The bacterial microbiome and pathogen reservoir potential of Rhipicephalus sanguineus ticks in South Africa

doi:10.21203/rs.3.rs-5283012/v1

Download PDF

Research Article

The bacterial microbiome and pathogen reservoir potential of Rhipicephalus sanguineus ticks in South Africa

https://doi.org/10.21203/rs.3.rs-5283012/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background: Tick-borne bacterial pathogens from both domestic and wild animals play a significant role in the (re)emergence of human diseases. Primary tick endosymbionts have considerable influence on tick fitness and pathogen acquisition or transmission, while secondary endosymbionts are more likely to be pathogens. Rhipicephalus sanguineus is one of the most widespread tick species as they predominantly parasitise domestic dogs, though they have also been documented to feed on domestic animals and humans. This makes them ideal vectors of bacterial pathogens that can pose a significant threat to human health. Rhipicephalus sanguineus is host to a species-specific Coxiellaendosymbiont. Tick-borne pathogens and endosymbiotic bacteria can be studied through a targeted microbiome approach.

Methods: We utilised a 16S rRNA microbiome and amplicon sequence variant (ASV) approach to study the bacterial groups present in the midgut and salivary gland tissues of R. sanguineus ticks collected from dogs in a rural community in Bushbuckridge, Mpumalanga, South Africa, from 2016 to 2019.

Results: Post processing, we obtained 43,161 total sequence reads which were clustered into ASVs by sample year. After contaminants were removed there were ASVs belonging to seven genera: Coxiella, Anaplasma, Escherichia/Shigella, Ehrlichia, Borrelia, Rickettsia and Wolbachia. Coxiella endosymbionts dominated the microbiome. In 2017 Anaplasma was introduced to the microbiome and increased at the 2019 sampling. All other genera were present at low levels.

Conclusions: Our study highlights the changes in the microbiome of the R. sanguineus ticks over time. We found high numbers of two pathogenic Anaplasma species, A. platys and A. centrale, which cause disease in dogs and cattle, respectively, although A. platys infections in humans have been documented. With the exclusion of Wolbachia, the other detected genera could have pathogenic potential. Given our findings of pathogenic bacterial species, our study highlights the role that R. sanguineusmight play as a reservoir of pathogens.

Tick-borne

Bacterial microbiome

Anaplasma

Coxiella

Amplicon Sequence Variants

Zoonotic pathogens from domestic and wild animals are a leading cause of emerging and re-emerging diseases in humans [1]. Ticks, with their hematophagous feeding behaviours, wide host range, and global distribution are ideal vectors of zoonotic pathogens among animals and humans [2]. Analysing the bacterial microbiome of specific tissues like the midgut (MG) and salivary glands (SG) is an effective method for identifying tick-borne pathogens (TBPs) and endosymbionts [3]. Primary endosymbionts significantly impact tick fitness and survival and can influence TBP acquisition and transmission [4,5].

TBPs pose a substantial risk to rural South African communities at the interface between wildlife, livestock, and humans [1]. Rhipicephalus sanguineus, the dominant tick species on domestic dogs, is commonly found around human dwellings and can parasitize humans, as well as most vertebrate hosts [6]. This tick transmits several pathogens, including Ehrlichia canis [7], Babesia canis, Rickettsia conorii [8], Rickettsia rickettsii [9], and Rickettsia massiliae [10]. While R. sanguineus may potentially transmit Anaplasma platys, its vector competence is still under investigation [11]. Thus, R. sanguineus can significantly contribute to the spread of zoonotic diseases in rural communities.

A rural community situated within the eastern part of Bushbuckridge Local Municipality, Mpumalanga, South Africa, is at a wildlife-livestock-human interface. Surrounded by conservation areas, community members rely on subsistence farming, and most people own livestock [12]. Historically, research has focused on the impact of TBPs on livestock, with less attention on human health in rural areas [13]. Recent cases of non-malarial acute febrile illness (AFI) in the community highlight the need to document and discover the presence of pathogens [14].

In order to identify potential causes of AFI in this community, this study aimed to characterise the bacterial microbiome from the SG and MG tissues of R. sanguineus ticks collected from dogs in the community. A Pacific Biosciences (PacBio) circular consensus sequencing (CCS) approach was used to sequence the 16S rRNA gene and an amplicon sequence variant (ASV) pipeline was used for the analysis of the microbiome data.

Ethical Approvals

The following committees approved this project: the Faculty of Veterinary Science, University of Pretoria (UP) Research Ethics Committee (REC010-18), the UP Animal Ethics Committee (V012-18 and V064-16), and the UP Faculty of Humanities Research Ethics Committee (GW20180719HS). Permission was obtained to conduct the research, in terms of Section 20 of the Animal Diseases Act of 1984, from the Department of Agriculture, Land Reform and Rural Development (DALRRD) South Africa, with reference numbers 12/11/1/1/8 and 12/11/1/1.

Sample collection and genomic DNA extraction

The aim of the study was to understand how the bacterial microbiome of R. sanguineus could impact human health in a rural community. Ticks were collected from dogs in the eastern part of the Bushbuckridge local Municipality, Mpumalanga, South Africa, in 2016, 2017, and 2019. Dogs were sampled at random, with inclusion based on factors like the weight, health, hostility and owner presence. If multiple dogs were present at a household, all were examined for ticks. Ticks were collected using blunt forceps, focusing on male R. sanguineus ticks due to the degeneration of certain organs in engorged females [15]. Collected ticks were stored in a temperature and humidity-controlled chamber for two days to allow for digestion of their blood meal [3] at the Hans Hoheisen Wildlife Research Station. Ticks were morphologically identified using a tick identification key [16] and surface sterilized using a triple tick rinse [17]. Ten male R. sanguineus ticks per dog were dissected using surface sterilized tweezers and Hyde single-edged razor blades (Hyde, Massachusetts, United States) [17]. The 10 SGs comprised one pool, while the 10 MGs comprised a second pool. Each pool was placed into a storage solution with Cell Lysis Solution (Qiagen, Valencia, CA) and proteinase K (1.25 mg/mL) (Thermo Fisher Scientific, Massachusetts, USA), and genomic DNA was extracted using the PureGene Extraction kit (Qiagen) according to the manufacturer’s specifications.

