Microbial communities associated with the camel tick, Hyalomma dromedarii: 16S rRNA gene-based analysis

Hyalomma dromedarii is an important blood-feeding ectoparasite that affects the health of camels. We assessed the profile of bacterial communities associated with H. dromedarii collected from camels in the eastern part of the UAE in 2010 and 2019. A total of 100 partially engorged female ticks were taken from tick samples collected from camels (n = 100; 50/year) and subjected to DNA extraction and sequencing. The 16S rRNA gene was amplified from genomic DNA and sequenced using Illumina MiSeq platform to elucidate the bacterial communities. Principle Coordinates Analysis (PCoA) was conducted to determine patterns of diversity in bacterial communities. In 2010 and 2019, we obtained 899,574 and 781,452 read counts and these formed 371 and 191 operational taxonomic units (OTUs, clustered at 97% similarity), respectively. In both years, twenty-five bacterial families with high relative abundance were detected and the following were the most common: Moraxellaceae, Enterobacteriaceae, Staphylococcaceae, Bacillaceae, Corynebacteriaceae, Flavobacteriaceae, Francisellaceae, Muribaculaceae, Neisseriaceae, and Pseudomonadaceae. Francisellaceae and Enterobacteriaceae coexist in H. dromedarii and we suggest that they thrive under similar conditions and microbial interactions inside the host. Comparisons of diversity indicated that microbial communities differed in terms of richness and evenness between 2010 and 2019, with higher richness but lower evenness in communities in 2010. Principle coordinates analyses showed clear clusters separating microbial communities in 2010 and 2019. The differences in communities suggested that the repertoire of microbial communities have shifted. In particular, the significant increase in dominance of Francisella and the presence of bacterial families containing pathogenic genera shows that H. dromedarii poses a serious health risk to camels and people who interact with them. Thus, it may be wise to introduce active surveillance of key genera that constitute a health hazard in the livestock industry to protect livestock and people.

Pathogens and the diseases they cause are of high importance to human and animal health 1,2 . Microbial and parasitic infections are ubiquitous in animal and human populations, and healthy ecosystems are often rich in pathogenic organisms 2,3 . In recent years, long-term host-pathogen associations have been disrupted primarily due to extensive anthropogenic changes in the environment resulting in emerging and re-emerging infectious diseases 1,2 . Density of hosts, vectors and pathogens in a geographic area are key determinants of disease transmission 4 . Globally, arthropods, such as ticks act as vectors of many human and animal pathogens (including viruses, bacteria and protozoa), often mediating transfer of infections from one host species to another [5][6][7][8][9] . Farming of animals throughout the world has resulted in artificially enhanced domestic animal populations. This in turn has increased tick abundance and distribution, particularly in peri-urban livestock industries.
Ticks feed exclusively on the blood of their vertebrate hosts 10 and simultaneously harbor a variety of endosymbiotic and pathogenic microbes 11,12 . The assortment of bacteria harbored and transmitted by ticks is diverse, representing a wide range of genera including Anaplasma, Borrelia, Coxiella, Cowdria, Ehrlichia, Francisella, and Rickettsia. These bacteria are adapted to undergo development in the tick vector for at least a portion of their lifecycle 11,13 . In terms of Francisella, it is known that it may exist either as pathogenic species or as intracellar endosymbionts (Francisella-like endosymbiont). Though humans are considered accidental hosts of ticks, the bacterial diseases such as rickettsial diseases transmitted by various arthropod vectors affect an estimated one OPEN Biology Department, United Arab Emirates University, P.O. Box 15551, Al-Ain, UAE. * email: m_aldeeb@uaeu.ac.ae
