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

Abstract

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.

A Novel Antimicrobial Peptide Sparamosin26–54 From the Mud Crab Scylla paramamosain Showing Potent Antifungal Activity Against Cryptococcus neoformans

“…The analysis of the localization of Sparamosin 26−54 in C. neoformans was carried out based on the previous report with slight modifications (Zhang et al, 2019). Briefly, C. neoformans cells were harvested in the logarithmic phase and washed with 10 mM sodium phosphate buffer (NaPB, pH 7.4).…”

A novel smaller β‐defensin‐derived peptide is active against multidrug‐resistant bacterial strains

“…Bacterial suspension, containing approximately 10 6 CFU/ml (adjusted by spectrophotometer to OD 600nm ) were diluted 1:100 in PBS1X and then incubated at 37°C with or without selected peptide at concentrations corresponding to 1, 2, and 4×MIC (as determined above). At baseline and after 1, 2, 3, and 5 h of incubation an aliquot of each sample was collected, serially diluted in PBS1X and seeded on BHI agar 31,32 33,34 .…”

“…At baseline and after 1, 2, 3, and 5 h of incubation an aliquot of each sample was collected, serially diluted in PBS1X and seeded on BHI agar. 31,32 The plates were incubated for 24-18 h at 37°C and viable bacterial counts were performed by CFU method. 33,34 All data were expressed as the mean ± SD of three independent experiments.…”

Machine Learning in Antibacterial Drug Design

“…Wu et al used previous amino acid substitution data for antibacterial peptides and developed an amino acid activity contribution matrix ( Wu et al, 2014 ). Using this methodology, the group developed a 12-mer DP7 peptide with antibacterial properties against multiple strains ( Zhang et al, 2019 ). Similarly, Yoshida et al used a natural antibacterial peptide Temporin-Ali (FFPIVGKLLSGLL-NH2) and PSI BLAST to create a library of distantly related and functionally similar sequences, prepared the peptides, and evaluated their antibacterial activities in vitro on E. coli to construct a fitness matrix.…”