Biology subjects

Biagioni, C.

Publications and source records attributed to Biagioni, C..

3 recordsLinked to original sources

bioRxiv2025

Membrane potential and feedback dynamics regulate CatSper-mediated progesterone signaling in human sperm

Activation of the sperm-specific Ca2+ channel CatSper by progesterone evokes rapid changes in intracellular Ca2+ in human sperm that are required for fertilization. However, the mechanisms regulating the progesterone-induced Ca2+ signals have remained elusive. Here, we used quantitative kinetic fluorimetry with fast voltage-sensitive fluorescent indicators to investigate how progesterone affects the membrane potential (Vm) of human sperm. Additionally, we employed the FASTM technique to simultaneously record at millisecond time resolution changes in both Vm and intracellular Ca2+. We show that progesterone evokes a rapid pulse-like depolarization and repolarization. The depolarization is caused by Ca2+ influx through CatSper, which pulls Vm away from a resting membrane potential (Vrest) of -65 mV set by the sperm-specific K+ channel Slo3. We further show that Vm- and Ca2+-dependent mechanisms limit the CatSper-mediated Ca2+ influx, thereby promoting repolarization and enabling K+ efflux through Slo3 channels to restore Vrest. Our findings demonstrate that non-genomic progesterone signaling in human sperm is regulated by negative feedback on CatSper and involves a dynamic interplay between CatSper and Slo3 in controlling Vm. We anticipate that our novel kinetic, quantitative Vm recording and Vm/Ca2+-multiplexing techniques will reveal additional molecular mechanisms underlying CatSper-mediated Ca2+ signaling in human sperm both in health and disease.

cell biology↗

bioRxiv2024

Sensitive tumor detection, accurate quantification, and cancer subtype classification using low-pass whole methylome sequencing of plasma DNA

The analysis of circulating tumor DNA (ctDNA) is increasingly used for monitoring disease in patients with metastatic cancer. Here, we introduce a robust and reproducible strategy combining low-pass whole methylome sequencing of plasma DNA with METER, a novel computational tool. Engaging prediction models trained on independent available datasets, METER enables the detection and quantification of tumor content (TC) and performs molecular cancer subtyping. Applied to plasma methylomes from early metastatic breast cancer patients, our method demonstrated reliable quantification, sensitive tumor detection below 3% of TC, and the ability to perform accurate Estrogen Receptor (ER) subtyping. METER provided clinically relevant predictions, underscored by associations with relevant prognostic factors, robust correlation with matched circulating tumor cells, and highly correlated with patients outcomes in challenging scenarios as TC<3%. Our strategy provides comprehensive and sensitive analysis of plasma samples, serving as a valuable yet cost-effective precision oncology tool.

cancer biology↗

bioRxiv2020

Cancer methylomes characterization enabled by Rocker-meth

Differentially DNA methylated regions (DMRs) inform on the role of epigenetic changes in cancer. We present Rocker-meth, a computational method exploiting a heterogeneous hidden Markov model to detect DMRs across multiple experimental platforms. Its application to more than 6,000 methylation profiles across 14 tumor types provides a comprehensive catalog of tumor type-specific and shared DMRs, also amenable to single-cell DNA-methylation data. In depth integrative analysis including orthogonal omics shows the enhanced ability of Rocker-meth in recapitulating known associations, further uncovering the pan-cancer relationship between DNA hypermethylation and transcription factor deregulation depending on the baseline chromatin state.

cancer biology↗