Received date: 31 August 2010; Accepted date: 18 September 2010
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We have used cDNA microarrays to compare gene expression profiles in brains from normal mice to those infected with the ANKA strain of Plasmodium berghei, a model of cerebral malaria. For each of three brains in each group, we computed ratios of all quantifiable genes with a composite reference sample and then computed ratios of gene expression in infected brains compared to untreated controls. Of the almost 12,000 unigenes adequately quantified in all arrays, approximately 3% were significantly downregulated (P < 0.05, ≥ 50% fold change) and about 7% were upregulated. Upon inspection of the lists of regulated genes, we identified a high number encoding proteins of importance to normal brain function or associated with neuropathology, including genes that encode for synaptic proteins or genes involved in cerebellar function as well as genes important in certain neurological diseases such as Alzheimer’s disease or autism. These results emphasize the important impact of malarial infection on gene expression in the brain and provide potential biomarkers that may provide novel therapeutic targets to ameliorate the neurological sequelae of this infection.
malaria; neurobiology; gene regulation; Plasmodium berghei; mouse models; vascular disease
A large study in sub-Saharan Africa reported that almost 50% of malarial patients exhibited neurological deficits  encompassing a number of symptoms, including ataxia, seizures, hemiplegia, and eventually coma and death [13, 15,16]. In addition, greater than 20% of children who survive an episode of cerebral malaria sustain persistent cognitive deficits, which can include memory impairment, visuospatial deficits, and psychiatric disorders as well as motor coordination dysfunction [2, 3, 6,12,20]. While the precise etiology of cerebral malaria has not fully been elucidated, recently vasculopathy has been recognized as contributory to mortality during cerebral malaria .We and others previously demonstrated that experimental cerebral malaria is associated with impairment of blood flow to the cerebral microvasculature, and that this directly correlated with neuronal and axonal damage [18, 31]. Impairment of the cerebral blood flow and associated axonal damage has also been observed in children with cerebral malaria [1, 35]. In addition, although cerebral malaria affects the vasculature, extensive immunological and inflammatory effects occur within the nervous system . In fact, recent studies intimate that the development of deficits in human cerebral malaria is a complex issue which involves the progression of metabolic and physiologic processes in several regions of the brain .
Microarray analysis of differentially expressed genes offers the possibility to search for pathways responsible for disease in a broad, unbiased approach. Using such a strategy, a number of authors have previously identified interferonregulated genes as prominently altered in brains of mice that are susceptible to cerebral malaria , with differential expression in mouse strains that are either susceptible or resistant to cerebral malaria [9, 25]. Most recently, Lovegrove et al.  identified neuronal apoptosis as another pathway that was differentially regulated. Although many genes show strain-specific expression and there are numerous differences between mouse models and human disease, the utility of this novel approach for appreciating alterations in expression of neural genes was highlighted in the accompanying commentary by John .
We have recently obtained evidence for cognitive deficits in mice infected with the ANKA strain of Plasmodium berghei, a well-studied mouse model of cerebral malaria [8, 10]. Because previous studies had observed such small numbers of altered genes in brain or had been focused on changes occurring in other tissues, we undertook the experiments described here, in which multiple biological replicas were used to provide statistically meaningful datasets of up- and downregulated genes. Our findings indicate profound changes in gene expression in the brains of infected animals, both with regard to total number of affected genes and the multiple signaling pathways that they encompass. Particularly surprising was the extraordinarily high number of affected genes that are associated with neurological disease. We conclude from this study that infection of mice with a Plasmodium strain which causes cerebral malaria leads to large-scale gene expression changes in the brain, emphasizing that the resulting disease is fundamentally neurological and identifying putative neural targets toward which therapy might be directed.