The relative abundance of genera was highly variable in the microbiome of H. dromedarii in all locations. Acinetobacter (75.66%) and Corynebacterium (36.62%) were the two most common genera with high relative abundance. Proteus had a relative abundance of 55.82% followed by Escherichia (53.13%) and Staphylococcus (37.68%). Flavobacterium, Francisella, Moraxella, Uruburuella and Stenotrophomonas occurred in moderately low relative abundance (6-25%). In addition, genera including Enterobacter, Comamonas, Brevibacterium, Helcococcus, Facklamia, Anaerococcus, Ignavigranum and Muribaculum were all low in terms of relative abundance (1-3.55%) ( Fig. 2A Table 8). The Escherichia showed a relative abundance of 48.41% followed by Bacillus, which had a relative abundance of 45.84% while Siccibacter had highest relative abundance of 30.81%. Corynebacterium was recorded in all locations; however, the Clostridium and Flavobacterium were recorded in samples from only two locations. Though, Staphylococcus was recorded in all locations it was in a low relative abundance (Fig. 2B). Principle Coordinates Analysis showed that Coordinates 1, 2 and 3 accounted for over 84% of the variation (based on cumulative Eigenvalues) and the first two coordinates accounted for over 78% of the variation. Furthermore, there was a clear separation among the microbial communities between years with the exception of one site (Malaket, MQ) ( Associations between bacterial genera. Pearson's correlation coefficients (r) indicated that many bacterial genera were significantly correlated with each other ( Fig. 4; Supplementary Table 9). Francisella was significantly negatively correlated with Acinetobacter, Corynebacterium and Escherichia. Bacillus was significantly positively correlated with Lysinibacillus. Staphyllococcus and was positively correlated with Corynebacterium. Escherichia was significantly positively correlated with Pseudomonas and Moraxella was correlated with Uruburuella. Acinetobacter, Fransicella and Escherichia were significant predictors of many bacterial genera (Table 1). Acinetobacter counts were significantly predicted by Corynebacterium, Escherichia, Francisella, Lysinibacillus, Moraxella, Pseudomonas and Psychrobacter. Similarly, Escherichia counts were significantly predicted by Acinetobacter, Corynebacterium, Francisella, Lysinibacillus, Moraxella, Pseudomonas and Psychrobacter. On the hand, Francisella counts were significantly predicted by Acinetobacter and Escherichia.

Discussion
Camel ticks can carry and transmit potential pathogens 6,[49][50][51][52][53] . Microbial diversity in ticks plays a significant role in pathogen transmission, vector competence 54,55 , and tick reproductive fitness 56 . Tick-borne pathogens can significantly decrease the production of camel milk and meat and may affect the racing breeds. We found a diverse array of pathogens in H. dromedarii ticks, highlighting the reservoir potential of this tick species for significant pathogens.
The patterns of bacterial phyla in the current study were consistent with findings of Elbir et al. 48 where the Proteobacteria was the most abundant followed by Firmicutes and Actinobacteria. In addition, they were consistent with the results of Thapa et al. 43 , who also found Proteobacteria with the highest relative abundance across Table 1. Significant multiple regression models that were retained after backward selection.  40 , where the taxonomical composition of tick samples indicated that the abundant bacterial class was Gammaproteobacteria along with Alphaproteobacteria, Actinobacteria, Bacilli and Deltaproteobacteria, which represented 80% to 99% of the population in each of the samples. However, Karim et al. 41 documented predominantly only six classes namely Bacilli, Gammaproteobacteria, Betaproteobacteria, Clostridia, Alphaproteobacteria and Actinobacteria, after profiling of the bacteria sampled from tick species collected from various livestock. In another study, the bacterial DNA sequences of Alphaproteobacteria and Gammaproteobacteria types were abundant in Ixodes persulcatus, Ixodes pavlovskyi, and Dermacentor reticulatus samples with 30.2% and 60.8% average occurrence, respectively 59 . Generally, these studies in addition to the current study show that the above-mentioned common bacterial classes have a wide geographical distribution occurring in ticks from the UAE, Malaysia, Pakistan and Russia.
Patterns of abundance of bacterial families in this study differed from the findings of Karim et al. 41 who found Oxalobacteraceae, Staphylococcaceae, Clostridiaceae, Enterobacteriaceae, Coxiellaceae, Rickettsiaceae, Streptococcaceae, and Lactobacillaceae as the predominant microbial families in tick samples that were not H. dromedarii. Some of this variation can be explained in light of quantitative and qualitative differences in microbial communities between hosts 41,67 . Enterobacteriaceae was the most abundant bacterial family in R. microplus ticks collected from cattle whereas Rickettsiaceae, Oxalobacteraceae, and Micrococcaceae were abundant in the R. turanicus ticks infesting goats 41 . Furthermore, the results of this study differ from Ravi et al. 60 who reported four   58 reported that Francisellaceae and Enterobacteriaceae were the prevalent bacterial families in Amblyomma maculatum ticks. Based on these findings, Francisellaceae and Enterobacteriaceae coexist in H. dromedarii and A. maculatum suggesting that they thrive under similar conditions and microbial interactions inside the host. In general, the composition of microbial families can be affected by external and stochastic factors, which contribute to producing high or low diversity inside each individual tick. Although in this study, we pointed out the diversity in microbial families within H. dromedarii, however we did not identify the environmental and host-related factors, which might shape this complex microbial ecosystem. We assume that certain interactions among microorganisms inside H. dromedarii result in the dominance of some families over the others. The use of 16S rRNA gene for identification of a broad range of clinically relevant bacterial pathogens is a good tool to assess microbial communities. However, short-read sequencing platforms which target different regions of 16S rRNA do not provide good taxonomic resolution when compared to sequencing the entire gene 61 . This implies that 16S rRNA gene-based identification is reliable up to the genus level. In addition, getting full-length or near full-length 16S sequences are crucial for making confident genus level taxonomic placements. Therefore, the genus level identifications presented in the current study are provided as preliminary baseline data, which may require further confirmation. Our results indicated that Acinetobacter and Corynebacterium were the two most abundant genera detected in the microbiota of H. dromedarii from all locations with high sequence ratios  We found significant associations between Acinetobacter, Escherichia and Francisella and between these three genera and several other genera. Little is known about Francisella and their associations with ticks. It appears that many diverse bacterial genera co-exist with tick-borne pathogens 62 and endosymbiotic forms could increase colonization potential of pathogenic forms 63 . Francisella appears to occur in many ticks species, most commonly in mutualistic forms 62 . However, phylogenetic similarities between mutualistic and pathogenic Francisella suggest periodic and perhaps even frequent shifts from non-pathogenic forms 62,64 . Nonetheless, the co-occurrence of non-pathogenic and pathogenic bacteria may not always result in genetic transformations 65 , suggesting that multiple factors could influence pathogenicity in tick microbiota. Moreover, the constant occurrence of the Francisella indicates a systemic association between arthropods and this bacterial genus. Our finding of negative associations between Francisella, Acinetobacter and Escherichia could indicate possible suppressive effects of the former on the latter two genera. On the other hand, positive association between Acinetobacter and a broad range of bacterial genera also deserves further consideration. Many species of Acinetobacter are known to be pathogenic, while others are considered commensal and even part of the normal flora of animals 66 .
It is important to recognize that Francisella was reported in 2010 and 2019 and was found with the highest abundance (99%) in 2019. This finding is consistent with the overall change in bacterial communities experienced in 2019, with the general rise in Francisella. If future studies confirm the presence of pathogenic genus, Francisella in the UAE, this could be a potential emerging disease pathogen in the country and may affect the people who are closely working with the camels such as workers at farms and slaughter houses, veterinary hospitals and research centers. Again, we emphasize that the above-mentioned bacterial genera and species need further confirmation.
In conclusion, the present study advances our knowledge about the microbial communities in H. dromedarii ticks. It provides clear evidence that the microbiota of H. dromedarii is rich and diverse with a potential of harboring pathogenic bacteria, which pose a serious health risk to camels and people. Overall, the 16S rRNA gene-based sequencing, presented in the current study, gives excellent phylum, class, and family identifications and sheds light on the microbial diversity in H. dromedarii in general. Additionally, it gives baseline genus identification considering some of the limitations of 16S rRNA gene-based sequencing and consequently these findings should serve as foundation for future studies. Existing evidence warrants further investigation of the microbial ecology of the H. dromedarii and calls for deeper understanding of how some species of its microbiota become dominant over time especially the pathogenic ones. Our results set the stage for further screening and www.nature.com/scientificreports/ detection (through active surveillance) of pathogenic genera and species that pose serious health risks to camels and people. Moreover, more research is required to investigate the functional and the ecological implications of the bacterial communities associated with H. dromedarii.