PCR and sequencing

The 16S rRNA gene (V1-V8) was amplified in triplicate, using modified universal barcoded 16S rDNA primers; 27F (5’-AGA GTT TGA TCM TGG CTC AGA ACG-3’) and 1435R (5’-CGA TTA CTA GCG ATT CCR RCT TCA-3’) [3], targeting an ~ 1300 bp region. In 2016–2017 amplification was performed with Platinum Pfx, following the protocol outlined by Gall (2016). In 2019, due to the discontinuation of Platinum Pfx, Phusion Flash High-Fidelity PCR Master Mix (Thermo Fisher Scientific) was used, following the manufacturer’s protocol. Cycling conditions were: initial denaturation at 98°C for 30 seconds, 40 cycles of 98°C for 10 seconds, 60°C for 30 seconds, and 72°C for 30 seconds, with a final extension at 72°C for 10 minutes. Triplicate PCR products were pooled, and DNA concentration was measured with a bioanalyzer (Agilent, Santa Clara, CA, USA). Pooled PCR products were submitted to the Washington State University’s Sequencing Core where the samples were pooled in equimolar amounts and CCS was conducted on the PacBio Sequel system (Pacific BioSciences, Menlo Park, CA).

Amplicon sequence variant analysis

The Dada2 PacBio pipeline, created specifically for long sequence reads was used for quality filtering and processing of the raw sequence data [18]. The analysis was implemented in R[19] and R studio [20], using the following R packages: Dada2 package[21] (version 1.30.0), Biostrings package[22] (version 2.70.1), ShortRead package[23] (version 1.60.0), and Reshape2 package[24] (version 1.44.4).

Raw sequencing reads from different runs were analysed individually on the Dada2 pipeline. Quality filtering removed low-quality sequences or reads with high expected errors, retaining sequences between 1250 bp and 1600 bp. Sequences were dereplicated, run through an error model, denoised and chimeras removed, to produce ASVs. Taxonomic and species assignments were made using the RefSeq + RDP taxonomic training dataset formatted for Dada2 [25]. The output was further analysed using the R phyloseq package (version 1.46.0).

To identify possible contaminants, a database was generated using information from previous studies [26–32] (Supplementary file 1: Table 1). The obtained ASVs were filtered to remove contaminant taxa and those not identified at the genus level. The final ASV data was visualised on the R ggplot2 package [33] (version 3.4.4) and R gridExtra package [34] (version 2.3), to create a 100% stacked bar plot containing the abundance of each ASV per sample.

For ASVs not identified to the species level, a nucleotide NCBI BLAST search using blastn [35] was performed to identify the closest match in GenBank. The association between the number of reads of Anaplasma and Coxiella in all samples was assessed using both the Kendall Correlation and Spearman Correlation tests using the R stats package (version 4.3.2).

Phylogenetic Analysis

ASVs from organisms of interest (i.e. Coxiella, Anaplasma, Ehrlichia, Rickettsia-like and Borrelia-like) were aligned with homologous sequences from GenBank using QIAGEN CLC Main Workbench 24.0 (QIAGEN, Aarhus, Denmark). Information for all 16S rDNA sequences retrieved from GenBank are shown in Supplementary Tables 2–6. Alignments were truncated as follows: Coxiella (1124 bp, 25 sequences), Anaplasma (1243 bp, 37 sequences), Ehrlichia (1251 bp, 21 sequences), Rickettsia (1251 bp, 24 sequences), and Borrelia (1297 bp, 23 sequences). Statistical selection of the best-fit model was performed using IQTREE ModelFinder [36]. Maximum likelihood (ML) analysis was performed on the alignments using the IQTREE web server [37] with ultrafast bootstrap replicates (UF). The models used were: Coxiella – K2P + I + G4 (1000 UF), Anaplasma - TPM2u + F + I + G4 (3000 UF), Ehrlichia - TIM3 + F + I + G4 (1000 UF), Rickettsia - GTR + F + I + G4 (1000 UF) and Borrelia - TIM3 + F + I + G4 (1000 UF). The ML output was visualised using ITOL: Interactive Tree of Life (version 6.8.1) [38,39] with ML bootstrap values above 75 shown on the tree, and values above 95 considered good support.

Sample collection

The following tick genera were observed co-feeding on the dogs: Rhipicephalus (R. sanguineus, R. simus, R. turanicus, R. microplus), Amblyomma (A. hebraeum), Haemaphysalis (H. leachi) and Hyalomma (Hy. truncatum). Tick species prevalence was not analysed, however, R. sanguineus was the most predominant tick observed on the dogs in all three years. In 2016, R. sanguineus ticks from 10 dogs were used for further analysis, while in 2017 and 2019, R. sanguineus ticks from seven dogs were used for further analysis.

Sequence Analysis

A total of 15 tick pools (seven MG and eight SG) were processed in 2016, 10 tick pools (four MG and six SG) were processed in 2017, while 12 tick pools (six MG and six SG) were processed in 2019. Some tick pools were removed due to lack of amplification.

Samples from 2016 contained 38,241 raw sequence reads (Supplementary file 1: Table 7). After quality control, 58 ASVs were detected from 17,027 sequence reads, assigned to nine genera. After filtering and removing contaminants and two SG samples with low read counts, the microbiome profile included one Coxiella ASV (98.23%) found in all samples, and seven Escherichia/Shigella ASVs (1.77%), in six samples (Fig. 1A). In 2017 samples contained 15,642 raw sequence reads (Supplementary file 1: Table 7). After quality control, 39 ASVs were detected from 8,556 sequence reads, assigned to 15 genera. After filtering, and removing contaminants, the microbiome profile consisted of one Coxiella ASV (98.17%) in all samples, five Escherichia/Shigella ASVs (1.16%) in three samples, and one Anaplasma ASV (0.67%) in two samples (Fig. 1B). In 2019 samples contained 80,695 raw sequence reads (Supplementary file 1: table 7). After quality control, 379 ASVs detected from 54,583 sequence reads, were assigned to 106 genera. After filtering, removing contaminants and two MG and one SG low read samples, the microbiome profile consisted of two Coxiella ASVs (54.21%) from all samples, five Escherichia/Shigella ASVs (0.63%) in four samples, 11 Anaplasma ASVs (27.99%) in all samples, two Ehrlichia ASVs (17.06%) in three samples, one Borrelia-like ASV (0.07%) in one sample and one Rickettsia-like ASV (0.04%) in one sample (Fig. 1C).

