Abstract:A strategy is presented that allows a causal analysis of co-expressed genes, which may be subject to common regulatory influences. A state-of-the-art promoter analysis for potential transcription factor (TF) binding sites in combination with a knowledge-based analysis of the upstream pathway that control the activity of these TFs is shown to lead to hypothetical master regulators. This strategy was implemented as a workflow in a comprehensive bioinformatic software platform. We applied this workflow to gene se… Show more
“…Figure 4d shows a scatterplot of items of four different substance groups at their transformed coordinates according to the first two principal components. No clustering of substance groups was observed during PCA, which is a good basis for further downstream analyses [29]. Due to the good RNA quality, we were able to detect differentially expressed genes for all samples.Fig.…”
BackgroundFunctional 3D organ models such as precision-cut lung slices (PCLS) have recently captured the attention of biomedical research. To enable wider implementation in research and development, these new biologically relevant organ models are being constantly refined. A very important issue is to improve the preparation of high-quality RNA (ribonucleic acid) from PCLS for drug discovery and development of new therapies. Gene expression analysis at different levels is used as an important experimental readout. Genome-wide analysis using microarrays is mostly applied for biomarker selection in disease models or in comprehensive toxicological studies. Specific biomarker testing by reverse transcriptase quantitative polymerase chain reaction (RTqPCR) is often used in efficacy studies. Both applications require high-quality RNA as starting material for the generation of reliable data. Additionally, a small number of slices should be sufficient for satisfactory RNA isolation to allow as many experimental conditions as possible to be covered with a given tissue sample. Unfortunately, the vast amount of agarose in PCLS impedes RNA extraction according to the standard procedures.ResultsWe established an optimized protocol for RNA isolation from PCLS from humans, rats, mice, marmosets, and rhesus macaques based on the separation of lysis and precipitation steps and a magnetic-bead cleanup procedure. The resulting RNA is of high purity and possesses a high degree of integrity. There are no contaminations affecting RTqPCR efficiency or any enzymatic step in sample preparation for microarray analysis.ConclusionsIn summary, we isolated RNA from PCLS from different species that is well suited for RTqPCR and for microarray analysis as downstream applications.
“…Figure 4d shows a scatterplot of items of four different substance groups at their transformed coordinates according to the first two principal components. No clustering of substance groups was observed during PCA, which is a good basis for further downstream analyses [29]. Due to the good RNA quality, we were able to detect differentially expressed genes for all samples.Fig.…”
BackgroundFunctional 3D organ models such as precision-cut lung slices (PCLS) have recently captured the attention of biomedical research. To enable wider implementation in research and development, these new biologically relevant organ models are being constantly refined. A very important issue is to improve the preparation of high-quality RNA (ribonucleic acid) from PCLS for drug discovery and development of new therapies. Gene expression analysis at different levels is used as an important experimental readout. Genome-wide analysis using microarrays is mostly applied for biomarker selection in disease models or in comprehensive toxicological studies. Specific biomarker testing by reverse transcriptase quantitative polymerase chain reaction (RTqPCR) is often used in efficacy studies. Both applications require high-quality RNA as starting material for the generation of reliable data. Additionally, a small number of slices should be sufficient for satisfactory RNA isolation to allow as many experimental conditions as possible to be covered with a given tissue sample. Unfortunately, the vast amount of agarose in PCLS impedes RNA extraction according to the standard procedures.ResultsWe established an optimized protocol for RNA isolation from PCLS from humans, rats, mice, marmosets, and rhesus macaques based on the separation of lysis and precipitation steps and a magnetic-bead cleanup procedure. The resulting RNA is of high purity and possesses a high degree of integrity. There are no contaminations affecting RTqPCR efficiency or any enzymatic step in sample preparation for microarray analysis.ConclusionsIn summary, we isolated RNA from PCLS from different species that is well suited for RTqPCR and for microarray analysis as downstream applications.
“…Transcription regulatory feedback loops driven by NF-kappaB/RelA and cooperating transcription factors were inferred based on existing knowledge about signalling pathways involving NF-kappaB/RelA transcription factor binding motifs and ChIP-seq experiment data targeting NF-kappaB/RelA-bound sites in the human genome. The analyses were mainly conducted using the geneXplain platform (37).…”
Section: Methodsmentioning
confidence: 99%
“…The enrichment of binding sites in promoters of target genes associated with selected GO functional classes was analysed using the algorithms developed by Koschmann et al (37). A subset of 190 positional weight matrices for the 24 transcription factors identified through our feedback loop analysis was extracted from TRANSFAC(R), release 2018.3.…”
ObjectiveInflammatory bowel diseases cause significant morbidity and mortality. Aberrant NF-κB signalling is strongly associated with these conditions, and several established drugs influence the NF-κB signalling network to exert their effect. This study aimed to identify drugs which alter NF-κB signalling and may be repositioned for use in inflammatory bowel disease.DesignThe SysmedIBD consortium established a novel drug-repurposing pipeline based on a combination of in-silico drug discovery and biological assays targeted at demonstrating an impact on NF-kappaB signalling, and a murine model of IBD.ResultsThe drug discovery algorithm identified several drugs already established in IBD, including corticosteroids. The highest-ranked drug was the macrolide antibiotic Clarithromycin, which has previously been reported to have anti-inflammatory effects in aseptic conditions.Clarithromycin’s effects were validated in several experiments: it influenced NF-κB mediated transcription in murine peritoneal macrophages and intestinal enteroids; it suppressed NF-κB protein shuttling in murine reporter enteroids; it suppressed NF-κB (p65) DNA binding in the small intestine of mice exposed to LPS, and it reduced the severity of dextran sulphate sodium-induced colitis in C57BL/6 mice. Clarithromycin also suppressed NF-κB (p65) nuclear translocation in human intestinal enteroids.ConclusionsThese findings demonstrate that in-silico drug repositioning algorithms can viably be allied to laboratory validation assays in the context of inflammatory bowel disease; and that further clinical assessment of clarithromycin in the management of inflammatory bowel disease is required.
“…The authors contrast a knowledge-driven variable selection (KDVS) tool, with the well-established method of gene enrichment analysis, in order to characterize functionality in the context of Parkinson’s disease data, demonstrating that KDVS provides more effective enhancement. Also concerned with upstream analysis and interpretation of microarray data by enhanced methods, Koschmann and co-authors [4] describe an integrated promoter-pathway analysis approach, which permits causal analysis of co-expressed genes, with potential common regulatory influences. Knowledge-based analysis of the upstream pathway is combined with promoter analysis to obtain hypothetical master regulators, using novel gene expression triclusters, where such regulators link to tumorigenic and apoptotic processes.…”
High-throughput microarray technologies have long been a source of data for a wide range of biomedical investigations. Over the decades, variants have been developed and sophistication of measurements has improved, with generated data providing both valuable insight and considerable analytical challenge. The cost-effectiveness of microarrays, as well as their fundamental applicability, made them a first choice for much early genomic research and efforts to improve accessibility, quality and interpretation have continued unabated. In recent years, however, the emergence of new generations of sequencing methods and, importantly, reduction of costs, has seen a preferred shift in much genomic research to the use of sequence data, both less ‘noisy’ and, arguably, with species information more directly targeted and easily interpreted. Nevertheless, new microarray data are still being generated and, together with their considerable legacy, can offer a complementary perspective on biological systems and disease pathogenesis. The challenge now is to exploit novel methods for enhancing and combining these data with those generated by alternative high-throughput techniques, such as sequencing, to provide added value. Augmentation and integration of microarray data and the new horizons this opens up, provide the theme for the papers in this Special Issue.
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