Open access
Host-Microbial Interactions
Research Article
28 February 2023

Cerebral Malaria Is Regulated by Host-Mediated Changes in Plasmodium Gene Expression

Special Series: Diversity, Equity, and Inclusivity 

ABSTRACT

Cerebral malaria (CM), the deadliest complication of Plasmodium infection, is a complex and unpredictable disease. However, our understanding of the host and parasite factors that cause CM is limited. Using a mouse model of CM, experimental CM (ECM), we performed a three-way comparison between ECM-susceptible C57BL/6 mice infected with ECM-causing Plasmodium ANKA parasites [ANKA(C57BL/6)], ECM-resistant BALB/c mice infected with Plasmodium ANKA [ANKA(BALB/c)], and C57BL/6 mice infected with Plasmodium NK65 that does not cause ECM [NK65(C57BL/6)]. All ANKA(C57BL/6) mice developed CM. In contrast, in ANKA(BALB/c) and NK65(C57BL/6), infections do not result in CM and proceed similarly in terms of parasite growth, disease course, and host immune response. However, parasite gene expression in ANKA(BALB/c) was remarkably different than that in ANKA(C57BL/6) but similar to the gene expression in NK65(C57BL/6). Thus, Plasmodium ANKA has an ECM-specific gene expression profile that is activated only in susceptible hosts, providing evidence that the host has a critical influence on the outcome of infection.
IMPORTANCE Hundreds of thousands of lives are lost each year due to the brain damage caused by malaria disease. The overwhelming majority of these deaths occur in young children living in sub-Saharan Africa. Thus far, there are no vaccines against this deadly disease, and we still do not know why fatal brain damage occurs in some children while others have milder, self-limiting disease progression. Our research provides an important clue to this problem. Here, we showed that the genetic background of the host has an important role in determining the course and the outcome of the disease. Our research also identified parasite molecules that can potentially be targeted in vaccination and therapy approaches.

INTRODUCTION

Cerebral malaria (CM) is the deadliest complication of Plasmodium infection (1). Despite occurring in only approximately 1% of infected individuals, CM is responsible for the majority of all malaria parasite-related deaths, which equals around 300,000 to 500,000 fatalities each year (24). According to the WHO, CM affects mostly young African children and is estimated to be 15 to 25% fatal even with antimalarial drug treatment against blood-stage infection (3, 5). Moreover, survivors of the disease often suffer from long-term neurological sequela, dramatically decreasing their quality of life (6, 7). CM is a complex disease characterized by sequestration of infected red blood cells (iRBCs) in brain vasculature, migration of innate and adaptive immune cells to brain parenchyma, and increased production of proinflammatory mediators, altogether leading to multifocal intracranial hemorrhage and brain edema (3, 812). Studies of the pathophysiology of CM are limited due to both rapid progression of disease—often fatal within 48 h after the onset of neurological symptoms—and limited access to pre- and postmortem patient material (1315). Therefore, we have a limited understanding of the pathogenesis of CM, and why Plasmodium infection in some patients progresses into CM while in vast majority of patients, the disease runs a course free of any neurological symptoms is still unclear.
Studies of CM in mice, known as experimental CM (ECM) have been used extensively to delineate the pathogenesis of CM (16, 17). In particular, Plasmodium berghei ANKA infection of the C57BL/6 host has been shown to recapitulate the majority of the CM symptoms (1822). The majority of ECM studies in mice are performed by transferring iRBCs from a sick animal to healthy recipients, therefore primarily focusing on the blood-stage parasite. However, limited research carried out using chemically attenuated or transgenic sporozoites reveals that changes in the preerythrocytic stage can alter the dynamics of the blood stage and thus affect the progression of the ECM phenotype (2326). Further research using P. berghei ANKA parasites in different hosts showed that although most mouse strains can be infected by P. berghei ANKA, only certain strains such as C57BL/6 and CBA/Ca were susceptible to ECM, whereas other strains such as BALB/c and DBA/2J were resistant (2730) . Additionally, it was shown that artificially inducing the proinflammatory cytokine response in BALB/c mice can break resistance to ECM in this strain (31). These findings pointed out the importance the of host in determining the outcome of parasite infection. In separate studies, infection of the ECM-susceptible C57BL/6 strain with a different Plasmodium berghei strain (P. berghei NK65) that is closely related to P. berghei ANKA had no ECM phenotype (32). Genomic analyses showed that P. berghei ANKA and P. berghei NK65 parasites differed by only 20 single nucleotide polymorphisms (SNPs) in their coding regions (32, 33). Recently, using CRISPR-Cas9-mediated point mutation in one of these SNPs located in the DNA binding domain of an ApiAP2 transcription factor, we reported major changes in the development of the host immune response against the parasite and the outcome of parasite infection but no change in ECM phenotype (32, 34). Altogether, these reports highlighted the importance of parasite genetic factors in determining the outcome of the disease.
Although such studies established that both host- and parasite-related factors determine whether Plasmodium infections lead to ECM, research aimed to identify how host and parasite factors influence each other is limited. Clearly, a better understanding of the contribution of parasite and host factors in mouse models would benefit efforts to determine the how human-to-human variation as well as continuously changing parasite gene expression determine the outcome of human Plasmodium infection.
Here, we performed a three-way comparison between ECM causing P. berghei ANKA in an ECM-susceptible C57BL/6 host [ANKA(C57BL/6)], ECM causing P. berghei ANKA in an ECM-resistant BALB/c host [ANKA(BALB/c)], and non-ECM causing P. Berghei NK65 in an ECM-susceptible C57BL/6 host [NK65(C57BL/6)]. Our comprehensive analyses showed that the host influences the disease progression by modulating parasite gene expression.

