Type III Collagen is Required for Adipogenesis and Actin Stress Fibre Formation in 3T3-L1 Preadipocytes

Mapping adipocyte interactome networks by HaloTag-enrichment-mass spectrometry

Mapping protein interaction complexes in their natural state in vivo is arguably the Holy Grail of protein network analysis. Detection of protein interaction stoichiometry has been an important technical challenge, as few studies have focused on this. This may, however, be solved by artificial intelligence (AI) and proteomics. Here, we describe the development of HaloTag-based affinity purification mass spectrometry (HaloMS), a high-throughput HaloMS assay for protein interaction discovery. The approach enables the rapid capture of newly expressed proteins, eliminating tedious conventional one-by-one assays. As a proof-of-principle, we used HaloMS to evaluate the protein complex interactions of 17 regulatory proteins in human adipocytes. The adipocyte interactome network was validated using an in vitro pull-down assay and AI-based prediction tools. Applying HaloMS to probe adipocyte differentiation facilitated the identification of previously unknown transcription factor (TF)-protein complexes, revealing proteome-wide human adipocyte TF networks and shedding light on how different pathways are integrated.

Clinical-Genomic Analysis of 1261 Patients with Ehlers-Danlos Syndrome Outlines an Articulo-Autonomic Gene Network (Entome)

Systematic evaluation of 80 history and 40 history findings diagnosed 1261 patients with Ehlers-Danlos syndrome (EDS) by direct or online interaction, and 60 key findings were selected for their relation to clinical mechanisms and/or management. Genomic testing results in 566 of these patients supported EDS relevance by their differences from those in 82 developmental disability patients and by their association with general rather than type-specific EDS findings. The 437 nuclear and 79 mitochondrial DNA changes included 71 impacting joint matrix (49 COL5), 39 bone (30 COL1/2/9/11), 22 vessel (12 COL3/8VWF), 43 vessel-heart (17FBN1/11TGFB/BR), 59 muscle (28 COL6/12), 56 neural (16 SCN9A/10A/11A), and 74 autonomic (13 POLG/25porphyria related). These genes were distributed over all chromosomes but the Y, a network analogized to an 'entome' where DNA change disrupts truncal mechanisms (skin constraint, neuromuscular support, joint vessel flexibility) and produces a mirroring cascade of articular and autonomic symptoms. The implied sequences of genes from nodal proteins to hypermobility to branching tissue laxity or dysautonomia symptoms would be ideal for large language/artificial intelligence analyses.

Human visceral adipose tissue microvascular endothelial cell isolation and establishment of co-culture with white adipocytes to analyze cell-cell communication

Communication between adipocytes and endothelial cells (EC) is suggested to play an important role in the metabolic function of white adipose tissue. In order to generate tools to investigate in detail the physiology and communication of EC and adipocytes, a method for isolation of adipose microvascular EC from visceral adipose tissue (VAT) biopsies of subjects with obesity was developed. Moreover, mature white adipocytes were isolated from the VAT biopsies by a method adapted from a previously published Membrane aggregate adipocytes culture (MAAC) protocol. The identity and functionality of the cultivated and isolated adipose microvascular EC (AMvEC) was validated by imaging their morphology, analyses of mRNA expression, fluorescence activated cell sorting (FACS), immunostaining, low-density lipoprotein (LDL) uptake, and in vitro angiogenesis assays. Finally, we established a new trans filter co-culture system (membrane aggregate adipocyte and endothelial co-culture, MAAECC) for the analysis of communication between the two cell types. EC-adipocyte communication in this system was validated by omics analyses, revealing several altered proteins belonging to pathways such as metabolism, intracellular transport and signal transduction in adipocytes co-cultured with AMvEC. In reverse experiments, induction of several pathways including endothelial development and functions was found in AMvEC co-cultured with adipocytes. In conclusion, we developed a robust method to isolate EC from small quantities of human VAT. Furthermore, the MAAECC system established during the study enables one to study the communication between primary white adipocytes and EC or vice-versa and could also be employed for drug screening.

Single-cell transcriptome dataset of human and mouse in vitro adipogenesis models

Adipogenesis is a process in which fat-specific progenitor cells (preadipocytes) differentiate into adipocytes that carry out the key metabolic functions of the adipose tissue, including glucose uptake, energy storage, and adipokine secretion. Several cell lines are routinely used to study the molecular regulation of adipogenesis, in particular the immortalized mouse 3T3-L1 line and the primary human Simpson-Golabi-Behmel syndrome (SGBS) line. However, the cell-to-cell variability of transcriptional changes prior to and during adipogenesis in these models is not well understood. Here, we present a single-cell RNA-Sequencing (scRNA-Seq) dataset collected before and during adipogenic differentiation of 3T3-L1 and SGBS cells. To minimize the effects of experimental variation, we mixed 3T3-L1 and SGBS cells and used computational analysis to demultiplex transcriptomes of mouse and human cells. In both models, adipogenesis results in the appearance of three cell clusters, corresponding to preadipocytes, early and mature adipocytes. These data provide a groundwork for comparative studies on these widely used in vitro models of human and mouse adipogenesis, and on cell-to-cell variability during this process.

Collagens Regulating Adipose Tissue Formation and Functions

The globally increasing prevalence of obesity is associated with the development of metabolic diseases such as type 2 diabetes, dyslipidemia, and fatty liver. Excess adipose tissue (AT) often leads to its malfunction and to a systemic metabolic dysfunction because, in addition to storing lipids, AT is an active endocrine system. Adipocytes are embedded in a unique extracellular matrix (ECM), which provides structural support to the cells as well as participating in the regulation of their functions, such as proliferation and differentiation. Adipocytes have a thin pericellular layer of a specialized ECM, referred to as the basement membrane (BM), which is an important functional unit that lies between cells and tissue stroma. Collagens form a major group of proteins in the ECM, and some of them, especially the BM-associated collagens, support AT functions and participate in the regulation of adipocyte differentiation. In pathological conditions such as obesity, AT often proceeds to fibrosis, characterized by the accumulation of large collagen bundles, which disturbs the natural functions of the AT. In this review, we summarize the current knowledge on the vertebrate collagens that are important for AT development and function and include basic information on some other important ECM components, principally fibronectin, of the AT. We also briefly discuss the function of AT collagens in certain metabolic diseases in which they have been shown to play central roles.

Single-cell transcriptome dataset of human and mouse in vitro adipogenesis models

Adipogenesis is a process in which fat-specific progenitor cells (preadipocytes) differentiate into adipocytes that carry out the key metabolic functions of the adipose tissue, including glucose uptake, energy storage, and adipokine secretion. Several cell lines are routinely used to study the molecular regulation of adipogenesis, in particular the immortalized mouse 3T3-L1 line and the primary human Simpson-Golabi-Behmel syndrome (SGBS) line. However, the cell-to-cell variability of transcriptional changes prior to and during adipogenesis in these models is not well understood. Here, we present a single-cell RNA-Sequencing (scRNA-Seq) dataset collected before and during adipogenic differentiation of 3T3-L1 and SGBS cells. To minimize the effects of experimental variation, we mixed 3T3-L1 and SGBS cells and used computational analysis to demultiplex transcriptomes of mouse and human cells. In both models, adipogenesis results in the appearance of three cell clusters, corresponding to preadipocytes, early and mature adipocytes. These data provide a groundwork for comparative studies on human and mouse adipogenesis, as well as on cell-to-cell variability in gene expression during this process.

Functional differentiation of the ovine preadipocytes -insights from gene expression profiling

The preadipocytes differentiation is a vital process of lipogenesis; exploring the molecular mechanisms of lipogenesis contributes to improve the meat quality and final commercial income. Lipogenesis has been widely reported in other livestock, but little is known about the gene expression profiles at different stages during preadipocytes differentiation in sheep. In this study, ovine preadipocytes were cultured in vitro and then induced to begin differentiation. Then, the gene expression profiles of preadipocytes collected on day 0 (D0), day 2 (D2), and day 8 (D8) of differentiation were analyzed by RNA-seq technology. According to the findings, 2254 differentially expressed genes (DEGs) were found in D2 vs D0; 1817 DEGs and 1902 DEGs were found in D8 vs D0 and D8 vs D2, respectively. The DEGs were found to be enriched in several biological processes, including focal adhesion, ECM-receptor interaction, PI3K-Akt signaling pathway, steroid biosynthesis, and MAPK signaling pathway, according to Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The regulatory network of the DEGs related to ovine preadipocytes differentiation was systematically constructed, which showed that hub genes might modulate ovine preadipocytes differentiation. In summary, preadipocyte differentiation is regulated by several key genes, including ACACB, CXCL6, SREBF1, INSIG1, APOE, GJA1, CDH11, SYNE1, PCSK1, S100A4, FN1, PLIN2, CXCL6, FN1, PTX3, and FABP3. This study provides a deeper knowledge of the roles of genes in sheep lipogenesis by revealing global gene expression profiles during preadipocyte differentiation.

Tri-Lineage Differentiation Potential of Osteosarcoma Cell Lines and Human Bone Marrow Stromal Cells from Different Anatomical Locations

The bone cancer osteosarcoma, found mainly in adolescents, routinely forms around the growth plate/metaphysis of long bones. Bone marrow composition changes with age, shifting from a more hematopoietic to an adipocyte-rich tissue. This conversion occurs in the metaphysis during adolescence, implicating a link between bone marrow conversion and osteosarcoma initiation. To assess this, the tri-lineage differentiation potential of human bone marrow stromal cells (HBMSCs) isolated from the femoral diaphysis/metaphysis (FD) and epiphysis (FE) was characterized and compared to two osteosarcoma cell lines, Saos-2 and MG63. Compared to FE-cells, FD-cells showed an increase in tri-lineage differentiation. Additionally, differences were found between the Saos-2 cells exhibiting higher levels of osteogenic differentiation, lower adipogenic differentiation, and a more developed chondrogenic phenotype than MG63, with the Saos-2 being more comparable to FD-derived HBMSCs. The differences found between the FD and FE derived cells are consistent with the FD region containing more hematopoietic tissue compared to the FE. This may be related to the similarities between FD-derived cells and Saos-2 cells during osteogenic and chondrogenic differentiation. These studies reveal distinct differences in the tri-lineage differentiations of 'hematopoietic' and 'adipocyte rich' bone marrow, which correlate with specific characteristics of the two osteosarcoma cell lines.

MMPP promotes adipogenesis and glucose uptake via binding to the PPARγ ligand binding domain in 3T3-L1 MBX cells

Peroxisome proliferator-activated receptor-gamma (PPARγ) is a transcription factor involved in adipogenesis, and its transcriptional activity depends on its ligands. Thiazolidinediones (TZDs), well-known PPARγ agonists, are drugs that improve insulin resistance in type 2 diabetes. However, TZDs are associated with severe adverse effects. As current therapies are not well designed, novel PPARγ agonists have been investigated in adipocytes. (E)-2-methoxy-4-(3-(4-methoxyphenyl) prop-1-en-1-yl) phenol (MMPP) is known to have anti-arthritic, anti-inflammatory, and anti-cancer effects. In this study, we demonstrated the adipogenic effects of MMPP on the regulation of PPARγ transcriptional activity during adipocyte differentiation in vitro. MMPP treatment increased PPARγ transcriptional activity, and molecular docking studies revealed that MMPP binds directly to the PPARγ ligand binding domain. MMPP and rosiglitazone showed similar binding affinities to the PPARγ. MMPP significantly promoted lipid accumulation in adipocyte cells and increased the expression of C/EBPβ and the levels of p-AKT, p-GSK3, and p-AMPKα at an early stage. MMPP enhanced the expression of adipogenic markers such as PPARγ, C/EBPα, FAS, ACC, GLUT4, FABP4 and adiponectin in the late stage. MMPP also improved insulin sensitivity by increasing glucose uptake. Thus, MMPP, as a PPARγ agonist, may be a potential drug for type 2 diabetes and metabolic disorders, which may help increase adipogenesis and insulin sensitivity.

