Biology subjects

Cammarota, E.

Publications and source records attributed to Cammarota, E..

3 recordsLinked to original sources

bioRxiv2026

Structure-function dissection of huntingtin exon 1 identifies a PRD-driven modifier of neuronal toxicity in Huntington's disease

The Huntingtin gene (HTT) contains a conserved, yet expandable CAG repeat within exon 1. While the pathogenic expansion in Huntingtons Disease (HD) is well studied, the role of surrounding domains remains unclear. Using genome-edited mini-organoids and neurons, we dissected HTT exon 1 and found species-specific toxicity: the human variant caused more severe deficits than the mouse. Swapping the proline-rich domain (PRD) - the most divergent region - revealed its key role: the mouse PRD mitigated, while the human PRD worsened neuronal phenotypes. Omics profiling showed that pathogenic human exon 1 induced broad protein dysregulation, largely reversed by mouse PRD replacement. Bioinformatics implicated the actin cytoskeleton and transcriptional coactivator MKL2/MRTFB. We validated MKL2/MRTFB dysregulation in HD models and showed that restoring its expression rescued neuronal abnormalities. These findings highlight the PRDs contribution to HD toxicity and point to MKL2/MRTFB and the cytoskeleton as candidate mediators.

neuroscience↗

bioRxiv2025

MicroSplit: Semantic Unmixing of Fluorescent Microscopy Data

Fluorescence microscopy, a key driver for progress in the life sciences, faces limitations due to the microscopes optics, fluorophore chemistry, and photon exposure limits, necessitating trade-offs in imaging speed, resolution, and depth. Here, we introduce Micro[S]plit, a computational multiplexing technique based on deep learning that allows multiple cellular structures to be imaged in a single fluorescent channel and then unmix them by computational means, allowing faster imaging and reduced photon exposure. We show that Micro[S]plit efficiently separates up to four superimposed noisy structures into distinct denoised fluorescent image channels. Furthermore, using Variational Splitting Encoder-Decoder (VSE) networks, our approach can sample diverse predictions from a trained posterior of solutions. The diversity of these samples scales with the uncertainty in a given input, allowing us to estimate the true prediction errors by computing the variability between posterior samples. We demonstrate the robustness of Micro[S]plit networks, which are trained for each splitting task at hand, across various datasets and noise levels and show its utility to image more, to image faster, and to improve downstream analysis. We provide Micro[S]plit along with all associated training and evaluation datasets as open resources, enabling life scientists to immediately benefit from the potential of computational multiplexing and thus help accelerate the rate of their scientific discovery process.

bioinformatics↗

bioRxiv2019

Criticality of plasma membrane lipids reflects activation state of macrophage cells

Signalling is of particular importance in immune cells, and upstream in the signalling pathway many membrane receptors are functional only as complexes, co-locating with particular lipid species. Work over the last 15 years has shown that plasma membrane lipid composition is close to a critical point of phase separation, with evidence that cells adapt their composition in ways that alter the proximity to this thermodynamical point. Macrophage cells are a key component of the innate immune system, responsive to infections, regulating the local state of inflammation. We investigate changes in the plasma membranes proximity to the critical point, as a response to stimulation by various pro- and anti-inflammatory agents. Pro-inflammatory (IFN-{gamma}, Kdo-LipidA, LPS) perturbations induce an increase in the transition temperature of the GMPVs; anti-inflammatory IL4 has the opposite effect. These changes recapitulate complex plasma membrane composition changes, and are consistent with lipid criticality playing a master regulatory role: being closer to critical conditions increases membrane protein activity.

biophysics↗