Methods in molecular biology
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Blindness is one of the most devastating conditions affecting the quality of life. Hereditary degenerative diseases, such as retinitis pigmentosa, are characterized by the progressive loss of photoreceptors, leading to complete blindness. No treatment is known, the current state-of-the-art of restoring vision are implanted electrode arrays. ⋯ Successful treatment strategies have to take into account this diversity, as only the existing retinal hardware can serve as substrate for optogenetic intervention. The goal is to salvage the retinal ruins and to revert the leftover tissue into a functional visual sensor that operates as optimally as possible. Here, we discuss three different successful approaches that have been applied to degenerated mouse retina.
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Stem cells are envisaged to be integral components of multicellular systems engineered for therapeutic applications. The reprogramming of somatic cells to induced pluripotent stem cells (iPSCs) via recombinant expression of a limited number of transcription factors, which was first achieved by Yamanaka and colleagues in 2007, heralded a major breakthrough in the stem cell field. Since then, there has been rapid progress in the field of iPSC generation, including the identification of various small molecules that can enhance reprogramming efficiency and reduce the number of different transcription factors required for reprogramming. ⋯ The use of recombinant cell-penetrating peptides and direct transfection of synthetic mRNA encoding appropriate transcription factors have both been shown to successfully reprogram somatic cells to iPSCs. It has also been shown more recently that the direct transfection of certain miRNA species can reprogram somatic cells to pluripotency without the need for any of the transcription factors commonly utilized for iPSC generation. This chapter describes protocols for iPSC generation with these new techniques, which would obviate the use of recombinant DNA and viral vectors in cellular reprogramming, thus avoiding permanent genetic modification to the reprogrammed cells.
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Genome sequencing and systems biology are revolutionizing life sciences. Proteomics emerged as a fundamental technique of this novel research area as it is the basis for gene function analysis and modeling of dynamic protein networks. Here a complete proteomics platform suited for functional genomics and systems biology is presented. ⋯ Moreover, the presented platform can also be utilized to integrate metabolomics and transcriptomics data for the analysis of metabolite-protein-transcript correlations and time course analysis using COVAIN. Examples for the integration of MAPA and MASS WESTERN data, proteogenomic and metabolic modeling approaches for functional genomics, phosphoproteomics by integration of MOAC (metal-oxide affinity chromatography) with MAPA, and the integration of metabolomics, transcriptomics, proteomics, and physiological data using this platform are presented. All software and step-by-step tutorials for data processing and data mining can be downloaded from http://www.univie.ac.at/mosys/software.html.
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Chondroitin sulphate proteoglycans (CSPGs) are one of the major families of inhibitory extracellular matrix molecules in the central nervous system. The expression of various CSPGs is strong during early nervous system development; however, it is downregulated during maturation and up-regulated again after nervous system injury. In vivo injection of an enzyme called chondroitinase ABC, which removes the inhibitory chondroitin sulphate chains on the CSPGs, in the injured area promotes both the regeneration and plasticity of the neurons. Here, we describe the method of in vivo injection of the chondroitinase ABC into the cortex of adult rat brain and the histochemical method to assess the successfulness of the digestion.
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As the field of proteomics shifts from qualitative identification of protein "subfractions" to quantitative comparison of proteins from complex biological samples, it is apparent that the number of approaches for quantitation can be daunting for the result-oriented biologist. There have been many recent reviews on quantitative proteomic approaches, discussing the strengths and limitations of each. ⋯ Here we present a detailed bioinformatics workflow for one of the simplest, most pervasive quantitative approach-spectral counting. The informatics and statistical workflow detailed here includes newly available freeware, such as SePro and PatternLab which post-process data according to false discovery rate parameters, and statistically model the data to detect differences and trends.