Australian winter and spring seasons, with
69\% of the samples being collected between June and October. Most of
the sampling occurred during cold weather months due to logistical
reasons outside of our control. Cold weather conditions negatively
influence the transmission rates of vector-borne diseases (Caminade,
McIntyre, \& Jones, 2019); therefore, sampling season may impact the
chances of detecting infected animals.

Extremely low parasite loads have been previously reported in wild
deer.\emph{Plasmodium} \emph{odocoilei} was estimated to infect
\textasciitilde{}1/65,000 red blood cells of white-tailed deer
(Martinsen et al., 2016; Templeton, Asada, et al., 2016; Templeton,
Martinsen, Kaewthamasorn, \& Kaneko, 2016), and molecular tests have
previously determined \emph{Plasmodium} parasitaemia levels (percentage
of infected red blood cells) in cervids to be as low as 0.003\%
(Martinsen et al., 2016; Templeton, Asada, et al., 2016). This low blood
parasite burden observed in adult individuals has led to the hypothesis
that blood-stage ungulate malaria is best characterised as a chronic,
occult infection without major health consequences (Templeton,
Martinsen, et al., 2016). Further, it is important to highlight that
molecular screening such as conducted in this study can only identify an
active infection (i.e. animals that have recovered from infection will
not be identified as they would be via serology). A variety of PCR-based
assays are now widely used for detection of parasite DNA in blood
(Garcia-Sanmartin et al., 2007; Li et al., 2014; Remesar et al., 2019;
Yang et al., 2014). In our study, we minimised the effects of PCR
inhibitors and the presence of false negatives by obtaining high-quality
DNA for each sample, however molecular assays are not infallible.

The opportunistic nature of our study allowed us to collect many
samples, but each sample was collected at a single time point (i.e. no
serial sampling of animals). Hence, the parasite life cycle at the time
of blood collection may have had a direct impact on the negative
findings of our study.

Despite the lack of evidence of current infection in the 243 blood
samples analysed in this study, the maximum possible prevalence was
calculated for each deer species (Table 2) and found to range between
3.5 and 11.4\% for fallow, rusa and sambar deer with a 99\% confidence
level. Since the maximum possible prevalence is directly influenced by
the number of samples screened, the maximum prevalence obtained for
chital deer (\emph{n} = 4) greatly exceeds the values obtained for the
other three deer species given the limited number of animals sampled. We
acknowledge our very limited sample size and recommend further studies
to expand on our initial screening of chital deer blood parasites in
Queensland.

Importantly, the impact of climate change might be considered as a
factor affecting the spread of wildlife diseases in new areas. Modelling
suggests that, by 2100, the average global temperature will have risen
by 1.0--3.5\selectlanguage{ngerman}ºC (Githeko, Lindsay, Confalonieri, \& Patz, 2000). Climate
change will strongly affect the distribution, abundance and transmission
rates, the intensity and temporal pattern of vector activity; and the
survival and reproduction of pathogens within vectors. This will
increase the likelihood of vector-borne diseases in new areas (Duncan,
Backus, Lynn, Powers, \& Salman, 2008; Guberti, Stancampiano, \&
Ferrari, 2014). The impact of climate change is evident in Europe
with\emph{Ixodes} ticks, vectors of several pathogens
including\emph{Babesia} and \emph{Anaplasma} , where, over the past
decade, an expansion in vectors' geographical range (spread to northern
areas) and increase in activity were observed as consequence of milder
winters and prolonged spring and autumn seasons, combined with increased
vegetative cover and the spread of animals carrying ticks into newly
suitable regions (Caminade et al., 2019). Although all the samples
screened in this study were negative for the parasites tested, the
presence of suitable vectors and previous evidence of infection in
domestic and wild animals (Bock et al., 2006; Spratt \& Beveridge, 2018;
Thompson et al., 2014) indicates that climate change could transform
current pathogen-free regions into `new habitats' for vectors and
pathogens.

