Introduction
Ticks (Acari: Ixodidae) are obligate haematophagous ectoparasites that play a central role in the transmission of a broad range of pathogens of medical, veterinary, and economic importance worldwide (Estrada-Peña et al., 2012). Among the bacterial pathogens associated with tick-borne diseases, species of the genera Rickettsia and Borrelia are well-established ixodid tick-borne bacteria, whereas Orientia tsutsugamushi, the causative agent of scrub typhus, is primarily transmitted by larval trombiculid mites (chiggers) (Madison-Antenucci et al., 2020; Seidi et al., 2024). The spotted fever group (SFG) Rickettsia comprises a suite of obligate intracellular α-proteobacteria transmitted primarily by ixodid ticks and responsible for a spectrum of febrile illnesses collectively referred to as spotted fever rickettsioses (Piotrowski and Rymaszewska, 2020).
Clinical manifestations range from mild febrile illness to severe, potentially fatal diseases characterised by fever, headache, rash, and in some cases, multi-organ dysfunction (Kelley et al., 2026). These pathogens are globally distributed wherever competent tick vectors and suitable reservoir hosts occur. SFG rickettsioses have been reported throughout the Asia-Pacific region, with molecular and seroepidemiological evidence from Malaysia and neighbouring countries.
Nevertheless, the diversity of SFG Rickettsia circulating in local tick populations remains poorly characterised (Chaorattanakawee et al., 2024; Kho et al., 2017; Tappe et al., 2019).
Spirochetes of the genus Borrelia include the causative agents of Lyme borreliosis and relapsing fever, two clinically distinct zoonotic diseases of public health importance. Recently, experts in Borrelia research have proposed genus Borrelia to consist of two subgenera: Borrelia and Borreliella, in which subgenera Borrelia exclusively contains species members causing relapsing fever, while Borreliella contains only species members causing Lyme borreliosis, formerly known as the Borrelia burgdorferi sensu lato complex (Margos et al., 2025). However, this taxonomic change has not yet been widely adopted by the scientific community.
To maintain clarity and avoid confusion, this work will refer to species members of both subgenera using the original (pre-2013) generic epithet Borrelia Swellengrebel 1907.
Relapsing fever Borrelia are transmitted by both hard and soft ticks and are characterised by recurrent febrile episodes resulting from antigenic variation (Talagrand-Reboul et al., 2018). In contrast, Lyme borreliosis is transmitted primarily by Ixodes ticks, and caused by species members within the Borrelia burgdorferi sensu lato complex (Mead, 2022). Evidence from Southeast Asia, including Malaysia, indicates that both Lyme disease-associated and relapsing fever-associated Borrelia circulate in wildlife, ticks, and rodent hosts.
Species such as Borrelia yangtzensis and Borrelia miyamotoi have been detected in Ixodes granulatus and small mammals, suggesting established enzootic transmission cycles with potential zoonotic implications (Khoo et al., 2018; Lau et al., 2020). Despite an increasing understanding of tick diversity in Malaysia and sporadic reports of tick-associated pathogens, comprehensive surveillance of Rickettsia, Borrelia, and O. tsutsugamushi across multiple tick species and ecological settings remains limited. Consequently, the prevalence, diversity, and ecological distribution of these bacterial pathogens remain poorly understood (Lim et al., 2020; Mohd-Azami et al., 2023).
These knowledge gaps have significant public health implications, as undetected or under-recognised tick-borne pathogens may contribute to cases of undifferentiated febrile illness in humans and animals (Faccini-Martínez et al., 2022). Additionally, environmental heterogeneity and land-use change may alter tick–host–pathogen interactions, influencing the distribution of ticks and their associated pathogens across tropical landscapes (Shahzad et al., 2025; Yean et al., 2024). Although O. tsutsugamushi is primarily transmitted by larval trombiculid mites (chiggers), there have been previous reports of O. tsutsugamushi DNA detected in ixodid ticks (Govindarajan et al., 2024; M.
Zhang et al., 2013), therefore it was included in the screening panel to evaluate its occurrence alongside established tick-borne bacterial pathogens.
To address these knowledge gaps, this study aimed to conduct a broad molecular survey of ixodid ticks collected from diverse hosts across contrasting ecological habitats in Peninsular Malaysia to detect and characterize SFG Rickettsia, Lyme diseases- and relapsing fever-associated Borrelia and scrub typhus-associated O. tsutsugamushi. Specifically, we sought to (i) estimate pathogen detection rates in pooled tick samples and (ii) describe patterns of pathogens detection across tick species and habitat types.
Materials and methods
Research approvals
Host trapping, immobilization via intramuscular anesthesia, and comprehensive physical examinations for tick collection were executed according to ethical and research approvals granted by the Malaysian Department of Wildlife and National Parks (approval nos. JPHL and TN [IP]: 100-34/1.24 Jld 16 and 100-34/1.24 Jld 19) and the Universiti Malaya Institutional Animal Care and Use Committee (approval no. T/22052023/1303202 3-02/R).
