Genetic structure and Rickettsia infection rates in Ixodes ovatus and Haemaphysalis flava ticks across different altitudes

Maria Angenica F Regilme; Megumi Sato; Tsutomu Tamura; Reiko Arai; Marcello Otake Sato; Sumire Ikeda; Kozo Watanabe

doi:10.1371/journal.pone.0298656

. 2024 Mar 13;19(3):e0298656. doi: 10.1371/journal.pone.0298656

Genetic structure and Rickettsia infection rates in Ixodes ovatus and Haemaphysalis flava ticks across different altitudes

Maria Angenica F Regilme ^1,^2,^¤, Megumi Sato ³, Tsutomu Tamura ⁴, Reiko Arai ⁴, Marcello Otake Sato ⁵, Sumire Ikeda ⁶, Kozo Watanabe ^1,^*

Editor: Maria Stefania Latrofa⁷

PMCID: PMC10936840 PMID: 38478554

Abstract

Ixodid ticks, such as Ixodes ovatus and Haemaphysalis flava, are important vectors of tick-borne diseases in Japan, such as Japanese spotted fever caused by Rickettsia japonica. This study describes the Rickettsia infection rates influenced by the population genetic structure of I.ovatus and H. flava along an altitudinal gradient. A total of 346 adult I. ovatus and 243 H. flava were analyzed for the presence of Rickettsia by nested PCR targeting the 17kDA, gltA, rOmpA, and rOmpB genes. The population genetic structure was analyzed utilizing the mitochondrial cytochrome oxidase 1 (cox1) marker. The Rickettsia infection rates were 13.26% in I. ovatus and 6.17% in H. flava. For I. ovatus, the global F_ST value revealed significant genetic differentiation among the different populations, whereas H. flava showed non-significant genetic differentiation. The cox1 I. ovatus cluster dendrogram showed two cluster groups, while the haplotype network and phylogenetic tree showed three genetic groups. A significant difference was observed in Rickettsia infection rates and mean altitude per group between the two cluster groups and the three genetic groups identified within I. ovatus. No significant differences were found in the mean altitude or Rickettsia infection rates of H. flava. Our results suggest a potential correlation between the low gene flow in I. ovatus populations and the spatially heterogeneous Rickettsia infection rates observed along the altitudinal gradient. This information can be used in understanding the relationship between the tick vector, its pathogen, and environmental factors, such as altitude, and for the control of tick-borne diseases in Japan.

Introduction

Tick-borne diseases are a significant public health concern in Japan and are transmitted by a diverse range of tick species, such as Ixodes ovatus [1] that potentially transmit Borrelia sp. causing Lyme disease [2] and Haemaphysalis flava [3], which transmits Rickettsia japonica and is a suspected vector of severe fever with thrombocytopenia syndrome virus [4–6]. Their dispersal is linked to the mobility of their hosts, relying on them to disperse into new landscapes and potentially introduce pathogens [7, 8]. The dynamics of tick-borne pathogens are influenced by the habitat distribution and dispersal behaviors of vectors and hosts along environmental gradients [9]. Therefore, understanding the complex interaction between these factors is important in understanding the spread of tick-borne diseases in Japan.

Tick population genetic analysis provides data that help identify the dispersal pattern of ticks based on gene flow between local populations [10]. The potential of spreading pathogens might be influenced by ticks’ dispersal, which is related to the movements of their vertebrate hosts, especially in three-host Ixodidae species [7, 8]. For example, contrasting patterns in the population genetic structures of I. ovatus and H. flava in the Niigata Prefecture of Japan suggest that host mobility during the immature stages of tick development may influence the genetic structure of adult ticks by affecting survivability into their adult stages [11, 12]. Ixodes ovatus populations had greater genetic divergence possibly due to the limited dispersal of their small mammalian hosts during the immature development stage; H. flava populations showed a more homogenized structure possibly due to the larger mobility of their large mammalian hosts and avian-mediated dispersal [11]. Other studies have also revealed low gene flow in ticks with low-mobility hosts (e.g., small mammals) and higher gene flow in ticks with highly mobile hosts (e.g., large mammals and birds) [10, 13–16].

The spatial distribution and movement of the vector (i.e., ticks) may determine the spatial distribution of the pathogen’s (i.e., Rickettsia) infection rate [17]. Previous studies have shown that the pathogen infection rate can be influenced by many factors, such as the vector’s genetic diversity, gene flow, and spatial structure [5, 6, 11, 18–25]. For example, previous studies have shown that strong gene flow between local vector populations tends to reduce the spatial heterogeneity of pathogen infection rates between populations [26, 27]. Thus, the spatial distribution and movement of the vector may affect the spatial distribution of the pathogen. To our knowledge, no previous studies have examined the relationship between the spatial heterogeneity of Rickettsia infection rates and population genetic structure in ticks.

Environmental factors may relate to the population genetic structure of ticks [28, 29], with limited gene flow increasing genetic variation between populations along an altitudinal gradient, as reported in several studies on other species [30–32]. In the study by [11], no significant influence of environmental factors, including altitude, was observed in the genetic structures of I. ovatus and H. flava based on the mantel test, but the study did not use any other robust analytical methods to thoroughly examine the influence of altitude on tick genetic structure. In another study, major spotted fever group Rickettsia (SFGR) prevalence was analyzed in a total of 3,336 immature and adult ticks across the Niigata Prefecture, Japan in the following tick species: Dermacentor taiwanensis, H. flava, Haemaphysalis hystricis, Haemaphysalis longicornis, Haemaphysalis megaspinosa, Ixodes columnae, Ixodes monospinosus, Ixodes nipponensis, Ixodes ovatus, and Ixodes persulcatus [6]. Three SFGR species namely Rickettsia asiatica, R. helvetica and R. monacensis were detected in H. flava, Haemaphysalis longicornis, Ixodes monospinus, Ixodes nipponensis, and Ixodes ovatus, no spatial distribution of Rickettsia infection rates was found among the local populations. To our knowledge, no previous studies have considered the influence of environmental factors on the spatial distribution of Spotted fever group Rickettsia infection rates along an altitudinal gradient in local Ixodid tick populations such as Ixodes ovatus and Haemaphysalis flava as influenced by the tick population’s genetic structure.

In this study, we elucidate the relationship between Rickettsia infection rates as influenced by population genetic structure along an altitudinal gradient to improve public health understanding of the distribution of ticks and tick-borne diseases. Based on the isolation by environment (IBE) theory, genetic differentiation increases with environmental variation, regardless of geographic distance [33–35]. Thus based on the results of [11], we hypothesized that in I. ovatus with a strong population genetic structure, we expect to see a heterogenous Rickettsia infection rate along an altitudinal gradient. In contrast to the homogenous genetic structure of H. flava wherein we expect to observe a homogenous Rickettsia infection rate.

Materials and method

Published data of [6, 11]

In this study, we used cox1 sequence data from [11] for I. ovatus (n = 307) and H. flava (n = 220) ticks collected from April 2016 to November 2017 from 30 sites across the Niigata Prefecture, Japan. Sequences used for analysis are available in the GenBank database under the accession numbers MW063669-MW064124 and MW065821—MW066347. Rickettsia infection rate data were obtained from [6] from I. ovatus (n = 29) and H. flava (n = 2), from 38 sites across Niigata Prefecture. The 38 sites surveyed in the previous study by [6] include the 30 sites that were used in this present study (S1 Table). Please refer to [6, 11] for more information about the study sites, collection, sampling identification, DNA extraction, PCR amplification, and sequencing methods used in each respective study.

To strengthen our analysis, we also added new cox1 sequences and Rickettsia-infected/uninfected ticks from I. ovatus (n = 39) and H. flava (n = 23) individuals collected from April to October 2018, a total of (n = 62) sampled at 30 sites across the Niigata Prefecture, including two sites not previously sampled by [11]. The sequences are available in the GenBank database under the accession numbers OR975837 to OR975875 and OR975876 to OR975898. At these sites, ticks were collected 2–14 times from six core sites among the 30 sites, while ticks were collected once at the remaining sites. The altitude at each site ranged from 8 to 1402 meters above sea level (m.a.s.l.), with a mean altitude of 348 m.a.s.l.

Unpublished data from the 2018 collection

Ticks collected were stored at 4°C in microcentrifuge tubes with 70% ethanol. Each collected tick was morphologically identified using a stereo microscope following the identification keys of [36]. Genomic DNA was extracted from individual ticks using Isogenome DNA extraction kits (Nippon Gene Co. Ltd. Tokyo, Japan) following the manufacturer’s recommended protocol.

In this study, we combined previously published data from [6] with our newly collected data to calculate the Rickettsia infection rate, which is the percentage of Rickettsia-infected ticks from each obtained population. We analyzed the obtained tick DNA for spotted fever group Rickettsia (SFGR) detection and host identification and amplified the mitochondrial gene cox1 for population genetic analysis. We performed nested PCR targeting the following genes for the detection of Rickettsia sp.: 17-kDA antigen gene (17-kDA); citrate synthase gene (gltA); spotted fever group (SFG)-specific outer membrane protein A gene (rOmpA); and outer membrane protein B gene (rOmpB) as described and analyzed in [6, 37–41] (S2 Table). Briefly, we first amplified the 17-kDa protein. If the results were positive, then PCR was performed to target gltA. Samples that were positive with both 17-kDA and gltA were regarded as positive for SFGR and a nested PCR was performed to target the rOmpA and rOmpB gene, samples that are positive for 17-Kda, gltA, rOmpA, and rOmpB genes were sequenced to identify the Rickettsia species. The amplified PCR products were purified using AMPure XP (Beckman Coulter Co., Japan) and sequenced using the Big Dye Terminator Cycle Sequence Kit (Thermo Fisher Scientific).

