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An optimised method for the proteomic profiling of full thickness human skin.
Bliss, Emily; Heywood, Wendy E; Benatti, Malika; Sebire, Neil J; Mills, Kevin.
Afiliación
  • Bliss E; Centre for Translational Omics, UCL Institute of Child Health, 30 Guilford Street, London, WC1N 1EH UK.
  • Heywood WE; Centre for Translational Omics, UCL Institute of Child Health, 30 Guilford Street, London, WC1N 1EH UK.
  • Benatti M; Histopathology Department, Great Ormond Street Hospital, London, WC1N 3JH UK.
  • Sebire NJ; Histopathology Department, Great Ormond Street Hospital, London, WC1N 3JH UK.
  • Mills K; Centre for Translational Omics, UCL Institute of Child Health, 30 Guilford Street, London, WC1N 1EH UK.
Biol Proced Online ; 18: 15, 2016.
Article en En | MEDLINE | ID: mdl-27445641
BACKGROUND: The skin is the largest organ of the human body and is the first line barrier defence against trauma, microbial infiltration and radiation. Skin diseases can be a result of multi-systemic disease or an isolated condition. Due to its proteolysis resistant properties there are relatively few human skin proteomic datasets published compared with other human organs or body fluids. Skin is a challenging tissue to analyse using traditional proteomic techniques due to its high lipid content, insolubility and extensive cross-linking of proteins. This can complicate the isolation and digestion of proteins for analysis using mass spectrometry techniques. RESULTS: We have optimised a sample preparation procedure to improve solubilisation and mass spectral compatibility of full thickness skin samples. Using this technique, we were able to obtain data for the proteome profile of full thickness human skin using on-line two-dimensional liquid chromatography, followed by ultra-high definition label-free mass spectrometry analysis (UDMS(E)). We were able to identify in excess of 2000 proteins from a full thickness skin sample. CONCLUSIONS: The adoption of on-line fractionation and optimised acquisition protocols utilising ion mobility separation (IMS) technology has significantly increased the scope for protein identifications ten-fold.
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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Biol Proced Online Año: 2016 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Biol Proced Online Año: 2016 Tipo del documento: Article