Study sites
Fig. 1 presents the map of the study locations involved in the tick collection from wild and domestic animals in Peninsular Malaysia. On-host ticks were collected from nine locations across Peninsular Malaysia between June 2022 and November 2023, encompassing three habitats: marginalized areas, oil palm plantations, and natural forests in four biogeographic regions: the north, south, east, and centre of Peninsular Malaysia (Table 3).Fig.
1Locations of the study sites across three ecological habitat types in Peninsular Malaysia and the distribution of Rickettsia- and Borrelia-positive tick pools detected in this study.
Host trapping and examination
List of animals examined for ticks is shown in Table 3. Wild animal hosts including wild boars and small mammals, and domestic hosts (cattle and galliformes) were trapped, handled and examined for tick infection in accordance with the methods detailed in a previous study in Husin et al. (2026a, 2026b).
Tick collection, identification and pooling strategy
All ticks were morphologically identified to species level using a NIKON SMZ200 stereomicroscope and compound microscope following established taxonomic keys (Tanskul and Inlao, 1989; Voltzit and Keirans, 2002; Yamaguti et al., 1971). Ticks from the same individual host were identified up to species level, and further grouped to same species and life stages (i.e. larva, nymph, adult). Each group contained 5-10 ticks of the same species and life stage collected from the same individual host, that were then labelled with specific pool numbers, and further subjected to DNA extraction.
This method aims to optimise DNA screening efficiency and maximise DNA detection sensitivity for pathogens expected to occur at low prevalence (<5–10%) while additionally minimising the financial and logistical burden of individual screening (Muñoz-Zanzi et al., 2000). Pooling concentrates template DNA from multiple specimens into a single PCR reaction, thereby increasing the probability of detecting low-intensity infections (Hepp et al., 2018; Sutherland and Nasci, 2007); however, this strategy precludes precise estimation of true individual-level prevalence, a trade-off critically evaluated in the discussion section.
Genomic DNA extraction
Prior to genomic DNA extraction, pooled ticks underwent surface decontamination in 70% ethanol, two sequential washes in sterile distilled water, and air-drying on sterile filter paper. Each pool was then suspended in phosphate-buffered saline (PBS) before being mechanically homogenised using Precellys® Lysing Kit (hard tissue grinding MK28) (Bertin Technologies, Montigny-le-Bretonneux, France) using Precellys® Evolution homogenizer (Bertin Instruments, France) until a uniform suspension was obtained. Genomic DNA was extracted and purified using Macherey-Nagel Nucleospin Tissue Kit (Macherey-Nagel, Düren, Germany) according to the manufacturer's specifications, with a modified final elution volume of 60 μL to maximise DNA yield.
Purified DNA was preserved at −20 °C pending molecular analysis.
PCR amplification
PCR primer sets, target genes, nucleotide sequences, expected amplicon sizes, and references used for the molecular detection of Rickettsia spp., Borrelia spp., and Orientia tsutsugamushi as shown in Table 1. All thermal cycling conditions used in this study are detailed in Table 2. PCR-based molecular detection is an established approach for identifying Rickettsia and Borrelia in vector surveillance studies (Arai et al., 2021; Chisu et al., 2018; Enríquez et al., 2024; Jiang et al., 2021; Kaenkan et al., 2020; Khan et al., 2023).
Among the genetic markers used, gltA, ompA, and ompB are widely employed in the molecular characterization and detection of Rickettsia spp. (Kho et al., 2017; Mohamad Tahir et al., 2025; X. Zhang et al., 2018), while flaB and rrs are commonly used targets for the detection and characterization of Borrelia spp.
(Lau et al., 2020; Soliman et al., 2025).Table 1PCR primer sets, target genes, nucleotide sequences, expected amplicon sizes, and references used for the molecular detection of Rickettsia spp., Borrelia spp., and Orientia tsutsugamushi in ixodid ticks collected from contrasting habitats in Peninsular Malaysia.Bacterial organismTarget genePrimerNucleotide sequence (5’ – 3′)Amplicon size (bp)ReferenceRickettsia spp.gltACS239FGCTCTTCTCATCCTATGGCTATTAT834Labruna et al. (2004)CS1069RCAGGGTCTTCGTGCATTTCTTompARr.190.70 pFATGGCGAATATTTCTCCAAAA542Regnery et al. (1991)Rr.190.602nRAGTGCAGCATTCGCTCCCCCTompB120-2788FAAACAATAATCAAGGTACTGT816Roux and Raoult (2000)120-3599RTACTTCCGGTTACAGCAAAGTBorrelia spp.rrsBF1FGCTGGCAGTGCGTCTTAAGC1395Roux and Raoult (1999)BR1RGCTTCGGGTATCCTCAACTCflaBBflaPADF1GATCARGCWCAAYATAACCAWATGCA800Lau et al.
