Helmholtz Gemeinschaft

Search
Browse
Statistics
Feeds

Identifying cell-type-specific metabolic signatures using transcriptome and proteome analyses

[img]
Preview
PDF (Original Article) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
2MB

Item Type:Article
Title:Identifying cell-type-specific metabolic signatures using transcriptome and proteome analyses
Creators Name:Gebert, N. and Rahman, S. and Lewis, C.A. and Ori, A. and Cheng, C.W.
Abstract:Studies in various tissues have revealed a central role of metabolic pathways in regulating adult stem cell function in tissue regeneration and tumor initiation. The unique metabolic dependences or preferences of adult stem cells, therefore, are emerging as a new category of therapeutic target. Recently, advanced methods including high-resolution metabolomics, proteomics, and transcriptomics have been developed to address the growing interest in stem cell metabolism. A practical framework integrating the omics analyses is needed to systematically perform metabolic characterization in a cell-type-specific manner. Here, we leverage recent advances in transcriptomics and proteomics research to identify cell-type-specific metabolic features by reconstructing cell identity using genes and the encoded enzymes involved in major metabolic pathways. We provide protocols for cell isolation, transcriptome and proteome analyses, and metabolite profiling and measurement. The workflow for mapping cell-type-specific metabolic signatures presented here, although initially developed for intestinal crypt cells, can be easily implemented for cell populations in other tissues, and is highly compatible with most public datasets
Keywords:Metabolism, Proteome, Stem Cell, Transcriptome
Source:Current Protocols
ISSN:2691-1299
Publisher:Wiley
Volume:1
Number:9
Page Range:e245
Date:28 September 2021
Official Publication:https://doi.org/10.1002/cpz1.245
PubMed:View item in PubMed

Repository Staff Only: item control page

Downloads

Downloads per month over past year

Open Access
MDC Library