The cox1 mitochondrial gene was amplified by PCR for cox1 (658 base pairs) using the primer pairs LCO-1490 (5′-GGTCAACAAATCATAAAGATATTGG-3’) and HCO1–2198 (5′–AAACTTCAGGGTGACCAAAAAATCA-3) for phylogenetic analysis and tick species identification [42]. The PCR amplification profile included an initial denaturation of 94°C for 2 min, followed by denaturation at 94°C for 30 s, then annealing at 38°C for 30 s, followed by an extension of 72°C for 1 min for 30 cycles, and a final extension of 72°C for 10 min. The obtained PCR products were purified using the QIAquick 96 PCR Purification Kit (Qiagen, Germany) following the manufacturer’s instructions and were sequenced by Eurofin Genomics, Inc. (Tokyo, Japan).

Each forward and reverse read was assembled using CodonCode Aligner version 1.2.4 software (https://www.codoncode.com/aligner/). Low-quality bases were removed in the aligned sequences, and no ambiguous bases were detected. We used the MAFFT alignment online program (https://mafft.cbrc.jp/alignment/server/) to perform multiple alignments using the default settings. The sequences were checked for similarities with the deposited reference sequences from GenBank for sequence quality and tick species confirmation using BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi). The protein-coding genes were translated to amino acids to confirm the absence of stop codons and the final aligned sequences were checked in Mesquite version 3.5 [43].

Population genetic analysis

Multiple sites that are within 80 kilometers were combined for population genetic analysis if less than eight individuals were obtained per site, which resulted in 8 populations labeled A to H (S1 Table). Three sites were excluded from the population genetic analysis because of the limited number of obtained individuals (<8) and the lack of a nearby site within 80 kilometers to combine into a single population.

The final cox1 sequences of the tick species: I. ovatus and H. flava were individually analyzed using DNASp version 6.12.03 to determine the haplotype diversity per species [44]. The level of genetic divergence between each population was quantified per species using global F_ST. Significance was tested using Arlequin software version 3.5.2.2 [45] with 9999 permutations.

The genetic relationship between the I. ovatus populations was visualized using the unweighted pair group with the arithmetic mean (UPGMA) cluster method using the APE package [46] for the RStudio software (R Development Core Team, 2016). A cluster dendrogram was created using pairwise F_ST values genetic distance matrix from GenAlEx.

Haplotype network and phylogenetic analyses

We constructed a haplotype network analysis using PopART program version 1.7 (http://popart.otago.ac.nz/index.shtml) on cox1 I. ovatus and H. flava sequences to assess haplotype relationships and the distribution of Rickettsia infected infected ticks using the median-joining network algorithm [47]. Briefly, we constructed a Bayesian phylogenetic tree of cox1 haplotypes for I. ovatus and H. flava, respectively, using Markov chain Monte Carlo (MCMC) approach implemented in the BEAST version 1.10.14 [48]. We used the Hasegawa-Kishino-Yano substitution model with estimated base frequencies. We employed a strict clock model and used the coalescent prior as the tree prior. A maximum clade credibility tree was acquired using TreeAnnotator version 1.10.14 using trees from BEAUti version1.10.14 with 90% of the trees as the burn-in. We viewed the constructed maximum clade credibility tree using FigTree version 1.4.4.

Statistical analysis

To determine whether there was a significant difference in the Rickettsia infection rate between haplotype groups for I. ovatus and H. flava, we performed a z-score test at p < 0.05. The z-score test was chosen because of the large sample size and because the population variance was known. To determine whether there were differences in the mean altitude between the haplotype groups, we used the Welch t-test at p < 0.05. Welch t-test was used when the means of the two populations were normally distributed and had equal variances.

Results

The total number of positive (pos) and negative (neg) ticks for Rickettsia infections from the ticks collected in 2018 were: I. ovatus (neg = 22, pos = 17) and H. flava (neg = 10, pos = 13). In this study, the total number of samples from the previously published data [6, 11] and the unpublished data from 2018 were: I. ovatus (n = 346) and H. flava (n = 243). The number of adult ticks whose cox1 was successfully sequenced per species were: I. ovatus (346) and H. flava (243) (Table 1).

Table 1. Summary of the haplotype and Rickettsia infection rates among the 7 ixodid tick species obtained in the Niigata Prefecture, Japan.

Tick species ^**	ns	n	nh	r	Global F_ST
1. Ixodes ovatus	30	346	59	46 (13.26%)	0.4154^*
2. Haemaphysalis flava	18	243	66	15 (6.17%)	0.3597
Total		589		61

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Abbreviations: ns no. of sampling sites; n sample size; nh no of haplotypes; r Rickettsia infection rate per species

*p < 0.05 **tick species identification is based on molecular identification using the cox1 marker and BLAST results

We detected SFGR in 78 (12.44%) out of 627 ixodid ticks, with the highest detected in I. ovatus (46/346; 13.29%) and in H. flava (15/243; 6.17%) as summarized in Table 1. Out of the 46 Rickettsia-infected I. ovatus ticks, 25 displayed a 100% identity match with Rickettsia asiatica in the 17kDA, gltA, and rOmpB markers [6], while an additional 19 adult I. ovatus from the 2018 collection were also positive with R. asiatica. Two haplotypes were found in the rOmpB and 17kDA markers, respectively. One haplotype was found in only one individual (17369). Two out of the 15 Rickettsia-infected H. flava ticks were found to have the same haplotypes in the 17Kda, gltA,and rOmpA markers, and were identified as Rickettsia sp. (LC461063). The remaining 13 Rickettsia-infected H. flava ticks were identified as Rickettsia sp.

Based on the population genetic analysis of the cox1 sequences, we found a significant global F_ST of 0.4154 at p < 0.05 for I. ovatus (Table 1). In contrast, no significant global F_ST values were observed in the H. flava (Table 1). There were 59 and 66 cox1 haplotypes found among the 346 I. ovatus and 243 H. flava individuals, respectively.

The cox1 haplotype network of I. ovatus (Fig 1) revealed four genetic groups, wherein three genetic groups (1, 2, and 3) were distributed along different altitudinal gradients, as shown in Fig 2. These four genetic groups were concordant with the four clusters found in the I. ovatus phylogenetic tree (S1 Fig). The habitat distribution of genetic group 3 was limited to high altitude sites only (range = 16–912 m.a.s.l.), whereas genetic groups 1 (255–471 m.a.s.l.) and 2 (84–1354 m.a.s.l.) were distributed at lower altitudes (Fig 2). The Welch t-test revealed a significant difference between the mean altitudes of genetic groups 1 and 3 at p < 0.05 (Table 2); however, no significant difference was observed between genetic groups 1 and 2 or groups 2 and 3. We found a significant difference in the Rickettsia infection rates between I. ovatus genetic groups 1 and 2 based on the z-score test, but no significant difference between groups 1 and 3 or groups 2 and 3 (Table 2). The mean altitude between the Rickettsia-infected (= 273.72 m.a.s.l.) and non-infected I. ovatus (= 369.61 m.a.s.l.) revealed a significant difference based on the Welch t-test at p < 0.05 (Fig 3). The UPGMA dendrogram of I. ovatus revealed two genetic clusters, 1 and 2 using the genetic distance among the seven populations excluding one population due to the limited number of samples (Fig 4).

Fig 2 — The points indicate the sampling sites of the collected individuals per I. *ovatus* haplotype group (n = 3) in the haplotype network (Fig 1). The map shows the elevation level across the sampling area, with Niigata Prefecture Japan depicted as a color gradation. Group 4, not shown in this figure, with haplotypes 54 and 55 was found on Sado island, which is encircled in black in box 3.

Table 2. The differences in Rickettsia infection rates and mean altitude in I. ovatus haplotype groups and cluster dendrogram groups.

The table shows the distribution of Rickettsia-infected and uninfected I. ovatus and the mean altitude in each of the haplotype groups as shown in Fig 1 (I. ovatus haplotype network) and the cluster dendrogram in Fig 4 (I. ovatus cluster dendrogram). The z-score test showed a significant difference at p < 0.05 between the Rickettsia detection rates in haplotype groups 1 and 2 (indicated by ^ab) and in cluster dendrogram groups 1 and 2. The Welch t-test at p < 0.05 revealed a significant difference in the mean altitude of haplotype groups 1 and 3 and cluster dendrogram groups 1 and 2 indicated by ^ab. Haplotype group 4 was not included in the analysis due to its low sample size.

Haplotype group	Rickettsia infection rate			Mean altitude
Haplotype group	Positive	Negative	Detection rate	Mean altitude
1	1	92	1.07%^ab	294^ab
2	28	99	22.04%^ab	341^a
3	16	110	12.70% ^a	374^ab
Dendrogram Group
1	4	120	3.23% ^ab	30
2	40	227	14.98% ^ab	345

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Fig 3 — Welch t-tests revealed a significant difference in the mean altitude between *Rickettsia-infected* and non-infected I. *ovatus* at p < 0.05. Populations with combined sites are labeled A to H.

Fig 4 — We excluded one population due to the limited number of samples.

The cox1 haplotype network of H. flava displayed two genetic groups (S2 Fig) consistent with the H. flava phylogenetic tree (S3 Fig). No significant difference between the Rickettsia infection rates of H. flava genetic groups 1 and 2 was observed using the z-score test at p < 0.05 (S3 Table).

Discussion

Our findings support our hypothesis that a genetically structured tick population, such as I. ovatus is associated with the Rickettsia infection rate to be spatially heterogenous due to limited gene flow along an altitudinal gradient. Our results were consistent with our previous study [11] which suggested that the low mobility of the host species for immature I. ovatus contributed to low gene flow in the tick populations. Despite the addition of new samples of I. ovatus and H. flava, we found a similar pattern of population genetic structure from the previous study of [11] thus supporting the robustness of their population genetic structure results. The low I. ovatus gene flow along the altitudinal gradient might have caused the spatial heterogeneity of Rickettsia infection rates among these populations, which is supported by the significant difference found in Rickettsia infection rates between genetic clusters 1 and 2. A similar pattern was observed in the studies of [49–51] which found that the infection rate of Borrelia burgdorferi, the causative agent of Lyme disease, decreased in ticks along the altitudinal gradient. Low gene flow can cause infected and uninfected ticks to have limited opportunities to traverse a wider spatial area thus causing a heterogeneous Rickettsia infection rate [52, 53].

