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Malaria systems immunology: Plasmodium vivax induces tolerance during primary infection through dysregulation of neutrophils and dendritic cells

  • Andres F. Vallejo
    Affiliations
    Clinical and Experimental Sciences and NIHR Southampton Biomedical Research Centre, Faculty of Medicine, University of Southampton, Southampton General Hospital, LE59, MP813, SO16 6YD, Southampton, UK
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  • Robert C. Read
    Affiliations
    Clinical and Experimental Sciences and NIHR Southampton Biomedical Research Centre, Faculty of Medicine, University of Southampton, Southampton General Hospital, LE59, MP813, SO16 6YD, Southampton, UK
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  • Myriam Arevalo-Herrera
    Affiliations
    Caucaseco Scientific Research Center, Cali, 760043, Colombia

    School of Health, Universidad del Valle, Cali, 76001, Colombia
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  • Sócrates Herrera
    Affiliations
    Caucaseco Scientific Research Center, Cali, 760043, Colombia
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  • Tim Elliott
    Affiliations
    Centre for Cancer Immunology, Faculty of Medicine, University of Southampton, SO16 6YD Southampton, UK

    Institute for Life Sciences, University of Southampton, SO17 1BJ, UK
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  • Marta E. Polak
    Correspondence
    Corresponding author at: Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LE59, MP813, SO16 6YD Southampton, UK.
    Affiliations
    Clinical and Experimental Sciences and NIHR Southampton Biomedical Research Centre, Faculty of Medicine, University of Southampton, Southampton General Hospital, LE59, MP813, SO16 6YD, Southampton, UK

    Institute for Life Sciences, University of Southampton, SO17 1BJ, UK
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Open AccessPublished:September 21, 2018DOI:https://doi.org/10.1016/j.jinf.2018.09.005

      Highlights

      • In silico analysis suggests that primary infection with P. vivax induces potent immunosuppression mediated by dendritic cells.
      • Antigen presentation is attenuated in malaria-experienced vs malaria-naïve individuals
      • Malaria induce immunosuppressive effect manifested with strong induction of IDO1.

      Summary

      Objectives

      To dissect the transcriptional networks underpinning immune cells responses during primary Plasmodium vivax infection of healthy human adults.

      Methods

      We conducted network co-expression analysis of next-generation RNA sequencing data from whole blood from P. vivax and P. falciparum controlled human malaria infection (CHMI) of healthy naïve and malaria-exposed volunteers. Single cell transcription signatures were used to deconvolute the bulk RNA-Seq data into cell-specific signals.

      Results

      Initial exposure to P. vivax induced activation of innate immunity, including efficient antigen presentation and complement activation. However, this effect was accompanied by strong immunosuppression mediated by dendritic cells via the induction of Indoleamine 2,3-Dioxygenase 1(IDO1) and Lymphocyte Activation Gene 3 (LAG3). Additionally, P. vivax induced depletion of neutrophil populations associated with down regulation of 3G-protein coupled receptors, CRXCR1, CXCR2 and CSF3R. Accordingly, in malaria-exposed volunteers the inflammatory response was attenuated, with a decreased class II antigen presentation in dendritic cells. While the immunosuppressive signalling was maintained between plasmodium species, response to P. falciparum was significantly more immunogenic.

      Conclusions

      In silico analyses suggest that primary infection with P. vivax induces potent immunosuppression mediated by dendritic cells, conditioning subsequent anti-malarial immune responses. Targeting immune evasion mechanisms could be an effective alternative for improving vaccine efficacy.

      Keywords

      Introduction

      Malaria remains an important public health problem worldwide, with more than 216 million cases per year 445,000 deaths.

      Organization WH. World malaria report 2017: World Health Organization; 2017.

