Plasmodium falciparum Infection of Human Volunteers Activates Monocytes and CD16+ Dendritic Cells and Induces Upregulation of CD16 and CD1c Expression

Abstract

Antigen-presenting cells (APCs) are key players in the induction and regulation of immune responses. In Plasmodium falciparum malaria, determination of which cells and pathways are activated in the network of APCs remains elusive. We therefore investigated the effects of a controlled human malaria infection in healthy, malaria-naive volunteers on the subset composition and activation status of dendritic cells (DCs) and monocytes. While subsets of monocytes increased in frequency during blood-stage infection, DC frequencies remained largely stable. Activation markers classically associated with peptide presentation to and priming of αβT cells, HLA-DR and CD86, were upregulated in monocytes and inflammatory CD16 myeloid DCs (mDCs) but not in the classical CD1c, BDCA2, or BDCA3 DC subsets. In addition, these activated APC subsets showed increased expression of CD1c, which is involved in glycolipid antigen presentation, and of the immune complex binding Fcγ receptor III (CD16). Our data show that P. falciparum asexual parasites do not activate classical DC subsets but instead activate mainly monocytes and inflammatory CD16 mDCs and appear to prime alternative activation pathways via induction of CD16 and/or CD1c. Changes in expression of these surface molecules might increase antigen capture and enhance glycolipid antigen presentation in addition to the classical major histocompatibility complex class II (MHC-II) peptide presentation and thereby contribute to the initiation of T-cell responses in malaria. (This study has been registered at Clinicaltrials.gov under registration no. NCT01086917.).

Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Figures

FIG 1

Antigen-presenting-cell (APC) gating strategy. (A) Single, viable PBMCs positive for HLA-DR and negative for the lineage markers CD3, CD19, and CD56. FSC, forward scatter; SSC, side scatter. (B) HLA-DR+ CD3− CD19− PBMCs were distinguished into CD14+ monocytes and CD14− APCs. (C) Monocytes were subdivided based on CD16 expression into CD14+ CD16− classical monocytes (I) and CD14+ CD16+ intermediate monocytes (II). (D) CD14− APCs were gated based on CD16 expression to distinguish CD14 CD16+ myeoloid dendritic cells (DCs) (III) (CD16 mDCs). (E) CD14− CD16− APCs were further subdivided into CD14− CD16− CD1c+ (IV) (type 1 myeloid DC [CD1c mDCs], also known as BDCA1 mDCs), CD14− CD16− BDCA3+ (V) (type 2 mDCs or BDCA3 mDCs), and CD14− CD16− BDCA2+ (VI) (plasmacytoid DCs [pDCs]).

FIG 2

Kinetics of APC subset frequencies and expression of activation markers during and after CHMI. (A) Kinetics of APC subset frequency (percentages of viable PBMCs). (B) Kinetics of HLA-DR expression (geometric mean fluorescence intensity [MFI]) of the six APC subsets. (C) Kinetics of CD86 expression (MFI) of the six APC subsets. Data are presented for each individual donor (gray dots) and as means (n = 15) with standard errors of the means (SEM) (black error bars). *, P < 0.05; **, P < 0.01; ***, P < 0.001 (one-way ANOVA with Dunnett's post hoc test compared to baseline [C −1]). Inclusion of the outlier (black square) in the CD1c mDC frequency in the statistical analysis renders the increase on the DT significant. C, challenge; DT, day of treatment.

FIG 3

CD1c and CD16 expression on APCs during CHMI. (A and B) Representative plots showing CD1c and CD16 expression on CD16 mDCs (black dots) (A) or CD1c mDCs (black dots) (B) at baseline (C −1) and peak activation (DT +3). Gray dots in panels A and B show all DCs. (C) Expression of CD1c on APC subsets. (D) Expression (geometric mean fluorescence intensity [MFI]) of CD1c on APC subsets over time. (E) CD16 expression on APC subsets. (F) Expression (MFI) of CD16 on APC subsets over time. Panels C and E show representative histogram plots from one donor at baseline (gray) and DT +3 (bold line). Data in panels D and F are presented for each individual donor (gray dots) and as means (n = 15) with SEM (black error bars).*, P < 0.05; **, P < 0.01; ***, P < 0.001 (one-way ANOVA with Dunnett's post hoc test compared to baseline [C −1]). C, challenge; DT, day of treatment.