Statistical estimation of cell-cycle progression and lineage commitment in Plasmodium falciparum reveals a homogeneous pattern of transcription in ex vivo culture

Abstract

We have cultured Plasmodium falciparum directly from the blood of infected individuals to examine patterns of mature-stage gene expression in patient isolates. Analysis of the transcriptome of P. falciparum is complicated by the highly periodic nature of gene expression because small variations in the stage of parasite development between samples can lead to an apparent difference in gene expression values. To address this issue, we have developed statistical likelihood-based methods to estimate cell cycle progression and commitment to asexual or sexual development lineages in our samples based on microscopy and gene expression patterns. In cases subsequently matched for temporal development, we find that transcriptional patterns in ex vivo culture display little variation across patients with diverse clinical profiles and closely resemble transcriptional profiles that occur in vitro. These statistical methods, available to the research community, assist in the design and interpretation of P. falciparum expression profiling experiments where it is difficult to separate true differential expression from cell-cycle dependent expression. We reanalyze an existing dataset of in vivo patient expression profiles and conclude that previously observed discrete variation is consistent with the commitment of a varying proportion of the parasite population to the sexual development lineage. malaria ͉ microarray

Transcriptional variation in the malaria parasitePlasmodium falciparum

“…Gene level log 2 (Cy5/Cy3) expression ratios were computed from probe level values using median polish. We calculated the most likely time post-invasion along the asexual cycle for each sample using a statistical likelihood method (Lemieux et al 2009), with the HB3 transcriptome as reference (Bozdech et al 2003). Expression values for each gene [log 2 (Cy5/Cy3)] were plotted against estimated times for each parasite line.…”

“…To account for this, we estimated the stage of the cycle for each microarray sample using a statistical likelihood-based method (Supplemental Fig. S1; Lemieux et al 2009) and plotted expression levels against estimated times post-invasion (Fig. 1C,D).…”

“…Some studies have compared global blood stages transcription between different P. falciparum lines, but their sample size and experimental design resulted in the identification of only a small number of variantly expressed genes: One study compared two isogenic lines selected to display different antigenic and adhesive properties (Mok et al 2007), whereas another study compared the transcriptome of three genetically different parasite lines, focusing on the comparison of patterns of expression along the life cycle rather than comparing transcript levels (Llinas et al 2006). Genome-wide transcriptional differences have also been analyzed in field isolates Lemieux et al 2009;Mackinnon et al 2009), but these studies suffer intrinsic limitations such as the inability to distinguish between spontaneous variation and selection, and the common occurrence of mixed infections. Furthermore, some of the transcript-level differences observed may be attributable to genetic polymorphism.…”

A glimpse into the clinical proteome of human malaria parasites Plasmodium falciparum and Plasmodium vivax

“…The genomes of both parasites have been sequenced; however, genome data from clinical isolates of both parasites are limited [6,7]. Analyses of transcriptome in clinical samples of Pf as well as Pv have been carried out [8][9][10][11]. A recent study has categorized the malaria patients on the basis of the differences in transcriptome profiles exhibited by the parasites they harbored [10].…”

NSR-seq transcriptional profiling enables identification of a gene signature of Plasmodium falciparum parasites infecting children

“…For this reason, earlier studies sought to associate the expression of particular parasite genes or proteins with disease severity by comparing the transcriptome and proteome of parasites obtained from different types of malaria episodes. Two recent DNA microarray studies failed to identify parasite genes whose expression was related to disease severity (13,14). In contrast, microarray and proteomic studies of pregnancy malaria have identified sets of genes and proteins, including VAR2CSA, that are more abundant in parasites isolated from pregnant women than in those from children (15,16) or that are more abundant in placental parasites than in a laboratory-adapted reference strain (17).…”