      The cyclical fever and pro-inflammatory state associated with malaria has been postulated to inhibit establishment and maintenance of immunological memory
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      ; indeed, humoral and cellular responses to Plasmodium antigens are inefficiently generated and rapidly lost in the absence of ongoing exposure. As a result, individuals from high malaria transmission areas develop partial protection against severe symptoms at an early age and experience a significant number of asymptomatic infections afterwards.
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      There is evidence that Plasmodium falciparum, the most investigated malaria species, can modulate immune responses by interfering with maturation of antigen-presenting cells, however the precise mechanisms leading to immune tolerance are poorly understood. Likewise, it has been suggested that malaria parasites impair dendritic cells (DC) function, resulting in the induction of tolerant T cell phenotype.
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      DCs can exert an immunosuppressive effect by increased surface expression of immune checkpoint proteins such as Programmed Cell Death 1(PD1) or production of tolerogenic substances such as indoleamine 2,3-dioxygenase (IDO1). It has been shown that DC uptake of infected red blood cells (iRBC) impairs the immune responses during blood stage malaria by interfering with the priming and elicitation of liver-stage immunity.
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      During the chronic phase of the infection, the inhibitory molecule IDO1 is up-regulated in DC, inducing PD1 and LAG-3 expression in CD4 T cells, interfering with the memory acquisition.
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      Immunity to P. vivax is more rapidly acquired than immunity to P. falciparum.
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      Whereas a single infection with P. vivax usually results in a strongly reduced incidence of febrile episodes upon re-infection, secondary P. falciparum infections are associated with fever and high parasitaemia. Comparing the immune responses induced by each parasite could reveal immune evasion mechanisms to be used as targets to increase the vaccine efficacy. Unlike P. falciparum, there are no established laboratory methods to culture P. vivax in vitro
      • Udomsangpetch R
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      which has retarded study of this parasite. Controlled human malaria infection (CHMI) models allow precise study of host-parasite interactions because they lack the wide biological variation associated with natural disease, such as strain-to-strain variation, host co-morbidities and time to presentation etc.
      • Rojas-Peña ML
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      • Gibson G
      • Arévalo-Herrera M
      Transcription profiling of malaria-naive and semi-immune Colombian volunteers in a Plasmodium vivax sporozoite challenge.
      Systems immunology analysis of CHMI models offers unique opportunities to study human immune responses during malaria infections by identifying major molecular players at each stage, providing a detailed and comprehensive understanding of the complex host-parasite interaction. Previously, we have developed systems immunology pipelines which allowed us to identify the molecular basis of the orchestration of immunity by DC, revealing potential molecular targets for immune interventions.
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      • Clayton K
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      Gene Expression signatures in tuberculosis have greater overlap with autoimmune diseases than with infectious diseases.
      Similar approaches have led to identification of molecular signatures capable of predicting the efficacy of vaccine-induced immunity and examining the transcriptional and cellular responses in P. falciparum CHMI models.
      • van den Berg RA
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      • Ballou WR
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      Predicting RTS, S vaccine-mediated protection from transcriptomes in a malaria-challenge clinical trial.
      • Kazmin D
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      • van der Most R
      • van den Berg RA
      • et al.
      Systems analysis of protective immune responses to RTS, S malaria vaccination in humans.
      To better understand immune responses induced by exposure to P. vivax we conducted systems immunology analyses of our publicly available RNA-Seq data from a P. vivax CHMI in order to elucidate key host-parasite interactions as potential vaccine targets. We optimised bioinformatic pipelines to enhance read-alignment and increase the number of identified transcripts, improving the sensitivity of the analysis. By using cell specific signatures obtained from single cells, we deconvoluted the signal from whole blood to specific cell types. Network analysis and in silico signal deconvolution allowed us to identify the role of DC in induced tolerance as well as specific targets in the antigen presentation pathway that could play a central role in establishing of immunological memory. Finally, we compared the P. vivax transcription programs with a similar CHMI in P. falciparum to define the specificity of the tolerogenic responses.

      Methods

      Systems immunology analysis of RNA-Seq data from malaria CHMI

      Our P. vivax dataset is deposited in Gene Expression Omnibus (GEO) under accession number GSE67184. The dataset is associated with a P. vivax CHMI, corresponding to the analysis of differences in gene expression between malaria-naïve (MN) and malaria-exposed (ME) volunteers. After challenge with P. vivax, whole blood transcriptomes from six naïve volunteers, were compared with six malaria-exposed to investigate the greater symptom severity in naïve infection, which occurs despite equivalent parasite loads and time to diagnosis.
      • Arévalo-Herrera M
      • Forero-Peña DA
      • Rubiano K
      • Gómez-Hincapie J
      • Martínez NL
      • Lopez-Perez M
      • et al.
      Plasmodium vivax sporozoite challenge in malaria-naive and semi-immune Colombian volunteers.
      The RNA-seq data was derived from 12 whole blood samples taken at two time points (before and 7 days post inoculation of human volunteers with P. vivax as described in.
      • Arévalo-Herrera M
      • Forero-Peña DA
      • Rubiano K
      • Gómez-Hincapie J
      • Martínez NL
      • Lopez-Perez M
      • et al.
      Plasmodium vivax sporozoite challenge in malaria-naive and semi-immune Colombian volunteers.
      The P. falciparum dataset deposited in Gene Expression Omnibus (GEO) under accession number GSE50957 is associated with a P. falciparum CHMI, were PBMC transcriptomic profiles were obtained to explore the association of malaria immunity with fever.
      • Tran TM
      • Jones MB
      • Ongoiba A
      • Bijker EM
      • Schats R
      • Venepally P
      • et al.
      Transcriptomic evidence for modulation of host inflammatory responses during febrile Plasmodium falciparum malaria.

      Next Generation Sequencing data processing

      All reads were subject to quality control using FastQC.

      Andrews S. (2010). FastQC: a quality control tool for high throughput sequence data. Available online at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc.

      Sequences were trimmed to remove adapter contamination and low-quality nucleotides using Trimmomatic
      • Bolger AM
      • Lohse M
      • Usadel B
      Trimmomatic: a flexible trimmer for Illumina sequence data.
      and only reads with quality scores  ≥10 and  ≥40 bp length were kept for further analysis. Hisat2
      • Pertea M
      • Kim D
      • Pertea GM
      • Leek JT
      • Salzberg SL
      Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown.
      was used to align each sample against a reference genome (GRCh38.p11). The alignment result files (bam files) were sorted and indexed using SAMtools.
      • Li H
      • Handsaker B
      • Wysoker A
      • Fennell T
      • Ruan J
      • Homer N
      • et al.
      The sequence alignment/map format and SAMtools.
      Alignments were counted for each gene using the HTSeq count
      • Anders S
      • Pyl PT
      • Huber W
      HTSeq—a Python framework to work with high-throughput sequencing data.
      (Table S1). For differential expression analysis and gene co-expression network analysis, gene expression was estimated as counts per million (CPM), filtering out genes lees that two gene counts in at least half of the samples were used. Determination of differentially expressed genes (DEG) was done using EdgeR
      • Robinson MD
      • McCarthy DJ
      • Smyth GK
      edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.
      with a nested paired design. The expected FDR was estimated using the Benjamini-and-Hochberg method. A P adj  ≤0.05 was considered to be significant. TPM (Transcripts per million) was used for comparing gene expression levels.

