Integrating Lipidomics and Transcriptomics Reveals the Crosstalk Between Oxidative Stress and Neuroinflammation in Central Nervous System Demyelination

Zhao, Z.; Zheng, Ruizhe; Wang, Xiaojing; Li, Tongqi; Dong, Xiaohua; Zhao, Changyi; Li, Xinyuan

doi:10.3389/fnagi.2022.870957

Cited by 26 publications

(15 citation statements)

References 29 publications

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“…Lipid profiling, identification, and quantification. Lipid profiling, identification, and quantification were implemented as described below, following the protocol from a previous study 70 . In more detail, the lipid profiling was first conducted with a LC-ESI-MS/MS system, which combines the ultra performance liquid chromatography (UPLC) using the SCIEX ExionLC AD system (Danaher Corporation, America) and the tandem mass spectrometry (MS/MS) using the SCIEX QTRAP ® LC-MS/ MS system (Danaher Corporation, America).…”

Section: Lipidomic Datamentioning

confidence: 99%

Whole-body adipose tissue multi-omic analyses in sheep reveal molecular mechanisms underlying local adaptation to extreme environments

Wang

Jing

et al. 2023

Commun Biol

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The fat tail of sheep is an important organ that has evolved to adapt to extreme environments. However, the genetic mechanisms underlying the fat tail phenotype remain poorly understood. Here, we characterize transcriptome and lipidome profiles and morphological changes in 250 adipose tissues from two thin-tailed and three fat-tailed sheep populations in summer and winter. We implement whole-genome selective sweep tests to identify genetic variants related to fat-tails. We identify a set of functional genes that show differential expression in the tail fat of fat-tailed and thin-tailed sheep in summer and winter. These genes are significantly enriched in pathways, such as lipid metabolism, extracellular matrix (ECM) remodeling, molecular transport, and inflammatory response. In contrast to thin-tailed sheep, tail fat from fat-tailed sheep show slighter changes in adipocyte size, ECM remodeling, and lipid metabolism, and had less inflammation in response to seasonal changes, indicating improved homeostasis. Whole-genome selective sweep tests identify genes involved in preadipocyte commitment (e.g., BMP2, PDGFD) and terminal adipogenic differentiation (e.g., VEGFA), which could contribute to enhanced adipocyte hyperplasia. Altogether, we establish a model of regulatory networks regulating adipose homeostasis in sheep tails. These findings improve our understanding of how adipose homeostasis is maintained, in response to extreme environments in animals.

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Section: Lipidomic Datamentioning

confidence: 99%

Whole-body adipose tissue multi-omic analyses in sheep reveal molecular mechanisms underlying local adaptation to extreme environments

Wang

Jing

et al. 2023

Commun Biol

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“…The lipidomics analysis method was similar to the previously reported ( Zhao et al, 2022 ). We first used unsupervised principal component analysis (PCA) to observe the overall distribution across samples as well as the stability of the entire analysis process ( Supplementary Figure S2A ), and then supervised partial least squares analysis (PLS-DA) and orthogonal partial least squares analysis (OPLS-DA) were used to distinguish the overall differences in metabolic profiles between groups and find the differential metabolites between groups ( Supplementary Figures S2C-D ).…”

Section: Methodsmentioning

confidence: 90%

Multi-omics analysis revealed the role of CYP1A2 in the induction of mechanical allodynia in type 1 diabetes

Chen

Liao²,

Yang³

et al. 2023

Front. Genet.

