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All issues Volume 32 (2025) Parasite, 32 (2025) 54 Full HTML
Open Access
Issue
Parasite
Volume 32, 2025
Article Number 54
Number of page(s) 9
DOI https://doi.org/10.1051/parasite/2025040
Published online 25 August 2025

© M.T. Kyaw et al., published by EDP Sciences, 2025

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Introduction

Tick-borne diseases have a profound negative impact on the cattle industry, particularly in tropical and subtropical regions worldwide. In addition to reduced meat and milk production caused by morbidity and mortality, they can result in economic losses imposed by treatment and tick control measures, amounting to approximately US$13.9–18.7 billion globally per year [23, 24, 46]. In Thailand, a developing agricultural nation in Southeast Asia, the growth of the livestock industry has been limited by the high occurrence of tick-borne diseases, mainly babesiosis and theileriosis [1, 21]. These diseases are caused by the piroplasms Babesia and Theileria, respectively and are exclusively transmitted by blood-feeding ixodid hard ticks affecting cattle [46].

Babesia bigemina and B. bovis are the primary causative agents of bovine babesiosis in the tropics and subtropics [10]. They share a common tick vector, Rhipicephalus (Boophilus) microplus, which is the most widely distributed tick species in Thailand [21, 37]. After invading host erythrocytes, Babesia species multiply asexually and destroy host erythrocytes. Bovine theileriosis is caused by several Theileria spp., including Theileria annulata and T. parva, which cause malignant lymphoproliferative disorders, and T. orientalis and T. sinensis, which cause benign theileriosis [5, 7, 33]. These pathogens are transmitted by ticks of the genera Rhipicephalus, Hyalomma, and Haemaphysalis [9, 16]. However, R. microplus is the primary vector of bovine theileriosis in Thailand [37, 51], and benign Theileria spp. have been reported in both cattle and R. microplus ticks in the country [22, 37, 39, 44, 51]. Theileria species invade host leukocytes and erythrocytes, and multiply asexually. Babesiosis and theileriosis can cause high fever, hemolytic anemia, jaundice, abortion, and death in cattle depending on the infecting Babesia or Theileria species [5, 10, 35]. In B. bovis infection, neurological manifestations known as cerebral babesiosis can occur [48]. Cases of bovine babesiosis and benign theileriosis have been reported in different parts of Thailand [3, 14, 43, 45].

For the diagnosis of these diseases, the gold-standard method is the microscopic examination of Giemsa-stained blood smears, which is cost-effective but labor-intensive and not very sensitive [2, 8, 12]. Serological assays such as enzyme-linked immunosorbent assay (ELISA) have been developed, but they are usually time-consuming and can yield cross-reactions [1, 32]. In contrast, molecular detection methods provide high sensitivity and specificity [17, 26, 27]. Several molecular detection methods, such as conventional PCR (cPCR) and nested PCR, have been developed to diagnose bovine babesiosis and theileriosis in Thailand [3, 14, 22, 39]. However, these methods are low throughput, require manipulation of amplicons during gel fractionation, and have a high risk of PCR-product cross-contamination [4]. Quantitative PCR assays using specific probes have also been developed [11, 25]. They are highly specific and sensitive but are costly, making them unsuitable for detecting multiple species in a large number of samples. On the other hand, the SYBR Green real-time PCR method is much cheaper and adaptable for any target sequences. Although it is less specific than use of probes, melting-curve analysis can increase its specificity [6, 34]. Molecular detection methods have been developed in other countries; however, our study advances the field by establishing a high-throughput system for simultaneous screening of both cattle blood and tick vectors within a single laboratory setting.

In this study, we established a reliable, robust, and high-throughput SYBR Green real-time PCR assay targeting the 18S rRNA gene of Theileria spp. and mitochondrial cytochrome b (Cytb) gene of Babesia spp. in both cattle blood and tick vectors from southern and northern Thailand. This method, specifically optimized for local strains, ensures high sensitivity and specificity, simultaneously detects and distinguishes three Theileria spp. and two Babesia spp. based on their melting profiles (Tm), and the first to integrate host and vector surveillance into a standardized platform in Thailand, providing a model adaptable for large-scale surveillance in other endemic regions.

Materials and methods

Ethics approval

The cattle blood and tick samples used in this study were collected according to the Guidelines for Animal Experimentation of the National Research Council of Thailand and approved by the Animal Ethics Committee of the Faculty of Medicine, Khon Kaen University, Thailand (AMEDKKU 003/2020 and AMEDKKU 009/2022).

Sample collection

Cattle blood samples (N = 143) were collected from apparently healthy beef cattle in northeastern provinces (Maha Sarakham, Khon Kaen, Nakhon Ratchasima, and Roi Et) and a southern province (Nakhon Si Thammarat) of Thailand. These samples were received from the biospecimen bank at the Department of Parasitology, Khon Kaen University. The tick samples (N = 65) were obtained from the biospecimen bank at the Department of Entomology and Plant Pathology, Khon Kaen University. They were collected from beef cattle in upper-northeastern Thailand (Provinces: Mukdahan, Bueng Kan, Nakhon Phanom, Khon Kaen, Loei, Sakon Nakhon, Roi-Et, Maha Sarakham, Nong Bua Lamphu, and Nong Khai) (Additional file 1: Tables S1, S2). Ticks were collected from different parts of cattle: neck, abdomen, ear, tail, udder-scrotum, and ano-vulva, carefully removed by forceps from the skin and transferred to 5 mL tubes containing 90% ethanol and then stored at −20 °C [50]. Morphological species identification was performed under a stereomicroscope using standard keys and guides [42, 49, 52].

