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Histone H5 is a potent Antimicrobial Agent and a template for novel Antimicrobial Peptides.

ABSTRACT: Modern medicine is challenged continuously by the increasing prevalence of antibiotic resistant bacteria. Cationic antimicrobial peptides and their derivatives are interesting potential alternatives to antibiotics due to their rapid action, broad-spectrum of antimicrobial activity and limited emergence of bacterial resistance. This study reports the novel antimicrobial properties of histone H5, purified from chicken erythrocytes, and histone H5-derived synthetic peptides. Broth microdilution assays revealed that histone H5 has potent broad-spectrum antimicrobial activity against Gram-positive and Gram-negative planktonic bacteria (MIC range: 1.9?±?1.8 to 4.9?±?1.5?µg/mL), including vancomycin-resistant Enterococcus (VRE) and methicillin-resistant Staphylococcus aureus (MRSA). Moreover, histone H5 displayed anti-biofilm activity against established Listeria monocytogenes and Pseudomonas aeruginosa biofilms. Scanning electron microscopy demonstrated bacterial membrane damage after histone H5 treatment, while a hemolytic assay revealed that histone H5 is non-toxic towards mammalian erythrocytes, even at a concentration of 1?mg/mL. Although the predicted H5-derived antimicrobial peptides tested in this study were located within the antimicrobial domain of histone H5, their synthetic versions did not possess more potent antimicrobial activity than the full length protein. Overall, this study demonstrates that histone H5 is a potent antimicrobial and therefore a promising template for the development of novel histone H5-derived antimicrobial peptides.

SUBMITTER: Jodoin J

PROVIDER: S-EPMC5799255 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Histone H5 is a potent Antimicrobial Agent and a template for novel Antimicrobial Peptides.

Jodoin Joelle J Hincke Maxwell T MT

Scientific reports 20180205 1

Modern medicine is challenged continuously by the increasing prevalence of antibiotic resistant bacteria. Cationic antimicrobial peptides and their derivatives are interesting potential alternatives to antibiotics due to their rapid action, broad-spectrum of antimicrobial activity and limited emergence of bacterial resistance. This study reports the novel antimicrobial properties of histone H5, purified from chicken erythrocytes, and histone H5-derived synthetic peptides. Broth microdilution ass ...[more]

PMID: 29402952

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Project description:BackgroundCurrent methods in machine learning provide approaches for solving challenging, multiple constraint design problems. While deep learning and related neural networking methods have state-of-the-art performance, their vulnerability in decision making processes leading to irrational outcomes is a major concern for their implementation. With the rising antibiotic resistance, antimicrobial peptides (AMPs) have increasingly gained attention as novel therapeutic agents. This challenging design problem requires peptides which meet the multiple constraints of limiting drug-resistance in bacteria, preventing secondary infections from imbalanced microbial flora, and avoiding immune system suppression. AMPs offer a promising, bioinspired design space to targeting antimicrobial activity, but their versatility also requires the curated selection from a combinatorial sequence space. This space is too large for brute-force methods or currently known rational design approaches outside of machine learning. While there has been progress in using the design space to more effectively target AMP activity, a widely applicable approach has been elusive. The lack of transparency in machine learning has limited the advancement of scientific knowledge of how AMPs are related among each other, and the lack of general applicability for fully rational approaches has limited a broader understanding of the design space.MethodsHere we combined an evolutionary method with rough set theory, a transparent machine learning approach, for designing antimicrobial peptides (AMPs). Our method achieves the customization of AMPs using supervised learning boundaries. Our system employs in vitro bacterial assays to measure fitness, codon-representation of peptides to gain flexibility of sequence selection in DNA-space with a genetic algorithm and machine learning to further accelerate the process.ResultsWe use supervised machine learning and a genetic algorithm to find a peptide active against S. epidermidis, a common bacterial strain for implant infections, with an improved aggregation propensity average for an improved ease of synthesis.ConclusionsOur results demonstrate that AMP design can be customized to maintain activity and simplify production. To our knowledge, this is the first time when codon-based genetic algorithms combined with rough set theory methods is used for computational search on peptide sequences.

Dataset Information

Histone H5 is a potent Antimicrobial Agent and a template for novel Antimicrobial Peptides.

Publications

Histone H5 is a potent Antimicrobial Agent and a template for novel Antimicrobial Peptides.

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