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Infect Immun. 2005 September; 73(9): 6091–6100.
PMCID: PMC1231079

Genome-Wide Expression Profiling in Malaria Infection Reveals Transcriptional Changes Associated with Lethal and Nonlethal Outcomes


High-density oligonucleotide microarrays are widely used to study gene expression in cells exposed to a variety of pathogens. This study addressed the global genome-wide transcriptional activation of genes in hosts infected in vivo, which result in radically different clinical outcomes. We present an analysis of the gene expression profiles that identified a set of host biomarkers which distinguish between lethal and nonlethal blood stage Plasmodium yoelii malaria infections. Multiple biological replicates sampled during the course of infection were used to establish statistically valid sets of differentially expressed genes. These genes that correlated with the intensity of infection were used to identify pathways of cellular processes related to metabolic perturbations, erythropoiesis, and B-cell immune responses and other innate and cellular immune responses. The transcriptional apparatus that controls gene expression in erythropoiesis was also differentially expressed and regulated the expression of target genes involved in the host's response to malaria anemia. The biological systems approach provides unprecedented opportunities to explore the pathophysiology of host-pathogen interactions in experimental malaria infection and to decipher functionally complex networks of gene and protein interactions.

The incidence and severity of malaria infection continue to be on the rise in many parts of the world (33). The situation is exacerbated by the emergence of multidrug resistance to Plasmodium falciparum and Plasmodium vivax, the two most important human malaria parasites. Malaria is a complex infectious disease in which the host response to infection is dependent upon the parasite stage, parasite virulence factors, and host genetic background. A detailed understanding of the molecular processes which regulate transcriptional activity and gene networks involved in the pathogenesis of or protection from disease may provide insights into protective mechanisms of immunity that aid in the design of more effective vaccines.

Animal models of malaria are particularly useful in unraveling such protective mechanisms, since they provide flexibility in terms of experimental design and sample collection. The murine malaria parasite, Plasmodium yoelii, has numerous similarities to human P. falciparum and P. vivax and is a useful model for the comparison of differences in gene expression differences between lethal and nonlethal infections. The parasite has evolved two distinct strains, presumably due to the evolution of different pathophysiologic pathways. During the asexual blood stage infection, P. yoelii XNL parasites invade primarily reticulocytes and the infection is self-limiting. The sister strain, P. yoelii XL, invades all forms of murine erythrocytes, and the resultant high parasitemias cause a lethal infection (13, 17, 36). A consequence of infection is a profound anemia, the cause of which is not fully understood but involves both the destruction of parasitized erythrocytes and a dyserythropoiesis which impedes the production of sufficient numbers of newly formed red cells (18, 28).

During murine malaria infection, the spleen becomes the primary site of erythrocyte production and is involved in the removal of both dead parasites and malaria-infected red cells. As red cells are destroyed by cycles of parasite invasion and erythrocyte rupture, the host response to the evolving anemia differs in animals infected with either the lethal or nonlethal P. yoelii strain. Previous histologic studies have shown that the spleens of animals infected with 17XNL parasites erect a cellular barrier that functions to isolate newly produced reticulocytes away from ongoing infection. In contrast, a competent blood-spleen barrier fails to develop in animals infected with the lethal 17XL strain, resulting in phagocytosis of parasitized erythrocytes and late-stage erythroblasts (30-32). The spleen plays critical roles in establishing immune responses to infection, particularly the suppression of B-cell proliferative responses in animals infected with nonlethal forms of P. yoelii (29).

The primary objective of this study was to analyze the transcriptional changes in animals infected with either a nonlethal or lethal variant of P. yoelii malaria in order to discover molecular processes and pathways that correlate changes in gene expression with outcome of infection. Two independent but complementary approaches were used: (i) we studied transcriptional patterns during the course of a nonlethal 17XNL infection as the parasitemia increased and then decreased after reaching a peak parasite density of 50%, and (ii) we compared gene expression changes between the lethal and nonlethal P. yoelii infections at the identical stage of parasite density, which revealed specific gene ontology (GO) functional groups that differed with respect to clinical outcome of infection. We have identified three distinct patterns of global genetic signatures in early infection that are related to the host's response to regulatory and target gene expression of erythropoiesis in response to anemia, metabolic perturbations in the glycolytic enzyme pathway, and B-cell immune responses that distinguish lethal from nonlethal P. yoelii infections.



