Back

Morphological and molecular characterisation of Orientia tsutsugamushi grown in tick cells

Rogowska-van der Molen, M.; Gallo, F.; Bell-Sakyi, L.; Salje, J.

2025-12-15 microbiology
10.64898/2025.12.15.694307 bioRxiv
Show abstract

Orientia tsutsugamushi (Ot), the causative agent of scrub typhus, is an obligate intracellular bacterium naturally maintained in Leptotrombidium mites, yet its interactions within arthropod hosts remain poorly understood. Here, we developed two tick cell lines, Ixodes scapularis ISE6 and Rhipicephalus microplus BME/CTVM23, as arthropod models to investigate the intracellular lifecycle of Ot strains TA686 and Karp. Both strains efficiently infected and replicated within tick cells, with ISE6 supporting more robust growth. Electron microscopy images revealed that Ot maintains its characteristic cytoplasmic, non-vacuolar location in tick cells and exits infected cells by budding off the surface in a membrane-encased structure. Time-course immunofluorescence imaging demonstrated progressive intracellular replication and dynamic expression of Ot outer membrane autotransporters ScaA and ScaC, with ScaC enriched early in infection and ScaA at later stages. Metabolic labelling using a clickable methionine analog L-homopropargylglycine showed that high ScaA abundance correlated with reduced translational activity, suggesting a link between ScaA abundance and late-stage or extracellular-like developmental states. The subcellular location of Ot in tick cells differs from the characteristic dynein-driven perinuclear clustering observed in mammalian cells, and was not sensitive to disruption of microtubules, indicating a distinct mode of distribution. Together, these findings identify tick cell lines as tractable and biologically relevant arthropod models for studying Ot and dissecting host-microbe interactions.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.