MOTIVATION: For systems biology of complex stratified epithelia like human epidermis, it will be of particular importance to reconstruct the spatiotemporal gene and protein networks regulating keratinocyte differentiation and homeostasis. RESULTS: Inside the epidermis, the differentiation state of individual keratinocytes is correlated with their respective distance from the connective tissue. We here present a novel method to profile this correlation for multiple epithelial protein biomarkers in the form of quantitative spatial profiles. Profiles were computed by applying image processing algorithms to histological sections stained with tri-color indirect immunofluorescence. From the quantitative spatial profiles, reflecting the spatiotemporal changes of protein expression during cellular differentiation, graphs of protein networks were reconstructed. CONCLUSION: Spatiotemporal networks can be used as a means for comparing and interpreting quantitative spatial protein expression profiles obtained from different tissue samples. In combination with automated microscopes, our new method supports the large-scale systems biological analysis of stratified epithelial tissues.
MOTIVATION: For systems biology of complex stratified epithelia like human epidermis, it will be of particular importance to reconstruct the spatiotemporal gene and protein networks regulating keratinocyte differentiation and homeostasis. RESULTS: Inside the epidermis, the differentiation state of individual keratinocytes is correlated with their respective distance from the connective tissue. We here present a novel method to profile this correlation for multiple epithelial protein biomarkers in the form of quantitative spatial profiles. Profiles were computed by applying image processing algorithms to histological sections stained with tri-color indirect immunofluorescence. From the quantitative spatial profiles, reflecting the spatiotemporal changes of protein expression during cellular differentiation, graphs of protein networks were reconstructed. CONCLUSION: Spatiotemporal networks can be used as a means for comparing and interpreting quantitative spatial protein expression profiles obtained from different tissue samples. In combination with automated microscopes, our new method supports the large-scale systems biological analysis of stratified epithelial tissues.
Authors: Aparna Bhaduri; Alexander Ungewickell; Lisa D Boxer; Vanessa Lopez-Pajares; Brian J Zarnegar; Paul A Khavari Journal: Dev Cell Date: 2015-11-23 Impact factor: 12.270
Authors: Joseph Cursons; Jerry Gao; Daniel G Hurley; Cristin G Print; P Rod Dunbar; Marc D Jacobs; Edmund J Crampin Journal: BMC Syst Biol Date: 2015-07-25