Sequence-function mapping of proline-rich antimicrobial peptides.

Jonathan Collins, Adam McConnell, Zachary D Schmitz,Benjamin J Hackel

bioRxiv : the preprint server for biology(2024)

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摘要
Antimicrobial peptides (AMPs) are essential elements of natural cellular combat and candidates as antibiotic therapy. Elevated function may be needed for robust physiological performance. Yet, both pure protein design and combinatorial library discovery are hindered by the complexity of antimicrobial activity. We applied a recently developed high-throughput technique, sequence-activity mapping of AMPs via depletion (SAMP-Dep), to proline-rich AMPs. Robust self-inhibition was achieved for metalnikowin 1 (Met) and apidaecin 1b (Api). SAMP-Dep exhibited high reproducibility with correlation coefficients 0.90 and 0.92, for Met and Api, respectively, between replicates and 0.99 and 0.96 for synonymous genetic variants. Sequence-activity maps were obtained via characterization of 26,000 and 34,000 mutants of Met and Api, respectively. Both AMPs exhibit similar mutational profiles including beneficial mutations at one terminus, the C-terminus for Met and N-terminus for Api, which is consistent with their opposite binding orientations in the ribosome. While Met and Api reside with the family of proline-rich AMPs, different proline sites exhibit substantially different mutational tolerance. Within the PRP motif, proline mutation eliminates activity, whereas non-PRP prolines readily tolerate mutation. Homologous mutations are more tolerated, particularly at alternating sites on one 'face' of the peptide. Important and consistent epistasis was observed following the PRP domain within the segment that extends into the ribosomal exit tunnel for both peptides. Variants identified from the SAMP-Dep platform were produced and exposed toward Gram-negative species exogenously, showing either increased potency or specificity for strains tested. In addition to mapping sequence-activity space for fundamental insight and therapeutic engineering, the results advance the robustness of the SAMP-Dep platform for activity characterization.
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