Female BALB/C mice 6 to 12 weeks in age were obtained from Jackson Laboratories (Bar Harbor, Maine) and were used under an institutionally approved protocol.

Experimental design.

Frozen stocks of 17XNL and 17XL P. yoelii-infected erythrocytes were thawed and used to infect donor mice. On day 0, 24 mice were infected intravenously with 1 × 106 17XNL parasites and 16 mice with 1 × 106 17XL parasites. Six mice were injected with phosphate-buffered saline, and the mean gene expression value from each spleen served as the control baseline reference for all other samples. Parasite density in each animal was checked daily by direct microscopic examination of thin blood films and recorded as the percent infected erythrocytes. Mice infected with the 17XL strain generally succumb to infection 7 to 10 days postinfection, while mice infected with the 17XNL strain reach maximum parasitemia (50%) at approximately around day 10, followed by a rapid clearance of parasites and complete resolution of infection by day 17. For mice infected with 17XNL parasites, six mice were sacrificed at each successive time interval: at 24 h postinfection and on days 4 (5% parasitemia), 9 (25% parasitemia), 10 (50% parasitemia), 14 (25% parasitemia), and 17 (<1% parasitemia). For animals infected with 17XL parasites, four mice were sacrificed at 24 h postinfection and on days 3 (5% parasitemia), 5 (25% parasitemia), and 7 (50% parasitemia) (Fig. (Fig.1A).1A). Six noninfected control animals were sacrificed 24 h after all the mice received either the 17XNL or 17XL infection. Spleens were removed, immediately snap frozen, and stored at −70°C until samples were processed.

FIG. 1.
Course of infection and differential gene expression in P. yoelii infection. (A) Kinetics of parasite replication in 17XNL and 17XL infection in mice. Error bars indicate standard deviations. (B) Number of differentially expressed genes (P < 0.005) ...

Tissue preparation and RNA isolation.

Fifty to 100 mg of spleen tissue was pulse homogenized with a tissue sonicator in 1 ml of Tri-Reagent (Molecular Research Center, Cincinnati, OH), and RNA was extracted according to the manufacturer's instructions. Total RNA was stored at −70°C. Integrity of total RNA was examined via gel electrophoresis. Poly(A) RNA purification was performed using the Ambion MicroPoly(A)Pure kit (Ambion, Austin, TX).

Sample preparation and GeneChip analysis.

Preparation of cDNA, in vitro transcription, staining, and scanning of Affymetrix U74Av2 GeneChips containing 12,489 probe sets and 8,305 genes (Affymetrix, Santa Clara, CA) were carried out essentially as described previously (27). Each spleen sample from uninfected and infected mice at each parasite density level was processed and hybridized individually to yield a data set of 58 total GeneChips for analysis. Scanned images were analyzed with Affymetrix MAS 5.0 to create .cel and Pivot data files. Two criteria were used to determine chip quality: the scaling factor determined by Affymetrix MAS 5.0 with the target signal intensity being set to its default (500) and the array outlier percentage determined by dChip version 1.3. GeneChip .cel files were normalized at the probe level by using the robust multichip average (RMA) method (12).

Differentially expressed genes were identified by a Student's t test comparing groups of mice at specified parasite density levels relative to spleen samples from six uninfected control mice, using a cutoff significance level set at a P value of <0.005. This significance value was chosen to minimize the false discovery rate (<1% by significance analysis of microarrays) (26) but to be generous enough to include a larger set of genes with functionally distinct gene expression programs. The data for each gene probe on the array were expressed as the log2 ratio of normalized fluorescence intensity of the sample and the average expression intensity from six uninfected control mice. Hierarchical cluster analysis of microarray data sets was performed using Cluster and Treeview software ( (10). Self-organizing maps and principal-component analysis (PCA) were performed with GeneLinker Gold software (Predictive Patterns Software, Kingston, Ontario, Canada). To assign gene ontology-annotated terms to differentially regulated sets of statistically significant genes or to groups of coexpressed genes detected in hierarchical clusters, the web-based tools Onto-Express ( (9) and dCHIP (http://biosun/ (15) were used.


