Publication

High-Order Epistasis in Catalytic Power of Dihydrofolate Reductase Gives Rise to a Rugged Fitness Landscape in the Presence of Trimethoprim Selection

Tamer, Y. T., Gaszek, I. K., Abdizadeh, H., Batur, T. A., Reynolds, K. A., Atilgan, A. R., Atilgan, C. & Toprak, E., Jul-2019, In : Molecular Biology and Evolution. 36, 7, p. 1533-1550 18 p.

Research output: Contribution to journalArticleAcademicpeer-review

  • Yusuf Talha Tamer
  • Ilona K. Gaszek
  • Haleh Abdizadeh
  • Tugce Altinusak Batur
  • Kimberly A. Reynolds
  • Ali Rana Atilgan
  • Canan Atilgan
  • Erdal Toprak

Evolutionary fitness landscapes of several antibiotic target proteins have been comprehensively mapped showing strong high-order epistasis between mutations, but understanding these effects at the biochemical and structural levels remained open. Here, we carried out an extensive experimental and computational study to quantitatively understand the evolutionary dynamics of Escherichia coli dihydrofolate reductase (DHFR) enzyme in the presence of trimethoprim-induced selection. To facilitate this, we developed a new in vitro assay for rapidly characterizing DHFR steady-state kinetics. Biochemical and structural characterization of resistance-conferring mutations targeting a total of ten residues spanning the substrate binding pocket of DHFR revealed distinct changes in the catalytic efficiencies of mutated DHFR enzymes. Next, we measured biochemical parameters (K-m, K-i, and k(cat)) for a mutant library carrying all possible combinations of six resistance-conferring DHFR mutations and quantified epistatic interactions between them. We found that the high-order epistasis in catalytic power of DHFR (k(cat) and K-m) creates a rugged fitness landscape under trimethoprim selection. Taken together, our data provide a concrete illustration of how epistatic coupling at the level of biochemical parameters can give rise to complex fitness landscapes, and suggest new strategies for developing mutant specific inhibitors.

Original languageEnglish
Pages (from-to)1533-1550
Number of pages18
JournalMolecular Biology and Evolution
Volume36
Issue number7
Publication statusPublished - Jul-2019

    Keywords

  • antibiotic resistance, molecular evolution, experimental evolution, epistasis, protein evolution, ANTIBIOTIC-RESISTANCE, ESCHERICHIA-COLI, MOLECULAR-DYNAMICS, DRUG-RESISTANCE, EVOLUTION, MUTATIONS, ALGORITHM, MODULATE, MUTANTS, COMPLEX

Download statistics

No data available

ID: 118501699