      Gene co-expression network analysis

      Un-supervised transcript co-expression analysis was performed using the graphical correlation-based tool BioLayout Express3D
      • Theocharidis A
      • Van Dongen S
      • Enright AJ
      • Freeman TC
      Network visualization and analysis of gene expression data using BioLayout Express3D.
      to visualize clusters or subgroups of genes that shared similar patterns of expression across different samples. Unlogged expression values pre-filtered for low expressed genes was used as input. A range of correlation coefficients (r = 0.8 to r = 0.95) and Markov Clustering Algorithm values were used (MCL = 1.7 − MCL = 5) to determine an optimal graph structure. Clusters were then manually curated to remove artefacts. The gene clusters with highest correlation scores were used to generate and visualize networks based on GO-enrichment analysis (GOEA) by using ToppGene.
      • Chen J
      • Bardes EE
      • Aronow BJ
      • Jegga AG
      ToppGene Suite for gene list enrichment analysis and candidate gene prioritization.
      Weighted gene set enrichment analysis (WGSEA) was performed using GeneTrial
      • Backes C
      • Keller A
      • Kuentzer J
      • Kneissl B
      • Comtesse N
      • Elnakady YA
      • et al.
      GeneTrail—advanced gene set enrichment analysis.
      using as input the DEGs from EdgeR. WGSEA was performed using a Kolmogorov–Smirnov non-parametric rank statistic with Benjamini and Yekutieli FDR multiple testing adjustment method. Gene lists were ranked based on fold change (keeping the dysregulation direction) with 1 × 106 permutations. The significance level was set at 0.05. Transcription factors were identified using the transcriptional regulatory relationships deposited in the TRRUST database.
      • Han H
      • Shim H
      • Shin D
      • Shim JE
      • Ko Y
      • Shin J
      • et al.
      TRRUST: a reference database of human transcriptional regulatory interactions.
      STRING 10.5
      • Mering Cv
      • Huynen M
      • Jaeggi D
      • Schmidt S
      • Bork P
      • Snel B
      STRING: a database of predicted functional associations between proteins.
      was used generating the edges based (score > 0.6) and PPI network building. Cytoscape 3.5 was used to create the network.

      Construction of cell type specific signatures from single cell RNA-Seq information to deconvolute bulk RNA-Seq samples

      To evaluate gene-specific differences between blood cells we retrieved the Zheng et al. SC-RNA-Seq dataset.
      • Zheng GX
      • Terry JM
      • Belgrader P
      • Ryvkin P
      • Bent ZW
      • Wilson R
      • et al.
      Massively parallel digital transcriptional profiling of single cells.
      This dataset contains gene expression profiles of 8K human peripheral blood mononuclear cells (PBMC), annotated based on similarity with 4 immune cell subpopulations (myeloid DC (mDC), B cells, T cells and NK cells). We extracted marker genes for each cell type based on high expression, high variation (Fano factor above mean-dependent threshold), and cell-type restricted (p < 10−5, defined by a Kolmogorov–Smirnov test). Because of a sample size requirement, we merged the original single cell data from T cell groups (CD4 and CD8) into one group. Neutrophil markers were obtained from a similar analysis using the Hoek et al. RNA-Seq dataset.
      • Hoek KL
      • Samir P
      • Howard LM
      • Niu X
      • Prasad N
      • Galassie A
      • et al.
      A cell-based systems biology assessment of human blood to monitor immune responses after influenza vaccination.
      The cell type-specific markers were applied to obtain a reference basis matrix which was used to infer the composition of bulk tissue samples from their total gene expression using CIBERSORT deconvolution method
      • Newman AM
      • Liu CL
      • Green MR
      • Gentles AJ
      • Feng W
      • Xu Y
      • et al.
      Robust enumeration of cell subsets from tissue expression profiles.
      with gene expression values without log-transformation as input. The dataset GEO entry (GSE60424) which contains raw RNA-Seq and sample annotation data form 6 immune cell subsets and whole blood was used for validating the signature.

      Statistical analysis

      Statistical analyses were performed using Prism 7 (GraphPad Software) and methods embedded in bioinformatic pipelines. The Shapiro–Wilk test was used to test for normality. For non-normally distributed data the Wilcoxon matched-pairs signed rank test was used for comparison of two groups. For normally distributed data a paired student's t test was used. The statistical test used and p values are described in the figure legends with *p < 0.05, **p < 0.01, and ***p < 0.001.

