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Surveillance of wild animals carrying infectious agents based on high-throughput screening platform in the Republic of Korea

BMC Veterinary Research volume 19, Article number: 158 (2023) Cite this article

Abstract

Background

Infectious diseases transmitted by wild animals are major threats to public health. This study aimed to investigate the potential of rescued wild animals that died of unknown causes as reservoirs of infectious agents. From 2018 to 2019, 121 dead wild animals (55 birds and 66 mammals) were included in this study. All wild animals died during treatment after anthropogenic events. After deaths of animals, necropsies were performed and trachea, lungs, large intestine (including stool), and spleen were collected to determine causes of deaths. A high-throughput screening (HTS) quantitative polymerase chain reaction (qPCR) designed to detect 19 pathogens simultaneously against 48 samples in duplicate was performed using nucleic acids extracted from pooled tissues and peripheral blood samples. If positive, singleplex real-time PCR was performed for individual organs or blood samples.

Results

The HTS qPCR showed positive results for Campylobacter jejuni (10/121, 8.3%), Campylobacter coli (1/121, 0.8%), Mycoplasma spp. (78/121, 64.5%), and Plasmodium spp. (7/121, 5.7%). Singleplex real-time PCR confirmed that C. jejuni was detected in the large intestine but not in the blood. C. coli was only detected in the large intestine. Mycoplasma spp. were detected in all organs, having the highest proportion in the large intestine and lowest in the blood. Plasmodium spp. was also detected in all organs, with proportions being were similar among organs.

Conclusions

This study shows that wild animals can become carriers of infectious agents without showing any clinical symptoms.

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Background

More than half of known infectious pathogens are zoonotic, 12% of which are causing emerging infectious diseases (EIDs) [1]. The number and diversity of diseases are increasing. Many diseases not only threaten human health, but also affect livestock and wild animals [2]. Globalization, environmental change, and migrating birds or wild animals living in borders can spread diseases or pathogens more easily and widely. For example, avian influenza (AI) is one of the most well-known viral diseases transmitted from migratory birds to poultry [3]. Climate change increases the risk of new inflows of wildlife-derived infectious diseases, especially arthropod-borne diseases such as malaria and Japanese encephalitis. It also increases the spread of disease [4]. The trade of wild animals and wild animal products can also affect the spread of diseases [5].

Most EIDs are considered to spread from wildlife. The importance of constructing surveillance programs and research is increasing [6]. Outbreaks of infectious diseases are recognized mainly by reporting them in clinical cases or by detecting pathogens extracted from the environment or carcasses. Constructing a surveillance program to enable rapid detection and response can help prevent the spread of diseases [7, 8]. High-throughput quantitative polymerase chain reaction (qPCR) platforms are useful because large-scale detection can be performed rapidly and sensitively [9, 10].

The importance of surveilling wildlife-derived infectious diseases is increasing, as is the number of diseases that require surveillance. Monitoring all diseases takes substantial time, finances, and reagent volume. Moreover, research on untamed and living wild animals requires greater effort [11]. Although the gold standard varies from disease to disease, molecular diagnosis is commonly considered a useful method [12]. Real-time qPCR is often used to detect pathogens because it is capable of performing quantitative analysis with a high-sensitivity [13]. However, with increasing number of diseases requiring surveillance, it is costly and time-consuming to test all samples for significant results [14]. A high-throughput qPCR platform can be used to address this issue to reduce time and cost. Its analytical sensitivity and specificity are not decreased compared to those of singleplex screening [9].

This study was conducted to investigate the potential of wild animals rescued from traumatic distress and died during treatment or were euthanized as carriers of infectious diseases using a high-throughput qPCR platform.

Results

Results of high-throughput qPCR platform

Results of high-throughput qPCR platform showed that samples were positive for Campylobacter jejuni (10/121, 8.3%), Campylobacter coli (1/121, 0.8%), Mycoplasma spp. (78/121, 64.5%), and Plasmodium spp. (7/121, 5.7%) (Table 1). C. coli was detected only in a kestrel. C. jejuni and C. coli were detected in water birds or other wild animals that had been rescued around water bodies such as rivers and seas. Mycoplasma spp. and Plasmodium spp. were detected in various species from rescued areas such as expressways, residential areas, and farmlands.

