Dataset Information

Unraveling CAF-1 family in Plasmodium falciparum: comparative genome-wide identification and phylogenetic analysis among eukaryotes, expression profiling and protein-protein interaction studies.

ABSTRACT: The present research reports a detailed in silico analysis of chromatin assembly factor-1 (CAF-1) family in human malaria parasite Plasmodium falciparum. Our analysis revealed five chromatin assembly factor-1 genes in P. falciparum (PfCAF-1) and the PfCAF-1 family was divided into two classes where, Class A belongs to the CAF-1 complex and others are kept in Class B. For comparative studies, orthologs of PfCAF-1 family were identified across 53 eukaryotic species and evolutionary relationships were drawn for different CAF-1 subfamilies. The phylogenetic analysis revealed grouping of evolutionary-related species together, although, divergence was observed in branching pattern. A detailed analysis of domain composition highlighted species-specific features viz. species-specific KDDS repeats of 84 amino acids were identified in PfCAF-1A whereas, members of CAF-1C/RbAp48 and RbAp46 subfamily exhibited least variation in size and domain composition. The qRT-PCR analysis revealed upregulation of PfCAF-1 members in trophozoite or schizont stage. Furthermore, a comparative expression analysis of the available transcriptome and proteome data along with qRT-PCR analysis revealed mixed expression patterns (coordination as well as non-coordination between different studies). Protein-protein interaction network analyses of PfCAF-1 family were carried out highlighting important complexes based on interologs. The PfRbAp48 was found to be highly connected with a total of 108 PPIs followed by PfRbAp46. The results unravel insights into the PfCAF-1 family and identify unique features, thus opening new perspectives for further targeted developments to understand and combat malaria menace.

SUBMITTER: Kaushik M

PROVIDER: S-EPMC7048900 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Unraveling CAF-1 family in Plasmodium falciparum: comparative genome-wide identification and phylogenetic analysis among eukaryotes, expression profiling and protein-protein interaction studies.

Kaushik Manjeri M Nehra Ashima A Gill Sarvajeet Singh SS Gill Ritu R

3 Biotech 20200228 3

The present research reports a detailed in silico analysis of chromatin assembly factor-1 (CAF-1) family in human malaria parasite Plasmodium falciparum. Our analysis revealed five chromatin assembly factor-1 genes in P. falciparum (PfCAF-1) and the PfCAF-1 family was divided into two classes where, Class A belongs to the CAF-1 complex and others are kept in Class B. For comparative studies, orthologs of PfCAF-1 family were identified across 53 eukaryotic speci ...[more]

PMID: 32206492

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Project description:Phylogenetic profiling in eukaryotes is of continued interest to study and predict the functional relationships between proteins. This interest is likely driven by the increased number of available diverse genomes and computational methods to infer orthologies. The evaluation of phylogenetic profiles has mainly focussed on reference genome selection in prokaryotes. However, it has been proven to be challenging to obtain high prediction accuracies in eukaryotes. As part of our recent comparison of orthology inference methods for eukaryotic genomes, we observed a surprisingly high performance for predicting interacting orthologous groups. This high performance, in turn, prompted the question of what factors influence the success of phylogenetic profiling when applied to eukaryotic genomes. Here we analyse the effect of species, orthologous group and interactome selection on protein interaction prediction using phylogenetic profiles. We select species based on the diversity and quality of the genomes and compare this supervised selection with randomly generated genome subsets. We also analyse the effect on the performance of orthologous groups defined to be in the last eukaryotic common ancestor of eukaryotes to that of orthologous groups that are not. Finally, we consider the effects of reference interactome set filtering and reference interactome species. In agreement with other studies, we find an effect of genome selection based on quality, less of an effect based on genome diversity, but a more notable effect based on the amount of information contained within the genomes. Most importantly, we find it is not merely selecting the correct genomes that is important for high prediction performance. Other choices in meta parameters such as orthologous group selection, the reference species of the interaction set, and the quality of the interaction set have a much larger impact on the performance when predicting protein interactions using phylogenetic profiles. These findings shed light on the differences in reported performance amongst phylogenetic profiles approaches, and reveal on a more fundamental level for which types of protein interactions this method has most promise when applied to eukaryotes.

Project description:Malaria is a mosquito borne infectious disease caused by protozoa of genus Plasmodium. There are five species of Plasmodium that are found to infect humans. Plasmodium falciparum can cause severe malaria leading to higher morbidity and mortality of malaria than the other four species. Antimalarial resistance is the major obstacle to control malaria. Mefloquine was used in combination with Artesunate for uncomplicated P. falciparum in South East Asia and it has developed and established mefloquine resistance in this region. Here, gel-enhanced liquid chromatography/tandem mass spectrometry (GeLC-MS/MS)-based proteomics and label-free quantification were used to explore the protein profiles of mefloquine-sensitive and -induced resistant P. falciparum. A Thai P. falciparum isolate (S066) was used as a model in this research. Our data revealed for the first time that 69 proteins exhibited at least 2-fold differences in their expression levels between the two parasite lines. Of these, 36 were up-regulated and 33 were down-regulated in the mefloquine-resistant line compared with the mefloquine-sensitive line. These findings are consistent with those of past studies, where the multidrug resistance protein Pgh1 showed an up-regulation pattern consistent with that expected from its average 3-copy pfmdr1 gene number. Pgh1 and eight other up-regulated proteins (i.e., histo-aspartyl protease protein, exportin 1, eukaryotic translation initiation factor 3 subunit 8, peptidyl-prolyl cis-trans isomerase, serine rich protein homologue, exported protein 1, ATP synthase beta chain and phospholipid scramblase 1) were further validated for their expression levels using reverse transcriptase quantitative real-time PCR. The data support the up-regulation status in the mefloquine-resistant parasite line of all the candidate genes referred to above. Therefore, GeLC-MS/MS-based proteomics combined with label-free quantification is a reliable approach for exploring mefloquine resistance biomarkers in P. falciparum. Identification of these proteins leads to better understanding of mefloquine resistant mechanisms in malaria parasites.

Dataset Information

Unraveling CAF-1 family in Plasmodium falciparum: comparative genome-wide identification and phylogenetic analysis among eukaryotes, expression profiling and protein-protein interaction studies.

Publications

Unraveling CAF-1 family in <i>Plasmodium falciparum</i>: comparative genome-wide identification and phylogenetic analysis among eukaryotes, expression profiling and protein-protein interaction studies.

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