      Results

      Transcriptional profile analysis indicates development of innate immune responses during the first P. vivax infection in naïve individuals

      Our previous analysis of differences in gene expression between malaria-naïve (MN) and malaria-exposed (ME) volunteers demonstrated significant changes in gene expression at the time of malaria diagnosis, particularly in the naïve volunteers, with downregulation of genes related to innate immunity, and inflammation.
      • Rojas-Peña ML
      • Vallejo A
      • Herrera S
      • Gibson G
      • Arévalo-Herrera M
      Transcription profiling of malaria-naive and semi-immune Colombian volunteers in a Plasmodium vivax sporozoite challenge.
      We performed paired differential gene expression analysis comparing MN individuals (n = 6) before and after the challenge, to establish the transcriptomic networks activated during malaria infection. A total of 1,072 DEGs (EdgeR, FDR p < 0.05) were identified, of which 39% were upregulated (Table S2). Co-expression analysis (CEA) identified eight main clusters (576 genes, Fig. 1(A)) split into 2 major isolated network structures, comprising up-regulated and down-regulated genes (BioLayout Express3D, r = 0.92, MCL = 1.7). Three largest clusters were made of 202 genes up-regulated on exposure to malaria and involved in innate immune responses (FDR = 9.4 × 10−33). Cluster 1, characterised by the highest average gene expression level at diagnosis, recapitulated the typical inflammation pattern including up-regulation of CXCL9, CXCL10, IFIT1, IFIT2, IFIT3, IFIT5, IRF1 and IRF7 (Fig. 1(B)). Cluster 2 and 3 contained co-expressed genes involved in antigen presentation, including HLA-DMB and CD74 (Cluster 2) and complement activation (Cluster 3). In contrast, cytokine response and endosome genes were downregulated during the infection (Clusters 4-6). Importantly, Cluster 4 comprised significantly down-regulated neutrophil-associated genes, including the neutrophil chemoattractants CXCR1, CXCR2 and CSF3R, which promotes neutrophil maturation.
      • Fleischman AG
      • Maxson JE
      • Luty SB
      • Agarwal A
      • Royer LR
      • Abel ML
      • et al.
      The CSF3R T618I mutation causes a lethal neutrophilic neoplasia in mice that is responsive to therapeutic JAK inhibition.
      Notably, these three G protein-coupled receptors have similar affinities to cytokines and chemokines and share structural conformation with the ACKR1 (DARC), the P. vivax receptor in reticulocytes.
      • Horuk R
      The Duffy antigen receptor for chemokines DARC/ACKR1.
      ,
      • Russo RC
      • Garcia CC
      • Teixeira MM
      • Amaral FA
      The CXCL8/IL-8 chemokine family and its receptors in inflammatory diseases.
      Other molecules with immune function that were down-regulated (in cluster 4) included the receptor CD163,
      • Moestrup S
      • Møller H
      CD163: a regulated hemoglobin scavenger receptor with a role in the anti‐inflammatory response.
      involved in haemoglobin clearance; CR1, a regulator of the complement cascade, CCR3 a receptor that binds to CCL11 and NCF4 involved in activates flavocytochrome b in neutrophils.
      Fig 1
      Fig. 1Gene co-expression analysis (CEA) indicates development of immunosuppression during P. vivax infection in naïve individuals. (A) Visual representation of whole transcriptome analysis of whole blood from human naïve volunteers during the controlled human malaria infection (CHMI). The analysis identified eight main clusters. (BioLayoutExpress3D, r = 0.92, MCL = 1.7). Lines (edges) represent the similarity between transcript expressions; circles (nodes) represent transcripts. Clusters of co-expressed genes are coded by colour. Enrichment of gene ontology terms in clusters was done using ToppGene
      • Chen J
      • Bardes EE
      • Aronow BJ
      • Jegga AG
      ToppGene Suite for gene list enrichment analysis and candidate gene prioritization.
      ) Mean (± SEM) expression profiles for clusters 1–8, pre-challenge (pre, blue bars) and on diagnosis day (Dx, grey bar). (B) Mean (±SEM) expression profiles for clusters 1–8, pre challenge (blue bars) and at the diagnosis (grey bars). (For interpretation of the references to colour in this figure, the reader is referred to the web version of this article.)

      Antigen presentation is attenuated in malaria-experienced vs malaria-naïve individuals

      In order to profile the changes in the immune response in malaria-exposed individuals during a P. vivax CHMI, we compared the genes differentially expressed upon P. vivax challenge in MN and ME individuals. A total of 400 DEGs were detected in ME individuals (FDR < 0.05), from which 30% were up regulated (Table S3). Importantly, ME volunteers showed 62% fewer DEGs compared with the MN volunteers with a lower proportion of upregulated genes (Fig. 2(A)). To determine biological processes either enriched or depleted due to differential malaria exposure, modules of co-expressed genes associated with ME and MN response patterns identified with WGSEA were correlated with Reactome pathways
      • Jupe S
      • Akkerman JW
      • Soranzo N
      • Ouwehand WH
      Reactome–a curated knowledgebase of biological pathways: megakaryocytes and platelets.
      as gene sets. The functional responses elicited were similar in both groups: P. vivax infection induced strong inflammatory responses including IFN-α/ IFN-γ and TCR pathway activation (Fig. 2(B)). However, notable differences between ME and MN transcriptomic responses were observed in antigen processing and presentation. Importantly, class II antigen presentation signature, strongly up-regulated upon the first encounter with Plasmodium in malaria-naïve individuals, was not significantly enriched in ME. In contrast, significant enrichment in cross-presentation and antigen processing, regulation of ornithine decarboxylase, and MAPK6/MAPK4 signalling was observed only in ME individuals.
      Fig 2
      Fig. 2Changes in gene expression during malaria infection in malaria naive and malaria-exposed volunteers. (A) Comparison of differentially expressed genes induced during P. vivax infection in naïve vs malaria-experienced volunteers, red: up-regulated genes, blue: down-regulated genes. (DEG identification: EdgeR, FDR p value <0.05) (B) Overexpressed biological pathways (REACTOME database) identified using weighted gene-set enrichment analysis (WGSEA) comparing MN and ME individuals using a Kolmogorov–Smirnov non-parametric rank statistic with Benjamini and Yekutieli FDR multiple testing adjustment method (significance level was set at 0.05). Gene lists were ranked based on fold change with 1 × 106 permutations. (For interpretation of the references to colour in this figure, the reader is referred to the web version of this article.)