Table 1 Prevalence of pathogen and reason for rescue of animals with pathogens detected
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Results of singleplex qPCR

In birds, singleplex qPCR revealed that C. jejuni was detected in 100% of large intestine samples, 63% of trachea samples, 75% of lung samples, and 50% of spleen samples. C. coli was detected only in the large intestine. Mycoplasma spp. was detected in 76% of large intestine samples, 68% of trachea samples, 63% of lung samples, 29% of spleen samples, and 5% of blood samples. Plasmodium spp. was found in 53% of lung and large intestine samples, 46% of trachea and blood samples, and 38% of spleen samples. In mammals, C. jejuni was detected in 100% of large intestine, trachea, and spleen samples and 50% of lung samples. Mycoplasma spp. was detected in 75% of large intestines, 70% of tracheae, 65% of lungs, 40% of spleens, and 45% of blood samples. Plasmodium spp. was only detected in the trachea with a high Ct value of 37.98.

Histopathological analysis

Pathogens were detected in 82 (67.8%) of 121 animals examined. All patients did not show any clinical signs regarding these pathogens. Morphologically, it was difficult to confirm the effect of infection because most patients showed hemorrhage or tissue damage due to trauma. Twenty-two (22/82, 18.2%) cases, including 4 mammals (4/22, 18.2%) and 18 birds (18/22, 81.8%), showed histopathological lesions such as inflammation or necrosis in internal organs associated with infections. In mammals, only Mycoplasma spp. was detected from three raccoon dogs and one Korean water deer. Among them, in one raccoon dog, Mycoplasma spp. was detected in the lung, large intestine, and trachea. However, histopathological lesions related to pathogens were only found in the lungs (mild interstitial pneumonia) [15]. The other raccoon dog with Mycoplasma spp. detected in blood only showed hepatic necrosis. Thus, additional qPCR was performed and Mycoplasma spp. was detected in the liver. The last raccoon dog infected by endoparasites and ectoparasites showed inflammation in kidney, heart, pancreas, large intestine, stomach, lung, and spleen. However, Mycoplasma spp. was only detected in the large intestine, heart, pancreas, and kidney. In one Korean water deer rescued after a car accident, Mycoplasma spp. was detected in the lung and trachea. However, histopathological lesion regarding infection was not confirmed in the lung or trachea. Instead, chronic nephritis showed and additional qPCR detected Mycoplasma spp. in the kidney. In birds, Mycoplasma spp. were detected the most frequently (16/18, 88.9%), followed by Plasmodium spp. (5/18, 27.8%). C. jejuni (2/18, 11.1%), and C. coli (1/18, 5.6%). The association between detected pathogen and histopathological lesion was not distinct except for two cases (1 Chinese Little Bittern and 1 Eurasian Woodcock) of Plasmodium spp. detected in the liver (mild hepatitis) [16].

Molecular analysis of Plasmodium spp.

A phylogenetic analysis was conducted based on sequence homologies of Plasmodium spp. in each organ (Fig. 1). Among Plasmodium spp. positive samples through high-throughput qPCR platform and singleplex qPCR, two avian species of Haemoproteus spp. and one Leucocytozoon spp. were found in three animals through nested and conventional PCR. Therefore, these three animals were excluded. Through phylogenetic analysis, we confirmed that pathogens obtained from different organs of one animal showed homologous sequences except for two cases. For one animal, the sequence from the spleen showed Haemoproteus spp. from nested PCR. However, a conventional PCR revealed Plasmodium spp. For the other animal, sequences from the blood revealed Plasmodium spp. in nested PCR. However, in conventional PCR and sequencing, Haemoproteus spp. was detected. In the analysis of geographical distribution of genotypes (Fig. 2), samples found in a Korean water deer (Hydropotes inermis) (18–809) and a Chinese little bittern (Ixobrychus sinensis) (18–617) were most similar to the sequence of Plasmodium spp. found in Japan (AB308051, AB308052). The Plasmodium spp. detected in a Eurasian Woodcock (Scolopax rusticola) (19–777) and a spot-billed duck (Anas poecilorhyncha) (18–649) were the most similar to Plasmodium circumflexum (KY653762) found in Lithuania or Plasmodium spp. (GQ141559) found in the USA. The Plasmodium spp. detected in a Eurasian Jay (Garrulus glandarius) (19–440) was identical to P. relicutum, which was most similar to that found in Spain (JN164729). Samples found in a brown hawk-owls (Ninox scutulata) (19–145) showed sequences identical to the sequence of Plasmodium spp. found in Singapore (AY099035). The sample found in a cattle egret (Bubulcus ibis) (19–603) was not clustered with any sequences used in this study.