Infection of mice
Experiments were performed with the approval of the Institutional Animal Care and Use Committee of the Albert Einstein College of Medicine. Four- to five-week old C57BL/6 female mice (Jackson laboratory, Bar harbor, ME) were either infected with Plasmodium berghei ANKA (PbA) or left uninfected for comparison. Blood containing either 5 × 105 red blood cells (RBCs) parasitized with PbA or uninfected blood was diluted in PBS, and 200 microliters were injected via the intraperitoneal route. The mice were then separated into two groups of infected or uninfected mice. Parasitemia, or the percentage of parasitized RBCs, was evaluated by examining Giemsa stained blood smears on day 6 postinfection (PI). On day 6 PI, mice were rapidly euthanized using carbon dioxide and the brains were harvested, frozen in liquid nitrogen, and then stored at −80◦C for future analysis.
RNA extraction and hybridization
We used a previously published protocol  and a composite reference RNA sample (R) prepared in sufficient quantity for the entire experiment from ten adult mouse tissues (aorta, brain, heart, kidney, liver, lung, ovary/testicles, spleen, and stomach—equal amounts from males and females). This combination of source tissues provided a high diversity of genes expressed in the midrange of the detection system for the AECOM mouse cDNA microarrays. Briefly, 60 μg total RNA, extracted in Trizol® (Invitrogen, Carlsbad, CA) from brains of three infected (I) and three control (C) mice, purified with RNeasy® mini kit (Qiagen, Valencia, CA), were reverse transcribed into cDNA incorporating fluorescent Cy3- dUTP. The composite reference was reverse transcribed to incorporate Cy5-dUTP. Each of the six Cy3-labeled brain extracts was cohybridized overnight at 50◦C against the Cy5-labeled reference with 32 k 70-mer oligonucleotide mouse microarrays produced by the Microarray Facility of the Albert Einstein College of Medicine (platform described in http://www.ncbi.nlm.nih.gov/geo/query/acc. cgi?acc=GPL5371). After hybridization, the slides were washed at room temperature, using solutions containing 0.1% sodium dodecyl sulfate (SDS) and 1% SSC (3M NaCl + 0.3M sodium citrate) to remove the nonhybridized cDNAs.
Acquisition, filtering, and normalization
All microarrays were scanned with an Axon GenePix® 4000B scanner1 and data acquired through GenePixTM Pro 6.0 software2. Spots with substantial local imperfections (customarily flagged by the acquisition program), those for which the medians of the foreground signals were not at least twice as high as the medians of the background signals in both channels, and those with saturated pixels were eliminated from the analysis to avoid inadequate quantification. Background-subtracted signals were normalized through an iterative algorithm, alternating within-array normalization with interarray normalization until the average corrected ratio differed by less than 5% in subsequent steps. Normalized relative expression levels were then organized into redundancy groups, each composed of all spots probing the same gene and each group then represented by the weighted average of the individual spot values.
Detection of differentially expressed genes
Detection of differentially expressed genes relied on both absolute >1.5x fold-change and < 0.05 P-value of the heteroscedastic t-test applied to the means of the background subtracted normalized fluorescence values in the four biological replicas of the compared transcriptomes. The P-values (two samples, unequal variance) were computed with a Bonferroni-type correction applied to the redundancy groups .
Data complying with the “Minimum Information About Microarray Experiments” (MIAMEs) were deposited in the National Center for Biotechnology Information Gene Expression Omnibus database (http://www.ncbi.nlm.nih. gov/geo/query/acc.cgi?acc=GSE24086). Of the 11,669 genes whose expression was adequately quantified on all arrays, 335 (2.87%) were significantly downregulated and 793 (6.90%) upregulated in infected mouse brain. These differentially expressed genes, along with their expression ratios and P-values are listed in Table 1.
