Cutting Edge: Plasmodium falciparum Induces Trained Innate Immunity

Jacob E. Schrum, Juliet N. Crabtree, Katherine R. Dobbs, Michael C. Kiritsy, George W. Reed, Ricardo T. Gazzinelli, Mihai G. Netea, James W. Kazura, Arlene E. Dent, Katherine A. Fitzgerald and Douglas T. Golenbock
J Immunol February 15, 2018, 200 (4) 1243-1248; DOI: https://doi.org/10.4049/jimmunol.1701010

Abstract

Malarial infection in naive individuals induces a robust innate immune response. In the recently described model of innate immune memory, an initial stimulus primes the innate immune system to either hyperrespond (termed training) or hyporespond (tolerance) to subsequent immune challenge. Previous work in both mice and humans demonstrated that infection with malaria can both serve as a priming stimulus and promote tolerance to subsequent infection. In this study, we demonstrate that initial stimulation with Plasmodium falciparum–infected RBCs or the malaria crystal hemozoin induced human adherent PBMCs to hyperrespond to subsequent ligation of TLR2. This hyperresponsiveness correlated with increased H3K4me3 at important immunometabolic promoters, and these epigenetic modifications were also seen in Kenyan children naturally infected with malaria. However, the use of epigenetic and metabolic inhibitors indicated that the induction of trained immunity by malaria and its ligands may occur via a previously unrecognized mechanism(s).

Introduction

A hallmark of malaria is robust proinflammatory cytokine production induced by widespread innate immune activation. Multiple innate immune receptors are involved in the recognition of Plasmodium-infected RBCs (iRBCs) and other malarial ligands (reviewed in Ref. 1). For example, the malaria crystal hemozoin (Hz), which becomes coated with Plasmodium-derived pathogen-associated molecular patterns including genomic DNA, activates TLR9 in the phagolysosome (2). Hz crystals can also induce phagolysosomal rupture, resulting in the activation of the nucleotide-binding domain, leucine-rich repeat−containing, pyrin domain containing 3 inflammasome as well as deliver Plasmodium DNA to the cytosol, where it is recognized by cytosolic DNA receptors including those that sense AT-rich stem-loop structures in Plasmodium genomes (3, 4). This innate immune response, although beneficial through limiting parasitemia and assisting in the activation of adaptive immunity, induces the systemic symptoms of fever, nausea, and malaise. Proinflammatory cytokinemia has been implicated in the development of cerebral malaria (5).

Multiple studies have demonstrated memory phenotypes in innate immune cells (6–8). In the prevailing model of innate immune memory, an initial stimulus primes the innate immune system, which induces epigenetic and metabolic changes that result in an increased or decreased response—termed training or tolerance, respectively—to a subsequent challenge occurring days to months later (9). Malarial infection serves as a robust priming stimulus, as whole blood samples from experimentally infected individuals and PBMCs from patients with acute febrile disease are hyperresponsive to ex vivo TLR ligand stimulation—a phenotype that can be recapitulated in vitro (10, 11).

Malaria can induce tolerance to subsequent infection or other immune challenge (reviewed in Ref. 12). The pyrogenic threshold, i.e., the level of parasitemia required to provoke fever, was higher for individuals after reinfection compared with initial infection (13). In an area of Mali with seasonal malaria transmission, nearly 50% of healthy individuals had detectable parasitemia at the end of the dry season in the absence of symptoms (14). Individuals infected with malaria as fever therapy for neurosyphilis and then challenged 2–3 d post–final defervescence with heat-killed Salmonella exhibited depressed febrile responses (15). Tolerance and training appear to be two ends of the same spectrum, as LPS and other ligands induce tolerance at higher concentrations but produce training at much lower concentrations (16). We hypothesized that malarial stimulation would also induce trained immunity, and set about to evaluate this possibility directly using human PBMCs.

Materials and Methods

Malaria cultures and iRBC/Hz isolation

P. falciparum clone 3D7 iRBCs were passed through a magnetic field resulting in enrichment consistently ≥90% iRBCs. Hz was isolated by passing malaria culture supernatants through a magnetic field as described previously (2).

