Infection Redistribution in Controlled Human Malaria with B Cell Subset

BAFF and BAFF Receptor Levels Correlate with B Cell Subset Activation and Redistribution in Controlled Human Malaria Infection This information is current as of September 29, 2021. Anja Scholzen, Anne C. Teirlinck, Else M. Bijker, Meta Roestenberg, Cornelus C. Hermsen, Stephen L. Hoffman and Robert W. Sauerwein J Immunol 2014; 192:3719-3729; Prepublished online 19 March 2014; Downloaded from doi: 10.4049/jimmunol.1302960 http://www.jimmunol.org/content/192/8/3719 http://www.jimmunol.org/ Supplementary http://www.jimmunol.org/content/suppl/2014/03/19/jimmunol.130296 Material 0.DCSupplemental References This article cites 60 articles, 24 of which you can access for free at: http://www.jimmunol.org/content/192/8/3719.full#ref-list-1

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The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2014 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology

BAFF and BAFF Receptor Levels Correlate with B Cell Subset Activation and Redistribution in Controlled Human Malaria Infection

Anja Scholzen,* Anne C. Teirlinck,* Else M. Bijker,* Meta Roestenberg,*,† Cornelus C. Hermsen,* Stephen L. Hoffman,‡ and Robert W. Sauerwein*

Characteristic features of Plasmodium falciparum malaria are polyclonal B cell activation and an altered composition of the blood B cell compartment, including expansion of CD212CD272 atypical memory B cells. BAFF is a key cytokine in B cell homeostasis, but its potential contribution to the modulation of the blood B cell pool during malaria remains elusive. In the controlled human malaria model (CHMI) in malaria-naive Dutch volunteers, we therefore examined the dynamics of BAFF induction and B cell

subset activation and composition, to investigate whether these changes are linked to malaria-induced immune activation and, in Downloaded from particular, induction of BAFF. Alterations in B cell composition after CHMI closely resembled those observed in endemic areas. We further found distinct kinetics of proliferation for individual B cell subsets across all developmental stages. Proliferation peaked either immediately after blood-stage infection or at convalescence, and for most subsets was directly associated with the peak parasitemia. Concomitantly, plasma BAFF levels during CHMI were increased and correlated with membrane-expressed BAFF on monocytes and dendritic cells, as well as blood-stage parasitemia and parasite-induced IFN-g. Correlating with in- 2 low 2 2 creased plasma BAFF and IFN-g levels, IgD CD38 CD21 CD27 atypical B cells showed the strongest proliferative response of http://www.jimmunol.org/ all memory B cell subsets. This provides unique evidence for a link between malaria-induced immune activation and temporary expansion of this B cell subset. Finally, baseline BAFF-R levels before CHMI were predictive of subsequent changes in proportions of individual B cell subsets. These ﬁndings suggest an important role of BAFF in facilitating B cell subset proliferation and redistribution as a consequence of malaria-induced immune activation. The Journal of Immunology, 2014, 192: 3719–3729.

umoral immune responses play a major role in conferring compartment as recently described in naturally malaria-exposed naturally acquired immunity to malaria (1). This immu- populations (15–20). These changes observed in acutely infected nity, however, appears to be slow to develop and inef- or continuously exposed individuals include increased levels of H + + by guest on September 29, 2021 fectively maintained (2, 3), also demonstrated by the low prevalence transitional B cells (TBCs) (15, 17), reduced levels of IgD CD27 of Plasmodium falciparum malaria Ag-speciﬁc memory B cells marginal zonelike nonswitched MBCs (nsMBCs) (17), and an (MBCs) even in high endemic areas (4–7). Although the complex enlarged proportion of atypical MBCs (atypMBCs), which have nature of the parasite (2, 5) and the high degree of antigenic become a recent research focus (16–20). In malaria-endemic areas, variation (8) certainly contribute to this apparently impaired gen- expansion of atypMBCs appears to be linked to both cumulative eration of humoral immune memory, there is also increasing ev- duration and frequency of parasite exposure (18–20). Because idence that the malaria parasite actively alters B cell function (9). of the cross-sectional nature of most of these studies, however, This includes not only polyclonal activation and modiﬁed re- conclusive evidence for a causal link is missing. Also unknown sponsiveness of B cells in vitro and in vivo (10–14), but also pro- are the mechanisms that govern these alterations of the blood found changes to the composition of the peripheral blood B cell B cell pool.

*Department of Medical Microbiology, Radboud University Medical Center, 6525 C.C.H. performed quantitative PCR analysis; S.L.H. contributed vital reagents; A.S., GA Nijmegen, The Netherlands; †Department of Infectious Diseases, Leiden Uni- A.C.T., E.M.B., and R.W.S. interpreted the data; A.S. and R.W.S. wrote the manu- versity Medical Center, 2333 ZA Leiden, The Netherlands; and ‡Sanaria Inc., Rock- script; and A.C.T., E.M.B., and S.L.H. critically revised the manuscript. ville, MD 20850 Address correspondence and reprint requests to Robert W. Sauerwein and Anja Received for publication November 1, 2013. Accepted for publication February 17, Scholzen, Radboud University Medical Center, Geert Grooteplein 28, 6525 GA 2014. Nijmegen, The Netherlands. E-mail addresses: [email protected] (R.W.S.) and [email protected] (A.S.) This work was supported by Top Institute Pharma (Grant T4-102) and the FP7- founded European Virtual Institute of Malaria Research (Grant 242095). A.S. re- The online version of this article contains supplemental material. ceived a long-term postdoctoral fellowship from the European Molecular Biology Abbreviations used in this article: actMBC, activated memory B cell; actN, activated Organization. A.C.T. was supported by the European Vaccine Initiative with a Euro- naive B cell; atypMBC, atypical memory B cell; BCMA, B cell maturation Ag; pean Malaria Vaccine Development Association Ph.D. scholarship. The development BDCA, blood dendritic cell Ag; C, challenge; CHMI, controlled human malaria and manufacturing of cryopreserved Plasmodium falciparum sporozoites (PfSPZ infection; cMBC, classical memory B cell; cN, classical naive B cell; DC, dendritic Challenge) was further supported by Small Business Innovation Research Grants cell; dnN, double-negative naive B cell; DT, day of treatment; FcRL4, FcR-like R44AI058375-03, 04, 05, and 05S1 from the National Institute of Allergy and In- protein 4; IQR, interquartile range; MBC, memory B cell; nsMBC, nonswitched fectious Diseases at the National Institutes of Health and through Grant 07984 from MBC; PB, plasmablast; PfSPZ, Plasmodium falciparum sporozoite; qPCR, quantita- the Program for Appropriate Technology in Health (PATH) Malaria Vaccine Initiative tive PCR; SLE, systemic lupus erythematosus; TACI, transmembrane activator and (with funds from the Bill and Melinda Gates Foundation). The funders had no role in calcium modulator and cyclophilin ligand interactor; TBC, transitional B cell; TS, study design, data collection and analysis, decision to publish, or preparation of the thick-smear. manuscript. A.S. and A.C.T. conducted experiments; A.S. designed the experiments and analyzed Copyright Ó 2014 by The American Association of Immunologists, Inc. 0022-1767/14/$16.00 the data; E.M.B. and M.R. performed the clinical study and collected clinical data; www.jimmunol.org/cgi/doi/10.4049/jimmunol.1302960 3720 BAFF AND B CELL SUBSET ACTIVATION IN HUMAN MALARIA

