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Increased circulation time of Plasmodium falciparum underlies persistent asymptomatic infection in the dry season


The dry season is a major challenge for Plasmodium falciparum parasites in many malaria endemic regions, where water availability limits mosquito vectors to only part of the year. How P. falciparum bridges two transmission seasons months apart, without being cleared by the human host or compromising host survival, is poorly understood. Here we show that low levels of P. falciparum parasites persist in the blood of asymptomatic Malian individuals during the 5- to 6-month dry season, rarely causing symptoms and minimally affecting the host immune response. Parasites isolated during the dry season are transcriptionally distinct from those of individuals with febrile malaria in the transmission season, coinciding with longer circulation within each replicative cycle of parasitized erythrocytes without adhering to the vascular endothelium. Low parasite levels during the dry season are not due to impaired replication but rather to increased splenic clearance of longer-circulating infected erythrocytes, which likely maintain parasitemias below clinical and immunological radar. We propose that P. falciparum virulence in areas of seasonal malaria transmission is regulated so that the parasite decreases its endothelial binding capacity, allowing increased splenic clearance and enabling several months of subclinical parasite persistence.

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Fig. 1: P. falciparum persists during the dry season.
Fig. 2: P. falciparum induces a minimal immune response during the dry season.
Fig. 3: P. falciparum genetic diversity is maintained throughout the year.
Fig. 4: Transcriptome of circulating P. falciparum at the end of the dry season differs from malaria-causing P. falciparum during the transmission season.
Fig. 5: Replication of persistent dry season P. falciparum is not impaired.
Fig. 6: Infected erythrocytes in circulation at the end of the dry season are at higher risk of splenic clearance.

Data availability

RNA-seq data (normalized counts data and raw sequencing reads) have been deposited in the National Center of Biotechnology Information’s Gene Expression Omnibus (GEO) and are accessible through GEO Series accession number GSE148125.

Metabolomics data are available at the National Institutes of Health (NIH) Common Fund’s National Metabolomics Data Repository website, the Metabolomics Workbench,, where it has been assigned project ID PR000948. The data can be accessed directly via This work is supported by NIH grant U2C-DK119886.

The data file of assembled var gene fragments of all isolates is available at


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We thank the residents of Kalifabougou, Mali, for participating in this study. We acknowledge the support of the Flow Cytometry Core Facility of DKFZ in Heidelberg, Germany, and the Immunology Core Lab of the UCRC in Bamako, Mali. We thank the Metabolomics Core Facility at Penn State University and A. Patterson and P. Smith from the Penn State Metabolomics Core. We thank Z. Bozdech and the lab at Nanyang Technological University, Singapore, for help and expertise with RNA extraction. This work was supported by the German Center for Infection Research (DZIF), the European Research Council under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement 759534), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) projektnummer240245660 SFB 1129 of the German Research Foundation and the Division of Intramural Research, National Institute of Allergy and Infectious Diseases, of the National Institutes of Health. R.T.L. was funded by the European Union’s Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie grant agreement DLV-839998.

Author information




C.M.A, H.F., R.T.-L., N.F.L., C.A., J.H., C.S.H., S.L., M.N., H.C., D.S., C.M., S.R., K.V., M.V.H., E.L.A. and S.P. performed experiments and analyzed data. S.D., D.D., K.K., A.O., B.T. and P.D.C. designed, conducted and supervised field work generating the clinical data and samples. J.M., N.O.S. and T.D.O. performed bioinformatic analysis. M.-E.N., C.L., T.L., M.A., A.F. and M.L. provided technical expertise, and T.L. and L.T. provided essential reagents. M.R. performed mathematical models. T.M.T., J.S. and V.W. provided statistics expertise. C.M.A. prepared figures, and C.M.A., H.F., R.T.-L., T.M.T., N.S.O. and T.D.O. helped prepare the manuscript. T.M.T., A.F., M.L., T.L., T.D.O., M.R. and P.D.C. provided insightful comments to the manuscript. P.D.C. discussed initial field and study designs. S.P. designed the study and wrote the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Silvia Portugal.

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Peer review information Alison Farrell is the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1

Characteristics of study participants stratified by year.

Extended Data Fig. 2 Parasite density of malaria cases during dry and transmission seasons.

Parasite density detected by microscopy on thick blood smear of 17 individuals that presented malaria cases both in the dry season (January to May, MALdry) and in the ensuing wet season (June to December, MALwet) in the years on 2017 and 2018. Parasitaemia data shows median ± IQR, two-tailed Mann-Whitney test.