(2020)BflaPDUR1AGATTCAAGTCTGTTTTGGAAAGCBflaPBUF2GCTGAAGAGCTTGGAATGCAACC345BflaPCRR2TGATCAGTTATCATTCTAATAGCAOrientia tsutsugamushiTSA47Ot-145FF1ACAGGCCAAGATATTGGAAG871Masakhwe et al. (2018)Ot-1780RR1AATCGCCTTTAAACTAGATTTACTTATTAOt-263FF2GTGCTAAGAAARGATGATACTTC850Ot-1133RR2ACATTTAACATACCACGACGAATFForward primer; Rreverse primer; 1first reaction; 2 s reaction.Table 2Oligonucleotide targets and thermal cycling conditions utilized for the molecular screening of Rickettsia, Borrelia, and Orientia species.Target geneInitial denaturation (°C, duration)Denaturation (°C, duration)Annealing (°C, duration)Extension (°C, duration)Final extension (°C, duration)CyclesReferencegltA95, 3 min95, 15 s48, 30 s72, 30 s72, 7 min40Labruna et al. (2004)ompA95, 3 min95, 15 s48, 30 s72, 30 s72, 7 min40Regnery et al.
(1991),Labruna et al. (2004)ompB95, 3 min95, 30 s50, 30 s68, 1 min 30 s68, 7 min40Roux and Raoult (2000)rrs95, 3 min95, 30 s55, 30 s72, 1 min72, 7 min40Roux and Raoult (1999)flaba94, 10 min94, 40 s52, 30 s72, 1 min72, 7 min32Lau et al. (2020)flabb94, 10 min94, 40 s50, 30 s72, 1 min72, 7 min35Lau et al.
(2020)TSA4795, 2 min94, 30 s54, 30 s68, 2 min72, 7 min40Masakhwe et al. (2018)aFirst reaction.bSecond reaction.Table 3Summary of ixodid tick pools and PCR detection results for Rickettsia, Borrelia, and Orientia tsutsugamushi. Tick pools are categorized by species, life stage, host, and habitat.
Detection outcomes are indicated as positive (+ve) or negative (−).Pool no.Tick speciesPool sizeLife stageHost (ID code)SiteaHabitat typePathogen screeningRickettsia spp.Borrelia spp.O. tsutsugamushiTP1A. cordiferum10LarvaMaxomys surifer (R08)PRNatural forest---TP2A. cordiferum10LarvaTupaia glis (R14)PRNatural forest---TP3A. cordiferum10LarvaTupaia glis (R15)PRNatural forest---TP4A. cordiferum10LarvaLeopoldamys sabanus (R19)PRNatural forest---TP5A. cordiferum10LarvaLeopoldamys sabanus (R27)PRNatural forest-+ve-TP6A. cordiferum10LarvaRattus tiomanicus (R58)RINatural forest (Island)---TP32A. cordiferum9LarvaMaxomys surifer (R37)PRNatural forest---TP43A. cordiferum7LarvaMaxomys surifer (R07)PRNatural forest---TP44A. cordiferum7LarvaMaxomys surifer (R29)PRNatural forest---TP45A. cordiferum7LarvaTupaia glis (R40)PRNatural forest---TP48A. cordiferum6LarvaLeopoldamys sabanus (R13)PRNatural forest+ve--TP55A. cordiferum5LarvaLeopoldamys sabanus (R11)PRNatural forest---TP56A. cordiferum5LarvaTupaia glis (R32)PRNatural forest---TP33D. auratus9Adult maleSus scrofa (WB07)PRLMarginalized+ve--TP46D. auratus7Adult femaleSus scrofa (WB07)PRLMarginalized+ve--TP49D. auratus6Adult maleSus scrofa (WB08)PRLMarginalized---TP7H. hystricis10LarvaGallus gallus (JF03)PRNatural forest---TP8H. hystricis10LarvaPolyplectron malacense (B07)PRNatural forest-+ve-TP10H. hystricis10LarvaPolyplectron malacense (B11)PRNatural forest---TP50H. hystricis6LarvaLeopoldamys sabanus (R13)PRNatural forest---TP57H. hystricis5NymphLophura erythrophthalma (B08)PRNatural forest---TP58H. hystricis5LarvaLophura erythrophthalma (B09)PRNatural forest---TP59H. nadchatrami5Adult femaleSus scrofa (WB04)KDHMarginal---TP60H. nadchatrami5NymphSus scrofa (WB05)KDHMarginal---TP9H. semermis10LarvaPolyplectron malacense (B10)PRNatural forest---TP11Haemaphysalis sp.10LarvaLeopoldamys sabanus (R27)PRNatural forest---TP12H. wellingtoni10Adult maleGallus gallus (CH04)UMPOil palm plantation---TP13H. wellingtoni10Adult maleGallus gallus (CH05)UMPOil palm plantation---TP14H. wellingtoni10NymphGallus gallus (CH05)UMPOil palm plantation---TP15H. wellingtoni10LarvaGallus gallus (CH08)UMPOil palm plantation---TP16H. wellingtoni10Adult maleGallus gallus (CH10)UMPOil palm plantation---TP17H. wellingtoni10NymphGallus