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Carrara, M.

Publications and source records attributed to Carrara, M..

5 recordsLinked to original sources

Identification and SAR optimization of FBXO22-mediated TEAD Targeted Glue degraders

TEAD transcription factors are emerging oncology targets due to their function as key effectors of the Hippo signalling pathway, which is frequently dysregulated in cancer. Here, we report the discovery and development of potent, deep, and rapid-acting TEAD Targeted Glue degraders that leverage an aldehyde-mediated degron mechanism. Our compounds demonstrate exceptional on-pathway selectivity profiles and exhibit the expected Hippo signalling modulation. Mechanistically, we demonstrate that amine-based TEAD degrader scaffolds undergo extracellular conversion to the active aldehyde species, which mediate covalent engagement of FBXO22 C326, triggering TEAD proteasomal degradation. The degraders identified were able to be rationally and systematically optimised for both degradation potency and kinetics, achieving enhanced degradation profiles compared to previously reported FBXO22-targeting approaches, establishing design principles for this degrader class. Our findings highlight strategies for the structure activity relationship (SAR) and rational optimization of aldehyde-mediated degrons to generate novel precision molecular glue degraders against TEAD, a high value oncology target.

cancer biology↗

Characterizing Co-Circulating Respiratory Virus Genomic Diversity in Switzerland with Hybrid-Capture Sequencing and Phylogenetic Reconstructions: Insights into the 2023/24 Season

Respiratory viruses circulate yearly with strain-specific patterns. Although SARS-CoV-2 and Influenza A/B genomic surveillance is well-developed, most respiratory viruses are unevenly monitored, lacking geographical diversity to capture wider population dynamics. Consequently, insights into respiratory virus evolution are limited. We investigated the genetic diversity of these viruses within one country. During the 2023/24 season, we conducted whole-genome sequencing of 1129 clinical samples using a hybrid-capture protocol. These samples were pre-tested by real-time PCR panels throughout Switzerland. Leveraging publicly-available full-length genomes, we constructed background datasets representative of geographical diversity and built phylogenies for all viruses with more than 40 new high-quality genomes from this study. We detected 981 viruses and recovered 461 high-quality genomes, including 18 co-infections, from 437 PCR-positive and 6 PCR-negative samples. All viruses detected by PCR were also detected by sequencing in 56% of samples. The four most prevalent viruses were Influenza A/H1N1, SARS-CoV-2, RSV-A, and HPIV-3, and their seasonal spread was consistent with wastewater monitoring and influenza-like illness reports. Swiss viral genomes were representative of the global genomic diversity, with evidence for multiple introductions into Switzerland, and we identified putative Swiss clusters. In this proof-of-concept study, we focus on 3 viruses (Influenza A/H1N1, RSV-A/B, and HPIV-3), and we demonstrate the streamlined implementation of a broad respiratory virus genomic surveillance workflow with an off-the-shelf protocol and publicly-available software. In addition, we highlight additional evolutionary insights that can only be derived from genomic surveillance. Going forward, this dataset will be a useful resource for future investigations into respiratory viral genomic diversity.

genetics↗

V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation

The large amount and diversity of viral genomic datasets generated by next-generation sequencing technologies poses a set of challenges for computational data analysis workflows, including rigorous quality control, adaptation to higher sample coverage, and tailored steps for specific applications. Here, we present V-pipe 3.0, a computational pipeline designed for analyzing next-generation sequencing data of short viral genomes. It is developed to enable reproducible, scalable, adaptable, and transparent inference of genetic diversity of viral samples. By presenting two large-scale data analysis projects, we demonstrate the effectiveness of V-pipe 3.0 in supporting sustainable viral genomic data science.

bioinformatics↗

gExcite - A start-to-end framework for single-cell gene expression, hashing, and antibody analysis

SummarySingle-cell RNA sequencing (scRNA-seq) based gene expression analysis is now an established powerful technique to decipher tissues at a single-cell level. Recently, CITE-seq emerged as a multimodal single-cell technology capturing gene expression and surface protein information from the same single-cells, which allows unprecedented insights into disease mechanisms and heterogeneity, as well as immune cell profiling. Multiple single-cell profiling methods exist, but they are typically focussed on either gene expression or antibody analysis, not their combination. Moreover, existing software suites are not easily scalable to a multitude of samples. To this end, we designed gExcite, a start-to-end workflow that provides both gene expression and CITE-seq analysis, as well as hashing deconvolution. Embedded in the Snakemake workflow manager, gExcite facilitates reproducible and scalable analyses. We showcase the output of gExcite on a study of different dissociation protocols on PBMC samples. AvailabilitygExcite is open source available on github at https://github.com/ETH-NEXUS/gExcite_pipeline The software is distributed under the GNU General Public License 3 (GPL3). Contactsinger@nexus.ethz.ch Supplementary InformationSupplementary information is available at the journals web site.

bioinformatics↗

Dysregulation of circular RNAs in myotonic dystrophy type 1

Circular RNAs (circRNAs) constitute a recently re-discovered class of non-coding RNAs functioning as sponge for miRNAs and proteins, affecting RNA splicing and regulating transcription. CircRNAs are generated by \"back-splicing\", linking covalently 3- and 5-ends of exons. Thus, circRNA levels might be deregulated in conditions associated to altered RNA-splicing. Indeed, increasing evidence indicates their role in human diseases. Specifically, myotonic dystrophy type 1 (DM1) is a multisystemic disorder caused by expanded CTG-repeats in the DMPK gene, resulting in abnormal mRNA-splicing. In this investigation, circRNAs expressed in DM1 skeletal muscles were identified by analyzing RNA-sequencing data-sets followed by qPCR validation. In muscle biopsies, out of 9 tested, 4 transcripts showed an increased circular fraction: CDYL, HIPK3, RTN4_03 and ZNF609. The circular fraction values correlated positively with skeletal muscle strength and Receiver-Operating-Characteristics curves showed that these four circRNAs allow to distinguish DM1 patients from controls. The identified circRNAs were also detectable in peripheral-blood-mononuclear-cells (PBMCs) and plasma of DM1 patients, but they were not regulated significantly, indicating a tissue-selectivity of the identified modulations. Finally, increased circular fractions of RTN4_03 and ZNF609 were also observed in differentiated myogenic cell lines derived from DM1 patients.\n\nIn conclusion, this proof-of-principle study identified circRNA dysregulation in DM1 patients.

molecular biology↗