RESULTS

ANKA(BALB/c) and NK65(C57BL/6) infections have similar disease courses.

We monitored the progression of malaria following ANKA(C57BL/6), ANKA(BALB/c), and NK65(C57BL/6) Plasmodium infection conditions. In order to do so, we passaged Plasmodium stocks that were originally grown in C57BL/6 mice in either C57BL/6 or BALB/c mice three times. This way, we kept the parasite passage numbers equal while eliminating any potential non-parasite-related confounding factors originating from allogeneic transfer of C57BL/6 red blood cells into the BALB/c host (see Fig. S1a in the supplemental material). Only ANKA(C57BL/6) rapidly progressed to severe disease, as evidenced by early uniform mortality with all mice dying by day 7 postinfection (p.i.) (Fig. 1a). Histopathological evaluations of brains taken from a group of animals on day 6 p.i. showed the ECM phenotype in the ANKA(C57BL/6) group, which showed multifocal hemorrhages (Fig. 1b and c). These hemorrhages localized particularly in the cerebellum (Fig. 1b) and olfactory bulb (Fig. 1c), which were formerly demonstrated as areas that are preferentially affected by ECM (17, 32, 35). On the other hand, the ANKA(BALB/c) and NK65(C57BL/6) groups both had longer disease courses (Fig. 1a) and no brain pathology (Fig. 1b and c), confirming that these two conditions do not develop ECM.
FIG 1
FIG 1 ANKA(BALB/c) and NK65(C57BL/6) infections have similar disease courses that are distinct from that of ANKA(C57BL/6). Mice were infected with 106 iRBCs from the relevant parasites. (a) Kaplan Meier graph showing the survival percentage for each group through the course of the disease. Each group contains 20 infected mice. Comparisons between two groups were made using the 95% confidence interval (CI) of hazard ratios (log rank test): ANKA(C57BL/6)/ANKA(BALB/c) CI, 1.7 to 8.494, ANKA(C57BL/6)/NK65(C57BL/6) CI, 1.7 to 8.494, NK65(C57BL/6)/ANKA(BALB/c) CI, 0.835 to 3.212. (b and c) Close-up images of hematoxylin and eosin-stained cerebellum (b) and olfactory bulb (c) sections taken at day 6 post infection. Arrowheads point to sites of local hemorrhage. White scale bars in the lower-left corner represent 200 μm. Images represent three brains per group.
We further characterized the progression of blood-stage malaria in ANKA(C57BL/6), ANKA(BALB/c), and NK65(C57BL/6) via regular blood checks for progression of parasitemia and hemoglobin levels. P. berghei ANKA-infected mice [ANKA(BALB/c) and ANKA(C57BL/6)], regardless of their host, showed a faster increase in parasitemia than NK65(C57BL/6) within the first few days p.i. (Fig. 2a), which may suggest an inherent proliferation advantage for P. berghei ANKA compared to P. berghei NK65. However, due to ECM-mediated mortality by day 7 p.i., no further measurements could be made from ANKA(C57BL/6). Later in the infection, around 6 days p.i., parasitemias continued to increase, with ANKA(BALB/c) reaching higher levels of parasitemia (60%) than NK65(C57BL/6) (30%). The higher levels of parasitemia in ANKA(BALB/c) than in NK65(C57BL/6) may contribute to the slightly higher clinical scores in ANKA(BALB/c) parasites despite the lack of ECM phenotype. Reductions in hemoglobin levels were comparable between ANKA(BALB/c) and NK65(C57BL/6), especially in later stages of the disease, despite higher starting hemoglobin levels in BALB/c mice prior to infection (Fig. 2b). The progressive decrease in hemoglobin levels in ANKA(BALB/c) and NK65(C57BL/6) is in line with previous observations which report anemia as the cause of death in these non-ECM cases (34, 3639).
FIG 2
FIG 2 ANKA(BALB/c) and NK65(C57BL/6) infections cause mortality due to anemia. Mice were infected as outlined in Fig. 1. (a and b) Changes in parasitemia (percentage of infected RBC among total RBC) (a) and hemoglobin concentration (b) were measured through routine blood checks. Each circle represents an individual animal. ns, P > 0.05; *, 0.01 < P ≤ 0.05; **, 0.001 < P ≤ 0.01; ***, 0.0001 < P ≤ 0.001. Comparisons between three groups were made using one-way analysis of variance (ANOVA) with Tukey’s test. Comparisons between two groups were made using Welch’s t test. The data represent two experiments.