|B. GO terms downregulated in malarial brain|
|GOID||GO name||Ttype||Number changed local||Number measured local||Number in GO local||Percent changed local||Z Score||Permuted P|
|1584||rhodopsin-like receptor activity||F||16||107||537||14.95327||3.388||0.001|
|4888||transmembrane receptor activity||F||1||15||88||6.666667||2.884||0.007|
|4930||G-protein coupled receptor activity||F||3||25||469||12||3.546||0|
|4984||olfactory receptor activity||F||28||193||1106||14.50777||2.61||0.013|
|7156||homophilic cell adhesion||P||7||37||122||18.91892||2.058||0.038|
|7166||cell surface receptor-linked signal transduction||P||3||13||140||23.07692||2.777||0.012|
|7186||G-protein coupled receptor protein signaling pathway||P||49||355||1776||13.80282||2.291||0.024|
|7608||sensory perception of smell||P||27||192||1095||14.0625||2.385||0.025|
|9968||negative regulation of signal trans-duction||P||1||15||34||6.666667||2.378||0.019|
|16503||pheromone receptor activity||F||6||25||150||24||2.572||0.022|
|42742||defense response to bacterium||P||5||12||69||41.66667||3.442||0.006|
|50896||response to stimulus||P||28||207||1194||13.52657||2.735||0.006|
|B. GO terms downregulated in malarial brain|
|16323||basolateral plasma membrane||C||2||18||32||11.11111||3.157||0.01|
|3746||translation elongation factor activity||F||3||14||32||21.42857||3.437||0.016|
|16820||“hydrolase activity\, acting on acid anhydrides\, catalyzing transmem- brane movement of substances”||F||2||13||33||15.38461||0.805||0.455|
|6333||chromatin assembly or disassembly||P||2||16||37||12.5||4.666||0|
|7179||transforming growth factor beta receptor signaling pathway||P||1||10||41||10||1.525||0.185|
|151||ubiquitin ligase complex||C||1||15||45||6.666667||1.441||0.155|
|6874||calcium ion homeostasis||P||3||18||47||16.66667||2.892||0.03|
|43066||negative regulation of apoptosis||P||3||23||57||13.04348||2.753||0.014|
|42981||regulation of apoptosis||P||1||33||116||3.030303||1.601||0.139|
|4721||phosphoprotein phosphatase activity||F||3||12||120||25||2.601||0.025|
|7001||chromosome organization and bio-genesis (sensu Eukaryota)||P||4||29||124||13.7931||3.221||0.001|
|6629||lipid metabolic process||P||5||66||217||7.575758||3.019||0.005|
|74||regulation of progression through cell cycle||P||2||43||248||4.651163||2.346||0.028|
|3676||nucleic acid binding||F||11||245||1299||4.489796||2.664||0.008|
|46872||metal ion binding||F||29||638||2173||4.545455||2.567||0.012|
Number changed local = the number of genes altered in pathway; number measured local = number of genes in pathway with measurable signal; number in GO local = total number of genes in GO pathway.
Table 1: Gene ontology terms of altered genes in CM brains.
When pathways of regulated genes were analyzed using GenMapp software, the most prominent pathways of upregulated genes (Table 1A) were those related to rhodopsin like receptors and related categories of olfactory, G-protein coupled, hormone and transmembrane receptors, and perception of smell, including the beta adrenergic receptor (Adrb3), muscarinic receptors Chrm2 and Chrm3, the orexin receptor Hetr1, the H1 histamine receptors Hrh1 and Htr1a1, the prostaglandin receptor Ptgfr, and the vomeronasal receptors V1rc20, V1rc8, V1rel18, and v1rd13. Other GO terms with disproportionately high number of regulated genes were cytokine production (Tnfs15, Inhbb, Cdlb1, Il17f, Cdld1, Nod1, and Spin), voltage gated chloride channels (Clic2, Clic4, Clic5), chromatin remodeling (Mta2, Smarcc1, Suv39h2, Suv39h1, Nasp), and genes related to defense and acute phase response (Fn1m Pxp, Serpna3n).
