Identification of hub glycogenes and their nsSNP analysis from mouse RNA-Seq data

Computational prediction of the effects of non-synonymous single nucleotide polymorphisms on the GPI-anchor transamidase subunit GPI8p of Plasmodium falciparum

Drug resistance is increasingly evolving in malaria parasites; hence, it is important to discover and establish alternative drug targets. In this context, GPI-anchor transamidase (GPI-T) is a potential drug target primarily of its crucial role in the development and survival of the parasite in the GPI anchor biosynthesis pathway. The present investigation was undertaken to explore the plausible effects of nsSNP on the structure and functions of GPI-T subunit GPI8p of Plasmodium falciparum. The GPI8p (PF3D7_1128700) was analyzed using various sequence-based and structure-based computational tools such as SIFT, PROVEAN, PredictSNP, SNAP2, I-Mutant, MuPro, ConSurf, NetSurfP, MUSTER, COACH server and STRING server. Of the 34 nsSNPs submitted for functional analysis, 18 nsSNPs (R124 L, N143 K, Y145 F, V157I, T195S, K379E, I392 K, I437 T, Y438H, N439D, Y441H, N442D, N448D, N451D, D457A, D457Y, I458 L and N460 K) were predicted to have deleterious effects on the protein GPI8p. Additionally, I-Mutant 2.0 and MuPro both showed a decrease in stability after mutation as a result of these nsSNPs, suggesting the destabilization of protein. ConSurf findings suggest that most of the regions were highly conserved. In addition, COACH server was used to predict the ligand binding sites. It was found that no mutation was present at the predicted ligand binding site. The results of the STRING database showed that the protein GPI8p interacts with those proteins which either involve the biosynthetic process of attaching GPI anchor to protein or GPI anchor. The present study suggested that the GPI8p could be a novel target for anti-malarial drugs, which provides significant details for further experimentation.

In silico identification of genes involved in chronic metabolic acidosis

AIMS

Chronic metabolic acidosis (CMA) refers to increased plasma acidity due to disturbed acid-base equilibrium in human body. CMA leads to many dysfunctions including disorders of intestinal metabolism and barrier functions. The human body responds to these intestinal dysfunctions by creating a compensatory mechanism at genomic level in intestinal epithelial cells. This study was to identify the molecular pathways involved in metabolic dysfunction and compensatory adaptations in intestinal epithelium during CMA.

MAIN METHODS

In silico approaches were utilized to characterize a set of 88 differentially expressed genes (DEGs) from intestinal cells of rat CMA model. Interaction networks were constructed for DEGs by GeneMANIA and hub genes as well as enriched clusters in the network were screened using GLay. Gene Ontology (GO) was used for enriching functions in each cluster.

KEY FINDINGS

Four gene hubs, i.e., trefoil factor 1, 5-hydroxytryptamine (serotonin) receptor 5a, solute carrier family 6 (neurotransmitter transporter), member 11, and glutamate receptor, ionotropic, n-methyl d-aspartate 2b, exhibiting the highest node degree were predicted. Six biologically related gene clusters were also predicted. Functional enrichment of GO terms predicted neurological processes such as neurological system process regulation and nerve impulse transmission which are related to negative and positive regulation of digestive system processes., intestinal motility and absorption and maintenance of gastrointestinal epithelium.

SIGNIFICANCE

The study predicted several important genomic pathways that potentially play significant roles in metabolic disruptions or compensatory adaptations of intestinal epithelium induced by CMA. The results provide a further insight into underlying molecular mechanisms associated with CMA.