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In silico and biological survey of transcription-associated proteins implicated in the transcriptional machinery during the erythrocytic development of Plasmodium falciparum.

Bischoff E, Vaquero C - BMC Genomics (2010)

Bottom Line: The transcription-associated proteins were clustered in three main sets of factors: general transcription factors, chromatin-related proteins (structuring, remodelling and histone modifying enzymes), and specific transcription factors.This is the first attempt to build a comprehensive directory of potential transcription-associated proteins in Plasmodium.In addition, all complete transcriptome, proteome and interactome raw data were re-analysed, compared and discussed for a better comprehension of the complex biological processes of Plasmodium falciparum transcriptional regulation during the erythrocytic development.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institut Pasteur, Unité d'Immunologie Moléculaire des Parasites, CNRS URA 2581, 25-28 rue du Dr Roux, 75724, Paris cedex 15, France. bischoff@pasteur.fr

ABSTRACT

Background: Malaria is the most important parasitic disease in the world with approximately two million people dying every year, mostly due to Plasmodium falciparum infection. During its complex life cycle in the Anopheles vector and human host, the parasite requires the coordinated and modulated expression of diverse sets of genes involved in epigenetic, transcriptional and post-transcriptional regulation. However, despite the availability of the complete sequence of the Plasmodium falciparum genome, we are still quite ignorant about Plasmodium mechanisms of transcriptional gene regulation. This is due to the poor prediction of nuclear proteins, cognate DNA motifs and structures involved in transcription.

Results: A comprehensive directory of proteins reported to be potentially involved in Plasmodium transcriptional machinery was built from all in silico reports and databanks. The transcription-associated proteins were clustered in three main sets of factors: general transcription factors, chromatin-related proteins (structuring, remodelling and histone modifying enzymes), and specific transcription factors. Only a few of these factors have been molecularly analysed. Furthermore, from transcriptome and proteome data we modelled expression patterns of transcripts and corresponding proteins during the intra-erythrocytic cycle. Finally, an interactome of these proteins based either on in silico or on 2-yeast-hybrid experimental approaches is discussed.

Conclusion: This is the first attempt to build a comprehensive directory of potential transcription-associated proteins in Plasmodium. In addition, all complete transcriptome, proteome and interactome raw data were re-analysed, compared and discussed for a better comprehension of the complex biological processes of Plasmodium falciparum transcriptional regulation during the erythrocytic development.

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Potential interactions observed by in silico and yeast two hybrid approach between the GTF and ApiAP2. TAP candidates eliciting interactions from in silico [53] and Y2D data [54] were extracted from PlasmoDB and only the proteins for which an interaction was inferred are presented. The two networks were merged and graphically represented using Cytoscape 2.6 http://www.cytoscape.org. Red circle stands for general transcription factors, yellow for chromatin-related proteins, green for specific transcription factors and blue for partners. Grey lines represent the in silico interactions and pink lines those proposed by the two-hybrid experiment. A. Interaction network for the preinitiation complexe. B. Interaction network for the ApiAP2 TF. For the complete interaction network see Additional file 5.
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Figure 4: Potential interactions observed by in silico and yeast two hybrid approach between the GTF and ApiAP2. TAP candidates eliciting interactions from in silico [53] and Y2D data [54] were extracted from PlasmoDB and only the proteins for which an interaction was inferred are presented. The two networks were merged and graphically represented using Cytoscape 2.6 http://www.cytoscape.org. Red circle stands for general transcription factors, yellow for chromatin-related proteins, green for specific transcription factors and blue for partners. Grey lines represent the in silico interactions and pink lines those proposed by the two-hybrid experiment. A. Interaction network for the preinitiation complexe. B. Interaction network for the ApiAP2 TF. For the complete interaction network see Additional file 5.

Mentions: Among the 202 TAPs of each class, around half were predicted to interact by in silico and Y2H approaches and far more interactions were detected with in silico method [27 of the 56 GTFs (red points), 35 of the 63 CTFs (yellow), 43 of 73 STFs (green) and three of the 10 partners (blue)]. The network of these factors, presented in figure 4 and additional file 5, was constructed as indicated in Methods, from the in silico (gray lines) and Y2H (pink lines) studies. The figure 4 is a blow up of interactions between the factors composing the PIC and between ApiAP2 with other TAPs. For the GTFs, the in silico data showed, as expected (Figure 4A), significant interactions between a number of RNA polymerases and TFII subunits composing the PIC, plus interactions with several CTFs and STFs (additional file 5), including several ApiAP2, Zf-C2H2 and PfMyb2 (PF10_0327) [53]. In contrast, no molecular interaction was detected by the Y2H approach between the PIC components, strongly highlighting that this experimental procedure missed many interactions and therefore the lack of robustness of the data. Figure 4B presents the interactions of the ApiAP2 including three ApiAP2 factors [16,17] that have been molecularly analysed: ApiAP2 ring (PF14_0633) and ApiAP2 early schizont (PFF0200, PF11_0442). Indeed, very few interactions were depicted in La Count's data (pink lines in additional file 5), for example some members of ApiAP2, Zinc finger and Myb as well as several GTFs and CTFs. The rbp6 polymerase was shown to interact with the NAP- PfB7 (PFI0930C). The best networks were centred around ADA/SAGA:GCN5 (PF10_0232) a SAGA protein [54], ADA (PF08_0034) and an ApiAP2 (MAL8P1.153). Finally, the total lack of overlap between the results based on these two approaches reflects their poor reliability.