DNA extraction of cattle blood and tick samples

DNA was extracted from 200 μL of cattle blood using a NucleoSpin® Blood Mini Kit (MACHEREY-NAGEL, Duren, Germany), according to the manufacturer’s instructions. Tick DNA was extracted using a NucleoSpin® tissue kit (MACHEREY-NAGEL), according to the manufacturer’s instructions. Concentrations of genomic DNA (gDNA) in each extract were measured on a NanoDrop™ One Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and the sample was stored at −20 °C until further use. The gDNAs of various blood and tissue pathogens stored at −70 °C in the Biobank of the Department of Parasitology, Faculty of Medicine, Khon Kaen University, including Anaplasma spp. (N = 2), Babesia canis (N = 2), Ehrlichia spp. (N = 2), Hepatozoon sp. (N = 1), Plasmodium falciparum (N = 1), P. vivax (N = 1), Trypanosoma evansi (N = 1), Toxoplasma (N = 1), Sarcocystis hominis (N = 1), S. sinensis (N = 1), and S. cruzi (N = 1) were used for specificity testing.

Tick identification

Molecular confirmation of identity was performed according to a previous study [50]. A part of the cox 1 gene was amplified using conventional PCR with forward primer S0725 (F1) (5′–TAC TCT ACT AAT CAT AAA GAC ATT GG–3′) and reverse primer S0726 (R1) (5′–CCT CCT CCT GAA GGG TCA AAA AAT GA–3′). The amplified products were then directly sequenced in both directions using the same PCR primers on an Applied Biosystems 3730XL DNA Analyzer, provided by Bionix sequencing service (Seoul, South Korea). The resulting sequences were identified and compared with others in the GenBank database using the Basic Local Alignment Search Tool (BLAST) from the National Center for Biotechnology Information (U.S. National Library of Medicine, Bethesda, MD) (http://blast.ncbi.nlm.nih.gov/Blast.cgi). Out of 65 ticks, 60 were identified as Rhipicephalus microplus (OM760991–OM760995, OM761006, OM761015, OM761016, OM761020, OM761021, OM761024, OM761032, OM761033, OM761037–OM761059, OM761062, and OM761064) and 5 were Haemaphysalis bispinosa (OM760846–OM760849 and OM760853), provided in Tables S1, S2. Representative alignment comparison between sequences from this study and reference sequences is presented in Supplementary Fig. 1.

Conventional PCR for screening of Babesia and Theileria infections

To obtain the positive samples for plasmid control construction, cPCR amplification was used to screen the cattle blood samples stored in biobank. This was performed by targeting a portion of the 18S rRNA gene for Theileria spp. [53] and of the mitochondrial cytochrome b (Cytb) gene for B. bigemina and B. bovis [13]. A PCR reaction mixture of total volume 50 μL was prepared containing 25 μL of 2× GoTaq® Green Master Mix (Promega, Madison, WI, USA), 1 μL of each primer (0.2 μM), 8 μL of template, and 15 μL of double-distilled water. The PCR cycling program was as follows: initial denaturation at 94 °C for 5 min; 35 cycles of denaturation at 94 °C for 30 s, annealing at 48.5 °C for 30 s, extension at 72 °C for 30 s, followed by a final extension step at 72 °C for 7 min. Aliquots of 5 μL of each reaction were analyzed on agarose gel 2% (w/v) for Babesia spp., 1% (w/v) for Theileria spp.) in 0.5× TBE buffer. The PCR product for each strain was subjected to electrophoresis at 100 V/cm for 25 min, after which the gel was stained with RedSafe™ Nucleic Acid Staining Solution (iNtRON Biotechnology, Gyeonggi‑do, South Korea) and visualized using an Axygen® Gel Documentation System-BL (Axygen, Corning, NY, USA). The PCR products were sequenced in both directions by ATCG Co., Ltd. Thailand, using the PCR primers as sequencing primers.

Plasmid DNA construction

Amplicons obtained by cPCR from field-collected samples positive for B. bigemina, T. orientalis, and T. sinensis and synthetic DNA of T. annulata and B. bovis (Tsingke Biotech Co., Ltd., Beijing, China) were purified with a GenepHlow™ Gel Extraction Kit (Geneaid Biotech, New Taipei City, Taiwan), cloned into pGEM-T Easy vector (Promega) and transformed into Escherichia coli JM109 competent cells (Promega). Three colonies from each sample were collected, and the inserted gene was detected using the colony PCR technique with primers M13F (-20)/M13R (-24) [31]. PCR products were sent for sequencing by ATGC Co., Ltd., Thailand. Plasmid DNA was extracted using a NucleoSpin® Plasmid EasyPure kit (MACHEREY-NAGEL). Plasmid DNA concentration was measured on a NanoDrop™ One Spectrophotometer (Thermo Fisher Scientific). Plasmids were serially diluted to 109–1 copies/μL with sterile deionized water for use in developing the real-time PCR detection method.