We found two genetic groups in the H. flava haplotype network, but no significant difference in the Rickettsia infection rates between the two groups. These results might be due to the high gene flow observed in the H. flava populations, which enable Rickettsia-infected and uninfected H. flava individuals to traverse between the study sites. The high mobility of the large mammalian hosts used by adult H. flava and avian-mediated dispersal during their immature stage probably contributed to their homogenized population genetic structure [11], and the resulting homogenized Rickettsia infection rates. Large mammalian hosts and birds have a wide dispersal range that enables the broader movement of Rickettsia-infected ticks, as observed in previous studies of Amblyomma Americanum [13, 14, 54], H. flava [11], and I. ricinus [55]. Birds are especially good at dispersing over large areas since they can easily traverse landscape barriers such as mountains, fences, glaciers, and oceans that would be difficult for mammals to cross [56].

The different Rickettsia infection rates and altitudinal ranges between the I. ovatus phylogenetic groups maybe caused by diverse factors such as host availability and distribution, other environmental factors such as climate and vegetation, and anthropogenic factors such as urbanization. However, the adaptive evolutionary theory, which states that organisms adjust to new or severe changes in their environment to become better suited to their habitat [57, 58] maybe the best explanation for our results. Based on the relationship between the I. ovatus phylogenetic groups and their mean attitudes, I. ovatus might be undergoing local adaptation along the altitudinal gradient due to the higher genetic differentiation between populations as supported by the significant global F_ST (0.4154) found in I. ovatus. Based on isolation by environment (IBE), genetic differentiation will increase with increased environmental differences independent of geographic distances [33, 34, 59]. Thus in our study, the addition of I. ovatus together with the published data of [11] collected from an altitudinal gradient have shown genetic differences and different Rickettsia infection rate. When environmental conditions differ, the success of immigration in a new habitat is reduced, which may increase the genetic fixation rate due to a lower chance of outcrossing; thereby enhancing genetic isolation [60]. Thus, the lower gene flow along the altitudinal gradient reduced the spatial homogeneity of Rickettsia infection rates among the I. ovatus tick populations, thus causing the different Rickettsia infection rates obtained.

The occurrence of local adaptation in tick populations could affect the future of the tick-borne disease landscape. Environmental factors, such as precipitation, temperature, and altitude, have been shown to drive population differentiation in insects, such as Anopheles mosquitoes and Drosophila flies [61–63], but studies on the environmental adaptation of ixodid ticks, such as I. ovatus, and its Rickettsia infection susceptibility, have not yet been performed. [7] suggested that environmental conditions that affect bird hosts can also affect the local adaptation of ticks. Few studies have assessed such local adaptation in multiple organisms with varying dispersal abilities [64–68] and is an area in need of future research.

One of the limitations of this study is the use of one mitochondrial gene cox1 which limited us to compare our results with other target genes to highly support our findings. If markers with high mutation rates or many markers were used, it might have been possible to look at even finer population genetic structure and see differences in infection rates among the subdivided populations. Despite this, we were able to determine the relationship between the tick population genetic structure and Rickettsia infection rates as influenced by the altitudinal gradient. The mitochondrial cox1 gene has been widely used for population genetic analysis of many tick species and was proven to be informative in determining the relationship from the subfamily to the population levels [69–73]. Mitochondrial genes have a mutation rate that is useful in species-level phylogenetics and can be used for wide geographic ranges however its resolution is not fine enough to study species selection [10]. In future studies, we suggest including additional mitochondrial genes and or nuclear genes.

Since ticks are blood-sucking ectoparasites, they directly influence their mammalian hosts and the pathogens they transmit [74–76]. The interaction between the vector (tick), host, and pathogen (Rickettsia) is essential in understanding and predicting the risk and transmission of tick-borne diseases [77]. Understanding the genetic structure of ticks can serve as an alternative indicator to infer the potential spread of its pathogen [78]. Our study found relationships between (1) the population genetic structure of ticks and the corresponding Rickettsia infection rates, (2) altitude and the population genetic structure of ticks, and (3) altitude and Rickettsia infection rates. Though our results can provide a useful information about the tick distribution and possible potential spread of pathogens, there are some factors that should also be considered to apply our results such as ticks can have different mammalian hosts during different life stages in the field that have varying hosts mobility and other environmental factors can also affect such as temperature, humidity etc.. can also be a factor. We found that host mobility may influence the genetic structure of ixodid ticks. This information can be used to design more effective tick-borne disease control programs that focus on screening and detecting pathogens found in ticks and their mammalian hosts. For example, patterns of disease transmission from ticks with a high genetic divergence and less mobile hosts, such as I. ovatus, are likely due to the movement of infected hosts rather than infected ticks. Thus, screening prospective tick hosts for Rickettsia infection would be more suitable in this example. We suggest screening the hosts of immature I. ovatus, such as small rodents, instead of screening ticks. The Rickettsia infection rate in tick genetic groups can predict the spread of tick-borne diseases caused by Rickettsia, such as the Japanese spotted fever. We also found that altitude may influence the Rickettsia infection rate of I. ovatus genetic groups. This information can be used to determine the high-risk areas (e.g., lowland, mountains, etc.) of tick-borne diseases along an altitudinal gradient. Genetically structured arthropod vectors, such as ticks, can have different vector competencies, and environmental factors, such as altitudinal gradients, that can influence the vector’s ability to acquire, transmit, and maintain the pathogen infection [79].

Supporting information

S1 Table. Summary of Ixodes ovatus and Haemaphysalis flava collected from the different locations of Niigata Prefecture and its corresponding sample number and number of Rickettsia infection per site.

(XLSX)

pone.0298656.s001.xlsx^{(16KB, xlsx)}

S2 Table. Summary of PCR primers used in the detection of Spotted fever group Rickettsia.

(DOCX)

pone.0298656.s002.docx^{(13.7KB, docx)}

S3 Table. The difference in Rickettsia infection rates in H. flava haplotype groups and a table showing the distribution of Rickettsia-infected and uninfected H. flava in each genetic groups as shown in S2 Fig (H. flava median-joining network).

The results of the z-score test for two populations proportions at p < 0.05 showed no significant difference between the Rickettsia detection rate in haplotype groups 1 and 2. The Welch t-test at p < 0.05 revealed no significant difference in the mean altitude of the two groups.

(XLSX)

pone.0298656.s003.xlsx^{(9.9KB, xlsx)}

S1 Fig. Phylogenetic tree from the BEAST analysis of 59 haplotype cox1 sequences of I. ovatus.

The blue-labeled haplotypes indicate the presence of Rickettsia infection. The red parentheses provide the number of Rickettsia-positive individuals per haplotype. The black labeled haplotypes are negative for Rickettsia infection.

(DOCX)

pone.0298656.s004.docx^{(100.8KB, docx)}

S2 Fig. Median-joining network of the 66 cox1 haplotype sequences of Rickettsia positive and negative H. flava.

Haplotype groups are indicated as 1 and 2.

(DOCX)

pone.0298656.s005.docx^{(204.1KB, docx)}

S3 Fig. Phylogenetic tree from the BEAST analysis of 66 haplotype cox1 sequences of H. flava.

The blue-labeled haplotypes indicate Rickettsia infection in individual samples. The parentheses in red provide the number of Rickettsia-infected ticks. The black-labeled haplotypes are negative for Rickettsia infection.

(DOCX)

pone.0298656.s006.docx^{(104.4KB, docx)}

Acknowledgments

The authors are thankful for the assistance from the Niigata Prefectural Office during the tick sampling collection. We would also like to thank the alumni of MECOH Lab Ehime University for their help in molecular analyses: Masaya Doi, Kohki Tanaka, and Mizuki Ueda. We are also grateful to Micanaldo Francisco for the construction of the map for this manuscript. We would like to thank Enago (www.enago.jp) for the English language review and proofreading of the manuscript.

Data Availability

Sequences used for analysis are available in the GenBank database under the accession numbers MW063669 to MW064124, MW065821 to MW066347, OR975837 to OR975875 and OR975876 to OR975898.

Funding Statement

This study was supported by the Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) to a project on Joint Usage/Research Center– Leading Academia in Marine and Environment Pollution Research (LaMer).The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PONE-D-23-12494Rickettsia infection rate along an altitudinal gradient as influenced by population genetic structure of Ixodid ticksPLOS ONE

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USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/

Additional Editor Comments:

Dear Authors, although the total number of ticks and haplotypes for I. ovatus and H. flava, were slightly increased, the main concepts have already been published (Infect Genet Evol. 2021 Oct;94:104999. doi: 10.1016/j.meegid.2021.104999).

I decided to rate/accept the work as a major revision if previously published data is removed from this paper (see, for example, lines 221-235 and 271-274).

I suggest focusing the article on Rickettsia data, supported by previous results.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The data of the manuscript have been previously published and re-analysis has been performed on them. I think you should just focus on the new main data. Therefore, it is recommended to rewrite the manuscript and also, submit it to an entomology journal.

Reviewer #2: The manuscript is really interesting and brings good results for scientific community. Authors studied the ecological and genetic factors that may affect the infection rate of Rickettsia spp., an important pathogen of zoonotic concern. The study is well designed, results are clear and shows a correlation between genetic structure of ticks and infection rate.

