bioRxivMicrobiologyPreprint
Single-cell transcriptomics resolves the developmental transitions from schizont to invasive extracellular merozoite to ring-stage Plasmodium falciparum parasites
Sebastiaan M. BoliD, Jake A Moore, Siddharth NeogiD, Vinit UpasaniiD, Ian Cheeseman, Evelien M. BunnikiD
Abstract
The progression from mature schizonts to newly formed ring-stage parasites represents one of the largest developmental transitions in the Plasmodium falciparum intraerythrocytic developmental cycle (IDC), encompassing parasite egress, erythrocyte invasion, and productive infection of the new host cell. While the transcriptional programs required for egress and invasion are well-documented, less is known about how the parasite prepares for intracellular survival inside the newly invaded erythrocyte. Here, we used single-cell RNA sequencing based on PIPseq chemistry to construct a transcriptional atlas spanning late schizogony, extracellular merozoites, and early ring-stage development. We show that schizogony is characterized by sequential waves of invasion gene expression that closely parallel secretory organelle biogenesis and are associated with cooperative regulation by ApiAP2 transcription factors. Immediately prior to egress, parasites shift from expression of invasion genes to genes required for establishing the intracellular host-parasite interface, including the parasitophorous vacuole and digestive vacuole. Extracellular merozoites separate into transcriptionally distinct invasive and non-invasive populations. Together, these findings provide high temporal resolution of late schizont development, reveal priming for intracellular survival prior to egress, and highlight the short lifespan of invasive merozoites and the resulting challenges of studying this elusive stage of the IDC.
- organism: plant (other)
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: trajectory inference
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
- approach: statistical model
- Citations
- 0
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