ANKA(BALB/c) and NK65(C57BL/6) infections trigger a stronger immune response than ANKA(C57BL/6) infection.

Having observed differences in the development of disease symptoms and progression of parasitemias (Fig. 1 and Fig. 2), we suggested the possibility that ANKA(C57BL/6), ANKA(BALB/c), and NK65(C57BL/6) infections trigger the host immune response differently. We analyzed spleen samples collected on day 6 p.i. and characterized the changes in immune cell numbers and their activation/differentiation states (Fig. 3). The ANKA(BALB/c)-, and NK65(C57BL/6)-infected groups had similar numbers of total B cells (Fig. 3a), CD4+ T cells (Fig. 3b), and CD8+ T cells (Fig. 3c) in their spleens. In contrast, ANKA(C57BL/6) had significantly lower numbers of all three cell types, indicating differences in immune responses. We analyzed B cell differentiation in terms of the expansion of cells in the germinal center (GC) and plasma cell (PC) lineages (Fig. 3d to g). Absolute numbers of GC and PC lineage cells were similar for ANKA(BALB/c) and NK65(C57BL/6), which were uniformly higher than those of ANKA(C57BL/6) (Fig. 3d and f). In addition to higher absolute numbers for GC and PC lineage cells for ANKA(BALB/c), and NK65(C57BL/6), the percentage of GC and PC lineage cells within the parent population B cells and live splenocytes, respectively, also increased compared to those of ANKA(C57BL/6) (Fig. 3e and g). These observations rule out the possibility that increases in absolute numbers of GC and PC are merely a reflection of the overall increase in total B cell numbers rather than B cell differentiation. In line with these observations of B cell differentiation, in ANKA(BALB/c) and NK65(C57BL/6) infections compared to ANKA(C57BL/6) infections, follicular helper T cells (Tfh) and activated CD8+ T cells were higher in both as absolute numbers and as percentages of total CD4+ and CD8+ T cells, respectively (Fig. 3h to k). Lastly, immunohistochemistry analysis of spleen sections showed, in addition to the lower GC numbers in ANKA(C57BL/6) (Fig. 3d and e), that GC cells failed to organize in proper clusters (Fig. 3l). Altogether, our findings show an inefficient and low-grade immune response against ECM-causing ANKA(C57BL/6) compared to non-ECM-causing groups.
FIG 3
FIG 3 ANKA(BALB/c) and NK65(C57BL/6) infections induce a robust immune response. (a to l) Mice were infected with parasites as outlined in Fig. 1. Spleens were harvested on day 6 postinfection, and development of the immune response was characterized using flow cytometry (a to k) or immunohistochemistry (l). Graphs show the absolute numbers of each cell group. Circles represent individual mice, and dotted lines refer to means (a to d, f, h, and j). (e, g, e, and k) Representative flow cytometry contour plots showing the frequencies of GCs among B cells (e), plasma cells among viable splenocytes (g), Tfh cells among CD4+ T cells (i), and activated CD8+ T cells among total CD8+ T cells (k) are shown. (l) Spleen sections stained with PNA and IgM to visualize localization and architecture of GCs in infected mice. ns, P > 0.05; *, 0.01 < P ≤ 0.05; **, 0.001 < P ≤ 0.01; ***, 0.0001 < P ≤ 0.001 (one-way ANOVA with Tukey test). Experiments were repeated three times.