Methods
Tick collection. In a cross-sectional study, we collected ticks manually from camels in 2010 and 2019. In 2010, we completed a project in which we collected large number of H. dromedarii ticks and stored them in − 80 °C. In 2019, we started a new project on this tick species and we were keen to collect ticks from the same locations sampled in 2010 so that we could make a comparison of microbial communities between the samples collected in both projects and detect changes over time. Farms and camels were selected randomly. In 2010, we collected ticks from 10 locations (Al-Wagan, Al-Yahar, Bede' Fares, Bede'Bent Suod, Dubai Road, Dwar Al-Shahenat, Malaket, Omghafa, Remah, and Swehan) in Al-Ain area at the eastern part of the UAE. In each location, we selected five camels, and from each camel we collected 10 ticks. In the laboratory, one partially engorged female tick was picked out of the 10 ticks collected per animal to be subjected to DNA extraction and sequencing. The same strategy of tick sampling was followed in 2019. As a result, we gathered 1000 ticks in total in 2010 and 2019 and from them we used 100 partially engorged female ticks at the rate of 50 ticks each year. Ticks were kept in plastic vials (50 ml) in − 80 °C freezer until DNA extraction. Tick collection was carried out in strict accordance with the recommendations of the Animal Research Ethics Committee (A-REC) of the UAE University (ethical approval# ERA_2019_5953). In addition, the experimental protocol was approved by the UAE University Research Office. www.nature.com/scientificreports/ Tick identification, genomic DNA extraction and pooling. The identification of ticks as H. dromedarii was done morphologically using the keys of Apanaskevich et al. 67 and Walker et al. 68 and based on DNA sequencing using cytochrome oxidase subunit I (COI) gene 49 . Briefly, in the males the sub-anal plates are aligned outside the adanal plates. In addition, the adanal plates have a characteristic shape with both long margins strongly curved in parallel. In the females, the genital aperture has posterior lips with a narrow V, which is also found in Hyalomma impeltatum, but the posterior margin of their scutum is distinctly sinuous compared to a slightly sinuous margin in H. dromedarii. With molecular identification, a segment of the COI gene was amplified in polymerase chain reaction using a primer pair Fish1F: 5′-TCA ACC AAC CAC AAA GAC ATT GGC AC-3′ Quantification and statistical analyses. We conducted Principle Coordinates Analysis (PCoA) to determine patterns of diversity in bacterial communities. The PCoA were conducted and visualized using the software PAST 5.27 Paleontological statistics software package 75 (Øyvind Hammer, Natural History Museum, University of Oslo, Norway, ohammer@nhm.uio.no ). OTU count of each genus was entered and the samples were categorized by year (2010 and 2019). Eigenvalues were examined to determine the extent of variation explained by the first three principle coordinates (Coordinates 1-3) 76 . We calculated different indices of diversity since a single index often does not reflect the true nature of diversity and a combination provides an approximation of diversity. We estimated Richness (total number of genera, based on OTUs obtained for each genus); Shannon Wiener Index; and the Index of Dominance. The Shannon Wiener Index of diversity was calculated using the following formula: where S-the total number of genera, i-the number of OTUs for genus i; and pi-relative proportion of genus i. Index of Evenness (relative abundance of each genus, based on OTUs) was calculated as follows: where H-Shannon-Weiner's Index and S is the total number genera. The Index of Dominance (D) was calculated using the following formula: We compared all these indices between years using paired two sample t-test using PAST 75 . Pearson's Correlation Coefficient (r) was calculated to determine associations between different genera that occurred in 2010 and 2019 77 . Genera with significant correlations were subjected to stepwise regression analysis, with backward selection 77 . One genus was used as the response variable and all other genera that had significant correlations with response variable were used as explanatory variables. Genera were removed individually based on significance to see the effect on the overall model. Only those genera that improved the overall model were retained, while genera did not affect the model were removed. The process was repeated with each genus that had a significant correlation with other genera. For all tests, the value of α was set at 0.05. www.nature.com/scientificreports/