Metagenomic Analysis and Characterization of Tick-Borne Pathogenic Bacteria across Six Counties in Kenya

Abstract

Ticks are arachnids that rely completely on vertebrate blood for their sustenance and survival. This blood-feeding lifestyle has placed them in a niche position to act as vectors for numerous viral, bacterial and protozoan pathogens. Ticks are only second to mosquitoes in the transmission of human diseases, yet tick-borne diseases and bacterial pathogens specifically are understudied in Kenya. This study addressed the knowledge gap in understanding variations in tick microbiomes and bacterial pathogens carried by ticks. This study sought to identify the bacteria in ticks collected from various counties within Kenya. The study also aimed to analyze the diversity of bacteria in ticks through metagenomic analysis and to confirm the identification of ticks through metabarcoding. The study also aimed to characterize the phenotypic, biochemical and antimicrobial susceptibility of the identified pathogens from the ticks and determine the basis of any geo-phylogenetic relationships uncovered. This cross-sectional study collected ticks from various sites, including farms, ranches, slaughterhouses, and livestock markets. The study sites were located across six counties: Baringo, Isiolo, Kilifi, Kisumu, Kwale and Turkana. The collected ticks were pooled, cleaned and homogenized in preparation for 16S rRNA gene metagenomic analysis combined with Cytochrome Oxidase Subunit I gene metabarcoding. The metagenomics results were used to guide the selection, culture and isolation of selected pathogenic bacteria. The metagenomic reads were used to calculate the diversity of tick microbiomes. These involved alpha diversity using Simpson and Shannon indices, Correlation analysis using Spearman rank correlation and Beta diversity using Permutational Analysis of Variance (PERMANOVA). The study conducted phenotypic characterization, antimicrobial susceptibility testing and whole genome sequencing on cultured bacterial isolates. The genomic sequencing data were used to generate insights into phylogenetic relationships. Metagenomic analysis identified a total of 163 bacterial species, with 33 being pathogenic. Analysis revealed that Rickettsia conorii and Coxiella burnetii were the most prevalent pathogens identified. Correlational analysis between 57 bacterial orders identified showed that 2,522 pairs had a significant correlation (p0.050) based on Spearman's rank correlation. Most of the relationships were positively correlated with a mean R2 of 0.228. Beta diversity using Permutational Analysis of Variance on a Bray-Curtis Dissimilarity matrix from the identified reads showed that the County had the highest impact on bacterial species and accounted for 44.1% (p0.001) of the changes between ticks. Coastal and lake regions were seen to have ticks with more diverse microbiomes as compared to arid regions. A total of 30 bacteria were isolated from 88 ticks that were identified to carry potentially pathogenic culturable bacteria. Proteus mirabilis was selected for further characterization based on it being the most prevalent (n=4) and least likely to be a commensal bacterial species in ticks. Non-swarming Proteus mirabilis was isolated from Hyalomma dromedarii ticks in Isiolo. Antimicrobial susceptibility testing revealed that the pathogen was susceptible to major classes of antibiotics, showing that effective treatment can be achieved in the case of infection. Phylogenetic analysis showed that the P. mirabilis isolate was closely related to isolates from clinical cases and domesticated animals, hinting at probable zoonoses. The study provided comprehensive insights into the diversity and distribution of tick-borne bacterial pathogens in various regions of Kenya. Coastal counties were seen to have ticks that had diverse microbiomes and harbor more pathogenic bacteria as compared to arid counties. The Proteus mirabilis identified in ticks was seen to be related to human and veterinary isolates but was susceptible to common antibiotics. This study is unique in that it uses long-read sequencing in its approach to identifying pathogenic bacteria in ticks. The findings of this study emphasise on the need for adequate education and tick control measures to reduce the impact of ticks and their associated pathogens on human health.