Real-time PCR (qPCR) analysis

Three separate pairs of specific primers were used for qPCR analysis. For detection of the two Babesia spp., primer pairs targeting mitochondrial cytochrome b (Cytb) were used: cbisg-1F: 5′–TGT TCC AGG AGA TGT TGA TTC–3′ and cbisg-2R: 5′–AGC ATG GAA ATA ACG AAG TGC–3′ for B. bigemina; cbosg-1: 5′–TGT TCC TGG AAG CGT TGA TTC–3′ and cbosg-2: 5′–AGC GTG AAA ATA ACG CAT TGC–3′ for B. bovis [13]. For detection of Theileria spp. (T. annulata, T. orientalis, and T. sinensis), a primer pair targeting the 18S rRNA gene (BovisT-5F: 5′–CGA GAC CTT AAC CTG CTA AAT AGG–3′ and BovisT-5R: 5′–CCC TCT AAG AAG CGA TAA CGG–3′) was used [53]. qPCR analysis was performed using a QuantStudio™ 6 Flex Real-time PCR system. The total volume of 25 μL of PCR reaction was prepared comprising 12.5 μL Maxima SYBR Green/ROX qPCR Master Mix (2×) (Thermo Fisher Scientific), 0.175 μL of each primer (0.07 μM), 2 μL of gDNA template, and 10.15 μL of nuclease-free water. The optimized qPCR reaction parameters were as follows: initial denaturation at 95 °C for 5 min, followed by 40 cycles of denaturation at 95 °C for 20 s, annealing temperature at 58 °C for 30 s, and extension at 72 °C for 45 s. Then, temperature was increased from 60 to 95 °C at 0.05 °C intervals, with a hold-time of 15 s at each step. Standard melting-curve analysis was performed at 95 °C for 15 s, 60 °C for 1 min, and 95 °C for 15 s for one cycle. The cutoff for the number of cycles (Ct) used in sample diagnosis was set to 35 to minimize the formation of primer-dimers. Under these conditions, the few non-specific products generated did not affect the interpretation of the amplification results.

The same cattle blood samples (N = 143), used in the developed assay, were amplified by cPCR followed by sequencing. Tick samples (N = 65) were amplified by cPCR and sequenced in the previous study [51]. Then, the results were compared with the developed qPCR assay.

Data analysis

Data analysis and graphical representation of results were performed using numpy v2.1.1 [18], pandas v3.12 [30], matplotlib v3.9.2 package [19] in Python 3 to generate melting curves. For clustering analysis, we use the K-Means module from scikit-learn v1.5.2 [36] to separate different melting-temperature groups [28].

R software version 4.4.1 [40] and R Studio Desktop version 2024.04.2 + 764 [41] were used for the statistical analyses. Tukey’s HSD (honestly significant difference) test was used to analyze the melting temperatures, setting a statistical significance value of p < 0.05. The R package agricolae version 1.3–5 [15] was used to perform pairwise comparisons and one-way ANOVA.

Results

Babesia- and Theileria-positive control samples

The plasmid controls for all species were validated by sequence analysis and deposited in GenBank. The sequences of B. bigemina (PV751017), B. bovis (PV751018), T. orientalis (PV774666), T. sinensis (PV774665), and T. annulata (PV751019) showed 100% identity with reference sequences in GenBank, including B. bigemina (OP361312) from cattle in Brazil, B. bovis (CP125253) from the USA, T. orientalis (MH208642) from ticks in China, T. sinensis (MT271911) from Malaysia, and T. annulata (MT341858) from cattle in Italy (Supplementary Fig. 2).

Sensitivity of plasmid control

The cycle threshold (Ct) results from qPCR for each ten-fold plasmid dilution (ranging from 105 copies to 1 copy; each time done in triplicate) were plotted to generate a standard curve. The detection limits for B. bigemina and B. bovis were 103 copies/μL of plasmid DNA, R2 > 0.99 and R2 > 0.96, respectively (Figs. 1a–1b). Theileria annulata and T. sinensis qPCR sensitivity curves showed a lower limit of quantification of 10 copies/μL of plasmid DNA, with R2 > 0.96–0.95 (Figs. 1c, 1e). For T. orientalis, the qPCR sensitivity curves demonstrated a limit of quantification at 102 copies/μL of plasmid DNA, with an R2 > 0.98 (Fig. 1d).

thumbnail Figure 1

Standard curve of plasmid DNA dilutions (105–1 copies/μL): a) B. bigemina, b) B. bovis, c) T. annulata, d) T. orientalis, and e) T. sinensis.

