Integrated multilayer omics reveals the genomic, proteomic and metabolic influences of the histidyl dipeptides on heart
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE192583 | GEO | 2021/12/27
REPOSITORIES: GEO
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Project description:Histidyl dipeptides, such as carnosine, present in a micro-millimolar ranges in the heart, are synthesized via the enzyme carnosine synthase (Carns). These dipeptides facilitate glycolysis by proton buffering, form conjugates with reactive aldehydes, such as acrolein, and attenuate ischemia and reperfusion injury. While these dipeptides exhibit multifunctional properties, a composite understanding of their roles in myocardium is lacking. To identify the landscape of histidyl dipeptide mediated responses in the heart, we used a triomics approach of genome wide RNA sequencing, global proteomics and unbiased metabolomics in the cardio specific Carns transgenic (Tg) mice and integrated the three data sets. Our result show higher myocardial levels of histidyl dipeptides lead to extensive changes in several microRNAs, which could target the expression of contractile proteins, beta-fatty acid oxidation and citric acid cycle (TCA) enzymes. Global proteomics shows, expression of contractile proteins, enzymes of beta-fatty acid oxidation and TCA cycle, were enriched in the CarnsTg heart. Under aerobic conditions, the CarnsTg hearts had lower levels of short and long-chain fatty acids and TCA cycle intermediate-succinic acid, whereas, under ischemic conditions the accumulation of fatty acids and TCA cycle intermediates were significantly attenuated in the CarnsTg heart. Integration of multiple data sets suggests that beta-fatty acid oxidation and TCA cycle pathways exhibited correlative changes in the CarnsTg hearts at all three levels. Our triomics approach shows histidyl dipeptides are critical regulators of myocardial structure, function and energetics.
2021-12-15 | ST002056 | MetabolomicsWorkbench
Project description:Histidyl dipeptides, such as carnosine, present in a micro-millimolar ranges in the heart, are synthesized via the enzyme carnosine synthase (Carns). These dipeptides facilitate glycolysis by proton buffering, form conjugates with reactive aldehydes, such as acrolein, and attenuate ischemia and reperfusion injury. While these dipeptides exhibit multifunctional properties, a composite understanding of their roles in myocardium is lacking. To identify the landscape of histidyl dipeptide mediated responses in the heart, we used a triomics approach of genome wide RNA sequencing, global proteomics and unbiased metabolomics in the cardio specific Carns transgenic (Tg) mice and integrated the three data sets.
2021-12-25 | PXD030647 |
Project description:Integrated multilayer omics reveals the genomic, proteomic and metabolic influences of the histidyl dipeptides on heart
| PRJNA792134 | ENA
Project description:Background Histidyl dipeptides such as carnosine are present in a micromolar to millimolar range in mammalian hearts. These dipeptides facilitate glycolysis by proton buffering. They form conjugates with reactive aldehydes, such as acrolein, and attenuate myocardial ischemia-reperfusion injury. Although these dipeptides exhibit multifunctional properties, a composite understanding of their role in the myocardium is lacking. Methods and Results To identify histidyl dipeptide-mediated responses in the heart, we used an integrated triomics approach, which involved genome-wide RNA sequencing, global proteomics, and unbiased metabolomics to identify the effects of cardiospecific transgenic overexpression of the carnosine synthesizing enzyme, carnosine synthase (Carns), in mice. Our result showed that higher myocardial levels of histidyl dipeptides were associated with extensive changes in the levels of several microRNAs, which target the expression of contractile proteins, β-fatty acid oxidation, and citric acid cycle (TCA) enzymes. Global proteomic analysis showed enrichment in the expression of contractile proteins, enzymes of β-fatty acid oxidation, and the TCA in the Carns transgenic heart. Under aerobic conditions, the Carns transgenic hearts had lower levels of short- and long-chain fatty acids as well as the TCA intermediate-succinic acid; whereas, under ischemic conditions, the accumulation of fatty acids and TCA intermediates was significantly attenuated. Integration of multiple data sets suggested that β-fatty acid oxidation and TCA pathways exhibit correlative changes in the Carns transgenic hearts at all 3 levels. Conclusions Taken together, these findings reveal a central role of histidyl dipeptides in coordinated regulation of myocardial structure, function, and energetics.
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Project description:Multilayer omics profiling has become a major venue for understanding complex diseases. We develop NCutYX, an R package for clustering analysis of multilayer omics data. The package and methods jointly analyze multiple layers of omics measurements and effectively accommodate their regulations. They systematically conduct a series of analysis based on the normalized cut technique, including the clusterings of subjects and omics measurements and biclustering. The package can be valuable for its timely context, novel methods, and comprehensiveness. https://cran.r-project.org/web/packages/NCutYX/. Supplementary data are available at Bioinformatics online.
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Project description:MotivationSingle-cell sequencing technologies that simultaneously generate multimodal cellular profiles present opportunities for improved understanding of cell heterogeneity in tissues. How the multimodal information can be integrated to obtain a common cell type identification, however, poses a computational challenge. Multilayer graphs provide a natural representation of multi-omic single-cell sequencing datasets, and finding cell clusters may be understood as a multilayer graph partition problem.ResultsWe introduce two spectral algorithms on multilayer graphs, spectral clustering on multilayer graphs and the weighted locally linear (WLL) method, to cluster cells in multi-omic single-cell sequencing datasets. We connect these algorithms through a unifying mathematical framework that represents each layer using a Hamiltonian operator and a mixture of its eigenstates to integrate the multiple graph layers, demonstrating in the process that the WLL method is a rigorous multilayer spectral graph theoretic reformulation of the popular Seurat weighted nearest neighbor (WNN) algorithm. Implementing our algorithms and applying them to a CITE-seq dataset of cord blood mononuclear cells yields results similar to the Seurat WNN analysis. Our work thus extends spectral methods to multimodal single-cell data analysis.Availability and implementationThe code used in this study can be found at https://github.com/jssong-lab/sc-spectrum. All public data used in the article are accurately cited and described in Materials and Methods and in Supplementary Information.Supplementary informationSupplementary data are available at Bioinformatics online.
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