Dataset Information

Integrative Proteome and Lysine Acetylation Analyses of Subcutaneous and Visceral Adipose Tissues in People with Metabolically Unhealthy Obesity

ABSTRACT: Adipose tissue is critical in the development of Metabolically unhealthy obesity (MUO). This study aimed to investigate the different responses and regulations of subcutaneous (SA) and visceral adipose tissue (VA) to MUO by integrative proteome and lysine acetylation (Kac) analyses. This study significantly expanded the known set of proteins and acetylated proteins by reporting the differential expression and Kac modifications in VA and SA in MUO for the first time, thereby establishing a foundation for exploring the pathogenesis and treatment of MUO.

ORGANISM(S): Homo Sapiens

SUBMITTER: Juntao Yang

PROVIDER: PXD056800 | iProX | Tue Oct 15 00:00:00 BST 2024

REPOSITORIES: iProX

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Publications

Depot-specific acetylation profiles of adipose tissues-therapeutic targets for metabolically unhealthy obesity.

Guo Haoyue H Zhang Zhiyi Z Yang Juntao J Liu Jiangfeng J Lin Hongwei H Yin Ningbei N

Diabetology & metabolic syndrome 20250129 1

<h4>Background</h4>Adipose tissue plays a critical role in the development of metabolically unhealthy obesity (MUO), with distinct adipose depots demonstrating functional differences. This study aimed to investigate the unique characteristics of subcutaneous (SA) and visceral adipose tissue (VA) in MUO.<h4>Methods</h4>Paired omental VA and abdominal SA samples were obtained from four male patients with MUO and subjected to Four-Dimensional Data Independent Acquisition (4D-DIA) proteomic and lysi ...[more]

PMID: 39881347

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Project description:Purpose: To investigate alterations in subcutaneous white adipose gene expression induced by genetic AMPK activation in vivo, in mice fed a chow or a high-fat diet. Methods: Subcutaneous white adipose tissue mRNA profiles of wild-type transgenic (WT-Tg) mice and mice expressing a gain-of-function AMPK mutant gamma1 subunit (D316A-Tg) were generated by deep sequencing. Results: RNA sequencing revealed over 3000 differentially expressed genes between WT-Tg and D316A-Tg subcutaneous white adipose tissue (WATsc) from mice fed a high fat diet (HFD), of which many were classified as 'skeletal muscle-associated'. Interestingly, uncoupling protein 1 (UCP1), associated with 'beige' adipocyte formation in WATsc, was not differentially expressed. On a chow diet, many differentially expressed genes were also identified, with gene ontology analysis identifiying glycolysis, TCA cycle and brown fat differentiation as highly enriched; key features of brown adipocyte identity. HFD-associated skeletal-muscle associated gene expression was either not significantly altered, or significantly down-regulated on a chow diet, indicating a diet-induced gene signature in D316A-Tg WATsc. Conclusions: Our study revealed gene signatures indicative of brown adipocyte development on a chow diet, where no overt metabolic phenotype was observed in gain-of-function animals. When fed a HFD, WATsc from D316A-Tg mice displayed a muscle-like gene signature, expressing key components of creatine and calcium thermogenic cycles including Ckmt2 (creatine kinase, mitochondrial 2) Atp2a1 (SERCA1-sarco/endoplasmic reticulum ATPase 1) and ryr1 (ryanodine receptor 1). UCP1 expression was not altered between WT-Tg and D316A-Tg mice fed a HFD. Our findings suggest a novel role for AMPK in the regulation of white adipocyte identity and a potentially novel cell population that, when metabolically challenged, preferrentially utilise muscle-like thermogenic futile cycles independent of UCP1 to mediate whole organism energy expenditure.

Project description:To map the genetics of gene expression in metabolically relevant tissues and investigate the diversity of expression SNPs (eSNPs) in multiple tissues from the same individual, we collected four tissues from approximately 1,000 patients undergoing Roux-en-y gastric bypass and clinical traits associated with their weight loss and co-morbidities. We then performed high-throughput genotyping and gene expression profiling and carried out a genome-wide association analyses for more than one hundred thousand gene expression traits representing four metabolically relevant tissues; liver, subcutaneous adipose, omental adipose and stomach. We successfully identified 24,531 eSNPs corresponding to ~10,000 distinct genes. This represents the greatest number of eSNPs identified to our knowledge by any study to date and the first study to identify eSNPs from stomach tissue. We then demonstrate how these eSNPs provide a high quality disease map for each tissue in morbidly obese patients to not only inform genetic associations indentified in this cohort, but in previously published genome wide association studies as well. eSNPs and gene co-expression modules identification in morbidly obese patients represent a great resource that will aid in elucidating the key networks associated with morbid obesity, response to RYGB and disease as a whole. Keywords: Tissue profiling in a human cohort. Subcutaneous adipose tissue was collected from patients at the time of RYGB surgery at Massachusetts General Hospital between 2000 and 2007. Samples were collected in RNAlater (Ambion/Applied Biosystems), stored at -80° and shipped to Rosetta Inpharmatics Gene Expression Laboratory Seattle, WA for extraction, amplification, labeling, and microarray processing. Samples processed ranged in size from 100-200mg. Total RNA extracted from subcutaneous adipose was converted to fluorescently labeled cRNA that was hybridized to custom 44K DNA oligonucleotide microarrays manufactured by Agilent Technologies as described previously (Hughes et al. 2001; Schadt et al. 2008). Successful gene expression profiling results were collected from 701 subcutaneous adipose samples.

Dataset Information

Integrative Proteome and Lysine Acetylation Analyses of Subcutaneous and Visceral Adipose Tissues in People with Metabolically Unhealthy Obesity

Publications

Depot-specific acetylation profiles of adipose tissues-therapeutic targets for metabolically unhealthy obesity.

Similar Datasets

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