Neuronal growth regulator 1 promotes adipocyte lipid trafficking via interaction with CD36

Sesamin ameliorates nonalcoholic hepatic steatosis by inhibiting CD36-mediated hepatocyte lipid accumulation in vitro and in vivo

Hepatic steatosis is a critical factor in the development of nonalcoholic steatohepatitis (NASH). Sesamin (Ses), a functional lignan isolated from Sesamum indicum, possesses hypolipidemic, liver-protective, anti-hypertensive, and anti-tumor properties. Ses has been found to improve hepatic steatosis, but the exact mechanisms through which Ses achieves this are not well understood. In this study, we observed the anti-hepatic steatosis effects of Ses in palmitate/oleate (PA/OA)-incubated primary mouse hepatocytes, AML12 hepatocytes, and HepG2 cells, as well as in high-fat, high-cholesterol diet-induced NASH mice. RNA sequencing analysis revealed that cluster of differentiation 36 (CD36), a free fatty acid (FA) transport protein, was involved in the Ses-mediated inhibition of hepatic fat accumulation. Moreover, the overexpression of CD36 significantly increased hepatic steatosis in both Ses-treated PA/OA-incubated HepG2 cells and NASH mice. Furthermore, Ses treatment suppressed insulin-induced de novo lipogenesis in HepG2 cells, which was reversed by CD36 overexpression. Mechanistically, we found that Ses ameliorated NASH by inhibiting CD36-mediated FA uptake and upregulation of lipogenic genes, including FA synthase, stearoyl-CoA desaturase 1, and sterol regulatory element-binding protein 1. The findings of our study provide novel insights into the potential therapeutic applications of Ses in the treatment of NASH.

Novel insights into perfluorinated compound-induced hepatotoxicity: Chronic dietary restriction exacerbates the effects of PFBS on hepatic lipid metabolism in mice

Perfluorobutane sulfonates (PFBS) have garnered extensive utilization because of their distinctive physicochemical properties. The liver acts as a key target organ for toxicity within the body and is vital for regulating metabolic processes, particularly lipid metabolism. However, there is currently a significant research gap regarding the influences of PFBS on hepatic lipid metabolism, especially in individuals with different dietary statuses. Here, the objective of this research was to examine the effects of PFBS on hepatic function under different dietary conditions. The results suggested that the levels of liver injury biomarkers were significantly upregulated, e.g., transaminase (GPT, GOT), while liver lipid levels were downregulated after exposure to PFBS at concentration of 50 μg/L for 42 days. Moreover, restricted diet further intensified the adverse effects of PFBS on the liver. Metabolomics analysis identified significant alterations in lipid-related metabolites in PFBS-induced hepatotoxicity, PFBS exposure induced a decrease in lysophosphatidylethanolamine and lysophosphatidylcholine. PFBS exposure caused an increase in aldosterone and prostaglandin f2alpha under restricted diet. In PFBS treatment group, histidine metabolism, beta-alanine metabolism, and arginine biosynthesis were the main pathway for PFBS toxicity. Aldosterone-regulated sodium reabsorption as a vital factor in inducing PFBS toxicity in the RD-PFBS treatment group. The analysis of 16S rRNA sequencing revealed that exposure to PFBS resulted in imbalance of gut microbial communities. PFBS exposure induced a decrease in Akkermansia and Lactobacillus, but an increase in Enterococcus. PFBS exposure caused the abundance of Lachnospiraceae_NK4A136_group was significantly elevated under restricted diet. Additionally, disruptions in the expression of genes involved in lipid production and consumption may significantly contribute to lipid imbalance in the liver. This study underscores the importance of recognizing the harmful impact of PFBS on liver function, along with the biotoxicity of contaminant influenced by dietary habits.

