Deep sequencing of 16 Ixodes ricinus ticks unveils insights into their interactions with endosymbionts
Language English Country United States Media print-electronic
Document type Journal Article
Grant support
184.035.007
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Ministerie van Volksgezondheid, Welzijn en Sport
PubMed
40521888
PubMed Central
PMC12282096
DOI
10.1128/msystems.00507-25
Knihovny.cz E-resources
- Keywords
- Ixodes ricinus, Midichloria mitochondrii, Rickettsia helvetica, cophylogenetic analysis, deep sequencing, genome reconstruction, genome-scale metabolic modeling, paternal transmission, symbionts,
- MeSH
- Phylogeny MeSH
- Genome, Bacterial MeSH
- Genome, Mitochondrial MeSH
- Ixodes * microbiology genetics MeSH
- Rickettsia * genetics physiology MeSH
- Symbiosis * genetics MeSH
- High-Throughput Nucleotide Sequencing methods MeSH
- Animals MeSH
- Check Tag
- Female MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
Ixodes ricinus ticks act as vectors for numerous pathogens that present substantial health threats. Additionally, they harbor vertically transmitted symbionts, some of which have been linked to diseases. The difficulty of isolating and cultivating these symbionts has hampered our understanding of their biological role, their potential to cause disease, and their modes of transmission. To expand our understanding of the tick symbiont Midichloria mitochondrii and Rickettsia helvetica, which has been linked to disease in humans, we utilized deep sequencing on 16 individual adult female ticks collected from coastal dune and forested areas in the Netherlands. By employing a combination of second- and third-generation sequencing techniques, we successfully reconstructed the complete genomes of M. mitochondrii from 11 individuals, R. helvetica from eight individuals, and the mitochondrial genome from all ticks. Additionally, we visualized the location of R. helvetica in tick organs and constructed genome-scale metabolic models (GEMs) of both symbionts to study their environmental dependencies. Our analysis revealed a strong cophylogeny between M. mitochondrii and mitochondrial genomes, suggesting frequent maternal transmission. In contrast, the absence of cophylogeny between R. helvetica and the mitochondrial genomes, coupled with its presence in the receptaculum seminis of I. ricinus females, raises the possibility of paternal transmission of R. helvetica. Notably, the genetic diversity of R. helvetica was found to be very low, except for the rickA virulence gene, where the presence of up to 13 insertions of a 33 nt-long repeat led to significant variability. However, this variation could not account for the differences in infection prevalence observed across eight distinct locations in the Netherlands. By employing deep sequencing, it becomes feasible to extract complete genomes and genetic data of symbionts directly from their host organisms. This methodology serves as a robust means to gain fresh insights into their interactions. Our observations, which suggest paternal transmission of R. helvetica, a relatively unexplored mode of transmission in ticks, require validation through experimental investigations. The genetic variations identified in the rickA virulence gene of R. helvetica have the potential to influence the infectivity and transmission dynamics of R. helvetica.IMPORTANCETicks are vectors of numerous human pathogens; however, the microbial interactions within ticks and the mechanisms governing pathogen transmission remain poorly understood. This study uses deep sequencing of individual Ixodes ricinus to reconstruct high-quality genomes of endosymbionts and the mitochondrion of the tick, revealing previously undetected microbial dynamics. Notably, we recovered low-abundance Rickettsia and Midichloria genomes from single ticks and present evidence that suggests paternal transmission of R. helvetica. These findings offer novel insights into the ecology and evolution of tick-associated microbes and have implications for understanding the origins and spread of tick-borne diseases.
Bundeswehr Institute of Microbiology Munich Bavaria Germany
Centre for Infectious Diseases Bilthoven Utrecht the Netherlands
Future Genomics Technologies BV Leiden the Netherlands
NVWA Centrum Monitoring Vectoren Wageningen the Netherlands
UNLOCK Wageningen University and Research Wageningen Gelderland the Netherlands
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