Integrated gut microbiome and lipidomic analyses in animal models of Wilson disease reveal a role of intestine ATP7B in copper-related metabolic dysregulation (Part 2)
Project description:Acute leukemias (AL) are aggressive neoplasms with high mortality rates. Metabolomics and oxidative status have emerged as important tools to identify new biomarkers with clinical utility. To identify the metabolic differences between healthy individuals (HI) and patients with AL, a multiplatform untargeted metabolomic and lipidomic approach was conducted using liquid and gas chromatography coupled with quadrupole-time-of-flight mass spectrometry (LC-QTOF-MS or GC-QTOF-MS). Additionally, the total antioxidant capacity (TAC) was measured. A total of 20 peripheral blood plasma samples were obtained from patients with AL and 18 samples from HI. Our analysis revealed 135 differentially altered metabolites in the patients belonging to 12 chemical classes; likewise, the metabolic pathways of glycerolipids and sphingolipids were the most affected in the patients. A decrease in the TAC of the patients with respect to the HI was evident. This study conducted with a cohort of Colombian patients is consistent with observations from other research studies that suggest dysregulation of lipid compounds. Furthermore, metabolic differences between patients and HI appear to be independent of lifestyle, race, or geographic location, providing valuable information for future advancements in understanding the disease and developing more global therapies.
Project description:Sesame is one of the most important oilseed crops and attracts significant attention because of its huge nutritional capacity. However, the molecular mechanisms underlying oil accumulation in sesame remains poorly understood. In this study, lipidomic and transcriptomic analyses in different stages of sesame seed (Luzhi No.1, seed oil content 56%) development were performed to gain insight into the regulatory mechanisms that govern differences in lipid composition, content, biosynthesis, and transport. In total, 481 lipids, including fatty acids (FAs, 38 species), triacylglycerol (TAG, 127 species), ceramide (33 species), phosphatidic acid (20 species), and diacylglycerol (17 species), were detected in developing sesame seed using gas and liquid chromatography-mass spectrometry. Most FAs and other lipids accumulated 21-33 days after flowering. RNA-sequence profiling in developing seed highlighted the enhanced expression of genes involved in the biosynthesis and transport of FAs, TAGs, and membrane lipids, which was similar to that seen during lipid accumulation. Through the differential expression analysis of genes involved in lipid biosynthesis and metabolism during seed development, several candidate genes were found to affect the oil content and FA composition of sesame seed, including ACCase, FAD2, DGAT, G3PDH, PEPCase, WRI1 and WRI1-like genes. Our study reveals the patterns of lipid accumulation and biosynthesis-related gene expression and lays an important foundation for the further exploration of sesame seed lipid biosynthesis and accumulation.
Project description:Mouse models have an essential role in cancer research, yet little is known about how various models resemble human cancer at a genomic level. Here, we complete whole genome sequencing and transcriptome profiling of two widely used mouse models of breast cancer, MMTV-Neu and MMTV-PyMT. Through integrative in vitro and in vivo studies, we identify copy number alterations in key extracellular matrix proteins including collagen 1 type 1 alpha 1 (COL1A1) and chondroadherin (CHAD) that drive metastasis in these mouse models. In addition to copy number alterations, we observe a propensity of the tumors to modulate tyrosine kinase-mediated signaling through mutation of phosphatases such as PTPRH in the MMTV-PyMT mouse model. Mutation in PTPRH leads to increased phospho-EGFR levels and decreased latency. These findings underscore the importance of understanding the complete genomic landscape of a mouse model and illustrate the utility this has in understanding human cancers.
Project description:Peripheral neuropathy (PN) is a complication of prediabetes and type 2 diabetes (T2D). Increasing evidence suggests that factors besides hyperglycaemia contribute to PN development, including dyslipidaemia. The objective of this study was to determine differential lipid classes and altered gene expression profiles in prediabetes and T2D mouse models in order to identify the dysregulated pathways in PN. Here, we used high-fat diet (HFD)-induced prediabetes and HFD/streptozotocin (STZ)-induced T2D mouse models that develop PN. These models were compared to HFD and HFD-STZ mice that were subjected to dietary reversal. Both untargeted and targeted lipidomic profiling, and gene expression profiling were performed on sciatic nerves. Lipidomic and transcriptomic profiles were then integrated using complex correlation analyses, and biological meaning was inferred from known lipid-gene interactions in the literature. We found an increase in triglycerides (TGs) containing saturated fatty acids. In parallel, transcriptomic analysis confirmed the dysregulation of lipid pathways. Integration of lipidomic and transcriptomic analyses identified an increase in diacylglycerol acyltransferase 2 (DGAT2), the enzyme required for the last and committed step in TG synthesis. Increased DGAT2 expression was present not only in the murine models but also in sural nerve biopsies from hyperlipidaemic diabetic patients with PN. Collectively, these findings support the hypothesis that abnormal nerve-lipid signalling is an important factor in peripheral nerve dysfunction in both prediabetes and T2D.This article has an associated First Person interview with the joint first authors of the paper.