Title: I would suggest (see coment bellow on results) to adjust the title of the manuscript:

Rickettsia infection rate along an altitudinal gradient as influenced by population genetic structure of Ixodes ovatus and Haemaphysalys flava ticks.

Since it was not possible to evaluate the altitudinal influence on the genetic structure of many Ixodid species, it is better to highlight the species present on the study. Also, on the abstract, authors wrote the goal/results of the study being: ‘This study describes the population genetic structure and gene flow of I.ovatus and H. flava and their Rickettsia infection rates along an altitudinal gradient. A total of 346 adult I. ovatus and 243 H. flava were analyzed for the presence of Rickettsia by nested PCR targeting the 17kDA, gltA, rOmpA, and rOmpB genes’, not mentioning the other tick species sampled and tested.

The manuscript could be benefit if some sections were rewrite to make the text more flowing.

For example:

Line 51: 'Tick dispersal of many three-host Ixodid ticks depends on the movements of their vertebrate hosts, which influences each tick’s potential to spread its pathogen [7-8].'

- The word tick is repeated 3 times in one sentence. Suggestion: The potential of spreading pathogens might be influenced by ticks’ dispersal, which is related to the movements of their vertebrate hosts, especially in three-host Ixodidae species.

Introduction

Lines 98-102: ‘The present study used cytochrome oxidase 1 (cox1) mitochondrial gene

sequences and Rickettsia-infected and uninfected data…..

- This is material and methods, and should not be mentioned in the introduction.

Material and Methods

Line 109: I. monospinus (n = 4), and I. nipponensis (n = 2) from…

- I suggest to remove the tick species, since it was not possible to evaluate the

Line 154: The protein-coding genes were translated to amino acids to confirm the absence of stop codons.

- Using which software - citation?

Line 158: Multiple sites that are in proximity to each other were combined for population genetic analysis

- What ‘in proximity’ means? If another research wants to repeat the experiment, how should populations be combined by ‘proximity’? Distance of 1 kilometer, 100 kilometers?

Results

Line 192: I. monospinus (neg = 11, pos = 6); I. asanumai (neg = 4, pos=5); I. nipponensis (pos = 4); I. persulcatus (neg = 4); and H. japonica (pos = 2).

- I would suggest to remove all results from the other tick species, since it does not fit the objective of the study: ‘This study describes the population genetic structure and gene flow of I. ovatus and H. flava and their Rickettsia infection rates along an altitudinal gradient’.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

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Attachment

Submitted filename: PONE-D-23-12494_reviewer.pdf

pone.0298656.s007.pdf^{(2.3MB, pdf)}

PLoS One. 2024 Mar 13;19(3):e0298656. doi: 10.1371/journal.pone.0298656.r002

Author response to Decision Letter 0

14 Aug 2023

2023 August 14

Dr. Maria Stefania Latrofa

Academic Editor

PLOS ONE

Dear Dr. Latrofa,

We are pleased to submit the revised version of the submitted manuscript entitled “Rickettsia infection rate along an altitudinal gradient as influenced by population genetic structure of Ixodes ovatus and Haemaphysalis flava ticks”.

The manuscript was modified accordingly to the editor’s and reviewers’ comments and suggestions. Moreover, the authors answered and explained carefully each of the feedback received from both the editors and reviewers. For your reference, the manuscript was revised accordingly with its corresponding line numbers and highlighted the changes within the manuscript.

The authors confirmed that this manuscript has not been published or is under consideration in another journal. All the authors have read and approved the revisions and contents of this manuscript and agreed to the submission policies of PLOS ONE. All authors have contributed to the research and manuscript writing. The authors have no conflicts of interest to disclose.

Moreover, following PLOS ONE’s style requirements and file naming, we have revised the manuscript carefully.

The authors acknowledge the editors and the reviewers for their helpful comments and suggestions thus improving the overall manuscript. We are looking forward that these revisions will warrant acceptance for publication in your notable journal, PLOS ONE.

Sincerely Yours,

Dr. Kozo Watanabe, Professor

Center for Marine Environmental Studies (CMES)

Ehime University, Bunkyo-cho 3, Matsuyama, 790-8577, Japan

Email: watanabe.kozo.mj@ehime-u.ac.jp

Editor’s comments: Changes are highlighted in green in the revised manuscript with the track changes file

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response: Thank you very much for this comment. We now revised the manuscript following the PLOS ONE style's requirements. Highlighted in green in the manuscript are the changes for the affiliation format, font size per manuscript section, and mention of Figures were changed to Fig. in adherence to PLOS ONE's style requirements.

We will update your Data Availability statement to reflect the information you provide in your cover letter.

Response: Sequences used for analysis are available in the GenBank database under the accession numbers MW063669-MW064124 and MW065821 - MW066347. Additional sequences of I.ovatus (n=39) and H.flava (n=23) collected in 2018 were deposited in NCBI Genbank with the accession numbers currently being processed, we will inform PLOS One immediately once we receive the numbers.

Response: The authors acknowledged this comment thus we deposited on NCBI Genbank the additional sequences of I.ovatus (n=39 ) and H.flava (n=23) currently under submission at NCBI and accessions numbers are being processed, once we receive it we will inform PLOS One immediately.

We require you to either (a) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (b) remove the figures from your submission:

a. You may seek permission from the original copyright holder of Figure 2 to publish the content specifically under the CC BY 4.0 license.

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

Please upload the completed Content Permission Form or other proof of granted permissions as an "Other" file with your submission.

The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/

Landsat: http://landsat.visibleearth.nasa.gov/

USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/

Response: The authors appreciate your comment about Figure 2. This figure is not a previously copyrighted map or satellite image from proprietary data. The map was created using ArcGIS software version 10.2 (ESRI, Redlands, CA). In creating the map, we used digital elevation data and administrative boundaries data. The digital elevation data is a single-band raster image generated from the Shuttle Radar Topography Mission (SRTM) satellite. STRM data is provided at a spatial resolution of 1 arc-second (approximately 30m) (Farr, et al. 2007). This satellite-based elevation data was freely obtained using Google Earth Engine (GEE) code editor platform (Gorelick, et al. 2017). GEE code editor is a web-based Integrated Development Environment for writing and running Java scripts to support geospatial analysis (Google 2021). The GIS data of administrative boundaries of Japan was freely obtained in vector polyline format from the DIVA-GIS website (DIVA-GIS n.d.). DIVA-GIS is aimed at those who cannot afford generic commercial geographic information system data and software (Hijmans, Guarino, and Mathur 2012).

5. Dear Authors, although the total number of ticks and haplotypes for I. ovatus and H. flava, were slightly increased, the main concepts have already been published (Infect Genet Evol. 2021 Oct;94:104999. doi: 10.1016/j.meegid.2021.104999).

I decided to rate/accept the work as a major revision if previously published data is removed from this paper (see, for example, lines 221-235 and 271-274).

I suggest focusing the article on Rickettsia data, supported by previous results.

Response: The authors are grateful for this valuable comment. We would like to clarify that

we agree with the editor's point that the concept of genetic differentiation along elevation has already been published. Therefore, in the discussion of the revised manuscript, we have removed all elements related to the published concepts, focusing primarily on the differences in Rickettsia infection rates observed among genetic groups of I. ovatus along an altitudinal gradient, which is the main and new concepts of this study. However, we could not remove the results of the population genetic structure based on the newly obtained in this study and previously published cox1 data from the result section, as this information is the basis for reporting the new concept of this study.

Specifically, the following lines in the original manuscript were removed in the revised manuscript.

Original MS, changes are highlighted in green with strikethrough

L284-286: The significant global FST estimate of 0.4154 among the I. ovatus populations revealed genetic differentiation between the populations as supported by the occurrence of two genetic clusters in the cluster dendrogram.

Original MS L309-329 In addition to host mobility, environmental factors can influence the population genetic structure of ticks [54]. Each tick species has preferred environmental conditions that are conducive to completing the tick life cycle, thus influencing the geographical distribution of ticks and the risk areas for tick-borne diseases [55-56]. Altitude may influence the population genetic structure of ticks through the effect of altitude on the distribution and abundance of ticks and/or their hosts [57-59]. Altitudinal differences between populations can affect genetic divergence [60], through, for example, ecological isolation, which causes natural selection against maladapted immigrants and limits gene flow [61-62]. For example, organisms adapted to low altitudinal sites that cannot tolerate the lower temperatures at higher altitudes would not survive if they dispersed to those higher altitude sites, thus restricting gene flow across the altitudinal gradient [60].

The difference in mean altitude between I. ovatus cluster groups 1 and 2 might be due to adaptive divergence along the altitudinal gradient. Individuals from cluster group 1 were distributed in higher altitude areas of the northern mountainous area of Niigata Prefecture, while cluster group 2 individuals were found in the lower altitude regions of northern Niigata Prefecture. Populations along an altitudinal gradient are prone to differentiating selection pressures, which result in local adaptation [63]. Altitudinal gradients may also cause the varying ambient temperature, precipitation, and humidity levels essential to ticks' development and survival [64]. These varying environmental factors may cause ticks to have difficulty dispersing over a wide habitat range. Thus, ticks may need to adapt to extreme habitats, such as extreme altitude or precipitation levels, for survival. For example, Rhipicephalus compositus were found in altitudes of 1000–2500 m, but optimal conditions were between 1200–2500 m [64-66].

And the following lines were left in the Revised MS: L221-239:

Based on the population genetic analysis of the cox1 sequences, we found a significant global FST of 0.4154 at p < 0.05 for I. ovatus (Table 1). In contrast, no significant global FST values were observed in the H. flava, I. monospinus, I. asanumai, I. nipponensis, or I. persulcatus samples (Table 1). There were 59 and 66 cox1 haplotypes found among the 346 I. ovatus and 243 H. flava individuals, respectively. We found the following number of cox1 haplotypes in the remaining species: I. monospinus (n = 9), I. asanumai (n = 4), I. nipponensis (n = 4), I. persulcatus (n = 3), and H. japonica (n = 2).

