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bioRxiv · 10.1101/2022.02.11.480160

Comparative single-cell transcriptional atlases of Babesia species reveal conserved and species-specific expression profiles

Rezvani, Y.·Keroack, C. D.·Elsworth, B.·Arriojas, A.·Gubbels, M.-J.·Duraisingh, M.·Zarringhalam, K.
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Abstract

Babesia is a genus of Apicomplexan parasites that infect red blood cells in vertebrate hosts. Pathology occurs during rapid replication cycles in the asexual blood-stage of infection. Current knowledge of Babesia replication cycle progression and regulation is limited and relies mostly on comparative studies with related parasites. Due to limitations in synchronizing Babesia parasites, fine-scale time-course transcriptomic resources are not readily available. Single-cell transcriptomics provides a powerful unbiased alternative for profiling asynchronous cell populations. Here, we applied single-cell RNA sequencing to three Babesia species (B. divergens, B. bovis, and B. bigemina). We used analytical approaches and algorithms to map the replication cycle and construct pseudo-synchronized time-course gene expression profiles. We identify clusters of co-expressed genes showing just-in-time expression profiles, with gradually cascading peaks throughout asexual development. Moreover, clustering analysis of reconstructed gene curves reveals coordinated timing of peak expression in epigenetic markers and transcription factors. Using a regularized Gaussian Graphical Model, we reconstructed co-expression networks and identified conserved and species-specific nodes. Motif analysis of a co-expression interactome of AP2 transcription factors identified specific motifs previously reported to play a role in DNA replication in Plasmodium species. Finally, we present an interactive web-application to visualize and interactively explore the datasets.

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Rezvani, Y., Keroack, C. D., Elsworth, B., Arriojas, A., Gubbels, M.-J., Duraisingh, M., Zarringhalam, K.. 2022-02-14. Comparative single-cell transcriptional atlases of Babesia species reveal conserved and species-specific expression profiles. https://doi.org/10.1101/2022.02.11.480160

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