We have used gene expression profiling from multiple biological replicates to discover the biological functions of sets of statistically significant differentially expressed genes in order to acquire a better understanding of the sequence of molecular events in hosts that either succumb to or self-resolve their infections with blood stage malaria parasites. Because of the differences in the kinetics of parasite growth between lethal and nonlethal infections, changes in gene expression were compared based upon equivalent parasite density levels (parasite density-dependent comparison) and not the same day postinfection (time-dependent comparison) (Fig. (Fig.1A).1A). The justification for this approach was twofold. First, we sought to avoid an experimental design bias which would have accentuated differences in transcription based on time-dependent comparisons with lethally infected mice at a high parasitemia compared to nonlethal infections at a lower parasite density in mice sacrificed on the same day postinfection. Second, the similarity in gene expression between the two infections is greater than the differences, as demonstrated by the concordance in the expression patterns for hundreds of genes shared between 17XL and 17XNL infection as analyzed with equivalent parasite densities (see Fig. S1 in the supplemental material), thus justifying the study design to detect small but statistically significant changes between 17XL and 17XNL infection that are parasite density dependent.

Patterns of gene expression in 17XL and 17XNL infection varied with the intensity of parasitemia (Fig. (Fig.1B).1B). PCA was used to reveal large differences in transcript abundance between groups of samples. PCA is an unsupervised clustering method that reduces dimensionality of data from which a large number of variables (genes) are interrelated. PCA identifies trends in the data that define distinct clusters by performing a covariance analysis between factors. Three-dimensional PCA plots often place objects that are similar next to each other and are reflective of the differences in gene expression in mice at various parasite density levels. The greatest change in gene expression relative to baseline in both the lethal and nonlethal infections occurred as the parasite density rose during two consecutive time intervals (from 0 to 5% and from 5 to 25% parasitemia), while significant changes in transcription continued to occur as the parasitemia increased to 50% in 17XL-infected mice (Fig. 1C and D).

Regardless of the ultimate outcome of an infection, transcriptional changes in innate immune genes occur within hours after a host senses an intact or degraded parasite. Within 24 h of infection and prior to the time parasites are detected on blood smears, a number of genes and associated gene ontology functional groups involved in innate immunity, inflammation, defense response, and cytokine signaling are induced in mice infected with either the 17XNL or 17XL strain (Fig. (Fig.2A).2A). Such genes include that for tumor necrosis factor alpha (TNF-α) and genes involved in antigen presentation and T-cell activation. A larger set of differentially expressed genes, including cytokine genes (for interleukin-1β, interleukin-6, gamma interferon, and TNF-α), chemokine genes, interferon-induced genes, and genes critical for adaptive immune responses were similarly induced by both lethal and nonlethal parasites as the parasite density rose to 5% (Fig. (Fig.2B).2B). Many transcriptional changes precede the action of inflammatory cytokines such as TNF-α and gamma interferon and have been shown to vary with parasite density and return to baseline upon resolution of infection (16, 19, 25). The changes in expression in genes associated with the defense response in murine malaria were similarly observed in an early infection in nonhuman primates infected with the nonlethal parasite Plasmodium cynomolgi (35). As the infection progressed and the parasitemia rose in 17XL- and 17XNL-infected mice, albeit at different rates, identical patterns of expression for hundreds of differentially expressed genes were observed in both infections, which were independent of whether animals ultimately died or survived their infection (see Fig. S1 in the supplemental material).

FIG. 2.
Concordance in gene expression of immune response genes between lethal 17XL and nonlethal 17XNL infection. The fold change in intensity of differentially expressed genes is depicted as a heat map at 24 h postinfection (A) and at 5% parasitemia (B) for ...

Gene ontology annotation of differentially expressed genes.

Multiple biological processes and molecular functions of GO annotations were derived from gene clusters identified from lists of significantly differentially expressed genes from 17XNL infection by using the web-based bioinformatics tool Onto-Express. The level of gene expression, which paralleled the rise and decline in parasitemia, returned to basal transcriptional activity upon resolution of the infection (data not shown). A representative set of functionally annotated genes that were separated into two clusters of up-regulated or down-regulated genes by self-organizing map analysis is shown in Fig. 3A and C (the full set of overrepresented GO terms is found in Table S1 in the supplemental material). A variety of overrepresented biological functions associated with ATP binding, regulation of transcription, cell cycle, DNA replication, and mRNA processing were observed from genes that were induced during infection (Fig. (Fig.3A).3A). Such genes play roles in cell growth and lymphocyte proliferation and activation and are important for metabolic and immunologic processes associated with infection. Clusters of genes which function in response to the shock and stress of a fever-inducing illness, such as those involved in heat shock protein activity (Fig. (Fig.3B),3B), or which are involved in chemotaxis and chemokine activation (Fig. (Fig.3D)3D) for cells that migrate into and out of lymphoid tissues are tightly regulated, as supported by the loss of transcriptional activation when the host clears infection. Importantly, some genes associated with chemokine activity are induced during infection (Fig. (Fig.2B),2B), while other statistically significant overrepresented chemokine genes detected by Onto-Express are consistently repressed (Fig. (Fig.3D3D).