Pathways with substantially higher expression in the malarial brain were chromatin remodeling genes (Htaitip, Nptxs, Mbd3, H2cfx, Hist \1h2b, Myst3, Nap1l3), cell development, chiefly genes related to negative regulation of apoptosis (Pten, Rblcc1, Stat5b, Eefk2, Polb, Nsh2), lipid metabolism (Adipor1, Fads2, Lysla1, Psap, Scd2), hydrolase activity (specifically, notrophenylphospatase), magnesium ion binding (Arsa, Atp1a1, Atp2a2, Brsk1, Cno16l), adult walking behavior (Cacnb4, Glrb), axon (Alcam, Dpysl2, Pacb1), and regulation of muscle contraction (Atp2a2, Atp1a1). Interestingly, both neuronal and vascular endothelial cell apoptosis have been described in human and experimental cerebral malaria, in association with glial cell damage and dysfunction [22,29,36] demonstrating that protein regulation occurs both at the transcription and the translation levels. The finding that substantial numbers of genes involved in chromatin remodeling are regulated in the infected brain raises the possibility that, in addition to involvement of epigenetic factors in the parasite itself , a major consequence of infection may be the epigenetic reprogramming of host nervous tissue.
These analyses of pathways affected by infection revealed that genes expected to be important in cerebral function (receptors cytokines, apoptosis, lipid metabolism, walking, axon, and muscle contraction) were disproportionately affected in these brains. As an additional method to mine the data corresponding to gene alteration in the brains of infected mice, we determined whether genes whose expression was altered were known to be associated with human neurological disease.
As can be seen from Table 2, the major subcategories of genes linked to neurological diseases that are up- and downregulated in malaria brain are channels/ receptors/transporters and components of the synapse including cytoskeletal linkages to vesicles. Channel genes with altered expression include Glrb (the beta subunit of the glycine receptor), Scn1b (the beta subunit of the voltage gated sodium channel), Cacnb4 (a beta subunit of voltage-dependent calcium channel), Cabp1 (a neuronspecific regulator of calcium channel activation), Accn2 (the neuronal amiloride sensitive cation channel2), Slc33a1 (the acetyl co-A transporter involved in gangliosides), and Vdac3 (the mitochondrial voltage-dependent anion channel). Genes whose encoded proteins are involved in synaptic or other contact between cells include Adam23 (which mediates integrin cell adhesion in brain), Ap2a1 (calcium Huntington interacting protein that links clathrin to receptors in vesicles , Akap8l and Akap9 (the latter of which also known as Yotaio, anchor protein kinase A and binds the Nr1 subunit to the cytoskeleton to the vesicle fusion protein Snap29 ), Scrib (a presynaptic scaffolding molecule), Pcdha6 and Pcdh9 (proto cadherins that link neural cells), Nlgn3 (neuroligin3, a neuron cell surface protein involved in formation of remodeling of CNS synapses), Nrnx2 (neurexin2, a neuron cell surface protein required for normal transmitter release), Rims3 (which enhances neurotransmitter release ), Cntnab1 (a contactin associated protein important for neurite outgrowth and differentiation), Gabarap (which links the Gabaa receptor with cytoskeleton), Gripap1 (a neuron-specific guanine release factor associated with the AMPA complex), Itsn1 (intersection 1, which associates with Ehb2 tyrosine kinase and the cytoskeletal protein Wasp to mediate dendritic spine morphogenesis). Several mitochondrial genes are regulated in the malaria brain whose dysfunction is associated with neurological disorders , including Vdac3 as mentioned above, Tmem70, Sncoa2, and Acad8.