A key cytokine in mediating B cell homeostasis by regulating was determined for all donors (n = 18; n =15TS+). FcR-like protein 4 differentiation and survival is the constitutively expressed BAFF (FcRL4), BAFF-R, transmembrane activator and calcium modulator and (21). BAFF is initially synthesized in membrane-anchored form by cyclophilin ligand interactor (TACI), and B cell maturation Ag (BCMA) expression on B cell subsets and surface BAFF expression on APCs was cytokine-activated myeloid cells such as monocytes and dendritic determined in those donors for which sufficient cells were available (n = 14; cells (DCs), and subsequently released after enzymatic cleavage n =11TS+). Abs used for flow cytometry are listed in Table II. For im- (22). In vitro, surface BAFF production and release by P. falcipa- munostaining, 500,000–1,000,000 cells/stain were transferred into a 96-well rum–activated human monocytes and concomitant naive B cell V-bottom plate, washed once with 200 ml PBS, and incubated with 50 ml fixable dead cell stain dilution in PBS for 30 min on ice. Cells were then activation has been demonstrated (23), whereas in a murine model washed twice with staining buffer (PBS containing 0.5% BSA; Sigma), of acute malaria infection, reduced surface BAFF expression by and stained with 50 ml Ab mixture diluted in staining buffer for 30 min at APCs corresponds with impaired MBC survival (24). Finally, in room temperature, followed by another wash step with staining buffer. children with acute malaria, increased plasma BAFF levels have This was repeated for the secondary surface staining step. Cells were then been reported, which correlate with disease severity (25). resuspended in 50 ml fixation/permeabilization buffer (eBioscience) and incubated for 30 min on ice, followed by a wash step with 150 mlper- A unique tool to gain insights into immunomodulatory effects meabilization buffer (eBioscience). For intracellular staining, cells were of the P. falciparum parasite in humans is the controlled human incubated for 30 min at room temperature with 50 ml Ab mixture diluted in malaria infection (CHMI) model, allowing analysis of sequential permeabilization buffer. Cells were washed with permeabilization buffer, samples of previously malaria-naive volunteers during a primary resuspended in 200 ml PBS/1% paraformaldehyde, and kept on ice until analyzed. Fifty thousand to 200,000 events/sample were acquired on a Cyan P. falciparum infection in comparison with their preinfection ADP 9-color flow cytometer (Dako/Beckman Coulter). Flow cytometry data status (26–28). We therefore took advantage of the CHMI model were analyzed using FlowJo v9.6 software. to study the dynamics of B cell activation and modulation during Downloaded from ELISA the very early stages of malaria infection. We further compre- hensively investigated the kinetics and source of P. falciparum– Plasma BAFF and IFN-g levels were determined in cryopreserved EDTA induced BAFF during CHMI, and addressed the question whether anticoagulated plasma samples using the Human BAFF/BLyS/TNFSF13B modifiedBAFFsecretionorBcellBAFF-Rexpressionmay Quantikine ELISA Kit (R&D Systems) and the Human IFN-g ELISA Ready-SET-Go kit (eBioscience) according to the manufacturer’s recom- provide an explanation for B cell subset activation or reshaping of mendations. the human B cell compartment during malaria. http://www.jimmunol.org/ Statistical analysis Materials and Methods Statistical analysis was performed using GraphPad prism software v5. We Study subjects and CHMI used parametric tests because the majority of data analyzed was normally distributed as determined by D’Agostino and Pearson omnibus normality Eighteen healthy, malaria-naive Dutch adult volunteers (age 19–30 y, test, and because nonparametric tests have limited power to detect sig- median 23 y) were subjected to CHMI by intradermal injection of 2500, nificant differences in small data set. Data for more than two time points 10,000 or 25,000 (n = 6 in each group) aseptic, purified, cryopreserved P. were analyzed by repeated-measures one-way ANOVA. Dunnett’s post hoc falciparum sporozoites (PfSPZ Challenge, strain P. falciparum NF54) in an test was used when comparing all time points to C-1 baseline data, whereas open-label phase I clinical trial at the Radboud University Medical Centre Bonferroni posttest was applied when comparing different B cell subsets.

from October 2010 to July 2011 (29). The three groups were subjected to Data for cell subsets at several time points were analyzed by repeated- by guest on September 29, 2021 CHMI at different time points, in 1-mo intervals. Written, informed con- measures two-way ANOVA with Bonferroni post hoc test. One-sample t sent was obtained from each volunteer. The trial was performed in ac- tests were used to determine whether fold changes in B cell proportions at cordance with Good Clinical Practice and an Investigational New Drug a given time point compared with C-1 were significantly different from 1 application was filed with the U.S. Food and Drug Administration. The (no change). Relationships between plasma BAFF and surface BAFF or study was approved by the Central Committee for Research Involving BAFF-R levels were analyzed by Pearson correlation. If parameters were Human Subjects of The Netherlands (CMO CCMO NL31858.091.10). The not normally distributed, nonparametric Spearman correlation was used for trial was registered at Clinicaltrials.gov (identifier: NCT 01086917). analysis (relationships between peak parasitemia, plasma BAFF and IFN-g As reported previously (29), 15 volunteers (n = 5 in each group) de- levels, and B cell subset proliferation). veloped patent parasitemia as determined by both thick-smear (TS; median prepatent period [range]: 12.6 [11–14.3] d) and retrospective quantitative PCR (qPCR; 10.3 [9–12] d). When TS+ (or at day 21 for volunteers re- Results maining TS2) volunteers were treated with atovaquone/proguanil. There Sequential blood samples were collected before, during, and after was no significant difference between the three groups by either time to CHMI by intradermal administration of cryopreserved P. falciparum positive qPCR or TS, parasite densities on day of TS positivity (day of sporozoites (29). Fifteen volunteers became TS+ between days 11 and treatment [DT]), or peak parasite density (measured at time of TS posi- 14.3 postinfection and reached peak parasitemia of 3–759 parasites/ml tivity 6 18 h). blood (median 56, interquartile range [IQR] 15–102). Three donors PBMC isolation, cryopreservation, and thawing remained negative by both TS and qPCR until day 21 after challenge (C+21), when they were presumptively drug treated. These donors Blood samples for PBMC isolation were collected at baseline (challenge + C-1), during liver-stage infection (C+5), during developing blood stage were analyzed in parallel with TS donors to ensure that any changes infection (C+9), at TS positivity just before treatment (DT), 3 d after observed after treatment were not solely related to drug treatment. treatment (DT+3), and 35 and 140 d post challenge infection (C+35, Hematological parameters showed significant changes over the course C+140). PBMCs were isolated by density gradient centrifugation from citrate of infection (Table I). Decreased total leukocyte, lymphocyte, and anticoagulated blood using Vacutainer cell preparation tubes (BD Diag- + nostics). After four washes in ice-cold PBS, cells were counted and cry- platelet counts in TS donors were most evident at 3 d after treatment opreserved at a concentration of 10 3 106 cells/ml in ice-cold FCS (Life (DT+3; all p , 0.001), with lymphocyte counts also significantly Technologies)/10% DMSO (Merck) using Mr. Frosty freezing containers decreasedonDT(p , 0.05). The proportion of total B cells within (Nalgene). Samples were stored in vapor-phase nitrogen. Immediately PBMCs mirrored this trend, showing a significant decrease at DT+3 before use, cells were thawed, washed twice in Dutch-modified RPMI , 1640 (Life Technologies/Invitrogen), and counted. compared with baseline (C-1; p 0.05). Increased plasma BAFF during CHMI is associated with Flow cytometry analysis parasitemia and IFN-g secretion Phenotypic analysis of sequential PBMC samples collected at different time points before, during, and after CHMI was conducted simultaneously for During CHMI, a statistically significant increase in plasma BAFF each individual donor in one experiment to avoid confounding influences of was detected from the day of TS positivity (DT) onward (Fig. 1A, day-to-day interexperimental variation. Ki67 expression on B cell subsets 1B). This increase was absent in the three donors who did not The Journal of Immunology 3721

