bioRxivMicrobiologyPreprint
Single-cell analysis of Plasmodium falciparum transcripts after drug perturbation identifies feedback regulation as well as increased transmission potential
Karla P. Godinez‐MaciasiD, Jaeson CallaiD, Kristen JepseniD, Elizabeth A. WinzeleriD
Abstract
Gene expression analysis in malaria parasites has been used to define transcriptional regulatory networks but has been used less frequently to characterize parasite response to drug treatment or to show how parasites may evade killing. Here, we applied single-cell RNA sequencing (scRNA-seq) to hundreds of thousands of individually infected asynchronous red blood cells to evaluate the parasites response to treatment with three chemotypes that can be used for treatment (artemisinin) or prophylaxis and treatment (atovaquone, ganaplacide). We found that each treatment gave rise to different cell populations with different transcriptional profiles. Comparing single cell transcription patterns in compound-treated cells, to transcript patterns observed previously with synchronized cells showed an enrichment of cells expressing gametocyte-associated genes after artemisinin treatment but fewer lifecycle perturbations after treatment with the two other compounds. In contrast, bulk analysis showed an enrichment of pyrimidine biosynthesis transcripts for atovaquone treatment. Our results show that scRNA-seq may be used to profile diverse drug responses across many lifecycle stages and to potentially classify drug classes. ImportanceDetermining the mechanism of action (MOA) of compounds with antimalarial activity remains a key activity in both drug development and drug resistance studies but remains challenging for some chemotypes. Here we highlight the potential of single cell transcriptional sequencing to augment the process of MOA deconvolution. We develop a new analytical pipeline that involves comparing single cell transcription patterns to existing profiles from synchronized parasites to comprehensively characterize life cycle stage enrichments that may be observed after chemical perturbations. We also show that transcriptional feedback regulation may be present for some drug classes.
- organism: plant (other)
- assay: scRNA-seq
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
- Citations
- 1
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Single-cell transcriptional changes of artemisinin-sensitive K13C580 and artemisinin-resistant K13580Y Plasmodium falciparum upon dihydroartemisinin exposure
S. V. Connelly, C. Cunningham, … C. I. Oduor·bioRxiv·Dec 6, 2023
- Machine learning approaches for classificationof Plasmodium falciparum life cycle stagesusing single-cell transcriptomes
Swarnim Shukla, Soham Choudhuri, … Bhaswar Ghosh·bioRxiv·Jun 22, 2022
- Single-cell transcriptomics of malaria parasites
Adam James Reid, Arthur M. Talman, … Mara Lawniczak·eLifePeer-reviewed·Mar 26, 2018
- Computational approach for decoding Malaria Drug Targets from Single-Cell Transcriptomics and finding potential drug molecule
Soham Choudhuri, Bhaswar Ghosh·Scientific ReportsPeer-reviewed·Oct 14, 2024
- Dihydroartemisinin induces a two-step transcriptional response and stage-specific developmental shifts in malaria parasites, Plasmodium falciparum
Josephine Boentoro, Michal Kucharski, … Zbynek Bozdech·bioRxiv·Jun 18, 2026
- A single-cell atlas of Plasmodium falciparum transmission through the mosquito
Eliana Real, Virginia M. Howick, … Mara Lawniczak·Nature CommunicationsPeer-reviewed·May 27, 2021