Lipidomic Phenotyping Reveals Extensive Lipid Remodeling during Adipogenesis in Human Adipocytes

Effect of Arthrospira maxima Phycobiliproteins, Rosiglitazone, and 17β-Estradiol on Lipogenic and Inflammatory Gene Expression during 3T3-L1 Preadipocyte Cell Differentiation

The study evaluated the effects of Arthrospira maxima phycobiliproteins (PBPs), rosiglitazone (RSG), and 17β-estradiol (E) on the differentiation process of 3T3-L1 cells and on their regulation of lipogenic and inflammatory gene expression at different stages of the process. The results showed that phycobiliproteins promoted cell proliferation after 24 h of treatment. Furthermore, for all three treatments, the regulation of the highest number of markers occurred on days 6 and 12 of differentiation, regardless of when the treatment was applied. Phycobiliproteins reduced lipid droplet accumulation on days 3, 6, 10, and 13 of the adipogenic process, while rosiglitazone showed no differences compared to the control. On day 6, both phycobiliproteins and rosiglitazone positively regulated Acc1 mRNA. Meanwhile, all three treatments negatively regulated Pparγ and C/ebpα. Phycobiliproteins and estradiol also negatively regulated Ucp1 and Glut4 mRNAs. Rosiglitazone and estradiol, on the other hand, negatively regulated Ppara and Il-6 mRNAs. By day 12, phycobiliproteins and rosiglitazone upregulated Pparγ mRNA and negatively regulated Tnfα and Il-1β. Additionally, phycobiliproteins and estradiol positively regulated Il-6 and negatively regulated Ppara, Ucp2, Acc1, and Glut4. Rosiglitazone and estradiol upregulate C/ebpα and Ucp1 mRNAs. The regulation exerted by phycobiliproteins on the mRNA expression of the studied markers was dependent on the phase of cell differentiation. The results of this study highlight that phycobiliproteins have an anti-adipogenic and anti-inflammatory effect by reducing the expression of adipogenic, lipogenic, and inflammatory genes in 3T3-L1 cells at different stages of the differentiation process.

Transcriptome and Metabolome Analyses Provide Insight into the Glucose-Induced Adipogenesis in Porcine Adipocytes

Glucose is a major energy substrate for porcine adipocytes and also serves as a regulatory signal for adipogenesis and lipid metabolism. In this study, we combined transcriptome and metabolome analyses to reveal the underlying regulatory mechanisms of high glucose (HG) on adipogenesis by comparing differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) identified in porcine adipocytes. Results showed that HG (20 mmol/L) significantly increased fat accumulation in porcine adipocytes compared to low glucose (LG, 5 mmol/L). A total of 843 DEGs and 365 DAMs were identified. Functional enrichment analyses of DEGs found that multiple pathways were related to adipogenesis, lipid metabolism, and immune-inflammatory responses. PPARγ, C/EBPα, ChREBP, and FOS were identified as the key hub genes through module 3 analysis, and PPARγ acted as a central regulator by linking genes involved in lipid metabolism and immune-inflammatory responses. Gene-metabolite networks found that PPARγ-13-HODE was the most important interaction relationship. These results revealed that PPARγ could mediate the cross-talk between adipogenesis and the immune-inflammatory response during adipocyte maturation. This work provides a comprehensive view of the regulatory mechanisms of glucose on adipogenesis in porcine adipocytes.

The lipidomic and inflammatory profiles of visceral and subcutaneous adipose tissues are distinctly regulated by the SGLT2 inhibitor empagliflozin in Zucker diabetic fatty rats

The pharmacological inhibition of sodium-glucose cotransporter 2 (SGLT2) has emerged as a treatment for patients with type 2 diabetes mellitus (T2DM), cardiovascular disease and/or other metabolic disturbances, although some of the mechanisms implicated in their beneficial effects are unknown. The SGLT2 inhibitor (SGLT2i) empagliflozin has been suggested as a regulator of adiposity, energy metabolism, and systemic inflammation in adipose tissue. The aim of our study was to evaluate the impact of a 6-week-empagliflozin treatment on the lipidome of visceral (VAT) and subcutaneous adipose tissue (SAT) from diabetic obese Zucker Diabetic Fatty (ZDF) rats using an untargeted metabolomics approach. We found that empagliflozin increases the content of diglycerides and oxidized fatty acids (FA) in VAT, while in SAT, it decreases the levels of several lysophospholipids and increases 2 phosphatidylcholines. Empagliflozin also reduces the expression of the cytokines interleukin-1 beta (IL-1β), IL-6, tumor necrosis factor-alpha (TNFα), monocyte-chemotactic protein-1 (MCP-1) and IL-10, and of Cd86 and Cd163 M1 and M2 macrophage markers in VAT, with no changes in SAT, except for a decrease in IL-1β. Empagliflozin treatment also shows an effect on lipolysis increasing the expression of hormone-sensitive lipase (HSL) in SAT and VAT and of adipose triglyceride lipase (ATGL) in VAT, together with a decrease in the adipose content of the FA transporter cluster of differentiation 36 (CD36). In conclusion, our data highlighted differences in the VAT and SAT lipidomes, inflammatory profiles and lipolytic function, which suggest a distinct metabolism of these two white adipose tissue depots after the empagliflozin treatment.

Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry

Dysregulated lipid metabolism underpins many chronic diseases including cardiometabolic diseases. Mass spectrometry-based lipidomics is an important tool for understanding mechanisms of lipid dysfunction and is widely applied in epidemiology and clinical studies. With ever-increasing sample numbers, single batch acquisition is often unfeasible, requiring advanced methods that are accurate and robust to batch-to-batch and interday analytical variation. Herein, an optimized comprehensive targeted workflow for plasma and serum lipid quantification is presented, combining stable isotope internal standard dilution, automated sample preparation, and ultrahigh performance liquid chromatography-tandem mass spectrometry with rapid polarity switching to target 1163 lipid species spanning 20 subclasses. The resultant method is robust to common sources of analytical variation including blood collection tubes, hemolysis, freeze-thaw cycles, storage stability, analyte extraction technique, interinstrument variation, and batch-to-batch variation with 820 lipids reporting a relative standard deviation of <30% in 1048 replicate quality control plasma samples acquired across 16 independent batches (total injection count = 6142). However, sample hemolysis of ≥0.4% impacted lipid concentrations, specifically for phosphatidylethanolamines (PEs). Low interinstrument variability across two identical LC-MS systems indicated feasibility for intra/inter-lab parallelization of the assay. In summary, we have optimized a comprehensive lipidomic protocol to support rigorous analysis for large-scale, multibatch applications in precision medicine. The mass spectrometry lipidomics data have been deposited to massIVE: data set identifiers MSV000090952 and 10.25345/C5NP1WQ4S.

Dysbiosis of Gut Microbiota and Lipidomics of Content Induced by Dietary Methionine Restriction in Rice Field Eel (Monopterus albus)

An 8-week feeding trial was conducted using the rice field eel (Monopterus albus) with six isonitrogenous and isoenergetic experimental diets of basic feed supplemented with different levels of methionine (0, 2, 4, 6, 8, or 10 g/kg). This study built upon previous research findings that showed dietary methionine restriction (M0, 0 g/kg) inhibited hepatic fatty acid metabolism and intestinal fatty acid transportation, but both are improved by dietary supplementation with a suitable level of methionine (M8, 8 g/kg). Hence, M0 and M8 were selected to investigate how methionine regulates the gut microbiota and lipidomics of M. albus. Compared with M0, values for gut bacterial Sobs, Shannon, ACE, and Chao1 indices of M8 were remarkably increased (p < 0.05), with Fusobacteria, Firmicutes, and Proteobacteria the dominant phyla and Cetobacterium, Plesiomonas, and Bacillus the main genera in the community under the M0 vs. M8 treatments. However, compared with M0, the proportion of phyla consisting of Fusobacteria decreased in M8, as did the Cetobacterium and Lactococcus at the genus level; conversely, the proportions corresponding to Firmicutes, Proteobacteria, and Chioroflexi phyla increased in M8, as did the Clostridium and Streptococcus genera. Many edges appeared in the circus and networks, demonstrating the interspecies interactions among different operational taxonomic units (OTUs). In addition, various OTUs within the same phylum were clustered within one module. Cooperative interactions were predominant in the two networks, while competitive interactions were prevalent in their submodules. Gut microbiota mainly played roles in nutrition (lipid, amino acid, and carbohydrate) transport and metabolism under the M0 vs. M8 treatments. The PLS-DA scores indicated a significant difference in the main lipidomic components between the M0 and M8 treatment groups. Namely, the TG(26:0/16:0/17:0), TG(28:0/16:0/16:0), TG(26:0/16:0/16:0), and TG(30:0/16:0/16:0)-among others-comprising the gut content were reduced under the M8 treatment (p < 0.001). The genus Clostridium was positively correlated with TG(18:1/18:1/22:5), TG(16:0/17:0/18:1), TG(18:0/18:1/20:3), and other compounds, yet negatively correlated with TG(18:0/17:0/20:0), TG(16:0/17:0/24:0), and TG(16:0/16:0/24:0), among others as well. According to the lipidomics analysis, the predicted KEGG pathways mainly included lipid and glycan biosynthesis and metabolism, and digestive, sensory, and immune systems. In conclusion, methionine restriction disturbed the microbial community balance and induced microbial dysfunctions, whereas methionine supplementation improved the homeostasis of gut microbiota and lipid metabolism of the rice eel.

