Dataset Information

Integrated analysis of the proteome and transcriptome in a MCAO mouse model revealed the molecular landscape during stroke progression.

ABSTRACT: Strokes usually results in long-term disability and death, and they occur worldwide. Recently, increased research on both on the physiopathological mechanisms and the transcriptome during stroke progression, have highlighted the relationship between stroke progression and immunity, with a special focus on inflammation. Here, we applied proteome analysis to a middle carotid artery occlusion (MCAO) mouse model at 0 h, 6 h, 12 h and 24 h, in which proteome profiling was performed with 23 samples, and 41 differentially expressed proteins (DEPs) were identified. Bioinformatics studies on our data revealed the importance of the immune response and particularly identified the inflammatory response, cytokine- cytokine receptor interactions, the innate immune response and reactive oxygen species (ROS) during stroke progression. In addition, we compared our data with multiple gene expression omnibus (GEO) datasets with and without a time series, in which similar pathways were identified, and three proteins, C3, Apoa4 and S100a9, were highlighted as markers or drug targets for stroke; these three proteins were significantly upregulated in the MCAO model, both in our proteomic data and in the GEO database.

SUBMITTER: Li L

PROVIDER: S-EPMC7063112 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrated analysis of the proteome and transcriptome in a MCAO mouse model revealed the molecular landscape during stroke progression.

Li Litao L Dong Lipeng L Xiao Zhen Z He Weiliang W Zhao Jingru J Pan Henan H Chu Bao B Cheng Jinming J Wang Hebo H

Journal of advanced research 20200112

Strokes usually results in long-term disability and death, and they occur worldwide. Recently, increased research on both on the physiopathological mechanisms and the transcriptome during stroke progression, have highlighted the relationship between stroke progression and immunity, with a special focus on inflammation. Here, we applied proteome analysis to a middle carotid artery occlusion (MCAO) mouse model at 0 h, 6 h, 12 h and 24 h, in which proteome profiling was performed with 23 samples, a ...[more]

PMID: 32181013

Similar Datasets

Project description:AimsAtrial fibrillation (AF) is a progressive cardiac arrhythmia that increases the risk of hospitalization and adverse cardiovascular events. There is a clear demand for more inclusive and large-scale approaches to understand the molecular drivers responsible for AF, as well as the fundamental mechanisms governing the transition from paroxysmal to persistent and permanent forms. In this study, we aimed to create a molecular map of AF and find the distinct molecular programmes underlying cell type-specific atrial remodelling and AF progression.Methods and resultsWe used a sheep model of long-standing, tachypacing-induced AF, sampled right and left atrial tissue, and isolated cardiomyocytes (CMs) from control, intermediate (transition), and late time points during AF progression, and performed transcriptomic and proteome profiling. We have merged all these layers of information into a meaningful three-component space in which we explored the genes and proteins detected and their common patterns of expression. Our data-driven analysis points at extracellular matrix remodelling, inflammation, ion channel, myofibril structure, mitochondrial complexes, chromatin remodelling, and genes related to neural function, as well as critical regulators of cell proliferation as hallmarks of AF progression. Most important, we prove that these changes occur at early transitional stages of the disease, but not at later stages, and that the left atrium undergoes significantly more profound changes than the right atrium in its expression programme. The pattern of dynamic changes in gene and protein expression replicate the electrical and structural remodelling demonstrated previously in the sheep and in humans, and uncover novel mechanisms potentially relevant for disease treatment.ConclusionsTranscriptomic and proteomic analysis of AF progression in a large animal model shows that significant changes occur at early stages, and that among others involve previously undescribed increase in mitochondria, changes to the chromatin of atrial CMs, and genes related to neural function and cell proliferation.

Project description:UnlabelledDisorders of pain neural systems are frequently chronic and, when recalcitrant to treatment, can severely degrade the quality of life. The pain pathway begins with sensory neurons in dorsal root or trigeminal ganglia, and the neuronal subpopulations that express the transient receptor potential cation channel, subfamily V, member 1 (TRPV1) ion channel transduce sensations of painful heat and inflammation and play a fundamental role in clinical pain arising from cancer and arthritis. In the present study, we elucidate the complete transcriptomes of neurons from the TRPV1 lineage and a non-TRPV1 neuroglial population in sensory ganglia through the combined application of next-gen deep RNA-Seq, genetic neuronal labeling with fluorescence-activated cell sorting, or neuron-selective chemoablation. RNA-Seq accurately quantitates gene expression, a difficult parameter to determine with most other methods, especially for very low and very high expressed genes. Differentially expressed genes are present at every level of cellular function from the nucleus to the plasma membrane. We identified many ligand receptor pairs in the TRPV1 population, suggesting that autonomous presynaptic regulation may be a major regulatory mechanism in nociceptive neurons. The data define, in a quantitative, cell population-specific fashion, the molecular signature of a distinct and clinically important group of pain-sensing neurons and provide an overall framework for understanding the transcriptome of TRPV1 nociceptive neurons.PerspectiveNext-gen RNA-Seq, combined with molecular genetics, provides a comprehensive and quantitative measurement of transcripts in TRPV1 lineage neurons and a contrasting transcriptome from non-TRPV1 neurons and cells. The transcriptome highlights previously unrecognized protein families, identifies multiple molecular circuits for excitatory or inhibitory autocrine and paracrine signaling, and suggests new combinatorial approaches to pain control.

Dataset Information

Integrated analysis of the proteome and transcriptome in a MCAO mouse model revealed the molecular landscape during stroke progression.

Publications

Integrated analysis of the proteome and transcriptome in a MCAO mouse model revealed the molecular landscape during stroke progression.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets