Efficacy of Antimicrobial Peptide DP7, Designed by Machine-Learning Method, Against Methicillin-Resistant Staphylococcus aureus

Abstract

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Antimicrobial peptides (AMPs) provide a promising strategy against infections involving multidrug-resistant pathogens. In previous studies, we designed a short 12 amino acid AMP DP7, using a machine-learning method based on an amino acid activity contribution matrix. DP7 shows broad-spectrum antimicrobial activities both in vitro and in vivo. Here, we aim to investigate the efficacy of DP7 against multidrug resistant Staphylococcus aureus (S. aureus) and reveal the potential mechanisms. First, by measuring the killing kinetics of DP7 against S. aureus and comparing these results with antibiotics with different antimicrobial mechanisms, we hypothesize that DP7, in addition to its known ability to induce cell wall cation damage, can also exert a full killing effect. With FITC-conjugated or biotin-labeled DP7, we tracked DP7’s attachment, membrane permeation and subsequent intracellular distribution in S. aureus. These results indicated that the possible targets of DP7 were within the bacterial cells. Transcriptome sequencing of S. aureus exposed to DP7 identified 333 differentially expressed genes (DEGs) influenced by DP7, involving nucleic acid metabolism, amino acid biosynthesis, cell wall destruction and pathogenesis, respectively, indicating the comprehensive killing efficacy of DP7. In addition, the genome sequencing results of the induced DP7 resistant strain S. aureus DP7-R revealed two-point mutations in the mprF and guaA gene. Moreover, in a murine model for MRSA blood stream infection, intravenously treating mice with DP7 showed a good protective effect on mice. In conclusion, DP7 is an effective bactericide for S. aureus, which deserves further study for clinical application and drug development.

Keywords

• antimicrobial peptides DP7
• MRSA
• antimicrobial efficacy
• blood stream infection
• drug development