The host has a strong influence on parasite gene expression.

Thus far our data showed that ANKA(BALB/c) and NK65(C57BL/6) infections show similarities in disease course as well as in the immune responses they trigger. In contrast ANKA(BALB/c) and ANKA(C57BL/6) differed dramatically in each aspect of the disease (Fig. 1 to 3). To reveal whether these observations can be related to differential parasite gene expression, we performed RNA sequencing on blood obtained from infected mice on day 6 p.i. Principal-component analysis (PCA) of the RNA sequencing showed overlapping patterns for ANKA(BALB/c) and NK65(C57BL/6) infections, whereas ANKA(C57BL/6) clustered at a distinct location (Fig. 4a and b). Similarly, three-way comparative analysis of infected groups showed similar parasite gene expression patterns with subtle differences between ANKA(BALB/c) and NK65(C57BL/6), whereas ANKA(BALB/c) versus ANKA(C57BL/6) and ANKA(C57BL/6) versus NK65(C57BL/6) showed major differences in both the number of differentially expressed genes and their expression patterns (Fig. 4c and d) (Data Set S1, Fig. S1b to d). We performed a thorough gene ontology pathway analysis of the transcriptome and found that the biological processes that were differentially affected between ANKA(C57BL/6) and the other groups were mainly related to parasitic motility in the host, protein turnover, exit from host cells, and parasite metabolism (Fig. 5a and b). In terms of molecular function, processes related to the catalytic activity of various enzymes, oxidoreductase activity, and hydrolase and peptidase activity were predominantly different between ANKA(C57BL/6) and the other groups (Fig. 5c and d). Neither biological process-focused pathway analysis nor molecular function-focused pathway analysis revealed a significant difference in parasite behavior between ANKA(BALB/c) and NK65(C57BL/6), indicating that these two groups are indeed highly similar. This may explain similarities in disease progression and outcome as observed in Fig. 1 to 3. Nevertheless, 70 genes were revealed to be differentially expressed between ANKA(BALB/c) and NK65(C57BL/6). The majority of these differences (38 of 70) belonged to the interspersed repeat (IR) of the P. berghei IR (BIR) gene family (P. berghei strain-specific nomenclature of genes of Plasmodium IR family [PIR] family [Data Set S1]) . PIR, the largest gene family in Plasmodium, is composed of genes that are thought to encode proteins expressed on iRBCs and are responsible for antigenic variation of parasite (40). Among the remaining differentially expressed genes, 4 of 70 belong to the fam-a and 6 of 70 belong to the fam-b gene families, which like PIRs, are thought to code iRBC surface proteins that play a role in immune evasion, antigenic variation, and entry of the parasite into host RBCs (33, 41, 42).
FIG 4
FIG 4 The host determines parasite gene expression. Mice were infected as outlined in Fig. 1, and blood samples were taken at day 6 postinfection. Changes in parasite gene expression were analyzed by transcriptome sequencing (RNA-seq) carried out on 6 blood samples per each group. (a and b) 3D principal-component analysis (a) and a scree plot (b) are shown. (c and d) Differentially expressing parasite genes (DEG)s between groups are shown as numbers of DEGs in a Venn diagram (c) and as a heat map (d).
FIG 5
FIG 5 Gene ontology pathway analyses reveal parasite biological pathways that are influenced by the host. (a to d) Gene ontology analyses were performed on the RNA-seq experiment data shown in Fig. 4 focusing on differentially regulated biological processes (a and b) and molecular functions (c and d). Dashed vertical cutoff lines are drawn at P = 0.05, P = 0.01, and P = 0.001 (Kolmogorov-Smirnov P value).

