Biophysical principles predict fitness landscapes of drug resistance

Abstract

Fitness landscapes of drug resistance constitute powerful tools to elucidate mutational pathways of antibiotic escape. Here, we developed a predictive biophysics-based fitness landscape of trimethoprim (TMP) resistance for Escherichia coli dihydrofolate reductase (DHFR). We investigated the activity, binding, folding stability, and intracellular abundance for a complete set of combinatorial DHFR mutants made out of three key resistance mutations and extended this analysis to DHFR originated from Chlamydia muridarum and Listeria grayi. We found that the acquisition of TMP resistance via decreased drug affinity is limited by a trade-off in catalytic efficiency. Protein stability is concurrently affected by the resistant mutants, which precludes a precise description of fitness from a single molecular trait. Application of the kinetic flux theory provided an accurate model to predict resistance phenotypes (IC50) quantitatively from a unique combination of the in vitro protein molecular properties. Further, we found that a controlled modulation of the GroEL/ES chaperonins and Lon protease levels affects the intracellular steady-state concentration of DHFR in a mutation-specific manner, whereas IC50 is changed proportionally, as indeed predicted by the model. This unveils a molecular rationale for the pleiotropic role of the protein quality control machinery on the evolution of antibiotic resistance, which, as we illustrate here, may drastically confound the evolutionary outcome. These results provide a comprehensive quantitative genotype–phenotype map for the essential enzyme that serves as an important target of antibiotic and anticancer therapies.

Plant-Derived Antimicrobials: Insights into Mitigation of Antimicrobial Resistance

“…Another example is observed in the overexpression of the enzyme dihydrofolate reductase, which is crucial in the nucleic acid precursor synthesis in Mycobacterium tuberculosis and E. coli. This enzyme confers resistance to antimicrobial drugs such as para-aminosalicylic acid and trimethoprim [42][43].…”

Transient protein-protein interactions perturb E. coli metabolome and cause gene dosage toxicity

“…We explored fitness of E. coli in a broad range of EcDHFR abundances – from strong down-regulation to ~850 fold overexpression and established that the basal expression level is close to the optimal at which fitness is the highest, while both down regulation and overexpression appear toxic. While the drop in E. coli fitness upon DHFR downregulation is predicted by the enzymatic flux kinetics analysis (Bershtein et al, 2015; Rodrigues, 2016), toxicity upon overexpression is at variance with enzymatic flux kinetics analysis, which predicts fitness neutrality once the functional capacity of an enzyme, defined as the product of its intracellular abundance and catalytic efficiency ( k cat /K M ), exceeds the threshold flux through a metabolic path (Feist and Palsson, 2010; Lewis et al, 2012; Kacser and Burns, 1981; Dykhuizen et al, 1987). …”

Using cellular fitness to map the structure and function of a major facilitator superfamily effluxer

“…Typically, well‐behaved proteins whose function is strongly correlated to organismal fitness are used to study this link as their biochemical properties can be readily measured in vitro . Such model proteins include TEM‐1 β‐lactamase, dihydrofolate reductase, and adenylate kinase (Wang et al , 2002; Couñago et al , 2006; Weinreich et al , 2006; Peña et al , 2010; Jacquier et al , 2013; Rodrigues et al , 2016). These advances have provided a greater understanding into how the physicochemical properties of a protein relate to fitness and allow investigators to explore the role of fitness landscapes in adaptive evolution (Weinreich et al , 2006; Dean & Thornton, 2007; Walkiewicz et al , 2012; Harms & Thornton, 2013; Meini et al , 2015; Palmer et al , 2015).…”