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Biology subjects

Biffo, S.

Publications and source records attributed to Biffo, S..

4 recordsLinked to original sources

Compressive stress couples calcium signalling to translational control and proteostasis

Compressive stress is a pervasive feature of solid tumour growth, and mechanical loading is known to activate calcium signalling through the mechanosensitive channel Piezo1. How this signal is converted into changes in cellular biosynthetic capacity, however, remains unclear. Here we show that compressive stress engages a Piezo1-dependent calcium checkpoint that reduces translational output with increasing mechanical load, independently of mTORC1 and the integrated stress response. Compression triggers Piezo1-dependent release of endoplasmic reticulum Ca2, activating eEF2 kinase to slow translational elongation. This same Ca2 signal drives mitochondrial remodelling and reactive oxygen species production, which reinforce translational repression through redox-dependent oxidation of the translation initiation factor eIF2{beta}. In parallel, Ca2-dependent AMPK activation triggers autophagic ribosome degradation, alleviating compression-induced macromolecular crowding and restoring cytoplasmic rheology despite sustained mechanical load. These mechanisms act at distinct levels of translational control: initiation, elongation and ribosome abundance; yet converge to limit biosynthetic output under compression. Consistent with a role for this pathway in tumour adaptation to mechanical constraint, eEF2K expression correlates with poor overall survival in a public PDAC patient dataset. Together, these findings define a mechano-metabolic checkpoint through which cells actively tune biosynthetic capacity to their physical environment.

cell biology↗

CIA: a Cluster Independent Annotation method to investigate cell identities in scRNA-seq data

Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of the transcriptional landscape of complex tissues, enabling the discovery of novel cell types and biological functions. However, the identification and classification of cells from scRNA-seq datasets remain significant challenges. To address this, we developed a new computational tool called CIA (Cluster Independent Annotation), which accurately identifies cell types across different datasets without requiring a fully annotated reference dataset or complex machine learning processes. Based on predefined cell type signatures, CIA provides a highly user-friendly and practical solution to functional annotation of single cells. Our results demonstrate that CIA outperforms other state-of-the-art approaches, while also having significantly lower computational running time. Overall, CIA simplifies the process of obtaining reproducible signature-based cell assignments that can be easily interpreted through graphical summaries providing researchers with a powerful tool to explore the complex transcriptional landscape of single cells. The CIA framework is implemented in both the Python and R programming languages, making it applicable to all main single-cell analysis frameworks, and it is available under the MIT license with its documentation at the following links: Python package: https://pypi.org/project/cia-python/ Python tutorial: https://cia-python.readthedocs.io/en/latest/tutorial/Cluster_Independent_Annotation.html R package and tutorial: https://github.com/ingmbioinfo/CIA_R

bioinformatics↗

Sacsin cotranslational degradation causes autosomal recessive spastic ataxia of Charlevoix-Saguenay

Autosomal recessive spastic ataxia of Charlevoix-Saguenay is caused by more than 200 different mutations in the SACS gene encoding sacsin, a huge multimodular protein of unknown function. ARSACS phenotypic spectrum is highly variable. Previous studies correlated the nature and position of SACS mutations with age of onset or disease severity, though the effects on protein stability were not considered. In this study, we explain mechanistically the lack of genotype-phenotype correlation in ARSACS, with important consequences for disease diagnosis and treatment. We found that sacsin is almost absent in ARSACS fibroblasts, regardless of the nature of the mutation. We did not detect sacsin in patients with truncating mutations, while we found it strikingly reduced or absent also in compound heterozygotes carrying diverse missense mutations. We excluded SACS mRNA decay, defective translation, or faster post-translational degradation as causes of protein reduction. Conversely, we demonstrated that nascent mutant sacsin protein undergoes preemptive cotranslational degradation, emerging as a novel cause of a human disease. Based on these findings, sacsin levels should be included in the diagnostic algorithm for ARSACS.

genetics↗

The Drosophila Eukaryotic Initiation Factor eIF6 affects development by regulating apoptosis via the ecdysone pathway

During development, ribosome biogenesis and translation reach peak activities, due to impetuous cell proliferation. Current models predict that protein synthesis elevation is controlled by transcription factors and signalling pathways. Developmental models addressing translation factors overexpression effects are lacking. Eukaryotic Initiation Factor (eIF6) is necessary for ribosome biogenesis and efficient translation. eIF6 is a single gene, conserved from yeasts to mammals, suggesting a tight regulation need. We generated a Drosophila melanogaster in vivo model of eIF6 upregulation, demonstrating a boost in general translation and the shut off of the ecdysone biosynthetic pathway. Translation modulation in S2 cells showed that translational rate and ecdysone biosynthesis are inversely correlated. In vivo, eIF6-driven alterations delayed programmed cell death (PCD), resulting in aberrant phenotypes, partially rescued by ecdysone administration. Our data show that eIF6 triggers a translation program with far-reaching effects on metabolism and development, stressing the driving and central role of translation.

developmental biology↗