gallus (CH10)UMPOil palm plantation---TP18H. wellingtoni10LarvaGallus gallus (CH10)UMPOil palm plantation---TP19H. wellingtoni10NymphGallus gallus (CH11)UMPOil palm plantation---TP20H. wellingtoni10Adult maleGallus gallus (CH12)UMPOil palm plantation---TP21H. wellingtoni10NymphGallus gallus (CH12)UMPOil palm plantation---TP22H. wellingtoni10Adult maleGallus gallus domesticus (CH08)TLKMarginal---TP23H. wellingtoni10Adult maleGallus gallus domesticus (CH10)TLKMarginal---TP24H. wellingtoni10Adult maleGallus gallus domesticus (CH12)TLKMarginal---TP25H. wellingtoni10Adult maleGallus gallus domesticus (CH16)TLKMarginal---TP26H. wellingtoni10Adult maleGallus gallus domesticus (CH18)TLKMarginal---TP27H. wellingtoni10NymphGallus gallus domesticus (CH06)TMRMarginal---TP28H. wellingtoni10LarvaGallus gallus (JF02)PRNatural forest---TP29H. wellingtoni10LarvaPolyplectron malacense (B11)PRNatural forest---TP30H. wellingtoni10LarvaGallus gallus domesticus (CH06)TMRMarginal---TP34H. wellingtoni9Adult maleGallus gallus (CH11)UMPOil palm plantation---TP35H. wellingtoni9Adult maleGallus gallus domesticus (CH09)TLKMarginal---TP36H. wellingtoni8Adult maleGallus gallus (CH02)UMPOil palm plantation---TP37H. wellingtoni8Adult maleGallus gallus (CH07)UMPOil palm plantation---TP38H. wellingtoni8Adult maleGallus gallus domesticus (CH02)TLKMarginal---TP39H. wellingtoni8Adult maleGallus gallus domesticus (CH04)TLKMarginal---TP40H. wellingtoni8LarvaPolyplectron malacense (B07)PRNatural forest---TP47H. wellingtoni7Adult maleGallus gallus (CH03)UMPOil palm plantation---TP51H. wellingtoni6Adult maleGallus gallus domesticus (CH15)TLKMarginal---TP52H. wellingtoni6Adult maleGallus gallus domesticus (CH17)TLKMarginal---TP53H. wellingtoni6NymphGallus gallus domesticus (CH09)KLTMarginal---TP54H. wellingtoni6NymphGallus gallus domesticus (CH13)KLTMarginal---TP61H. wellingtoni5Adult maleGallus gallus domesticus (CH13)TLKMarginal---TP62H. wellingtoni5Adult maleGallus gallus domesticus (CH15)KLTMarginal---TP63H. wellingtoni5NymphGallus gallus (CH08)UMPOil palm plantation---TP64H. wellingtoni5LarvaGallus gallus (CH11)UMPOil palm plantation---TP65H. wellingtoni5LarvaGallus gallus (CH17)UMPOil palm plantation---TP31I. granulatus10NymphCrocidura malayana (R61)RINatural forest (Island)---TP41I. granulatus8Adult femaleLeopoldamys sabanus (R55)TIONatural forest (Island)-+ve-TP42I. granulatus8Adult femaleLeopoldamys sabanus (R57)TIONatural forest (Island)-+ve-TP66Rh. microplus5Adult femaleBos taurus (BT2)KDHMarginal---aPR = Pasir Raja Forest Reserve, Terengganu; RI = Redang Island, Terengganu; UMP = UM Plantations Kota Tinggi, Johor; TLK = Teluk Intan, Perak; TMR = Temerloh, Pahang; TIO = Tioman Island, Pahang; PRL = Padang Besar, Perlis; KLT = Tanah Merah, Kelantan; KDH = Kuala Muda, Kedah; +ve = PCR-positive.
All PCR assays were performed in 25 μL reactions containing 12.5 μL DreamTaq Green PCR Master Mix (Thermo Scientific, Massachusetts, USA), 1 μL of each primer (10 μM), 8.5 μL molecular-grade water, and 2 μL DNA template, unless specified otherwise. A positive control consisting of reference DNA previously confirmed to contain the respective target pathogen, while nuclease-free water was included as a negative control, were included in each PCR assay to verify amplification efficiency and the integrity of the PCR reagents. All PCR amplicons (5 μL) were electrophoresed on 1.0% agarose gels in 1 ×Tris-acetate-EDTA (TAE) buffer, stained with FloroSafe DNA Stain (1st BASE, Axil Scientific, Singapore) and visualized under blue light, with molecular weight markers (Thermo Fisher Scientific, Shah Alam, Malaysia) for size estimation.