Fig. 1
figure 1

Sequence homologies of Plasmodium spp. detected in multiple organs in a single case. Plasmodium spp. detected in the same individual showed the same sequence except for two cases. Sequences obtained from this study are written in terms of the year of rescue and detected organs followed by species. Neighbor-joining phylogenetic analysis was performed with MEGA-X. Bootstrap percentage values are shown on branches

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Fig. 2
figure 2

Phylogenetic analysis of Plasmodium identified in wild birds in this study, showing diverse genotypes. Sequences obtained from this study are written in terms of rescue year and detected organs. Neighbor-joining genetic analysis was performed using MEGA-X. Bootstrap percentage values are shown on branches

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Discussion

This study confirmed the presence of major infectious pathogens in the Republic of Korea in wildlife that died or euthanized at wildlife rescued center using a high-throughput platform. In this study, more than one pathogen was detected in 67.8% of examined wild animals. Pathogen detection was higher in wild birds (40/55, 72.7%) than in wild mammals (42/66, 63.6%). Clinical symptoms corresponding to detected pathogens were not observed in all animals during treatment periods. On the other hand, 18.2% of detected pathogens were confirmed to be associated with histopathological lesions regarding infections. Histopathological lesions related to detected pathogens were only shown in six patients (3 raccoon dogs, 1 Korean water deer, 1 Chinese Little Bittern, and 1 Eurasian Woodcock). Even in these six patients, specific lesions for each pathogen were not shown or no lesion was identified in any organs where pathogens were detected. Therefore, the detection of such pathogens was more likely to be from secondary infections or incidental finding due to the effect of trauma or other infections such as ectoparasites or endoparasites. Considering that all wild animals included in this study were rescued from anthropogenic accidents or injuries, or from serious ectoparasitic infections (severe scabies infection in raccoon dogs), wild animals are carrying pathogens as asymptomatic carriers.

Wild birds are considered as carriers of human camphylobacteriosis [17]. The transmission of this pathogen occurs through a fecal-oral route, causing waterborne outbreaks [18]. Campylobacter spp. is also a thermophilic pathogen. Birds are considered good reservoir of these pathogens because birds have higher body temperatures than mammals [19]. Patients carrying Campylobacter spp. showed common features consistent with those described in previous studies [17,18,19]. All patients were waterfowl or the rescued area was near water. In addition, more were detected in birds (14.5%) than in mammals (3%). In addition, patients did not show any symptoms corresponding to these pathogens such as enteritis. Since wild birds living near the water are more likely to asymptomatic reservoirs of Campylobacter spp., monitoring should be conducted for them.

In this study, Mycoplasma spp. had the highest prevalence (64.5%). However, clinical signs and histopathological lesions associated with these pathogens were rarely observed. Only four (4/78, 5.1%) patients showed histopathological lesions in organs from which pathogens were detected. Even in wild animals with histopathological lesions, the direct cause of death was trauma due to accidents, indicating that wild animals might be potential carriers of Mycoplasma spp. A variety of Mycoplasma spp. have been identified in wild animals worldwide. Although the pathogenesis has not been elucidated yet, Mycoplasma spp. is known to cause various diseases [20]. Further studies are necessary to identify the correlation between the presence of bacteria and pathological changes in wild animals.

In this study, in all wild animals in which Plasmodium spp. was detected in multiple organs, the same sequence was confirmed as a result of sequencing of pathogens detected for each organ except for two cases. Sequence comparison also revealed that Plasmodium spp. detected in the trachea of Korea water deer (Hydropotes inermis) (18–809) shared 99% sequence similarities with those detected in Chinese little bitterns (Ixobrychus sinensis) (18–617). It was unclear why Plasmodium spp., which is highly similar to that isolated from birds, was detected in organs of herbivores. However, cases of pathogenic induction by erythrocyte development of Plasmodium spp. have been reported [21]. Although rare, interspecies transmission cases indicate that mammals have contact with birds in the wild [22]. A more extensive study on the degree of Plasmodium spp. infection in wild mammals and its genetic similarity with avian isolates if Plasmodium spp. is needed in the future.

