Bioinformatics (Oxford, England) · 2010
Spatial quantification and classification of skin response following perturbation using organotypic skin cultures.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Pommerencke Thora, Westphal Kathi, Ernst Claudia, Safferling Kai, Dickhaus Hartmut, Steinberg Thorsten, Tomakidi Pascal, Grabe Niels
Аннотация
MOTIVATION: For a mechanistic understanding of skin and its response to an induced perturbation, systems biology is gaining increasing attention. Unfortunately, quantitative and spatial expression data for skin, like for most other tissues, are almost not available.
RESULTS: Integrating organotypic skin cultures, whole-slide scanning and subsequent image processing provides bioinformatics with a novel source of spatial expression data. We here used this approach to quantitatively describe the effect of treating organotypic skin cultures with sodium dodecyl sulphate in a non-corrosive concentration. We first measured the differentiation-related spatial expression gradient of Heat-Shock-Protein 27 in a time series of up to 24 h. Secondly, a multi-dimensional tissue classifier for predicting skin irritation was developed based on abstract features of these profiles. We obtained a high specificity of 0.94 and a sensitivity of 0.92 compared with manual classification. Our results demonstrate that the integration of tissue cultures, whole-slide scanning and image processing is well suited for both the standardized data acquisition for systems biological tissue models and a highly robust classification of tissue responses.
RESULTS: Integrating organotypic skin cultures, whole-slide scanning and subsequent image processing provides bioinformatics with a novel source of spatial expression data. We here used this approach to quantitatively describe the effect of treating organotypic skin cultures with sodium dodecyl sulphate in a non-corrosive concentration. We first measured the differentiation-related spatial expression gradient of Heat-Shock-Protein 27 in a time series of up to 24 h. Secondly, a multi-dimensional tissue classifier for predicting skin irritation was developed based on abstract features of these profiles. We obtained a high specificity of 0.94 and a sensitivity of 0.92 compared with manual classification. Our results demonstrate that the integration of tissue cultures, whole-slide scanning and image processing is well suited for both the standardized data acquisition for systems biological tissue models and a highly robust classification of tissue responses.