Detection of Rickettsia spp
Initial molecular screening for Rickettsia spp. was performed by amplifying an 871-bp fragment of the gltA gene utilizing the CS239 and CS1069 primer pair, following the cycling conditions described by Labruna et al. (2004) (Table 1). To ensure robust species-level identification, all gltA-positive samples were subsequently subjected to multi-locus characterization targeting the ompA (542 bp) and ompB (816 bp) genes.
The ompA assay deployed primers Rr190.70p and Rr190.602n (Regnery et al., 1991) in a 25-μL reaction volume containing 5 μL of template DNA, adhering to the protocol by Labruna et al. (2004). The ompB gene was amplified using primers 120-2788 and 120-3599 (Roux and Raoult, 2000) in a 25-μL reaction containing 0.5 μL of each primer and 2.5 μL of template DNA.
Each assay included positive control of DNA from R. raoultii (strain Bialystok1) cultured in BME/CTVM23 cells (Palomar et al., 2019).
Detection of Borrelia spp
Detection of Borrelia spp. was initiated using nested PCR targeting a 345-bp fragment of the flaB gene, as described by Lau et al. (2020). The primary amplification employed primers BflaPAD and BflaPDU in a 25-μL reaction volume containing 4.0 μL of template DNA.
The secondary amplification utilized primers BflaPBU and BflaPCR in a 50-μL reaction, using 5 μL of the primary PCR amplicon as the template. To ensure robust multi-locus characterization, all flaB-positive samples were subsequently screened for the 16S rRNA-encoding gene (rrs, 1395 bp) using primers BF1 and BR1 (Roux and Raoult, 1999) in a 25-μL reaction volume, following the protocol outlined by Soliman et al. (2025).
Thermal cycling conditions for all assays were performed as detailed in Table 2.
Detection of Orentia tsutsugamushi spp
For Orientia tsutsugamushi detection, a nested PCR was performed using species-specific primers targeting the 850 bp TSA47 gene, following the protocol of Masakhwe et al. (2018). Primer pairs Ot-145F and Ot-1780R were used in the first reaction and Ot-263F and Ot-1133R in the second reaction.
Positive control DNA (isolated from liver and lung tissues of O. tsutsugamushi-infected rodents) and negative control of nuclease-free water were included in each run.
DNA sequencing and sequence homology
Following amplification, PCR products were electrophoresed on agarose gels and visualized under ultraviolet illumination. Samples yielding distinct bands of the expected molecular sizes were considered positive for target bacterial DNA and subsequently submitted as unpurified amplicons for bi-directional Sanger sequencing (Apical Scientific Sdn. Bhd., Selangor, Malaysia).
The resulting nucleotide sequences were trimmed using Sequence Scanner v2.0 (Applied Biosystems, CA, USA), and consensus sequences were assembled in MEGA12 v12.1 (Kumar et al., 2024). Species identification and sequence homology evaluations were performed by comparing the generated consensus sequences against reference entries in the NCBI GenBank database using the BLASTn algorithm.
Sequence characterization
To evaluate sequence homology and visualize species clustering for biological identification, phylogenetic trees were constructed. Nucleotide sequences were aligned using the MUSCLE algorithm in MEGA12. Maximum likelihood (ML) trees were generated utilizing the Tamura 3-parameter substitution model with a discrete Gamma distribution and invariant sites (T92+G+I), which was identified as the optimal substitution model.
For the ompB alignment, the model was applied without the Gamma distribution (T92+I). The topological reliability of the constructed trees was assessed via bootstrap analysis with 1000 replicates.
Data analysis
Pool positivity rate (PPR), referring to the ratio of the number of positive pools to the total number of pools tested, was calculated for each pathogen successfully detected. Estimating positivity rates using minimum infection rate (MIR) method was deemed inaccurate and statistically weak, given the study's low detection rates (<10%) and small sample size (n < 100) (Fracasso et al., 2023; Matsui et al., 2026). Instead, maximum likelihood estimation (MLE) was calculated, taking into account varied pool sizes and uncertainty levels (95% confidence intervals) for both Rickettsia and Borrelia using the R package “PoolTestR” (McLure et al., 2020).
Results
Detection of bacterial pathogens in ticks
Of the 539 ixodid ticks (representing nine species) screened across 66 pools, Rickettsia DNA was detected in 4.5% (3/66) of the pools, and Borrelia DNA was detected in 6.1% (4/66) of the pools. Orientia tsutsugamushi was not detected in any samples (Table 3). To account for variable pool sizes, estimated infection rates were calculated using Maximum Likelihood Estimation (MLE).
The MLE for Rickettsia was 0.57% (95% CI: 0.14–1.46%), and the MLE for Borrelia was 0.77% (95% CI: 0.24–1.77%).
Rickettsia-positive pools originated from Dermacentor auratus (n = 2) and Amblyomma cordiferum (n = 1). Borrelia-positive pools originated from A. cordiferum (n = 1), Haemaphysallis hystricis (n = 1), and Ixodes granulatus (n = 2). None of the targeted bacterial pathogens were detected in H. semermis, H. wellingtoni, H. nadchatrami, or Rhipicephalus microplus, nor were any detected in ticks collected from oil palm plantations.