In a previous study conducted in the same area [23], Plasmodium spp. was detected in 6 (5.1%) out of 118 birds, whereas it was detected in 6 (10.9%) out of 55 birds in this study, showing a higher prevalence. Plasmodium spp. identified in the previous study were mainly similar to those identified in Asian countries regarding their genetic diversities, while Plasmodium spp. identified in this study became more diverse to include those detected in Europe or the United States. It can also be seen that genotypes between migratory birds or between migratory birds and resident birds are still similar. Sequences of a Plasmodium spp. isolated from a Korean water deer (Hydropotes inermis) (18–809) was most similar to that of a Plasmodium spp. isolated from Japan. They both were in the same clade as Plasmodium spp. detected from Chinese little bitterns (Ixobrychus sinensis) (18–617) and brown hawk owl (Ninox scutulata) (16–794). This may indicate that migratory birds’ role as mediators of Plasmodium spp. is at risk of expanding to mammals as well as resident birds. However, this study was limited to those with histopathological evaluations among those who died or were euthanized. Since screening criteria of samples were different from those of the previous study, direct comparison of prevalence was limited. A separate study should be conducted to analyze changes in the prevalence of Plasmodum spp. in the study area.

Conclusion

Since pathogens of wild animals can also be pathogens of humans and livestock, various investigations of diseases centered on wild animal carcasses have been conducted. This study confirms that wild animals that appear healthy without having specific pathogen-specific lesions can carry pathogens, demonstrating that wild animals can be asymptomatic carriers of pathogens. Future studies on wildlife-borne diseases should use carcasses and determine the possibility of simple carriers simultaneously.

Methods

Sample Collection

A total of 121 wild animals (55 birds and 66 mammals) rescued between January 2018 and December 2019 that died or were euthanized during treatment were included in this study (Table 2). In the case of euthanizing wild animals because they could not be release into the wild, T-61 euthanasia solution (Embutramide, Mebenzonium iodide, Tetracaine hydrochloride infectable solution) was injected at 0.3 mg/kg under unconsciousness after deep inhalation anesthesia with isoflurane. In the course of treatment, animals had no specific clinical symptoms for infectious diseases. No other signs were observed in clinical laboratory tests (complete blood count and clinical chemistry analysis). After death or euthanasia, necropsy and histopathological examination were performed to determine the cause of death. During necropsy, four organ tissues (trachea, lung, large intestine [including stool], and spleen) were collected and stored in ethanol for screening of infectious agents. The peripheral blood collected and used for blood tests during medical treatment and stored was also included in the investigation of infectious agents.

Table 2 Information on wildlife species (scientific name) included in this study
Full size table

Nucleic acid extraction and reverse transcription

Tissues were washed with distilled water to remove ethanol. Blood and tissue samples were ground separately using TissueLyser II (Qiagen, Hilden, Germany) with nuclease-free water and then mixed together. The total volume was 200 or 250 µL. DNA and RNA were extracted simultaneously using a MagMAX™ Total Nucleic Acid Isolation Kit (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s instructions. Nucleic acid extraction was also conducted for positive samples using a QIAamp DNA Mini Kit (Qiagen). For RNA viruses, reverse transcriptase PCR was performed using a high-capacity cDNA reverse transcription kit (Thermo Fisher Scientific). Extracted nucleic acids were stored at -20℃.

High-throughput qPCR platform

A high-throughput qPCR platform panel was designed to simultaneously detect 19 pathogens (Brucella spp., Campylobacter jejuni, Campylobacter coli, Chlamydia pneumoniae, Chlamydia psittaci, Chlamydia abortus, Mycoplasma haemofelis, Mycoplasma haemominutum, Mycobacterium avium, Mycobacterium bovis, Mycoplasma spp., Japanese encephalitis virus, Severe fever with thrombocytopenia syndrome virus, West Nile virus, Newcastle virus, avian influenza, Cryptococcus neoformans, Leucocytozoon spp, and Plasmodium spp.) in duplicates (48 samples could be examined simultaneously). PCR amplification was performed in a total volume of 5 µL. The reaction mixture contained 1.2 µL nucleic acid, 2.5 µL TaqMan® Fast Advanced Master Mix (Thermo Fisher Scientific), and 1.3 µL of nuclease-free water. The reaction mixture was then loaded onto a plate using an automated sample loading system (Thermo Fisher Scientific). In the plate, each through-hole contained 33 nL reaction mixture. The primer and probe sets were obtained from published sources [24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41]. Additional information about primers and probes can be found in additional file [see Additional file 1]. The PCR protocol consisted of 40 cycles of 95 °C for 15 s and 60 °C for 1 min.