Species-level assignment indicated that Coxiella ASV 1, detected in all three years, was identical to the sequence of the 16S rRNA gene of a known Coxiella-like endosymbiont (CE) (MZ836861) isolated from an R. sanguineus tick. Coxiella ASV 2, detected in 2019, was not identified to the species level but had 99.92% identity to a CE from an R. microplus tick (CP094229.1). Escherichia/Shigella ASVs indicated that all ASVs were similar to 16S rRNA gene sequences from various known Escherichia coli strains (MT647245.1, CP053607.1, CP142044.1) [40,41]. Anaplasma ASVs were divided into two groups. Group one (Anaplasma ASV 11), detected in two samples from 2017 and one sample from 2019, was identical to a known A. platys sequence (CP046391.1), isolated from a dog [42]. Group two (Anaplasma ASV 1 to Anaplasma ASV 10) detected in 2019 matched A. centrale. Anaplasma ASV 1 was identical to the 16S rRNA sequence of the Israel strain of A. centrale (CP001759.1) [43]. Anaplasma ASV 2 to Anaplasma ASV 10 were not assigned to species level. A BLAST search indicated that these ASVs matched A. centrale (CP001759.1) with an average of 99.68% identity.

Ehrlichia ASV 1 could not be assigned to species level using the Dada2, however, a BLAST search identified it as identical to a known Wolbachia endosymbiont (MN383047.1) from mosquitoes. Ehrlichia ASV 1 will hereafter be referred to as Wolbachia ASV1. Ehrlichia ASV 2 was identical to E. canis (MK507008.1) isolated from a dog and an uncultured Ehrlichia (JN121380). Borrelia-like ASV 1 was not assigned to species level; the highest BLAST match (98.81% identity) was to an uncultured bacterium (EU137037.1) [44], with 58% query coverage, and it also matched “Candidatus Borreliella tachyglossi” (CP025785.1) with 85.69% identity and 100% query coverage. Rickettsia-like ASV 1 was not assigned to species level, however a BLAST search indicated that the highest match (91.24% identity), was to an uncultured Rickettsiales bacteria (MK616428.1) from a nucleariid amoeba (Pompholyxophrys punicea) sampled from a lake in Zwönitz, Germany [45].

Kendall Correlation and Spearman Correlation tests found a moderate negative association between Anaplasma and Coxiella sequences. This was, however, not statistically significant (Spearman: R = 0.061, p = 0.78. Kendall: R = 0.051, p = 0.074) (Fig. 2).

Phylogenetic Analysis

A ML analysis of the Coxiella ASVs (Fig. 3) indicated that Coxiella ASVs clustered in a monophyletic group with known CE sequences from Rhipicephalus ticks, but with low bootstrap support. This monophyletic group split into two subgroups with moderate bootstrap support (92). One subgroup contained Coxiella ASV 1 and sequences from known CEs isolated from R. sanguineus (CP024961, KU892220, MZ836861 and KP994843) [46–48] and a Candidatus Coxiella mudrowiae from R. turanicus (CP011126) [49]. The second subgroup contained Coxiella ASV 2 and sequences from known CEs isolated from R. decoloratus (KP994833), R. microplus (KP994839) and R. evertsi (KP994835) [46]. Within this group, Coxiella ASV 2 and the CE from R. microplus clustered together (99.92% identity), with good bootstrap support (100).

A ML tree (Fig. 4) of the 11 Anaplasma ASVs, indicated that Anaplasma ASV 1 to ASV 10 formed a monophyletic group with two previously characterised A. centrale sequences (A. centrale Uganda: KU686784 and A. centrale Israel: CP001759) [43], with bootstrap support of 92. Anaplasma ASV 11 formed a monophyletic group with two known A. platys sequences [A. platys S3 (CP046391)[42] and A. platys Apla1 from a dog in the study community (MK814419) [50]] with high bootstrap support of 99.

Wolbachia ASV 1 grouped with known Wolbachia endosymbionts (MN383047 and KX155506)[51] and an uncultured bacterium (JX669531) with bootstrap support of 100. It was most closely related to a Wolbachia endosymbiont from Aedes aegypti (MN383047) (Supplementary file 1: Fig. 1). Ehrlichia ASV 2 grouped with known E. canis and uncultured Ehrlichia sequences (MK507008, NR118741 and JN121380)[52,53] with bootstrap support of 100. ML phylogenetic analysis indicated that Rickettsia-like ASV 1 was ancestral to known Rickettsia, Orientia and Occidentia sequences and clustered together with uncultured bacterial sequences, but with low bootstrap support (Supplementary file 1: Fig. 2). Borrelia-like ASV 1 did not group with known Borrelia sequences or closely related genera (Spirochaeta, Treponema and Cristispira) (Supplementary file 1: Fig. 3). Instead, it branched off from the Cristispira genus, with good bootstrap support of 96.

This study showed that the bacterial microbiome of MG and SG tissues from R. sanguineus ticks changed over the three-year study, and highlighted the role that R. sanguineus ticks might play as reservoirs of potential pathogens.

Rhipicephalus sanguineus was the most abundant tick species observed on the dogs in all three years of our study, in agreement with previous findings [54]. As R. sanguineus ticks are well adapted to human dwellings and rely on dogs as their main host, infestations can become extremely high with a consequent increase in the risk of exposure to TBPs for animals and humans [55]. Thus, R. sanguineus ticks can be seen as a keystone species that should be investigated with regard to TBPs.

