Search

Motivation Drug repositioning has been proposed as an effective shortcut to drug discovery. The availability of large collections of transcriptional responses to drugs enables computational approaches to drug repositioning directly based on measured molecular effects. Results We introduce a novel computational methodology for rational drug repositioning, which exploits the transcriptional responses following treatment with small molecule. Specifically, given a therapeutic target gene, a prioritization of potential effective drugs is obtained by assessing their impact on the transcription of genes in the pathway(s) including the target. We performed in silico validation and comparison with a state-of-art technique based on similar principles. We next performed experimental validation in two different real-case drug repositioning scenarios: (i) upregulation of the glutamate-pyruvate transaminase (GPT), which has been shown to induce reduction of oxalate levels in a mouse model of primary hyperoxaluria, and (ii) activation of the transcription factor TFEB, a master regulator of lysosomal biogenesis and autophagy, whose modulation may be beneficial in neurodegenerative disorders. Availability and implementation A web tool for Gene2drug is freely available at http://gene2drug.tigem.it. An R package is under development and can be obtained from https://github.com/franapoli/gep2pep. Supplementary information Supplementary data are available at Bioinformatics online.

We performed an integrated analysis of drug chemical structures and drug-induced transcriptional responses. We demonstrated that a network representing three-dimensional structural similarities among 5452 compounds can be used to automatically group together drugs with similar scaffolds, physicochemical parameters and mode-of-action. We compared the structural network to a network representing transcriptional similarities among a subset of 1309 drugs for which transcriptional response were available in the Connectivity Map data set. Analysis of structurally similar, but transcriptionally different drugs sharing the same MOA enabled us to detect and remove weak and noisy transcriptional responses, greatly enhancing the reliability of transcription-based approaches to drug discovery and drug repositioning. Cardiac glycosides exhibited the strongest transcriptional responses with a significant induction of pathways related to epigenetic regulation, which suggests an epigenetic mechanism of action for these drugs. Drug classes with the weakest transcriptional responses tended to induce expression of cytochrome P450 enzymes, hinting at drug-induced drug resistance. Analysis of transcriptionally similar, but structurally different drugs with unrelated MOA, led us to the identification of a 'toxic' transcriptional signature indicative of lysosomal stress (lysosomotropism) and lipid accumulation (phospholipidosis) partially masking the target-specific transcriptional effects of these drugs. We found that this transcriptional signature is shared by 258 compounds and it is associated to the activation of the transcription factor TFEB, a master regulator of lysosomal biogenesis and autophagy. Finally, we built a predictive Random Forest model of these 258 compounds based on 128 physicochemical parameters, which should help in the early identification of potentially toxic drug candidates., Systems pharmacology: the chemical-transcriptional landscape of small molecules Transcriptional responses to drug treatment can reveal mechanism of action and off-target effects thus enabling drug repositioning, but only if measured in the appropriate cells at clinically relevant concentrations. A team led by Diego di Bernardo and Diego Medina generated a network representing structural similarities among compounds to automatically group together drugs with similar scaffolds and MOA. By comparing the structural drug network with a transcriptional drug network based on similarities in transcriptional response, the team observed broad differences between the two. This observation led to the identification of a transcriptional signature related lysosomal stress and phospholipidosis, and a physicochemical model to identify such compounds. These results provide general guidelines to prevent erroneous conclusion when using transcriptional responses of small molecules for drug discovery and drug repositioning

The human retina is a specialized tissue involved in light stimulus transduction. Despite its unique biology, an accurate reference transcriptome is still missing. Here, we performed gene expression analysis (RNA-seq) of 50 retinal samples from non-visually impaired post-mortem donors. We identified novel transcripts with high confidence (Observed Transcriptome (ObsT)) and quantified the expression level of known transcripts (Reference Transcriptome (RefT)). The ObsT included 77 623 transcripts (23 960 genes) covering 137 Mb (35 Mb new transcribed genome). Most of the transcripts (92%) were multi-exonic: 81% with known isoforms, 16% with new isoforms and 3% belonging to new genes. The RefT included 13 792 genes across 94 521 known transcripts. Mitochondrial genes were among the most highly expressed, accounting for about 10% of the reads. Of all the protein-coding genes in Gencode, 65% are expressed in the retina. We exploited inter-individual variability in gene expression to infer a gene co-expression network and to identify genes specifically expressed in photoreceptor cells. We experimentally validated the photoreceptors localization of three genes in human retina that had not been previously reported. RNA-seq data and the gene co-expression network are available online (http://retina.tigem.it).