Singleplex qPCR

Singleplex qPCR was performed for high-throughput qPCR platform-positive samples to determine which tissues or blood samples contained the pathogen. It was laso performed for additional organ tissues showing histopathologic lesions. For nucleic acid amplification, 2 µL of nucleic acid from each organ and blood was used as a template in a final volume of 20 µL with TaqMan® Fast Advanced Master Mix (Thermo Fisher Scientific), 0.2 µM of each primer, and 0.1 µM of each probe. The thermal cycler protocol consisted of incubation at 50 °C for 2 min, 95 °C for 20 s, and 40 cycles at 95 °C for 1 s and at 60 °C for 20 s. The primer and probe were the same as those designed for the high-throughput qPCR platform panel. After qPCR, all positive samples were sequenced and compared to BLAST database to determine pathogenic organisms.

Molecular Analysis for Plasmodium spp.

Two gel-based PCRs and sequencing was performed for phylogenetic analysis of identified Plasmodium spp. One was nested PCR for comparing sequence homologies of identified hemoparasites in a single case and the other one was a conventional PCR for comparing geographical distribution of genotypes. Both steps of nested PCR were performed in a final volume of 50 µL using a HotStarTaq Master Mix Kit (Qiagen). The template consisted of 2 µL of nucleic acid isolated from each organ and blood. The mixture was denatured for 15 min at 95oC, followed by 40 cycles at 95oC for 45 s, 50oC for 45 s, and 72oC for 1 min, and finally extended at 72oC for 7 min before maintaining at 4oC. The first PCR product was used as a template for the second PCR. For nested PCR, HameNF1-HaemNR3 primers were used for the first PCR and HaemF-HaemR2 primers were used for the second PCR. PCR amplicons had an expected size of 617 bp for nested PCR [42]. For conventional PCR, the first reaction was performed using 3760 F-4292Rw2 primers. If the fragment was not amplified, a follow-up reaction was performed with smaller fragments using F1-4292Rw2, F3-4292Rw2, and 3760 F-R1 primer pairs. PCR amplicons had an expected size of 400–500 bp [43, 44].

Phylogenetic analysis was conducted by comparing base pair of cytochrome b sequence. Phylogenetic analysis was performed for two purposes: (1) to compare sequence homology of Plasmodium spp. detected in each organ (Fig. 1); and (2) to estimate geographical distribution of Plasmodium spp. mainly transmitted by wild birds (Fig. 2). For the phylogenetic tree for confirming sequence homology, a sequence of Theileria annulata (GenBank accession number: M63015) was used as outgroup. For comparing geographical diversity, the phylogenetic tree was made using a sequence of Plasmodium spp. (GenBank accession numbers AY099029 and JN164729) as outgroup. Neighbor-joining genetic analysis was performed using MEGA-X. Numbers on branches indicate bootstrap values based on 1,000 replicates.

Data availability

This article contains all data created or analyzed throughout the investigation.

Abbreviations

EID:

Emerging infectious disease

AI:

Avian influenza

qPCR:

Quantitative polymerase chain reaction

PCR:

Polymerase chain reaction

C.jejuni :

Campylobacter jejuni

C.coli :

Campylobacter coli\

P. relicutum :

Plasmodium relicutum

References

  1. Taylor LH, Latham SM, Woolhouse MEJ. Risk factors for human disease emergence. Philos Trans R Soc Lond B Biol Sci. 2001;356:983–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Cunningham AA, Daszak P, Wood JLN. One health, emerging infectious diseases and wildlife: two decades of progress? Philos Trans R Soc Lond B Biol Sci. 2017;372:20160167.

    PubMed  PubMed Central  Google Scholar 

  3. Altizer S, Bartel R, Han BA. Animal migration and infectious disease risk. Science. 2011;331:296–302.

    CAS  PubMed  Google Scholar 

  4. Baylis M. Potential impact of climate change on emerging vector-borne and other infections in the UK. Environ Health. 2017;16(Suppl 1):112.

    PubMed  PubMed Central  Google Scholar 

  5. Fèvre EM, Bronsvoort BM, Hamilton KA, Cleaveland S. Animal movements and the spread of infectious diseases. Trends Microbiol. 2006;14:125–31.

    PubMed  PubMed Central  Google Scholar 

  6. Hukić M, Numanović F, Sisirak M, Moro A, Dervović E, Jakovec S. Salimović Bešić I. Surveillance of wildlife zoonotic diseases in the Balkans region. Med Glas (Zenica). 2010;7:96–105.

