Proteomic analysis from skin swabs reveals a new set of proteins identifying skin impairment in atopic dermatitis.

Atopic Dermatitis (AD) is a common inflammatory skin disease characterized by skin and systemic inflammation, and barrier dysfunction. Herein, we investigate the proteomic profile of AD skin barrier to identify a unique signature with an easy-performed sampling approach. We enrolled 8 moderate-to-severe AD patients and 8 age- and gender-matched healthy controls. Swabs were obtained from non-lesional skin of retroauricular area and antecubital fold. Peptide mixtures obtained through protein precipitation and in-solution digestion were analysed using NanoLC-MS/MS. Label-free quantification and statistical analysis were conducted in MaxQuant and Perseus. Bioinformatics analysis was performed using Gene Ontology and STRING. We identified 908 proteins and 35 differentially expressed proteins were selected (fold change 2, FDR < 0.05). Particularly, AD skin showed downregulation of skin hydration factors, structural and epidermal proteins, abnormalities in protease-proteasome complex and lipid metabolism profile. Imbalance of antioxidant and inflammatory processes, along with TDRD15 upregulation was also observed. Our result showed partial overlap with skin biopsy/tape-strips studies, showing the reliability of our sampling approach which could be an easier method of detection of hallmark barrier proteins in AD. Furthermore, we displayed a new differentially expressed set of proteins, not yet explored in AD which can have a potential role in AD pathomechanisms.

PyElph - a software tool for gel images analysis and phylogenetics.

BACKGROUND: This paper presents PyElph, a software tool which automatically extracts data from gel images, computes the molecular weights of the analyzed molecules or fragments, compares DNA patterns which result from experiments with molecular genetic markers and, also, generates phylogenetic trees computed by five clustering methods, using the information extracted from the analyzed gel image. The software can be successfully used for population genetics, phylogenetics, taxonomic studies and other applications which require gel image analysis. Researchers and students working in molecular biology and genetics would benefit greatly from the proposed software because it is free, open source, easy to use, has a friendly Graphical User Interface and does not depend on specific image acquisition devices like other commercial programs with similar functionalities do. RESULTS: PyElph software tool is entirely implemented in Python which is a very popular programming language among the bioinformatics community. It provides a very friendly Graphical User Interface which was designed in six steps that gradually lead to the results. The user is guided through the following steps: image loading and preparation, lane detection, band detection, molecular weights computation based on a molecular weight marker, band matching and finally, the computation and visualization of phylogenetic trees. A strong point of the software is the visualization component for the processed data. The Graphical User Interface provides operations for image manipulation and highlights lanes, bands and band matching in the analyzed gel image. All the data and images generated in each step can be saved. The software has been tested on several DNA patterns obtained from experiments with different genetic markers. Examples of genetic markers which can be analyzed using PyElph are RFLP (Restriction Fragment Length Polymorphism), AFLP (Amplified Fragment Length Polymorphism), RAPD (Random Amplification of Polymorphic DNA) and STR (Short Tandem Repeat). The similarity between the DNA sequences is computed and used to generate phylogenetic trees which are very useful for population genetics studies and taxonomic classification. CONCLUSIONS: PyElph decreases the effort and time spent processing data from gel images by providing an automatic step-by-step gel image analysis system with a friendly Graphical User Interface. The proposed free software tool is suitable for researchers and students which do not have access to expensive commercial software and image acquisition devices.