In the context of animal health, wildlife disease surveillance is an
important tool to obtain information of morbidity and mortality, changes
in patterns of disease occurrence over time, and early detection of
disease outbreaks, including those linked to emerging diseases (Duncan
et al., 2008; Grogan et al., 2014). For example, surveillance programs
in Europe resulted in detection of a new disease in rabbits, the
European brown hare syndrome caused by a calicivirus (Artois et al.,
2009). However, detection of a new disease depends on its prevalence,
patterns of transmission and disease-induced mortality. Therefore,
sampling effort is crucial. Our sampling methodology involved
recreational hunters and staff in deer control programs, who provided
samples and data, but obtaining information on the health status of deer
at the time of sampling was challenging. Considering the likelihood of
chronic and low burden parasitic infections of deer, a key factor that
would increase the efficacy and efficiency of wildlife disease
surveillance is a clearer definition of the term 'suspect case'. This
description could be available and shared with the wide range of
stakeholders including hunters and wildlife rangers who could be
involved in retrieving important information during their traditional
activities (Grogan et al., 2014; Guberti et al., 2014). In Australia,
recreational hunting is an economically important activity, contributing
AU\$335 to the economy, with deer among the primary species hunted
(Australian Government Department of Health, 2019). In Victoria alone
there were over 36,000 licensed deer hunters that harvested
\textasciitilde{}100,000 deer in 2018 (Victoria State Government, 2019).
This large hunter population, if utilised to enable wildlife disease
surveillance (Ryser-Degiorgis, 2013), represents an opportunity to
implement a passive surveillance program to detect and identify endemic
and emerging infections in new areas.

The focus of this study was on parasites, but the approach taken could
be readily expanded to consider bacterial and viral pathogens. Our data
suggest that it is unlikely that a large proportion of Australian deer
are involved in maintaining the life cycle of \emph{Trypanosoma}
,\emph{Plasmodium} , \emph{Neospora} , \emph{Sarcocystis}
,\emph{Toxoplasma} , \emph{Babesia} and \emph{Theileria} , as our
maximum possible prevalence of infection are lower than those reported
in Italy (Zanet et al., 2014) and Canada (Milnes et al., 2019).
Importantly, this survey represents the first molecular study of its
type in Australian deer and provides important baseline information
about the disease status of wild deer in eastern Australia. Despite our
best efforts, we could not conduct extensive deer sampling in warmer
months or in tropical areas. Considering the additional limitations of
our study discussed above, further studies combining serology assays and
high-throughput sequencing are desirable. This would enhance parasite
detection, and ultimately characterise the epidemiology of such
pathogens in Australian wild deer populations. Assessment of the
infection status of invasive species such as deer is necessary for
future planning and successful implementation of disease eradication
programs in livestock (Gortazar et al., 2015).

\textbf{Acknowledgements}

We would like to thank Richard Francis (ABZECO), Jake Haddad (VPAC),
Kirk Stone (Strathbogie Wildlife), Andrew Bengsen, Troy Crittle and
Quentin Hart (New South Wales Department of Primary Industries), Bob
McKinnon and Amy Sheridan (North West Local Land Services), Michael
Brennan and Matt Amos (Biosecurity Queensland), and staff from Parks
Victoria for assisting with sample collection. In addition, we thank Kim
O'Riley and Peter Mee for technical support. Finally, we thank Peter
Irwin (Murdoch University), Darren Creek (Monash Institute for
Pharmaceutical Sciences), Brian Cooke (Monash University) and Abdul
Jabbar (University of Melbourne) for providing genomic DNA samples of
various parasites used in this study as PCR positive controls. This work
was supported by the Centre for Invasive Species Solutions under Grant
PO1-L-002.

\textbf{Conflict of Interest Statement}

No potential conflict of interest was reported by the authors.

\textbf{Data availability statement}

The data that supports the findings of this study are available in the
various sections of this article. If needed, further information is
available from the corresponding author upon request.

\textbf{Ethical statement}

The authors confirm that the ethical policies of the journal, as noted
on the journal's author guidelines page, have been adhered to. No
ethical approval was required as samples for this study were collected
from carcasses. Relevant permits for the culling programs that
facilitated the sample collections are held by the organizations that
organized and conducted the culling.

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\textbf{Figure legend}

\textbf{Figure 1} . Map of Australia indicating where sampling was
carried out and detailing the number of animals sampled by jurisdiction
and the deer species, chital deer (\emph{Axis axis} ), rusa deer
(\emph{Rusa timorensis} ), sambar deer (\emph{Rusa unicolor} ) and
fallow deer (\emph{Dama dama} ). Sample size is reported for whole blood
samples only.

\textbf{Figure 2} . PCR amplification of the 18S rRNA gene
from\emph{Babesia bovis} (1409bp), \emph{Neospora caninum}
(400bp),\emph{Sarcocystis gigantea} (400bp), \emph{Theileria
orientalis}(1409bp), \emph{Toxoplasma gondii} (400bp), \emph{Trypanosoma
brucei}(950bp), and cytochrome b gene from \emph{Plasmodium falciparum}
(750 bp).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-1/Figure-1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-2/Figure-2}

\end{center}
\end{figure}

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