    PubMed  Google Scholar 

  7. Buehler JW, Hopkins RS, Overhage JM, Sosin DM, Tong V, CDC Working Group. Framework for evaluating public health surveillance systems for early detection of outbreaks: recommendations from the CDC Working Group. MMWR Recomm Rep. 2004;53:1–11.

    PubMed  Google Scholar 

  8. Min J, Kim HW, Ko Y, Oh JY, Kang JY, Lee J, Park YJ, Lee SS, Park JS, Kim JS. Tuberculosis surveillance and monitoring under the national public-private mix tuberculosis control project in South Korea 2016–2017. Tuberc Respir Dis (Seoul). 2020;83:218–27.

  9. Grigorenko E, Fisher C, Patel S, Winkelman V, Williamson P, Chancey C, Añez G, Rios M, Majam V, Kumar S, Duncan R. Highly multiplex real-time PCR-Based screening for blood-borne pathogens on an openarray platform. J Mol Diagn. 2017;19:549–60.

    CAS  PubMed  Google Scholar 

  10. Gonzales TK, Kulow M, Park DJ, Kaspar CW, Anklam KS, Pertzborn KM, Kerrish KD, Ivanek R, Döpfer D. A high-throughput open-array qPCR gene panel to identify, virulotype, and subtype O157 and non-O157 enterohemorrhagic Escherichia coli. Mol Cell Probes. 2011;25:222–30.

    CAS  PubMed  Google Scholar 

  11. Belant JL, Deese AR. Importance of wildlife disease surveillance. Human-Wildlife Interact. 2010;4:165–9.

    Google Scholar 

  12. Procop GW. Molecular diagnostics for the detection and characterization of microbial pathogens. Clin Infect Dis. 2007;45(Suppl 2):99–S111.

    Google Scholar 

  13. Schmittgen TD, Livak KJ. Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc. 2008;3:1101–8.

    CAS  PubMed  Google Scholar 

  14. Rhyan JC, Spraker TR. Emergence of diseases from wildlife reservoirs. Vet Pathol. 2010;47:34–9.

    CAS  PubMed  Google Scholar 

  15. Sumithra TG, Chaturvedi VK, Susan C, Siju SJ, Rai AK, Harish C, Sunita SC. Mycoplasmosis in wildlife: a review. Eur J Wildl Res. 2013;59:769–81.

    Google Scholar 

  16. Meister SL, Richard OK, Hoby S, Gurtner C, Basso WU. Fatal avian malaria in captive Atlantic puffins (Fratercula arctica) in Switzerland. Int J Parasitol Parasites Wildl. 2021;14:97–106.

    PubMed  PubMed Central  Google Scholar 

  17. Cody AJ, McCarthy ND, Bray JE, Wimalarathna HM, Colles FM, van Jansen MJ, Dingle KE, Waldenström J, Maiden MC. Wild bird-associated Campylobacter jejuni isolates are a consistent source of human disease, in Oxfordshire, United Kingdom. Environ Microbiol Rep. 2015;7(5):782–8.

    PubMed  Google Scholar 

  18. Hyllestad S, Iversen A, MacDonald E, Amato E, Borge BÃS, Bøe A, Sandvin A, Brandal LT, Lyngstad TM, Naseer U, Nygård K, Veneti L, Vold L. Large waterborne Campylobacter outbreak: use of multiple approaches to investigate contamination of the drinking water supply system, Norway, June 2019. Euro Surveill. 2020;25:17–26.

    Google Scholar 

  19. Prince Milton AA, Agarwal RK, Priya GB, Saminathan M, Aravind M, Reddy A, Athira CK, Anjay, Ramees TP, Dhama K, Sharma AK, Kumar A. Prevalence of campylobacter jejuni and campylobacter coli in captive wildlife species of india. Iran J Vet Res. 2017;18:177–82.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Akerstedt J, Hofshagen M. Bacteriological investigation of infectious keratoconjunctivitis in norwegian sheep. Acta Vet Scand. 2004;45:19–26.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Valkiūnas G, Iezhova TA. Exo-erythrocytic development of avian malaria and related haemosporidian parasites. Malar J. 2017;16:1–24.

    Google Scholar 

  22. Ricklefs RE, Fallon SM. Diversification and host switching in avian malaria parasites. Proc Biol Sci. 2002;269:885–92.

