Cumulative malaria parasite exposure in endemic regions often results in the acquisition of partial immunity and asymptomatic infections. There is limited information on how host-parasite interactions mediate maintenance of chronic symptomless infections that sustain malaria transmission. Here, we have determined the gene expression profiles of the parasite population and the corresponding host peripheral blood mononuclear cells (PBMCs) from 21 children (<15 years). We compared children who were defined as uninfected, asymptomatic and those with febrile malaria. Children with asymptomatic infections had a parasite transcriptional profile characterized by a bias toward trophozoite stage (~12 hours-post invasion) parasites and low parasite levels, while earlier ring stage parasites were characteristic of febrile malaria. The host response of asymptomatic children was characterized by downregulated transcription of genes associated with inflammatory responses, compared to children with febrile malaria. Interestingly, the host responses during febrile infections that followed an asymptomatic infection featured stronger inflammatory responses, whereas the febrile host responses from previously uninfected children featured increased humoral immune responses. The priming effect of prior asymptomatic infection may explain the blunted acquisition of antibody responses seen to malaria antigens following natural exposure or vaccination in malaria endemic areas.

Proteins were extracted from PBMCs by resuspending the pellet with 5µl of 6M UREA (Thermo scientific). The protein samples were then adjusted with 50mM Triethylamonium bicarbonate (TEAB, Sigma-Aldrich) to 100µl and the protein concentration determined using the Bicinchoninic acid (BCA) protein assay (Thermo scientific). The protein samples were then reduced with 40mM dithiothretol, alkylated with 80mM iodoacetamide in the dark, and quenched with 80mM iodoacetamide at room temperature, followed by digestion with1µg/µl of trypsin (57). Nine pools, each containing 9 samples and 1 control for batch correction, were prepared by combining 1µl aliquots from each sample. The samples were pooled using a custom randomization R script. The pooled samples were then individually labelled using the Tandem Mass Tag (TMT) 10-plex kit (Thermo Scientific) according to the manufacturer’s instructions. One isobaric tag was used solely for the pooled samples and combined with peptides samples labelled with the remaining 9 tags. The labelled peptide pools were then desalted using a P10 C18 pipette ZipTips (Millipore) according to the manufacturer’s instructions. Eluted peptides were dried in a Speedvac concentrator (Thermo Scientific) and re-suspended in 15μl loading solvent (98% H2O, 2% acetonitrile, 0.05% formic acid). The peptides were then quantified using Qubit Protein Assay Kit (Thermo Fisher Scientific). A standardized protein concentration of 5µg was finally injected into the LC-MS/MS for analysis. The peptides were then loaded onto the liquid chromatography and separated on reverse-phase analytical column of 75µm x 50cm C18 (Thermo Scientific) and measured using a Q Exactive Orbitrap mass spectrometer as described by (Njunge et al., 2019) and mass spectrometer output files generated.

To identify and quantify proteins, mass spectrometer output files were analyzed using MaxQuant software version 2.0.3.0 (Cox and Mann, 2008) by searching against the Uniprot human proteome (downloaded on 10/06/2021) using the Andromeda search engine (Cox et al., 2011). N-terminal acetylation and methionine oxidations were set as variable modifications while cysteine carbamidomethylation and TMT-10plex labelled N-terminus and lysine were set as a fixed modification. The false discovery rate (FDR) cut-off was set as 0.01 for both proteins and peptides with a minimum length of seven amino acids and was determined by searching a reverse database. Enzyme specificity was set as C-terminal to arginine and lysine with trypsin as the protease. Only up to two missed cleavages were allowed in the database search. Peptide identification was performed with an allowed fragment mass deviation maximum of 20 ppm (parts per million) and an initial precursor mass deviation maximum of 7 ppm. Default parameters for Orbitrap-type data were used. The pooled sample channels were used for batch correction. The 10-plex corrected reported ion intensity matrix was extracted from the protein groups output file and used for downstream analysis. Proteins matching the reversed part of a decoy database, potential contaminants and proteins only identified by a modification site, were excluded. Differential protein abundance analysis of the labelled samples intensities generated by MaxQuant were performed using PERSEUS v2.05.0 MaxQuant software (MaxPlanck Institute of Biochemistry, Martinsried, Germany) as described in (Tyanova and Cox, 2018).

The files can be opened using MaxQuant software, specifically version 2.0.3.0 was used for analysis.

Differential protein abundance analysis of MaxQuant output was done using PERSEUS version 2.05.0 software.

Protein-protein interaction and Gene ontology analyses was perforened using STRING database version 11.5 (https://string-db.org/).