|GB Acc||NAME||SYMBOL||I/C||P-I/C||Neurological consequence of ablation/mutation|
|A. Channels receptors transporters and synapse components|
|NM 010298||glycine receptor, beta subunit||Glrb||1.9||0.023||Hyperekplexia, autosomal recessive|
|NM 011322||sodium channel, voltage-gated, type I, beta||Scn1b||2.0||0.018||Generalized epilepsy with febrile seizures; regulates Na channel density and localization|
|NM 146123||calcium channel, voltage-dependent, beta 4 subunit||Cacnb4||2.2||0.033||Mouse “lethargic”: ataxic, first example of neurological disease in accessory subunit|
|NM 013879||calcium binding protein 1||Cabp1||−2.5||0.048||Neuronal signal transduction and memory|
|NM 009597||amiloride-sensitive cation channel 2, neuronal||Accn2||1.8||0.032||Enhanced fear conditioning; deletion protective in EAE|
|NM 015728||solute carrier family 33 (acetyl-coa transporter), member 1||Slc33a1||1.8||0.004||Spastic paraplegia42, autsomal dominant|
|NM 011696||voltage-dependent anion channel 3||Vdac3||1.5||0.017||Mitochondrial disease|
|XM 344168||vesicle-associated membrane protein 4 (predicted)||Vamp4||2.3||0.009||Vesicle component|
|B. Genes involved in synapse or other inter-cellular contact|
|NM 017476||A kinase (PRKA) anchor protein 8-like||Akap8l||−3.4||0.042||Binds huntingtin in Huntington disease|
|NM 007458||Adaptor protein complex AP-2, alpha 1 subunit||Ap2a1||2.1||0.016||Huntingtin protein binding; vesicle trafficking|
|NM 194462||A kinase (PRKA) anchor protein (yotiao) 9||Akap9||2.1||0.011||Long QT syndrome 11 [kcnq1, ser1570leu]|
|NM 011780||A disintegrin and metalloprotease domain 23||Adam23||2.0||0.012||Brain specific|
|NM 023348||Synaptosomal-associated protein||Snap29||1.8||0.015||Cerebral dysgenesis, neuropathy, ichthyosis, and palmoplantar keratoderma syndrome|
|NM 134089||Scribbled homolog (Drosophila)||Scrib||1.7||0.045||Craniorachischisis, a severe neural tube defect|
|XM 139187||Protocadherin 9||Pcdh9||2.2||0.015||Possibly autism|
|NM 172932||Neuroligin 3||Nlgn3||2.3||0.041||Ligand for neurexin: linked to autism, Asperger syndrome|
|NM 007767||Protocadherin alpha 6||Pcdha6||2.1||0.024||Synaptic junction protein|
|NM 020253||Neurexin II||Nrxn2||−2.4||0.001||Organize presynaptic terminals by functionally coupling Ca channels to presynaptic machinery|
|NM 153508||Calsyntenin 3||Clstn3||−2.8||0.006||Postsynaptic protein|
|NM 016782||Contactin associated protein 1||Cntnap1||−2.9||0.010||Essential for formation of axonal septate junc-tions|
|NM 182929||Regulating synaptic membrane exocy-tosis 3||Rims3||2.3||0.005||Enhances neurotransmitter secretion|
|NM 019749||Gamma-aminobutyric acid receptor-associated protein||Gabarap||1.9||0.030||Autophagy; binding GABA-A receptors|
|NM 207670||GRIP1-associated protein 1||Gripap1||1.8||0.038||Regulates neuronal Ras signaling and con-tributes to the regulation of AMPA receptor distribution|
|NM 010587||Intersectin 1 (SH3 domain protein 1A)||Itsn1||2.0||0.029||Dendritic spine morphogenesis|
|B. Genes involved in synapse or other inter-cellular contact|
|C. Mitochondrial genes associated with neurological disorders|
|AK181541||Transmembrane protein 70||Tmem70||2.1||0.038||Encephalomyopathy and mitochondrial DNA depletion syndrome|
|NM 025862||Acyl-Coenzyme A dehydrogenase family, member 8||Acad8||1.8||0.031||Isobutyryl-coa dehydrogenase deficiency|
|NM 011506||Succinate-Coenzyme A ligase, ADP-forming, beta subunit||Sucla2||2.7||0.032||Encephalomyopathy and mitochondrial DNA depletion syndrome|
|GB Acc||NAME||SYMBOL||I/C||P-I/C||Neurological consequence of ablation/mutation|
|D. Ataxia and cerebellar function and development|
|NM 145358||Calcium/calmodulin-dependent protein kinase kinase 2, beta||Camkk2||−3.1||0.003||Mouse null impaired spatial memory for-mation; altered cerebellar granule cell development|
|NM 021477||Ataxin 2 binding protein 1, transcript variant 2||A2bp1||2.7||0.045||Spinocerebellar ataxia 2|
|NM 033526||Ubiquilin 4||Ubqln4||2.7||0.009||Spinocerebellar ataxia 1|
|NM 007597||Calnexin||Canx||2.6||0.019||Unstable gait, truncal ataxia, abnormal relexes; loss of large nerve fibers|
