Advances in metabolic flux analysis toward genome-scale profiling of higher organisms
- Methodological and technological advances have recently paved the way for metabolic flux profiling in higher organisms, like plants. However, in comparison with omics technologies, flux profiling has yet to provide comprehensive differential flux maps at a genome-scale and in different cell types, tissues, and organs. Here we highlight the recent advances in technologies to gather metabolic labeling patterns and flux profiling approaches. We provide an opinion of how recent local flux profiling approaches can be used in conjunction with the constraint-based modeling framework to arrive at genome-scale flux maps. In addition, we point at approaches which use metabolomics data without introduction of label to predict either non-steady state fluxes in a time-series experiment or flux changes in different experimental scenarios. The combination of these developments allows an experimentally feasible approach for flux-based large-scale systems biology studies.
Author details: | Georg Basler, Alisdair FernieORCiDGND, Zoran NikoloskiORCiDGND |
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DOI: | https://doi.org/10.1042/BSR20170224 |
ISSN: | 0144-8463 |
ISSN: | 1573-4935 |
Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/30341247 |
Title of parent work (English): | Bioscience reports : communications and reviews in molecular and cellular biology |
Publisher: | Portland Press (London) |
Place of publishing: | London |
Publication type: | Review |
Language: | English |
Date of first publication: | 2018/10/19 |
Publication year: | 2018 |
Release date: | 2021/07/30 |
Volume: | 38 |
Number of pages: | 11 |
Funding institution: | Federal Ministry of Education and Research of Germany within the project RECONSTRUCT [031B0200 A-E]; Federal Ministry of Education and Research of Germany within the project FULLTHROTTLE [031B0205 B]; University of Potsdam; Max Planck SocietyMax Planck Society |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie |
DDC classification: | 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie |
Peer review: | Referiert |
Publishing method: | Open Access / Gold Open-Access |
DOAJ gelistet | |
License (German): | CC-BY - Namensnennung 4.0 International |