FIG. 3.
Functional annotation of differentially expressed genes in 17XNL infection. (A and C) Pie charts depict the representative number of overrepresented GO terms from genes up-regulated (A) or down-regulated (C) during infection. The size of each slice represents ...

Since the majority of differentially expressed genes in P. yoelii infection occur during ascending parasitemia, subsets of genes were examined for significantly overrepresented GO functional groups by capturing only those genes which are differentially expressed at two consecutive time intervals (from 24 h postinfection to 5% parasitemia and from 5% to 25% parasitemia). Groups of 10 or more differentially expressed genes that represent functions attributed to gene ontology terms were identified in genes that were induced (see Table S2 in the supplemental material) relative to the mean gene expression from uninfected mice. Some functional groups of up-regulated genes included cell cycle, DNA replication, nucleus, and nucleotide binding clusters that were overrepresented during two consecutive time intervals in lethal and nonlethal infections (see Table S2 in the supplemental material). In contrast, some GO functional terms, including immune response genes and proteasome core complex genes, were statistically overrepresented only during the early phase of infection (0 to 5% parasitemia) when the host initially encountered the pathogen. As the parasitemia rose from 5 to 25%, significant divergence and dissimilarity in the extent of gene ontology terms were noted in 17XNL-infected mice (13 overrepresented GO terms) compared to the lethal infection (one GO term, i.e., cytokinesis) (see Table S2 in the supplemental material). Whether the dissimilarity in the kinetics of parasite replication between the two models accounts for the differences in gene ontology annotations awaits further investigation.

Differential expression of genes in erythropoiesis.

Anemia is a severe consequence of experimental and human malaria infection, and the mechanism comprises both elements of red cell destruction and ineffective erythropoiesis. As the spleen is a major site for erythrocyte production during murine malaria infection, the kinetics of red cell production vis-a-vis parasite clearance is an important element in the host's response to anemia (6, 30). The expression of a number of transcription factors and their target genes associated with erythrocyte function, iron metabolism, heme biosynthesis, and erythrocyte transcriptional regulation was examined. Early in 17XNL and 17XL infection there was a down-regulation of genes that encode erythrocyte membrane proteins (glycophorin A, band 3), the erythropoietin receptor, iron metabolism proteins (transferrin receptors), and heme binding proteins (Fig. (Fig.4A).4A). However, as the parasitemia increased from 5% to 25%, the transcript abundance of genes involved in erythropoiesis was consistently and dramatically induced in all mice infected with the nonlethal P. yoelii strain, while gene expression remained at or below basal levels in lethally infected mice relative to uninfected controls (Fig. (Fig.4A).4A). Remarkably, all eight of the genes encoding enzymes involved in the biosynthesis of heme, including the rate-limiting enzyme aminolevulinic acid synthase, followed an identical expression profile that was observed for genes encoding red cell membrane receptors and iron metabolism proteins (Fig. (Fig.4B).4B). The mean transcriptional activity for mice infected with the 17XNL strain for each of the genes involved in the heme biosynthetic pathway was significantly induced (mean 2.5-fold increase) compared to that for mice infected with the 17XL strain.

FIG. 4.
Differential gene expression in erythropoiesis. (A) Centroid plot of mean expression of 13 genes involved in iron transport and erythrocyte membrane proteins, with heat maps showing fold change in transcript abundance (columns represent individual mice). ...

The coordination of gene expression with gene regulation is tightly controlled and influences the expression of many genes involved in the pathological manifestations of disease. Analysis of the microarray data revealed a group of transcription factors crucial for erythroid propagation and terminal differentiation of erythroid cells, such as Kruppel-1, Kruppel-3, GATA-1, FOG, TAL-1, LMO2, and NF-E2, that were significantly induced (mean, 2.3-fold induction) in nonlethal malaria but remained statistically unchanged from baseline in lethal malaria (Fig. (Fig.4C4C).

Differential expression of genes regulating glycolysis.

