Dataset Information

Molecular profiling reveals features of clinical immunity and immunosuppression in asymptomatic P. falciparum malaria

ABSTRACT: Clinical immunity to P. falciparum malaria is non-sterilizing, with adults often experiencing asymptomatic infection. Historically, asymptomatic malaria has been viewed as beneficial and required to help maintain clinical immunity. Emerging views suggest that these infections are detrimental and constitute a parasite reservoir that perpetuates transmission. To define the impact of asymptomatic malaria, we pursued a systems approach integrating antibody responses, mass cytometry, and transcriptional profiling of individuals experiencing symptomatic and asymptomatic P. falciparum infection. Defined populations of classical and atypical memory B cells and a TH2 cell bias were associated with reduced risk of clinical malaria. Despite these protective responses, asymptomatic malaria featured an immunosuppressive transcriptional signature with upregulation of pathways involved in the inhibition of T cell function, and CTLA-4 as a predicted regulator in these processes. As proof of concept, we demonstrated a role for CTLA-4 in the development of asymptomatic parasitemia in infection models. The results suggest that asymptomatic malaria is not innocuous and might not support the induction of immune processes to fully control parasitemia or efficiently respond to malaria vaccines.

SUBMITTER: Ms. Stephanie, I Studniberg

PROVIDER: S-SCDT-MSB-2021-10824 | biostudies-other |

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:BackgroundThe transcriptome of Plasmodium falciparum clinical isolates varies according to strain, mosquito bites, disease severity and clinical history. Therefore, it remains a challenge to directly interpret the parasite's transcriptomic information into a more general biological signature in a natural human malaria infection. These confounding variations can be potentially overcome with parasites derived from controlled-human malaria infection (CHMI) studies.MethodsWe performed CHMI studies in healthy and immunologically naïve volunteers receiving the same P. falciparum strain ((Sanaria® PfSPZ Challenge (NF54)), but with different sporozoite dosage and route of infection. Parasites isolated from these volunteers at the day of patency were subjected to in vitro culture for several generations and synchronized ring-stage parasites were subjected to transcriptome profiling.FindingsWe observed clear deviations between CHMI-derived parasites from volunteer groups receiving different PfSPZ dose and route. CHMI-derived parasites and the pre-mosquito strain used for PfSPZ generation showed significant transcriptional variability for gene clusters associated with malaria pathogenesis, immune evasion and transmission. These transcriptional variation signature clusters were also observed in the transcriptome of P. falciparum isolates from acute clinical infections.InterpretationOur work identifies a previously unrecognized transcriptional pattern in malaria infections in a non-immune background. Significant transcriptome heterogeneity exits between parasites derived from human infections and the pre-mosquito strain, implying that the malaria parasites undergo a change in functional state to adapt to its host environment. Our work also highlights the potential use of transcriptomics data from CHMI study advance our understanding of malaria parasite adaptation and transmission in humans. FUND: This work is supported by German Israeli Foundation, German ministry for education and research, MOE Tier 1 from the Singapore Ministry of Education Academic Research Fund, Singapore Ministry of Health's National Medical Research Council, National Institute of Allergy and Infectious Diseases, National Institutes of Health, USA and the German Centre for Infection Research (Deutsches Zentrum für Infektionsforschung-DZIF).

Dataset Information

Molecular profiling reveals features of clinical immunity and immunosuppression in asymptomatic P. falciparum malaria

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets