Autophagic Regulation of Adipogenesis Through TP53INP2: Insights from In Silico and In Vitro Analysis.

Obesity is an epidemic disease associated with multimorbidity resulting in higher mortality risk. The imbalance between energy storage and expenditure is the prime factor in the prognosis of the disease. Specifically, excessive lipid storage through adipogenesis leads to obesity. Adipogenesis is the process that converts preadipocytes into mature adipocytes by regulating major transcription factors like PPARγ and C/EBPα, contributes to lipid storage in adipose tissue. On the contrary, autophagy is a self-degradative process that maintains homeostasis in adipose tissue by regulating adipogenesis and lipolysis. TP53INP2 is a key player that regulates the autophagy process, and it negatively regulates adipogenesis and lipid storage. The gene expression profile GSE93637 was retrieved from the GEO database and analyzed using an integrated bioinformatics approach. The differentially expressed genes (DEGs) were analyzed using R-Bioconductor for TP53INP2 knockdown microarray dataset of 3T3L1 cells, and the DEGs were analyzed for the functional enrichment analysis. Further, the genes involved in the potential biological and molecular functions were evaluated for pathway enrichment analysis by KEGG (Kyoto Encyclopedia of Genes and Genomes). A total of 726 DEGs were found including 391 upregulated and 335 downregulated genes. Further, the functional and pathway enrichment analysis was employed to identify the highly interacting genes, and we identified a total of 56 genes that are highly interacting through a protein-protein interaction network. The DEGs mainly regulate the Peroxisome proliferator-activated receptor (PPAR) signaling pathway, lipolysis, and autophagy. Further, we investigated the associated Hub genes for enriched pathway genes and found the involvement of two autophagic genes ATG7 and sequestosome 1 (p62). In addition, in vitro studies of qRT-PCR (Quantitative real-time polymerase chain reaction) and Western blot analysis revealed that increased autophagy resulted in reduced lipid storage through down-regulation of the adipogenic gene. Moreover, increased expression of autophagic gene TP53INP2 and ATG7 facilitates the down-regulation of p62 and PPARγ gene resulting in lipolysis in mature adipocytes through autophagy. There is no specific treatment to reduce obesity other than a caloric diet and exercise. Hence, this study provides sufficient evidence to conclude that TP53INP2 negatively regulates adipogenesis and increases the degradation of lipids in mature adipocytes which is crucial for reducing obesity. Therefore, it is plausible to consider TP53INP2 as a promising therapeutic target for managing adipogenesis and obesity. However, further studies are necessary to validate their functional and molecular pathway analysis in the regulation of adipogenesis and obesity.

Dynamics of redox signaling in aging via autophagy, inflammation, and senescence.

Review paper attempts to explain the dynamic aspects of redox signaling in aging through autophagy, inflammation, and senescence. It begins with ROS source in the cell, then states redox signaling in autophagy, and regulation of autophagy in aging. Next, we discuss inflammation and redox signaling with various pathways involved: NOX pathway, ROS production via TNF-α, IL-1ß, xanthine oxidase pathway, COX pathway, and myeloperoxidase pathway. Also, we emphasize oxidative damage as an aging marker and the contribution of pathophysiological factors to aging. In senescence-associated secretory phenotypes, we link ROS with senescence, aging disorders. Relevant crosstalk between autophagy, inflammation, and senescence using a balanced ROS level might reduce age-related disorders. Transducing the context-dependent signal communication among these three processes at high spatiotemporal resolution demands other tools like multi-omics aging biomarkers, artificial intelligence, machine learning, and deep learning. The bewildering advancement of technology in the above areas might progress age-related disorders diagnostics with precision and accuracy.

Autophagy: a molecular switch to regulate adipogenesis and lipolysis.