MicroRNAs play a fundamental role in retinal development and function. To characterise the miRNome of the human retina, we carried out deep sequencing analysis on sixteen individuals. We established the catalogue of retina-expressed miRNAs, determined their relative abundance and found that a small number of miRNAs accounts for almost 90% of the retina miRNome. We discovered more than 3000 miRNA variants (isomiRs), encompassing a wide range of sequence variations, which include seed modifications that are predicted to have an impact on miRNA action. We demonstrated that a seed-modifying isomiR of the retina-enriched miR-124-3p was endowed with different targeting properties with respect to the corresponding canonical form. Moreover, we identified 51 putative novel, retina-specific miRNAs and experimentally validated the expression for nine of them. Finally, a parallel analysis of the human Retinal Pigment Epithelium (RPE)/choroid, two tissues that are known to be crucial for retina homeostasis, yielded notably distinct miRNA enrichment patterns compared to the retina. The generated data are accessible through an ad hoc database. This study is the first to reveal the complexity of the human retina miRNome at nucleotide resolution and constitutes a unique resource to assess the contribution of miRNAs to the pathophysiology of the human retina.

The endocannabinoid system refers to a widespread signaling system and its alteration is implicated in a growing number of human diseases. However, the potential role of endocannabinoids in skeletal muscle disorders remains unknown. Here we report the role of the endocannabinoid CB1 receptors in Duchenne’s muscular dystrophy. In murine and human models, CB1 transcripts show the highest degree of expression at disease onset, and then decline overtime. Similar changes are observed for PAX7, a key regulator of muscle stem cells. Bioinformatics and biochemical analysis reveal that PAX7 binds and upregulates the CB1 gene in dystrophic more than in healthy muscles. Rimonabant, an antagonist of CB1, promotes human satellite cell differentiation in vitro, increases the number of regenerated myofibers, and prevents locomotor impairment in dystrophic mice. In conclusion, our study uncovers a PAX7–CB1 cross talk potentially exacerbating DMD and highlights the role of CB1 receptors as target for potential therapies., The regenerative capacity of muscle stem cells is impaired in Duchenne muscular dystrophy (DMD). Here, the authors show that the endocannabinoid receptor CB1 is activated by PAX7 in muscle stem cells, and that pharmacological inhibition of CB1 promotes stem cell activation and ameliorates symptoms in DMD mouse models.

Motivation: Automated screening approaches are able to rapidly identify a set of small molecules inducing a desired phenotype from large small-molecule libraries. However, the resulting set of candidate molecules is usually very diverse pharmacologically, thus little insight on the shared mechanism of action (MoA) underlying their efficacy can be gained. Results: We introduce a computational method (Drug-Set Enrichment Analysis—DSEA) based on drug-induced gene expression profiles, which is able to identify the molecular pathways that are targeted by most of the drugs in the set. By diluting drug-specific effects unrelated to the phenotype of interest, DSEA is able to highlight phenotype-specific pathways, thus helping to formulate hypotheses on the MoA shared by the drugs in the set. We validated the method by analysing five different drug-sets related to well-known pharmacological classes. We then applied DSEA to identify the MoA shared by drugs known to be partially effective in rescuing mutant cystic fibrosis transmembrane conductance regulator (CFTR) gene function in Cystic Fibrosis. Availability and implementation: The method is implemented as an online web tool publicly available at http://dsea.tigem.it. Contact: dibernardo@tigem.it Supplementary information: Supplementary data are available at Bioinformatics online.