Human subject use

Human subject use was approved by the University of Massachusetts Medical School Institutional Review Board (H-10368), University Hospitals Cleveland Medical Center Institutional Review Board (06-11-22), and the Kenya Medical Research Institute Ethical Review Committee (SSC 2207). Samples from Kenyan children aged 1–10 y with febrile malaria were obtained from Chulaimbo Sub-County Hospital, Kisumu. Venous blood was obtained at presentation and 6 wk after curative treatment. Individuals with submicroscopic infections detected at recovery visits by PCR (17) were excluded from further analysis. PBMCs from Kenyan children and healthy adult North American controls (three male, three female, aged 33–68 y) were cryopreserved (18). Monocytes were negatively selected from thawed PBMCs using a Pan Monocyte Isolation Kit (Miltenyi Biotec).

Human adherent PBMC isolation and stimulation

PBMCs from healthy donors were plated at 5 × 105 cells per well (in 96-well round-bottom plates) or 10 × 106 cells per well (in 6- or 12-well flat-bottom plates) and incubated at 37°C for ≥1 h. Nonadherent cells were removed by washing 3× with PBS. Adherent PBMCs were then incubated in RPMI 1640 supplemented with 10% human serum (RPMI+) and stimulated for 24 h. Stimulation with iRBCs or Hz did not decrease cell number or viability (data not shown). Cells were washed with PBS and allowed to rest in RPMI+ for 3 d. Cells were then harvested for chromatin immunoprecipitation (ChIP) analysis or stimulated with Pam3CSK4 (InvivoGen) for 4–24 h. Stimulated cells were harvested for mRNA analysis or supernatants were frozen at −20°C for subsequent cytokine measurement.

Cytokine measurement

TNF-α and IL-6 ELISA kits were from R&D Systems. A mouse thymic stroma tetrazolium dye assay [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt] (Promega) was used to determine relative cell number poststimulation. Cytokine values were normalized to cell number.

mRNA expression

Total RNA was extracted using the RNeasy Mini Kit (Qiagen). cDNA synthesis and quantitative PCR (qPCR) were performed using an iScript cDNA synthesis kit and iQ SYBR Green supermix (both Bio-Rad). The following primer pairs were used: ACTB, forward (FW) 5′-TGAAGTCTGACGTGGACATC-3′, reverse (RV) 5′-ACTCGTCATACTCCTGCTTG-3′; GAPDH, FW 5′-GAGTCAACGGATTTGGTCGT-3′, RV 5′-TTGATTTTGGAGGGATCTCG-3′; IL-6, FW 5′-ACTCACCTCTTCAGAACGAATTG-3′, RV 5′-CCATCTTTGGAAGGTTCAGGTTG-3′; TNF, FW 5′-TGCTTGTTCCTCAGCCTCTT-3′, RV 5′-GGTTTGCTACAACATGGGCT-3′. Cycle threshold values were normalized to ACTB and GAPDH expression and analyzed using Bio-Rad software. NanoString analysis was performed using the nCounter Human Inflammation v2 Codeset, which simultaneously measures mRNA expression levels of 249 inflammation-related genes, according to the manufacturer’s instructions (NanoString Technologies).

Neutralizing Abs and inhibitors

Mouse anti-human IFN-γ IgG1 and IgG1 isotype control were from BioLegend; 5′-deoxy-5′-(methylthio)adenosine (MTA) and rapamycin were from Sigma.

ChIP analysis

Briefly, cells were fixed in 1% formaldehyde for 10 min and quenched with glycine. Chromatin was sonicated from these cells using a Bioruptor UCD-300 (Diagenode) for four cycles of 10× (30 s ON, 30 s OFF) on the HIGH setting. Chromatin precipitation was performed using rabbit anti-human H3K4me3 IgG Ab (Diagenode) as described previously (7). DNA was then quantified using qPCR with the following primer pairs: GAPDH, FW 5′-ATCCAAGCGTGTAAGGGTCC-3′, RV 5′-GACTGAGATTGGCCCGATGG-3′; IL-6, FW 5′-AGCTCTATCTCCCCTCCAGG-3′, RV 5′-ACACCCCTCCCTCACACAG-3′; MTOR, FW 5′-ATAAAGAGCGCTAGCCCGAA-3′, RV 5′-GACCCCTCCCGGTGTAATTC-3′; TNF, FW 5′-CAGGCAGGTTCTCTTCCTCT-3′, RV 5′-GCTTTCAGTGCTCATGGTGT-3′. For all ChIP experiments, qPCR values were normalized as percent recovery of the input DNA.