In the MG and SG microbiomes of R. sanguineus ticks collected in the study, we found Coxiella, Anaplasma, Ehrlichia¸ Escherichia, Rickettsia-like and Borrelia-like 16S rRNA sequences. The microbiomes were initially dominated by a CE in 2016 and 2017, consistent with other studies of R. sanguineus tick microbiomes from northern Spain, France, Senegal, Arizona and Oklahoma [56–58]. In 2017, A. platys was introduced into the microbiome. By 2019, Anaplasma species had increased, with the introduction of large numbers of A. centrale sequences. Other pathogens (Ehrlichia, Rickettsia-like and Borrelia-like) emerged in 2019, but at very low levels. Our findings align with Portillo et al. [57], who also found low levels of Rickettsia, Borrelia, Ehrlichia and Wolbachia in R. sanguineus ticks. This difference in the microbiome between 2017 and 2019 could be attributed to climatic differences with a long drought ending in the beginning of 2019. The drought affected tick numbers, with a decrease in the overall tick population which led to decreased transmission of bacterial organisms within the community. Once the drought ended, tick populations increased allowing for more transmission of bacterial organisms and changes in the bacterial microbiome.

In 2019, we detected many potentially contaminating sequences. Given the sensitivity of next-generation sequencing, microbiome studies are prone to external and cross-contamination [59], warranting the need for negative controls, however this was not part of our standard protocol when this study began. A list of bacterial genera identified as possible contaminants in microbiome studies were removed from the dataset (Supplementary file 1: Table 1). This list included Bacillus, which was previously detected in the R. sanguineus tick microbiome [56], but because it has also been found in laboratory reagents, it was removed as a possible contaminant. This allowed for the 2019 dataset to be compared in a more meaningful way to the 2016 and 2017 dataset.

In this study, Coxiella endosymbiont (CE) sequences were detected in every MG and SG sample over three years. Historically, the genus Coxiella included only Coxiella burnetii, the agent of Q-fever, which is endemic in South Africa, with a prevalence of up to 59% in vulnerable communities [60]. More recently, various Coxiella endosymbionts (CEs) have been discovered, mainly in ticks, but also in the spleens of some wild mammals [61]. CEs have evolved with their tick hosts, causing different CEs to appear specific for different tick species [48]. These CEs benefit ticks by enhancing immunity, defense, and nutrition [62] and can affect pathogen acquisition and transmission [63]. Molecular methods for detection of C. burnetii may cross-react with CEs, potentially overestimating infection rates [64]. As R. sanguineus can bite humans, CE transmission to humans might contribute to Q-fever positive results in South Africa, while not manifesting disease. Two Coxiella ASVs were present in the 2019 datasets: ASV 1, identical to the known CE from R. sanguineus ticks, and ASV 2, closely related (99.92% identity) to a CE from R. microplus ticks. The presence of Coxiella ASV 2 could be due to co-feeding of different tick species at the same site on the dog host, or potentially an R. microplus tick could have been erroneously included in one of our 2019 pools. Therefore, we performed molecular typing on the2019 ticks, which confirmed they were R. sanguineus (data not shown).

Anaplasma sequences were detected only in 2017 and 2019. Analysis revealed two species: A. platys and A. centrale. In 2017, A. platys was found in two samples, while in 2019, A. platys was found in a single sample, and A. centrale was detected in all nine samples. Anaplasma platys causes canine thrombocytopenia in dogs [65], and has been reported in humans [66,67]. Arraga-Alvarado et al. [67] provided the first clinical evidence of A. platys infection in a human patient from Venezuela who exhibited fever symptoms as well as headache and thrombocytopenia. Though studies on the vector competence of R. sanguineus for A. platys are limited, R. sanguineus is thought to transmit A. platys, since their geographical distributions overlap and dogs are the primary hosts for both R. sanguineus and A. platys [68]. Although Simpson et al. [11] found no detectable A. platys in R. sanguineus fed on laboratory-infected dogs, Snellgrove et al. [69] showed that R. sanguineus could maintain A. platys through transovarial, transstadial, and horizontal transmission, under laboratory conditions. Detection of A. platys in one MG and two SG samples of R. sanguineus in our study highlights the possible role of R. sanguineus as a vector.

An unexpected finding was the detection of A. centrale in 2019, as dogs are not known hosts, nor is R. sanguineus a known vector. Anaplasma centrale has been shown to be transmitted by Rhipicephalus simus and Dermacentor andersoni [70–72] and causes a less virulent form of bovine anaplasmosis [73]. A previous study identified A. centrale in the SG of R. sanguineus ticks but did not demonstrate transmission to calves [72]. The R. sanguineus ticks in our study may have acquired A. centrale during co-feeding with R. simus also detected on the dogs.

The introduction of A. platys and A. centrale into the R. sanguineus microbiome in 2017 and 2019, respectively, could be from wildlife or cattle. While there is little information regarding the role of wildlife in the epidemiology of Anaplasma in Africa, A. platys and A. centrale have been documented in African buffalo [74–77], and A. centrale has also been documented in wildebeest, eland, zebra, warthog, and lion [73,77]. The introduction of these organisms into adult R. sanguineus ticks could occur through transstadial transmission from immature ticks feeding on smaller wildlife hosts. This emphasizes the significance of R. sanguineus at the wildlife-livestock-human interface. Another source could be the movement of cattle and dogs within the community. During sampling, we observed livestock being moved between residences, grazing areas, and dip tanks, with dogs often accompanying them as herding dogs. This movement could facilitate the introduction of ticks and bacteria from other areas of the community.

The introduction of Anaplasma coincided with a moderate decline in Coxiella, suggesting a potential influence of Anaplasma on the Coxiella population. A Spearman and Kendall Rank correlation indicated a slight negative correlation, though not significant. These preliminary findings warrant further study into the correlation between these bacteria in R. sanguineus. It is also important to mention that while the proportion of a given bacteria must change with the introduction of additional species, 16S rRNA microbiome sequencing does not indicate whether absolute numbers of bacteria have changed significantly.

This study also detected Escherichia/Shigella sequences in various samples across all three years. Escherichia/Shigella has been detected in several bacterial tick microbiome studies [78–80]. All variants of Escherichia/Shigella were similar to known E. coli strains, however there is currently no evidence to suggest that E. coli is transmitted by R. sanguineus.

In two 2019 samples, we detected Ehrlichia ASVs. One sequence present at low read numbers (Ehrlichia ASV 2), was classified as E. canis, the etiological agent of canine monocytic ehrlichiosis. Rhipicephalus sanguineus is a known vector of E. canis, and E. canis has been previously detected in R. sanguineus ticks as well as in dogs in the community [81,82]. While E. canis has not been documented in humans, it does infect wild canids [83].