Table I. Hematological parameters at baseline and during CHMI in TS+ volunteers

C-1 DT DT+3 C+35 p Compared with C-1 Leukocyte counta 5.1 (4.3–6.2) 4.9 (4.5–5.6) 2.6 (2.0–3.8) 5.4 (4.4–5.8) DT+3*** Lymphocyte counta 1.7 (1.52–2.31) 1.1 (0.84–1.67) 0.88 (0.81–1.18) 2.14 (1.93–2.62) DT*, DT+3*** % B cellsb 8.92 (6.03–12.23) 10.66 (6.54–15.17) 5.35 (3.43–7.15) 8.41 (6.13–12.2) DT+3* Platelet counta 240 (190–251) 224 (186–281) 149 (95–191) 243 (213–297) DT+3*** Hbc 8.2 (7.7–8.9) 8 (7.7–8.7) 8.1 (7.6–8.5) 7.9 (7.3–8.5) aLeukocyte, lymphocyte, and platelet counts 3 109/L, median 6 IQR. bB cells as % of viable PBMCs by flow cytometry, median 6 IQR. cHb in mm/L, median 6 IQ. *p , 0.05, ***p , 0.001 as determined by one-way ANOVA with Dunnett’s post hoc test. C-1, day before challenge. acquire blood-stage parasitemia (Fig. 1B). BAFF levels peaked at Fig. 2C). We next analyzed which APC populations contributed to DT+2 or DT+3, with a median 3.3-fold increase (IQR 2.3–5.9) CHMI-induced surface-BAFF expression. Based on differential and an absolute increase of 1053 pg/ml (median; IQR 616–2956 expression of the LPS receptor CD14 and the low-affinity FcgRIII pg/ml) compared with baseline. Increased plasma BAFF concen- CD16, HLA-DR+lin2 APCs were subdivided into classical trations were precededbyelevatedplasmaIFN-g (Fig. 1B), an monocytes (CD14+CD162), intermediate monocytes (CD14+ important factor in mediating BAFF release (22). The increase in CD16+), and inflammatory monocytes (CD142CD16+). CD142 Downloaded from IFN-g closely followed the increase in parasitemia, and peak IFN-g CD162 APCs were further gated on blood DC Ag 1–positive levels correlated with peak parasitemia (Spearman r = 0.70, p = (BDCA-1+) DCs, BDCA-2+ DCs, and BDCA-3+ DCs (Fig. 2D). 0.004; Fig. 1C). The interval between peak IFN-g (on DT+1) and The proportion of BAFF+ APCs within PBMCs was already peak BAFF levels (on DT+3) in plasma was 2 d (Fig. 1B), and markedly elevated on DT and then further increased until DT+3 peak BAFF levels positively correlated with peak IFN-g concen- (Fig. 2E), a pattern that was again not observed in TS2 individuals 2 trations (r = 0.78, p = 0.001; Fig. 1D). The correlation between (Supplemental Fig. 1). CD14+CD16 classical monocytes constituted http://www.jimmunol.org/ peak BAFF and parasite load, however, was only weak and did not the largest proportion of BAFF+ APCs, followed by inflammatory reach significance (r = 0.47, p = 0.08; Fig. 1E). monocytes (Fig. 2E). Classical, inflammatory, and intermediate monocytes, as well as BDCA-1 DCs, showed a significant increase in BAFF+ Surface BAFF expression on APC populations is increased cells on DT+3 compared with C-1 (Fig. 2F), whereas no such increase during CHMI wasseenforBDCA-2andBDCA-3DCs.Thefoldincreasein Major sources of plasma BAFF are myeloid cells, which initially BAFF+ cells was highest within classical monocytes (median 2.76 express the cytokine in membrane-bound form (22). Indeed, [IQR 1.7–3.5]), followed by inflammatory monocytes (2.63 [2.3– HLADR+ lineage (CD3, CD19, CD56)-negative APCs showed in- 4.5]) and BDCA-1 DCs (2.18 [1.4–3.7]). When analyzing absolute creased levels of surface BAFF expression at DT+3 (p , 0.001; percentages of BAFF+ cells, there was no difference among the by guest on September 29, 2021 Fig. 2A, 2B), and this increase in BAFF+ APCs correlated with the three monocyte subsets at baseline (C-1; median [IQR]: classical increase in plasma BAFF levels (Pearson r = 0.70, p = 0.016; monocytes, 2.9% [2.1–5.1%]; intermediate monocytes, 3.0%

FIGURE 1. Plasma BAFF levels during CHMI. Plasma BAFF was quantified for (A, B, D, E) n =15TS+ and (B) n =3TS2 donors on baseline (C-1), and from 1 d before (DT-1) until 3 d after treatment (DT+3) and after resolved infection (C+35). (A) Dots depict individual TS+ donors; error bars denote the median and IQR; asterisks show significant differences compared with C-1 by one-way ANOVAwith Dunnett’s post hoc test (*p , 0.05, **p , 0.01, ***p , 0.001). (B) Kinetics of P. falciparum parasite load (open triangles), plasma IFN-g (gray filled circles), and BAFF (black filled squares) were analyzed in TS+ donors, depicted as meanandSEM.BAFFinTS2 donors is shown in open squares (light gray). The individual P. falciparum load per day was calculated per donor as the mean of all PCR samples taken on that day for this individual donor. Relationships among (C) peak P. falciparum load and peak IFN-g,(D) peak IFN-g and peak plasma BAFF, and (E) peak P. falciparum load and peak plasma BAFF in TS+ donors were analyzed by nonparametric Spearman correlation. 3722 BAFF AND B CELL SUBSET ACTIVATION IN HUMAN MALARIA Downloaded from http://www.jimmunol.org/

2 FIGURE 2. Surface BAFF expression on DC and monocyte populations during CHMI. Surface BAFF expression on HLADR+ CD3/CD19/CD56 APC by guest on September 29, 2021 subsets was determined by flow cytometry. Data are shown as representative flow cytometry plots for (A) one donor and (B) for all analyzed TS+ donors (n = 11), with dots depicting individual donors, and error bars the median and IQR. (C) The relationship between the increases (calculated by subtracting C-1 from DT+3 values) in plasma BAFF levels and proportion of BAFF+ APCs was determined by Pearson correlation analysis. (D) APCs were further subdivided into: (i) classical monocytes (class mono; CD14+CD162), (ii) intermediate monocytes (interm mono; CD14+CD16+), (iii) inflammatory monocytes (inflamm mono; CD142CD16+) and CD142CD162,(iv) BDCA-1+ DCs, (v) BDCA-2+ DCs, and (vi) BDCA-3+ DCs. (E) Median proportions of BAFF+ APC subsets were analyzed within viable PBMCs on C-1, DT, and DT+3. (F) Percentages of BAFF+ cells within APC subsets are shown as individual data, medians, and IQR. Asterisks show significant differences compared with C-1 by one-way ANOVAwith Dunnett’s post hoc test (*p , 0.05, ***p , 0.001).