Obesity is a complex epidemic disease caused by an imbalance of adipose tissue function that results in hyperglycemia, hyperlipidemia and insulin resistance which further develop into type 2 diabetes, cardiovascular disease and nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. Adipose tissue is responsible for fat storage; white adipose tissue stores excess energy as fat for availability during starvation, whereas brown adipose tissue regulates thermogenesis through fat oxidation using uncoupling protein 1. However, hypertrophic fat storage results in inflammation and increase the chances for obesity which triggers autophagy genes and lipolytic enzymes to regulate lipid metabolism. Autophagy degrades cargo molecule with the help of lysosome and redistributes the energy back to the cell. Autophagy regulates adipocyte differentiation by modulating master regulators of adipogenesis. Adipogenesis is the process which stores excessive energy in the form of lipid droplets. Lipid droplets (LD) are dynamic cellular organelles that store toxic free-fatty acids into neutral triglycerides in adipose tissue. LD activates both lipolysis and lipophagy to degrade excess triglycerides. In obese tissue, autophagy is activated via pro-inflammatory cytokines produced by surplus fat stored in the adipose tissue. This review focused on the process of autophagy and adipogenesis and the transcription factors that regulate lipogenesis and lipolysis in the adipose tissue. We have also discussed about the importance of autophagic regulation within adipose tissue which controls the onset of obesity and its associated diseases.

Dynamics of HOX gene expression and regulation in adipocyte development.

HOX proteins are homeodomain-containing transcription factors that play a central role in development. We have applied genome-wide approaches to develop time-dependent profile of differentially expressed genes in early and mature adipocytes. The list of differentially expressed HOX genes were developed by analyzing the microarray datasets of murine adipocyte samples at different time points of development. Since these datasets were obtained from Gene Expression Omnibus (GEO), we were able to find a new HOX gene, HOXC13 in adipogenesis. To investigate whether these members of the homeobox gene family are expressed and regulated in preadipocytes or mature adipocytes, RNA was isolated from 3T3-L1 preadipocyte cells at different time point's through-out the preadipocyte and adipocyte state. A reverse transcriptase-polymerase chain reaction strategy was applied for the analysis of gene expression. We have observed that HOXA5 and HOXC13 were differentially expressed in preadipocytes and HOXD4 and HOXD8 in mature adipocytes. To understand this difference in expression pattern, we have considered to investigate the role of the major regulators of adipogenesis in HOX gene regulation. Since Retinoic acid receptor (RAR) was reported previously as a regulator of Hox genes, we chose the combination of Peroxisome proliferator-activated receptor gamma (PPARγ) and Retinoic X receptor (RXR) which are modulated by the presence of RAR. To provide a detailed analysis of retinoic acid (RA) and/or PPARγ induced transcriptional and epigenetic changes within the homeotic clusters of mouse fibroblast cells (3T3-L1), we have performed a promoter mapping of HOX genes and observed an enriched binding site for PPARγ and RXR in their promoter regions. We further confirmed this PPARγ and RXR binding to HOX gene promoters by re-analyzing the anti-PPARγ/anti-RXR ChIP-Seq data. Based on the results, we modulated the PPARγ expression at the transcriptional and translational levels by using 5 different pharmacological molecules (TSA, GW9662, ATRA, FH535, and Pioglitazone) to elucidate their effect on the HOX gene transcription. These pharmacological molecules had a direct or indirect regulatory effect on the PPARγ activity. We observed that PPARγ suppression alone is enough for the upregulation of HOXA5 and HOXD4 genes. In addition, HOXD8 regulation was mediated by RAR activation in mature adipocytes but the regulation of HOXC13 gene expression was not clear. We suggest that it might be partially mediated through suppressing PPARγ activation. Further insights are required to provide a mechanistic detail about HOX gene regulation through PPARγ. In this study, we have reported a time-dependent expression analysis of HOXA5, HOXD4, HOXD8, and HOXC13 in preadipocytes and mature adipocytes. Also, we have suggested PPARγ/RAR dependent regulation for these genes during adipogenesis.