Development of antibacterial compounds that constrain evolutionary pathways to resistance

Antibiotic resistance is a worldwide challenge. A potential approach to block resistance is to simultaneously inhibit WT and known escape variants of the target bacterial protein. Here, we applied an integrated computational and experimental approach to discover compounds that inhibit both WT and trimethoprim (TMP) resistant mutants of E. coli dihydrofolate reductase (DHFR). We identified a novel compound (CD15-3) that inhibits WT DHFR and its TMP resistant variants L28R, P21L and A26T with IC50 50–75 µM against WT and TMP-resistant strains. Resistance to CD15-3 was dramatically delayed compared to TMP in in vitro evolution. Whole genome sequencing of CD15-3-resistant strains showed no mutations in the target folA locus. Rather, gene duplication of several efflux pumps gave rise to weak (about twofold increase in IC50) resistance against CD15-3. Altogether, our results demonstrate the promise of strategy to develop evolution drugs - compounds which constrain evolutionary escape routes in pathogens.


Sample-size estimation
 You should state whether an appropriate sample size was computed when the study was being designed  You should state the statistical method of sample size computation and any required assumptions  If no explicit power analysis was used, you should describe how you decided what sample (replicate) size (number) to use Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission:

Replicates
 You should report how often each experiment was performed  You should include a definition of biological versus technical replication  The data obtained should be provided and sufficient information should be provided to indicate the number of independent biological and/or technical replicates  If you encountered any outliers, you should describe how these were handled  Criteria for exclusion/inclusion of data should be clearly stated  High-throughput sequence data should be uploaded before submission, with a private link for reviewers provided (these are available from both GEO and ArrayExpress) Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Our study involved no clinical subject and hence the issue of sample size issues in trial statistics is not applicable (N/A). Replicates were decided from experience of the techniques/experiments performed and previously standardized methods. Statistical analyses are given in figure legend. Error bars in the datasets for activity plots in Figure 3 and growth rate plots in Figure 4, 6, 7, 8 are derived considering at least three independent readouts as replicates. Sample sizes for OD measurements of growth ranged from 10 4 to 10 10 bacterial cells per well. This is w.r.t established relationship between OD and cell numbers in the volume of a well in 96-well plates.
No outliers have been excluded in the analysis. Statistical reporting  Statistical analysis methods should be described and justified  Raw data should be presented in figures whenever informative to do so (typically when N per group is less than 10)  For each experiment, you should identify the statistical tests used, exact values of N, definitions of center, methods of multiple test correction, and dispersion and precision measures (e.g., mean, median, SD, SEM, confidence intervals; and, for the major substantive results, a measure of effect size (e.g., Pearson's r, Cohen's d)  Report exact p-values wherever possible alongside the summary statistics and 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05.
Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: (For large datasets, or papers with a very large number of statistical tests, you may upload a single table file with tests, Ns, etc., with reference to sections in the manuscript.)

Group allocation
 Indicate how samples were allocated into experimental groups (in the case of clinical studies, please specify allocation to treatment method); if randomization was used, please also state if restricted randomization was applied  Indicate if masking was used during group allocation, data collection and/or data analysis Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Additional data files ("source data")  We encourage you to upload relevant additional data files, such as numerical data that are represented as a graph in a figure, or as a summary table  Where provided, these should be in the most useful format, and they can be uploaded as "Source data" files linked to a main figure or table  Include model definition files including the full list of parameters used  Include code used for data analysis (e.g., R, MatLab) Experiments involving bacterial growth involved at least three biological replicates. As biological replicates we mean three independent starter culture derived from three randomly selected independent colonies in a plate. Further each biological replicate had at minimum three technical replicate sets in the experimental exhibits. Growth rate plots in Figures 4, 6, 7 and 8 shows mean +/-SD.
Method section mentions relevant statistical details used in the calculations. Growth experiments and enzyme activity (Figure 3) results show error bar based on the raw data derived from at least three replicates. Sample size distribution in the imaging experiments is mentioned in the methods section. Box and whisker plots (with mean and median) are provided too.
Not applicable. The current study does not involve any of the above mentioned points.
eLife Sciences Publications, Ltd is a limited liability non-profit non-stock corporation incorporated in the State of Delaware, USA, with company number 5030732, and is registered in the UK with company number FC030576 and branch number BR015634 at the address 1st Floor, 24 Hills Road, Cambridge CB2 1JP | August 2014 3  Avoid stating that data files are "available upon request" Please indicate the figures or tables for which source data files have been provided: None.