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Background: Mechanical allodynia (MA) is one of the leading clinical symptoms of painful diabetic peripheral neuropathy (PDPN), which is a primary reason for non-traumatic amputations, foot ulceration, and gait abnormalities in patients with diabetes. However, the pathogenic mechanisms of MA have not yet been fully elucidated, and there is no effective treatment. This study aims to study the potential pathogenetic mechanisms of MA and to provide targets for the therapy of MA.Methods: A single intraperitoneal injection of streptozotocin induced type 1 diabetes in rat models. Subsequently, rats were divided into the control group, the diabetic group without MA, and the diabetic group with MA based on weekly behavioral assays. The differentially expressed lipids in the sciatic nerve of each group were detected using untargeted lipidomics, and the differentially expressed genes in the sciatic nerve of each group were detected by transcriptomics. The pathogenesis of MA was predicted using integrated analysis and validated by immunofluorescence staining and transmission electron microscopy.Results: Untargeted lipidomics revealed the accumulation of a more severe lipid in MA rats. Transcriptomics results suggested that differentially expressed genes in MA rats were primarily related to lipid droplets and myelin sheath. Integrated analysis results indicated that the downregulation of Cytochrome P450 1A2 (CYP1A2) expression was closely linked to lipid metabolism disorders. Immunofluorescence staining demonstrated that down-regulation of CYP1A2 expression occurred in MA rats. Transmission electron microscopy results showed that more severe lipid droplet accumulation and myelin sheath degeneration occurred in MA rats.Conclusion: Our findings imply that the downregulation of CYP1A2 expression leads to disorders of lipid metabolism and further leads to lipid droplet accumulation and myelin sheath degeneration, which might ultimately lead to the development of MA. Therefore, our study contributes to promoting the understanding of the molecular mechanisms of MA and providing potential targets for the clinical treatment of MA.

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“…We also used the CopyKAT R package ( 29 ) to analyze the CNV characteristics of CAFs clusters and distinguish between tumor cells and normal ones. Finally, we performed Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the marker genes using the clusterProfiler package ( 30 ).…”

Section: Methodsmentioning

confidence: 99%

A novel signature predicts prognosis and immunotherapy in lung adenocarcinoma based on cancer-associated fibroblasts

et al. 2023

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BackgroundExtensive research has established the significant correlations between cancer-associated fibroblasts (CAFs) and various stages of cancer development, including initiation, angiogenesis, progression, and resistance to therapy. In this study, we aimed to investigate the characteristics of CAFs in lung adenocarcinoma (LUAD) and develop a risk signature to predict the prognosis of patients with LUAD.MethodsWe obtained single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the public database. The Seurat R package was used to process the scRNA-seq data and identify CAF clusters based on several biomarkers. CAF-related prognostic genes were further identified using univariate Cox regression analysis. To reduce the number of genes, Lasso regression was performed, and a risk signature was established. A novel nomogram that incorporated the risk signature and clinicopathological features was developed to predict the clinical applicability of the model. Additionally, we conducted immune landscape and immunotherapy responsiveness analyses. Finally, we performed in vitro experiments to verify the functions of EXO1 in LUAD.ResultsWe identified 5 CAF clusters in LUAD using scRNA-seq data, of which 3 clusters were significantly associated with prognosis in LUAD. A total of 492 genes were found to be significantly linked to CAF clusters from 1731 DEGs and were used to construct a risk signature. Moreover, our immune landscape exploration revealed that the risk signature was significantly related to immune scores, and its ability to predict responsiveness to immunotherapy was confirmed. Furthermore, a novel nomogram incorporating the risk signature and clinicopathological features showed excellent clinical applicability. Finally, we verified the functions of EXP1 in LUAD through in vitro experiments.ConclusionsThe risk signature has proven to be an excellent predictor of LUAD prognosis, stratifying patients more appropriately and precisely predicting immunotherapy responsiveness. The comprehensive characterization of LUAD based on the CAF signature can predict the response of LUAD to immunotherapy, thus offering fresh perspectives into the management of LUAD patients. Our study ultimately confirms the role of EXP1 in facilitating the invasion and growth of tumor cells in LUAD. Nevertheless, further validation can be achieved by conducting in vivo experiments.

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Integrating Lipidomics and Transcriptomics Reveals the Crosstalk Between Oxidative Stress and Neuroinflammation in Central Nervous System Demyelination

Cited by 26 publications

References 29 publications

Whole-body adipose tissue multi-omic analyses in sheep reveal molecular mechanisms underlying local adaptation to extreme environments

Whole-body adipose tissue multi-omic analyses in sheep reveal molecular mechanisms underlying local adaptation to extreme environments

Multi-omics analysis revealed the role of CYP1A2 in the induction of mechanical allodynia in type 1 diabetes

A novel signature predicts prognosis and immunotherapy in lung adenocarcinoma based on cancer-associated fibroblasts

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