The genetic landscape of a metabolic interaction

Thuy N Nguyen; Christine Ingle; Samuel Thompson; Kimberly A Reynolds

doi:10.1038/s41467-024-47671-0

The genetic landscape of a metabolic interaction

Nat Commun. 2024 Apr 18;15(1):3351. doi: 10.1038/s41467-024-47671-0.

Authors

Thuy N Nguyen^{1

2

3

4}, Christine Ingle^{1

2

3}, Samuel Thompson^{5

6}, Kimberly A Reynolds^{7

8

9}

Affiliations

¹ The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
² The Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
³ The Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
⁴ Form Bio, Dallas, TX, 75226, USA.
⁵ Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, 94158, USA.
⁶ Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
⁷ The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA. kimberly.reynolds@utsouthwestern.edu.
⁸ The Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA. kimberly.reynolds@utsouthwestern.edu.
⁹ The Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA. kimberly.reynolds@utsouthwestern.edu.

Abstract

While much prior work has explored the constraints on protein sequence and evolution induced by physical protein-protein interactions, the sequence-level constraints emerging from non-binding functional interactions in metabolism remain unclear. To quantify how variation in the activity of one enzyme constrains the biochemical parameters and sequence of another, we focus on dihydrofolate reductase (DHFR) and thymidylate synthase (TYMS), a pair of enzymes catalyzing consecutive reactions in folate metabolism. We use deep mutational scanning to quantify the growth rate effect of 2696 DHFR single mutations in 3 TYMS backgrounds under conditions selected to emphasize biochemical epistasis. Our data are well-described by a relatively simple enzyme velocity to growth rate model that quantifies how metabolic context tunes enzyme mutational tolerance. Together our results reveal the structural distribution of epistasis in a metabolic enzyme and establish a foundation for the design of multi-enzyme systems.

MeSH terms

Mutation
Thymidylate Synthase* / metabolism

Substances

Thymidylate Synthase

Grants and funding

R01 GM136842/GM/NIGMS NIH HHS/United States