Functions of G protein-coupled receptor 56 in health and disease

Human G protein-coupled receptor 56 (GPR56) is encoded by gene ADGRG1 from chromosome 16q21 and is homologously encoded in mice, at chromosome 8. Both 687 and 693 splice forms are present in humans and mice. GPR56 has a 381 amino acid-long N-terminal extracellular segment and a GPCR proteolysis site upstream from the first transmembrane domain. GPR56 is mainly expressed in the heart, brain, thyroid, platelets, and peripheral blood mononuclear cells. Accumulating evidence indicates that GPR56 promotes the formation of myelin sheaths and the development of oligodendrocytes in the cerebral cortex of the central nervous system. Moreover, GPR56 contributes to the development and differentiation of hematopoietic stem cells, induces adipogenesis, and regulates the function of immune cells. The lack of GPR56 leads to nervous system dysfunction, platelet disorders, and infertility. Abnormal expression of GPR56 is related to the malignant transformation and tumor metastasis of several cancers including melanoma, neuroglioma, and gastrointestinal cancer. Metabolic disorders and cardiovascular diseases are also associated with dysregulation of GPR56 expression, and GPR56 is involved in the pharmacological resistance to some antidepressant and cancer drug treatments. In this review, the molecular structure, expression profile, and signal transduction of GPR56 are introduced, and physiological and pathological functions of GRP56 are comprehensively summarized. Attributing to its significant biological functions and its long N-terminal extracellular region that interacts with multiple ligands, GPR56 is becoming an attractive therapeutic target in treating neurological and hematopoietic diseases.

Effect of Lauric vs. Oleic Acid-Enriched Diets on Leptin Autoparacrine Signalling in Male Mice

High-fat diets enriched with lauric acid (SOLF) do not enhance leptin production despite expanding white adipose tissue (WAT). Our study aimed at identifying the influence of SOLF vs. oleic acid-enriched diets (UOLF) on the autoparacrine effect of leptin and was carried out on eight-week-old mice consuming control chow, UOLF or SOLF. Phosphorylation of kinases integral to leptin receptor (LepR) signalling pathways (705Tyr-STAT3, 473Ser-Akt, 172Thr-AMPK), adipocyte-size distribution, fatty acid content, and gene expression were analyzed in WAT. SOLF enhanced basal levels of phosphorylated proteins but reduced the ability of leptin to enhance kinase phosphorylation. In contrast, UOLF failed to increase basal levels of phosphorylated proteins and did not modify the effect of leptin. Both SOLF and UOLF similarly affected adipocyte-size distribution, and the expression of genes related with adipogenesis and inflammation. WAT composition was different between groups, with SOLF samples mostly containing palmitic, myristic and lauric acids (>48% w/w) and UOLF WAT containing more than 80% (w/w) of oleic acid. In conclusion, SOLF appears to be more detrimental than UOLF to the autoparacrine leptin actions, which may have an impact on WAT inflammation. The effect of SOLF and UOLF on WAT composition may affect WAT biophysical properties, which are able to condition LepR signaling.

Characterization of DNA methylation as well as mico-RNA expression and screening of epigenetic markers in adipogenesis

This study aimed to use bioinformatics methods to characterize epigenetic changes in terms of micro-RNA(miRNA) expression and DNA methylation during adipogenesis. The mRNA and miRNA expression microarray and DNA methylation dataset were obtained from the GEO database. Differentially expressed genes (DEGs), differentially expressed miRNAs (DEMs) and differentially methylated probes (DMPs) were filtered using the limma package. The R language cluster profile package was used for functional and enrichment analysis. A protein–protein interaction (PPI) network was constructed using STRING and visualized in Cytoscape. The Connection map (CMap) website tool was used to screen potential therapeutic drugs for adipogenesis. When comparing the early and late stages of adipogenesis, 111 low miRNA targeted upregulated genes and 64 high miRNA targeted downregulated genes were obtained, as well as 663 low-methylated high-expressed genes and 237 high-methylated low-expressed genes. In addition, 41 genes (24 upregulated and 17 downregulated) were simultaneously regulated by abnormal miRNA changes and DNA methylation. Ten chemicals were identified as putative therapeutics for adipogenesis. In addition, among the dual-regulated genes identified, CANX, HNRNPA1, MCL1, and PPIF may play key roles in the epigenetic regulation of adipogenesis and may serve as aberrant methylation or miRNA targeting biomarkers.