The cox1 haplotype network of I. ovatus (Fig 1) revealed four genetic groups, wherein three genetic groups (1, 2, and 3) were distributed along different altitudinal gradients, as shown in Fig 2. These four genetic groups were concordant with the four clusters found in the I. ovatus phylogenetic tree (S1 Fig). The habitat distribution of genetic group 3 was limited to high altitude sites only (range = 16–912 m.a.s.l.), whereas genetic groups 1 (255–471 m.a.s.l.) and 2 (84–1354 m.a.s.l.) were distributed at lower altitudes (Fig 2). The Welch t-test revealed a significant difference between the mean altitudes of genetic groups 1 and 3 at p < 0.05 (Table 2); however, no significant difference was observed between genetic groups 1 and 2 or groups 2 and 3.

The following L271-274 were also removed: The cox1 haplotype network of H. flava displayed two genetic groups (S2 Fig) consistent with the H. flava phylogenetic tree (S3 Fig). Based on the Welch t-test, we found no significant differences in mean altitude (205 and 165 m.a.s.l.) at p < 0.05 between the two H. flava genetic groups (S3 Table).

The authors also modified the objectives of the manuscript to highlight the relationship between Rickettsia infection rate and population genetic structure.

The following lines were removed in the introduction L73-77: Thus, in this study, we expected to see a highly divergent population genetic structure in I. ovatus along an altitudinal gradient due to the limited movement of their mammalian hosts along that gradient; whereas H. flava should show a less divergent structure along the altitudinal gradient due to the higher mobility of its hosts. To our knowledge, no studies have focused on tick gene flow along an altitudinal gradient.

We also revised the following lines 92-93: Here, we determine the relationship between Rickettsia infection rates as influenced by population genetic structure along an altitudinal gradient.

We also included the following lines 95-98: Thus based on the results of [11], we hypothesized that in I. ovatus with a strong population genetic structure, we expect to see a heterogenous Rickettsia infection rate along an altitudinal gradient. In contrast to the homogenous genetic structure of H. flava wherein we expect to observe a homogenous Rickettsia infection rate.

The following lines 288-290 were added: Despite the addition of new samples of I. ovatus and H. flava, we found a similar pattern of population genetic structure from the previous study of [11] thus proving the robustness of their population genetic structure results.

Reviewer 1’s comments: Changes are highlighted in purple in the revised manuscript with the track changes file

1. Is the manuscript technically sound, and do the data support the conclusions?

Response: The authors appreciate your comment.

2. Has the statistical analysis been performed appropriately and rigorously? No

Response: The authors have performed rigorous statistical analysis to determine the significant difference of the Rickettsia infection rate between the haplotype groups for both species I.ovatus and H. flava, please see L237-241:

The Welch t-test revealed a significant difference between the mean altitudes of genetic groups 1 and 3 at p < 0.05 (Table 2); however, no significant difference was observed between genetic groups 1 and 2 or groups 2 and 3. We found a significant difference in the Rickettsia infection rates between I. ovatus genetic groups 1 and 2 based on the z-score test, but no significant difference between groups 1 and 3 or groups 2 and 3 (Table 2). The mean altitude between the Rickettsia-infected (=273.72 m.a.s.l.) and non-infected I. ovatus (=369.61 m.a.s.l.) revealed a significant difference based on the Welch t-test at p < 0.05 (Fig 3).

3. Have the authors made all data underlying the findings in their manuscript fully available?

Response: The authors have uploaded the sequences used in the analysis in NCBI repository with accession numbers MW063669-MW064124 and MW065821 - MW066347. Additional sequences of I.ovatus (n=39) and H.flava (n=23) collected in 2018 were deposited in NCBI Genbank and are currently being processed for accession number. We will inform PLOS One soon once we received the accession numbers.

4. Is the manuscript presented in an intelligible fashion and written in standard English?

Response: Thank you for your comment. Our manuscript has been checked for English grammar and language style and revised accordingly by a reputable language proofreading company for scientific research articles, Enago.

5. Review Comments to the Author

The data of the manuscript have been previously published and re-analysis has been performed on them. I think you should just focus on the new main data. Therefore, it is recommended to rewrite the manuscript and also, submit it to an entomology journal.

Response: The authors are thankful for this comment. We revised the manuscript accordingly to highlight the Rickettsia data and use the previously published data and additional sequence data for both I. ovatus and H. flava to support our results that low gene flow in the I. ovatus populations has caused spatially heterogenous Rickettsia infection rates along the altitudinal gradient. Please also see our response to the editor’s comment E5.

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Response: The authors respect the decision of the reviewer to remain anonymous once the manuscript is accepted for publication.

Reviewer 2’s comments: Changes are highlighted in blue in the revised manuscript with the track changes file

1. Is the manuscript technically sound, and do the data support the conclusions?

Yes

Response: The authors are grateful for this feedback.

2. Has the statistical analysis been performed appropriately and rigorously? Yes

Response: Thank you for this comment.

3. Have the authors made all data underlying the findings in their manuscript fully available?

Response: The authors are thankful for these comments.

4. Is the manuscript presented in an intelligible fashion and written in standard English?

Response: Thank you for your time and effort to read and give valuable comments for the improvement of the manuscript.

5. Review Comments to the Author

The manuscript is really interesting and brings good results for scientific community. Authors studied the ecological and genetic factors that may affect the infection rate of Rickettsia spp., an important pathogen of zoonotic concern. The study is well designed, results are clear and shows a correlation between genetic structure of ticks and infection rate.

Response: The authors are thankful for Reviewer 2’s comments and suggestions to improve the manuscript.

6. I would suggest (see coment bellow on results) to adjust the title of the manuscript:

Rickettsia infection rate along an altitudinal gradient as influenced by population genetic structure of Ixodes ovatus and Haemaphysalys flava ticks. Since it was not possible to evaluate the altitudinal influence on the genetic structure of many Ixodid species, it is better to highlight the species present on the study. Also, on the abstract, authors wrote the goal/results of the study being: ‘This study describes the population genetic structure and gene flow of I.ovatus and H. flava and their Rickettsia infection rates along an altitudinal gradient. A total of 346 adult I. ovatus and 243 H. flava were analyzed for the presence of Rickettsia by nested PCR targeting the 17kDA, gltA, rOmpA, and rOmpB genes’, not mentioning the other tick species sampled and tested.

The manuscript could be benefit if some sections were rewrite to make the text more flowing.

Response: We appreciate your suggestion and agreed with it. We changed the title, please see L1-2:

Rickettsia infection rate along an altitudinal gradient as influenced by population genetic structure of Ixodes ovatus and Haemaphysalis flava tick

Please see L23-24:

This study describes the Rickettsia infection rates influenced by the population genetic structure of I.ovatus and H. flava along an altitudinal gradient.

7. Line 51: Tick dispersal of many three-host Ixodid ticks depends on the movements of their vertebrate hosts, which influences each tick’s potential to spread its pathogen [7-8].'

Response: The following L50-52 have been revised accordingly:

The potential of spreading pathogens might be influenced by ticks’ dispersal, which is related to the movements of their vertebrate hosts, especially in three-host Ixodidae species [7-8].

8. Lines 98-102 ‘The present study used cytochrome oxidase 1 (cox1) mitochondrial gene

sequences and Rickettsia-infected and uninfected data…..

- This is material and methods, and should not be mentioned in the introduction.

Response: Thank you for your valuable comment. We removed the following L97-101

in the introduction of the original MS and incorporated it in the materials and methods section of the revised MS L105-106:

In this study, we used cox1 sequence data from [11] for I. ovatus (n = 307) and H. flava (n = 220) ticks collected from April 2016 to November 2017 from 30 sites across the Niigata..... and L113-116 To strengthen our analysis, we also added new cox1 sequences and Rickettsia-infected/uninfected ticks from I. ovatus (n= 39) and H. flava (n=23) individual collected from April to October 2018 , total of (n=62) sampled at 30 sites across the Niigata Prefecture, including two sites not previously sampled by [11].

9. Line 109 I. monospinus (n = 4), and I. nipponensis (n = 2) from…

- I suggest to remove the tick species, since it was not possible to evaluate the

Response: Thank you for the suggestion. We would like to clarify what is not possible to evaluate? Since the comment was incomplete, the authors are unsure of the whole meaning of the comment however we removed the following L108: I. monospinus (n = 4), and I. nipponensis (n = 2).

Please see L109-110 of the revised MS: Rickettsia infection rate data were obtained from [6] from I. ovatus (n = 29) and H. flava (n = 2) from 38 sites across Niigata Prefecture.

10. Line 154 The protein-coding genes were translated to amino acids to confirm the absence of stop codons.

- Using which software - citation?

Response: We revised it accordingly, please see L156-158:

The protein-coding genes were translated to amino acids to confirm the absence of stop codons and the final aligned sequences were checked in Mesquite version 3.5 [38].

11. Line 158: Multiple sites that are in proximity to each other were combined for population genetic analysis

- What ‘in proximity’ means? If another research wants to repeat the experiment, how should populations be combined by ‘proximity’? Distance of 1 kilometer, 100 kilometers?

Response: We revised the sentence accordingly. Please see L161-162:

In this regard, we also added information about this in the following L163-165:

Three sites were excluded from the population genetic analysis because of the limited number of obtained individuals (<8) and the lack of a nearby site within 80 kilometers to combine into a single population.

12. Line 192: I. monospinus (neg = 11, pos = 6); I. asanumai (neg = 4, pos=5); I. nipponensis (pos = 4); I. persulcatus (neg = 4); and H. japonica (pos = 2).