Optimized cell type signatures revealed from single-cell data by combining principal feature analysis, mutual information, and machine learning

Machine learning techniques are excellent to analyze expression data from single cells. These techniques impact all fields ranging from cell annotation and clustering to signature identification. The presented framework evaluates gene selection sets how far they optimally separate defined phenotypes or cell groups. This innovation overcomes the present limitation to objectively and correctly identify a small gene set of high information content regarding separating phenotypes for which corresponding code scripts are provided. The small but meaningful subset of the original genes (or feature space) facilitates human interpretability of the differences of the phenotypes including those found by machine learning results and may even turn correlations between genes and phenotypes into a causal explanation. For the feature selection task, the principal feature analysis is utilized which reduces redundant information while selecting genes that carry the information for separating the phenotypes. In this context, the presented framework shows explainability of unsupervised learning as it reveals cell-type specific signatures. Apart from a Seurat preprocessing tool and the PFA script, the pipeline uses mutual information to balance accuracy and size of the gene set if desired. A validation part to evaluate the gene selection for their information content regarding the separation of the phenotypes is provided as well, binary and multiclass classification of 3 or 4 groups are studied. Results from different single-cell data are presented. In each, only about ten out of more than 30000 genes are identified as carrying the relevant information. The code is provided in a GitHub repository at https://github.com/AC-PHD/Seurat_PFA_pipeline.

Neuronal growth regulator 1 may modulate interleukin-6 signaling in adipocytes

Interleukin-6 (IL-6) is a pleiotropic cytokine that plays both anti- and pro-inflammatory roles. Due to the restricted expression of membrane IL-6 receptor (IL-6R), most pro-inflammatory functions of IL-6 are attributed to its association with soluble IL-6R (sIL-6R). Neuronal growth regulator 1 (NEGR1) is a brain-enriched membrane protein that has recently been recognized as a risk factor for many human diseases including obesity, depression, and autism. In the present study, we report that the expression levels of IL-6 and IL-6R, as well as the phosphorylation of signal transducer and activator of transcription (STAT) 3, were significantly elevated in white adipose tissues of Negr1 knockout mice. Elevated levels of circulating IL-6 and sIL-6R have also been observed in Negr1 ^-/- mice. Furthermore, NEGR1 interacted with IL-6R, which was supported by subcellular fractionation and an in situ proximity ligation assay. Importantly, NEGR1 expression attenuated the phosphorylation of STAT3 by sIL-6R, suggesting that NEGR1 negatively regulates IL-6 trans-signaling. Taken together, we propose that NEGR1 may play a regulatory role in IL-6 signaling by interacting with IL-6R, which may contribute to a molecular link underlying obesity, inflammation, and the depression cycle.

Six genetically linked mutations in the CD36 gene significantly delay the onset of Alzheimer's disease

The risk of Alzheimer’s disease (AD) has a strong genetic component, also in the case of late-onset AD (LOAD). Attempts to sequence whole genome in large populations of subjects have identified only a few mutations common to most of the patients with AD. Targeting smaller well-characterized groups of subjects where specific genetic variations in selected genes could be related to precisely defined psychological traits typical of dementia is needed to better understand the heritability of AD. More than one thousand participants, categorized according to cognitive deficits, were assessed using 14 psychometric tests evaluating performance in five cognitive domains (attention/working memory, memory, language, executive functions, visuospatial functions). CD36 was selected as a gene previously shown to be implicated in the etiology of AD. A total of 174 polymorphisms were tested for associations with cognition-related traits and other AD-relevant data using the next generation sequencing. Several associations between single nucleotide polymorphisms (SNP’s) and the cognitive deficits have been found (rs12667404 with language performance, rs3211827 and rs41272372 with executive functions, rs137984792 with visuospatial performance). The most prominent association was found between a group of genotypes in six genetically linked and the age at which the AD patients presented with, or developed, a full-blown dementia. The identified alleles appear to be associated with a delay in the onset of LOAD. In silico studies suggested that the SNP’s alter the expression of CD36 thus potentially affecting CD36-related neuroinflammation and other molecular and cellular mechanisms known to be involved in the neuronal loss leading to AD. The main outcome of the study is an identification of a set of six new mutations apparently conferring a distinct protection against AD and delaying the onset by about 8 years. Additional mutations in CD36 associated with certain traits characteristic of the cognitive decline in AD have also been found.