Statistical analysis

Statistical comparisons were made between the indicated condition and control-trained cells (RPMI+). Multiple analyses were carried out for experiments with multiple replicates for an individual donor performed on different days; for the experiments represented in Fig. 1B and 1C: a mixed model regression analysis, a Wilcoxon signed-rank test with clustering (analysis at the replicate level accounting for correlation of data within donor), a Wilcoxon signed-rank test using one averaged value per donor (mean of all replicates), and a paired t test using one averaged value per donor. All four tests provided nearly identical hypothesis decisions (α = 0.05), so paired t tests using one value per donor was used for all other experiments. When ratios to controls were compared, one-sample t tests [H0 log(ratio) = 0] were performed on log-transformed ratio values.

Results

Training with malaria parasites or ligands induces increased proinflammatory and decreased anti-inflammatory cytokine production in response to secondary TLR stimulation

Adherent PBMCs from healthy donors were stimulated with RPMI+ alone, P. falciparum iRBCs, uninfected RBCs (uRBCs), or Hz for 24 h. The cells were washed and allowed to rest in RPMI+ for 3 d. At this point, the cells were either harvested for ChIP analysis or stimulated with the TLR2 ligand Pam3CSK4 for 4–24 h to measure cytokine production (Fig. 1A). Training with either 1 × 105 or 1 × 106 iRBCs, but not uRBCs, induced increased production of proinflammatory cytokines TNF-α and IL-6 but decreased production of the anti-inflammatory cytokine IL-10 24 h after second stimulation with Pam3CSK4 as compared with controls (Fig. 1B, Supplemental Fig. 1). Similarly, primary stimulation with Hz induced a similar pattern of training following Pam3CSK4 stimulation (Fig. 1C).

FIGURE 1.
FIGURE 1.

P. falciparum iRBCs and Hz induce trained immunity. (A) Schematic of trained immunity assay. Adherent PBMCs were treated with media (RPMI+), iRBCs, uRBCs, or Hz for 24 h, and then washed. After 3 d rest, cells were harvested for ChIP or challenged with Pam3CSK4 (10 μg/ml) for 4–24 h. (B and C) TNF-α, IL-6, and IL-10 ELISA measurements of supernatants from adherent PBMCs trained with iRBCs (B) or Hz (C), rested for 3 d, then challenged with Pam3CSK4 for 24 h. Bars represent mean ± SEM for three (IL-10) or eight (TNF-α, IL-6) donors (all comparisons to RPMI+ trained, *p < 0.05, **p < 0.01, ***p < 0.001, paired t test).

Malarial training has wide-ranging effects on the inflammatory transcriptome post-TLR second stimulus

The prevailing model of trained immunity is that increased responsiveness to secondary stimuli results from epigenetic remodeling that increases chromatin accessibility, and that increased proinflammatory gene transcription follows secondary stimulation. In our in vitro model, stimulation of iRBC- or Hz-trained adherent PBMCs with Pam3CSK4 increased transcription at the TNF locus as compared with cells trained with media alone (Fig. 2A). Surprisingly, malarial training did not lead to increased IL-6 transcription after 4 h Pam3CSK4 s stimulation, although there was a trend toward increased IL-6 transcription in iRBC- and Hz-trained cells after 12 h Pam3CSK4 stimulation (Fig. 2B). To determine if malarial training has a more global effect on inflammatory gene expression, we performed a NanoString analysis on RNA harvested from trained cells given Pam3CSK4 as a secondary stimulus. For each gene, we normalized the iRBC-, uRBC-, or Hz-trained transcript count to the control-trained transcript count at each secondary stimulus time point. These normalized ratios are displayed as a heatmap (Fig. 2C), demonstrating that although uRBC training had little effect on the inflammatory transcriptome, both iRBC and Hz training had wide-ranging and similar effects. The majority of transcripts could be classified into the following cohorts: globally upregulated (C1), upregulated after 4 h Pam3CSK4 stimulation (C2), upregulated after 12 h Pam3CSK4 stimulation (C3), downregulated after 12 h Pam3CSK4 stimulation (C4), downregulated after 4 h Pam3CSK4 stimulation (C5), or globally downregulated (C6). A subset of genes previously implicated in malarial pathogenesis and/or trained immunity are listed for each cohort (19–23), and a complete list of transcripts in each cohort can be found in Supplemental Table I.

FIGURE 2.
FIGURE 2.

Malaria-induced training has wide-ranging effects on the transcriptional response to subsequent challenge. (A and B) mRNA was harvested from adherent PBMCs trained with iRBCs or Hz, rested for 3 d, and challenged with Pam3CSK4 for 4 or 12 h. Levels of TNF (A) and IL-6 (B) relative to RPMI+ trained cells are shown. Bars represent mean ± SEM for eight (4 h Pam3CSK4) or three (12 h Pam3CSK4) donors (**p < 0.01, paired t test). (C) Gene expression from cells treated as in (A) and (B) was quantified using NanoString technology. Expression counts are represented as log2 fold change compared with control-trained cells using hierarchical clustering. Each row represents one gene. A subset of the total genes measured is listed after each cohort. Values shown are the means of two independent experiments from one of the donors in (A) and (B).