Response: Thank you for your suggestions. The authors agreed to focus on I.ovatus and H. flava data only, please see the revised L191-192:

The total number of positive (pos) and negative (neg) ticks for Rickettsia infections from the ticks collected in 2018 were: I. ovatus (neg = 22, pos = 17) and H. flava (neg = 10, pos = 13) .

We removed the information about the other tick species, please see L195-196:

In this study, the total number of samples from the previously published data [6;11] and the adult ticks whose cox1 was successfully sequenced per species were: I. ovatus (346) and H. flava (243).

Table 1 was also revised and only the information about the I. ovatus and H.flava were retained.

Also in L214-215 We detected SFGR in 78 (12.44%) out of 627 ixodid ticks, with the highest detected in I. ovatus (46/346; 13.29%) and in H. flava (15/243; 6.17%).

We also removed in the discussion L343-363 In this study, only a few (n < 20) I. monospinus, I. asanumai, I. nipponensis and H. japonica were collected; however, a high Rickettsia infection rate (31.58%–100%) was found despite these limited numbers. In previous studies, high Rickettsia infection rates despite a few individuals were also observed in I. monospinus in several prefectures in Japan [71-73]. The extent of tick habitat distribution may vary between species, which may have influenced the widely different Rickettsia infection rates observed among the species in this study. The high Rickettsia infection rate in these ticks is probably due to effective transovarial transmission [74]. Furthermore, Rickettsial endosymbionts are inclined to have a high infection rate in some tick species populations because they contribute to the tick microbiome which might imply nutritional symbiosis in the tick species with high Rickettsia infection despite the low number of samples tested [75-77]. Additionally, the few collected individuals of these species may be habitat specialists that thrive in a narrow habitat range in contrast to I. ovatus and H. flava, which may be habitat generalists capable of thriving in a wide habitat range [78]. The narrow habitat range of habitat specialist ticks might have enabled increased interactions between infected and uninfected Rickettsia ticks within the small spatial scale compared to the habitat generalist ticks, thus causing their high Rickettsia infection rates. This conclusion should be considered with caution, since the limited number of individual ticks collected across the Niigata Prefecture may have caused a bias in the estimated Rickettsia infection rates determined in this study. We suggest conducting future research on Rickettsia infection rates in a wider sampling range with an increased number of I. monospinus, I. asanumai, I. nipponensis, and H. japonica individuals to further increase our understanding of the association between Rickettsiae and their tick vectors.

13. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Response: The authors understand and respect the decision of Reviewer 2, to not disclose his/ her identity for peer review history once the manuscript is published.

14. From the attached file: Line 56: Ixodes ovatus (complete scientific name at beginning of the sentence).

Response: The authors acknowledge this comment, and we revised this accordingly, please see L55-56

Ixodes ovatus populations had greater genetic divergence possibly…..

15. Line 84: Haemaphysalis flava to H. flava

Response: This was changed accordingly, please see L83: Japan in the following tick species: Dermacentor taiwanensis, H. flava, Haemaphysalis hystricis, …...

References:

DIVA-GIS. n.d. Free Spatial Data. Accessed 2021. https://www.diva-gis.org/Data.

Farr, T.G., P.A. Rosen, E. Caro, R. Crippen, R. Duren, S. Hensley, M. Kobrick, et al. 2007. The shuttle radar topography mission: Reviews of Geophysics, v. 45, no. 2, RG2004.

Google. 2021. Google Earth Engine Code Editor. Accessed 1 6, 2022. https://earthengine.google.com/platform/.

Gorelick, Noel Hancher, Matt Dixon, Mike Ilyushchenko, Simon Thau, David Moore, and Rebecca. 2017. "Google Earth Engine: Planetary-scale geospatial analysis for everyone." Remote Sensing of Environment (Elsevier) 202: 18-27. doi:10.1016/j.rse.2017.06.031.

Hijmans, Robert J., Luigi Guarino, and Prem Mathur. 2012. DIVA-GIS Manual Version 7.5. California.

PLoS One. doi: 10.1371/journal.pone.0298656.r003

Decision Letter 1

Maria Stefania Latrofa

16 Oct 2023

PONE-D-23-12494R1Rickettsia infection rate along an altitudinal gradient as influenced by population genetic structure of Ixodes ovatus and Haemaphysalis flava ticksPLOS ONE

Dear Dr. Watanabe,

Please submit your revised manuscript by Nov 30 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
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We look forward to receiving your revised manuscript.

Kind regards,

Maria Stefania Latrofa

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

Reviewer #3: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: No

Reviewer #3: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #2: The manuscript was changed according to my suggestions. Although using already published data, all references were properly added, and authors reanalyzed and showed new results. The manuscript has a good flow of ideas, with all results presented in details. Also, ecological studies, although many times “suggestive”, are important for epidemiological information.

I would recommend another correction of the manuscript once the sequences are available at GenBank, so we can confirm and reanalyze the data. Only a few suggestions regarding the text.

Line: 114 ‘Genomic DNA was extracted using Isogenome DNA extraction kits (Nippon Gene Co.Ltd. Tokyo, Japan) following the manufacturer's recommended protocol.’

- Authors said that each tick was individually identified morphologically. Ticks were also extracted individually or in pools? Add please.

Table 1: ‘** not 195 enough samples for analysis’

- There is no ** on the table, only * and ***. Maybe it is a typing error?

Table 2: (indicated by ab). Please correct the ), it is not overwritten.

References

The references need standardization. Each reference is shown in a different format. Please check the author guidelines for proper standardization. Please be careful in the next submission, all references must be according to guidelines.

Data availability

Before the next ‘round’ of corrections, it would be necessary to control accession numbers. In the section “Material and Methods, Published data”, please add the accession numbers of the used sequences. They are already (I hope) available at GenBank, since it was already published. Also, in the section “Unpublished data”, add all accession numbers.

Reviewer #3: Overall, the authors have been receptive to the feedback and have made several changes in the manuscript to address the previous reviewers' concerns. However, the manuscript still echoes significantly with your previously published popgen study. The data and findings still appear to be an extension rather than presenting novel insights specific to Rickettsia. Below are specific suggestions for each section:

The title

"as influenced by population genetic structure" suggests a strong causal relationship between the genetic structure of the ticks and the Rickettsia infection rate. Also, there may be more than just the influence of the genetic structure on the infection rate (e.g., environmental factors, tick behavior, etc.). A suggestion: “Genetic Structure and Rickettsia Infection Rates in Ixodes ovatus and Haemaphysalis flava Ticks Across Different Altitudes"

Abstract

L25-26: Change to “The population genetic structure was analyzed utilizing the mitochondrial…”

L30-31: Change to “A significant difference was observed in Rickettsia infection rates and mean altitude per group between the two cluster groups and the three genetic groups identified within I. ovatus”

L33-34: I suggest a more cautious tone when making such conclusions eg. “Our results suggest a potential correlation between the low gene flow in I. ovatus populations and the spatially heterogeneous Rickettsia infection rates observed along the altitudinal gradient”

Introduction

L43-44: This sentence seems isolated, elaborate on why the size of ticks influences their dispersal and how host movement plays a role e.g. “Their dispersal is linked to the mobility of their hosts, relying on them to disperse into new landscapes and potentially introduce pathogens”

L83-44: This statement is overgeneralizing by saying “ticks” and “rickettsia”, try to be more specific.

L86-87: Add to this sentence the reasoning why this relationship is important to strengthen the introduction of your objectives. Can be reworded eg. “In this study, we elucidate the relationship between Rickettsia infection rates and population genetic structure along an altitudinal gradient…to improve public health etc.”

Methodology

L121: A table with PCR primers for rickettsia (like in Arai 2021), the target size and references and annealing temps used could be useful. Also try to reference the primary primer source for each rickettsial gene rather than secondary source (authors previously published work)

L175-178: It might be useful to provide more details about why these specific tests were chosen and if the data meet the assumptions of these tests (e.g. normality, equal variances etc.).

L130-135: The primer pair sequences for forward and reverse primers seems to be identical, please double check this info. Although you referenced your previous study for the details, include a reference for primer sequences as you’ve stated them with none.

L167-169: It’s not clear if a model testing tool was used to select the model used for the trees, if a model-testing tool was used but not mentioned, add a few sentences detailing this step as it will help improve stats robustness.

L170-177: After explaining the method, immediately tie it back to the implications it has for understanding Rickettsia infection rates or distribution.

Discussion

L256-257: use terms like “associated with” instead of “can cause” to ensure that the language reflects the type of relationship (causal or correlational) indicated by your data

Line 262-263: same as above point

L281-287: This is a strong point but could be strengthened. Discuss how your findings specifically align with adaptive evolutionary theory. Consider discussing any alternative explanations for the observed patterns and why local adaptation might be the most plausible explanation.

L288-290: Consider removing the emphasis of the previous study's results and instead highlight how these new samples provide additional insight or a different perspective on Rickettsia infection rates.

L303- 306: Consider also discussing how this limitation might specifically impact your findings

L310-327: Are there challenges/considerations that might need to be addressed to apply these findings in a real-world context?

GenBank Accession numbers: You mentioned uploading the new Cox sequences, what about the Rickettsia sequences as these are the focal point of the study (maybe I missed them while checking?) and are required for validation of your findings

Figures 1-4 : they are blurry and lack clarity, which might hinder the understanding of the data presented. guidelines by Plos one "Ensure that your images have a resolution of at least 300 pixels per inch (ppi) and appear sharp, not pixelated.

Be careful not to inadvertently reduce the resolution when creating a file in graphics editing software "

I hope the comments and suggestions are helpful with your paper.

Warm regards and happy revising!