[1.7–4.0%]; inflammatory monocytes, 3.2% [2.8–4.2%]). On DT for so-called atypical CD212CD272MBCs expanded in malaria- +3, however, inflammatory monocytes (11.1% [8.1–14.5%]) showed exposed individuals living in highly endemic areas (16, 19). In significantly higher levels of BAFF expression than classical (7.1% contrast with a subset of tonsil B cells (Fig. 3F), peripheral blood [5.4–10.7%]; p , 0.05) and intermediate monocytes (5.2% [3.3–8. B cells, including CD212CD272 atypMBCs from healthy Dutch 2%]; p , 0.001). individuals, did not express the inhibitory FcRL4 (Fig. 3G, 3H). FcRL4 expression on B cells was not induced during or immedi- CHMI induces low, transient FcRL4 expression and ately after CHMI, but 2 wk posttreatment (C+35; p , 0.001) in proliferation of B cell subsets with distinct kinetics 2 TS+ donors (Fig. 3H), and not in those three that remained TS Increased BAFF secretion after CHMI is likely to have an impact (data not shown). This induction of FcRL4 expression was only on B cell activation. To analyze the peripheral blood B cell com- temporary, occurred on a very small proportion of B cells, did not partment, we developed a 9-color B cell panel (Table II) and gating correlate with peak parasitemia, IFN-g, or BAFF levels, and was strategy to delineate 10 phenotypically distinct B cell populations not confined to atypMBCs (p , 0.05), but also was observed in (Fig. 3A) based first on IgD and CD38 expression (Fig. 3B), fol- cMBCs (p , 0.05), nsMBCs (p , 0.001), activated MBCs lowed by further subdivision using CD10, CD21, and CD27 (actMBCs; p , 0.01), classical naive B cells (cNs; p , 0.001), and 2 2 (Fig. 3C). As reported previously, CD21 CD27 MBCs in healthy, CD212CD272 double-negative naive B cells (dnNs; p , 0.05; malaria-naive donors (before CHMI) constitute only a small pro- Fig. 3I). portion of circulating B cells (median 1.96% [IQR 1.76–2.66%]) B cell activation was assessed by Ki67 expression (30), which is in contrast, for instance, with classical MBCs (cMBCs; median found only in currently dividing cells. Increased levels of prolif- 2 2 12.43% [IQR 9.9–16.64%]; Fig. 3D). These CD21 CD27 MBCs eration after CHMI were observed in nearly all B cell subsets closely resembled the phenotype (high expression of CCR6 and (Fig. 4A) with the exception of actMBCs (Fig. 4Biii) and plasma- CD86, low expression of CXCR5 and CD24; Fig. 3E) reported blasts (PBs), the latter being consistently .95% Ki67+ (Fig. 4Bi). The Journal of Immunology 3723

Table II. Abs used for ﬂow cytometry

Purpose Target Ag Fluorochrome Clone Supplier B cell panel Viability Fixable viability eFluor 450 n/a eBioscience Dump channela CD3 FITC or PE HIT3 Biolegend CD56 FITC or PE HCD56 Biolegend CD14 FITC or PE HCD14 Biolegend B cell lineage CD19 Allophycocyanin-eF780 HIB19 eBioscience B cell subset CD10 ECD ALB1 Beckman Coulter CD38 PerCP HIT2 Biolegend CD27 PC7 IA4CD27 Beckman Coulter CD21 Allophycocyanin B-ly4 BD Biosciences IgD Biotin IA6-2 BD Biosciences Streptavidin Paciﬁc Orange n/a Invitrogen Variable marker BAFF-R FITC 11C1 Biolegend Ki67 FITC B56 BD Biosciences TACI PE 1A1 Biolegend BCMA PE polyclonal R&D Systems CD86 FITC 2331 (FUN-1) BD Biosciences CCR6 FITC 53103 R&D Systems CXCR5 PE 51505 R&D Systems Downloaded from CD24 FITC ML5 Biolegend FcRL4 PE 413D12 Biolegend DC/monocyte panel Viability Live/dead stain Aqua n/a Invitrogen Dump channela CD3 PerCP/Cy5,5 HIT3 Biolegend CD19 PerCP/Cy5,5 HIB19 Biolegend CD56 PerCP/Cy5,5 HCD56 Biolegend http://www.jimmunol.org/ Monocyte lineage CD16 PECy7 3G8 Biolegend CD14 Paciﬁc Blue HCD14 Biolegend HLA-DR Allophycocyanin-Cy7 L243 Biolegend DC subset BDCA-1 PE AD5-8E7 Miltenyi Biotech BDCA-2 Biotin AC144 Miltenyi Biotech Streptavidin ECD n/a Beckman Coulter BDCA-3 Allophycocyanin AD5-14H12 Miltenyi Biotech Variable marker BAFF FITC 137314 R&D Systems aDump channel composed of lineage markers to gate out nonrelevant PBMC subsets. n/a, not applicable. by guest on September 29, 2021