During the ASV-based taxonomy assignment, a second “Ehrlichia variant” (Ehrlichia ASV 1) was detected. However, BLAST search and phylogenetic analysis revealed it to be identical to a Wolbachia endosymbiont from a mosquito. While ticks harbour endosymbionts like Coxiella, little is known regarding Wolbachia in ticks. One study found Wolbachia in Ixodes ticks due to parasitism by Ixodiphagus hookeri harbouring a Wolbachia endosymbiont [84]. In our study we saw high read numbers in one MG sample with lower numbers in the corresponding SG sample, and a second positive MG sample, which suggests that this was not an accidental finding. Further investigation is needed to determine the origin of this Wolbachia variant.

In 2019, we detected very low read counts of a Borrelia-like sequence from a single MG sample. Neither the ASV method nor a manual NCBI BLAST search could identify the sequence to species level, and phylogenetic analysis also failed to determine its relationship to known Borrelia sequences. This sequence might belong to an unclassified genus within the Borreliaceae family (closest match is 85.69% identity to “Candidatus Borreliella tachyglossi”), or it could be a chimeric sequence, as each half of the sequence has a higher match (> 94%) to different uncultured bacteria.

A Rickettsia-like sequence was detected in a single SG sample from 2019 at very low read counts. Further investigation could not identify the sequence to species level, using either the ASV method or a manual BLAST search. The highest match was to an uncultured Rickettsiales bacterium, an endosymbiont of the amoeba, Pompholyxophrys punicea [45]. Phylogenetic analysis indicated that it clustered with 16S rRNA sequences from various uncultured Rickettsiales, some from amoebas and others from environmental samples. Further investigation is needed to determine the occurrence and importance of this Rickettsia-like organism.

This study had several limitations that should be taken into consideration. Firstly, no negative “blank” controls were included during sample preparation and sequencing, making it difficult to identify potential contaminants. Secondly, during the study certain PCR reagents became unavailable, which led to protocol alterations between years, potentially affecting the microbiome profile. Thirdly, the study had a small sample size due to the difficulty in collecting enough adult male R. sanguineus ticks from the community dogs. Lastly, samples were collected in non-consecutive years, creating a data gap between 2017 and 2019, which may have missed valuable information on the introduction of Anaplasma. Advantages of our study include the use of dissected organs (allows for a cleaner look at the actual tick microbiome rather than environmental species that cling to the surface of the tick), use of pools (which provide a better grasp of the overall population, and reduces the variation seen when analysing individual ticks) and our longitudinal study demonstrates how the tick microbiome varies over time.

While the endosymbionts of ticks have been studied far less than those of insects, it has been proposed that ubiquitous endosymbionts (such as CE) are primary endosymbionts, whereas sporadically distributed species are secondary endosymbionts[58] Our study confirms CE as a primary endosymbiont of R. sanguineus. The secondary endosymbiont population is expected to vary by region and climatic factors. For example, A. centrale, a secondary endosymbiont, has a limited global distribution, and during the drought the microbiome was less diverse – once the drought broke, secondary endosymbionts increased, presumably due to the presence of more ticks in the ecosystem, allowing for greater movement between animals.

Our study revealed the bacterial microbiome diversity of R. sanguineus ticks from dogs from a rural community in Mpumalanga, South Africa. We identified R. sanguineus ticks as potential reservoirs for pathogens like A. platys and A. centrale, though further research is needed to confirm their reservoir role and vector competence. Our findings also suggest that R. sanguineus from the community hosts a species-specific Coxiella endosymbiont, corroborating earlier findings in R. sanguineus ticks [46]. We observed a potential correlation between Coxiella and Anaplasma, warranting further investigation. Additionally, while other pathogenic bacteria were detected, their impact remain unclear. Overall, our research highlights the role of R. sanguineus in influencing pathogen diversity and distribution at the wildlife-livestock-human interface in rural South Africa.

ASV: amplicon sequence variant

MG: midgut

SG: salivary glands

TBP: tick-borne pathogens

AFI: acute febrile illness

CCS: circular consensus sequencing

ML: Maximum likelihood

UF: ultrafast bootstrap replicates

CE: Coxiella-like endosymbiont

Acknowledgements

We acknowledge Luis Neves for verifying the tick identification. We also thank the staff of the Hans Hoheisen Wildlife Research Station for logistical support, environmental monitors, Handry Mathebula and Julia D. Sithole, for assistance in the Bushbuckridge-East community, and the tribal council for allowing us to work in their community. Appreciation is extended to Derek Pouchnik and Mark Wildung from the Genomics Sequencing Core at Washington State University for assistance with microbiome sequencing.

Funding:

We thank the South African National Research Foundation (NRF) for grants 92739 and 110448, and 109350, NIH NIAID R01AI136832, and the Belgian Directorate General for Development Cooperation Framework FA4 (ITM-DGCD) awarded to Marinda Oosthuizen, as well as the Agricultural Sector Education Training Authority (AgriSETA; BU18UP124-18.2) Scholarship and the Meat Industry Trust for the bursary awarded to Rebecca E. Ackermann. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding bodies.

Availability of data and materials

The raw microbiome datasets generated during the current study are available in the NCBI SRA. 16S sequences reported in this study are available on GenBank under accession numbers: Currently in progress.

Authors’ contributions

Conception/design of the work: KAB, CAG, NEC, MCO, REA

Sample Acquistion: IW, REA, CAG, JW

Data acquisition: REA, AOK

Analysis: REA

Interpretation of data: REA, MCO, KAB, NEC, CAG

Drafted the manuscript: REA

Editing of the manuscript: REA, CAG, KAB NEC, IW, JW, AOK, MCO.

Ethics approval and consent to participate

Consent for publication

Not applicable

Competing interests:

The authors declare they have no competing interests.

