Salusin­α alleviates lipid metabolism disorders via regulation of the downstream lipogenesis genes through the LKB1/AMPK pathway.

Lipid metabolism disorders are a major cause of several chronic metabolic diseases which seriously affect public health. Salusin­α, a vasoactive peptide, has been shown to attenuate lipid metabolism disorders, although its mechanism of action has not been reported. To investigate the effects and potential mechanisms of Salusin­α on lipid metabolism, Salusin­α was overexpressed or knocked down using lentiviral vectors. Hepatocyte steatosis was induced by free fatty acid (FFA) after lentiviral transfection into HepG2 cells. The degree of lipid accumulation was assessed using Oil Red O staining and by measuring several biochemical indices. Subsequently, bioinformatics was used to analyze the signaling pathways that may have been involved in lipid metabolism disorders. Finally, semi­quantitative PCR and western blotting were used to verify the involvement of the liver kinase B1 (LKB1)/AMPK pathway. Compound C, an inhibitor of AMPK, was used to confirm this mechanism's involvement further. The results showed that Salusin­α significantly attenuated lipid accumulation, inflammation and oxidative stress. In addition, Salusin­α increased the levels of LKB1 and AMPK, which inhibited the expression of sterol regulatory element binding protein­1c, fatty acid synthase and acetyl­CoA carboxylase. The addition of Compound C abrogated the Salusin­α­mediated regulation of AMPK on downstream signaling molecules. In summary, overexpression of Salusin­α activated the LKB1/AMPK pathway, which in turn inhibited lipid accumulation in HepG2 cells. This provides insights into the potential mechanism underlying the mechanism by which Salusin­α ameliorates lipid metabolism disorders while identifying a potential therapeutic target.

Wnt/Wingless signaling promotes lipid mobilization through signal-induced transcriptional repression.

The Wnt/Wingless signaling pathway plays critical roles in metazoan development and energy metabolism, but its role in regulating lipid homeostasis remains not fully understood. Here, we report that the activation of canonical Wnt/Wg signaling promotes lipolysis while concurrently inhibiting lipogenesis and fatty acid ß-oxidation in both larval and adult adipocytes, as well as cultured S2R+ cells, in Drosophila. Using RNA-sequencing and CUT&RUN (Cleavage Under Targets & Release Using Nuclease) assays, we identified a set of Wnt target genes responsible for intracellular lipid homeostasis. Notably, active Wnt signaling directly represses the transcription of these genes, resulting in decreased de novo lipogenesis and fatty acid ß-oxidation, but increased lipolysis. These changes lead to elevated free fatty acids and reduced triglyceride (TG) accumulation in adipocytes with active Wnt signaling. Conversely, downregulation of Wnt signaling in the fat body promotes TG accumulation in both larval and adult adipocytes. The attenuation of Wnt signaling also increases the expression of specific lipid metabolism-related genes in larval adipocytes, wing discs, and adult intestines. Taken together, these findings suggest that Wnt signaling-induced transcriptional repression plays an important role in regulating lipid homeostasis by enhancing lipolysis while simultaneously suppressing lipogenesis and fatty acid ß-oxidation.

Deciphering the lipid-cancer nexus: comprehensive Mendelian randomization analysis of the associations between lipid profiles and digestive system cancer susceptibility.