Project description:Background: Adrenocortical adenocarcinoma (ACC) is known to be a relatively uncommon malignant tumor of the adrenal gland with patients having a poor prognosis. At present, few reports are available concerning the m6A modifications of lncRNAs as well as their clinical and immunological significance in the occurrence and progression of ACC. Materials and Methods: In the present research, 21 m6A-related genes were analyzed. Both multivariate and univariate Cox regression analyses were conducted to examine the prognostic m6A-related lncRNAs. A sum of 165 m6A-related lncRNAs was obtained from The Cancer Genome Atlas (TCGA) dataset. Based on the expressions of m6A-related lncRNAs, all ACC patients were classified into distinct subgroups using the consistent clustering method. Finally, m6A-related lncRNAs that were shown to have prognostic value were utilized to develop an m6A-related lncRNA risk model, which may be employed in the prediction of prognosis and survival. Results: Using TCGA data set, 26 m6A-associated lncRNAs having putative prognostic values were identified according to their expression levels, TCGA-AAC patients were classified into two clusters with the aid of consistent clustering analysis. The correlation between the two clusters was low, in which cluster1 consisted of 42% of all ACC patients. The survival analysis showed that cluster1 was associated with an unfavorable prognosis relative to cluster2. A risk model was constructed incorporating 26 m6A-associated lncRNAs that were correlated with patient prognosis. The model was subsequently validated by univariate and multivariate Cox, receiver operating characteristic (ROC) curve, and survival analyses. We also observed that the m6A-related risk model performed well in anticipating prognoses and survival status of patients with AAC. The overall survival (OS) of the high-risk cohort, as predicted by the model, was lower as opposed to that of the low-risk cohort. Conclusion: In the present research, we developed a risk model consisting of 4 m6A-related long-noncoding RNAs (lncRNAs), which can exert independent predictive values in patients with ACC. Our findings demonstrated that these 4 m6A-related lncRNAs perform integral functions in the tumor immune microenvironment, and also revealed the possibility of using these lncRNAs to guide the development of prognostic classifications and therapy approaches for ACC patients.
Project description:In Duchenne muscular dystrophy (DMD), lack of dystrophin increases the permeability of myofiber plasma membranes to ions and larger macromolecules, disrupting calcium signaling and leading to progressive muscle wasting. Although the biological origin and meaning are unclear, alterations of phosphatidylcholine (PC) are reported in affected skeletal muscles of patients with DMD that may include higher levels of fatty acid (FA) 18:1 chains and lower levels of FA 18:2 chains, possibly reflected in relatively high levels of PC 34:1 (with 16:0_18:1 chain sets) and low levels of PC 34:2 (with 16:0_18:2 chain sets). Similar PC alterations have been reported to occur in the mdx mouse model of DMD. However, altered ratios of PC 34:1 to PC 34:2 have been variably reported, and we also observed that PC 34:2 levels were nearly equally elevated as PC 34:1 in the affected mdx muscles. We hypothesized that experimental factors that often varied between studies; including muscle types sampled, mouse ages, and mouse diets; may strongly impact the PC alterations detected in dystrophic muscle of mdx mice, especially the PC 34:1 to PC 34:2 ratios. In order to test our hypothesis, we performed comprehensive lipidomic analyses of PC and phosphatidylethanolamine (PE) in several muscles (extensor digitorum longus, gastrocnemius, and soleus) and determined the mdx-specific alterations. The alterations in PC 34:1 and PC 34:2 were closely monitored from the neonate period to the adult, and also in mice raised on several diets that varied in their fats. PC 34:1 was naturally high in neonate's muscle and decreased until age ∼3-weeks (disease onset age), and thereafter remained low in WT muscles but was higher in regenerated mdx muscles. Among the muscle types, soleus showed a distinctive phospholipid pattern with early and diminished mdx alterations. Diet was a major factor to impact PC 34:1/PC 34:2 ratios because mdx-specific alterations of PC 34:2 but not PC 34:1 were strictly dependent on diet. Our study identifies high PC 34:1 as a consistent biochemical feature of regenerated mdx-muscle and indicates nutritional approaches are also effective to modify the phospholipid compositions.
Project description:Aim: Neonates are notably vulnerable, however they have improved outcomes if they are fed human milk. Human milk lipids constitute the primary constituents of human milk and serve a pivotal role in safeguarding infants from diseases. We assessed the lipid differences between preterm and term human milk and predicted the prospective impacts of these lipids on the development of neonates. Methods and results: We collected colostrum from healthy breast-feeding mothers who had delivered either term or preterm infants. We analyzed the lipid profiles of preterm, as well as term human milk using an LC-MS/MS metabolomics strategy. The orthogonal partial least-squares discriminant analysis score plots revealed remarkable distinction of lipids in preterm and term human milk. In total, 16 subclasses of 235 differential lipids (variable importance in projection > 1, P < 0.05) were identified. Notably, phosphatidylethanolamine and phosphatidylcholine were robustly increased in preterm human milk, while diacylglycerol and ceramide were markedly decreased in preterm human milk. Pathway analysis revealed that these dysregulated lipids are closely associated with glycerophospholipid metabolism, sphingolipid metabolism, Reelin signaling in neurons, and LXR/RXR activation. Conclusion: The results show that the lipids in preterm and term human colostrum vary, which may be critical for neonatal development.
Project description:Mutations in MECP2 cause the autism-spectrum disorder Rett syndrome. MeCP2 is predicted to bind to methylated promoters and silence transcription. However, the first large-scale mapping of neuronal MeCP2-binding sites on 26.3 Mb of imprinted and nonimprinted loci revealed that 59% of MeCP2-binding sites are outside of genes and that only 6% are in CpG islands. Integrated genome-wide promoter analysis of MeCP2 binding, CpG methylation, and gene expression revealed that 63% of MeCP2-bound promoters are actively expressed and that only 6% are highly methylated. These results indicate that the primary function of MeCP2 is not the silencing of methylated promoters.