Metabolic acidosis resulting from the accumulation of lactate is an important prognostic indicator for the severity of malaria and has been implicated in the pathogenesis of human P. falciparum and murine Plasmodium berghei infection (8). The transcriptome of glycolytic pathway genes in 17XNL- and 17XL-infected mice at different stages of infection was examined. Each of the 10 genes encoding enzymatic reactions involved in the glycolytic pathway was significantly up-regulated early in 17XL and 17XNL infection (Fig. (Fig.5),5), and mice infected with the lethal 17XL strain showed increased gene expression for all the enzymes throughout infection. Conversely, in the nonlethal infection, a transient initial increase in expression was followed by a dramatic suppression of glycolytic enzyme transcription in the interval of time that the parasitemia rose from 5% to 25% (Fig. (Fig.55).

FIG. 5.
Expression of glycolytic enzyme genes. The log2 fold changes of the mean expression of glycolysis genes from 0 to 25% parasitemia for the 17XNL (n = 6) (Fig. (Fig.4A)4A) and 17XL (n = 4) (Fig. (Fig.4B)4B) infections are ...

Discordant gene expression in B-cell and plasma cell proliferation and differentiation.

Hierarchical cluster analysis revealed several clusters of coexpressed genes with statistically overrepresented GO functional annotations that distinguished a 17XNL from a 17XL infection. GO annotations related to signal transduction, mitochondrial activity, gene regulation, and adaptive immune responses were particularly prominent (Fig. (Fig.6a).6a). Principal among such functional groups were signature patterns of gene expression associated primarily with B-cell proliferation and immunoglobulin production (Fig. (Fig.6b).6b). Immunoglobulin gene expression is tightly regulated and is parasite density dependent. In the 17XNL infection, the differential suppression of B-cell activation genes and concomitant activation of plasma cell genes as the parasitemia rose from 5 to 25% was stage specific, as this pattern was not observed earlier in infection (Fig. 6B and C). In contrast, the expression profiles of genes involved in B-cell proliferation (i.e., Lyn, CD22, and HLA) in lethal infection displayed a pattern dissimilar to those in the 17XNL infection and remained essentially unchanged relative to baseline (Fig. (Fig.6B).6B). A large number of immunoglobulin genes that are expressed only in cells committed to plasma cell differentiation were differentially transcribed at greater levels in 17XNL infection (Fig. (Fig.6C),6C), indicating that a delay in antiparasite immunoglobulin production in 17XL lethal infection may have profound consequences for the host's ability to control the infection.

FIG. 6.
Expression of B-cell proliferation and plasma cell differentiation genes. (A) Hierarchical clustering of genes significantly differentially expressed between 17XNL and 17XL infection. The red-green matrix represents the normalized expression pattern for ...


In order to gain a better understanding of the sequence of molecular events in hosts that succumb to or recover from a malaria infection, global gene expression profiling on high-density oligonucleotide microarrays was exploited to assess the function of differentially regulated genes in the context of the kinetics of transcription and to describe the biological processes that are regulated by such genes. It is reasonable to hypothesize that clusters of up- or down-regulated genes would show patterns of expression that mirrored the course of parasitemia and that the magnitude of transcriptional activity would vary as a function of disease progression or resolution. Factors that may influence such transcriptional changes include both the molecular interactions that regulate gene expression and the dynamic changes in cellular composition that occur in the spleens of animals during the course of infection. Using multiple biological replicates at specific intervals during 17XNL infection, a large number of statistically significant genes were identified, such as heat shock protein genes, whose expression correlated directly with the pattern of ascending and descending parasitemia.

Biological and molecular processes linking sets of up-regulated genes to gene ontology-annotated terms were discovered from gene clusters identified through hierarchical clustering and self-organizing maps. The overrepresented GO terms assigned to sets of differentially expressed genes during specific phases of infection suggested that the functions of coexpressed genes may also be coregulated. The networks of cis-regulatory elements and transcription factors that regulate induction or silencing of gene expression during malaria infection play critical but as-yet-undefined roles in coordinating the activation of gene expression and may help explain why transcriptional activation continues after the host successfully clears the infection. The coordination of gene expression with gene regulation is tightly controlled and influences the expression of many genes involved in the pathological manifestations of disease. In particular, the differential expression of transcription factors and their target genes in regulating erythropoiesis illustrates how expression profiling differentiates between groups of animals that die (24; this paper) or recover from infection and associates that outcome with the host's response to severe malaria anemia. Such transcription factors and cis-regulatory elements, singly or in molecular complexes, regulate red cell proliferation and expression of erythrocyte genes for band 4.2, uroporphyrinogen III synthase, transferrin receptor 2, glycophorin A, and hemoglobin (3, 5, 20, 34).