BACKGROUND: Digestive system cancers represent a significant global health challenge and are attributed to a combination of demographic and lifestyle changes. Lipidomics has emerged as a pivotal area in cancer research, suggesting that alterations in lipid metabolism are closely linked to cancer development. However, the causal relationship between specific lipid profiles and digestive system cancer risk remains unclear. METHODS: Using a two-sample Mendelian randomization (MR) approach, we elucidated the causal relationships between lipidomic profiles and the risk of five types of digestive system cancer: stomach, liver, esophageal, pancreatic, and colorectal cancers. The aim of this study was to investigate the effect impact of developing lipid profiles on the risk of digestive system cancers utilizing data from public databases such as the GWAS Catalog and the UK Biobank. The inverse‒variance weighted (IVW) method and other strict MR methods were used to evaluate the potential causal links. In addition, we performed sensitivity analyses and reverse MR analyses to ensure the robustness of the results. RESULTS: Significant causal relationships were identified between certain lipidomic traits and the risk of developing digestive system cancers. Elevated sphingomyelin (d40:1) levels were associated with a reduced risk of developing gastric cancer (odds ratio (OR) = 0.68, P < 0.001), while elevated levels of phosphatidylcholine (16:1_20:4) increased the risk of developing esophageal cancer (OR = 1.31, P = 0.02). Conversely, phosphatidylcholine (18:2_0:0) had a protective effect against colorectal cancer (OR = 0.86, P = 0.036). The bidirectional analysis did not suggest reverse causality between cancer risk and lipid levels. Strict MR methods demonstrated the robustness of the above causal relationships. CONCLUSION: Our findings underscore the significant causal relationships between specific lipidomic traits and the risk of developing various digestive system cancers, highlighting the potential of lipid profiles in informing cancer prevention and treatment strategies. These results reinforce the value of MR in unraveling complex lipid-cancer interactions, offering new avenues for research and clinical application.

Unveiling the role of AGT in lipid metabolism and regulated cell death in colon cancer.

BACKGROUND: Lipid metabolism and regulated cell death (RCD) play a role in the remodeling of tumor immune microenvironment and regulation of cancer progression. Since the underlying immune mechanisms of colon cancer remain elusive, this study aims to identify potential therapeutic target genes. METHODS: Differential genes related to lipid metabolism and RCD in COAD patients were identified using R language and online tools. Based on the expression of genes, two groups were classified using consensus clustering. CIBERSORT and ssGSEA were used to detect immune infiltration in both groups. Prognostic signature genes for colon cancer were screened using machine learning algorithms. KEGG, GO and GSEA for gene pathway enrichment. In addition, interacting genes in the immune module were obtained using a weighted gene co-expression network (WGCNA). Finally, expression and mutation of key in colon cancer genes were detected using TIMER, HPR, cBioPortal website and qPCR. RESULTS: The consensus clustering analysis revealed that 231 relevant differential genes were highly associated with immune infiltration. A series of machine learning and website analyses identified AGT as a hub gene linked to lipid metabolism and regulated cell death, which is overexpressed in colon cancer. CONCLUSION: AGT, as a signature gene of lipid metabolism and regulated cell death, plays a critical role in the development of COAD and is associated with tumor immune infiltration.

Identification of lipid metabolism-related gene signature in the bone marrow microenvironment of multiple myelomas through deep analysis of transcriptomic data.

Dysregulated lipid metabolism in the bone marrow microenvironment (BMM) plays a vital role in multiple myeloma (MM) development, progression, and drug resistance. However, the exact mechanism by which lipid metabolism impacts the BMM, promotes tumorigenesis, and triggers drug resistance remains to be fully elucidated.By analyzing the bulk sequencing and single-cell sequencing data of MM patients, we identified lipid metabolism-related genes differential expression significantly associated with MM prognosis, referred to as LMRPgenes. Using a cohort of ten machine learning algorithms and 117 combinations, LMRPgenes predictive models were constructed. Further exploration of the effects of the model risk score (RS) on the survival status, immune status of patients with BMM, and response to immunotherapy was conducted. The study also facilitated the identification of personalized therapeutic strategies targeting specified risk categories within patient cohorts.Analysis of the scRNA-seq data revealed increased lipid metabolism-related gene enrichment scores (LMESs) in erythroblasts and progenitor, malignant, and Tprolif cells but decreased LMESs in lymphocytes. LMESs were also strongly correlated with most of the 50 hallmark pathways within these cell populations. An elevated malignant cell ratio and reduced lymphocytes were observed in the high LMES group. Moreover, the LMRPgenes predictive model, consisting of 14 genes, showed great predictive power. The risk score emerged as an independent indicator of poor outcomes. Inverse relationships between the RS and immune status were noted, and a high RS was associated with impaired immunotherapy responses. Drug sensitivity assays indicated the effectiveness of bortezomib, buparlisib, dinaciclib, staurosporine, rapamycin, and MST-312 in the high-RS group, suggesting their potential for treating patients with high-RS values and poor response to immunotherapy. Ultimately, upon verification via qRT-PCR, we observed a significant upregulation of ACBD6 in NDMM group compared to the control group.Our research enhances the knowledge base regarding the association between lipid metabolism-related genes (LMRGs) and the BMM in MM patients, offering substantive insights into the mechanistic effects of the BMM mediated by LMRGs.