Cystic fibrosis (CF) is caused by mutations in CF transmembrane conductance regulator (CFTR). The most frequent mutation (F508del-CFTR) results in altered proteostasis, that is, in the misfolding and intracellular degradation of the protein. The F508del-CFTR proteostasis machinery and its homeostatic regulation are well studied, while the question whether ‘classical’ signalling pathways and phosphorylation cascades might control proteostasis remains barely explored. Here, we have unravelled signalling cascades acting selectively on the F508del-CFTR folding-trafficking defects by analysing the mechanisms of action of F508del-CFTR proteostasis regulator drugs through an approach based on transcriptional profiling followed by deconvolution of their gene signatures. Targeting multiple components of these signalling pathways resulted in potent and specific correction of F508del-CFTR proteostasis and in synergy with pharmacochaperones. These results provide new insights into the physiology of cellular proteostasis and a rational basis for developing effective pharmacological correctors of the F508del-CFTR defect. DOI: http://dx.doi.org/10.7554/eLife.10365.001, eLife digest Cystic fibrosis is a genetic disease that commonly affects people of European descent. The condition is caused by mutations in the gene encoding a protein called “cystic fibrosis transmembrane conductance regulator” (or CFTR for short). CFTR forms a channel in the membrane of cells in the lungs that help transport salt across the membrane. Mutated versions of the protein are not as efficient at transporting salts, and eventually this damages the lung tissue. As the damage progresses, individuals become very vulnerable to bacterial infections that further damage the lungs and may eventually lead to death. One of the reasons CFTR mutations are harmful is that they cause the protein to fold up incorrectly and remain trapped inside the cell. Cells have quality control systems that recognize and destroy poorly folded proteins, and so only a few of the mutated CFTR proteins ever make it to the membrane to move salts. New therapies have been developed that improve folding of the protein and/or help the CFTR proteins that make it to the membrane work better. But more and better treatment options are needed. Hegde, Parashuraman et al. have now tested drugs that control how proteins fold and move to the membrane to see how they affect gene expression in cells with the most common cystic fibrosis-causing mutation. These drugs are known to improve the activity of the CFTR mutant, but do so too weakly to be of clinical interest. The experiments revealed that the expression of a few hundred genes was changed in response the drugs. Many of these genes were involved in major signalling pathways that control how CFTR is folded and trafficked within cells. Next, Hegde, Parashuraman et al. tested drugs that inhibit these signalling pathways to see if they improve salt handling in the mutated cells. The experiments demonstrated that these inhibitor drugs efficiently block the breakdown of misfolded CFTR, or boost the likelihood of CFTR making it to the membrane, helping improve salt trafficking in the cells. The inhibitors produced even better results when used in combination with a known CFTR-protecting drug. The results suggest that identifying and targeting signalling pathways involved in the folding, trafficking, and breakdown of CFTR may prove a promising way to treat cystic fibrosis. DOI: http://dx.doi.org/10.7554/eLife.10365.002

Background Mistrafficking of CFTR protein caused by F508del, the most frequent mutation in cystic fibrosis (CF), can be corrected by cell incubation at low temperature, an effect that may be mediated by altered expression of proteostasis genes. Methods To identify small molecules mimicking low temperature, we compared gene expression profiles of cells kept at 27°C with those previously generated from more than 1300 compounds. The resulting candidates were tested with a functional assay on a bronchial epithelial cell line. Results We found that anti-inflammatory glucocorticoids, such as mometasone, budesonide, and fluticasone, increased mutant CFTR function. However, this activity was not confirmed in primary bronchial epithelial cells. Actually, glucocorticoids enhanced Na + absorption, an effect that could further impair mucociliary clearance in CF airways. Conclusions Our results suggest that rescue of F508del-CFTR by low temperature cannot be easily mimicked by small molecules and that compounds with closer transcriptional and functional effects need to be found.