Obesity III: Obesogen assays: Limitations, strengths, and new directions

There is increasing evidence of a role for environmental contaminants in disrupting metabolic health in both humans and animals. Despite a growing need for well-understood models for evaluating adipogenic and potential obesogenic contaminants, there has been a reliance on decades-old in vitro models that have not been appropriately managed by cell line providers. There has been a quick rise in available in vitro models in the last ten years, including commercial availability of human mesenchymal stem cell and preadipocyte models; these models require more comprehensive validation but demonstrate real promise in improved translation to human metabolic health. There is also progress in developing three-dimensional and co-culture techniques that allow for the interrogation of a more physiologically relevant state. While diverse rodent models exist for evaluating putative obesogenic and/or adipogenic chemicals in a physiologically relevant context, increasing capabilities have been identified for alternative model organisms such as Drosophila, C. elegans, zebrafish, and medaka in metabolic health testing. These models have several appreciable advantages, including most notably their size, rapid development, large brood sizes, and ease of high-resolution lipid accumulation imaging throughout the organisms. They are anticipated to expand the capabilities of metabolic health research, particularly when coupled with emerging obesogen evaluation techniques as described herein.

The Insulin-Sensitizer Pioglitazone Remodels Adipose Tissue Phospholipids in Humans

The insulin-sensitizer pioglitazone exerts its cardiometabolic benefits in type 2 diabetes (T2D) through a redistribution of body fat, from ectopic and visceral areas to subcutaneous adipose depots. Whereas excessive weight gain and lipid storage in obesity promotes insulin resistance and chronic inflammation, the expansion of subcutaneous adipose by pioglitazone is associated with a reversal of these immunometabolic deficits. The precise events driving this beneficial remodeling of adipose tissue with pioglitazone remain unclear, and whether insulin-sensitizers alter the lipidomic composition of human adipose has not previously been investigated. Using shotgun lipidomics, we explored the molecular lipid responses in subcutaneous adipose tissue following 6months of pioglitazone treatment (45mg/day) in obese humans with T2D. Despite an expected increase in body weight following pioglitazone treatment, no robust effects were observed on the composition of storage lipids (i.e., triglycerides) or the content of lipotoxic lipid species (e.g., ceramides and diacylglycerides) in adipose tissue. Instead, pioglitazone caused a selective remodeling of the glycerophospholipid pool, characterized by a decrease in lipids enriched for arachidonic acid, such as plasmanylethanolamines and phosphatidylinositols. This contributed to a greater overall saturation and shortened chain length of fatty acyl groups within cell membrane lipids, changes that are consistent with the purported induction of adipogenesis by pioglitazone. The mechanism through which pioglitazone lowered adipose tissue arachidonic acid, a major modulator of inflammatory pathways, did not involve alterations in phospholipase gene expression but was associated with a reduction in its precursor linoleic acid, an effect that was also observed in skeletal muscle samples from the same subjects. These findings offer important insights into the biological mechanisms through which pioglitazone protects the immunometabolic health of adipocytes in the face of increased lipid storage.

Insights into in vivo adipocyte differentiation through cell-specific labeling in zebrafish

White adipose tissue hyperplasia has been shown to be crucial for handling excess energy in healthy ways. Though adipogenesis mechanisms have been underscored in vitro, we lack information on how tissue and systemic factors influence the differentiation of new adipocytes. While this could be studied in zebrafish, adipocyte identification currently relies on neutral lipid labeling, thus precluding access to cells in early stages of differentiation. Here we report the generation and analysis of a zebrafish line with the transgene fabp4a(-2.7):EGFPcaax. In vivo confocal microscopy of the pancreatic and abdominal visceral depots of transgenic larvae, revealed the presence of labeled mature adipocytes as well as immature cells in earlier stages of differentiation. Through co-labeling for blood vessels, we observed a close interaction of differentiating adipocytes with endothelial cells through cell protrusions. Finally, we implemented hyperspectral imaging and spectral phasor analysis in Nile Red-labeled transgenic larvae and revealed the lipid metabolic transition towards neutral lipid accumulation of differentiating adipocytes. Altogether our work presents the characterization of a novel adipocyte-specific label in zebrafish and uncovers previously unknown aspects of in vivo adipogenesis.

This article has an associated First Person interview with the first author of the paper.

Summary: Analysis of the differentiation of adipocytes in vivo through cell-specific labeling in zebrafish, revealed their early interaction with blood vessels as well as early lipid metabolic changes.

Generation of immune cell containing adipose organoids for in vitro analysis of immune metabolism

Adipose tissue is an organized endocrine organ with important metabolic and immunological functions and immune cell-adipocyte crosstalk is known to drive various disease pathologies. Suitable 3D adipose tissue organoid models often lack resident immune cell populations and therefore require the addition of immune cells isolated from other organs. We have created the first 3D adipose tissue organoid model which could contain and maintain resident immune cell populations of the stromal vascular fraction (SVF) and proved to be effective in studying adipose tissue biology in a convenient manner. Macrophage and mast cell populations were successfully confirmed within our organoid model and were maintained in culture without the addition of growth factors. We demonstrated the suitability of our model for monitoring the lipidome during adipocyte differentiation in vitro and confirmed that this model reflects the physiological lipidome better than standard 2D cultures. In addition, we applied mass spectrometry-based lipidomics to track lipidomic changes in the lipidome upon dietary and immunomodulatory interventions. We conclude that this model represents a valuable tool for immune-metabolic research.