Notably, while initial molecular screening of the flaB gene confirmed the presence of Borrelia in four pools, subsequent amplification targeting the rrs gene was unsuccessful; this discrepancy is addressed in the Discussion.
Identification of Rickettsia spp. and Borrelia spp. genospecies
BLASTn maximum identities of Rickettsia spp. amplified from tick pools by gltA, ompA, and ompB genes is shown in Table 4. Initial BLASTn analysis of the partial gltA sequences revealed 100% nucleotide identity with an uncharacterized Rickettsia sp. previously detected in a Thai Dermacentor steini tick, as well as with R. aeschlimannii from Russia. Multi-locus characterization of one positive sample (TP48) yielded partial ompA and ompB sequences exhibiting 99.04–99.37% identity to Candidatus Rickettsia laoensis from India and R. aeschlimannii from China.Table 4BLASTn maximum identities of Rickettsia spp. amplified from tick pools by gltA, ompA, and ompB genes.Sample ID.Tick species (Site)BLAST analysis (Accession no.)gltAompAompBTP33Dermacentor auratus (Perlis)100% Rickettsia sp. isolate KY455 (OR523931.1)--TP46Dermacentor auratus (Perlis)100% Rickettsia sp. isolate KY455 (OR523931.1)--TP48Amblyomma cordiferum (Pasir Raja Forest Reserve)100% Rickettsia aeschlimannii isolate Kalmykia-20 (OR687023.1)99.04% Ca.
Rickettsia laoensis isolate MIVLW5/2017 (MK905250.1)99.37% Rickettsia aeschlimannii isolate Xinjiang-CBCE (MF002557.1)
Sequence analysis of the Borrelia-positive samples revealed notable genetic diversity. Sample TP5 exhibited 98.81% nucleotide identity to B. valaisiana (GenBank accession no. AB091710.1) from Japan, while TP8 shared 98.71% identity with B. theileri (PV389468.1) from South Korea.
Furthermore, TP41 demonstrated 100% identity to Borrelia sp. UM-SNI18 (OP375132.1), previously identified in a Malaysian Rattus tanezumi, and TP42 showed 98.95% identity to B. yangtzensis (LC572308.1) from a Malaysian Ixodes granulatus. All sequences generated in this study were deposited in the GenBank database under accession numbers QB148865–QB148867 (Rickettsia gltA) and QB148868–QB148871 (Borrelia flaB).
Sequence homology and species clustering
To visualize sequence homology and support biological species identification, sequence clustering was evaluated for the detected pathogens. Based on gltA sequence analysis, samples TP33 and TP46 clustered with ancestral group (AG) rickettsiae alongside Rickettsia bellii. Conversely, sample TP48 clustered with the spotted fever group (SFG), demonstrating close sequence homology to R. rhipicephali and R. aeschlimannii (Fig.
2). The clustering of TP48 ompA and ompB partial sequences corroborated this biological identification, grouping the sample tightly with SFG members R. aeschlimannii, R. rhipicephali, and R. massiliae (Fig. 3, Fig.
4).Fig. 2Identification of Rickettsia sp. using maximum likelihood (ML) phylogenetic tree based on 871 bp region of rickettsial citrate synthase (gltA) gene. Reference sequences are included with accession numbers, followed by species, strain, and geographic origin.
Sequences obtained from this study are indicated by bold type, with labels beginning with pool ID, then tick species, host species, and collection site. Bootstrap values above 75% are indicated below branches.Fig. 3Maximum likelihood (ML) phylogenetic tree based on 542 bp region of rickettsial outer membrane protein A (ompA) gene.
Reference sequences are included with accession numbers, followed by species, strain, and geographic origin. The sequence obtained from this study is indicated by bold type, with label beginning with pool ID, then tick species, host species, and collection site. Bootstrap values above 75% are indicated below branches.
Rickettsia felis (Accession no. FJ157325) was used as the outgroup.Fig. 4Maximum likelihood (ML) phylogenetic tree based on 816 bp region of rickettsial outer membrane protein B (ompB) gene.
Reference sequences are included with accession numbers, followed by species, strain, and geographic origin. The sequence obtained from this study is indicated by bold font, with label beginning with pool ID, then tick species, host species, and collection site. Bootstrap values above 75% are indicated below branches.
Rickettsia prowazekii (AF123718) was used as the outgroup.
Borrelia sequences segregated into two primary similarity groups, consistent with established classifications (Adeolu and Gupta, 2014). Three specimens (TP5, TP41, and TP42) clustered with species belonging to the Lyme disease complex, with TP41 grouping closely alongside a previously characterized Malaysian Borrelia sp. isolate. In contrast, sample TP8 clustered unequivocally with the relapsing fever group, exhibiting the highest sequence homology to B. theileri strains from East Asia (Fig.
