Project description:Mechanisms regulating gene expression in malaria parasites are not well understood. Little is known about how this parasite regulates its gene expression during transition from one developmental stage to another and in response to various environmental conditions. Parasites in a diseased host face environments which differ from the static, well adapted in vitro conditions in culture. Parasites thus need to adapt quickly and effectively to these conditions by establishing transcriptional states which is best suited for better survival. With the discovery of natural antisense transcripts (NATs) in this parasite and considering the various proposed mechanisms by which NATs might regulate gene expression, it has been speculated that these might be playing a critical role in gene regulation. We report here the diversity of NATs that exist in this parasite, using isolates taken directly from patients with differing clinical symptoms caused by malaria infection. A total of 797 NATs targeted against annotated loci have been detected using a custom designed strand specific microarray. Out of these, 545 are unique to this study. The majority of NATs were positively correlated with the expression pattern of the sense transcript. Many were found to be differentially regulated in response to disease conditions. Antisense transcripts mapped to a wide variety of biochemical/ metabolic pathways, especially pathways pertaining to the central carbon metabolism and stress related pathways. Our data strongly suggests that a large group of NATs detected here are unannotated transcription units antisense to annotated gene models. The results reveal a previously unknown set of NATs that prevails in this parasite, their differential regulation in disease conditions and mapping to functionally well annotated genes. The results detailed here call for studies to deduce the possible mechanism of action, which would help in understanding the in vivo pathological adaptations of these parasites.

Project description:Mechanisms regulating gene expression in malaria parasites are not well understood. Little is known about how this parasite regulates its gene expression during transition from one developmental stage to another and in response to various environmental conditions. Parasites in a diseased host face environments which differ from the static, well adapted in vitro conditions in culture. Parasites thus need to adapt quickly and effectively to these conditions by establishing transcriptional states which is best suited for better survival. With the discovery of natural antisense transcripts (NATs) in this parasite and considering the various proposed mechanisms by which NATs might regulate gene expression, it has been speculated that these might be playing a critical role in gene regulation. We report here the diversity of NATs that exist in this parasite, using isolates taken directly from patients with differing clinical symptoms caused by malaria infection. A total of 797 NATs targeted against annotated loci have been detected using a custom designed strand specific microarray. Out of these, 545 are unique to this study. The majority of NATs were positively correlated with the expression pattern of the sense transcript. Many were found to be differentially regulated in response to disease conditions. Antisense transcripts mapped to a wide variety of biochemical/ metabolic pathways, especially pathways pertaining to the central carbon metabolism and stress related pathways. Our data strongly suggests that a large group of NATs detected here are unannotated transcription units antisense to annotated gene models. The results reveal a previously unknown set of NATs that prevails in this parasite, their differential regulation in disease conditions and mapping to functionally well annotated genes. The results detailed here call for studies to deduce the possible mechanism of action, which would help in understanding the in vivo pathological adaptations of these parasites. Plasmodium falciparum isolates were collected from patients (n = 11) with differing clinical conditions.The patients exhibited symptoms categorized as un-complicated (n =2) or complicated malaria (n = 9). Criteria for determination of complicated disease were based on World Health Organization year 2000 guidelines. Microarray array based transcriptional profiling was carried out to detect prevalence of natural antisense transcript.

Dataset Information

Comparative proteomic analysis of metabolically labelled proteins from Plasmodium falciparum isolates with different adhesion properties.

Publications

Comparative proteomic analysis of metabolically labelled proteins from Plasmodium falciparum isolates with different adhesion properties.

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