    PubMed  PubMed Central  Google Scholar 

  23. Rhim H, Bae J, Kim H, Han JI. Prevalence and phylogenetic analysis of avian haemosporidia in wild birds in the Republic of Korea. J Wildl Dis. 2018;54:772–81.

    CAS  PubMed  Google Scholar 

  24. Best EL, Powell EJ, Swift C, Grant KA, Frost JA. Applicability of a rapid duplex real-time PCR assay for speciation of Campylobacter jejuni and Campylobacter coli directly from culture plates. FEMS Microbiol Lett. 2003;229(2):237–41.

    CAS  PubMed  Google Scholar 

  25. Kuoppa Y, Boman J, Scott L, Kumlin U, Eriksson I, Allard A. Quantitative detection of respiratory Chlamydia pneumoniae infection by real-time PCR. J Clin Microbiol. 2002;40(6):2273–4.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Pantchev A, Sting R, Bauerfeind R, Tyczka J, Sachse K. Detection of all Chlamydophila and Chlamydia spp. of veterinary interest using species-specific real-time PCR assays. Comp Immunol Microbiol Infect Dis. 2010;33(6):473–84.

    PubMed  Google Scholar 

  27. Veron V, Simon S, Blanchet D, Aznar C. Real-time polymerase chain reaction detection of Cryptococcus neoformans and Cryptococcus gattii in human samples. Diagn Microbiol Infect Dis. 2009;65(1):69–72.

    CAS  PubMed  Google Scholar 

  28. Zhang Z, Liu D, Sun W, Liu J, He L, Hu J, Gu M, Wang X, Liu X, Hu S, Chen S, Peng D, Liu X. Multiplex one-step real-time PCR by Taqman-MGB method for rapid detection of pan and H5 subtype avian influenza viruses. PLoS ONE. 2017;12(6):e0178634.

    PubMed  PubMed Central  Google Scholar 

  29. Spackman E, Senne DA, Bulaga LL, Myers TJ, Perdue ML, Garber LP, Lohman K, Daum LT, Suarez DL. Development of real-time RT-PCR for the detection of avian influenza virus. Avian Dis. 2003;47(3 Suppl):1079–82.

    CAS  PubMed  Google Scholar 

  30. Shirato K, Miyoshi H, Kariwa H, Takashima I. Detection of West Nile virus and japanese encephalitis virus using real-time PCR with a probe common to both viruses. J Virol Methods. 2005;126(1–2):119–25.

    CAS  PubMed  Google Scholar 

  31. Smith MM, Schmutz J, Apelgren C, Ramey AM. A real-time, quantitative PCR protocol for assessing the relative parasitemia of Leucocytozoon in waterfowl. J Microbiol Methods. 2015;111:72–7.

    CAS  PubMed  Google Scholar 

  32. Slana I, Kaevska M, Kralik P, Horvathova A, Pavlik I. Distribution of Mycobacterium avium subsp. avium and M. a. hominissuis in artificially infected pigs studied by culture and IS901 and IS1245 quantitative real time PCR. Vet Microbiol. 2010;144(3–4):437–43.

    CAS  PubMed  Google Scholar 

  33. Watanabe Pinhata JM, Cergole-Novella MC, Moreira Dos Santos Carmo A, Ruivo Ferro E, Silva R, Ferrazoli L, Tavares Sacchi C, de Siqueira R. Rapid detection of Mycobacterium tuberculosis complex by real-time PCR in sputum samples and its use in the routine diagnosis in a reference laboratory. J Med Microbiol. 2015;64(9):1040–45.

    PubMed  Google Scholar 

  34. Barker EN, Langton DA, Helps CR, Brown G, Malik R, Shaw SE, Tasker S. Haemoparasites of free-roaming dogs associated with several remote Aboriginal communities in Australia. BMC Vet Res. 2012;14:8:55.

    Google Scholar 

  35. Janetzko K, Rink G, Hecker A, Bieback K, Klüter H, Bugert P. A single-tube real-time PCR assay for Mycoplasma detection as a routine quality control of cell therapeutics. Transfus Med Hemother. 2014;41(1):83–9.

    PubMed  Google Scholar 

  36. Cellier-Holzem E, Esparza-Salas R, Garnier S, Sorci G. Effect of repeated exposure to Plasmodium relictum (lineage SGS1) on infection dynamics in domestic canaries. Int J Parasitol. 2010;40(12):1447–53.