Chitanga S, Gaff H, Mukaratirwa S. Tick-borne pathogens of potential zoonotic importance in the southern African region. J S Afr Vet Assoc. 2014;85:1084–7.
de la Fuente J, Estrada-Pena A, Venzal JM, Kocan KM, Sonenshine DE. Overview: ticks as vectors of pathogens that cause disease in humans and animals. Frontiers in Bioscience. 2008;13:6938–46.
Gall CA. Functional characterization of the bacterial microbiome of the Dermacentor andersoni tick exhibits interactions with pathogen acquisition. Washington State University; 2016.
Bonnet SI, Binetruy F, Hernández-Jarguín AM, Duron O. The tick microbiome: Why non-pathogenic microorganisms matter in tick biology and pathogen transmission. Front Cell Infect Microbiol. 2017;7.
Gall CA, Reif KE, Scoles GA, Mason KL, Mousel M, Noh SM, et al. The bacterial microbiome of Dermacentor andersoni ticks influences pathogen susceptibility. ISME Journal. 2016;10:1846–55.
Gray J, Dantas-Torres F, Estrada-Peña A, Levin M. Systematics and ecology of the brown dog tick, Rhipicephalus sanguineus. Ticks Tick Borne Dis. 2013;4:171–80.
Socolovschi C, Gomez J, Marié JL, Davoust B, Guigal PM, Raoult D, et al. Ehrlichia canis in Rhipicephalus sanguineus ticks in the Ivory Coast. Ticks Tick Borne Dis. 2012;3:411–3.
Dantas-Torres F, Otranto D. Further thoughts on the taxonomy and vector role of Rhipicephalus sanguineus group ticks. Vet Parasitol. 2015;208:9–13.
Byrd Jr, Ryland P, Vasquez J. Respiratory Manifestations of Tick-Borne Diseases in the Southeastern United States. South Med J. 1997;90:1–4.
García-García JC, Portillo A, Núñez MJ, Santibáñez S, Castro B, Oteo JA. Case report: A patient from Argentina infected with Rickettsia massiliae. American Journal of Tropical Medicine and Hygiene. 2010;82:691–2.
Simpson RM, Gaunt SD, Hair JA, Kocan KM, Henk WG, Casey HW. Evaluation of Rhipicephalus sanguineus as a potential biologic vector of Ehrlichia platys. Am J Vet Res. 1991;52:1537–41.
Berrian AM, van Rooyen J, Martínez-López B, Knobel D, Simpson GJG, Wilkes MS, et al. One Health profile of a community at the wildlife-domestic animal interface, Mpumalanga, South Africa. Prev Vet Med. 2016;130:119–28.
Hotez PJ, Kamath A. Neglected tropical diseases in sub-Saharan Africa: Review of their prevalence, distribution, and disease burden. PLoS Negl Trop Dis. 2009;3:e412.
Oruganti P, Root E, Ndlovu V, Mbhungele P, Van Wyk I, Berrian AM. Gender and zoonotic pathogen exposure pathways in a resource-limited community, Mpumalanga, South Africa: A qualitative analysis. PLOS Global Public Health. 2023;3:e0001167.
Wang H, Zhang X, Wang X, Zhang B, Wang M, Yang X, et al. Comprehensive analysis of the global protein changes that occur during salivary gland degeneration in female Ixodid ticks Haemaphysalis longicornis. Front Physiol. 2019;9.
Walker A, Bouattour A, Camicas J, Estrada-Peña A, Horak I, Latif A, et al. Ticks of domestic animals in Africa: a guide to identification of species. 1st ed. Bioscience Reports; 2003.
Scoles GA, Ueti MW, Palmer GH. Variation among geographically separated populations of Dermacentor andersoni (Acari: Ixodidae) in midgut susceptibility to Anaplasma marginale (Rickettsiales: Anaplasmataceae). J Med Entomol. 2005;42:153–62.
Callahan BJ, Wong J, Heiner C, Oh S, Theriot CM, Gulati AS, et al. High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution. Nucleic Acids Res. 2019;47:E103.
R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2023.
Posit team. RStudio: Integrated Development Environment for R. Boston, MA: Posit Software, PBC; 2024.
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.
Pagès H, Aboyoun P, Gentleman R, DebRoy S. Biostrings: Efficient manipulation of biological strings. 2023.
Morgan M, Anders S, Lawrence M, Aboyoun P, Pages H, Gentleman R. ShortRead: a Bioconductor package for input, quality assessment and exploration of high-throughput sequence data. Bioinformatics. 2009;25:2607–8.
Wickham H. Reshaping Data with the reshape Package. J Stat Softw. 2007;21:1–20.
Alishum A. DADA2 formatted 16S rRNA gene sequences for both bacteria & archaea. 2021.
Bedarf JR, Beraza N, Khazneh H, Özkurt E, Baker D, Borger V, et al. Much ado about nothing? Off-target amplification can lead to false-positive bacterial brain microbiome detection in healthy and Parkinson’s disease individuals. Microbiome. 2021;9:75–90.
Laurence M, Hatzis C, Brash DE. Common contaminants in next-generation sequencing that hinder discovery of low-abundance microbes. PLoS One. 2014;9:e97876.
Lejal E, Estrada-Peña A, Marsot M, Cosson JF, Rué O, Mariadassou M, et al. Taxon appearance from extraction and amplification steps demonstrates the value of multiple controls in tick microbiota analysis. Front Microbiol. 2020;11:1093.
Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, et al. Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol. 2014;12:87–99.
Walker SP, Tangney M, Claesson MJ. Sequence-based characterization of intratumoral bacteria - A guide to best practice. Front Oncol. 2020;10.
Weyrich LS, Farrer AG, Eisenhofer R, Arriola LA, Young J, Selway CA, et al. Laboratory contamination over time during low-biomass sample analysis. Mol Ecol Resour. 2019;19:982–96.
Zhu X, Li X, Wang W, Ning K. Bacterial contamination screening and interpretation for biological laboratory environments. Medicine in Microecology. 2020;5:100021.
Wickham H. ggplot2: Elegant Graphics for Data Analysis. New York: Springer-Verlag; 2016.