In silico and biological survey of transcription-associated proteins implicated in the transcriptional machinery during the erythrocytic development of Plasmodium falciparum.

Bischoff E, Vaquero C - BMC Genomics (2010)

Potential interactions observed by in silico and yeast two hybrid approach between the GTF and ApiAP2. TAP candidates eliciting interactions from in silico [53] and Y2D data [54] were extracted from PlasmoDB and only the proteins for which an interaction was inferred are presented. The two networks were merged and graphically represented using Cytoscape 2.6 http://www.cytoscape.org. Red circle stands for general transcription factors, yellow for chromatin-related proteins, green for specific transcription factors and blue for partners. Grey lines represent the in silico interactions and pink lines those proposed by the two-hybrid experiment. A. Interaction network for the preinitiation complexe. B. Interaction network for the ApiAP2 TF. For the complete interaction network see Additional file 5.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2821373&req=5

Figure 4: Potential interactions observed by in silico and yeast two hybrid approach between the GTF and ApiAP2. TAP candidates eliciting interactions from in silico [53] and Y2D data [54] were extracted from PlasmoDB and only the proteins for which an interaction was inferred are presented. The two networks were merged and graphically represented using Cytoscape 2.6 http://www.cytoscape.org. Red circle stands for general transcription factors, yellow for chromatin-related proteins, green for specific transcription factors and blue for partners. Grey lines represent the in silico interactions and pink lines those proposed by the two-hybrid experiment. A. Interaction network for the preinitiation complexe. B. Interaction network for the ApiAP2 TF. For the complete interaction network see Additional file 5.
Mentions: Among the 202 TAPs of each class, around half were predicted to interact by in silico and Y2H approaches and far more interactions were detected with in silico method [27 of the 56 GTFs (red points), 35 of the 63 CTFs (yellow), 43 of 73 STFs (green) and three of the 10 partners (blue)]. The network of these factors, presented in figure 4 and additional file 5, was constructed as indicated in Methods, from the in silico (gray lines) and Y2H (pink lines) studies. The figure 4 is a blow up of interactions between the factors composing the PIC and between ApiAP2 with other TAPs. For the GTFs, the in silico data showed, as expected (Figure 4A), significant interactions between a number of RNA polymerases and TFII subunits composing the PIC, plus interactions with several CTFs and STFs (additional file 5), including several ApiAP2, Zf-C2H2 and PfMyb2 (PF10_0327) [53]. In contrast, no molecular interaction was detected by the Y2H approach between the PIC components, strongly highlighting that this experimental procedure missed many interactions and therefore the lack of robustness of the data. Figure 4B presents the interactions of the ApiAP2 including three ApiAP2 factors [16,17] that have been molecularly analysed: ApiAP2 ring (PF14_0633) and ApiAP2 early schizont (PFF0200, PF11_0442). Indeed, very few interactions were depicted in La Count's data (pink lines in additional file 5), for example some members of ApiAP2, Zinc finger and Myb as well as several GTFs and CTFs. The rbp6 polymerase was shown to interact with the NAP- PfB7 (PFI0930C). The best networks were centred around ADA/SAGA:GCN5 (PF10_0232) a SAGA protein [54], ADA (PF08_0034) and an ApiAP2 (MAL8P1.153). Finally, the total lack of overlap between the results based on these two approaches reflects their poor reliability.

Bottom Line: The transcription-associated proteins were clustered in three main sets of factors: general transcription factors, chromatin-related proteins (structuring, remodelling and histone modifying enzymes), and specific transcription factors.This is the first attempt to build a comprehensive directory of potential transcription-associated proteins in Plasmodium.In addition, all complete transcriptome, proteome and interactome raw data were re-analysed, compared and discussed for a better comprehension of the complex biological processes of Plasmodium falciparum transcriptional regulation during the erythrocytic development.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institut Pasteur, Unité d'Immunologie Moléculaire des Parasites, CNRS URA 2581, 25-28 rue du Dr Roux, 75724, Paris cedex 15, France. bischoff@pasteur.fr

ABSTRACT

Background: Malaria is the most important parasitic disease in the world with approximately two million people dying every year, mostly due to Plasmodium falciparum infection. During its complex life cycle in the Anopheles vector and human host, the parasite requires the coordinated and modulated expression of diverse sets of genes involved in epigenetic, transcriptional and post-transcriptional regulation. However, despite the availability of the complete sequence of the Plasmodium falciparum genome, we are still quite ignorant about Plasmodium mechanisms of transcriptional gene regulation. This is due to the poor prediction of nuclear proteins, cognate DNA motifs and structures involved in transcription.

Results: A comprehensive directory of proteins reported to be potentially involved in Plasmodium transcriptional machinery was built from all in silico reports and databanks. The transcription-associated proteins were clustered in three main sets of factors: general transcription factors, chromatin-related proteins (structuring, remodelling and histone modifying enzymes), and specific transcription factors. Only a few of these factors have been molecularly analysed. Furthermore, from transcriptome and proteome data we modelled expression patterns of transcripts and corresponding proteins during the intra-erythrocytic cycle. Finally, an interactome of these proteins based either on in silico or on 2-yeast-hybrid experimental approaches is discussed.

Conclusion: This is the first attempt to build a comprehensive directory of potential transcription-associated proteins in Plasmodium. In addition, all complete transcriptome, proteome and interactome raw data were re-analysed, compared and discussed for a better comprehension of the complex biological processes of Plasmodium falciparum transcriptional regulation during the erythrocytic development.

Show MeSH
Related in: MedlinePlus