As erythropoiesis is not limited to the spleen, future investigations should include genome-wide expression profiling of tissues such as the bone marrow and liver, in addition to correlating the expression patterns of regulatory proteins (transcription factors) with their target genes to improve our understanding of the molecular interactions that may predict prognostic signatures for severe malarial anemia in young children.

Physiologic adaptations to malaria infection have indicated that lactic acidosis resulting from the conversion of pyruvate to lactate is implicated in the pathogenesis of human P. falciparum and lethal murine P. berghei infection and is a prognostic indicator of severe disease (8). Sexton et al. have recently reported on the up-regulation of nine glycolytic pathway genes in the spleens of mice infected with P. berghei that favor the conversion of pyruvate to lactate and the down-regulation of counterregulatory genes which shunt or divert products from this pathway (24). Other reports have shown that acidosis correlates with increased parasitemia, progression of disease, and increased glycolytic activity (7, 8, 23). In the study presented here, mice infected with lethal 17XL P. yoelii parasites showed increased gene expression of all the enzymes present in the glycolytic pathway throughout infection. Conversely, in the nonlethal infection, transient increases in gene expression were followed by a dramatic reversal in gene transcription in the interval of time when the parasitemia rose from 5% to 25%. Whether the divergence in patterns of expression between lethal and nonlethal infections reflects the cause or effect of mechanisms that influence death or survival is unknown. However, the observation that the reversal in transcriptional activation of glycolytic pathway genes in nonlethal infection precedes the peak of maximal parasite density suggests that expression patterns may have prognostic significance as predictors of clinical outcome.

Signature patterns of gene expression in immune response genes that distinguished 17XNL from 17XL infection were associated primarily with B-cell proliferation and immunoglobulin production. Antibody responses and plasma cell production in lethal P. berghei and P. yoelii infection are suppressed (21, 30), while nonlethal P. chabaudi and P. yoelii infections induce a large expansion of plasma cells within the red pulp of the spleen (1, 2, 32). The suppression of gene expression of CXCL13, a chemokine important for B-cell homing to germinal centers (14), observed here coincided with the suppression observed for other B-cell proliferation genes, such as Lsp1 and Dock2, necessary for cytoskeletal rearrangements and lymphocyte motility and proliferation (4, 11), while genes involved in plasma cell differentiation were induced. Critically, the relative contribution of antibody-mediated immune mechanisms that appear to control the 17XNL infection studied here in an immunologically intact animal may mask or impede the transcription of genes that are crucial for resolving infections primarily by cell-mediated immune mechanisms (22). In addition, care must be taken not to overinterpret the differences in B-cell and plasma cell gene expression in animals infected with a lethal compared to a nonlethal infection, since the rate of 17XL parasite replication may outstrip the host's ability to elicit a timely and effectual immunologic response. The immune response in animals infected with the lethal strain of P. yoelii may in fact be normal (as shown by the early induction of gene ontology functional groups associated with immune response and cytokine and chemokine signaling pathways), but these animals die prior to the acquisition of antiparasite antibodies.

In conclusion, expression profiling is an extraordinarily useful tool to explore the molecular features of the host's response to infection and can provide insights into transcriptional regulatory mechanisms that influence both the pathogenesis of disease and the host's recovery from infection. While immune responses in human P. falciparum and P. vivax malaria may share many similar features of the global gene expression program observed in murine malaria, important differences in expression profiles in humans infected clinically or experimentally with malaria will depend heavily on the type of tissue (peripheral blood, bone marrow, spleen, or brain) and the stage of infection (early asymptomatic versus clinical malaria) that is studied.

Supplementary Material

[Supplemental material]


The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting the views of the Department of the Army, the Department of Defense, or the Food and Drug Administration.


Editor: W. A. Petri, Jr.