Malarial training does not depend on IFN-γ signaling

IFN-γ was one of the cytokines highly upregulated by malarial training. NK cells produce IFN-γ starting ∼6 h post–iRBC stimulation (24, 25). In a murine malaria model, malarial priming was IFN-γ dependent (11), and IFN-γ was required for Candida albicans–induced trained immunity (26). We used a neutralizing Ab against IFN-γ to test the role of this cytokine in malaria-induced training. Treatment of adherent PBMCs with anti–IFN-γ IgG during the 24 h first stimulation did not inhibit iRBC- or Hz-induced training (Fig. 3). We conclude that IFN-γ signaling is dispensable for malarial training.

FIGURE 3.
FIGURE 3.

Malaria-induced training is not inhibited by cotreatment with anti–IFN-γ neutralizing mAb. TNF-α and IL-6 ELISA measurements of supernatants from adherent PBMCs trained with iRBCs or Hz for 24 h, rested for 3 d, and challenged with Pam3CSK4 for 24 h. Cells were treated with control IgG or neutralizing Ab during the 24 h training. Bars represent mean ± SEM for two donors (all comparisons to control IgG conditions were not significant, paired t test).

Differential epigenetic and metabolic regulation of malaria-induced trained immunity

Trained immunity is believed to be the result of intracellular metabolic shifts leading to changes in epigenetic regulation of immune-related genetic loci (9). To determine the role of naturally acquired malaria on epigenetic remodeling, we performed H3K4me3 ChIP on monocytes isolated from Kenyan children with acute febrile malaria, the same children 6 wk after curative antimalarial treatment, and malaria-naive adult North American controls (Fig. 4A). The Pan Monocyte Isolation Kit (Miltenyi) used for this monocyte isolation enriches for both CD14++CD16− and CD14+CD16++ monocytes. Increased H3K4me3 was seen at the TNF, IL-6, MTOR, and GAPDH promoters during acute malaria compared with controls. Increased H3K4me3 levels were unchanged 6 wk after antimalarial treatment. We performed a similar experiment using our in vitro model on adherent PBMCs given a 24 h first stimulation and then rested for 3 d. Increased H3K4me3 was seen at the TNF, PTGS2, and IL-6 promoters after iRBC (but not Hz) training compared with RPMI+ training (Fig. 4B).

FIGURE 4.
FIGURE 4.

Epigenetic and metabolic regulation of malaria-induced training. (A) H3K4me3 ChIP was performed on monocytes from Kenyan children with acute malaria (AM), the same children 6 wk after therapy (6 wk), or adult North American controls (NAM). Bars represent mean ± SEM for five (AM), three (6 wk), or six (NAM) donors (*p < 0.05, Kruskal–Wallis test). (B) H3K4me3 ChIP was performed on adherent PBMCs trained for 24 h and rested for 3 d. Bars represent mean ± SEM for five (RPMI+, iRBC, uRBC) or three (Hz) donors (all comparisons to RPMI+ trained, *p < 0.05, **p < 0.01, paired t test). (C and D) Adherent PBMCs were cotreated with MTA (C), rapamycin (D), or relevant vehicle controls during the 24 h training stimulation. Cells were rested for 3 d and challenged with Pam3CSK4 for 24 h. Cytokine concentrations in supernatants were assessed by ELISA. Bars represent mean ± SEM for three or four donors (all comparisons to no inhibitor conditions and were not significant unless indicated, paired t test). *p < 0.05.

We used the methyltransferase inhibitor MTA as well as the mechanistic target of rapamycin inhibitor, rapamycin, which has been demonstrated to inhibit bacillus Calmette-Guérin–induced training (7) and C. albicans β-glucan–induced training (27), respectively, to investigate the importance of these mechanisms in malaria-induced training. Treatment with 1 mM MTA for the 24 h first stimulation had no effect on iRBC-induced training (Fig. 4C). MTA treatment appeared to inhibit Hz-induced training, although this did not achieve statistical significance due to the relatively small sample size. Treatment with 10 nM rapamycin during the 24 h first stimulation blocked iRBC-induced training as measured by IL-6 protein production but had no effect on malarial training as measured by TNF-α protein levels (Fig. 4D).