Auguie B. gridExtra: Miscellaneous Functions for “Grid” Graphics. 2017.
Sayers EW, Bolton EE, Brister JR, Canese K, Chan J, Comeau DC, et al. Database resources of the national center for biotechnology information. Nucleic Acids Res. 2022;50:D20–6.
Kalyaanamoorthy S, Minh BQ, Wong TKF, von Haeseler A, Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods. 2017;14:587–9.
Trifinopoulos J, Nguyen L, von Haeseler A, Minh BQ. W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis. Nucleic Acids Res. 2016;44:W232–5.
Letunic I, Bork P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 2021;49:W293–6.
Letunic I, Bork P. Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics. 2007;23:127–8.
Anton BP, Raleigh EA. Complete genome sequence of NEB 5-alpha, a derivative of Escherichia coli K-12 DH5α. Genome Announc. 2016;4.
El-Gendy MMAA, Abdel-Wahhab KG, Hassan NS, El-Bondkly EA, Farghaly AA, Ali HF, et al. Evaluation of carcinogenic activities and sperm abnormalities of Gram-negative bacterial metabolites isolated from cancer patients after subcutaneous injection in albino rats. Antonie Van Leeuwenhoek. 2021;114:287–302.
Llanes A, Rajeev S. First whole genome sequence of Anaplasma platys, an obligate intracellular Rickettsial pathogen of dogs. Pathogens. 2020;9:277.
Herndon DR, Palmer GH, Shkap V, Knowles DP, Brayton KA. Complete genome sequence of Anaplasma marginale subsp. centrale. J Bacteriol. 2010;192:379–80.
Jones SE, Newton RJ, McMahon KD. Potential for atmospheric deposition of bacteria to influence bacterioplankton communities. FEMS Microbiol Ecol. 2008;64:388–94.
Galindo LJ, Torruella G, Moreira D, Eglit Y, Simpson AGB, Völcker E, et al. Combined cultivation and single-cell approaches to the phylogenomics of nucleariid amoebae, close relatives of fungi. Philosophical Transactions of the Royal Society B: Biological Sciences. 2019;374:20190094.
Duron O, Noël V, McCoy KD, Bonazzi M, Sidi-Boumedine K, Morel O, et al. The recent evolution of a maternally-inherited endosymbiont of ticks led to the emergence of the Q Fever pathogen, Coxiella burnetii. PLoS Pathog. 2015;11:e1004892.
Oskam CL, Gofton AW, Greay TL, Yang R, Doggett S, Ryan UM, et al. Molecular investigation into the presence of a Coxiella sp. in Rhipicephalus sanguineus ticks in Australia. Vet Microbiol. 2017;201:141–5.
Tsementzi D, Castro Gordillo J, Mahagna M, Gottlieb Y, Konstantinidis KT. Comparison of closely related, uncultivated Coxiella tick endosymbiont population genomes reveals clues about the mechanisms of symbiosis. Environ Microbiol. 2018;20:1751–64.
Gottlieb Y, Lalzar I, Klasson L. Distinctive genome reduction rates revealed by genomic analyses of two Coxiella-like endosymbionts in ticks. Genome Biol Evol. 2015;7:1779–96.
Kolo AO, Collins NE, Brayton KA, Chaisi M, Blumberg L, Frean J, et al. Anaplasma phagocytophilum and other Anaplasma spp. In various hosts in the mnisi community, Mpumalanga Province, South Africa. Microorganisms. 2020;8:1–21.
Matsumoto K, Izri A, Dumon H, Raoult D, Parola P. First detection of Wolbachia spp., including a new genotype, in sand flies collected in Marseille, France. J Med Entomol. 2008;45:466–9.
Anderson BE, Dawson JE, Jones DC, Wilson KH. Ehrlichia chaffeensis, a new species associated with human ehrlichiosis. J Clin Microbiol. 1991;29:2838–42.
Díaz-Sánchez AA, Corona-González B, Meli ML, Roblejo-Arias L, Fonseca-Rodríguez O, Pérez Castillo A, et al. Molecular diagnosis, prevalence and importance of zoonotic vector-borne pathogens in cuban shelter dogs - A preliminary study. Pathogens. 2020;9:901–19.
Bryson NR, Horak IG, Höhn EW, Louw JP. Ectoparasites of dogs belonging to people in resource-poor communities in North West Province, South Africa. J S Afr Vet Assoc. 2000;3:175–9.
Horak IG, Fourie LJ, Heyne H, Walker JB, Needham GR. Ixodid ticks feeding on humans in South Africa: with notes on preferred hosts, geographic distribution, seasonal occurrence and transmission of pathogens. Exp Appl Acarol. 2002;27:113–36.
René-Martellet M, Minard G, Massot R, Van Tran V, Valiente Moro C, Chabanne L, et al. Bacterial microbiota associated with Rhipicephalus sanguineus (s.l.) ticks from France, Senegal and Arizona. Parasit Vectors. 2017;10:416.
Portillo A, Palomar AM, de Toro M, Santibáñez S, Santibáñez P, Oteo JA. Exploring the bacteriome in anthropophilic ticks: To investigate the vectors for diagnosis. PLoS One. 2019;14:e0213384.
Rounds MA, Crowder CD, Matthews HE, Philipson CA, Scoles GA, Ecker DJ, et al. Identification of endosymbionts in ticks by broad-range polymerase chain reaction and electrospray ionization mass spectrometry. J Med Entomol. 2012;49:843–50.
Eisenhofer R, Minich JJ, Marotz C, Cooper A, Knight R, Weyrich LS. Contamination in low microbial biomass microbiome studies: issues and recommendations. Trends Microbiol. 2019;27:105–17.
Quan VC, Frean J, Simpson G, Knobel D, Meiring S, Weyer J, et al. Zoonotic infections in adults in the Bushbuckridge District of Mpumalanga Province. International Journal of Infectious Diseases. 2014;21:186.
Brinkmann A, Hekimoǧlu O, Dinçer E, Hagedorn P, Nitsche A, Ergünay K. A cross-sectional screening by next-generation sequencing reveals Rickettsia, Coxiella, Francisella, Borrelia, Babesia, Theileria and Hemolivia species in ticks from Anatolia. Parasit Vectors. 2019;12:26.
Kolo AO, Raghavan R. Impact of endosymbionts on tick physiology and fitness. Parasitology. 2023;150:859–65.