DISCUSSION

In this article, we provide evidence that in ECM-resistant BALB/c hosts, the ECM-causing P. berghei ANKA strain behaves more similarly to the non-ECM-causing P. berghei NK65 strain in susceptible C57BL/6 host than the P. berghei ANKA infections in C57BL/6 hosts. We showed that ANKA(BALB/c) and NK65(C57BL/6) infections have overlapping disease courses, both having no symptoms of ECM, and mortality occurring in 21 days due to severe anemia. We also show that unlike ANKA(C57BL/6), which failed to trigger a strong immune response, ANKA(BALB/c) and NK65(C57BL/6) infections induce prominent B and T cell activation/differentiation. The Plasmodium berghei infection model is fatal regardless of the host and parasite strain. However, our data showing a strong systemic immune response against the pathogens ANKA(BALB/c) and NK65(C57BL/6) may, in part, be linked to why ECM does not develop under these conditions.
CM is an important public health problem, especially among young children living in sub-Saharan Africa. Despite ever-growing scientific research, it remains unclear why only a small proportion, approximately 1%, of uncomplicated malaria cases progress to CM and what determines survival. Animal models have been widely used to overcome the limitations of studying CM using human samples. Studies of ECM in mice have revealed that complex interactions between Plasmodium parasites and the host immune system play a role in the disease pathogenesis. For instance, while CD8+ T cells are essential for clearing the parasite (43, 44), their accumulation in the brain is linked to the development of ECM (20, 45). Similarly, multiple soluble mediators and humoral factors have been linked to both antimalarial host defense and triggering of brain pathogenesis (34, 4648). Separate studies showed that very closely related Plasmodium strains such as P. berghei NK65 and P. berghei ANKA can have dramatic differences in their ability to trigger ECM (32). Therefore, it is apparent that CM is mediated by factors related to both parasite and host.
In terms of how hosts modulate disease progression, we revealed that hosts have a strong influence on parasite gene expression turning an ECM-causing parasite into a non-ECM-causing one. Our analysis of differentially expressed genes between infection groups showed that ANKA(BALB/c) and NK65(C57BL/6) differed from ANKA(C57BL/6), with 989 and 772 genes, respectively, while there were only 70 genes differentially expressed between ANKA(BALB/c) and NK65(C57BL/6). These data explain why ANKA(BALB/c) and NK65(C57BL/6) had so many similarities during the disease progression and why ANKA(C57BL/6) behaved differently. With in-depth pathway analyses, we further revealed that major differences in parasite gene expression between non-ECM- and ECM-causing conditions cluster around biological processes related to parasite metabolism, protein turnover, and parasite motility within the host. Therefore, it is apparent that the BALB/c host modulates P. berghei ANKA gene expression related to these processes in a way that it is comparable to gene expression in P. berghei NK65, and thus P. berghei ANKA is no longer able to trigger ECM. Likewise, the same set of transcriptional alterations are responsible for the longer disease course characterized by a stronger immune response seen in both ANKA(BALB/c) and NK65(C57BL/6). Despite the remarkable similarity we observed in parasite gene expression between ANKA(BALB/c) and NK65(C57BL/6), there are still 70 differentially expressed genes. Among these genes, 48 of 70 belong to the BIR, fam-a, or fam-b gene families, which are collectively thought to regulate antigenic variation and host-pathogen interaction. These genes were recently shown to express at different times during the blood stage of the parasite and may account for slight variation in the distribution of ring, trophozoite, and schizont forms (33). Altogether, these changes might be a result of adaptation of parasites to different characteristics of C57BL/6 and BALB/c hosts and may account for slight differences between disease courses.
In conclusion, through our comprehensive multidimensional comparative analyses of ANKA(C57BL/6), ANKA(BALB/c), and NK65(C57BL/6) infections, we revealed, in great detail, how the host can modulate parasite behavior, dictating the outcome of malaria disease. Our observations in mouse studies can also be linked to human CM in terms of showing how important host genetic background is in determining whether blood-stage malaria progresses to cerebral disease. Our studies highlight the complex nature of ECM, with hundreds of parasite genes altering their expression between ECM-causing and non-ECM-causing conditions. Nevertheless, the genes and pathways we identify here will facilitate further research on the pathogenesis of the disease.