Discussion

Malaria is an extraordinarily complicated disease. Individuals from endemic regions of the world have a clinical syndrome that is influenced by age and previous exposure. Children with little or no immunity to malaria are at highest risk for acute febrile disease, which may be complicated by severe sequelae such as cerebral disease (28). This corresponds with our findings that Kenyan children have increased H3K4me3 at promoters relevant to inflammation and immunometabolism both during acute malaria and after curative therapy as compared with healthy North American adult controls. This is especially striking as baseline monocyte H3K4me3 levels are higher in otherwise healthy adults than neonates at both proinflammatory and metabolic promoters (29). Monocytes were chosen for ChIP analysis because enriching for the population of cells that produce the cytokines we measured in our in vitro studies seemed logical. It is worth noting that the t1/2 of monocytes is 1–3 d, suggesting that training almost certainly occurred at the level of myeloid progenitor cells (9). We recognize that these early data using patient specimens were necessary to include in this report, although these data were not conclusive. Long-term approaches to definitively identify training would require following individuals over the course of years (as has been done for bacillus Calmette-Guérin vaccine). These data support our hypothesis that malarial infection serves as a robust priming and training stimulus. Indeed, we predict that malaria-infected children are at risk to hyperrespond to superinfection in ways that might be predicted based on the in vitro responses we observed.

Older children and adults from endemic areas are likely to have experienced multiple episodes of malaria. These individuals will often have detectable parasitemia without symptoms (14). Although the level of parasitemia in these asymptomatic malaria cases is often quite low, some individuals have levels of parasites in their blood that would be incapacitating in the immunologically naive. It is our hypothesis that the differences in outcome in disease between young individuals or even immunologically mature adults who become infected for the first time later in life (e.g., travelers) compared with multiply infected asymptomatic individuals, are due to epigenetic changes at proinflammatory and immunometabolic promoters.

In this work, we report that the malaria parasite and its crystal Hz can induce trained immunity as measured by inflammatory gene expression after a secondary TLR ligand challenge. Although these two stimuli have similar effects on the inflammatory transcriptome post-Pam3CSK4 challenge, the differential regulation of iRBC- and Hz-induced training by known trained immunity inhibitors and differing levels of H3K4me3 at immunometabolic promoters suggests divergent training mechanisms for the two stimuli. One potential explanation for this divergence is that the parasite contains multiple additional ligands with innate immune stimulatory capacity. Although these TLRs use the same signaling cascades and transcription factors as the receptors stimulated by Hz, the balance in signaling between the cascades may be sufficiently diverse to explain these differences.

Rapamycin treatment only inhibited training as measured by IL-6 and not TNF-α, which differs from previous studies on other training stimuli (27, 30). This discrepancy in rapamycin inhibition is not completely surprising given that the TNF and IL-6 loci have different initiation kinetics and epigenetic requirements for transcription (31). However, along with the apparent dispensability of IFN-γ signaling for malaria training, this provides further evidence that both malaria parasites and Hz induce innate immune training by mechanisms that differ from other infectious stimuli. Any hope for immunomodulation of malaria, either for the purposes of improving outcome in the critically ill or enhancing acquired immunity, requires a more thorough understanding of the basic pathogenesis of the disease. The methods for acquiring this understanding are at hand.

Disclosures

The authors have no financial conflicts of interest.

Footnotes

  • This work was supported by National Institutes of Health Grants R01AI079293 (to D.T.G., K.A.F., R.T.G., and G.W.R.), R01NS098747 (to R.T.G.), U19AI0089681 (to D.T.G. and R.T.G.) T32AI095213 (to J.E.S.), R01AI095192 (to J.W.K., A.E.D., and K.R.D.), and R01AI130131 (to J.W.K.). M.G.N. was supported by European Research Council Consolidator Grant 310372 and a Spinoza grant of the Netherlands Organization for Scientific Research.

  • The online version of this article contains supplemental material.

  • Abbreviations used in this article:

    ChIP
    chromatin immunoprecipitation
    FW
    forward
    Hz
    hemozoin
    iRBC
    Plasmodium-infected RBC
    MTA
    5′-deoxy-5′-(methylthio)adenosine
    qPCR
    quantitative PCR
    RPMI+
    RPMI 1640 supplemented with 10% human serum
    RV
    reverse
    uRBC
    uninfected RBC.

  • Received July 27, 2017.
  • Accepted December 4, 2017.

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