Hard ticks of the order Ixodidae serve as vectors for numerous human pathogens, including the causative agent of Lyme Disease Borrelia burgdorferi. Tick-associated microbes can influence pathogen colonization, offering the potential to inhibit disease transmission through engineering of the tick microbiota. Here, we investigate whether B. burgdorferi encounters abundant bacteria within the midgut of wild adult Ixodes scapularis, its primary vector. Through the use of controlled sequencing methods and confocal microscopy, we find that the majority of field-collected adult I. scapularis harbor limited internal microbial communities that are dominated by endosymbionts. A minority of I. scapularis ticks harbor abundant midgut bacteria and lack B. burgdorferi. We find that the lack of a stable resident midgut microbiota is not restricted to I. scapularis since extension of our studies to I. pacificus, Amblyomma maculatum, and Dermacentor spp showed similar patterns. Finally, bioinformatic examination of the B. burgdorferi genome revealed the absence of genes encoding known interbacterial interaction pathways, a feature unique to the Borrelia genus within the phylum Spirochaetes. Our results suggest that reduced selective pressure from limited microbial populations within ticks may have facilitated the evolutionary loss of genes encoding interbacterial competition pathways from Borrelia.
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http://dx.doi.org/10.1038/s41396-018-0161-6 | DOI Listing |
Viruses
January 2025
Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna (IZSLER), 25124 Brescia, Italy.
The European subtype of tick-borne encephalitis virus (TBEV-Eur; species , family ) was the only tick-borne flavivirus present in central Europe known to cause neurologic disease in humans and several animal species. Here, we report a tick-borne flavivirus isolated from Alpine chamois () with encephalitis and attached ticks, present over a wide area in the Alps. Cases were detected in 2017 in Salzburg, Austria, and 2023 in Lombardy and Piedmont, Italy.
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January 2025
Department of Health Biohazards and Parasitology, Institute of Rural Health, Jaczewskiego 2, 20-090 Lublin, Poland.
is an important vector of infectious human and livestock diseases in Europe. Co-infections of pathogens in ticks and hosts have been reported. Tick cell lines offer a useful model system for study of co-infections.
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December 2024
Diagnostic Department and Public Health Laboratories, Hellenic Pasteur Institute, 11521 Athens, Greece.
Ticks are temporary ectoparasites that serve as vectors for a wide range of pathogens affecting both wildlife and humans. In Greece, research on the prevalence of tick-borne pathogens in wildlife is limited. This study investigates the presence of pathogens, including spp.
View Article and Find Full Text PDFVet Parasitol Reg Stud Reports
January 2025
Government Boys Degree College, Ziarat, Balochistan, University of Balochistan, Pakistan.
Ticks, being ectoparasites, are vectors for the transmission of various pathogens that can infect animals and can also pose a significant threat to human health. Due to hot and humid climatic conditions across different agro-ecological regions of Pakistan, ticks are widespread and infest a diverse range of animal species. This study aimed for taxonomic identification and prevalence determination of ticks in sheep collected from four different marketplaces in the Quetta district of Balochistan.
View Article and Find Full Text PDFTicks Tick Borne Dis
January 2025
Department of Health, Sport and Bioscience. University of East London, Water Lane, Stratford E15 4LZ, United Kingdom. Electronic address:
The interplay of biotic and abiotic factors driving Ixodes ricinus abundance trends are not fully understood. Machine learning (ML) approaches are being increasingly used to explore this and predict future abundance patterns of this species, however, the studies focusing on this to date have had limitations (including short study duration, limited sample size, narrow geographical range and use of a single ML model). This study was undertaken to address these limitations by applying 11 predictive ML models (across three data clustering techniques) to a large I.
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