MATERIALS AND METHODS

Mice and parasites.

For all experiments, female mice aged 7 to 8 weeks old were used. BALB/c (stock no. 000651) and C57BL/6 mice (stock no. 000664) were purchased from Jackson Laboratories and were maintained in the National Institute of Allergy and Infectious Diseases (NIAID) animal facility according to Animal Care and Use Committee standards. For parasite infections Plasmodium berghei NK65 (NYU strain) and Plasmodium berghei ANKA strains were used.

Ethics statement.

Live animal experiments were carried out according to NIAID-approved Institutional Animal Care and Use Committee (IACUC) protocol LIG-2E and the Ohio State University-approved IACUC protocol 2022A00000061.

Reagents.

The following anti-mouse antibodies and other fluorescent markers were used for parasitemia checks, flow cytometry analysis, and immunohistochemistry: CXCR5 (BV421-BioLegend), CD4 (BV605-BioLegend), CD8 (Percp Cy 5.5-BioLegend), PD1 (PE-BioLegend), ICOS (AF647-BioLegend), CD44 (AF700-BioLegend), GL7 (e660-Thermo Fisher), CD95 (AF488-BioLegend), CD19 (BV650-BioLegend), CD138 (PE-BioLegend), Live/Dead near IR (Thermo Fisher), CD16/32 (Fc block-BioLegend), B220 (AF700-BioLegend), CD45 (APC-BioLegend), Ter119 (APC Cy7- BioLegend), Peanut agglutinin (PNA) (biotin-Vector Labs), IgM-(eBioscience).

Infection of animals with parasitized RBCs.

Both P. berghei ANKA and P. berghei NK65 parasite stocks were originally grown in C57BL/6 mice. To avoid a non-parasite-specific immune response against infected C57BL/6 RBCs in BALB/c animals, the initial P. berghei ANKA stock was divided into two and injected into both C57BL/6 and BALB/c donor animals as outlined in Fig. S1a. These parasites were passaged three times in the respective mouse strains in order to fully adapt the parasite into the host. This strategy also ensured using comparable passage numbers for all animals. Following this adaptation, blood drawn from the third donor, once parasitemia reached to the 5 to 10% range, was diluted in phosphate-buffered saline and injected intraperitoneally into experimental animals at 106 iRBCs per mouse.

Monitoring disease progression in infected animals.

Progression of blood-stage parasites was monitored by routine parasitemia checks using blood smear- and flow cytometry-based methods described in detail earlier (49, 50). Hemoglobin levels were measured using a HemoCue Hb201 analyzer. Disease-related worsening of clinical symptoms was analyzed using a 10-point clinical scoring system as described earlier (32). A total clinical score of at least 6 and hemoglobin levels of 2.5 g/dL or below were determined as endpoint criteria. Animals meeting one or both criteria were euthanized. Parasitemia and hemoglobin level analyses were stopped after day 14 postinfection (i) because significantly lowered hemoglobin levels at this point made reliable parasitemia analyses nonfeasible and (ii) in order to prevent the potential impact of blood draws to survival analyses due to the vulnerable state of the infected animals.

Flow cytometry and tissue section analyses.

Spleens harvested from infected animals were meshed, and RBCs were removed using ammonium-chloride-potassium (ACK) buffer (Lonza). Cells were stained with fluorochrome-conjugated antibodies and analyzed in a BD X20 flow cytometer. Flow cytometry data were analyzed in FlowJo software v10. For histological analyses, whole brains and spleens were harvested, fixed in 10% buffered formalin, and embedded in paraffin. Brain sections were stained with hematoxylin and eosin (H&E). Spleen sections were stained with PNA and IgM and visualized using the strategy outlined in reference 48.

RNA sequencing and data analysis.