Melting-curve analysis of qPCR assays

Melting-curve analysis with a cycle cutoff of <35 cycles clearly distinguished the plasmid controls for B. bigemina, B. bovis, T. annulata, T. orientalis, and T. sinensis, with each species showing a distinct melting curve (Figs. 2a, 2b, 2e, 2f). Pairwise comparisons using Tukey’s HSD test revealed significant differences in melting temperatures among all species (p < 0.05). The melting temperatures were as follows: B. bigemina 74.38 ± 0.04 °C, B. bovis 75.7 ± 0.06 °C (Fig. 3a), T. annulata 74.06 ± 0.03 °C, T. orientalis 74.61 ± 0.03 °C, and T. sinensis 75.84 ± 0.03 °C (Fig. 3b).

thumbnail Figure 2

Melting-curve analysis of Babesia and Theileria species: a) Normalized melting curves, and b) Difference curves of Babesia spp. (Cytb gene) (plasmid controls), c) Normalized melting curves, and d) Difference curves of Babesia spp. (Cytb gene) (field samples compared with plasmid controls), e) Normalized melting curves, and f) Difference curves of Theileria spp. (18S rRNA gene) (plasmid controls), g) Normalized melting curves, and h) Difference curves of Theileria spp. (18S rRNA gene) (field samples compared with plasmid controls).
thumbnail Figure 3

Melting temperatures boxplot of plasmid control (3 replicates) and samples of a) Babesia spp., and b) Theileria spp. Statistically significant differences (Tukey’s HSD test, p < 0.05) are indicated in the figure with different letters; boxplot with the same letter indicates no statistical difference. Figure 3a), A: plasmid controls for B. bovis, B1: plasmid controls for B. bigemina, B2: positive samples for B. bigemina. Figure 3b), A1: plasmid control for T. sinensis, A2: positive samples for T. sinensis, B1: plasmid controls for T. orientalis, B2: positive samples for T. orientalis, C: plasmid control for T. annulata.

Evaluation of the qPCR assay using plasmid controls and field samples

Melting-curve analysis of the cattle blood samples compared with plasmid controls revealed Theileria orientalis in 12 out of 143 (8.4%), T. sinensis in 37 out of 143 (25.9%), and Babesia bigemina in 1 out of 143 (0.7%). In the tick samples, Theileria orientalis was found in 5 out of 65 specimens (7.7%), T. sinensis in 11 specimens (16.9%), and B. bigemina in 4 specimens (6.1%), from R. microplus only (Additional files 1 and 2: Tables S1, S2). The melting curves for each species were clearly distinguishable (Figs. 2c, 2d, 2g, 2h). A comparison of the mean melting temperature for each species using Tukey’s HSD tests indicated statistically significant differences (Fig. 3) (p < 0.05). Neither B. bovis nor T. annulata was detected in any of the samples. Additionally, none of the other biobank samples tested for specificity (Anaplasma spp., B. canis, Ehrlichia spp., Hepatozoon sp., P. falciparum, P. vivax, T. evansi, Toxoplasma, S. hominis, S. sinensis, and S. cruzi) yielded positive results, as all showed Ct values above the detection cutoff (>35).

cPCR amplification of cattle blood samples (N = 143) showed 4 samples positive for B. bigemina, and sequencing confirmed the identity (not submitted to GenBank due to short sequence length), 3 samples for T. orientalis (PV592335 and PV592336), and 17 samples for T. sinensis (PV592339–PV592343) (Supplementary Fig. 2). Those of tick samples were 4 samples positive for B. bigemina, 5 samples positive for T. orientalis (Accession numbers: PP30060–PP30063) and 12 samples for T. sinensis, all positive sequences were submitted to the GenBank database (Accession numbers: PP188642–PP188663) [51].

Discussion

This study successfully developed and validated a high-throughput qPCR assay for the detection and differentiation of Babesia bigemina, B. bovis, Theileria orientalis, T. sinensis, and T. annulata in both cattle blood and tick vectors. Compared to traditional microscopy and serological methods, this qPCR assay offers superior sensitivity, allowing early detection and differentiation of multiple pathogens in co-infected cases [20, 21, 29, 47]. Its high-throughput nature makes it a valuable tool for large-scale epidemiological surveillance and disease control [43]. The robustness of the assay was evident through distinct melting curves, with statistically significant differences in melting temperatures between species. This highlights the assay’s specificity in differentiating closely related species of Babesia and Theileria, which is critical for accurate diagnosis and effective disease management.

Field samples revealed a high prevalence of T. sinensis and T. orientalis in tick vectors, consistent with reports of benign theileriosis in Southeast Asia [5, 35]. The detection of B. bigemina in cattle blood at lower prevalence aligns with previous studies documenting the endemicity of bovine babesiosis in Thailand [43, 45]. Since most of the tick vectors in this study were R. microplus, this also corroborates previous studies on the abundance of this species in Thailand, and its role in the possible transmission of B. bigemina, B. bovis, T. orientalis, and T. sinensis [21, 37]. Neither Babesia nor Theileria spp. were detected in H. bispinosa which is also a cattle tick, but not a known vector for these species. However, only 6 ticks of the species were tested. The absence of B. bovis and T. annulata in the field samples may reflect regional differences in tick vector populations or could be attributed to limited sample sizes. Similar studies have suggested that such variations may result from environmental factors, vector competence, and host availability, which influence the distribution of these pathogens [30, 38]. Despite its numerous advantages, the qPCR assay has some limitations. The main limitation is the reliance on high-quality DNA; low-quality samples may result in false negatives, highlighting the importance of optimized sample collection and storage methods. This assay showed negative for samples that were positive for B. bigemina by cPCR and sequencing. This can be due to extremely low concentration of parasites. The implications of this study are significant for disease management and control strategies in cattle populations. The ability to accurately distinguish between Babesia and Theileria species enables targeted treatment approaches, reducing the misuse of chemotherapeutic agents and the emergence of drug resistance​ [35]. Furthermore, the assay can serve as a valuable epidemiological tool to monitor the spread of tick-borne pathogens, aiding in the development of effective vector control programs [43]. The presence of genetically different strains of Theileria orientalis and Babesia bovis in different regions suggests that future diagnostic tools should incorporate broader strain-specific primers to enhance detection accuracy [45]. Moreover, the findings emphasize the importance of region-specific surveillance to mitigate disease outbreaks and improve livestock health management strategies [37].

