Back

Single-cell analysis of Plasmodium falciparum transcripts after drug perturbation identifies feedback regulation as well as increased transmission potential

Godinez-Macias, K. P.; Calla, J.; Jepsen, K.; Winzeler, E. A.

2026-05-29 microbiology
10.64898/2026.05.27.728291 bioRxiv
Show 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.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Malaria Journal
48 papers in training set
Top 0.1%
40.0%
2
PLOS Computational Biology
1633 papers in training set
Top 5%
6.9%
3
PLOS Pathogens
721 papers in training set
Top 2%
6.9%
50% of probability mass above
4
Scientific Reports
3102 papers in training set
Top 16%
6.5%
5
eLife
5422 papers in training set
Top 13%
6.4%
6
mBio
750 papers in training set
Top 4%
3.6%
7
BMC Genomics
328 papers in training set
Top 1%
2.4%
8
Frontiers in Cellular and Infection Microbiology
98 papers in training set
Top 2%
1.9%
9
Nature Communications
4913 papers in training set
Top 49%
1.9%
10
mSphere
281 papers in training set
Top 3%
1.7%
11
PLOS Biology
408 papers in training set
Top 11%
1.5%
12
PLOS Neglected Tropical Diseases
378 papers in training set
Top 3%
1.5%
13
PLOS ONE
4510 papers in training set
Top 57%
1.4%
14
Antimicrobial Agents and Chemotherapy
167 papers in training set
Top 1%
1.2%
15
iScience
1063 papers in training set
Top 23%
1.1%
16
The Journal of Infectious Diseases
182 papers in training set
Top 4%
0.8%
17
Microbiology Spectrum
435 papers in training set
Top 5%
0.8%
18
Nucleic Acids Research
1128 papers in training set
Top 18%
0.7%
19
International Journal for Parasitology
21 papers in training set
Top 0.4%
0.7%
20
The American Journal of Tropical Medicine and Hygiene
60 papers in training set
Top 4%
0.7%
21
Peer Community Journal
254 papers in training set
Top 5%
0.5%
22
Science Advances
1098 papers in training set
Top 35%
0.5%
23
FEBS Letters
42 papers in training set
Top 0.6%
0.5%
24
Bioinformatics Advances
184 papers in training set
Top 6%
0.5%
25
Molecular Ecology Resources
161 papers in training set
Top 1%
0.5%