CPT1A loss disrupts BCAA metabolism to confer therapeutic vulnerability in TP53-mutated liver cancer.

Driver genomic mutations in tumors define specific molecular subtypes that display distinct malignancy competence, therapeutic resistance and clinical outcome. Although TP53 mutation has been identified as the most common mutation in hepatocellular carcinoma (HCC), current understanding on the biological traits and therapeutic strategies of this subtype has been largely unknown. Here, we reveal that fatty acid ß oxidation (FAO) is remarkable repressed in TP53 mutant HCC and which links to poor prognosis in HCC patients. We further demonstrate that carnitine palmitoyltransferase 1 (CPT1A), the rate-limiting enzyme of FAO, is universally downregulated in liver tumor tissues, and which correlates with poor prognosis in HCC and promotes HCC progression in the de novo liver tumor and xenograft tumor models. Mechanically, hepatic Cpt1a loss disrupts lipid metabolism and acetyl-CoA production. Such reduction in acetyl-CoA reduced histone acetylation and epigenetically reprograms branched-chain amino acids (BCAA) catabolism, and leads to the accumulation of cellular BCAAs and hyperactivation of mTOR signaling. Importantly, we reveal that genetic ablation of CPT1A renders TP53 mutant liver cancer mTOR-addicted and sensitivity to mTOR inhibitor AZD-8055 treatment. Consistently, Cpt1a loss in HCC directs tumor cell therapeutic response to AZD-8055. CONCLUSION: Our results show genetic evidence for CPT1A as a metabolic tumor suppressor in HCC and provide a therapeutic approach for TP53 mutant HCC patients.

Deficiency of SDHC promotes metastasis by reprogramming fatty acid metabolism in colorectal cancer.

BACKGROUND: Several studies have demonstrated a strong correlation between impaired Succinate dehydrogenase (SDH) function and the advancement of tumors. As a subunit of SDH, succinate dehydrogenase complex subunit C (SDHC) has been revealed to play tumor suppressive roles in several cancers, while its specific role in colorectal cancer (CRC) still needs further investigation. METHODS: Online database were utilized to investigate the expression of SDHC in colorectal cancer and to assess its correlation with patient prognosis. Cell metastasis was assessed using transwell and wound healing assays, while tumor metastasis was studied in a nude mice model in vivo. Drug screening and RNA sequencing were carried out to reveal the tumor suppressor mechanism of SDHC. Triglycerides, neutral lipids and fatty acid oxidation were measured using the Triglyceride Assay Kit, BODIPY 493/503 and Colorimetric Fatty Acid Oxidation Rate Assay Kit, respectively. The expression levels of enzymes involved in fatty acid metabolism and the PI3K/AKT signaling pathway were determined by quantitative real-time PCR and western blot. RESULTS: Downregulation of SDHC was found to be closely associated with a poor prognosis in CRC. SDHC knockdown promoted CRC metastasis both in vitro and in vivo. Through drug screening and Gene set enrichment analysis, it was discovered that SDHC downregulation was positively associated with the fatty acid metabolism pathways significantly. The effects of SDHC silencing on metastasis were reversed when fatty acid synthesis was blocked. Subsequent experiments revealed that SDHC silencing activated the PI3K/AKT signaling axis, leading to lipid accumulation by upregulating the expression of aldehyde dehydrogenase 3 family member A2 (ALDH3A2) and reduction of fatty acid oxidation rate by suppressing the expression of acyl-coenzyme A oxidase 1 (ACOX1) and carnitine palmitoyltransferase 1A (CPT1A). CONCLUSIONS: SDHC deficiency could potentially enhance CRC metastasis by modulating the PI3K/AKT pathways and reprogramming lipid metabolism.