Supplemental material for this article may be found at


1. Achtman, A. H., M. Khan, I. C. M. Maclennan, and J. Langhorne. 2003. Plasmodium chabaudi chabaudi infection in mice induces strong B-cell responses and striking but temporary changes in splenic cell distribution. J. Immunol. 171:317-324. [PubMed]
2. Alves, H. J., W. Weidanz, and L. Weiss. 1996. The spleen in murine Plasmodium chabaudi adami malaria: stromal cells, T lymphocytes, and hematopoiesis. Am. J. Trop. Med. Hyg. 55:370-378. [PubMed]
3. Andrews, N. C. 1994. Erythroid transcription factor NF-E2 coordinates hemoglobin synthesis. Ped. Res. 36:419-423. [PubMed]
4. Bilen, J. J., P. A. Janmey, J. H. Hartwig, S. Galea, and J. Jongstra. 1992. The lymphocyte-specific protein LSP1 binds to F-actin and to the cytoskeleton through its COOH-terminal basic domain. J. Cell Biol. 118:1443-1453. [PMC free article] [PubMed]
5. Cantor, A. B., and S. H. Orkin. 2002. Transcriptional regulation of erythropoiesis: an affair involving multiple partners. Oncogene 21:3368-3376. [PubMed]
6. Chang, K. H., and M. M. Stevenson. 2004. Inappropriately low reticulocytosis in a severe malarial anemia correlates with suppression in the development of late erythroid precursors. Blood 103:3727-3735. [PubMed]
7. Chang, W. L., S. P. Jones, D. J. Lefer, T. Welbourne, G. Sun, L. Yin, H. Suzuki, J. Huang, D. N. Granger, and H. C. Heyde. 2001. CD8-T-cell depletion ameliorates circulatory shock in Plasmodium berghei-infected mice. Infect. Immun. 69:7341-7348. [PMC free article] [PubMed]
8. Day, N. P., N. H. Phu, N. T. Mai, T. T. Chau, P. P. Loc, L. V. Chuong, D. X. Sinh, P. Holloway, T. T. Hien, and N. J. White. 2000. The pathophysiologic and prognostic significance of acidosis in severe adult malaria. Crit. Care Med. 28:1833-1840. [PubMed]
9. Draghici, S., P. Khatri, P. Bhavsar, A. Shah, S. Krawetz, and M. A. Tainsky. 2003. Onto-Tools, the toolkit of the modern biologist: Onto-Express, Onto-Compare, Onto-Design and Onto-Translate. Nucleic Acids Res. 31:3775-3781. [PMC free article] [PubMed]
10. Eisen, M. B., P. T. Spellman, P. O. Brown, and D. Botstein. 1998. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95:14863-14868. [PubMed]
11. Fukui, Y., O. Hashimoto, T. Sanui, T. Oono, H. Koga, M. Abe, A. Inayoshi, M. Noda, M. Oike, T. Shirai, and T. Sasazuki. 2001. Haematopoietic cell-specific CDM family protein DOCK2 is essential for lymphocyte migration. Nature 412:826-831. [PubMed]
12. Irizarry, R. A., B. Hobbs, F. Collin, F., Y. D. Beazer-Barclay, K. J. Antonellis, U. Scherf, and T. P. Speed. 2003. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4:249-264. [PubMed]
13. Jayawardena, A. N., R. Mogil, D. B. Murphy, D. Burger, and R. K. Gershon. 1983. Enhanced expression of H-2K and H-2D antigens on reticulocytes infected with Plasmodium yoelii. Nature 302:509-516. [PubMed]
14. Legler, D. F., M. Loetscher, R. S. Roos, I. C. Lewis, M. Baggiolini, and B. Moser. 1998. B cell-attracting chemokine 1, a human CSC chemokine expressed in lymphoid tissues, selectively attracts B lymphocytes via BLR1/CXCR5. J. Exp. Med. 187:655-660. [PMC free article] [PubMed]
15. Li, C., and W. H. Wong. 2001. Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. Proc. Natl. Acad. Sci. USA 98:31-36. [PubMed]
16. Lucas, B., K. Smith, and A. Haque. 1995. Plasmodium yoelii in mice: differential induction of cytokine gene expression during hypresponsiveness induction and re-stimulation. Cell. Immunol. 160:79-90. [PubMed]
17. Majarian, W. R., T. M. Daly, W. Weidanz, and C. A. Long. 1984. Passive immunization against murine malaria with an IgG3 monoclonal antibody. J. Immunol. 133:3131-3137. [PubMed]
18. McDevitt, M. A., J. Xie, V. Gordeuk, and R. Bucala. 2004. The anemia of malaria infection: role of inflammatory cytokines. Curr. Hematol. Rep. 3:97-106. [PubMed]
