Science AdvancesSynthetic BiologyPeer-reviewed journal article
Exploring Antibiotic Resistance in Diverse Homologs of the Dihydrofolate Reductase Protein Family through Broad Mutational Scanning
Karl J. RomanowicziD, Carmen ResnickiD, Samuel R. HintoniD, Calin PlesaiD
Abstract
Current antibiotic resistance studies often focus on individual protein variants, neglecting broader protein family dynamics. Dihydrofolate reductase (DHFR), a key antibiotic target, has been extensively studied using deep mutational scanning, yet resistance mechanisms across this diverse protein family remain poorly understood. Using DropSynth, a scalable gene synthesis platform, we designed a library of 1,536 synthetic DHFR homologs representing 778 species of bacteria, archaea, and viruses, including clinically relevant pathogens. A multiplexed in vivo assay tested their ability to restore metabolic function and confer trimethoprim resistance in an E. coli {Delta}folA strain. Over half of the synthetic homologs rescued the phenotype without supplementation, and mutants with up to five amino acid substitutions increased the rescue rate to 90%, highlighting DHFRs evolutionary resilience. Broad Mutational Scanning (BMS) of homologs and 100,000 mutants provided critical insights into DHFRs fitness landscape and resistance pathways, representing the most extensive analysis of homolog complementation and inhibitor tolerance to date and advancing our understanding of antibiotic resistance mechanisms. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/634126v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@165b786org.highwire.dtl.DTLVardef@f3cc77org.highwire.dtl.DTLVardef@1f4b2c3org.highwire.dtl.DTLVardef@432a6_HPS_FORMAT_FIGEXP M_FIG C_FIG TeaserDropSynth technology enables scalable and cost-effective exploration of antibiotic resistance across the DHFR protein family.
- organism: bacteria (other)
- organism: virus
- assay: protein sequence
- research focus: drug response / drug discovery
- research focus: variant effect prediction
- approach: experimental assay
- Citations
- 10
- FWCI
- 2.79
- Field percentile
- top 9%
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