      Single cell-based deconvolution of bulk gene expression samples confirms depletion of neutrophil populations and a significant expansion of dendritic cells

      The availability of single-cell gene expression data offers improved means for deconvolution by providing profiles from a large number of minimally perturbed primary cells. To estimate the proportions of B cells, monocytes, mDC, neutrophils, NK and T cells in the whole blood samples obtained during the CHMI trial, we optimized and validated a bioinformatics pipeline for dissecting the characteristic expression profiles of immune cell types using a data set comprising 8K single cells from a healthy donor.
      • Zheng GX
      • Terry JM
      • Belgrader P
      • Ryvkin P
      • Bent ZW
      • Wilson R
      • et al.
      Massively parallel digital transcriptional profiling of single cells.
      Based on this analysis we built a deconvolution matrix containing 443 specific markers for 5 cell types (Table S4). Information on specific cell-type transcriptomic expression is captured by the single cell deconvolution matrix (SC-matrix) as shown by the (Fig. S1). We used the SC-matrix to assess the relative proportions of immune cells during malaria infection of naïve individuals and individuals with prior exposure. While estimated frequency of B cells, T cells, monocytes, and NK cells remained stable between naïve and previously-exposed individuals, pre and post challenge, proportion of DC signal dramatically increased upon challenge with P. vivax in both groups (Fig. 3). This indicates, that the biology of blood DCs is uniquely regulated during malaria infection, and identifies the cellular source of the changes in antigen processing and presentation signal, detected in co-expression analysis (Fig. 1). Furthermore, we observed a significant decrease in the neutrophil population in MN at the time of malaria diagnosis, (Fig. 3). This decrease in neutrophils is consistent with the significant downregulation of CXCR1, CXCR2 and CSF3R (Fig. S3). A smaller, statistically insignificant, decrease was observed for the ME group. Both groups exhibited a significant increase in expression of CXCL9 and CXCL10 during the infection which could be correlated with the levels in T cell and monocytes. The receptor of the monocyte chemoattractant protein-1, CCR2, was up-regulated only in MN individuals which correlates with the high predicted levels at the time of diagnosis (Tables S2 and 3).
      Fig 3
      Fig. 3Bulk RNA sample deconvolution into specific cell proportions. Estimated proportions of B cells, monocytes, mDC, neutrophils, NK and T cells based on single-cell-specific gene expression (n = 5, unpaired t-test; *P < 0.05) in naïve (MN) and malaria-exposed (ME) pre (grey bars) and post (orange bars) exposure to P vivax. Mean of n = 6  ±  SEM shown. (For interpretation of the references to colour in this figure, the reader is referred to the web version of this article.)

      P. vivax-induced immunosuppression is associated with IDO1 expression and decrease of class II antigen presentation

      An essential function of DCs is to prime naïve T cells, shaping the immune response to be tolerogenic or inflammatory depending on the DCs’ activation phenotype.
      • Clayton K
      • Vallejo AF
      • Davies J
      • Sirvent-Bernal S
      • Polak MEP
      Langerhans cells-programmed by the epidermis.
      While initial exposure to malaria resulted in strong innate immune system activation (Fig. 1) and expansion of blood DC signal (Fig. 3), strong immunosuppressive signaling was observed in parallel. The immunosuppressive effect induced by the first malaria infection was manifested with strong induction of IDO1 (the top up-regulated transcript, FC = 55.3, Padj = 7 × 10−7), correlating with the expression of EGR2, a transcription factor binding to IDO1 promoter (Fig. 4(A) and (B)). IDO1 has been shown to be mainly expressed in DC
      • Villani A-C
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      • Fletcher J
      • et al.
      Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors.
      and is known to induce a tolerogenic signal through the activation of T-cells (Treg), maintaining the homoeostatic balance and controlling immunopathogenesis through the modulation of the excessive inflammatory response.
      • Walther M
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      • et al.
      Upregulation of TGF-β, FOXP3, and CD4+ CD25+ regulatory T cells correlates with more rapid parasite growth in human malaria infection.
      Lymphocyte-activation gene 3 (LAG3) expressed exclusively in activated T and NK lymphocytes, was upregulated only in MN, is a CD4 homologue that binds MHC class II molecules with very high affinity and has a negative regulatory effect on T cell function and DC maturation (Fig. 4(C)).
      • Workman C
      • Vignali D
      Negative regulation of T cell homeostasis by LAG-3 (CD223).
      • Huang C-T
      • Workman CJ
      • Flies D
      • Pan X
      • Marson AL
      • Zhou G
      • et al.
      Role of LAG-3 in regulatory T cells.
      Analysis of the expression of transcription factors in MN indicated that IRF1, STAT1 and STAT2 were the most highly expressed transcription factors activated in similar proportions in both groups, whereas, E2F1, PLM and KLF5 were the transcription factors changing the most after infection. The interferon-induced proteins IRF1 and IRF9 were the most up-regulated genes of the interferon-induced family (Fig. S4). Two of the main transcription factors involved in the antigen presentation gene regulatory network, CIITA and RFX5, where significantly up regulated in MN but not in ME suggesting a less activated antigen presentation in the ME individuals (Fig. 4(D)-(E)). The Colony Stimulating Factor 3 Receptor (CSF3R) a receptor that that controls the production, differentiation, and function of granulocytes was significantly down-regulated in MN but not in the ME group (Fig. 4(F)) which correlates with strong drop in the estimated neutrophil abundance.
      Fig 4
      Fig. 4P. vivax induced immunosuppression is mediated by IDO1. Paired analysis of key regulatory genes during a P. vivax CHMI (n = 5, paired t-test; *P < 0.05). Normalised gene counts (scaled TPM) shown in naïve (MN) and malaria-exposed (ME) Pre (grey dots) and post (orange dots) exposure to P vivax. (For interpretation of the references to colour in this figure, the reader is referred to the web version of this article.)