This proliferative response showed distinct kinetics for individual peak IFN-g concentrations correlated with the proportion of prolif- B cell subsets: proliferation of TBCs, cMBCs, CD272 MBCs, and erating atypMBCs (r =0.86,p , 0.0001; Fig. 4F), their nonswitched atypMBCs (all p , 0.001; Fig. 4Bii, v, vii, ix), as well as dnN dnN counterparts (r =0.64,p = 0.01), and in contrast with BAFF, B cells (p , 0.05; Fig. 4Ax) peaked at DT+3. Among MBC cMBC proliferation (r =0.57,p = 0.03). subsets, atypMBCs showed the strongest proliferative response at DT+3 (Fig. 4C). Finally, significant proliferative responses were Altered B cell subset proportions associate with BAFF-R found 3 wk after resolved malaria infection (C+35) for cN expression, but not proliferation Bcells(p , 0.01; Fig. 4Bviii), activated naive B cells (actNs) Selective proliferation of individual B cell subsets at different time and nsMBCs (both p , 0.001; Fig. 4Biv, vi), and were still ongoing points during CHMI might affect the composition of the peripheral for dnNs (p , 0.001; Fig. 4Bx) and cMBCs (p , 0.01; Fig. 4Bv). blood B cell compartment. Indeed, the percentage of PBs, TBCs, The three donors remaining negative for parasitemia showed no atypMBCs, and dnNs within CD19+ B cells was significantly in- proliferation (Supplemental Fig. 2). Despite the strong proliferative creased at DT+3 (Fig. 5A). There was, however, no correlation responses, also in the MBC compartment, we found no evidence for between the increased proportion and proliferative response for hypergammaglobulinemia, with plasma IgG levels remaining stable any of these subsets at this time point. Proportions of other subsets during CHMI (median [IQR]: C-1, 8.98 mg/ml [8.2–12.3]; DT, 9.11 were significantly decreased during exposure to blood-stage para- mg/ml [6.4–13.1]; DT+3, 7.47 mg/ml [6.5–9.3]; C+35, 8.98 mg/ml sitemia (cNs and cMBCs at DT+3; nsMBCs at DT and DT+3; [6.9–10.4]). Fig. 5A and data not shown), despite active proliferation (cMBCs at The proportion of Ki67+ cells correlated with peak parasitemia DT+3). Finally, increases in the proportion of activated naive and within atypMBCs (Spearman r = 0.56, p = 0.03; Fig. 4D) and MBC subsets were particularly evident after parasite clearance cMBCs (r =0.71,p = 0.003) on DT+3, as well as within cMBCs (C+35; Fig. 5B), but again were not associated with proliferation at (r =0.63,p =0.01),CD212CD272 dnNs (r =0.55,p =0.03),and this time point. These patterns of altered B cell subset proportions cN B cells (r =0.62,p =0.014)onC+35.Moreover,onDT+3,the were again not found for the three donors who remained negative proportion of proliferating atypMBCs (r =0.68,p = 0.005; for parasitemia (Supplemental Fig. 3). Fig. 4E) and their nonswitched dnN counterparts (r =0.64,p = 0.01), Another potential cause of altered proportions of individual cir- but not other B cell subsets, correlated with plasma BAFF. There culating B cell subsets is redistribution between blood and lym- was no correlation between DT+3 plasma BAFF levels and B cell phatic tissues, and this chemotactic B cell migration can be subset proliferation on C+35. Because plasma BAFF levels strongly augmented by BAFF signaling through its receptor BAFF-R (31). correlated with plasma IFN-g, we also assessed the relationship be- Intriguingly, we found an inverse correlation between baseline tween peak IFN-g levels and B cell subset proliferation. As for BAFF, BAFF-R expression levels of the 10 different B cell subsets and 3724 BAFF AND B CELL SUBSET ACTIVATION IN HUMAN MALARIA

FIGURE 3. Proportion and phenotype of B cell subsets during CHMI. After exclusion of debris, doublets, and dead cells, lineage (CD3/CD56/ CD14)-negative, CD19+ Bcellswere subdivided based on (A) IgD and CD38, and then on (B) CD10 expression. (C)CD38hi B cells were divided into: (i)CD102IgD2CD38hiCD27+ PBs and (ii)CD10+ IgD+CD38hi CD272 TBCs. CD38lowCD102 B cells were subdivided ﬁrst based on IgD and then CD21 and CD27 expression into four pairs of switched

and nonswitched/naive B cell pop- Downloaded from ulations (C): (iii)CD212CD27+ actMBCs and (iv)actNs;(v)CD21+ CD27+ classical MBCs (cMBC) and (vi) nsMBCs; (vii)CD21+CD272 MBC (CD272 MBC) and (viii)cNs; and (ix)CD212CD272 atypical

MBCs (atypMBC) and (x)dnNs.(D) http://www.jimmunol.org/ Proportions of individual B cell subsets within total CD19+ Bcellsat baseline (C-1). (E) PBMCs from healthy, malaria-naive volunteers (n = 10) were analyzed by flow cytometry to determine surface expression of CD86, CCR6, CXCR5, and CD24 on cN B cells, cMBCs, and atypMBCs. Data are depicted as whisker box by guest on September 29, 2021 plots, with boxes indicating the IQR and whiskers the min/max values. Representative flow cytometry plots are shown for FcRL4 expression on (F) total tonsil B cells as a positive staining control and (G) peripheral blood B cell subsets in healthy, malaria-naive donors (n = 11) before (C-1) or after (C+35) CHMI. FcRL4+ cells were analyzed as proportion of (H)totalCD19+ Bcells or (I) within individual B cell subsets in n =11TS+ volunteers. (H and I) Dots depict individual donors. (H) Error bars show the median and IQR. (I) Asterisks show significant differences compared with C-1 by one-way ANOVA with Dunnett’s post hoc test (*p , 0.05, ***p , 0.001).

their change in proportion at DT+3 (Spearman r = 20.33, p = BAFF-R expression levels inversely correlated with DT+3 plasma 0.0004): B cell subsets such as PBs and atypMBCs that were in- BAFF concentrations (Pearson: r = 20.63, p = 0.04; Fig. 5F), creased showed very low BAFF-R expression at C-1, whereas B cell suggesting a negative impact of high plasma BAFF levels on subsets (nsMBCs and cMBCs) that were decreased the most had the BAFF-R expression. Expression levels of the two other BAFF highest baseline BAFF-R levels (Fig. 5C). receptors, TACI and BCMA, however, remained unaltered by During acute infection (DT and DT+3), B cell BAFF-R ex- CHMI on all B cell subsets, except cMBCs, for which we ob- pression was strongly reduced (Fig. 5D), particularly on B cell served a slight increase at DT+3 (both p , 0.01 compared with subsets with high baseline BAFF-R levels (Fig. 5E). DT+3 B cell C-1; data not shown). The Journal of Immunology 3725 Downloaded from http://www.jimmunol.org/ by guest on September 29, 2021

FIGURE 4. Proliferative response of B cell subsets during CHMI. Ki67 expression by individual B cell subsets was determined by flow cytometry of PBMCs collected before CHMI (C-1) and during liver (C+5) and developing blood stage (C+9), immediately before (DT) and 3 d after treatment (DT+3) and after parasite clearance (C+35, C+140). (A) Flow cytometry plots showing Ki67 gating in TBCs, cMBCs, and atypMBCs. (B) Data are expressed as percentage of Ki67+ cells within each individual B cell subset. Dots depict individual TS+ donors (n = 15); error bars depict the median and IQR. Asterisks show significant differences compared with C-1 by one-way ANOVA with Dunnett’s post hoc test (*p , 0.05, **p , 0.01, ***p , 0.001). (C) The fold change in the percentage of Ki67+ cells within individual MBC subsets at DT+3 was compared with C-1. Dots depict individual TS+ donors (n = 15); error bars denote the median and IQR. Asterisks show significant differences between MBC subsets by one-way ANOVAwith Bonferroni post hoc test (***p , 0.001). Relationships between atypMBC proliferation at DT+3 with (D) peak parasitemia, (E) DT+3 plasma BAFF levels, and (F) peak IFN-g in TS+ donors (n = 15) were analyzed by nonparametric Spearman correlation. 3726 BAFF AND B CELL SUBSET ACTIVATION IN HUMAN MALARIA Downloaded from http://www.jimmunol.org/

