Frequency of sequence groups in transcripts from the organs of paediatric malaria patients

<p><b>Copyright information:</b></p><p>Taken from "Differential gene expression in the organs of patients dying of falciparum malaria"</p><p></p><p>Molecular Microbiology 2007;65(4):959-967.</p><p>Published online Jan 2007</p><p>PMCID:PMC2170262.</p><p>© 2007 Liverpool School of Tropical Medicine; Journal compilation © 2007 Blackwell Publishing Ltd</p> Shading represents the sequence groups as identified by , which are characterized by the number of cysteine residues and other semi-conserved motifs known as positions of limited variance. The data are expressed as the percentage of types within each organ containing the corresponding sequence motifs. Brn, brain; Lng, lung; Hrt, heart; Spl, spleen

MOESM1 of Microclimate variables of the ambient environment deliver the actual estimates of the extrinsic incubation period of Plasmodium vivax and Plasmodium falciparum: a study from a malaria-endemic urban setting, Chennai in India

Additional file 1. Month-wise mean, minimum, maximum temperature and relative humidity (RH) variations observed during the diurnal and nocturnal period in indoor and outdoor environments

MOESM3 of Microclimate variables of the ambient environment deliver the actual estimates of the extrinsic incubation period of Plasmodium vivax and Plasmodium falciparum: a study from a malaria-endemic urban setting, Chennai in India

Additional file 3. Month-wise pattern of temperature (a), relative humidity (b), daily temperature range and daily relative humidity range (c), rainfall (d), man-hour density of Anopheles stephensi (e), malaria prevalence of the study area from 2006 to 2013 (f)

Distribution of individual <i>var</i>/PfEMP1-DBL1α types in fatal paediatric malaria hosts.

<p>100 DBL1α tags were amplified and sequenced from each tissue biopsy and different sequence variants identified. Each pie graph represents all DBL1α types from a single organ of an individual host shown in the brain (A), heart (B) and gut (C). Case numbers are shown in the upper left corner of each graph and they are arranged by diagnostic group (CM, cerebral malaria; PC, parasitaemic controls). Tags are coloured by whether they are classified as group A-like <i>var</i> types (green) or non-group A (blue).</p

Distribution of individual <i>var</i>/PfEMP1-DBL1α types in the organs of fatal paediatric malaria hosts.

<p>Each pie graph represents all DBL1α variants from a single organ of an individual host shown in the brain (A), heart (B) and gut (C). Case numbers are shown in the upper left corner of each graph and they are arranged by diagnostic group (CM, cerebral malaria; PC, parasitaemic controls). These charts are identical to those in Fig. 2 except that sections are shaded to highlight the DBL1α types that were detected in the highest number of different hosts. Further information on these can be found in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004537#ppat.1004537.s004" target="_blank">S1 Table</a>. The two DBL1α types detailed in results are marked with an asterisk.</p

Clinical details of patients.

a<p>months,</p>b<p>hours:minutes,</p>c<p>parasites/l in peripheral blood,</p>d<p>pneumonia (Streptococcus),</p>e<p>malaria parasitaemic with non-malarial cause of death,</p>f<p>meningoencephalitis.</p><p>Clinical details of patients.</p

Expression of <i>var</i> gene groups in the organs of paediatric hosts.

<p>Primers specific for <i>var</i> groups A, B and C were used to measure their relative expression in tissue biopsies from fatal paediatric malaria patients. Panels A–C display hosts within diagnostic groups CM2 (A), CM1 (B) and parasitaemic controls (C). Panels D–F represent <i>P. falciparum</i> populations in the brain (D), heart (E) and gut (F) of HIV-infected (HIV+) and uninfected (HIV-) hosts. Each dot point represents analysis from a single organ biopsy from one patient and the horizontal lines depict the mean level of expression for each group. In panels D–F, CM2/PC hosts are denoted by filled shapes and CM1 patients with open shapes. * p<0.05, ** p<0.005.</p

Stage-predictive gene sets are enriched for specific biological processes but show no signature of selection by diversity/divergence measures.

<p>(A) Top 15 model <i>β_g,s</i> parameters specific to each stage; values indicate for each gene the degree of its expression attributed to each stage. (B) Gene set enrichments of GO and KEGG processes by stage (Supplementary <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003392#pcbi.1003392.s004" target="_blank">Table S2</a>). (C) Genetic diversity (within patient) vs. divergence (between isolate) of the <i>P. falciparum</i> genome (see Methods for data sources), highlighting genes identified as stage-specific. Several known markers are labeled for reference.</p

<i>In silico</i> dissection approach developing a linear regression model to identify stage-specific gene expression profiles within bulk parasite population gene expression.

<p>(A) Definition of physiologically relevant stage categories within <i>P. falciparum</i> development for which we will identify stage-specific expression signatures. Stages are as follows: R: asexual ring, T: asexual trophozoite and schizont, YG: young gametocyte ring and stage I, DG: developing gametocyte stages II, III, and IV, IG: all immature gametocytes (YG+DG), MG: mature gametocyte stage V, and U: unexpected profile not captured by our defined stages. (B) Linear regression model for the deconvolution of bulk gene expression data from mixed stage samples. Terms are as follows: <i>y_g</i>: total expression of gene g, β<i>_g,s</i>: expression of gene g attributed to stage s, <i>X_s</i>: proportion of the sample that is stage s. (C) Marker Selection. Filters used to narrow down gene sets to our set of sentinel markers for field-applicable qRT-PCR assay. As we chose markers for ring and trophozoite/schizont stages <i>a priori</i> based on published stage-specific gene expression data for asexual development <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003392#pcbi.1003392-Bozdech1" target="_blank">[4]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003392#pcbi.1003392-LeRoch1" target="_blank">[5]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003392#pcbi.1003392-Merrick1" target="_blank">[46]</a>, we used this selection method to identify markers for the remaining gametocyte stage categories. (D) Overall stage prediction schematic.</p

qRT-PCR assay optimization.

<p>(A) We collected and analyzed a range of <i>in vitro</i> time points with varying contributions of asexual and sexual stages, from both gametocyte-producing and non-producing lines of 3D7. Absolute number of parasites stages that went into each qRT-PCR reaction well is plotted. (B) Relative qRT-PCR-based gene expression of stage-specific markers for R, T, IG and MG are shown for time points corresponding vertically to those in part A. (C) Inferred proportion of each stage in the total parasite load (model predictions) are shown corresponding vertically to the time points in A and B, plotted as a percentage of total parasites in that sample. (D) <i>In vivo</i> peripheral blood samples from severe malaria patients in Blantyre, Malawi were collected and analyzed. Absolute numbers of parasites stages per µL of blood, as determined by microscopy, are plotted. (E) Relative qRT-PCR-based gene expression of stage-specific markers for T, IG and MG (normalized to <i>SBP1</i>) is shown for time points corresponding vertically to those in part D. (F) Inferred proportion of each stage (model predictions) are shown corresponding vertically to the time points in D and E. Stars indicate subjects in which gametocytes were observed by highly sensitive thick smear examination (one or more gametocytes in 100 high power fields).</p