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

Reviewer #3: No

**********

PLoS One. 2024 Mar 13;19(3):e0298656. doi: 10.1371/journal.pone.0298656.r004

Author response to Decision Letter 1

27 Dec 2023

2023 December 27

Dr. Maria Stefania Latrofa

Academic Editor

PLOS ONE

Dear Dr. Latrofa,

We are pleased to submit the revised version of our manuscript entitled "Genetic structure and Rickettsia infection rates in Ixodes ovatus and Haemaphysalis flava ticks across different altitudes". This resubmission incorporates all the modifications based on the valuable comments and suggestions provided by both the editors and reviewers.

Throughout the revision process, we carefully addressed each comment and suggestion received, ensuring a thorough response to improve the manuscript. We have made the necessary revisions in line with the editor's and reviewers' recommendations, and these changes have been indicated within the manuscript with their corresponding line numbers.

The authors agreed that this manuscript has not been published elsewhere nor is it under consideration by another journal. All authors have carefully reviewed and approved the revised content, aligning with PLOS ONE's submission policies. Additionally, we confirm that there are no conflicts of interest to disclose among the authors.

We revised the manuscript in adherence to PLOS ONE's style requirements and file naming. The authors are grateful to the editors and reviewers for their constructive comments and valuable suggestions, which have significantly improved the overall quality of the manuscript.

We hope that these revisions have improved the manuscript, making it suitable for publication in PLOS ONE journal. We look forward to your kind consideration and hope for a positive outcome.

Sincerely Yours,

Dr. Kozo Watanabe, Professor

Center for Marine Environmental Studies (CMES)

Ehime University, Bunkyo-cho 3, Matsuyama, 790-8577, Japan

Email: watanabe.kozo.mj@ehime-u.ac.jp

Reviewer 2’s comments: Changes are highlighted in yellow in the revised manuscript with the track changes file

All comments have been addressed

Response: The authors are thankful for the reviewer’s comments and suggestions.

2. Is the manuscript technically sound, and do the data support the conclusions?

Yes

Response: We are thankful for this comment.

3. Has the statistical analysis been performed appropriately and rigorously?

Yes

Response: We appreciate your response.

4. Have the authors made all data underlying the findings in their manuscript fully available?

Response:

Please see L103-104 Sequences used for analysis are available in the GenBank database under the accession numbers MW063669 to MW064124 and MW065821 to MW066347.

For the unpublished data and additional samples, please see L113-114 The sequences are available in the GenBank database under the accession numbers OR975837 to OR975875 and OR975876 to OR975898.

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Yes

Response: Thank you for the feedback.

6. The manuscript was changed according to my suggestions. Although using already published data, all references were properly added, and authors reanalyzed and showed new results. The manuscript has a good flow of ideas, with all results presented in details. Also, ecological studies, although many times “suggestive”, are important for epidemiological information.

I would recommend another correction of the manuscript once the sequences are available at GenBank, so we can confirm and reanalyze the data. Only a few suggestions regarding the text.

Response: The authors appreciate all the comments and suggestions and we carefully addressed all of these in this revision. All the sequences have been deposited in Genbank as previously mentioned in the previous comment #4.

7. Line: 122-123 ‘Genomic DNA was extracted using Isogenome DNA extraction kits (Nippon Gene Co.Ltd. Tokyo, Japan) following the manufacturer's recommended protocol.’

Authors said that each tick was individually identified morphologically. Ticks were also extracted individually or in pools? Add please.

Response: We revised it accordingly please see L122-123: Genomic DNA was extracted from individual ticks using Isogenome DNA extraction kits (Nippon Gene Co. Ltd. Tokyo, Japan) following the manufacturer's recommended protocol.

8. Table 1: ‘** not 195 enough samples for analysis’

- There is no ** on the table, only * and ***. Maybe it is a typing error?

Response: The authors removed L203: ** not enough samples for analysis. Instead, we retained L204: **tick species identification is based on molecular identification using the cox1 marker and BLAST results

9. Table 2: (indicated by ab). Please correct the ), it is not overwritten.

Response: The authors removed the ), please see L258: cluster dendrogram groups 1 and 2 indicated by ab

10. References

The references need standardization. Each reference is shown in a different format. Please check the author's guidelines for proper standardization. Please be careful in the next submission, all references must be according to guidelines.

Response: Each reference was checked and formatted into PLOS one reference style, Vancouver. We have updated the list of references and its corresponding line in the manuscript.

11. Data availability

Response:

Please see L103-104 Sequences used for analysis are available in the GenBank database under the accession numbers MW063669 to MW064124 and MW065821 to MW066347.

For the unpublished data and additional samples, please see L113-114 The sequences are available in the GenBank database under the accession numbers OR975837 to OR975875 and OR975876 to OR975898.

Reviewer 3’s comments: Changes are highlighted in green in the revised manuscript with the track changes file.

(No Response)

Response: The authors respect the reviewer’s opinion.

2. Is the manuscript technically sound, and do the data support the conclusions?

Partly

Response: The authors are thankful for the comments and suggestions of the Reviewer.

3. Has the statistical analysis been performed appropriately and rigorously?

Yes

Response: We appreciate your response

4. Have the authors made all data underlying the findings in their manuscript fully available?

Response: We have addressed this comment as previously mentioned in Reviewer 2, no. 4. Please see L103-104 Sequences used for analysis are available in the GenBank database under the accession numbers MW063669 to MW064124 and MW065821 to MW066347.

For the unpublished data and additional samples, please see L113-114 The sequences are available in the GenBank database under the accession numbers OR975837 to OR975875 and OR975876 to OR975898.

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Yes

Response: The manuscript has been checked thoroughly for any English grammatical errors by an English proofreading company for scientific manuscripts.

6. Overall, the authors have been receptive to the feedback and have made several changes in the manuscript to address the previous reviewers' concerns. However, the manuscript still echoes significantly with your previously published popgen study. The data and findings still appear to be an extension rather than presenting novel insights specific to Rickettsia. Below are specific suggestions for each section:

Response: Thank you the authors have carefully addressed each of the comments and suggestions of the reviewers and editors.

7. The title

Response: We revised the title as suggested, please see L1-2 Full Title: Genetic structure and Rickettsia infection rates in Ixodes ovatus and Haemaphysalis flava ticks across different altitudes

Abstract

8. L25-26: Change to “The population genetic structure was analyzed utilizing the mitochondrial…”

Response: Please see L26-27 “The population genetic structure was analyzed utilizing the mitochondrial cytochrome oxidase 1 (cox1) marker.”

9. L30-31: Change to “A significant difference was observed in Rickettsia infection rates and mean altitude per group between the two cluster groups and the three genetic groups identified within I. ovatus”

Response: The authors agreed to this suggestion, please see L31-33: A significant difference was observed in Rickettsia infection rates and mean altitude per group between the two cluster groups and the three genetic groups identified within I. ovatus.

10. L33-34: I suggest a more cautious tone when making such conclusions eg. “Our results suggest a potential correlation between the low gene flow in I. ovatus populations and the spatially heterogeneous Rickettsia infection rates observed along the altitudinal gradient”

Response: We revised it accordingly, please see L34-36 “Our results suggest a potential correlation between the low gene flow in I. ovatus populations and the spatially heterogeneous Rickettsia infection rates observed along the altitudinal gradient.”

Introduction

11. L43-44: This sentence seems isolated, elaborate on why the size of ticks influences their dispersal and how host movement plays a role e.g. “Their dispersal is linked to the mobility of their hosts, relying on them to disperse into new landscapes and potentially introduce pathogens”

Response: Kindly see L45-47: Their dispersal is linked to the mobility of their hosts, relying on them to disperse into new landscapes and potentially introduce pathogens [7-8].

12. L83-44: This statement is overgeneralizing by saying “ticks” and “rickettsia”, try to be more specific.

Response: We appreciate this comment thus we revised the sentence into, please see L86-89: “To our knowledge, no previous studies have considered the influence of environmental factors on the spatial distribution of Spotted fever group Rickettsia infection rates along an altitudinal gradient in local Ixodid tick populations such as Ixodes ovatus and Haemaphysalis flava as influenced by the tick population’s genetic structure.”

13. L86-87: Add to this sentence the reasoning why this relationship is important to strengthen the introduction of your objectives. Can be reworded eg. “In this study, we elucidate the relationship between Rickettsia infection rates and population genetic structure along an altitudinal gradient…to improve public health etc.”

Response: Please see L90-92: “In this study, we elucidate the relationship between Rickettsia infection rates as influenced by population genetic structure along an altitudinal gradient to improve public health understanding of the distribution of ticks and tick-borne diseases.

Methodology

14. L121: A table with PCR primers for rickettsia (like in Arai 2021), the target size and references and annealing temps used could be useful. Also try to reference the primary primer source for each rickettsial gene rather than secondary source (authors previously published work)

Response: The authors have agreed to this suggested thus we included a supplementary table to show the PCR primers, target size, annealing temperature and its corresponding references in Supplementary Table 2 (S2 Table).

Please see the revised L131: … and and outer membrane protein B gene (rOmpB) as described and analyzed in [6,37-41] (S2 Table) and L667-668: S2 Table. Summary of PCR primers used in the detection of Spotted fever group Rickettsia

15. L175-178: It might be useful to provide more details about why these specific tests were chosen and if the data meet the assumptions of these tests (e.g. normality, equal variances etc.).

Response: Kindly see L185-190: To determine whether there was a significant difference in the Rickettsia infection rate between haplotype groups for I. ovatus and H. flava, we performed a z-score test at p < 0.05. The z-score test was chosen because of the large sample size and because the population variance was known. To determine whether there were differences in the mean altitude between the haplotype groups, we used the Welch t-test at p < 0.05. Welch t-test was used when the means of the two populations were normally distributed and had equal variances.

16. L130-135: The primer pair sequences for forward and reverse primers seems to be identical, please double check this info. Although you referenced your previous study for the details, include a reference for primer sequences as you’ve stated them with none.

