Biodegradable, bile salt microparticles for localized fat dissolution

Assessing causal associations of bile acids with obesity indicators: A Mendelian randomization study

Maintaining a balanced bile acids (BAs) metabolism is essential for lipid and cholesterol metabolism, as well as fat intake and absorption. The development of obesity may be intricately linked to BAs and their conjugated compounds. Our study aims to assess how BAs influence the obesity indicators by Mendelian randomization (MR) analysis. Instrumental variables of 5 BAs were obtained from public genome-wide association study databases, and 8 genome-wide association studies related to obesity indicators were used as outcomes. Causal inference analysis utilized inverse-variance weighted (IVW), weighted median, and MR-Egger methods. Sensitivity analysis involved MR-PRESSO and leave-one-out techniques to detect pleiotropy and outliers. Horizontal pleiotropy and heterogeneity were assessed using the MR-Egger intercept and Cochran Q statistic, respectively. The IVW analysis revealed an odds ratio of 0.94 (95% confidence interval: 0.88, 1.00; P = .05) for the association between glycolithocholate (GLCA) and obesity, indicating a marginal negative causal association. Consistent direction of the estimates obtained from the weighted median and MR-Egger methods was observed in the analysis of the association between GLCA and obesity. Furthermore, the IVW analysis demonstrated a suggestive association between GLCA and trunk fat percentage, with a beta value of -0.014 (95% confidence interval: -0.027, -0.0004; P = .04). Our findings suggest a potential negative causal relationship between GLCA and both obesity and trunk fat percentage, although no association survived corrections for multiple comparisons. These results indicate a trend towards a possible association between BAs and obesity, emphasizing the need for future studies.

Microbial Fermentation Enhances the Effect of Black Tea on Hyperlipidemia by Mediating Bile Acid Metabolism and Remodeling Intestinal Microbes

Black tea (BT), the most consumed tea worldwide, can alleviate hyperlipidemia which is a serious threat to human health. However, the quality of summer BT is poor. It was improved by microbial fermentation in a previous study, but whether it affects hypolipidemic activity is unknown. Therefore, we compared the hypolipidemic activity of BT and microbially fermented black tea (EFT). The results demonstrated that BT inhibited weight gain and improved lipid and total bile acid (TBA) levels, and microbial fermentation reinforced this activity. Mechanistically, both BT and EFT mediate bile acid circulation to relieve hyperlipidemia. In addition, BT and EFT improve dyslipidemia by modifying the gut microbiota. Specifically, the increase in Lactobacillus johnsonii by BT, and the increase in Mucispirillum and Colidextribacter by EFT may also be potential causes for alleviation of hyperlipidemia. In summary, we demonstrated that microbial fermentation strengthened the hypolipidemic activity of BT and increased the added value of BT.

Multi-Functional Polymer Nanoparticles with Enhanced Adipocyte Uptake and Adipocytolytic Efficacy

Multi-functional polymer nanoparticles have been widely utilized to improve cellular uptake and enhance therapeutic efficacy. In this study, it is hypothesized that the cellular uptake of poly(D,L-lactide-co-glycolide) (PLG) nanoparticles loaded with calcium carbonate minerals into adipocytes can be improved by covalent modification with nona-arginine (R9 ) peptide. It is further hypothesized that the internalization mechanism of R9 -modified PLG nanoparticles by adipocytes may be contingent on the concentration of R9 peptide present in the nanoparticles. R9 -modified PLG nanoparticles followed the direct penetration mechanism when the concentration of R9 peptide in the nanoparticles reached 38 µM. Notably, macropinocytosis is the major endocytic mechanism when the R9 peptide concentration is ≤ 26 µM. The endocytic uptake of the nanoparticles effectively generated carbon dioxide gas at an endosomal pH, resulting in significant adipocytolytic effects in vitro, which are further supported by the findings in an obese mouse model induced by high-fat diet. Gas-generating PLG nanoparticles, modified with R9 peptide, demonstrated localized reduction of adipose tissue (reduction of 13.1%) after subcutaneous injection without significant side effects. These findings highlight the potential of multi-functional polymer nanoparticles for the development of effective and targeted fat reduction techniques, addressing both health and cosmetic considerations.

Chenodeoxycholic Acid-Loaded Nanoparticles Are Sufficient to Decrease Adipocyte Size by Inducing Mitochondrial Function

Excess fat accumulation is not only associated with metabolic diseases but also negatively impacts physical appearance and emotional well-being. Bile acid, the body's natural emulsifier, is one of the few FDA-approved noninvasive therapeutic options for double chin (submental fat) reduction. Synthetic sodium deoxycholic acid (NaDCA) causes adipose cell lysis; however, its side effects include inflammation, bruising, and necrosis. Therefore, we investigated if an endogenous bile acid, chenodeoxycholic acid (CDCA), a well-known signaling molecule, can be beneficial without many of the untoward effects. We first generated CDCA-loaded nanoparticles to achieve sustained and localized delivery. Then, we injected them into the subcutaneous fat depot and monitored adipocyte size and mitochondrial function. Unlike NaDCA, CDCA did not cause cytolysis. Instead, we demonstrate that a single injection of CDCA-loaded nanoparticles into the subcutaneous fat reduced the adipocyte size by promoting fat burning and mitochondrial respiration, highlighting their potential for submental fat reduction.