      Distinctive gene expression profile in P. falciparum infections

      In order to assess the specificity of the tolerogenic responses detected in P. vivax we used the NGS data from Tran et al.,
      • Tran TM
      • Jones MB
      • Ongoiba A
      • Bijker EM
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      • et al.
      Transcriptomic evidence for modulation of host inflammatory responses during febrile Plasmodium falciparum malaria.
      documenting the gene expression profile in naïve individuals exposed to P. falciparum CHMI (n = 5). While molecules associated with immunosuppression (IDO, CD274) were observed in both datasets, P. falciparum induced stronger inflammatory responses with expression of a wide spectrum of chemokines, chemokine receptors and Toll-like receptors, in contrast to P. vivax. Toll like receptor 7 was upregulated during the infection with both parasites, whereas TLR 1-5 and 8 where exclusively upregulated in P. falciparum. CXCL9 and 10 where highly upregulated in both parasites, whereas CXCL11 and CCL2, two potent chemoattractant molecules for lymphocytes and monocytes respectively were only upregulated in P. falciparum infections.
      CXCR3 downregulation on P. falciparum could be related with a negative feedback with the CXCL11. IL15 was the most highly cytokine in P. falciparum, whereas in P. vivax was IL18. While expression of transcription factors involved in activating innate immune responses, including interferon regulatory factors (IRF) 1,2,5,7 and 8 was highly significant in P. falciparum, only IRF 1,7 and 9 were significantly up-regulated upon exposure to P. vivax. Down-regulation of CXCR1, CXCR2, CCR3 and CXCL6, specific to neutrophils, was absent in the P. falciparum dataset due to the sample preparation (Fig. 5).
      Fig 5
      Fig. 5Distinct gene expression profiles in induced by different Plasmodium species Comparative analysis of selected immunomodulatory genes DEG during P. vivax and P. falciparum CHMI. Mean/median fold change in gene expression level between post and pre-exposure to P. falciparum and P. vivax shown for each gene. Genes down-regulated on exposure: blue, genes up-regulated on exposure: red. Black outline: significant FDR corrected p value. Green outline: neutrophil-associated genes, not detected in PBMC. Genes are ranked by fold change in P. falciparum CHMI. (For interpretation of the references to colour in this figure, the reader is referred to the web version of this article.)