Li LH, Zhang Y, Zhu D, Zhou XN. Endosymbionts alter larva-to-nymph transstadial transmission of Babesia microti in Rhipicephalus haemaphysaloides ticks. Front Microbiol. 2018;9:1415.
Jourdain E, Duron O, Séverine B, González-Acuña D, Sidi-Boumedine K. Molecular methods routinely used to detect Coxiella burnetii in ticks cross-react with Coxiella-like bacteria. Infect Ecol Epidemiol. 2015;5:29230.
Harvey JW, Simpson CF, Gaskin JM. Cyclic thrombocytopenia induced by a Rickettsia-like agent in dogs. J Infect Dis. 1978;137:182–8.
Breitschwerdt EB, Hegarty BC, Qurollo BA, Saito TB, Maggi RG, Blanton LS, et al. Intravascular persistence of Anaplasma platys, Ehrlichia chaffeensis, and Ehrlichia ewingii DNA in the blood of a dog and two family members. Parasit Vectors. 2014;7:298.
Arraga-Alvarado CM, Qurollo BA, Parra OC, Berrueta MA, Hegarty BC, Breitschwerdt EB. Case report: Molecular evidence of Anaplasma platys infection in two women from Venezuela. American Journal of Tropical Medicine and Hygiene. 2014;91:1161–5.
Yuasa Y, Tsai YL, Chang CC, Hsu TH, Chou CC. The prevalence of Anaplasma platys and a potential novel Anaplasma species exceed that of Ehrlichia canis in asymptomatic dogs and Rhipicephalus sanguineus in Taiwan. Journal of Veterinary Medical Science. 2017;79:1494–502.
Snellgrove AN, Krapiunaya I, Ford SL, Stanley HM, Wickson AG, Hartzer KL, et al. Vector competence of Rhipicephalus sanguineus sensu stricto for Anaplasma platys. Ticks Tick Borne Dis. 2020;11:101517.
Ueti MW, Knowles DP, Davitt CM, Scoles GA, Baszler T V., Palmer GH. Quantitative differences in salivary pathogen load during tick transmission underlie strain-specific variation in transmission efficiency of Anaplasma marginale. Infect Immun. 2009;77:70–5.
Potgieter FT, Van Rensburg L. Tick transmission of Anaplasma centrale. Onderstepoort Journal of Veterinary Research. 1987;54:5–7.
Shkap V, Kocan K, Molad T, Mazuz M, Leibovich B, Krigel Y, et al. Experimental transmission of field Anaplasma marginale and the A. centrale vaccine strain by Hyalomma excavatum, Rhipicephalus sanguineus and Rhipicephalus (Boophilus) annulatus ticks. Vet Microbiol. 2009;134:254–60.
Khumalo ZTH, Brayton KA, Collins NE, Chaisi ME, Quan M, Oosthuizen MC. Evidence confirming the phylogenetic position of Anaplasma centrale (Ex theiler 1911) Ristic and Kreier 1984. Int J Syst Evol Microbiol. 2018;68:2682–91.
Al-Hosary A, Rǎileanu C, Tauchmann O, Fischer S, Nijhof AM, Silaghi C. Epidemiology and genotyping of Anaplasma marginale and co-infection with piroplasms and other Anaplasmataceae in cattle and buffaloes from Egypt. Parasit Vectors. 2020;13:495–506.
Khumalo ZTH, Catanese HN, Liesching N, Hove P, Collins NE, Chaisi ME, et al. Characterization of Anaplasma marginale subsp. centrale strains by use of msp1aS genotyping reveals a wildlife reservoir. J Clin Microbiol. 2016;54:2503–12.
Machado RZ, Teixeira MMG, Rodrigues AC, André MR, Gonçalves LR, Barbosa Da Silva J, et al. Molecular diagnosis and genetic diversity of tick-borne Anaplasmataceae agents infecting the African buffalo Syncerus caffer from Marromeu Reserve in Mozambique. Parasit Vectors. 2016;9:454–63.
Makgabo SM, Brayton KA, Oosthuizen MC, Collins NE. Unravelling the diversity of Anaplasma species circulating in selected African wildlife hosts by targeted 16S microbiome analysis. Curr Res Microb Sci. 2023;5:e100198.
Gomez-Chamorro A, Hodžić A, King KC, Cabezas-Cruz A. Ecological and evolutionary perspectives on tick-borne pathogen co-infections. Current Research in Parasitology & Vector-Borne Diseases. 2021;1:100049.
Chigwada AD, Mapholi NO, Ogola HJO, Mbizeni S, Masebe TM. Pathogenic and endosymbiotic bacteria and their associated antibiotic resistance biomarkers in Amblyomma and Hyalomma ticks infesting Nguni Cattle (Bos spp.). Pathogens. 2022;11:432.
Khalaf JM, Mohammed IA, Karim AJ. The epidemiology of tick in transmission of Enterobacteriaceae bacteria in buffaloes in Marshes of the south of Iraq. Vet World. 2018;11:1677–81.
Kolo AO, Oosthuizen MC, Brayton K, Collins N. Detection of zoonotic bacterial pathogens in multiple hosts using a microbiome approach and molecular characterization of Anaplasma phagocytophilum. University of Pretoria; 2019.
Kolo AO. Identification and molecular characterization of zoonotic rickettsiae and other vector-borne pathogens infecting dogs in Mnisi, Bushbuckridge, Mpumalanga Province, South Africa. University of Pretoria; 2014.
Woodroffe R, Prager KC, Munson L, Conrad PA, Dubovi EJ, Mazet JAK. Contact with domestic dogs increases pathogen exposure in endangered African wild dogs (Lycaon pictus). PLoS One. 2012;7:e30099.
Plantard O, Bouju-Albert A, Malard M, Hermouet A, Capron G, Verheyden H. Detection of Wolbachia in the tick Ixodes ricinus is due to the presence of the Hymenoptera endoparasitoid Ixodiphagus hookeri. PLoS One. 2012;7:e30692.

No competing interests reported.

Supplementraryfile1.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

The bacterial microbiome and pathogen reservoir potential of Rhipicephalus sanguineus ticks in South Africa

Status:

Version 1

Abstract

Figures

Background

Materials and Methods

Ethical Approvals

Sample collection and genomic DNA extraction

PCR and sequencing

Amplicon sequence variant analysis

Phylogenetic Analysis

Results

Sample collection

Sequence Analysis

Phylogenetic Analysis

Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1