Modulating the cellular context broadly reshapes the mutational landscape of a model enzyme

Abstract

20Protein mutational landscapes are shaped by the cellular environment, but key factors and their 21 quantitative effects are often unknown. Here we show that Lon, a quality control protease 22 naturally absent in common E. coli expression strains, drastically reshapes the mutational 23 landscape of the metabolic enzyme dihydrofolate reductase (DHFR). Selection under conditions 24 that resolve highly active mutants reveals that 23.3% of all single point mutations in DHFR are 25 advantageous in the absence of Lon, but advantageous mutations are largely suppressed when 26Lon is reintroduced. Protein stability measurements demonstrate extensive activity-stability 27 tradeoffs for the advantageous mutants and provide a mechanistic explanation for Lon's 28 widespread impact. Our findings suggest possibilities for tuning mutational landscapes by 29 modulating the cellular environment, with implications for protein design and combatting 30 antibiotic resistance. 31 & Ranganathan, 2011), we aimed first to measure a mutational landscape for DHFR and then to 55 determine how a change to the cellular environment might affect the landscape. Because DHFR 56 is known to progress through multiple conformational states during catalysis (Boehr, McElheny, 57 Dyson, & Wright, 2006;Sawaya & Kraut, 1997) (Figure S1), we expected the mutational 58 landscape of DHFR to be constrained by the requirement to adopt these different conformations. 59Moreover, prior work had suggested DHFR is impacted by cellular constraints such as protein 60 quality control (Bershtein, Mu, Serohijos, Zhou, & Shakhnovich, 2013) and the build-up of a 61 toxic metabolic intermediate (Schober et al., 2019). We hence expected deep mutational scanning 62 to reveal a highly constrained mutational landscape for DHFR that would contrast with the 63 mutational tolerance observed in other systems. 64 65 Results 66As the basis for our studies, we first sought to establish highly sensitive selection conditions for 67 DHFR function that would be calibrated to DHFR activity and capable of resolving mutants with 68 turnover rates near-to or faster-than wild-type. We anticipated that we would need to control 69 DHFR expression because two prior studies that modified the chromosomal DHFR gene had 70 reported an overall high mutational tolerance under permissive selection conditions that revealed 71 determinants of antibiotic resistance (Garst et al., 2017) and that DHFR expression can be 72 reduced to ~30% without a growth impact (Bershtein et al., 2013). We used an E. coli strain 73 derived from ER2566 with the genes for DHFR and a downstream enzyme, thymidylate 74 synthase, deleted in the genome and complemented on a pACYC-DUET plasmid with a weak 75 ribosome binding site (see Methods). To tightly control growth conditions, we performed 76 selections in a turbidostat to maintain the culture in early Log phase growth (Figure 1A, Figure 77

Comprehensive exploration of the translocation, stability and substrate recognition requirements in VIM-2 lactamase

“…Indeed, these positions include all six active-site metal coordinating residues (His114, His116, Asp118, His179, Cys198, His240), as well as 3-4 residues adjacent to each metal binding residue in the amino acid sequence that are likely to play important roles in the metal configuration and enzymatic function. Additionally, 92% of positions with high mutational sensitivityincluding all metal binding residues-are located in the core of the protein (accessible surface area, ASA, of residue < 30%) and 63% are almost completely buried (ASA < 5%), congruent with previous findings 25,32,37,42,46,50 (Fig. 4a).…”

“…Essential and temperature dependent residues display an enrichment of sidechain-backbone h-bonding relative to the proportion of h-bonding residues in each class ( Supplementary Fig. 8b, Supplementary Data 7), suggesting-when combined with the formation of a hydrophobic core-these residues are largely involved in protein folding and stability 39,46,66…”

“…In particular, conducting DMS on a protein of interest under varying conditions-e.g. against different substrates or in different environments-has further unveiled indepth molecular details of a protein, such as residues contributing substrate specificity 42,43 and protein-environment interactions [44][45][46] .…”