      Discussion

      CHMI system is a well-controlled system allowing investigations of immune responses to infection with malaria parasites as they develop in a human host, offering the opportunity to capture the initial programming of systemic immune responses. Applying novel systems immunology approaches to the whole transcriptome data from a unique CHMI study has allowed us, for the first time, to describe molecular and cellular mechanisms potentially involved in malaria-induced immunosuppression.
      We have shown that P. vivax induces a strong immunosuppression mediated by DCs associated with the induction of IDO1. DCs are the key immune regulators keeping in check excessive inflammation to control the cellular immune response through direct contact with effector immune cells and by the production of regulatory cytokines including IL-10 and TGF-β.
      • Belkaid Y
      • Tarbell K
      Regulatory T cells in the control of host-microorganism interactions.
      • Riley E
      • Wahl S
      • Perkins D
      • Schofield L
      Regulating immunity to malaria.
      • Rodrigues F
      • Neto GC
      • Menezes J
      • Gama M
      • Gonçalves E
      • Silva A
      • et al.
      Expression of Foxp3, TGF-β and IL-10 in American cutaneous leishmaniasis lesions.
      Here, signal deconvolution identified DCs as the cell population most significantly activated by the initial P. vivax infection. However, despite the DC potential to prime effective adaptive immune responses, in the context of malaria infection DC induction was associated with immunosuppressive signalling. Thanks to their pivotal role in regulation of immunity, DC could be key for understanding the tolerance induced during the first P. vivax malaria infection and could underlie the relatively benign disease experienced in ME individuals. IDO1 has been identified as an important immunoregulator inhibiting T-cell responses and promoting immune tolerance.
      • Mbongue JC
      • Nicholas DA
      • Torrez TW
      • Kim N-S
      • Firek AF
      • Langridge WH
      The role of indoleamine 2, 3-dioxygenase in immune suppression and autoimmunity.
      In leishmaniasis
      • Makala LH
      • Baban B
      • Lemos H
      • El-Awady AR
      • Chandler PR
      • Hou D-Y
      • et al.
      Leishmania major attenuates host immunity by stimulating local indoleamine 2, 3-dioxygenase expression.
      and malaria,
      • Miu J
      • Ball HJ
      • Mellor AL
      • Hunt NH
      Effect of indoleamine dioxygenase-1 deficiency and kynurenine pathway inhibition on murine cerebral malaria.
      IDO mediated attenuation of adaptive immunity may facilitate parasite persistence and disease severity. The high expression levels of IDO1 are likely to be produced by DCs and in combination with the observed reduction in the HLA class II antigen presentation activity, may be responsible for induction of immunosuppressive responses. Remarkably, studies of P. vivax asymptomatic individuals found substantially lower levels of inflammatory and regulatory cytokines,
      • Andrade BB
      • Reis-Filho A
      • Souza-Neto SM
      • Clarêncio J
      • Camargo L
      • Barral A
      • et al.
      Severe Plasmodium vivax malaria exhibits marked inflammatory imbalance.
      contrasting with higher levels of the regulatory cytokine interleukin (IL)-10 in Brazilian P. vivax malaria patients.
      • Goncalves RM
      • Scopel KK
      • Bastos MS
      • Ferreira MU
      Cytokine balance in human malaria: does Plasmodium vivax elicit more inflammatory responses than Plasmodium falciparum?.
      Our data are consistent with previous findings of increased Treg activation in adults with clinical illness and controlled infections of P. vivax malaria.
      • Bueno LL
      • Morais CG
      • Araujo FF
      • Gomes JAS
      • Corrêa-Oliveira R
      • Soares IS
      • et al.
      Plasmodium vivax: induction of CD4+ CD25+ FoxP3+ regulatory T cells during infection are directly associated with level of circulating parasites.
      • Woodberry T
      • Loughland JR
      • Minigo G
      • Burel JG
      • Amante FH
      • Piera KA
      • et al.
      Early Immune regulatory changes in a primary controlled human plasmodium vivax infection: CD1c+ Myeloid dendritic cell maturation arrest, induction of the Kynurenine pathway, and regulatory T cell activation.
      Transcriptomic programming of P. vivax can be understood better when contrasted with highly immunogenic P. falciparum infection. While P. falciparum induces both tolerogenic and immunogenic transcriptomic responses, exposure to P. vivax seems to be distinctively tolerogenic. This important difference may be explained by differential expression of transcription factors regulating innate immunity. While P. vivax induces only two members of IRF family, IRF1 and IRF7, potentially limiting the extend of antigen presentation and cytokine/chemokine production, exposure to P. falciparum promotes also IRF5, IRF9 and most importantly IRF8, proven to regulate DC survival and pro-inflammatory function.
      • Cohen SB
      • Smith NL
      • McDougal C
      • Pepper M
      • Shah S
      • Yap GS
      • et al.
      Beta-catenin signaling drives differentiation and proinflammatory function of IRF8-dependent dendritic cells.
      • la Sala A
      • He J
      • Laricchia-Robbio L
      • Gorini S
      • Iwasaki A
      • Braun M
      • et al.
      Cholera toxin inhibits IL-12 production and CD8alpha+ dendritic cell differentiation by cAMP-mediated inhibition of IRF8 function.
      • Tailor P
      • Tamura T
      • Kong HJ
      • Kubota T
      • Kubota M
      • Borghi P
      • et al.
      The feedback phase of type I interferon induction in dendritic cells requires interferon regulatory factor 8.
      In concordance, P. falciparum infection induces broader cytokine, chemokine and TLR spectrum. Importantly, IL-7 and CXCR6, two key molecules involved in memory responses where dysregulated significantly only in P. falciparum infections, likely potentiating aberrant immune responses, including survival of memory CD4 + T cells (IL7) and inefficient CD8 memory responses (CXCR6).
      • Tse S-W
      • Radtke AJ
      • Espinosa DA
      • Cockburn IA
      • Zavala F
      The chemokine receptor CXCR6 is required for the maintenance of liver memory CD8+ T cells specific for infectious pathogens.
      This strong inflammatory response induced by P. falciparum appears to be essential to expeditiously control a highly pathogenic infection at the expense of the long-term immunity.
      Conversely, initial exposure to P. vivax induces dramatic drops in neutrophil population, specifically downregulating of CXCR1, CXCR2 and CCR3. Neutrophils regulate DC function during microbial infection, probably by cross-talk between these cell populations as an important component of the innate immune response to infection.
      • Bennouna S
      • Bliss SK
      • Curiel TJ
      • Denkers EY
      Cross-talk in the innate immune system: neutrophils instruct recruitment and activation of dendritic cells during microbial infection.
      IL-8 (CXCL8), the main ligand of CXCR1, is a powerful neutrophil chemotactic factor and its binding to CXCR1 induces activation and migration of neutrophils.
