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The Visualization of Biofilms in Chronic Diabetic Foot Wounds Using Routine Diagnostic Microscopy Methods

Diabetic foot wounds are commonly colonised by taxonomically diverse microbial communities and may additionally be infected with specific pathogens. Since biofilms are demonstrably less susceptible to antimicrobial agents than are planktonic bacteria, and may be present in chronic wounds, there is i...

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Detalles Bibliográficos
Autores principales: Oates, Angela, Bowling, Frank L., Boulton, Andrew J. M., Bowler, Philip G., Metcalf, Daniel G., McBain, Andrew J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4009286/
https://www.ncbi.nlm.nih.gov/pubmed/24839608
http://dx.doi.org/10.1155/2014/153586
Descripción
Sumario:Diabetic foot wounds are commonly colonised by taxonomically diverse microbial communities and may additionally be infected with specific pathogens. Since biofilms are demonstrably less susceptible to antimicrobial agents than are planktonic bacteria, and may be present in chronic wounds, there is increasing interest in their aetiological role. In the current investigation, the presence of structured microbial assemblages in chronic diabetic foot wounds is demonstrated using several visualization methods. Debridement samples, collected from the foot wounds of diabetic patients, were histologically sectioned and examined using bright-field, fluorescence, and environmental scanning electron microscopy and assessed by quantitative differential viable counting. All samples (n = 26) harboured bioburdens in excess of 5 log(10) CFU/g. Microcolonies were identified in 4/4 samples by all three microscopy methods, although bright-field and fluorescence microscopy were more effective at highlighting putative biofilm morphology than ESEM. Results in this pilot study indicate that bacterial microcolonies and putative biofilm matrix can be visualized in chronic wounds using florescence microscopy and ESEM, but also using the simple Gram stain.