Mantra 2.0: An online collaborative resource for drug mode of action and repurposing by network analysis

Elucidation of molecular targets of a compound (mode of action, MoA) and of its off-targets is a crucial step in drug development. We developed an online collaborative resource (MANTRA 2.0) that supports this process by exploiting similarities between drug-induced transcriptional profiles. Drugs are organised in a network of nodes (drugs) and edges (similarities) highlighting “communities” of drugs sharing a similar MoA. A user can upload gene expression profiles (GEPs) before and after drug treatment in one or multiple cell types. An automated processing pipeline transforms the GEPs into a unique drug ”node” embedded in the drug-network. Visual inspection of the neighbouring drugs and communities helps in revealing its MoA, and to suggest new applications of known drugs (drug repurposing). MANTRA 2.0 allows storing and sharing user-generated network nodes, thus making MANTRA 2.0 a collaborative ever-growing resource

Genetic and pharmacological regulation of the endocannabinoid CB1 receptor in Duchenne muscular dystrophy

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

A Vanadium(III) Complex with Blue and NIR-II Spin-Flip Luminescence in Solution

Luminescence from Earth-abundant metal ions in solution at room temperature is a very challenging objective due to the intrinsically weak ligand field splitting of first-row transition metal ions, which leads to efficient nonradiative deactivation via metal-centered states. Only a handful of 3dn metal complexes (n ≠ 10) show sizable luminescence at room temperature. Luminescence in the near-infrared spectral region is even more difficult to achieve as further nonradiative pathways come into play. No Earth-abundant first-row transition metal complexes have displayed emission >1000 nm at room temperature in solution up to now. Here, we report the vanadium(III) complex mer-[V(ddpd)2][PF6]3 yielding phosphorescence around 1100 nm in valeronitrile glass at 77 K as well as at room temperature in acetonitrile with 1.8 × 10–4% quantum yield (ddpd = N,N′-dimethyl-N,N′-dipyridine-2-ylpyridine-2,6-diamine). In addition, mer-[V(ddpd)2][PF6]3 shows very strong blue fluorescence with 2% quantum yield in acetonitrile at room temperature. Our comprehensive study demonstrates that vanadium(III) complexes with d2 electron configuration constitute a new class of blue and NIR-II luminophores, which complement the classical established complexes of expensive precious metals and rare-earth elements

Synthetic long non-coding RNAs [SINEUPs] rescue defective gene expression in vivo

Non-coding RNAs provide additional regulatory layers to gene expression as well as the potential to being exploited as therapeutic tools. Non-coding RNA-based therapeutic approaches have been attempted in dominant diseases, however their use for treatment of genetic diseases caused by insufficient gene dosage is currently more challenging. SINEUPs are long antisense non-coding RNAs that up-regulate translation in mammalian cells in a gene-specific manner, although, so far evidence of SINEUP efficacy has only been demonstrated in in vitro systems. We now show that synthetic SINEUPs effectively and specifically increase protein levels of a gene of interest in vivo. We demonstrated that SINEUPs rescue haploinsufficient gene dosage in a medakafish model of a human disorder leading to amelioration of the disease phenotype. Our results demonstrate that SINEUPs act through mechanisms conserved among vertebrates and that SINEUP technology can be successfully applied in vivo as a new research and therapeutic tool for gene-specific up-regulation of endogenous functional proteins

Continuous population-level monitoring of SARS-CoV-2 seroprevalence in a large European metropolitan region.

Effective public health measures against SARS-CoV-2 require granular knowledge of population-level immune responses. We developed a Tripartite Automated Blood Immunoassay (TRABI) to assess the IgG response against three SARS-CoV-2 proteins. We used TRABI for continuous seromonitoring of hospital patients and blood donors (n = 72'250) in the canton of Zurich from December 2019 to December 2020 (pre-vaccine period). We found that antibodies waned with a half-life of 75 days, whereas the cumulative incidence rose from 2.3% in June 2020 to 12.2% in mid-December 2020. A follow-up health survey indicated that about 10% of patients infected with wildtype SARS-CoV-2 sustained some symptoms at least twelve months post COVID-19. Crucially, we found no evidence of a difference in long-term complications between those whose infection was symptomatic and those with asymptomatic acute infection. The cohort of asymptomatic SARS-CoV-2-infected subjects represents a resource for the study of chronic and possibly unexpected sequelae

gep2pep: A bioconductor package for the creation and analysis of pathway-based expression profiles

Pathway-based expression profiles allow for high-level interpretation of transcriptomic data and systematic comparison of dysregulated cellular programs. We have previously demonstrated the efficacy of pathway-based approaches with two different applications: the drug set enrichment analysis and the Gene2drug analysis. Here, we present a software tool that allows to easily convert gene-based profiles to pathway-based profiles and analyze them within the popular R framework. We also provide pre-computed profiles derived from the original Connectivity Map and its next generation release, i.e. the LINCS database. Availability and implementation: The tool is implemented as the R/Bioconductor package gep2pep and can be freely downloaded from https://bioconductor.org/packages/gep2pep