Search

Objective SSc is a rheumatic autoimmune disease affecting roughly 20 000 people worldwide and characterized by excessive collagen accumulation in the skin and internal organs. Despite the high morbidity and mortality associated with SSc, there are no approved disease-modifying agents. Our objective in this study was to explore transcriptomic and model-based drug discovery approaches for SSc. Methods In this study, we explored the molecular basis for SSc pathogenesis in a well-studied mouse model of scleroderma. We profiled the skin and lung transcriptomes of mice at multiple timepoints, analysing the differential gene expression that underscores the development and resolution of bleomycin-induced fibrosis. Results We observed shared expression signatures of upregulation and downregulation in fibrotic skin and lung tissue, and observed significant upregulation of key pro-fibrotic genes including GDF15, Saa3, Cxcl10, Spp1 and Timp1. To identify changes in gene expression in responses to anti-fibrotic therapy, we assessed the effect of TGF-β pathway inhibition via oral ALK5 (TGF-β receptor I) inhibitor SB525334 and observed a time-lagged response in the lung relative to skin. We also implemented a machine learning algorithm that showed promise at predicting lung function using transcriptome data from both skin and lung biopsies. Conclusion This study provides the most comprehensive look at the gene expression dynamics of an animal model of SSc to date, provides a rich dataset for future comparative fibrotic disease research, and helps refine our understanding of pathways at work during SSc pathogenesis and intervention. [ABSTRACT FROM AUTHOR]

Abstract Background Genome-wide screening in human and mouse cells using RNA interference and open reading frame over-expression libraries is rapidly becoming a viable experimental approach for many research labs. There are a variety of gene expression modulation libraries commercially available, however, detailed and validated protocols as well as the reagents necessary for deconvolving genome-scale gene screens using these libraries are lacking. As a solution, we designed a comprehensive platform for highly multiplexed functional genetic screens in human, mouse and yeast cells using popular, commercially available gene modulation libraries. The Gene Modulation Array Platform (GMAP) is a single microarray-based detection solution for deconvolution of loss and gain-of-function pooled screens. Results Experiments with specially constructed lentiviral-based plasmid pools containing ~78,000 shRNAs demonstrated that the GMAP is capable of deconvolving genome-wide shRNA "dropout" screens. Further experiments with a larger, ~90,000 shRNA pool demonstrate that equivalent results are obtained from plasmid pools and from genomic DNA derived from lentivirus infected cells. Parallel testing of large shRNA pools using GMAP and next-generation sequencing methods revealed that the two methods provide valid and complementary approaches to deconvolution of genome-wide shRNA screens. Additional experiments demonstrated that GMAP is equivalent to similar microarray-based products when used for deconvolution of open reading frame over-expression screens. Conclusion Herein, we demonstrate four major applications for the GMAP resource, including deconvolution of pooled RNAi screens in cells with at least 90,000 distinct shRNAs. We also provide detailed methodologies for pooled shRNA screen readout using GMAP and compare next-generation sequencing to GMAP (i.e. microarray) based deconvolution methods.

Abstract Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density), but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO) collection used for screens of pooled yeast (Saccharomyces cerevisiae) deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density.

The translation of novel pulmonary fibrosis therapies from preclinical models into the clinic represents a major challenge demonstrated by the high attrition rate of compounds that showed efficacy in preclinical models but demonstrated no significant beneficial effects in clinical trials. A precision-cut lung tissue slice (PCLS) contains all major cell types of the lung and preserves the original cell-cell and cell-matrix contacts. It represents a promising ex vivo model to study pulmonary fibrosis. In this study, using RNA sequencing, we demonstrated that transforming growth factor-β1 (TGFβ1) induced robust fibrotic responses in the rat PCLS model, as it changed the expression of genes functionally related to extracellular matrix remodeling, cell adhesion, epithelial-to-mesenchymal transition, and various immune responses. Nintedanib, pirfenidone, and sorafenib each reversed a subset of genes modulated by TGFβ1, and of those genes we identified 229 whose expression was reversed by all three drugs. These genes define a molecular signature characterizing many aspects of pulmonary fibrosis pathology and its attenuation in the rat PCLS fibrosis model. A panel of 12 genes and three secreted biomarkers, including procollagen I, hyaluronic acid, and WNT1-inducible signaling pathway protein 1 were validated as efficacy end points for the evaluation of antifibrotic activity of experimental compounds. Finally, we showed that blockade of αV-integrins suppressed TGFβ1-induced fibrotic responses in the rat PCLS fibrosis model. Overall, our results suggest that the TGFβ1-induced rat PCLS fibrosis model may represent a valuable system for target validation and to determine the efficacy of experimental compounds. [ABSTRACT FROM AUTHOR]

Precision- cut liver tissue slice (PCLS) contains all major cell types of the liver parenchyma and preserves the original cell-cell and cell-matrix contacts. It represents a promising ex vivo model to study liver fibrosis and test the antifibrotic effect of experimental compounds in a physiological environment. In this study using RNA sequencing, we demonstrated that various pathways functionally related to fibrotic mechanisms were dysregulated in PCLSs derived from rats subjected to bile duct ligation. The activin receptor-like kinase-5 (Alk5) inhibitor SB525334, nintedanib, and sorafenib each reversed a subset of genes dysregulated in fibrotic PCLSs, and of those genes we identified 608 genes whose expression was reversed by all three compounds. These genes define a molecular signature characterizing many aspects of liver fibrosis pathology and its attenuation in the model. A panel of 12 genes and 4 secreted biomarkers including procollagen I, hyaluronic acid (HA), insulin-like growth factor binding protein 5 (IGFBP5), and WNT1-inducible signaling pathway protein 1 (WISP1) were further validated as efficacy end points for the evaluation of antifibrotic activity of experimental compounds. Finally, we showed that blockade of αV-integrins with a small molecule inhibitor attenuated the fibrotic phenotype in the model. Overall, our results suggest that the rat fibrotic PCLS model may represent a valuable system for target validation and determining the efficacy of experimental compounds. [ABSTRACT FROM AUTHOR]