Literature DB >> 28288339

Lessons on enzyme kinetics from quantitative proteomics.

Dan Davidi1, Ron Milo2.   

Abstract

Enzyme kinetics are fundamental to an understanding of cellular metabolism and for crafting synthetic biology applications. For decades, enzyme characterization has been based on in vitro enzyme assays. However, kinetic parameters are only available for <10% of reactions, and this data scarcity limits the predictive power of metabolic models. Here we review recent studies that leverage quantitative proteomics to gain insight into in vivo enzyme kinetics. We discuss findings on the relationship between in vivo and in vitro enzyme catalysis and show how proteomics can be used to characterize the efficiency of enzyme utilization across conditions. Lastly, the efficient use of enzymes is shown to rationalize preference for low energy-yield metabolic strategies, such as aerobic fermentation at high growth rate.
Copyright © 2017 Elsevier Ltd. All rights reserved.

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Year:  2017        PMID: 28288339     DOI: 10.1016/j.copbio.2017.02.007

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


  19 in total

1.  Growth-Optimized Aminoacyl-tRNA Synthetase Levels Prevent Maximal tRNA Charging.

Authors:  Darren J Parker; Jean-Benoît Lalanne; Satoshi Kimura; Grace E Johnson; Matthew K Waldor; Gene-Wei Li
Journal:  Cell Syst       Date:  2020-07-28       Impact factor: 10.304

2.  Leaf Energy Balance Requires Mitochondrial Respiration and Export of Chloroplast NADPH in the Light.

Authors:  Sanu Shameer; R George Ratcliffe; Lee J Sweetlove
Journal:  Plant Physiol       Date:  2019-06-18       Impact factor: 8.340

3.  An alternative resource allocation strategy in the chemolithoautotrophic archaeon Methanococcus maripaludis.

Authors:  Albert L Müller; Wenyu Gu; Vadim Patsalo; Jörg S Deutzmann; James R Williamson; Alfred M Spormann
Journal:  Proc Natl Acad Sci U S A       Date:  2021-04-20       Impact factor: 11.205

4.  Protein allocation and utilization in the versatile chemolithoautotroph Cupriavidus necator.

Authors:  Michael Jahn; Nick Crang; Markus Janasch; Andreas Hober; Björn Forsström; Kyle Kimler; Alexander Mattausch; Qi Chen; Johannes Asplund-Samuelsson; Elton Paul Hudson
Journal:  Elife       Date:  2021-11-01       Impact factor: 8.140

5.  Absolute Proteome Quantification in the Gas-Fermenting Acetogen Clostridium autoethanogenum.

Authors:  Kaspar Valgepea; Gert Talbo; Nobuaki Takemori; Ayako Takemori; Christina Ludwig; Vishnuvardhan Mahamkali; Alexander P Mueller; Ryan Tappel; Michael Köpke; Séan Dennis Simpson; Lars Keld Nielsen; Esteban Marcellin
Journal:  mSystems       Date:  2022-04-06       Impact factor: 7.324

6.  The Moderately (D)efficient Enzyme: Catalysis-Related Damage In Vivo and Its Repair.

Authors:  Ulschan Bathe; Bryan J Leong; Donald R McCarty; Christopher S Henry; Paul E Abraham; Mark A Wilson; Andrew D Hanson
Journal:  Biochemistry       Date:  2021-11-03       Impact factor: 3.321

Review 7.  The Scope of Big Data in One Medicine: Unprecedented Opportunities and Challenges.

Authors:  Molly E McCue; Annette M McCoy
Journal:  Front Vet Sci       Date:  2017-11-16

8.  The genetic basis for the adaptation of E. coli to sugar synthesis from CO2.

Authors:  Elad Herz; Niv Antonovsky; Yinon Bar-On; Dan Davidi; Shmuel Gleizer; Noam Prywes; Lianet Noda-Garcia; Keren Lyn Frisch; Yehudit Zohar; David G Wernick; Alon Savidor; Uri Barenholz; Ron Milo
Journal:  Nat Commun       Date:  2017-11-22       Impact factor: 14.919

9.  Allosteric Feedback Inhibition Enables Robust Amino Acid Biosynthesis in E. coli by Enforcing Enzyme Overabundance.

Authors:  Timur Sander; Niklas Farke; Christoph Diehl; Michelle Kuntz; Timo Glatter; Hannes Link
Journal:  Cell Syst       Date:  2019-01-09       Impact factor: 10.304

10.  Capacity for instantaneous catabolism of preferred and non-preferred carbon sources in Escherichia coli and Bacillus subtilis.

Authors:  Marieke F Buffing; Hannes Link; Dimitris Christodoulou; Uwe Sauer
Journal:  Sci Rep       Date:  2018-08-06       Impact factor: 4.379

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