Machine learning survival prediction using tumor lipid metabolism genes for osteosarcoma.

Osteosarcoma is a primary malignant tumor that commonly affects children and adolescents, with a poor prognosis. The existence of tumor heterogeneity leads to different molecular subtypes and survival outcomes. Recently, lipid metabolism has been identified as a critical characteristic of cancer. Therefore, our study aims to identify osteosarcoma's lipid metabolism molecular subtype and develop a signature for survival outcome prediction. Four multicenter cohorts-TARGET-OS, GSE21257, GSE39058, and GSE16091-were amalgamated into a unified Meta-Cohort. Through consensus clustering, novel molecular subtypes within Meta-Cohort patients were delineated. Subsequent feature selection processes, encompassing analyses of differentially expressed genes between subtypes, univariate Cox analysis, and StepAIC, were employed to pinpoint biomarkers related to lipid metabolism in TARGET-OS. We selected the most effective algorithm for constructing a Lipid Metabolism-Related Signature (LMRS) by utilizing four machine-learning algorithms reconfigured into ten unique combinations. This selection was based on achieving the highest concordance index (C-index) in the test cohort of GSE21257, GSE39058, and GSE16091. We identified two distinct lipid metabolism molecular subtypes in osteosarcoma patients, C1 and C2, with significantly different survival rates. C1 is characterized by increased cholesterol, fatty acid synthesis, and ketone metabolism. In contrast, C2 focuses on steroid hormone biosynthesis, arachidonic acid, and glycerolipid and linoleic acid metabolism. Feature selection in the TARGET-OS identified 12 lipid metabolism genes, leading to a model predicting osteosarcoma patient survival. The LMRS, based on the 12 identified genes, consistently accurately predicted prognosis across TARGET-OS, testing cohorts, and Meta-Cohort. Incorporating 12 published signatures, LMRS showed robust and significantly superior predictive capability. Our results offer a promising tool to enhance the clinical management of osteosarcoma, potentially leading to improved clinical outcomes.

CD63 + tumor-associated macrophages drive the progression of hepatocellular carcinoma through the induction of epithelial-mesenchymal transition and lipid reprogramming.

BACKGROUND: Tumor-associated macrophages (TAMs) constitute a substantial part of human hepatocellular carcinoma (HCC). The present study was devised to explore TAM diversity and their roles in HCC progression. METHODS: Through the integration of multiple 10 × single-cell transcriptomic data derived from HCC samples and the use of consensus nonnegative matrix factorization (an unsupervised clustering algorithm), TAM molecular subtypes and expression programs were evaluated in detail. The roles played by these TAM subtypes in HCC were further probed through pseudotime, enrichment, and intercellular communication analyses. Lastly, vitro experiments were performed to validate the relationship between CD63, which is an inflammatory TAM expression program marker, and tumor cell lines. RESULTS: We found that the inflammatory expression program in TAMs had a more obvious interaction with HCC cells, and CD63, as a marker gene of the inflammatory expression program, was associated with poor prognosis of HCC patients. Both bulk RNA-seq and vitro experiments confirmed that higher TAM CD63 expression was associated with the growth of HCC cells as well as their epithelial-mesenchymal transition, metastasis, invasion, and the reprogramming of lipid metabolism. CONCLUSIONS: These analyses revealed that the TAM inflammatory expression program in HCC is closely associated with malignant tumor cells, with the hub gene CD63 thus representing an ideal target for therapeutic intervention in this cancer type.