    PubMed  Google Scholar 

  37. Sun Y, Liang M, Qu J, Jin C, Zhang Q, Li J, Jiang X, Wang Q, Lu J, Gu W, Zhang S, Li C, Wang X, Zhan F, Yao W, Bi Z, Wang S, Li D. Early diagnosis of novel SFTS bunyavirus infection by quantitative real-time RT-PCR assay. J Clin Virol. 2012;53(1):48–53.

    CAS  PubMed  Google Scholar 

  38. Di Trani L, Bedini B, Donatelli I, Campitelli L, Chiappini B, De Marco MA, Delogu M, Buonavoglia C, Vaccari G. A sensitive one-step real-time PCR for detection of avian influenza viruses using a MGB probe and an internal positive control. BMC Infect Dis. 2006;25:6:87.

    Google Scholar 

  39. Hinić V, Brodard I, Thomann A, Cvetnić Z, Makaya PV, Frey J, Abril C. Novel identification and differentiation of Brucella melitensis, B. abortus, B. suis, B. ovis, B. canis, and B. neotomae suitable for both conventional and real-time PCR systems. J Microbiol Methods. 2008;75(2):375–8.

    PubMed  Google Scholar 

  40. Vázquez A, Herrero L, Negredo A, Hernández L, Sánchez-Seco MP, Tenorio A. Real time PCR assay for detection of all known lineages of West Nile virus. J Virol Methods. 2016;236:266–70.

    PubMed  Google Scholar 

  41. Turgeon N, Toulouse MJ, Martel B, Moineau S, Duchaine C. Comparison of five bacteriophages as models for viral aerosol studies. Appl Environ Microbiol. 2014;80(14):4242–50.

    PubMed  PubMed Central  Google Scholar 

  42. Hellgren O, Waldenström J, Bensch S. A new PCR assay for simultaneous studies of Leucocytozoon, Plasmodium, and Haemoproteus from avian blood. J Parasitol. 2004;90:797–802.

    CAS  PubMed  Google Scholar 

  43. Bensch S, Stjernman M, Hasselquist D, Ostman O, Hansson B, Westerdahl H, Pinheiro RT. Host specificity in avian blood parasites: a study of Plasmodium and Haemoproteus mitochondrial DNA amplified from birds. Proc Biol Sci. 2000;267:1583–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Ishtiaq F, Gering E, Rappole JH, Rahmani AR, Jhala YV, Dove CJ, Milensky C, Olson SL, Peirce MA, Fleischer RC. Prevalence and diversity of avian hematozoan parasites in Asia: a regional survey. J Wildl Dis. 2007;43:382–98.

    PubMed  Google Scholar 

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Funding

This work was supported by the National Institute of Wildlife Disease Control and Prevention as “Specialized Graduate School Support Project for Wildlife Disease Specialists”.

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Authors and Affiliations

  1. Laboratory of Wildlife Medicine, College of Veterinary Medicine, Jeonbuk National University, Iksan, 54596, Republic of Korea

    Myeongsu Kim, Jieun Bae, Haerin Rhim, Somyeong Yang & Jae-Ik Han

  2. Laboratory of Veterinary Pathology, College of Veterinary Medicine, Jeonbuk National University, Iksan, 54596, Republic of Korea

    Byungkwan Oh, Myeon-Sik Yang & Bumseok Kim

  3. Jeonbuk Wildlife Center, Jeonbuk National University, Iksan, 54596, Republic of Korea

    Myeongsu Kim & Haerin Rhim

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  1. Myeongsu Kim
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Contributions

MK, JB, and JH designed this study. MK, JB, HR, SY a,nd JH collected samples and performed experiments. BO, MY, and BK contributed to histopathologic diagnosis. MK, JB, BO, and JH interpreted the results and drafted the manuscript. All authors have read and approved the final version of the manuscript.

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Correspondence to Jae-Ik Han.

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This study analyzed samples obtained during the course of treatment of clinical patients. Data were compiled with permission from the rescue center. It is not subject to review by the Research Ethics Committee of the author’s affiliated institution.

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The authors declare no competing interests.

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Kim, M., Bae, J., Oh, B. et al. Surveillance of wild animals carrying infectious agents based on high-throughput screening platform in the Republic of Korea. BMC Vet Res 19, 158 (2023). https://doi.org/10.1186/s12917-023-03714-0

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Keywords

BMC Veterinary Research

ISSN: 1746-6148

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