Extended Data Fig. 3 Flow cytometry gating strategies.

a, Major leucocyte populations from frozen and fresh PBMCs (Surface staining) and fresh PBMCs intracellular content (Intracellular staining). b, P. falciparum-specific memory B cells in frozen PBMCs at the end of the dry season of children with or without subclinical P. falciparum infection.

Extended Data Fig. 4 Immune responses to P. falciparum during the dry season.

a, Proportions of NK subpopulations defined by CD56 and CD16 in children carrying (May+) or not (May) P. falciparum at the end of the dry season. Median ± IQR; One sided Dunn’s Kruskal-Wallis Multiple Comparisons test. b, Proportion of P. falciparum-specific IgG+ MBCs in classical, activated or atypical MBCs of P. falciparum carriers (May+) or uninfected individuals (May) at the end of the dry season. Median ± IQR; One sided Dunn’s Kruskal-Wallis Multiple Comparisons test. c, Proportion of children with antibodies specific to PfEMP1 domains binding to unknown receptors at the beginning (Jan) and end (May) of the dry season (n=106 Jan and May, 112 Jan and May+). Boxplots indicate median ± IQR. Values >1.5 times the IQR are plotted as individual points (Tukey method), RM one-way ANOVA (with Greenhouse-Geisser correction). d, Magnitude of IgG antibodies against PfEMP1 domains of B/A subtype between the beginning and end of the dry season in children carrying (May+) or not (May) subclinical P. falciparum infection at the end of the dry season (n=106 Jan and May, 112 Jan and May+) e, Breadth (left) and magnitude (right) of IgG reactivity to invasion-related antigens (Supplementary Table 11) at the end of the dry season in non-infected and subclinical children carrying P. falciparum (n=143 May, 139 May+). Individual antigen reactivity (detailed in Portugal et al.13) of invasion-related antigens based on Cowman et al.23. Breadth is the number of antigens to which the level of IgG reactivity exceeds 2 SDs above the no DNA control. Magnitude is the sum of log2 -IgG intensity values for all antigens per sample. Boxplots indicate median ± IQR, Tukey method, two-tailed Mann-Whitney test. f, P. falciparum invasion ratio between merozoite invasion in antibody depleted plasma and merozoite invasion in paired complete plasma from subclinical carriers and non-infected children (n=28 May+, 23 May), and malaria-naïve control (German adults’ plasma, n=9). One sided Dunn’s Kruskal-Wallis Multiple Comparisons test.

Extended Data Fig. 5 Volcano plots comparing the DEGs found in this study with the DEGs reported in two other studies26,27.

a, 141 DEGs previous reported in the comparison of transcriptomes of severe vs moderate malaria parasite physiological states were matched to the present study. 69 were not DEG in the dry season, 67 were upregulated and 5 were downregulated. b, 306 DEGs previous reported in the comparison of high vs low transmission clinical malaria causing parasites were matched to the present study. 182 were not DEGs in the dry season, 103 were upregulated and 21 were downregulated. DEGs found in this study are highlighted in yellow. Dots in blue represent the transcripts up-regulated (1131) and in red the transcripts down-regulated (476) in the dry season compared to clinical malaria samples.

Extended Data Fig. 6 Expression patterns in 3D7 parasites along the ~48 h intraerythrocytic developmental cycle (defined by Bozdech et al. PLoS Biology, 2003) of DEGs between P. falciparum of asymptomatic carriers at the end of the dry season (May) and at the first clinical malaria case (MAL) in the ensuing transmission season.

a, Glycerophospholipid metabolism b, Purine and Pyrimidine metabolism pathways by KEGG enrichment analysis using the DAVID tool.

Extended Data Fig. 7

Modelled removal of infected RBCs from circulation by means of cytoadhesion and splenic clearance over the 48 h replicative cycle, assuming the rate of removal increases with increasing expression of cytoadhering variant surface antigens, and where RBC modification by the parasite gradually increases the cell’s rigidity and hence splenic retention.

Extended Data Fig. 8

LARSFADIG motifs that identify PfEMP1 coding genes of 12 subclinical individuals at the end of the dry season (May) and 12 first clinical malaria episodes in the ensuing wet season (MAL).

Supplementary information

Supplementary Information

Supplementary Tables 1–5, 7 and 9–12.

Reporting Summary

Supplementary Tables

Supplementary Tables 6 and 8

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Andrade, C.M., Fleckenstein, H., Thomson-Luque, R. et al. Increased circulation time of Plasmodium falciparum underlies persistent asymptomatic infection in the dry season. Nat Med 26, 1929–1940 (2020).

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