Conclusions

This study successfully developed and validated a high-throughput qPCR assay for the detection and differentiation of B. bigemina, B. bovis, T. orientalis, T. sinensis, and T. annulata in cattle blood and tick vectors. The assay demonstrated high specificity and robustness, with clear differentiation between closely related species based on melting curves and statistically significant temperature differences. Field sample analyses indicated a high prevalence of T. sinensis and T. orientalis in the tick vector, R. microplus, highlighting its role in transmission of bovine theileriosis – in addition to bovine babesiosis – in Thailand. Cattle blood samples showed a lower prevalence of B. bigemina, consistent with previous reports from Southeast Asia. The absence of B. bovis and T. annulata may reflect regional differences or sample limitations. Overall, the real-time SYBR Green PCR assay developed here is a valuable molecular tool for early and accurate diagnosis of tick-borne protozoan infections, enhancing efforts in disease management and control. Further research into the geographic distribution of tick vectors and pathogens is essential for better-targeted interventions.

Acknowledgments

We would like to acknowledge Prof. David Blair for editing the MS via Publication Clinic KKU, Thailand. This Research was supported by Fundamental Fund of Khon Kaen University, the National Science Research and Innovation Fund (NSRF), Thailand.

Conflicts of interest

The authors declare that they have no conflicts of interest.

Supplementary material

Supplementary Figure 1: Homology comparisons of reference sequences and sequences submitted in this study for tick species identification. OR545517: reference sequence of R. microplus, OR335052: reference sequence of H. bispinosa, Representative sequences from each province (KK: Khon Kaen, BK: Bueng Kan, SK: Sakon Nakhon, NP: Nakhon Phanom, LI: Loei, RE: Roi Et, and MS: Maha Sarakham), were aligned.

Supplementary Figure 2: Comparison of plasmid control sequences with GenBank references. a) Plasmid controls: B. bigemina (PV751017) and B. bovis (PV751018), reference sequences: B. bigemina (OP361312) and B. bovis (CP125253), b) Plasmid controls: T. annulata (PV751019), T. orientalis (PV774666), and T. sinensis (PV774665), references sequences: T. annulata (MT341858), T. orientalis (MH208642), and T. sinensis (MT271911).

Table S1: Real-Time PCR results of Theileria detection.

Table S2: Real-Time PCR results of Babesia detection.

