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Qualitative and Quantitative Assays for Detection and Characterization of Protein Antimicrobials
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Deep Antimicrobial Activity and Stability Analysis Inform Lysin Sequence-Function Mapping.

Daniel T Tresnak1, Benjamin J Hackel1

  • 1Department of Chemical Engineering and Materials Science, University of Minnesota─Twin Cities, 421 Washington Avenue SE, Minneapolis, Minnesota55455, United States.

ACS Synthetic Biology
|January 4, 2023
PubMed
Summary
This summary is machine-generated.

Researchers developed a high-throughput assay to engineer antimicrobial proteins called lysins. This method rapidly screened thousands of variants, discovering a potent lysin with enhanced activity and stability to combat antibiotic resistance.

Keywords:
antimicrobial proteinlysinmutational scanningsequence−function mapping

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Area of Science:

  • Biochemistry
  • Microbiology
  • Protein Engineering

Background:

  • Antibiotic-resistant infections pose a significant global health threat.
  • Antimicrobial proteins, like lysins, show promise but require engineering for efficacy.
  • High-throughput methods are needed to characterize lysin function for discovery and design.

Purpose of the Study:

  • To develop a high-throughput platform for measuring lysin inhibitory activity and proteolytic stability.
  • To expand the understanding of the lysin sequence-function landscape.
  • To discover novel lysin variants with improved antimicrobial properties.

Main Methods:

  • Developed a depletion-based assay for library-scale measurement of lysin inhibitory activity.
  • Coupled activity assay with a high-throughput proteolytic stability assay.
  • Assessed activity and stability of approximately 5 × 10^4 lysin catalytic domain variants.

Main Results:

  • Discovered a lysin variant with 70% increased activity and 7.2°C higher thermal denaturation midpoint (stability).
  • Ridge regression analysis showed higher Hamming distance libraries improved pairwise models.
  • Coupled assays enabled better prediction of catalytically active lysins, with models achieving high Pearson's correlation coefficients for stability (0.87) and activity (0.61).

Conclusions:

  • The developed platform provides an efficient strategy for protein sequence-function landscape construction.
  • This approach significantly increases screening throughput for engineering lysins.
  • The study yielded promising lysin variants for further development against antibiotic-resistant bacteria.