Profiling of m6A methylation in porcine intramuscular adipocytes and unravelling PHKG1 represses porcine intramuscular lipid deposition in an m6A-dependent manner.

Intramuscular fat (IMF) content is mainly determined by intramuscular preadipocyte adipogenesis. Epigenetic modifications are known to have a regulatory effect on IMF. As N6-methyladenosine (m6A) is the most abundant epigenetic modification in eukaryotic RNAs. In the present study, we used m6A methylation and RNA sequencing (seq) to identify the m6A-modified RNAs associated with the adipogenic differentiation of intramuscular preadipocytes. Among them, the expression and m6A level of phosphorylase kinase subunit G1 (PHKG1) were found to be significantly changed during adipogenesis. Further studies revealed that knockdown of the methylase METTL3 decreased the m6A methylation of PHKG1 and led to a reduction in PHKG1. Moreover, knockdown of PHKG1 promoted adipogenic differentiation by upregulating the expression of adipogenic genes. In addition, we found that the IMF content in the longissimus thoracis (LT) of Bamei (BM) pigs was greater than that in Large White (LW) pigs, whereas the m6A and PHKG1 expression levels were lower in BM pigs. These findings indicate that the m6A level and expression of PHKG1 were significantly correlated with IMF content and meat quality. In conclusion, this study sheds light on the mechanism by which m6A modification regulates IMF deposition.

Unravelling effects of phytochemicals from buckwheat on cholesterol metabolism and lipid accumulation in HepG2 cells and its validation through gene expression analysis.

BACKGROUND: The objective of this research was to elucidate the hypocholesterolemic effects of a bioactive compound extracted from buckwheat, and to delineate its influence on the regulatory mechanisms of cholesterol metabolism. The compound under investigation was identified as quercetin. MATERIAL AND RESULTS: In vitro experiments conducted on HepG2 cells treated with quercetin revealed a significant reduction in intracellular cholesterol accumulation. This phenomenon was rigorously quantified by assessing the transcriptional activity of key genes involved in the biosynthesis and metabolism of cholesterol. A statistically significant reduction in the expression of HMG-CoA reductase (HMGCR) was observed, indicating a decrease in endogenous cholesterol synthesis. Conversely, an upregulation in the expression of cholesterol 7 alpha-hydroxylase (CYP7A1) was also observed, suggesting an enhanced catabolism of cholesterol to bile acids. Furthermore, the study explored the combinatory effects of quercetin and simvastatin, a clinically utilized statin, revealing a synergistic action in modulating cholesterol levels at various dosages. CONCLUSIONS: The findings from this research provide a comprehensive insight into the mechanistic pathways through which quercetin, a phytochemical derived from buckwheat, exerts its hypocholesterolemic effects. Additionally, the observed synergistic interaction between quercetin and simvastatin opens up new avenues for the development of combined therapeutic strategies to manage hyperlipidemia.

Identification of lipid-modifying drug targets for autoimmune diseases: insights from drug target mendelian randomization.

