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Bioinformatic analysis of functional proteins involved in obesity associated with diabetes.

ABSTRACT: The twin epidemic of diabetes and obesity pose daunting challenges worldwide. The dramatic rise in obesity-associated diabetes resulted in an alarming increase in the incidence and prevalence of obesity an important complication of diabetes. Differences among individuals in their susceptibility to both these conditions probably reflect their genetic constitutions. The dramatic improvements in genomic and bioinformatic resources are accelerating the pace of gene discovery. It is tempting to speculate the key susceptible genes/proteins that bridges diabetes mellitus and obesity. In this regard, we evaluated the role of several genes/proteins that are believed to be involved in the evolution of obesity associated diabetes by employing multiple sequence alignment using ClustalW tool and constructed a phylogram tree using functional protein sequences extracted from NCBI. Phylogram was constructed using Neighbor-Joining Algorithm a bioinformatic tool. Our bioinformatic analysis reports resistin gene as ominous link with obesity associated diabetes. This bioinformatic study will be useful for future studies towards therapeutic inventions of obesity associated type 2 diabetes.

SUBMITTER: Rao AA

PROVIDER: S-EPMC3614673 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature

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Bioinformatic analysis of functional proteins involved in obesity associated with diabetes.

Rao Allam Appa AA Tayaru N Manga NM Thota Hanuman H Changalasetty Suresh Babu SB Thota Lalitha Saroja LS Gedela Srinubabu S

International journal of biomedical science : IJBS 20080301 1

The twin epidemic of diabetes and obesity pose daunting challenges worldwide. The dramatic rise in obesity-associated diabetes resulted in an alarming increase in the incidence and prevalence of obesity an important complication of diabetes. Differences among individuals in their susceptibility to both these conditions probably reflect their genetic constitutions. The dramatic improvements in genomic and bioinformatic resources are accelerating the pace of gene discovery. It is tempting to specu ...[more]

PMID: 23675069

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Project description:PurposeTo investigate the potential pathophysiological association between tuberculosis (TB) and diabetes mellitus (DM) using bioinformatic analyses.Patients and methodsGene expression datasets for healthy controls (HCs), TB patients, DM patients, TB+DM patients (GSE114192), and metformin-treated cells (GSE102677) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified from pairwise dataset comparisons TB vs HCs and DM vs HCs. DEGs were verified by comparing them to DEGs for TB+DM vs HCs. Enrichment analysis of DEGs common to all three dataset comparisons was conducted using DAVID. The protein-protein interaction (PPI) network was established via STRING and visualised in Cytoscape. Hub genes were identified using the Cytoscape plug-in cytoHubba and then were verified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis. Targeted miRNA prediction analysis identified metformin treatment-induced gene expression changes in peripheral blood mononuclear cells.ResultsA total of 422 DEGs were common to all three dataset comparisons. Functional enrichment analysis revealed these DEGs were enriched for functional terms of type I interferon signaling pathway, innate immune response, inflammatory response, and infectious diseases. Ten hub genes identified using PPI network analysis were screened for interactions with metformin target gene INS using cytoHubba based on maximal clique centrality (MCC) score. Subsequently, five hub genes were predicted to functionally interact with INS, including STAT1, IFIT3, RSAD2, IFI44L, and XAF1, as verified by RT-qPCR. Meanwhile, seven miRNAs (miR-3680-3p, miR-3059-5p, miR-629-3p, miR-29b-2-5p, miR-514b-5p, miR-4755-5p, miR-4691-3p) were associated with regulation of hub genes. Notably, six hub genes (STAT1, IFIT3, RSAD2, ISG15, IFI44, IFI6) were down-regulated in cells exposed to both metformin and Mycobacterium tuberculosis antigens.ConclusionNetwork hub genes hold promise as disease status biomarkers and as metformin treatment targets for alleviating TB and DM. This study describes a strategy for exploring pathogenic mechanisms of diseases such as TB and DM.

Project description:Background: Unlike mammals, zebrafish have a remarkable capacity to regenerate a variety of tissues, including central nervous system tissue. The function of macrophages in tissue regeneration is of great interest, as macrophages respond and participate in the landscape of events that occur following tissue injury in all vertebrate species examined. Understanding macrophage populations in regenerating tissue (such as in zebrafish) may inform strategies that aim to regenerate tissue in humans. We recently published an RNA-seq experiment that identified genes enriched in microglia/macrophages in regenerating zebrafish retinas. Interestingly, a small number of transcripts differentially expressed by retinal microglia/macrophages during retinal regeneration did not have predicted orthologs in human or mouse. We reasoned that at least some of these genes could be functionally important for tissue regeneration, but most of these genes have not been studied experimentally and their functions are largely unknown. To reveal their possible functions, we performed a variety of bioinformatic analyses aimed at identifying the presence of functional protein domains as well as orthologous relationships to other species.Results: Our analyses identified putative functional domains in predicted proteins for a number of selected genes. For example, we confidently predict kinase function for one gene, cytokine/chemokine function for another, and carbohydrate enzymatic function for a third. Predicted orthologs were identified for some, but not all, genes in species with described regenerative capacity, and functional domains were consistent with identified orthologs. Comparison to other published gene expression datasets suggest that at least some of these genes could be important in regenerative responses in zebrafish and not necessarily in response to microbial infection.Conclusions: This work reveals previously undescribed putative function of several genes implicated in regulating tissue regeneration. This will inform future work to experimentally determine the function of these genes in vivo, and how these genes may be involved in microglia/macrophage roles in tissue regeneration.

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Bioinformatic analysis of functional proteins involved in obesity associated with diabetes.

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Bioinformatic analysis of functional proteins involved in obesity associated with diabetes.

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