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References

  1. Adjou Moumouni PF, Galon EM, Tumwebaze MA, Byamukama B, Ngasaman R, Tiwananthagorn S, Kamyingkird K, Inpankaew T, Xuan X. 2023. Tick-borne pathogen detection and its association with alterations in packed cell volume of dairy cattle in Thailand. Animals, 13, 2844. [Google Scholar]
  2. Almeria S, Castellà J, Ferrer D, Ortuño A, Estrada-Peña A, Gutiérrez JF. 2001. Bovine piroplasms in Minorca (Balearic Islands, Spain): a comparison of PCR-based and light microscopy detection. Veterinary Parasitology, 99, 249–259. [Google Scholar]
  3. Altangerel K, Sivakumar T, Inpankaew T, Jittapalapong S, Terkawi MA, Ueno A, Xuan X, Igarashi I, Yokoyama N. 2011. Molecular prevalence of different genotypes of Theileria orientalis detected from cattle and Water Buffaloes in Thailand. Journal of Parasitology, 97, 1075–1079. [Google Scholar]
  4. Annoscia G, Latrofa MS, Cantacessi C, Olivieri E, Manfredi MT, Dantas-Torres F, Otranto D. 2017. A new PCR assay for the detection and differentiation of Babesia canis and Babesia vogeli. Ticks and Tick-Borne Diseases , 8, 862–865. [Google Scholar]
  5. Aparna M, Ravindran R, Vimalkumar MB, Lakshmanan B, Rameshkumar P, Kumar KG, Promod K, Ajithkumar S, Ravishankar C, Devada K, Subramanian H, George AJ, Ghosh S. 2011. Molecular characterization of Theileria orientalis causing fatal infection in crossbred adult bovines of South India. Parasitology International, 60, 524–529. [Google Scholar]
  6. Arya M, Shergill IS, Williamson M, Gommersall L, Arya N, Patel HR. 2005. Basic principles of real-time quantitative PCR. Expert Review of Molecular Diagnostics, 5, 209–219. [Google Scholar]
  7. Bai Q, Liu GY, Yin H. 2002. Theileria sinensis sp nov: A new species of bovine Theileria – molecular taxonomic studies. Acta Veterinaria et Zootechnica Sinica, 33, 185–190. [Google Scholar]
  8. Bishop JP, Adams LG. 1973. Combination thin and thick blood films for the detection of Babesia parasitemia. American Journal of Veterinary Research, 34, 1213–1214. [Google Scholar]
  9. Bishop R, Musoke A, Morzaria S, Gardner M, Nene V. 2004. Theileria: intracellular protozoan parasites of wild and domestic ruminants transmitted by ixodid ticks. Parasitology, 129, S271–S283. [Google Scholar]
  10. Bock R, Jackson L, de Vos A, Jorgensen W. 2004. Babesiosis of cattle. Parasitology, 129, S247–S269. [CrossRef] [PubMed] [Google Scholar]
  11. Bogema DR, Deutscher AT, Fell S, Collins D, Eamens GJ, Jenkinsa C. 2015. Development and validation of a quantitative PCR assay using multiplexed hydrolysis probes for detection and quantification of Theileria orientalis isolates and differentiation of clinically relevant subtypes. Journal of Clinical Microbiology, 53, 941–950. [Google Scholar]
  12. Böse R, Jorgensen WK, Dalgliesh RJ, Friedhoff KT, de Vos AJ. 1995. Current state and future trends in the diagnosis of babesiosis. Veterinary Parasitology, 57, 61–74. [Google Scholar]
  13. Buling A, Criado-Fornelio A, Asenzo G, Benitez D, Barba-Carretero JC, Florin-Christensen M. 2007. A quantitative PCR assay for the detection and quantification of Babesia bovis and B. bigemina. Veterinary Parasitology, 147, 16–25. [Google Scholar]
  14. Cao S, Aboge GO, Terkawi MA, Yu L, Kamyingkird K, Luo Y, Li Y, Goo YK, Yamagishi J, Nishikawa Y, Yokoyama N, Suzuki H, Igarashi I, Maeda R, Inpankaew T, Jittapalapong S, Xuan X. 2012. Molecular detection and identification of Babesia bovis and Babesia bigemina in cattle in northern Thailand. Parasitology Research, 111, 1259–1266. [Google Scholar]
  15. De Mendiburu F. 2023. Agricolae: statistical procedures for agricultural research. R package version 1.3-7. Available at: https://www.CRAN.R-project.org/package=agricolae. Accessed 22 February 2024. [Google Scholar]
  16. Dinkel KD, Herndon DR, Noh SM, Lahmers KK, Todd SM, Ueti MW, Scoles GA, Mason KL, Fry LM. 2021. A U.S. isolate of Theileria orientalis, Ikeda genotype, is transmitted to cattle by the invasive Asian longhorned tick, Haemaphysalis longicornis. Parasites & Vectors, 14, 157. [Google Scholar]
  17. Gubbels JM, de Vos AP, van der Weide M, Viseras J, Schouls LM, de Vries E, Jongejan F. 1999. Simultaneous detection of bovine Theileria and Babesia species by reverse line blot hybridization. Journal of Clinical Microbiology, 37, 1782–1789. [Google Scholar]
  18. Harris CR, Millman KJ, van der Walt SJ, Gommers R, Virtanen P, Cournapeau D, Wieser E, Taylor J, Berg S, Smith NJ, Kern R, Picus M, Hoyer S, van Kerkwijk MH, Brett M, Haldane A, Del Río JF, Wiebe M, Peterson P, Gérard-Marchant P, Sheppard K, Reddy T, Weckesser W, Abbasi H, Gohlke C, Oliphant TE. 2020. Array programming with NumPy. Nature, 585, 357–362. [NASA ADS] [CrossRef] [Google Scholar]
  19. Hunter JD, 2007. Matplotlib: A 2D graphics environment. Computing in Science & Engineering, 9, 90–95. [NASA ADS] [CrossRef] [Google Scholar]
  20. Iseki H, Zhou L, Kim C, Inpankaew T, Sununta C, Yokoyama N, Xuan X, Jittapalapong S, Igarashi I. 2010. Seroprevalence of Babesia infections of dairy cows in northern Thailand. Veterinary Parasitology, 170, 193–196. [Google Scholar]
  21. Mosqueda J, Olvera-Ramirez A, Aguilar-Tipacamu G, Canto GJ. 2012. Current advances in detection and treatment of babesiosis. Current Medicinal Chemistry, 19, 1504–1518. [Google Scholar]
  22. Jirapattharasate C, Adjou Moumouni PF, Cao S, Iguchi A, Liu M, Wang G, Zhou M, Vudriko P, Changbunjong T, Sungpradit S, Ratanakorn P, Moonarmart W, Sedwisai P, Weluwanarak T, Wongsawang W, Suzuki H, Xuan X. 2016. Molecular epidemiology of bovine Babesia spp. and Theileria orientalis parasites in beef cattle from northern and northeastern Thailand. Parasitology International, 65, 62–69. [Google Scholar]
  23. Jongejan F, Uilenberg G. 2004. The global importance of ticks. Parasitology, 129, S3–S14. [CrossRef] [PubMed] [Google Scholar]
  24. Johansson M, Mysterud A, Flykt A. 2020. Livestock owners’ worry and fear of tick-borne diseases. Parasites & Vectors, 13, 331. [Google Scholar]
  25. Kim C, Iseki H, Herbas MS, Yokoyama N, Suzuki H, Xuan X, Fujisaki K, Igarashi I. 2007. Development of TaqMan-based real-time PCR assays for diagnostic detection of Babesia bovis and Babesia bigemina. American Journal of tropical Medicine and Hygiene, 77, 837–841. [Google Scholar]