5).Fig. 5Identification of Borrelia sp. using maximum likelihood (ML) phylogenetic tree based on the 345 bp region of borrelial flagellin B (flaB) gene. Reference sequences are included with accession numbers, followed by species, strain, and geographic origin.
Sequences obtained from this study are indicated by bold type, with labels beginning with pool ID, then tick species, host species, and collection site. Bootstrap values above 75% are indicated below branches. Treponema pallidum (Accession no.
CP004011) was used as the outgroup.
Discussion
This study provides molecular evidence for the circulation of spotted fever group (SFG) Rickettsia and both Lyme disease (LD)- and relapsing fever (RF)- Borrelia in ixodid ticks parasitizing wildlife across three ecologically distinct landscapes in Peninsular Malaysia: natural forests, marginal habitats, and oil palm plantations. Our findings substantiate earlier reports that tick-borne bacterial pathogens are enzootically maintained within wildlife-associated transmission networks across Southeast Asia (Chaorattanakawee et al., 2024; Lim et al., 2020; Low et al., 2022; Mohd-Azami et al., 2023).
The detection of SFG Rickettsia in Dermacentor auratus and Amblyomma cordiferum aligns with the established role of these genera as known vectors for rickettsial bacteria across the region (Chaloemthanetphong et al., 2023; Parola et al., 2003). Notably, two of the three Rickettsia-positive pools originated from ticks infesting Sus scrofa in marginal habitats, while the third was recovered from A. cordiferum parasitizing Leopoldamys sabanus in a primary forest reserve. The A. cordiferum detection is particularly noteworthy, as recent local surveys have identified this tick species on Tupaia glis and Lipaugus vociferans, with strict fidelity to forested environments (Husin et al., 2026a).
Sequence homology analysis placing this sample within the SFG, closely related to R. aeschlimannii and R. rhipicephali, adds to the growing body of evidence that genetically diverse SFG genospecies circulate in Southeast Asian tick populations (Chaorattanakawee et al., 2024; Takhampunya et al., 2021). However, the limited number of positive detections precludes robust inferences regarding vector competence, host specificity, or transmission efficiency, and these findings should be interpreted as hypothesis-generating rather than confirmatory.
Borrelia DNA was detected across a broader taxonomic range of tick genera (A. cordiferum, Haemaphysalis hystricis, and Ixodes granulatus) compared to Rickettsia, suggesting potentially wider ecological associations or differential host-seeking behaviors among borreliae. Sequence clustering identified three LD-associated Borrelia sequences (TP5, TP41, TP42) and one RF-associated Borrelia sequence (TP8), consistent with prior reports of co-circulating Borrelia lineages in Southeast Asia (Kazim et al., 2024). The detection of Borrelia sequences in I. granulatus is highly significant, as this tick species has been repeatedly implicated as an important vector of LD borreliae in the region (Chao et al., 2010; Khoo et al., 2018; Kuo et al., 2017; Lau et al., 2020).
The close sequence similarity of TP42 to B. yangtzensis strain IG-228, previously isolated from a Malaysian I. granulatus (Lau et al., 2020), further strengthens the association between this tick and LD-related spirochetes in Peninsular Malaysia. Likewise, the clustering of TP41 alongside a locally sourced Borrelia sp. from Johor (Mohd-Azami et al., 2023) may represent a geographically restricted strain endemic to Peninsular Malaysia. The presence of B. valaisiana (TP5), a taxon primarily associated with Ixodes spp. and suspected to carry pathogenic potential (Levin et al., 2026; Parola and Raoult, 2001), raises important questions regarding the zoonotic risks posed by these pathogens, particularly in areas where human–wildlife overlap is intensifying.
Notably, although four samples were positive for Borrelia via flaB-targeted PCR, subsequent amplification of the rrs gene was unsuccessful. Similar discrepancies were reported by Lau et al. (2020), who successfully obtained rrs sequences from only 50% of flaB-positive tick samples.
This discordance may reflect differences in amplicon length, as the targeted rrs fragment (1370 bp) is substantially longer than the partial flaB fragment (345 bp). Longer amplicons may be more susceptible to amplification failure due to DNA degradation, reduced template integrity, or primer-target mismatches.
The absence of Orientia tsutsugamushi DNA across all ixodid tick pools was anticipated, given that scrub typhus is predominantly transmitted by trombiculid mites (chiggers) rather than hard ticks (Elliott et al., 2019). While rare detections of Orientia in ixodid ticks have been reported (Govindarajan et al., 2024; Zhang et al., 2013), our findings reinforce the paradigm that ixodid ticks are unlikely to serve as primary vectors or significant reservoirs for this pathogen. Consequently, future scrub typhus surveillance in Malaysia should continue to prioritize chigger collections and rodent hosts, which constitute the classic epidemiological triad for this disease (Chen et al., 2025).
