Skeleton binding protein-1-mediated parasite sequestration inhibits spontaneous resolution of malaria-associated acute respiratory distress syndrome.
Hendrik PossemiersThao-Thy PhamMarion CoensEmilie PollenusSofie KnoopsSam NoppenLeen VandermostenSigrid D'haeseLuna DillemansFran PrenenDominique ScholsBlandine Franke-FayardPhilippe E Van den SteenPublished in: PLoS pathogens (2021)
Malaria is a hazardous disease caused by Plasmodium parasites and often results in lethal complications, including malaria-associated acute respiratory distress syndrome (MA-ARDS). Parasite sequestration in the microvasculature is often observed, but its role in malaria pathogenesis and complications is still incompletely understood. We used skeleton binding protein-1 (SBP-1) KO parasites to study the role of sequestration in experimental MA-ARDS. The sequestration-deficiency of these SBP-1 KO parasites was confirmed with bioluminescence imaging and by measuring parasite accumulation in the lungs with RT-qPCR. The SBP-1 KO parasites induced similar lung pathology in the early stage of experimental MA-ARDS compared to wildtype (WT) parasites. Strikingly, the lung pathology resolved subsequently in more than 60% of the SBP-1 KO infected mice, resulting in prolonged survival despite the continuous presence of the parasite. This spontaneous disease resolution was associated with decreased inflammatory cytokine expression measured by RT-qPCR and lower expression of cytotoxic markers in pathogenic CD8+ T cells in the lungs of SBP-1 KO infected mice. These data suggest that SBP-1-mediated parasite sequestration and subsequent high parasite load are not essential for the development of experimental MA-ARDS but inhibit the resolution of the disease.
Keyphrases
- plasmodium falciparum
- acute respiratory distress syndrome
- binding protein
- extracorporeal membrane oxygenation
- mechanical ventilation
- early stage
- poor prognosis
- single molecule
- oxidative stress
- high resolution
- mass spectrometry
- long non coding rna
- metabolic syndrome
- diabetic rats
- type diabetes
- lymph node
- high glucose
- artificial intelligence
- big data
- free survival
- quantum dots