Supporting data for: Low-cost anti-mycobacterial drug discovery using engineered E. coli

Supporting data for: Low-cost anti-mycobacterial drug discovery using engineered E. col

This dataset pertains to our work developing TESEC Mtb ALR, a genetically engineered strain of E. coli expressing the enzyme ALR derived from Mtb. We used the TESEC Mtb ALR strain in a high-throughput drug screen and identified benazepril as targeted inhibitor of the ALR enzyme. We then performed additional experiments to characterize the activity of benazepril against E. coli, Mtb and purified enzymes. Finally, we tested the extensibility of the platform by constructing and screening against similar strains for additional targets: Asd, CysH, DapB, and TrpD.

These files include growth measurements, biochemical assays and other forms of biological data. They are packaged together with scripts used to analyze the data and present them in figures. Our goal in creating this archive was to present our complete analysis pipeline in the spirit of open science. It is not intended to be a stand-alone resource. Consult the associated manuscript for protocols, units of measurement and other essential technical context.

Our scripts were written for Python 3.8. The raw data is presented as human-readable .csv files intended to be imported as Pandas DataFrames. Some data is also packaged as Python dictionaries saved with the Pickle package.