Back

Single-cell multiomics reveals epigenetic rewiring of splenic memory B cells during murine malaria reinfection

Coronado, M.; Vincelle-Nieto, A.; Azcarate, I. G.; Perez-Benavente, S.; Puyet, A.; Diez, A.; Bautista, J. M.; Reyes-Palomares, A.

2025-12-12 genomics
10.64898/2025.12.10.693423 bioRxiv
Show abstract

Malaria induces slow, gradually acquired, non-sterilizing immunity whose cellular and regulatory underpinnings remain incompletely understood. Here, we combine a sequential Plasmodium yoelii 17XNL infection model in BALB/c mice, in which primary parasitemia resolves spontaneously and confers robust protection upon homologous reinfection, with single-cell RNA and chromatin accessibility profiling to dissect how primary infection and recall reshape splenic immunity, with a focus on B cells. We generate a multiomic atlas of >50,000 splenic mononuclear cells, resolving thirteen major immune lineages and 48 subpopulations, and show that B cells dominate the response and diversify into naive/mature, germinal center, memory, and plasmablast compartments. Trajectory analysis reveals distinct differentiation paths towards germinal center, memory, and mature B cells, and uncovers infection-dependent shifts in transcription factor activity, cis-regulatory element usage, and gene regulatory networks. Reinfection is associated with a shift in memory B-cell composition and transcriptional programs towards extrafollicular-like, IgM- conventional memory B cells together with epigenetic modules linked to rapid antibody production. Together, these data provide a systems-level view of B cell plasticity in experimental malaria and provides a mechanistic framework from a highly protective P. yoelii reinfection model with implications for understanding non-sterilizing immunity in endemic settings.

Matching journals

The top 6 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.