Berberine Protects against High-Energy and Low-Protein Diet-Induced Hepatic Steatosis: Modulation of Gut Microbiota and Bile Acid Metabolism in Laying Hens

Berberine (BBR) is a natural alkaloid with multiple biotical effects that has potential as a treatment for fatty liver hemorrhagic syndrome (FLHS). However, the mechanism underlying the protective effect of BBR against FLHS remains unclear. The present study aimed to investigate the effect of BBR on FLHS induced by a high-energy, low-protein (HELP) diet and explore the involvement of the gut microbiota and bile acid metabolism in the protective effects. A total of 90 healthy 140-day-old Hy-line laying hens were randomly divided into three groups, including a control group (fed a basic diet), a HELP group (fed a HELP diet), and a HELP+BBR group (high-energy, high-protein diet supplemented with BBR instead of maize). Our results show that BBR supplementation alleviated liver injury and hepatic steatosis in laying hens. Moreover, BBR supplementation could significantly regulate the gut's microbial composition, increasing the abundance of Actinobacteria and Romboutsia. In addition, the BBR supplement altered the profile of bile acid. Furthermore, the gut microbiota participates in bile acid metabolism, especially taurochenodeoxycholic acid and α-muricholic acid. BBR supplementation could regulate the expression of genes and proteins related to glucose metabolism, lipid synthesis (FAS, SREBP-1c), and bile acid synthesis (FXR, CYP27a1). Collectively, our findings demonstrate that BBR might be a potential feed additive for preventing FLHS by regulating the gut microbiota and bile acid metabolism.

Supervised learning model predicts protein adsorption to carbon nanotubes

Engineered nanoparticles are advantageous for biotechnology applications including biomolecular sensing and delivery. However, testing compatibility and function of nanotechnologies in biological systems requires a heuristic approach, where unpredictable protein corona formation prevents their effective implementation. We develop a random forest classifier trained with mass spectrometry data to identify proteins that adsorb to nanoparticles based solely on the protein sequence (78% accuracy, 70% precision). We model proteins that populate the corona of a single-walled carbon nanotube (SWCNT)–based nanosensor and study the relationship between the protein’s amino acid–based properties and binding capacity. Protein features associated with increased likelihood of SWCNT binding include high content of solvent-exposed glycines and nonsecondary structure–associated amino acids. To evaluate its predictive power, we apply the classifier to identify proteins with high binding affinity to SWCNTs, with experimental validation. The developed classifier provides a step toward undertaking the otherwise intractable problem of predicting protein-nanoparticle interactions.

Supervised learning model predicts protein adsorption to carbon nanotubes

Engineered nanoparticles are advantageous for biotechnology applications including biomolecular sensing and delivery. However, testing compatibility and function of nanotechnologies in biological systems requires a heuristic approach, where unpredictable protein corona formation prevents their effective implementation. We develop a random forest classifier trained with mass spectrometry data to identify proteins that adsorb to nanoparticles based solely on the protein sequence (78% accuracy, 70% precision). We model proteins that populate the corona of a single-walled carbon nanotube (SWCNT)–based nanosensor and study the relationship between the protein’s amino acid–based properties and binding capacity. Protein features associated with increased likelihood of SWCNT binding include high content of solvent-exposed glycines and nonsecondary structure–associated amino acids. To evaluate its predictive power, we apply the classifier to identify proteins with high binding affinity to SWCNTs, with experimental validation. The developed classifier provides a step toward undertaking the otherwise intractable problem of predicting protein-nanoparticle interactions.

The Role of Fat Reducing Agents on Adipocyte Death and Adipose Tissue Inflammation

Deoxycholic Acid (DCA), which is an FDA-approved compound for the reduction of submental fat, has evolved through an unanticipated and surprising sequence of events. Initially, it was used as a solvent for Phosphatidylcholine (PDC), which was thought to promote lipolysis, but it was later proven to be the bioactive component of the formula and is currently widely used as Kybella. It has also been used off-label to treat other types of fat deposits like lipomas, HIV lipodystrophy, and excess orbital fat. Despite widespread clinical use, there has been no consensus clarifying the mechanisms of DCA and PDC alone or in combination. Furthermore, despite PDC's removal from the FDA-approved formula, some studies do suggest it plays an important role in fat reduction. To provide some clarity, we conducted a PubMed search and reviewed 41 articles using a comprehensive list of terms in three main categories, using the AND operator: 1) Phosphatidylcholines 2) Deoxycholic Acid, and 3) Lipoma. We isolated articles that studied PDC, DCA, and a PDC/DCA compound using cell biology, molecular and genetic techniques. We divided relevant articles into those that studied these components using histologic techniques and those that utilized specific cell death and lipolysis measurement techniques. Most morphologic studies indicated that PDC/DCA, DCA, and PDC, all induce some type of cell death with accompanying inflammation and fibrosis. Most morphologic studies also suggest that PDC/DCA and DCA alone are non-selective for adipocytes. Biochemical studies describing PDC and DCA alone indicate that DCA acts as a detergent and rapidly induces necrosis while PDC induces TNF-α release, apoptosis, and subsequent enzymatic lipolysis after at least 24 hours. Additional papers have suggested a synergistic effect between the two compounds. Our review integrates the findings of this growing body of literature into a proposed mechanism of fat reduction and provides direction for further studies.