      • Holmes WE
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      Structure and functional expression of a human interleukin-8 receptor.
      • Horikawa T
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      • Furukawa M
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      Expression of interleukin‐8 receptor a predicts poor outcome in patients with nasopharyngeal carcinoma.
      Taken together, this data, and the recent finding of P. vivax affecting bone marrow
      • Baro B
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      we hypothesise that the parasite infection could have deep effects on haematopoietic progenitor cells expressing structural related G coupled receptors. Elevated levels of EZH2 at CIITApIV and the resulting increases in CIITApIV H3K27me3 occur in the presence of IFN-γ and leave the proximal promoter inaccessible for transcription factor binding or transcription initiation.
      • Truax AD
      • Thakkar M
      • Greer SF
      Dysregulated recruitment of the histone methyltransferase EZH2 to the class II transactivator (CIITA) promoter IV in breast cancer cells.
      Decreased expression of E2F1 could result in the modulation of EZH2 which results in expression of CIITA and MHC II. This observation correlates with the low antibody response observed in sera from the same volunteers tested against a protein microarray comprising ∼50% of the P. vivax proteome.
      • Arévalo-Herrera M
      • Lopez-Perez M
      • Dotsey E
      • Jain A
      • Rubiano K
      • Felgner PL
      • et al.
      Antibody profiling in Naïve and semi-immune individuals experimentally challenged with Plasmodium vivax sporozoites.
      Based in the activation of EZH2, HDAC7 and CREBBP is possible that the changes induced by the infection could be genomically imprinted. Indeed, case-control and longitudinal studies indicate that children undergoing malaria episodes have increased susceptibility to infection with non-typhoidal Salmonella species and other bacteria.
      • Scott JAG
      • Berkley JA
      • Mwangi I
      • Ochola L
      • Uyoga S
      • Macharia A
      • et al.
      Relation between falciparum malaria and bacteraemia in Kenyan children: a population-based, case-control study and a longitudinal study.
      Plasmodium-infected mice are highly susceptible to infection with non-typhoidal Salmonella species. It has been reported that malaria-induced immune-modulatory haem oxygenase 1 and IL-10 dampen the effector functions of neutrophils and macrophages.
      • Cunnington AJ
      • De Souza JB
      • Walther M
      • Riley EM
      Malaria impairs resistance to Salmonella through heme-and heme oxygenase-dependent dysfunctional granulocyte mobilization.
      • Lokken KL
      • Mooney JP
      • Butler BP
      • Xavier MN
      • Chau JY
      • Schaltenberg N
      • et al.
      Malaria parasite infection compromises control of concurrent systemic non-typhoidal Salmonella infection via IL-10-mediated alteration of myeloid cell function.
      Similarly, impaired neutrophil function has been described both in P. falciparum and P. vivax malaria.
      • Cunnington AJ
      • Njie M
      • Correa S
      • Takem EN
      • Riley EM
      • Walther M
      Prolonged neutrophil dysfunction after Plasmodium falciparum malaria is related to hemolysis and heme oxygenase-1 induction.
      Interestingly, our approach revealed transcriptional networks of gene modules related to type I interferon, innate immunity and T cell signalling. Importantly, these gene networks were associated with specific phenotypes and predicted changes in immune cell populations. Among these pathways, IDO1 has been shown to modulate the T in response to the parasitic infection.
      • Mbongue JC
      • Nicholas DA
      • Torrez TW
      • Kim N-S
      • Firek AF
      • Langridge WH
      The role of indoleamine 2, 3-dioxygenase in immune suppression and autoimmunity.
      This suggests that transcriptional programs associated with particular immunological processes might determine the clinical outcome of P. vivax malaria. While development of immunological memory facilitates an immediate recall of effector cells which rapidly clear the parasite preventing an excessive inflammatory response and tissue damage, previous studies have shown that release of pro-inflammatory mediators like TNF-a and IFN-γ during malaria infections, potentially can contribute to organ damage.
      • Webster DP
      • Dunachie S
      • Vuola JM
      • Berthoud T
      • Keating S
      • Laidlaw SM
      • et al.
      Enhanced T cell-mediated protection against malaria in human challenges by using the recombinant poxviruses FP9 and modified vaccinia virus Ankara.
      Thus, the observed induction of the immunosuppression may be an effect of evolutionary adaptation to prevent excessive damaging inflammation. Taken together, these results indicate that the immune response to P. vivax infection is tightly associated with previous host malaria experience. This might explain the lack of correlation between protection achieved in CHMI and vaccine efficacy in the field.
      • Bojang KA
      • Milligan PJ
      • Pinder M
      • Vigneron L
      • Alloueche A
      • Kester KE
      • et al.
      Efficacy of RTS, S/AS02 malaria vaccine against Plasmodium falciparum infection in semi-immune adult men in The Gambia: a randomised trial.
      • Stoute JA
      • Slaoui M
      • Heppner DG
      • Momin P
      • Kester KE
      • Desmons P
      • et al.
      A preliminary evaluation of a recombinant circumsporozoite protein vaccine against Plasmodium falciparum malaria.
      Applying a combination of whole transcriptome network analysis and cell signature deconvolution allowed us to gain novel insights into the mechanisms underpinning P. vivax infection. The most significant limitation in our study is that the deconvolution method is highly dependent on the fidelity of reference profiles which can potentially over- or under-represent the cell types. However, the use of SC-RNA-Seq data as well as the validation of the signature with data sets from purified cell population mitigate this issue, and allow identification of plausible cell-specific immune mechanisms. A better understanding of immune systems in individuals with varying degrees of immunity to P. vivax will be useful to improve rational vaccine design and development novel therapeutic interventions. The mechanisms of immunosuppression that we have shown here could be harnessed to improve current malaria vaccines by targeting specific molecules such as the IDO1, to overcome parasite immune evasion.

      Funding

      MEP is funded by Sir Henry Dale Fellowship, Wellcome Trust. Grant no 109377/Z/15/Z . AV is funded by the Royal Society grant no CH160056.

      Conflict of interest

      The authors declare to have no conflict of interest.

      Acknowledgments

      We are grateful to the subjects who participated in this study; and Elena Vataga, Computational Modelling Group, University of Southampton, for assistance with the High-Performance Computing | HPC Platform.

      Appendix. Supplementary materials

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