Terms used or introduced in this study and their definition.

For some terms, references are provided for clarity.

Hypercube descriptions of the TEM1/TEM-50 fitness landscape examined in this study.

The TEM-50 variant is represented by the quadruple mutant, LKSD, and the wild-type, MEGN, represents TEM-1. The figure highlights the variation in the topography of the various fitness landscapes. Y-axes correspond to the growth rates relative to the wild-type of the allelic variants. The X-axis corresponds to the number of mutations away from the TEM-1 wild-type MEGN.

Data from empirical fitness landscapes can be used to compute two metrics: variant vulnerability (for allelic variants) and drug applicability (for drugs).

Growth of allelic variants, relative to control (wild-type), for seven drug treatments. Bars represent the mean value for each group; orange bars indicate significantly lower growth with respect to control (one-tailed t-test, P < 0.01), grey bars otherwise. The bars, from left to right, along the bottom correspond to the variant vulnerability of the variants. The bars along the right side, from top to bottom, describe the drug applicability the seven drugs analyzed in this study. Dashed lines correspond to the TEM-1 growth rate in the putative drug environment.

The rank order of the alleles with respect to variant vulnerability.

An allele with a high drug applicability is most susceptible to the collection of drugs in a panel (seven β-lactamase drugs and drug combinations in this study). MEGN (0000) is the genotype known as the TEM-1 variant of β-lactamase. LKSD (1111) is the genotype know as the TEM-50 variant of β-lactamase.

The variant vulnerability of the 16 allelic variants do not correlate with that of their one-step mutational neighbors.

(A) The variant vulnerability values for the 16-allelic variants as a function of the number of mutations away (hamming distance) from TEM-1 (MEGN). (B) The variant vulnerability values of all 16 allelic variants (x-axis) against the average variant vulnerability values of one-step neighbors (each allelic variant has four such neighbors). The analysis demonstrates no correlation, suggesting that variant vulnerability values are distributed nonlinearly across the fitness landscape (linear regression R2 = 0.01, P = 0.69).

The rank order of the seven drugs with respect to their drug applicability.

A drug with a high drug applicability is, on average, highly effective across the range of allelic variants in a set (in this study, a combinatorial set of four mutations that compose the TEM-50 variant of β-lactamase in this study). We emphasize that the findings in this study do not apply to clinical settings nor are based on clinical data.

Environmental epistasis underlies the drug-allele interactions that drive the variant vulnerability and drug applicability.

Effect on growth (in standard deviations of the wild-type control values), estimated by LASSO regression, for individual loci and their interactions. [A] corresponds to M69L, [B] to E104K, [C] to G238S, and [D] to N276D. As in a mutation effect reaction norm (Ogbunugafor 2022), the information describes how the effect of mutations changes across drug environments. This analysis is akin to a large deconstruction of the SNP x SNP x Environment (G x G x E) interactions, also known as environmental epistasis [26].