FIGURE 5. BAFF-R expression and its association with altered B cell subset proportions during CHMI. Flow cytometry was conducted on PBMCs collected before, during, and after CHMI. B cell subsets were analyzed as percentage of total viable CD19+ B cells, and their fold change in proportion compared with C-1 was calculated for (A)DT+3and(B) C+35. Data are depicted as whisker box plots, indicating median, IQR, and min/max values of n =15TS+ donors. Asterisks show significant differences compared with 1 (no change, dashed line) as tested by one-sample t test. BAFF-R levels on (C and E) individual B cell subsets and (D) total B cells were determined by flow cytometry analysis of PBMC samples from n =11TS+ donors and are expressed as median fluorescence intensity (MFI). (C) The fold change in the proportion of each individual B cell subset on DT+3 (compared with C-1) plotted against baseline (C-1) BAFF-R levels, analyzed by by guest on September 29, 2021 nonparametric Spearman correlation. Small gray dots depict all individual B cell subsets from each individual donor, whereas large black dots represent the median (of n =11TS+ donors) fold change in subset proportion and BAFF-R expression for each of the B cell subsets: (i)PBs,(ii) TBCs, (iii) actMBCs, (iv) actNs, (v) cMBCs, (vi) nsMBCs, (vii)CD272 MBCs, (viii)cNs,(ix) atypMBC, and (x)dnNs.(D) Data for total B cells are depicted for individual donors (dots); error bars show the median and IQR. Asterisks show significant differences compared with C-1 by one-way ANOVA with Dunnett’s post hoc test. (E)Datafor individual B cell subsets are shown for C-1 (white) and DT+3 (gray), depicted as whisker box plots, indicating median, IQR, and min/max values of n =11TS+ donors. The dashed line in (D)and(E) indicates median BAFF-R expression levels on CD192 lymphocytes. Asterisks show significant differences compared with C-1 by two-way ANOVAwith Bonferroni post hoc test. (F) The relationship between the DT+3 plasma BAFF levels and median B cell BAFF-R expression levels on DT+3 was determined by Pearson correlation analysis. *p , 0.05, **p , 0.01, ***p , 0.001.

Discussion first time, to our knowledge, that in vivo, malaria infection also In this study, we investigated the kinetics and source of P. falci- results in increased expression of the membrane-bound form of parum–induced BAFF, and its association with B cell subset ac- BAFF on various monocyte populations, as well as on myeloid tivation and modulation of the composition of the human B cell BDCA-1 DCs up to 3 wk after resolved infection. Myeloid cells compartment during the very early stages of malaria infection. expressing BAFF can act on B cells in two manners: directly by Within 3 d after peak parasitemia and antimalaria treatment, we cross-linking the MBC BAFF receptor TACI via surface-expressed found a significant increase in both surface BAFF expression on BAFF and indirectly by enzymatic release of soluble BAFF with various APC subsets and plasma BAFF concentrations, as well as high affinity for BAFF-R (33). The increase in surface BAFF+ strong proliferative responses and altered proportions of nu- BDCA-1 DCs observed in this study stands in contrast with find- merous B cell subsets. Both BAFF induction and B cell subset ings in a murine malaria model showing a loss of surface BAFF- proliferation directly correlated with peak parasitemia. For expressing myeloid DCs from the spleen (and as a result, reduced CD212CD272 B cell subsets (atypMBC and dnN), proliferation survival of MBCs) during acute infection (24). Because we only correlated with plasma BAFF and IFN-g levels, and for B cell subsets examined circulating, but not lymphoid tissue-resident APCs, we with particularly high or baseline BAFF-R levels, these were in- cannot exclude that a similar depletion of BAFF-expressing DCs versely associated with their changeinproportionafterCHMI. might also be observed in these organs after CHMI, possibly be- Increased plasma BAFF during CHMI is in line with previous cause of transition to the circulation. Our data are reminiscent of findings in naturally exposed individuals, showing elevated BAFF in findings in human HIV patients (34), who also show increased plasma from acutely malaria-infected children (25) and in placental levels of monocyte- and DC-expressed membrane BAFF, plasma tissue from malaria-infected pregnant women (32). In vitro, both BAFF, and alterations/activation in the B cell compartment sim- malarial hemozoin and soluble parasite extract are capable of in- ilar to what is observed in malaria (35–40). In as how far in either ducing BAFF release from monocytes (23). We now show for the setting increases in APC surface-expressed BAFF via TACI, and The Journal of Immunology 3727 soluble BAFF via BAFF-R, indeed contribute to activating B cells, subsets correlated with the degree of parasite exposure. Although however, remains to be established. The monocyte subset showing Ag-specific expansion cannot be excluded, this is unlikely true for the highest proportion of BAFF expression 3 d after drug treatment the majority of cells, seeing the large proportion of responding was CD14low/2CD16+ monocytes. This subset is one of two “non- cells across subsets after a primary exposure. Moreover, whereas classical” CD16+ monocyte subsets that are known to be increased atypMBCs have been shown to contain a similar proportion of upon immune activation, as also found for P. falciparum malaria (41, malaria Ag-specific cells as cMBCs (16), any circulating prolifer- 42). CD14low/2 monocytes have proinflammatory properties (includ- ating B cells seen as early as 3 d after drug treatment, and thus only ing TNF-a secretion), whereas CD14+CD16+ intermediate monocytes 5 d after blood-stage parasites became detectable by PCR, are un- secrete the anti-inflammatory cytokine IL-10 (43, 44). Significantly likely to stem from a memory-generating germinal center re- higher BAFF expression on the CD14low/2 subset as found in our sponse, which would still be ongoing at this time point. Instead, any volunteers during CHMI is consistent with this functional division. changes in cell proportion or proliferation seen already at the peak Parasite-induced BAFF secretion from monocytes might be of infection are more likely related to generalized immune activa- further augmented by IFN-g derived from innate or adaptive im- tion during acute infection rather than Ag-specific activation and mune cell activation (22). Although previous experiments were the generation of memory responses. Whether this is mediated by performed with highly enriched monocytes/B cell cocultures, it cytokines such as IFN-g or BAFF (suggested by the correlation could not be definitively concluded that this process was entirely between plasma levels of those cytokines and atypMBC and dnN T cell independent (23). Indeed, we also found only a weak and proliferation) (23, 25) or by direct parasite–B cell interaction (10, not significant relationship between peak parasitemia and plasma 13, 14) remains to be established. One possible consequence of

