Literature DB >> 27838571

Recent advances in high-throughput 13C-fluxomics.

Stéphanie Heux1, Cécilia Bergès1, Pierre Millard1, Jean-Charles Portais1, Fabien Létisse2.   

Abstract

The rise of high throughput (HT) strain engineering tools accompanying the area of synthetic biology is supporting the generation of a large number of microbial cell factories. A current bottleneck in process development is our limited capacity to rapidly analyze the metabolic state of the engineered strains, and in particular their intracellular fluxes. HT 13C-fluxomics workflows have not yet become commonplace, despite the existence of several HT tools at each of the required stages. This includes cultivation and sampling systems, analytics for isotopic analysis, and software for data processing and flux calculation. Here, we review recent advances in the field and highlight bottlenecks that must be overcome to allow the emergence of true HT 13C-fluxomics workflows.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2016        PMID: 27838571     DOI: 10.1016/j.copbio.2016.10.010

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  10 in total

Review 1.  Tracing metabolic flux in vivo: basic model structures of tracer methodology.

Authors:  Il-Young Kim; Sanghee Park; Yeongmin Kim; Hee-Joo Kim; Robert R Wolfe
Journal:  Exp Mol Med       Date:  2022-09-08       Impact factor: 12.153

2.  Exploring the Glucose Fluxotype of the E. coli y-ome Using High-Resolution Fluxomics.

Authors:  Cécilia Bergès; Edern Cahoreau; Pierre Millard; Brice Enjalbert; Mickael Dinclaux; Maud Heuillet; Hanna Kulyk; Lara Gales; Noémie Butin; Maxime Chazalviel; Tony Palama; Matthieu Guionnet; Sergueï Sokol; Lindsay Peyriga; Floriant Bellvert; Stéphanie Heux; Jean-Charles Portais
Journal:  Metabolites       Date:  2021-04-26

3.  Assessing glycolytic flux alterations resulting from genetic perturbations in E. coli using a biosensor.

Authors:  Christina E Lehning; Solvej Siedler; Mostafa M H Ellabaan; Morten O A Sommer
Journal:  Metab Eng       Date:  2017-07-12       Impact factor: 9.783

4.  Dynamic Labeling Reveals Temporal Changes in Carbon Re-Allocation within the Central Metabolism of Developing Apple Fruit.

Authors:  Wasiye F Beshir; Victor B M Mbong; Maarten L A T M Hertog; Annemie H Geeraerd; Wim Van den Ende; Bart M Nicolaï
Journal:  Front Plant Sci       Date:  2017-10-18       Impact factor: 5.753

5.  Parallel isotope differential modeling for instationary 13C fluxomics at the genome scale.

Authors:  Zhengdong Zhang; Zhentao Liu; Yafei Meng; Zhen Chen; Jiayu Han; Yimin Wei; Tie Shen; Yin Yi; Xiaoyao Xie
Journal:  Biotechnol Biofuels       Date:  2020-06-08       Impact factor: 6.040

6.  The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis.

Authors:  Martin Beyß; Salah Azzouzi; Michael Weitzel; Wolfgang Wiechert; Katharina Nöh
Journal:  Front Microbiol       Date:  2019-05-24       Impact factor: 5.640

Review 7.  Fluxomics - New Metabolomics Approaches to Monitor Metabolic Pathways.

Authors:  Abdul-Hamid Emwas; Kacper Szczepski; Inas Al-Younis; Joanna Izabela Lachowicz; Mariusz Jaremko
Journal:  Front Pharmacol       Date:  2022-03-21       Impact factor: 5.810

8.  Hot isopropanol quenching procedure for automated microtiter plate scale 13C-labeling experiments.

Authors:  Jochen Nießer; Moritz Fabian Müller; Jannick Kappelmann; Wolfgang Wiechert; Stephan Noack
Journal:  Microb Cell Fact       Date:  2022-05-09       Impact factor: 5.328

9.  A Pareto approach to resolve the conflict between information gain and experimental costs: Multiple-criteria design of carbon labeling experiments.

Authors:  Katharina Nöh; Sebastian Niedenführ; Martin Beyß; Wolfgang Wiechert
Journal:  PLoS Comput Biol       Date:  2018-10-31       Impact factor: 4.475

10.  ScalaFlux: A scalable approach to quantify fluxes in metabolic subnetworks.

Authors:  Pierre Millard; Uwe Schmitt; Patrick Kiefer; Julia A Vorholt; Stéphanie Heux; Jean-Charles Portais
Journal:  PLoS Comput Biol       Date:  2020-04-14       Impact factor: 4.475

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.