BACKGROUNDS: A growing body of evidence has highlighted the interactions of lipids metabolism and immune regulation. Nevertheless, there is still a lack of evidence regarding the causality between lipids and autoimmune diseases (ADs), as well as their possibility as drug targets for ADs. OBJECTIVES: This study was conducted to comprehensively understand the casual associations between lipid traits and ADs, and evaluate the therapeutic possibility of lipid-lowering drug targets on ADs. METHODS: Genetic variants for lipid traits and variants encoding targets of various lipid-lowering drugs were derived from Global Lipid Genetics Consortium (GLGC) and verified in Drug Bank. Summary data of ADs were obtained from MRC Integrative Epidemiology Unit (MER-IEU) database and FinnGen consortium, respectively. The causal inferences between lipid traits/genetic agents of lipid-lowering targets and ADs were evaluated by Mendelian randomization (MR), summary data-based MR (SMR), and multivariable MR (MVMR) analyses. Enrichment analysis and protein interaction network were employed to reveal the functional characteristics and biological relevance of potential therapeutic lipid-lowering targets. RESULTS: There was no evidence of causal effects regarding 5 lipid traits and 9 lipid-lowering drug targets on ADs. Genetically proxied 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) inhibition was associated with a reduced risk of rheumatoid arthritis (RA) in both discovery (OR [odds ratio] = 0.45, 95%CI: 0.32, 0.63, P = 6.79 × 10- 06) and replicate datasets (OR = 0.37, 95%CI: 0.23, 0.61, P = 7.81 × 10- 05). SMR analyses supported that genetically proxied HMGCR inhibition had causal effects on RA in whole blood (OR = 0.48, 95%CI: 0.29, 0.82, P = 6.86 × 10- 03) and skeletal muscle sites (OR = 0.75, 95%CI: 0.56, 0.99, P = 4.48 × 10- 02). After controlling for blood pressure, body mass index (BMI), smoking and drinking alchohol, HMGCR suppression showed a direct causal effect on a lower risk of RA (OR = 0.33, 95%CI: 0.40, 0.96, P = 0.042). CONCLUSIONS: Our study reveals causal links of genetically proxied HMGCR inhibition (lipid-lowering drug targets) and HMGCR expression inhibition with a decreased risk of RA, suggesting that HMGCR may serve as candidate drug targets for the treatment and prevention of RA.

Phospholipid isotope tracing suggests ß-catenin-driven suppression of phosphatidylcholine metabolism in hepatocellular carcinoma.

Activating mutations in the CTNNB1 gene encoding ß-catenin are among the most frequently observed oncogenic alterations in hepatocellular carcinoma (HCC). Profound alterations in lipid metabolism, including increases in fatty acid oxidation and transformation of the phospholipidome, occur in HCC with CTNNB1 mutations, but it is unclear what mechanisms give rise to these changes. We employed untargeted lipidomics and targeted isotope tracing to measure phospholipid synthesis activity in an inducible human liver cell line expressing mutant ß-catenin, as well as in transgenic zebrafish with activated ß-catenin-driven HCC. In both models, activated ß-catenin expression was associated with large changes in the lipidome including conserved increases in acylcarnitines and ceramides and decreases in triglycerides. Lipid isotope tracing analysis in human cells revealed a reduction in phosphatidylcholine (PC) production rates as assayed by choline incorporation. We developed lipid isotope tracing analysis for zebrafish tumors and observed reductions in phosphatidylcholine synthesis by both the CDP-choline and PEMT pathways. The observed changes in the ß-catenin-driven HCC phospholipidome suggest that zebrafish can recapitulate conserved features of HCC lipid metabolism and may serve as a model for identifying future HCC-specific lipid metabolic targets.

Lipid traits and lipid-lowering drug target genes and risk of melanoma: a mendelian randomization study.

Our study aimed to investigate the role of lipids in melanoma risk and the effect of lipid-lowering drug targets on melanoma. Using Mendelian Randomization analysis, we examined the genetic agents of nine lipid-lowering drugs and their association with melanoma risk. We found that genetically proxied inhibition of HMGCR, ABCG5/ABCG8, and ANGPTL3 was associated with a reduced risk of melanoma. On the other hand, inhibition of LPL and Apo-B100 was significantly associated with an increased risk of melanoma. Sensitivity analyses did not reveal any statistical evidence of bias from pleiotropy or genetic confounding. We did not find a robust association between lipid traits NPC1L1, PCSK9, APOC3 inhibition, and melanoma risk. These findings were validated using two independent lipid datasets. Our analysis also revealed that HMGCR, ANGPTL3, and ABCG5/ABCG8 inhibitors reduced melanoma risk independent of their effects on lipids. This suggests that these targets may have potential for melanoma prevention or treatment. In conclusion, our study provides evidence for a causal role of lipids in melanoma risk and highlights specific lipid-lowering drug targets that may be effective in reducing the risk of melanoma. These findings contribute to the understanding of the underlying mechanisms of melanoma development and provide potential avenues for further research and therapeutic interventions.

