Biology subjects

Magi, A.

Publications and source records attributed to Magi, A..

11 recordsLinked to original sources

bioRxiv2026

Triptans reprogram Schwann cells to drive medication-overuse headache via β-glycan/TGF-β3 signaling

Medication-overuse headache (MOH) is one of the leading causes of chronic daily headache worldwide and arises from the repeated use of acute anti-migraine medications, including triptans. However, the cellular substrates and intracellular pathways driving this paradoxical chronification remain unknown. Here, using Schwann cell-selective silencing of the 5-HT1B/D receptor, we observed that acute triptan administration counteracts CGRP-induced, endosome-confined cAMP accumulation, preventing the development of periorbital mechanical allodynia in mice. In contrast, prolonged 5-HT1B/D activation in Schwann cells induces epigenetic and transcriptomic dysregulation associated with MOH in mice. Specifically, intronic hypermethylation-driven overexpression of BETAGLYCAN promotes activation of a non-canonical TGF-{beta}-dependent signaling cascade. The resulting TGF-{beta}3 upregulation establishes a feed-forward loop that sustains proalgesic paracrine communication between Schwann cells and primary sensory neurons. Analysis of plasma levels from patients with MOH confirmed elevated TGF-{beta}3 levels specifically associated with triptan-dependent MOH, supporting the translational relevance of these findings. Together, our data identify Schwann cell 5-HT1B/D signaling as a dual mediator of both the acute anti-migraine efficacy and the maladaptive mechanisms underlying MOH. These results provide a conceptual framework for strategies aimed at preserving the therapeutic benefits of triptans while limiting the adverse consequences of chronic administration. One Sentence SummarySchwann cell 5-HT1B/D receptor signaling mediates the dual effects of triptans by acutely inhibiting CGRP-driven nociceptive pathways while chronically promoting epigenetically driven TGF-{beta}3-dependent proalgesic signaling that causes medication-overuse headache.

pharmacology and toxicology↗

bioRxiv2025

Long-term mavacamten exposure reduces force and sarcomere density in a hiPSC model of hypertrophic cardiomyopathy

BackgroundMavacamten, a first-in-class allosteric myosin inhibitor, has demonstrated efficacy and safety in obstructive hypertrophic cardiomyopathy (oHCM), notably reducing symptoms, left ventricular outflow obstruction, and wall thickness over 30 weeks. We recently reported that the MYBPC3:c.772G>A variant causes HCM through cMyBP-C haploinsufficiency, leading to accelerated sarcomere kinetics and higher energy consumption in patient myocardium and hiPSC- derived cardiomyocytes (hiPSC-CMs). These effects are counterbalanced by prolonged action potentials and slower Ca{superscript 2} transients, which preserve twitch duration but may increase arrhythmic risk. Mavacamten may reduce myocardial energetic defects in HCM. ObjectivesTo investigate the long-term effects of Mavacamten on sarcomere structure, contractility, and transcriptional remodeling using patient-specific and CRISPR-corrected isogenic hiPSC-derived cardiomyocyte models of HCM. MethodsHiPSC-CMs and engineered heart tissues (EHTs) derived from a MYBPC3:c.772G>A patient and its CRISPR-corrected line were first exposed to increasing concentrations of Mavacamten to assess acute dose-response relationships and determine IC50 values. Based on these data, chronic treatments (0.3- 0.75 M for 20 days) were performed mechanical, structural, electrophysiological, and transcriptomic adaptations. ResultsAcute exposure produced a rapid and fully reversible reduction in active force, while chronic treatment for 20 days induced a sustained decrease in contractility with incomplete recovery after 4 days of washout, indicating a two-phase mechanism of action. Long-term force reduction was paralleled by decreased cell area and sarcomere density, indicating that structural disassembly contributes to sustained functional depression and re-assembly after washout. Electrophysiological analysis confirmed the specific alterations of the MYBPC3:c.772G>A mutation previously observed, with no detectable effects following treatment with Mavacamten. In addition, transcriptome analysis was used to study the molecular mechanisms underlying the long-term effect. ConclusionsMavacamten induces a biphasic, persistent-to-reversible, reduction of sarcomeric force associated with structural remodeling, providing mechanistic insight into its capacity to promote favorable cardiac remodeling in oHCM.

physiology↗

bioRxiv2025

Benchmarking DNA Foundation Models for zero-shot variant effect prediction: the role of context, training, and architecture

In this study, we systematically evaluate the performance of several DNA foundation models (NT, DNABERT, and HyenaDNA) in predicting the functional impact of genetic variants using Zero-shot scoring, a method that does not require task-specific fine-tuning. We assess the models sensitivity to sequence alterations introduced by Single Nucleotide Variants (SNVs), comparing their ability to capture both local and extended contextual effects. Using pathogenic, benign, and uncertain SNVs from ClinVar, we show that large multi-species NT models outperform other architectures in detecting functional consequences, not only at the mutation site but also in adjacent regions. These models exhibit superior discriminative power across variant categories, especially when aggregating Zero-shot scores over multiple surrounding tokens. Conversely, models trained solely on human sequences, such as DNABERT and HyenaDNA, show limited contextual awareness and reduced ability to differentiate variant effects. Our findings highlight the critical importance of model size, training objective, and training data diversity in shaping model performance. Furthermore, we discuss current limitations in modeling long-range dependencies in genomic sequences and suggest that innovations in transformer architectures, such as sparse attention or memory-augmented models, may provide viable paths toward scalable, genome-wide variant effect prediction.