|NM 011179||Prosaposin||Psap||1.9||0.047||Loss of cerebellar purkinje cells due to ceremide buildup|
|D26114||CCG1, complete cds||CCG1, complete cds||1.6||0.029||Neuropathy ataxia-17syndrome; spinocerebellar|
|E. Genes associated with autism|
|NM 011814||Fragile X mental retardation gene 2, autosomal homolog||Fxr2h||2.0||0.028||Mental retardation|
|NM 054097||Phosphatidylinositol-4-phosphate 5-kinase, type II, gamma||Pip5k2c||1.9||0.025||Mental retardation|
|F. Genes associated with Alzheimer’s disease|
|NM 009685||Amyloid beta (A4) precursor protein-binding, family B, member 1||Apbb1||1.6||0.031||Dementia of the Alzheimer’s type|
|NM 009053||Radical fringe gene homolog (Drosophila)||Rfng||2.0||0.022||Notch signaling in cell fate determination in neurogenesis|
|NM 010487||ELAV (embryonic lethal, abnormal vision, Drosophila)-like 3 (Hu antigen C)||Elavl3||1.8||0.018||Paraneoplastic neurologic disorder due to autoimmune neuronal destruction|
GB Acc = gene bank accession number; I/C = Fold change in gene expression of infected/control; P-I/C = p value.
Table 2: Neurological diseases corresponding to genes altered in malarial brain.
Our study of transcriptomic regulation in the setting of cerebral malaria identified numerous genes whose altered expression or mutation has been associated with disorders of brain. Many of these regulated genes are associated with ataxia or altered cerebellum development or function (e.g.: Camkk2, A2bp1, Ubqln4, Canx, Cacnb4, Psap, CCG1), consistent with a common neurological consequence of the disease . It is also noteworthy that several of the encoded proteins (Fxr2h, Pip5k2c, Pcdh9) have been associated with autism , which in a small study of 20 children in Tanzania was diagnosed in a significant fraction of CM patients . Another neurological overlap is with Alzheimer’s disease. Delahaye et al.  reported overexpression of beta amyloid only in a mouse strain susceptible to cerebral malaria. In addition, axonal damage has been demonstrated as a feature of cerebral malaria with increased immunoreactivity of the amyloid precursor protein (APP) in the white matter adjacent to areas of vascular damage and of hemorrhage . In Table 2, we demonstrate that Apbb1 mRNA is significantly upregulated in infected brain.
The classification of cerebral malaria as a vascular disease [5,11] emphasizes the therapeutic potential of agents directed toward increasing brain perfusion. Long-term cognitive and motor deficits correspond with the geographical distribution of vascular damage in experimental cerebral malaria . Likewise, decreased cerebral blood flow has been demonstrated to contribute to mortality in cerebral malaria, and vasodilitory agents increase survival in the experimental model . However, focusing exclusively on microvascular damage presents an incomplete approach to a complex disease process, as cerebral malaria is also unquestionably a disease that affects neural components of the brain, resulting in impaired gait, cognition and neural processing, as well as cognitive and motor impairment [8, 10]. The identification of altered genes encoding proteins within pathways prominently associated with neurologic disease in the present study provides alternative or adjunctive disease targets to improve treatment outcomes for the vast number of individuals who have recovered from acute parasitic infection but for whom there is neural damage that extends beyond impaired brain microcirculation.
This work was supported by the NIH Training Grant in Mechanisms of Cardiovascular Diseases (T32 HL-07675) to MSD; Dominick P. Purpura Department of Neuroscience and Department of Psychiatry and Behavioral Sciences (neuroscience fellowship support to MSD), Albert Einstein College of Medicine; Burroughs-Wellcome Fund’s Career Awards for Medical Scientists to MSD; Einstein-Montefiore Institute for Clinical and Translational Research Career Development Award to MSD; AI076248 to HBT; AI39454 to LMW; NS041282 to DCS.
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