Integrated Plasmodium falciparum Transcriptomics Reveals Coordinated Stress Adaptation and Metabolic Remodeling in Severe Malarial Anemia
Abstract
Malaria remains a leading cause of childhood morbidity and mortality in sub-Saharan Africa, with severe malarial anemia (SMA; hemoglobin (Hb) < 6.0 g/dL) representing one of the life-threatening complications of Plasmodium falciparum infection. While limited studies have examined host transcriptional responses in SMA, parasite transcriptional adaptations remain unexplored. Here, we performed parasite transcriptomic profiling in the same cohort of Kenyan children under five years of age in whom we previously characterized host transcriptional responses to SMA, including children presenting with SMA (n = 20) or non-SMA malaria (n = 40). Differential expression analysis identified 566 P. falciparum genes associated with SMA, predominantly involving up-regulated transcripts linked to proteostasis, translational regulation, stress-response pathways, and metabolic remodeling. Transcriptomic deconvolution indicated greater trophozoite and schizont representation in SMA, with reduced ring-stage and gametocyte signatures. Weighted gene co-expression network analysis and protein-protein interaction network analysis identified coordinated transcriptional programs enriched for proteasomal degradation, ubiquitin-mediated protein turnover, chaperone activity, RNA processing, and metabolic adaptation. XGBoost-SHAP modeling identified a small subset of parasite genes that captured much of the transcriptomic signal, classifying SMA from non-SMA malaria. Collectively, these findings define a distinct parasite transcriptional landscape in SMA characterized by coordinated stress adaptation and metabolic flexibility, highlighting proteostasis-associated pathways for further therapeutic investigation.
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BibTeX
@misc{perkins2026integrated,
title = {{Integrated Plasmodium falciparum Transcriptomics Reveals Coordinated Stress Adaptation and Metabolic Remodeling in Severe Malarial Anemia}},
author = {Douglas Perkins and Clinton Onyango and Shamim Osata and Sharley Wasena and Ivy Hurwitz and Philip Seidenberg and Collins Ouma and Samuel Anyona and Kristan Schneider and Benjamin McMahon and Qiuying Cheng},
howpublished = {Research Square},
year = {2026},
month = oct,
doi = {10.21203/rs.3.rs-11245373/v1},
url = {https://doi.org/10.21203/rs.3.rs-11245373/v1},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Integrated Plasmodium falciparum Transcriptomics Reveals Coordinated Stress Adaptation and Metabolic Remodeling in Severe Malarial Anemia
AU - Douglas Perkins
AU - Clinton Onyango
AU - Shamim Osata
AU - Sharley Wasena
AU - Ivy Hurwitz
AU - Philip Seidenberg
AU - Collins Ouma
AU - Samuel Anyona
AU - Kristan Schneider
AU - Benjamin McMahon
AU - Qiuying Cheng
PY - 2026
DA - 2026/10/16
PB - Research Square
DO - 10.21203/rs.3.rs-11245373/v1
UR - https://doi.org/10.21203/rs.3.rs-11245373/v1
AB - Malaria remains a leading cause of childhood morbidity and mortality in sub-Saharan Africa, with severe malarial anemia (SMA; hemoglobin (Hb) < 6.0 g/dL) representing one of the life-threatening complications of Plasmodium falciparum infection. While limited studies have examined host transcriptional responses in SMA, parasite transcriptional adaptations remain unexplored. Here, we performed parasite transcriptomic profiling in the same cohort of Kenyan children under five years of age in whom we previously characterized host transcriptional responses to SMA, including children presenting with SMA (n = 20) or non-SMA malaria (n = 40). Differential expression analysis identified 566 P. falciparum genes associated with SMA, predominantly involving up-regulated transcripts linked to proteostasis, translational regulation, stress-response pathways, and metabolic remodeling. Transcriptomic deconvolution indicated greater trophozoite and schizont representation in SMA, with reduced ring-stage and gametocyte signatures. Weighted gene co-expression network analysis and protein-protein interaction network analysis identified coordinated transcriptional programs enriched for proteasomal degradation, ubiquitin-mediated protein turnover, chaperone activity, RNA processing, and metabolic adaptation. XGBoost-SHAP modeling identified a small subset of parasite genes that captured much of the transcriptomic signal, classifying SMA from non-SMA malaria. Collectively, these findings define a distinct parasite transcriptional landscape in SMA characterized by coordinated stress adaptation and metabolic flexibility, highlighting proteostasis-associated pathways for further therapeutic investigation.
SN - 2693-5015
ER -