The detection of zoonotic bacterial agents in wildlife-associated ticks from both natural and marginal habitats has direct implications for public health. As urbanization and agricultural expansion continue to augment the human–wildlife interface, novel opportunities for pathogen spillover emerge (Jones et al., 2008). In Peninsular Malaysia, rural communities, agricultural workers, and recreational forest visitors are at potential risk of exposure to tick-borne pathogens (Kho et al., 2017; Lim et al., 2020).
The presence of SFG Rickettsia and LD/RF-associated Borrelia in ticks parasitizing peridomestic wildlife, such as Sus scrofa and synanthropic rodents, underscores the proximity of enzootic cycles to human settlements (Hotta et al., 2016). While clinical cases of spotted fever and borrelioses are sporadically reported in Malaysia, the true burden of these diseases is likely underdiagnosed due to limited clinical awareness and diagnostic capacity. Our findings highlight that tick-borne diseases should be routinely considered in the differential diagnosis of febrile illnesses in Malaysia, particularly among individuals with a history of outdoor activities or occupational exposure to peri-urban and forest-edge environments.
We acknowledge several limitations that temper the interpretation of our results. The use of pooled tick samples, while logistically efficient and widely employed in vector surveillance (Ramírez et al., 2018; Sutherland and Nasci, 2007), inherently constrains the estimation of true infection prevalence and may underestimate pathogen occurrence when infection rates are low. Furthermore, conventional and nested PCR were utilized as the primary methods for molecular detection; advanced techniques such as quantitative real-time PCR (qPCR) have demonstrated higher sensitivity and reliability for detecting Rickettsia (Zemtsova et al., 2015).
Additionally, the molecular markers used for the detection and biological characterization of Borrelia differ in their genetic stability and conservation (Fukunaga et al., 1996; Oshaghi et al., 2011). Although both flaB and rrs are standard targets for investigating Borrelia diversity, differences in primer–template compatibility may contribute to the discordant amplification observed between molecular targets. Despite these constraints, this study provides valuable baseline, hypothesis-generating data for a region where comprehensive tick-borne pathogen surveillance remains critically sparse.
To advance the understanding of tick-borne disease ecology in Malaysia, future research must prioritize several key directions. First, larger-scale, systematic surveys utilizing individual-level tick testing are essential to establish robust prevalence estimates and identify host–vector–pathogen associations with greater precision. Second, the integration of ecological data including host abundance, habitat fragmentation metrics, and microclimatic variables, will be critical for elucidating the environmental determinants of pathogen distribution.
Third, the application of high-throughput sequencing and metagenomics offers unprecedented opportunities to characterize the full spectrum of tick-associated microorganisms and investigate co-infection dynamics. Fourth, longitudinal studies across varying seasons and years are required to capture temporal variability in pathogen prevalence. Finally, translational research bridging vector surveillance, clinical microbiology, and public health policy is urgently needed to convert these findings into actionable diagnostic and preventive strategies.
Conclusion
This study presents molecular evidence for the presence of SFG Rickettsia and both LD- and RF-associated Borrelia in ixodid ticks from wildlife in Peninsular Malaysia, with distinct patterns of pathogen detection across the sampled habitats. While limited by the relatively small number of positive pools and the use of pooled samples, which precluded estimation of individual infection prevalence, our findings provide a critical foundation for future investigations and highlight the pressing need for comprehensive, multi-disciplinary surveillance to inform risk assessment and public health preparedness. As Southeast Asia continues to undergo profound land-use transformation, understanding the interplay between ecological change and pathogen emergence is not merely an academic pursuit, it is an imperative for safeguarding human and animal health in the region.
CRediT authorship contribution statement
Anis Suhaila Taufik: Writing – review & editing, Writing – original draft, Visualization, Methodology, Conceptualization. Nurul Aini Husin: Writing – review & editing, Writing – original draft, Visualization, Validation, Methodology, Data curation, Conceptualization. Auni Atikah AbdulHalim: Methodology, Data curation.
M. Haiqal Syarriman AbdulRahim: Data curation. Edley A.
Jiliun: Data curation. Mufasirin: Writing – review & editing. Poedji Hastutiek: Writing – review & editing.
Zubaidah Ya'cob: Writing – review & editing, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization.
Ethics declaration
This study was conducted in accordance with the following guidelines for animal welfare and/or reporting: Guide for the Care and Use of Laboratory Animals: Eighth Edition. (Washington, DC: The National Academies Press). This study was approved by the Universiti of Malaya Institutional Animal Care and Use Committee.
(Approval No. T/22052023/1303202 3-02/R). No human subjects were involved.
Data availability
Data supporting main conclusions of this study are included in the manuscript.
Funding
This research was supported by Dana Langganan Sukuk Pakej Rangsangan Ekonomi Prihatin Rakyat (SUKUK PRIHATIN), Malaysia Ministry of Finance through the Ministry of Higher Education, Malaysia, [sub-program MO002A-2021], as well as Universiti Malaya Research University (RU) Grant [grant code RU006-2025A].
Declaration of competing interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.