  26. Liu A, Guan G, Du P, Gou H, Liu Z, Liu J, Ma M, Yang J, Li Y, Niu Q, Ren Q, Bai Q, Yin H, Luo J. 2012. Loop-mediated isothermal amplification (LAMP) method based on two species-specific primer sets for the rapid identification of Chinese Babesia bovis and B. bigemina. Parasitology International, 61, 658–663. [Google Scholar]
  27. Liu J, Yin H, Liu G, Guan G, Ma M, Liu A, Liu Z, Li Y, Ren Q, Dang Z, Gao J, Bai Q, Zhao H, Luo J. 2008. Discrimination of Babesia major and Babesia ovata based on ITS1-5.8S-ITS2 region sequences of rRNA gene. Parasitology Research, 102, 709–713. [Google Scholar]
  28. Liu Y. 2021. PyHRM. Available at: https://github.com/liuyigh/PyHRM. Accessed 11 September 2024. [Google Scholar]
  29. Ma Y, Jian Y, Wang G, Li X, Wang G, Hu Y, Yokoyama N, Ma L, Xuan X. 2024. Molecular identification of Babesia and Theileria infections in livestock in the Qinghai- Tibetan Plateau area, China. Animals, 14, 476. [Google Scholar]
  30. McKinney W. 2010. Data structures for statistical computing in python, in: Proceedings of the 9th Python in Science Conference (SCIPY 2010), pp. 51–56. [Google Scholar]
  31. Messing J. 1983. New M13 vectors for cloning. Methods in Enzymology, 101, 20–78. [Google Scholar]
  32. Mosqueda J, Olvera-Ramirez A, Aguilar-Tipacamu G, Canto GJ. 2012. Current advances in detection and treatment of babesiosis. Current Medicinal Chemistry, 19, 1504–1518. [Google Scholar]
  33. Mukhebi AW, Perry BD, Kruska R. 1992. Estimated economics of theileriosis control in Africa. Preventive Veterinary Medicine, 12, 73–85. [Google Scholar]
  34. Navarro E, Serrano-Heras G, Castaño MJ, Solera J. 2015. Real-time PCR detection chemistry. Clinica Chimica Acta, 439, 231–250. [Google Scholar]
  35. Onuma M, Kakuda T, Sugimoto C. 1998. Theileria parasite infection in East Asia and control of the disease. Comparative Immunology, Microbiology and Infectious Diseases, 21, 165–177. [Google Scholar]
  36. Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, Vanderplas J, Passos A, Cournapeau D, Brucher PM, Duchesnay E. 2011. Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12, 2825–2830. [Google Scholar]
  37. Poolkhetkit S, Chowattanapon W, Sungpradit S, Changbunjong T. 2015. Molecular detection of blood protozoa in ticks collected from cattle in the buffer zone of Sai Yok National Park, Thailand. Thai Journal of Veterinary Medicine, 45, 619–625. [Google Scholar]
  38. Prado ICB, Capuno LXBJr., Collera PD, Cabralda APD, De Ramos KAS, Bernardo JMG, Divina BP, Masatani T, Tanaka T, Galay RL. 2022. Molecular detection and characterization of Babesia and Theileria in cattle and water buffaloes from southern Luzon, Philippines. Microorganisms, 10, 678. [Google Scholar]
  39. Rakwong P, Keawchana N, Ngasaman R, Kamyingkird K. 2022. Theileria infection in bullfighting cattle in Thailand. Veterinary World, 15, 2917–2921. [Google Scholar]
  40. R Core Team. 2020. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation fo Statistical Computing. Available at: http://www.R-project.org. Accessed 13 September 2024. [Google Scholar]
  41. R Studio Team. 2024. RStudio: Integrated Development for R. Boston, MA: RStudio, Inc. Available at: http://www.rstudio.com. Accessed 22 February 2024. [Google Scholar]
  42. Roy BC, Estrada-Peña A, Krücken J, Rehman A, Nijhof AM. 2018. Morphological and phylogenetic analyses of Rhipicephalus microplus ticks from Bangladesh, Pakistan and Myanmar. Ticks and Tick-Borne Diseases, 9, 1069–1079. [Google Scholar]
  43. Sarataphan N, Kakuda T, Chansiri K, Onuma M. 2003. Survey of benign Theileria parasites of cattle and buffaloes in Thailand using allele-specific polymerase chain reaction of major piroplasm surface protein gene. Journal of Veterinary Medical Science, 65, 133–135. [Google Scholar]
  44. Seerintra T, Krinsoongnern W, Thanchomnang T, Piratae S. 2024. Molecular occurrence and genetic identification of Babesia spp. and Theileria spp. in naturally infected cattle from Thailand. Parasitology Research, 123, 287. [Google Scholar]
  45. Simking P, Saengow S, Bangphoomi K, Sarataphan N, Wongnarkpet S, Inpankaew T, Jittapalapong S, Munkhjargal T, Sivakumar T, Yokoyama N, Igarashi I. 2013. The molecular prevalence and MSA-2b gene-based genetic diversity of Babesia bovis in dairy cattle in Thailand. Veterinary Parasitology, 197, 642–648. [Google Scholar]
  46. Slodki J, Jasik K, Kępa M, Idzik D, Wojtyczka R. 2011. Tick-transmitted diseases caused by Apicomplexa. Acta Protozoologica, 50, 155–161. [Google Scholar]
  47. Srionrod N, Nooroong P, Poolsawat N, Minsakorn S, Watthanadirek A, Junsiri W, Sangchuai S, Chawengkirttikul R, Anuracpreeda P. 2022. Molecular characterization and genetic diversity of Babesia bovis and Babesia bigemina of cattle in Thailand. Frontiers in Cellular and Infection Microbiology, 12, 1065963. [Google Scholar]
  48. Suarez CE, Laughery JM, Schneider DA, Sondgeroth KS, McElwain TF. 2012. Acute and persistent infection by a transfected Mo7 strain of Babesia bovis. Molecular and Biochemical Parasitology, 185, 52–57. [Google Scholar]
  49. Tanskul P, Inlao I. 1989. Keys to the adult ticks of Haemaphysalis Koch, 1844, in Thailand with notes on changes in taxonomy (Acari: Ixodoidea: Ixodidae). Journal of Medical Entomology, 26, 573–600. [Google Scholar]
  50. Thinnabut K, Rodpai R, Sanpool O, Maleewong W, Tangkawanit U. 2023. Genetic diversity of tick (Acari: Ixodidae) populations and molecular detection of Anaplasma and Ehrlichia infesting beef cattle from upper-northeastern Thailand. Infection, Genetics and Evolution, 107, 105394. [Google Scholar]
  51. Thinnabut K, Rodpai R, Sanpool O, Maleewong W, Tangkawanit U. 2024. Detection of Theileria in cattle ticks (Rhipicephalus microplus) (Canestrini, 1888) in upper-northeastern Thailand. Acta Tropica, 260, 107452. [Google Scholar]
  52. Walker AR. 2003. Ticks of domestic animals in Africa: a guide to identification of species. Vol. 74. Edinburgh: Bioscience Reports [Google Scholar]
  53. Wang J, Yang J, Gao S, Liu A, Rashid M, Li Y, Liu Z, Liu J, Liu G, Luo J, Guan G, Yin H. 2020. Rapid detection and differentiation of Theileria annulata, T. orientalis and T. sinensis using high-resolution melting analysis. Ticks and Tick-Borne Diseases, 11, 101312. [Google Scholar]