19. Morgner, C. O., M. M. Mota, and A. Rodriguez. 2003. Malaria blood stage suppression of liver stage immunity by dendritic cells. J. Exp. Med. 197:143-151. [PMC free article] [PubMed]
20. Perry, C., and H. Soreq. 2002. Transcriptional regulation of erythropoiesis: fine tuning of combinatorial multi-domain elements. Eur. J. Biochem. 269:3607-3618. [PubMed]
21. Poels, L. G., and C. C. Niekerk. 1977. Plasmodium berghei: immunosuppression and hyperimmunoglobulinemia. Exp. Parasitol. 42:235-247. [PubMed]
22. Roberts, D. W., and W. Weidanz. 1979. T-cell immunity to malaria in the B-cell deficient mouse. Am. J. Trop. Med. Hyg. 28:1-3. [PubMed]
23. Schofield, L., M. C. Hewitt, K. Evans, M. A. Siomos, and P. H. Seeberger. 2002. Synthetic GPI as a candidate anti-toxic vaccine in a model of malaria. Nature 418:785-789. [PubMed]
24. Sexton, A. C., R. T. Good, D. S. Hansen, M. C. D'Ombrain, L. Buckingham, K. Simpson, and L. Schofield. 2004. Transcriptional profiling reveals suppressed erythropoiseis, up-regulated glycolysis, and interferon-associated responses in murine malaria. J. Infect. Dis. 189:1245-1256. [PubMed]
25. Shear, H. L., M. W. Marina, C. Wanidworanun, J. W. Berman, and R. L. Nagel. 1998. Correlation of increased expression of intercellular adhesion molecule-1, but not high levels of tumor necrosis factor-α, with lethality of Plasmodium yoelii 17XL, a rodent model of cerebral malaria. Am. J. Trop. Med. Hyg. 59:852-858. [PubMed]
26. Tusher, V. G., R. Tibshirani, and G. Chu. 2001. Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. USA 98:5116-5121. [PubMed]
27. Vahey, M. T., M. E. Nau, M. Taubman, J. Yalley-Ogunro, P. Silvera, and M. G. Lewis. 2003. Patterns of gene expression in peripheral blood mononuclear cells of rhesus macaques infected with SIVmac251 and exhibiting differential rates of disease progression. AIDS Res. Hum. Retroviruses 19:369-387. [PubMed]
28. Weatherall, D. J., L. H. Miller, D. I. Baruch, K. Marsh, O. Doumbo, C. Casals-Pascual, and D. J. Roberts. 2002. Malaria and the red cell. Hematology (Am. Soc. Hematol. Ed. Program), p.35-57. [PubMed]
29. Weidanz, W. P., and R. G. Rank. 1975. Regional immunosuppression induced by Plasmodium berghei yoelii infection in mice. Infect. Immun. 11:211-212. [PMC free article] [PubMed]
30. Weiss, L. Mechanisms of splenic control of murine malaria: cellular reactions of the spleen in lethal (strain 17XL) Plasmodium yoelii malaria in BALB/c mice, and the consequences of pre-infective splenectomy. Am. J. Trop Med. Hyg. 41:144-160. [PubMed]
31. Weiss, L., J. Johnson, and W. Weidanz. 1989. Mechansims of splenic control of murine malaria: tissue culture studies of the erythropoietic interplay of spleen, bone marrow, and blood in lethal (strain 17XL) Plasmodium yoelii malaria in BALB/c mice. Am. J. Trop. Med. Hyg. 41:135-143. [PubMed]
32. Weiss, L., U. Geduldig, and W. Weidanz. 1986. Mechanisms of splenic control of murine malaria: reticular cell activation and the development of a blood-spleen barrier. Am. J. Anat. 176:251-285. [PubMed]
33. World Health Organization. 1999. The world health report, p. 49. World Health Organization, Geneva, Switzerland.
34. Xu, Z., S. Huang, L. S. Chang, A. D. Agulnick, and S. J. Brandt. 2003. Identification of a TAL1 target gene reveals a positive role for the LIM domain-binding protein Lbd1 in erythroid gene expression and differentiation. Mol. Cell. Biol. 23:7585-7599. [PMC free article] [PubMed]
35. Ylostalo, J., A. C. Randall, T. A. Myers, M. Metzger, D. J. Krogstad, and F. B. Cogswell. 2005. Transcriptome profiles of host gene expression in a monkey model of human malaria. J. Infect. Dis. 191:400-409. [PubMed]
36. Yoeli, M., B. Hargreaves, R. Carter, and D. Walliker. 1975. Sudden increase in virulence in a strain of Plasmodium berghei yoelii. Ann. Trop. Med. Parasitol. 69:173. [PubMed]

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