4.6 Editorial Material

High-throughput and reliable acquisition of in vivo turnover number fuels precise metabolic engineering

Journal

SYNTHETIC AND SYSTEMS BIOTECHNOLOGY
Volume 7, Issue 1, Pages 541-543

Publisher

KEAI PUBLISHING LTD
DOI: 10.1016/j.synbio.2021.12.006

Keywords

Turnover number; Genome scale models; High throughput; Metabolic reconstitution; Machine learning

Funding

  1. National Natural Science Foundation of China [31922002, 32101174]
  2. National Key RAMP
  3. D program of China [2020YFA0907800]
  4. 111 Project [B18022]
  5. Youth Innovation Promotion Association CAS [Y202027]
  6. China Postdoctoral Science Foundation [2021M703379]

Ask authors/readers for more resources

With the development of synthetic biology, mathematical information can provide accurate understanding of cell metabolism and growth, and guide precision metabolic engineering. Enzyme kinetic parameters are important for describing enzyme activity and quantitatively understanding biological systems.
As synthetic biology enters the era of quantitative biology, mathematical information such as kinetic parameters of enzymes can offer us an accurate knowledge of metabolism and growth of cells, and further guidance on precision metabolic engineering. k(cat), termed the turnover number, is a basic parameter of enzymes that describes the maximum number of substrates converted to products each active site per unit time. It reflects enzyme activity and is essential for quantitative understanding of biosystems. Usually, the k(cat) values are measured in vitro, thus may not be able to reflect the enzyme activity in vivo. In this case, Davidi et al. defined a surrogate k(max)(vivo) (k(app)) for k(cat) and developed a high throughput method to acquire k(max)(vivo) from omics data. Heckmann et al. and Chen et al. proved that the surrogate parameter can be a good embodiment of the physiological state of enzymes and exhibit superior performance for enzyme-constrained metabolic model to the default one. These breakthroughs will fuel the development of system and synthetic biology.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available