A novel signature incorporating genes related to lipid metabolism and immune for prognostic and functional prediction of breast cancer.

PURPOSE: Breast cancer prognosis and functioning have not been thoroughly examined in relation to immunological and lipid metabolism. However, there is a lack of prognostic and functional analyses of the relationship between lipid metabolism and immunity in breast cancer. METHODS: DEGs in breast cancer were obtained from UCSC database, and lipid metabolism and immune-related genes were obtained from GSEA and Immune databases. A predictive signature was constructed using univariate Cox and LASSO regression on lipid metabolism and immune-related DEGs. The signature's prognostic significance was assessed using Kaplan-Meier, time-dependent ROC, and risk factor survival scores. Survival prognosis, therapeutic relevance, and functional enrichment were used to mine model gene biology. We selected IL18, which has never been reported in breast cancer before, in the signature to learn more about its function, potential to predict outcome, and immune system role. RT-PCR was performed to verify the true expression level of IL18. RESULTS: A total of 136 DEGs associated with breast cancer responses to both immunity and lipid metabolism. Nine key genes (CALR, CCL5, CEPT, FTT3, CXCL13, FLT3, IL12B, IL18, and IL24, p < 1.6e-2) of breast cancer were identified, and a prognostic was successfully constructed with a good predictive ability. IL18 in the model also had good clinical prognostic guidance value and immune regulation and therapeutic potential. Furthermore, the expression of IL18 was higher than that in paracancerous tissue. CONCLUSIONS: A unique predictive signature model could effectively predict the prognosis of breast cancer, which can not only achieve survival prediction, but also screen out key genes with important functional mechanisms to guide clinical drug experiments.

Identification and validation of lipid metabolism-related key genes as novel biomarkers in acute myocardial infarction and pan-cancer analysis.

BACKGROUND: Acute myocardial infarction (AMI) is associated with high morbidity and mortality, and is associated with abnormal lipid metabolism. We identified lipid metabolism related genes as biomarkers of AMI, and explored their mechanisms of action. METHODS: Microarray datasets were downloaded from the GEO database and lipid metabolism related genes were obtained from Molecular Signatures Database. WGCNA was performed to identify key genes. We evaluated differential expression and performed ROC and ELISA analyses. We also explored the mechanism of AMI mediated by key genes using gene enrichment analysis. Finally, immune infiltration and pan-cancer analyses were performed for the identified key genes. RESULTS: TRL2, S100A9, and HCK were identified as key genes related to lipid metabolism in AMI. Internal and external validation (including ELISA) showed that these were good biomarkers of AMI. In addition, the results of gene enrichment analysis showed that the key genes were enriched in inflammatory response, immune system process, and tumor-related pathways. Finally, the results of immune infiltration showed that key genes were concentrated in neutrophils and macrophages, and pan-cancer analysis showed that the key genes were highly expressed in most tumors and were associated with poor prognosis. CONCLUSIONS: TLR2, S100A9, and HCK were identified as lipid metabolism related novel diagnostic biomarkers of AMI. In addition, AMI and tumors may be related through the inflammatory immune response.

Impact of miR-222-3p-mediated downregulation of arylacetamide deacetylase on drug hydrolysis and lipid accumulation.

Arylacetamide deacetylase (AADAC) is involved in drug hydrolysis and lipid metabolism. In 23 human liver samples, no significant correlation was observed between AADAC mRNA (19.7-fold variation) and protein levels (137.6-fold variation), suggesting a significant contribution of post-transcriptional regulation to AADAC expression. The present study investigated whether AADAC is regulated by microRNA in the human liver and elucidate its biological significance. Computational analysis predicted two potential miR-222-3p recognition elements in the 3'-untranslated region (UTR) of AADAC. Luciferase assay revealed that the miR-222-3p recognition element was functional in downregulating AADAC expression. In HEK293 cells transfected with an AADAC expression plasmid containing 3'-UTR, miR-222-3p overexpression decreased AADAC protein level and activity, whereas miR-222-3p inhibition increased them. Similar results were observed in human hepatoma-derived Huh-1 cells endogenously expressing AADAC and HepaSH cells that are hepatocytes from chimeric mice with humanized livers. In individual human liver samples, AADAC protein levels inversely correlated with miR-222-3p levels. Overexpression of miR-222-3p resulted in increased lipid accumulation in Huh-1 cells, which was reversed by AADAC overexpression. In contrast, miR-222-3p inhibition decreased lipid accumulation, which was reversed by AADAC knockdown. In conclusion, we found that hepatic AADAC was downregulated by miR-222-3p, resulting in decreased drug hydrolysis and increased lipid accumulation.

