Development of a new delayed healing model of an open skin wound and effects of M-1011G(ointment gauze containing 5% lysozyme hydrochloride) on the model.

Tanaka, Hirokazu; Kitoh, Yasuhiko; Kitabayashi, Noriko; Matsumura, Yumi; Okayachi, Hiroshi; Nakatsuji, Yoko; Tanaka, Kouji; Kubota, Katsuaki; Namba, Kazuhiko; Takemura, Koen

doi:10.1254/fpj.104.121

Cited by 2 publications

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“…Antimicrobial properties of peptidoglycan hydrolase (such as lysozyme) have been known since several decades [ 20 ]. The efficacy of lysozyme has been shown for skin treatment and in the infections of mucus membranes and is used as an ingredient in wound healing ointments [ 21 , 22 ]. Bacteriophage endolysin PlyC in an aerosolized form was active against pathogenic Streptococcus equi and is considered as the first narrow-spectrum disinfectant against the bacterial strain [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

Prediction of peptidoglycan hydrolases- a new class of antibacterial proteins

et al. 2016

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BackgroundThe efficacy of antibiotics against bacterial infections is decreasing due to the development of resistance in bacteria, and thus, there is a need to search for potential alternatives to antibiotics. In this scenario, peptidoglycan hydrolases can be used as alternate antibacterial agents due to their unique property of cleaving peptidoglycan cell wall present in both gram-positive and gram-negative bacteria. Along with a role in maintaining overall peptidoglycan turnover in a cell and in daughter cell separation, peptidoglycan hydrolases also play crucial role in bacterial pathophysiology requiring development of a computational tool for the identification and classification of novel peptidoglycan hydrolases from genomic and metagenomic data.ResultsIn this study, the known peptidoglycan hydrolases were divided into multiple classes based on their site of action and were used for the development of a computational tool ‘HyPe’ for identification and classification of novel peptidoglycan hydrolases from genomic and metagenomic data. Various classification models were developed using amino acid and dipeptide composition features by training and optimization of Random Forest and Support Vector Machines. Random Forest multiclass model was selected for the development of HyPe tool as it showed up to 71.12 % sensitivity, 99.98 % specificity, 99.55 % accuracy and 0.80 MCC in four different classes of peptidoglycan hydrolases. The tool was validated on 24 independent genomic datasets and showed up to 100 % sensitivity and 0.94 MCC. The ability of HyPe to identify novel peptidoglycan hydrolases was also demonstrated on 24 metagenomic datasets.ConclusionsThe present tool helps in the identification and classification of novel peptidoglycan hydrolases from complete genomic or metagenomic ORFs. To our knowledge, this is the only tool available for the prediction of peptidoglycan hydrolases from genomic and metagenomic data.Availability: http://metagenomics.iiserb.ac.in/hype/ and http://metabiosys.iiserb.ac.in/hype/.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2753-8) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Prediction of peptidoglycan hydrolases- a new class of antibacterial proteins

et al. 2016

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“…These models include wounds in diabetic mice, 25,26 ulcers created by injection of a chemical agent (sodium tetradecyl sulfate) in guinea pigs, 27 and by application of pressure on dog limbs. 28 Wounds inflicted in rats after the induction of malnutrition 29 or steroid impairment 223 224 BERNATCHEZ ET AL, have also been used . 30,3 'Additionally, radiation also has been used to delay healing in rat full-thickness skin incisions.…”

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Histological characterization of a delayed wound healing model in pig

Bernatchez

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Grussing

et al. 1998

Wound Repair Regeneration

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Chronic wounds, such as venous ulcers and pressure ulcers, frequently remain unresponsive to currently available treatments. Several animal models of wound healing have been published, including models of impaired healing developed to mimic the clinical condition of chronic wounds better. We used a delayed wound healing model in the pig that uses irradiation of the skin prior to creation of the surgical wounds and characterized it histologically. Radiation was used on one side of the back prior to making four full-thickness wounds on each side. Clinical observations were performed to record granulation tissue, reepithelialization, and wound area as a function of time. Histology data were obtained at 1, 2, 3, and 4 weeks, and slides were stained with hematoxylin and eosin for general observations. Immunohistochemistry was performed using laminin as a marker for blood vessels, and the number, size, and circularity of blood vessels found in the granulation tissue were measured. Our results show that this model causes a delay in wound healing that is mostly apparent between days 7 and 15. Granulation tissue took more time to form and fill the wounds on the irradiated side, and blood vessels were slower to develop. Blood vessels were larger and more irregular in shape on the irradiated side than on the control side. After 2 weeks, healing resumed, indicating that the induced damage was not irreversible. These results suggest that this model can be used to test the effects of therapeutic approaches intended to treat chronic wounds.

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Development of a new delayed healing model of an open skin wound and effects of M-1011G(ointment gauze containing 5% lysozyme hydrochloride) on the model.

Cited by 2 publications

References 2 publications

Prediction of peptidoglycan hydrolases- a new class of antibacterial proteins

Prediction of peptidoglycan hydrolases- a new class of antibacterial proteins

Histological characterization of a delayed wound healing model in pig

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