Cite this article as: Kyaw MT, Janwan P, Thanchomnang T, Rodpai R, Tangkawanit U, Boonroumkaew P, Sadaow L, Intapan PM, Maleewong W & Sanpool O. 2025. Development and validation of a real-time SYBR green PCR method for the detection and differentiation of Babesia and Theileria species (Apicomplexa: Piroplasmida) in hard ticks and cattle blood from Thailand. Parasite 32, 54. https://doi.org/10.1051/parasite/2025040.

All Figures

thumbnail Figure 1

Standard curve of plasmid DNA dilutions (105–1 copies/μL): a) B. bigemina, b) B. bovis, c) T. annulata, d) T. orientalis, and e) T. sinensis.
In the text
thumbnail Figure 2

Melting-curve analysis of Babesia and Theileria species: a) Normalized melting curves, and b) Difference curves of Babesia spp. (Cytb gene) (plasmid controls), c) Normalized melting curves, and d) Difference curves of Babesia spp. (Cytb gene) (field samples compared with plasmid controls), e) Normalized melting curves, and f) Difference curves of Theileria spp. (18S rRNA gene) (plasmid controls), g) Normalized melting curves, and h) Difference curves of Theileria spp. (18S rRNA gene) (field samples compared with plasmid controls).
In the text
thumbnail Figure 3

Melting temperatures boxplot of plasmid control (3 replicates) and samples of a) Babesia spp., and b) Theileria spp. Statistically significant differences (Tukey’s HSD test, p < 0.05) are indicated in the figure with different letters; boxplot with the same letter indicates no statistical difference. Figure 3a), A: plasmid controls for B. bovis, B1: plasmid controls for B. bigemina, B2: positive samples for B. bigemina. Figure 3b), A1: plasmid control for T. sinensis, A2: positive samples for T. sinensis, B1: plasmid controls for T. orientalis, B2: positive samples for T. orientalis, C: plasmid control for T. annulata.
In the text

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