De novo transcriptome and lipidome analysis of Desmodesmus abundans under model flue gas reveals adaptive changes after ten years of acclimation to high CO2.

Microalgae's ability to mitigate flue gas is an attractive technology that can valorize gas components through biomass conversion. However, tolerance and growth must be ideal; therefore, acclimation strategies are suggested. Here, we compared the transcriptome and lipidome of Desmodesmus abundans strains acclimated to high CO2 (HCA) and low CO2 (LCA) under continuous supply of model flue gas (MFG) and incomplete culture medium (BG11-N-S). Initial growth and nitrogen consumption from MFG were superior in strain HCA, reaching maximum productivity a day before strain LCA. However, similar productivities were attained at the end of the run, probably because maximum photobioreactor capacity was reached. RNA-seq analysis during exponential growth resulted in 16,435 up-regulated and 4,219 down-regulated contigs in strain HCA compared to LCA. Most differentially expressed genes (DEGs) were related to nucleotides, amino acids, C fixation, central carbon metabolism, and proton pumps. In all pathways, a higher number of up-regulated contigs with a greater magnitude of change were observed in strain HCA. Also, cellular component GO terms of chloroplast and photosystems, N transporters, and secondary metabolic pathways of interest, such as starch and triacylglycerols (TG), exhibited this pattern. RT-qPCR confirmed N transporters expression. Lipidome analysis showed increased glycerophospholipids in strain HCA, while LCA exhibited glycerolipids. Cell structure and biomass composition also revealed strains differences. HCA possessed a thicker cell wall and presented a higher content of pigments, while LCA accumulated starch and lipids, validating transcriptome and lipidome data. Overall, results showed significant differences between strains, where characteristic features of adaptation and tolerance to high CO2 might be related to the capacity to maintain a higher flux of internal C, regulate intracellular acidification, active N transporters, and synthesis of essential macromolecules for photosynthetic growth.

Roles of glutamic pyruvate transaminase 2 in reprogramming of airway epithelial lipidomic and metabolomic profiles after smoking.

Metabolic abnormalities represent one of the pathological features of chronic obstructive pulmonary disease (COPD). Glutamic pyruvate transaminase 2 (GPT2) is involved in glutamate metabolism and lipid synthesis pathways, whilst the exact roles of GPT2 in the occurrence and development of COPD remains uncertain. This study aims at investigating how GPT2 and the associated genes modulate smoking-induced airway epithelial metabolism and damage by reprogramming lipid synthesis. The circulating or human airway epithelial metabolomic and lipidomic profiles of COPD patients or cell-lines explored with smoking were assessed to elucidate the pivotal roles of GPT2 in reprogramming processes. We found that GPT2 regulate the reprogramming of lipid metabolisms caused by smoking, especially phosphatidylcholine (PC) and triacylglycerol (TAG), along with changes in the expression of lipid metabolism-associated genes. GPT2 modulated cell sensitivities and survival in response to smoking by enhancing mitochondrial functions and maintaining lipid and energy homeostasis. Our findings provide evidence for the involvement of GPT2 in the reprogramming of airway epithelial lipids following smoking, as well as the molecular mechanisms underlying GPT2-mediated regulation, which may offer an alternative of therapeutic strategies for chronic lung diseases.