BAFF levels, indicating that in vivo, this direct effect may be of generalized B cell activation could be hypergammaglobulinemia Downloaded from lesser importance. Instead, peak plasma BAFF levels correlated (1); however, we did not detect any increase in plasma IgG during with peak plasma IFN-g levels, an important factor in mediating CHMI, nor does this necessarily occur in the ﬁeld (25). BAFF release from myeloid cells (22), which preceded them by Next to B cell subset proliferation during acute infection, we also 2 d, and is in line with previous ﬁndings (25). This strongly suggests observed proliferative responses as late as 35 d postinfection (and that P. falciparum–driven immune activation is an important con- thus 3 wk after parasite clearance) in cNs, activated and dnNs, as

tributing factor in parasite-mediated BAFF secretion. Peak IFN-g well as nsMBCs and classical MBCs. The majority of these subsets http://www.jimmunol.org/ levels were only reached 1 and 3 d after initiation of treatment, also showed reduced proportions in the B cell compartment 3 d likely because of the fact that release of P. falciparum material after drug treatment. Although these reduced proportions are likely upon mass parasite killing further enhances immune activation. due to redistribution of B cells from the circulation, for instance, to The 2-d delay between peak plasma IFN-g and BAFF concen- secondary lymphoid organs such as the spleen, we cannot exclude trations can be explained with the time it takes for APCs to get that there might also be a loss in B cells, for example, due to activated by IFN-g and initiate sufficient surface BAFF protein apoptosis (47, 48). An explanation for these late proliferative re- expression (which also peaked 2 d later) and cleavage, and is sponses might therefore be either: 1) the release of elsewhere re- consistent with in vitro studies showing that BAFF release from cruited activated cells back into the circulation, or 2) a physiological IFN-g–treated monocytes is only minimal after 24 h, peaks after counterreaction to replenish the apoptosis-diminished B cell pool. by guest on September 29, 2021 48 h, and surface expression continues to increase until 72 h (23). For atypMBCs, as well as their nonswitched dnN counterparts, Concomitantly with increasing plasma BAFF levels, we ob- their particularly strong proliferative response correlated not only served reduced expression of BAFF-R on B cells, corroborating with peak parasitemia, but also plasma BAFF levels, a relationship findings in acutely malaria-infected children (25), HIV infection, not observed for other B cell subsets. This may appear counter- 2 Sjo¨gren’s syndrome, and systemic lupus erythematosus (SLE) (34, intuitive, because CD21 B cells express lower levels of BAFF-R 35, 38). At least in autoimmune diseases, this downregulation is not than other B cell subsets. A possible explanation is that BAFF may transcriptionally regulated (38). Instead, physiological regulation be a costimulating factor rather than a driving force of prolifera- by receptor internalization or shedding, but also partial masking by tion (49–51). If CD212CD272 naive and MBCs are more recep- BAFF binding may be the explanation. Two other members of the tive than other B cell subsets to BAFF-costimulated, proliferation- BAFF receptor family, TACI and BCMA, which have low or no driving stimuli, low BAFF-R expression would not necessarily be affinity for soluble BAFF (33), did show no downregulation during a limiting factor. In this scenario, factors other than BAFF should acute infection. also correlate with CD212CD272 B cell proliferation. This is true Despite very low parasite densities during CHMI, we observed for peak IFN-g levels and may further extend to other B cell a number of profound, albeit temporary, changes in B cell com- stimuli not assessed in this study. To establish whether there is position either during or immediately after the blood stage of indeed a causal link between the expansion of CD212CD272 CHMI. These included increased proportions of TBCs, atypMBCs, B cells and P.falciparum–induced cytokines, and to unravel potentially and PBs, as well as the reduction in marginal zonelike nsMBCs synergistic effects of BAFF, IFN-g, and other cytokines or stimuli, (CD21+CD27+IgD+), and are consistent with previous observations future mechanistic in vitro studies are needed. Of note, in other diseases in persistently exposed or acutely infected individuals in malaria- with elevated plasma BAFF, including HIV and SLE, atypMBCs or endemic areas (15, 17–20, 45, 46). A number of factors can influ- phenotypically similar populations are also expanded (34, 38–40). ence the proportions of individual subsets within the peripheral This study provides, to our knowledge, the first direct link be- blood B cell compartment, including redistribution between blood tween malaria infection and increased proportions of atypMBCs. and tissues, cell death or proliferation. Our data demonstrate that The temporary nature of this increase is in line with decreasing different B cell subsets respond with different proliferation kinetics proportions of these cells in individuals from malaria-endemic areas to P. falciparum exposure. Proliferative responses during acute in- after prolonged nonexposure (52). The fact that atypMBCs at fection are likely related to either direct interaction with blood- baseline showed only little proliferation, but increased this after stage parasite products or as a bystander effect of P. falciparum– parasite exposure suggests that these cells may not be exhausted per induced immune activation and release of soluble mediators, both se. This is also in line with a sizable proportion of atypMBCs of which would be driven by the level of parasitemia encountered showing proliferation in vivo in naturally exposed individuals (16). during infection. Indeed, proliferative responses of several B cell The notion of atypMBC exhaustion stems from a failed in vitro 3728 BAFF AND B CELL SUBSET ACTIVATION IN HUMAN MALARIA attempt to differentiate them into Ab-producing cells (19). Future baseline BAFF-R levels on individual subsets and their propor- studies will need to show whether activation of atypMBCs in vivo tion within the B cell compartment on DT+3, that is, the time of can result in the generation of Ab-producing PBs after all, as sug- highest plasma BAFF levels. This phenomenon might be further gested previously (16), or whether atypMBCs may have alternative exacerbated by differential expression of the corresponding che- functional properties upon activation. mokine receptors by different B cell subsets. AtypMBCs and PBs, Although CHMI-activated CD212CD272 atypMBCs closely for instance, express low levels of CCR7, CXCR4, and CXCR5 resemble the phenotype of atypMBCs in viremic HIV patients and (data not shown) (19, 40). individuals from highly malaria-endemic areas in regard to CD21, In summary, by analyzing longitudinal samples collected during CD27, CD86, CCR6, CXCR5, and CD24 expression (19, 40), they CHMI, we were able to extract potentially causal relationships be- lack expression of FcRL4. FcRL4 is an IgA-binding inhibitory tween parasite exposure and B cell activation and modulation during receptor (53) that impairs BCR signaling but augments TLR malaria. We show that plasma BAFF levels are increased in the responses (54, 55). IgD2CD272 cells (of which IgD2CD212 context of P. falciparum–induced immune activation and may be at CD272 MBCs are a subpopulation) in healthy individuals or in those least partially derived from monocyte subsets and BDCA-1+ DCs, with SLE also lack FcRL4 expression (39). FcRL4 expression was which increase membrane BAFF expression during CHMI. B cell induced by CHMI 2 wk after parasite clearance, but this induction subsets were activated and proliferated with distinct kinetics, and was temporary and occurred not only on atypMBCs but also nu- these responses depended on peak parasitemia levels during CHMI. merous B cell subsets. It is thus possible that atypMBCs during Finally, our data suggest that parasite-induced BAFF elevation may CHMI may functionally differ from those found in malaria-endemic contribute to orchestrating the changes in the B cell compartment by areas. However, even in frequently malaria-exposed individuals, two distinct mechanisms, namely, facilitating B cell subset prolifer- Downloaded from FcRL4 expression varies (19, 52). Future studies will be necessary to ation and redistribution. This phenomenon is likely not malaria in- determine whether sustained, high FcRL4 expression is a necessary trinsic but may be a common pathway of B cell modulation, because or specific feature of atypMBCs (the function of which is still un- malaria shares several features including polyclonal B cell activation known), may only be induced at high levels upon chronic immune and specific alterations in the phenotype and composition of the activation, and what the triggers for this induction are. Recently, the peripheral B cell pool with other diseases that are also characterized