Response: Thank you for this comment, we revised it carefully please check L139-140: LCO-1490 (5′- GGTCAACAAATCATAAAGATATTGG-3') and HCO1–2198 (5′– AAACTTCAGGGTGACCAAAAAATCA- 3) for phylogenetic analysis and tick species identification [42].

17. L167-169: It’s not clear if a model testing tool was used to select the model used for the trees, if a model-testing tool was used but not mentioned, add a few sentences detailing this step as it will help improve stats robustness

Response: Kindly see L174-176: Briefly, we constructed a Bayesian phylogenetic tree of cox1 haplotypes for I. ovatus and H. flava, respectively, using Markov chain Monte Carlo (MCMC) approach implemented in the BEAST version 1.10.14 [43].

18. L170-177: After explaining the method, immediately tie it back to the implications it has for understanding Rickettsia infection rates or distribution.

Response: We have included this in the manuscript, please see L172-175: We constructed a haplotype network analysis using PopART program version 1.7 (http://popart.otago.ac.nz/index.shtml) on cox1 I. ovatus and H. flava sequences to assess the haplotype relationships and the distribution of Rickettsia infected ticks using the median-joining network algorithm [47].

Also L185-187: To determine whether there was a significant difference in the Rickettsia infection rate between haplotype groups for I. ovatus and H. flava, we performed a z-score test at p < 0.05.

Discussion

19. L256-257: use terms like “associated with” instead of “can cause” to ensure that the language reflects the type of relationship (causal or correlational) indicated by your data

Response: We agreed to these suggestions, thus we revised L268-271: Our findings support our hypothesis that a genetically structured tick population, such as I. ovatus is associated with the Rickettsia infection rate to be spatially heterogenous due to limited gene flow along an altitudinal gradient.

20. Line 262-263: same as above point

Response: Kindly see L272-274: Despite the addition of new samples of I. ovatus and H. flava, we found a similar pattern of population genetic structure from the previous study of [11] thus supporting the robustness of their population genetic structure results.

21. L281-287: This is a strong point but could be strengthened. Discuss how your findings specifically align with adaptive evolutionary theory. Consider discussing any alternative explanations for the observed patterns and why local adaptation might be the most plausible explanation.

Response: Please see L293-301: “The different Rickettsia infection rates and altitudinal ranges between the I. ovatus phylogenetic groups may be caused by diverse factors such as host availability and distribution, other environmental factors such as climate and vegetation, and anthropogenic factors such as urbanization. However, the adaptive evolutionary theory, which states that organisms adjust to new or severe changes in their environment to become better suited to their habitat [59-60] best explains our results. Based on the relationship between the I. ovatus phylogenetic groups and their mean attitudes, I. ovatus might be undergoing local adaptation along the altitudinal gradient due to the higher genetic differentiation between populations as supported by the significant global FST (0.4154) found in I. ovatus.”

22. L288-290: Consider removing the emphasis of the previous study's results and instead highlight how these new samples provide additional insight or a different perspective on Rickettsia infection rates.

Response: The authors agreed into this comment, thus please see L301-305: Based on isolation by environment (IBE), genetic differentiation will increase with increased environmental differences independent of geographic distances [33-34;61]. Thus in our study, I.ovatus collected across an altitudinal gradient have shown genetic differences and different Rickettsia infection rates.

23. L303- 306: Consider also discussing how this limitation might specifically impact your findings

Response: We have revised these sentences and incorporated your suggestions, please see L319-324: One of the limitations of this study is the use of one mitochondrial gene cox1 which limited us to compare our results with other target genes to highly support our findings. If markers with high mutation rates or many markers were used, it might have been possible to look at even finer population genetic structure and see differences in infection rates among the subdivided populations. Despite this, we were able to determine the relationship between the tick population genetic structure and Rickettsia infection rates as influenced by the altitudinal gradient. The mitochondrial cox1 gene has been widely used for population genetic analysis of many tick species and was proven to be informative in determining the relationship from the subfamily to the population levels [87-91].

24. L310-327: Are there challenges/considerations that might need to be addressed to apply these findings in a real-world context?

Response: The authors appreciate these suggestions thus we revised it accordingly, please see L328-339: In future studies, we suggest including additional mitochondrial genes and or nuclear genes.

Since ticks are blood-sucking ectoparasites, they directly influence their mammalian hosts and the pathogens they transmit [76-78]. The interaction between the vector (tick), host, and pathogen (Rickettsia) is essential in understanding and predicting the risk and transmission of tick-borne diseases [79]. Understanding the genetic structure of ticks can serve as an alternative indicator to infer the potential spread of its pathogen [80]. Our study found relationships between (1) the population genetic structure of ticks and the corresponding Rickettsia infection rates, (2) altitude and the population genetic structure of ticks, and (3) altitude and Rickettsia infection rates. Though our results can provide useful information about the tick distribution and possible potential spread of pathogens, some factors should also be considered to apply our results in the field setting such as ticks can have different mammalian hosts during different life stages that have varying hosts mobility and other environmental factors such as temperature, humidity etc.. can also be a factor.

25. GenBank Accession numbers: You mentioned uploading the new Cox sequences, what about the Rickettsia sequences as these are the focal point of the study (maybe I missed them while checking?) and are required for validation of your findings

For the unpublished data and additional samples, please see L113-114 The sequences are available in the GenBank database under the accession numbers OR975837 to OR975875 and OR975876 to OR975898.

26. Figures 1-4 : they are blurry and lack clarity, which might hinder the understanding of the data presented. guidelines by Plos one "Ensure that your images have a resolution of at least 300 pixels per inch (ppi) and appear sharp, not pixelated.

Be careful not to inadvertently reduce the resolution when creating a file in graphics editing software "

Response: The authors have edited the figures to obtain a clearer and higher resolution, thank you for these suggestion.

27. I hope the comments and suggestions are helpful with your paper.

Warm regards and happy revising!

Response: The authors are thankful for all the comments and suggestions of the reviewers and editor which greatly improved our manuscript for publication.

28. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Response: The authors respect the decision of the Reviewer to be anonymous.

PLoS One. doi: 10.1371/journal.pone.0298656.r005

Decision Letter 2

Maria Stefania Latrofa

30 Jan 2024

Genetic structure and Rickettsia infection rates in Ixodes ovatus and Haemaphysalis flava ticks across different altitudes

PONE-D-23-12494R2

Dear Dr. Watanabe,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Maria Stefania Latrofa

Academic Editor

PLOS ONE

PLoS One. doi: 10.1371/journal.pone.0298656.r006

Acceptance letter

Maria Stefania Latrofa

3 Mar 2024

PONE-D-23-12494R2

PLOS ONE

Dear Dr. Watanabe,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

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on behalf of

Dr. Maria Stefania Latrofa

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

(XLSX)

pone.0298656.s001.xlsx^{(16KB, xlsx)}

S2 Table. Summary of PCR primers used in the detection of Spotted fever group Rickettsia.

(DOCX)

pone.0298656.s002.docx^{(13.7KB, docx)}

(XLSX)

pone.0298656.s003.xlsx^{(9.9KB, xlsx)}

S1 Fig. Phylogenetic tree from the BEAST analysis of 59 haplotype cox1 sequences of I. ovatus.

(DOCX)

pone.0298656.s004.docx^{(100.8KB, docx)}

S2 Fig. Median-joining network of the 66 cox1 haplotype sequences of Rickettsia positive and negative H. flava.

Haplotype groups are indicated as 1 and 2.

(DOCX)

pone.0298656.s005.docx^{(204.1KB, docx)}

S3 Fig. Phylogenetic tree from the BEAST analysis of 66 haplotype cox1 sequences of H. flava.

(DOCX)

pone.0298656.s006.docx^{(104.4KB, docx)}

Attachment

Submitted filename: PONE-D-23-12494_reviewer.pdf

pone.0298656.s007.pdf^{(2.3MB, pdf)}

Data Availability Statement

Sequences used for analysis are available in the GenBank database under the accession numbers MW063669 to MW064124, MW065821 to MW066347, OR975837 to OR975875 and OR975876 to OR975898.

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PERMALINK

Genetic structure and Rickettsia infection rates in Ixodes ovatus and Haemaphysalis flava ticks across different altitudes

Maria Angenica F Regilme

Megumi Sato

Tsutomu Tamura

Reiko Arai

Marcello Otake Sato

Sumire Ikeda

Kozo Watanabe

Roles

Abstract

Introduction

Materials and method

Published data of [6, 11]

Unpublished data from the 2018 collection

Population genetic analysis

Haplotype network and phylogenetic analyses

Statistical analysis

Results

Table 1. Summary of the haplotype and Rickettsia infection rates among the 7 ixodid tick species obtained in the Niigata Prefecture, Japan.

Fig 1. Median-joining network of the 59 cox1 haplotype sequences of Rickettsia positive and negative I. ovatus.

Fig 2. The influence of altitude on the habitat distribution of I. ovatus.

Table 2. The differences in Rickettsia infection rates and mean altitude in I. ovatus haplotype groups and cluster dendrogram groups.

Fig 3. The relationship between the mean altitude of Rickettsia positive (n = 46) and negative (n = 300) I. ovatus.

Fig 4. An unweighted pair group method with the arithmetic mean (UPGMA) dendrogram of I. ovatus based on the pairwise genetic distance (FST) of cox1 among the 7 populations across Niigata Prefecture, Japan.

Discussion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Maria Stefania Latrofa

Roles

Author response to Decision Letter 0

Decision Letter 1

Maria Stefania Latrofa

Roles

Author response to Decision Letter 1

Decision Letter 2

Maria Stefania Latrofa

Roles

Acceptance letter

Maria Stefania Latrofa

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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Fig 4. An unweighted pair group method with the arithmetic mean (UPGMA) dendrogram of I. ovatus based on the pairwise genetic distance (F_ST) of cox1 among the 7 populations across Niigata Prefecture, Japan.