Mouse cheek blood samples were mixed with TRIzol LS (Thermo Fisher) in a 1:3 ratio, and RNA was isolated according to the manufacturer’s guidelines. Using a drop of the same blood sample, blood smears were made, and the distribution of trophozoite, schizont, and ring forms of blood-stage parasites were quantified. Samples with comparable distributions of these forms between infection groups were selected for next-generation sequencing (NGS). Six samples per condition containing 4 μg of total RNA were used for TruSeq mRNA library preparation (Illumina) after being treated with a Globin-Zero gold rRNA removal kit (Illumina). A Bioanalyzer DNA 1000 chip was used to fragment-size libraries. A Kapa Library Quant kit (Illumina) and Universal quantitative PCR (qPCR) mix (Roche) were used to quantitate libraries to facilitate the generation of a normalized, 2-nM multiplexed pool. This pool was clustered around two RAPID flow cell lanes at 10-pM concentrations. Paired-end sequencing was carried out on an Illumina HiSeq instrument (100 cycles from fragment ends plus 7 more cycles to sequence the index).
Cutadapt v1.12 (51) was used to remove adapter sequences from raw NGS data. Reads were then trimmed and filtered (35 bp or longer) using a FastX tool kit v0.0.14 (Hannon Lab, Cold Spring Harbor Laboratory). HISAT2 v2.0.5 (52) set to report only matched pairs was used for mapping. DESeq2 (10.18129/B9.bioc.DESeq2) was then used to generate the final transcripts based on combined replicates and differentials for each comparison.

Gene Ontology (GO) term enrichment.

The GO term annotation file for Plasmodium berghei was acquired from the PlasmoDB database (June 2022 release). Enrichment was performed as explained earlier (53) using R software v4.2.1 with the topGO package (54).

Data analysis.

Heatmaps were created using R software v4.2.1 with the heatmap2 package. Statistical analyses were carried out using GraphPad Prism v7 software.

Data availability.

The sequencing data have been deposited in NCBI’s Gene Expression Omnibus and are accessible through GEO series accession number GSE215359.

ACKNOWLEDGMENTS

This study was funded by intramural research grants from the National Institute of Allergy and Infectious Diseases allocated to Susan K. Pierce and research funds from the Ohio State University College of Medicine allocated to Munir Akkaya.
We declare no conflicts of interest.
M.A. designed the project. M.A., M.P., C.K.C., A.S., B.P.T., M.V.P., and C.Q. carried out the experiments. M.A., C.K.C., M.V.P., D.S., P.L.C., S.M.G., S.K.P., and L.H.M. analyzed the data. M.A. wrote the manuscript. S.K.P. edited the manuscript. M.A. and S.K.P. secured funding.

Footnote

This article is a direct contribution from Susan K. Pierce, a Fellow of the American Academy of Microbiology, who arranged for and secured reviews by Michelle Wykes, QIMR Berghofer MRI, and Marcelo Jacobs-Lorena, Johns Hopkins University.

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Information & Contributors

Information

Published In

cover image mBio
mBio
Volume 14Number 225 April 2023
eLocator: e03391-22
Editor: L. David Sibley, Washington University in St Louis School of Medicine
PubMed: 36852995

History

Received: 2 February 2023
Accepted: 6 February 2023
Published online: 28 February 2023

Keywords

  1. Plasmodium
  2. cell-mediated immunity
  3. cerebral malaria
  4. host-parasite relationship
  5. malaria

Contributors

Authors

Clare K. Cimperman
Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA
Mirna Pena
Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA
Sohret M. Gokcek
Division of Rheumatology and Immunology, Department of Internal Medicine, The Ohio State University College of Medicine, Columbus, Ohio, USA
Department of Microbial Infection and Immunity, The Ohio State University College of Medicine, Columbus, Ohio, USA
Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, College of Medicine, The Ohio State University, Columbus, Ohio, USA
Brandon P. Theall
Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA
Meha V. Patel
Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA
Anisha Sharma
Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA
ChenFeng Qi
Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA
Daniel Sturdevant
Research Technologies Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, Hamilton, Montana, USA
Louis H. Miller
Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA
Patrick L. Collins
Department of Microbial Infection and Immunity, The Ohio State University College of Medicine, Columbus, Ohio, USA
Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, College of Medicine, The Ohio State University, Columbus, Ohio, USA
Susan K. Pierce
Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA
Munir Akkaya [email protected]
Division of Rheumatology and Immunology, Department of Internal Medicine, The Ohio State University College of Medicine, Columbus, Ohio, USA
Department of Microbial Infection and Immunity, The Ohio State University College of Medicine, Columbus, Ohio, USA
Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, College of Medicine, The Ohio State University, Columbus, Ohio, USA

Editor

L. David Sibley
Editor
Washington University in St Louis School of Medicine

Notes

The authors declare no conflict of interest.

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