HIV envelope protein gp120 has been shown to trigger FcRL4 ex- by excessive plasma BAFF levels, including HIV infection and SLE. http://www.jimmunol.org/ pression in primary human B cells by direct interaction with B cell– expressed a4b7 and subsequent induction of TGF-b (56). Whether Acknowledgments P. falciparum similarly expresses FcRL4-inducing molecules re- We thank the trial volunteers and the staff from the Clinical Research Centre mains to be established. Of note, FcRL4 expression by gp120 in vitro Nijmegen, the Radboud University Medical Center, and the Sanaria was increased within 24 h, whereas we only observed FcRL4 ex- Manufacturing Team, all of whom made this study possible. pression 3 wk after peak parasitemia and drug treatment–mediated parasite clearance. We cannot exclude, however, that FcRL4 ex- Disclosures pression might have already peaked much earlier and remained S.L.H. is Chief Executive and Scientific Officer at Sanaria Inc., which manu- stable for a prolonged period, because no PBMC samples were factured PfSPZ Challenge, and does thus have a potential conflict of interest. by guest on September 29, 2021 collected between DT+3 and C+35. To our knowledge, this is the first study to investigate changes in B cell FcRL4 expression in vivo References post an acute infection or immune activation, and follow-up studies 1. Cohen, S., I. A. McGregor, and S. Carrington. 1961. Gamma-globulin and ac- are needed to further investigate the kinetics of FcRL4 expression quired immunity to human malaria. Nature 192: 733–737. 2. Langhorne, J., F. M. Ndungu, A. M. Sponaas, and K. Marsh. 2008. Immunity to postinfection. The temporary induction of inhibitory FcRL4 ex- malaria: more questions than answers. Nat. Immunol. 9: 725–732. pression might be yet another facet of negative immune regulation 3. Struik, S. S., and E. M. Riley. 2004. Does malaria suffer from lack of memory? upon activation. In T cells, this well-known process is mediated by Immunol. Rev. 201: 268–290. 4. Dorfman, J. R., P. Bejon, F. M. Ndungu, J. Langhorne, M. M. Kortok, inhibitory receptors such as PD-1 or CTLA-4 (57), pathways that B. S. Lowe, T. W. Mwangi, T. N. Williams, and K. Marsh. 2005. B cell memory have also been described and contribute to reduced T cell respon- to 3 Plasmodium falciparum blood-stage antigens in a malaria-endemic area. J. siveness in malaria infection (20, 58). Importantly, negative immune Infect. Dis. 191: 1623–1630. 5. Nogaro, S. I., J. C. Hafalla, B. Walther, E. J. Remarque, K. K. Tetteh, regulation of T cells not only leads to what is described as “ex- D. J. Conway, E. M. Riley, and M. Walther. 2011. The breadth, but not the haustion,” but is also an important factor in preventing immune magnitude, of circulating memory B cell responses to P. falciparum increases with age/exposure in an area of low transmission. PLoS ONE 6: e25582. pathology (59) and in mediating contraction of immune responses 6. Weiss, G. E., B. Traore, K. Kayentao, A. Ongoiba, S. Doumbo, D. Doumtabe, when a pathogen is cleared (60). In analogy, temporary induction of Y. Kone, S. Dia, A. Guindo, A. Traore, et al. 2010. The Plasmodium falciparum- FcRL4 on activated B cells across all B cell subsets post malaria specific human memory B cell compartment expands gradually with repeated malaria infections. PLoS Pathog. 6: e1000912. infection may be a physiological response and simply serve to bring 7. Wipasa, J., C. Suphavilai, L. C. Okell, J. Cook, P. H. Corran, K. Thaikla, these cells back to the steady-state. W. Liewsaree, E. M. Riley, and J. C. Hafalla. 2010. Long-lived antibody and Despite partially overlapping kinetics, we found no correlation B cell memory responses to the human malaria parasites, Plasmodium falciparum and Plasmodium vivax. PLoS Pathog. 6: e1000770. between B cell subset proliferation and the change in their indi- 8. Ferreira, M. U., M. da Silva Nunes, and G. Wunderlich. 2004. Antigenic diversity vidual proportions, suggesting selective B cell subset redistribution and immune evasion by malaria parasites. Clin. Diagn. Lab. Immunol. 11: 987–995. 9. Scholzen, A., and R. W. Sauerwein. 2013. How malaria modulates memory: as a more important parameter in the altered composition of the activation and dysregulation of B cells in Plasmodium infection. Trends Para- peripheral blood B cell compartment during malaria. BAFF has sitol. 29: 252–262. previously been shown to enhance B cell chemotaxis to the CCR7, 10. Simone, O., M. T. Bejarano, S. K. Pierce, S. Antonaci, M. Wahlgren, M. Troye- Blomberg, and D. Donati. 2011. 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Supplementary Figure S1

Figure S1. Surface BAFF expression on DC and monocyte populations of thick-smear negative, PfSPZ-exposed volunteers

(A) Median proportions of BAFF+ APC subsets were analyzed within viable PBMCs on C-1,

DT and DT+3 in PfSPZ-exposed that remained TS- and were presumptively drug-treated on day C+21 (n=3). (B) Percentages of BAFF+ cells within classical monocytes (class mono;

CD14+CD16-), intermediate monocytes (interm mono; CD14+CD16+), inflammatory monocytes (inflamm mono; CD14-CD16+) and CD14-CD16- BDCA-1+ DCs were determined prior to (C-1) and 9 days after CHMI (C+9), immediately prior to (DT; C+21) and three days after treatment (DT+3; C+24), and are shown as individual data, lines indicate medians and error bars the range. Supplementary Figure S2

Figure S2. Proliferative response of B-cell subsets in thick-smear negative, PfSPZ- exposed volunteers

Ki67 expression by individual B-cell subsets was determined by flow cytometry analysis of sequential PBMC samples collected prior to CHMI (C-1) and during liver (C+5) and developing blood-stage (C+9), immediately prior to (DT) and three days after treatment

(DT+3) and one and four months later (C+35, C+140). Data are expressed as percentage of

Ki67+ cells within each individual B-cell subset. Dots depict individual PfSPZ-exposed volunteers that remained TS- and were presumptively drug-treated on day C+21 (n=3). The line shows the median and error bars the range. Supplementary Figure S3

Figure S3. Kinetics of B-cell subset proportions during CHMI in thick-smear positive and thick-smear negative PfSPZ-exposed volunteers

Flow cytometry analysis was conducted on sequential PBMC samples collected prior to

CHMI by intradermal injection of PfSpZ (C-1), immediately prior to (DT) and three days after treatment (DT+3) and 35 and 140 days post CHMI (C+35, C+140). B-cell subsets were analyzed as percentage of total viable CD19+ B-cells. Data are depicted as whisker-box-plots, boxes indicating the IQR and whiskers the min/max values of n=15 TS+ donors (grey lines, left) and n=3 volunteers that remained TS- until 21 days after PfSPZ challenge (red lines, right). Red arrows indicate the time points at which TS+ volunteers showed significant changes in the proportions of individual B-cell subsets (compared to baseline, C-1) as assessed by one-way ANOVA with Dunnett’s post-hoc test.