genomics↗

bioRxiv2024

PoreMeth2: decoding the evolution of methylome alterations with Nanopore sequencing

In epigenetic analysis, identifying differentially methylated regions (DMRs) typically involves detecting groups of consecutive CpGs that show significant changes in their average methylation levels. However, the methylation state of a genomic region can also be characterized by a mixture of patterns (epialleles) with variable frequencies, and the relative proportions of such patterns can provide insights into its mechanisms of formation. Traditional methods based on bisulfite conversion and NGS, due to the read size (150 bp), allow epiallele frequency analysis only in high-CpG-density regions, limiting differential methylation studies to just 50% of the human methylome. Nanopore sequencing, with its long reads, enables the analysis of epiallele frequency across both high- and low-CpG-density regions. We introduce a novel computational approach, PoreMeth2, an R library that integrates epiallelic diversity and methylation frequency changes from Nanopore data to identify DMRs, assess their formation mechanisms, and annotate them to genic and regulatory elements. We applied PoreMeth2 to cancer and glial cell datasets, demonstrating its ability to distinguish epigenomic changes with a strong effect on gene expression from those with a weaker impact on transcriptional activity. PoreMeth2 is publicly available at https://github.com/Lab-CoMBINE/PoreMeth2.

bioinformatics↗

bioRxiv2023

GASOLINE: detecting germline and somatic structural variants from long-reads data.

Long-read sequencing allows analyses of single nucleic-acid molecules and produces sequences in the order of tens to hundreds kilobases. Its application to whole-genome analyses allows identification of complex genomic structural-variants (SVs) with unprecedented resolution. SV identification, however, requires complex computational methods, based on either read-depth or intra- and inter-alignment signatures approaches, which are limited by size or type of SVs. Moreover, most currently available tools only detect germline variants, thus requiring separate computation of sample pairs for comparative analyses. To overcome these limits, we developed a novel tool (Germline And SOmatic structuraL varIants detectioN and gEnotyping; GASOLINE) that groups SV signatures using a sophisticated clustering procedure based on a modified reciprocal overlap criterion, and is designed to identify germline SVs, from single samples, and somatic SVs from paired test and control samples. GASOLINE is a collection of Perl, R and Fortran codes, it analyzes aligned data in BAM format and produces VCF files with statistically significant somatic SVs. Germline or somatic analysis of 30x sequencing coverage experiments requires 4-5 hours with 20 threads. GASOLINE outperformed currently available methods in the detection of both germline and somatic SVs in synthetic and real long-reads datasets. Notably, when applied on a pair of metastatic melanoma and matched-normal sample, GASOLINE identified 6 genuine somatic SVs that were missed using five different sequencing technologies and state-of-the art SV calling approaches. Thus, GASOLINE identifies germline and somatic SVs with unprecedented accuracy and resolution, outperforming currently available state-of-the-art WGS long-reads computational methods.

bioinformatics↗

bioRxiv2022

High-resolution Nanopore methylome-maps reveal random hyper-methylation at CpG-poor regions as driver of chemoresistance in leukemias.

Aberrant DNA methylation at CpG dinucleotides is a hallmark of cancer and is associated with the emergence of resistance to anti cancer treatment, though molecular mechanisms and biological significance remain elusive. Genome scale methylation maps by currently used methods are based on chemical modification of DNA and are best suited for analyses of methylation at CpG rich regions (CpG islands). We report the first high coverage whole genome map in cancer using the long read nanopore technology, which allows simultaneous DNA-sequence and -methylation analyses on native DNA. We analyzed clonal epigenomic/genomic evolution in Acute Myeloid Leukemias (AMLs) at diagnosis and relapse, after chemotherapy. Long read sequencing coupled to a novel computational method allowed definition of differential methylation at unprecedented resolution, and showed that the relapse methylome is characterized by hypermethylation at both CpG islands and sparse CpGs regions. Most differentially methylated genes, however, were not differentially expressed nor enriched for chemoresistance genes. A small fraction of under-expressed and hyper-methylated genes at sparse CpGs, in the gene body, was significantly enriched in transcription factors (TFs). Remarkably, these few TFs supported large gene-regulatory networks including 50% of all differentially expressed genes in the relapsed AMLs and highly-enriched in chemoresistance genes. Notably, hypermethylated regions at sparse CpGs were poorly conserved in the relapsed AMLs, under-represented at their genomic positions and showed higher methylation entropy, as compared to CpG islands. Relapsed AMLs carried few patient specific structural variants and DNA mutations, apparently not involved in drug resistance. Thus, drug resistance in AMLs can be mainly ascribed to the selection of random epigenetic alterations at sparse CpGs of a few transcription factors, which then induce reprogramming of the relapsing phenotype, independently of clonal genomic evolution.

genomics↗

bioRxiv2021

Third Generation Cytogenetic Analysis (TGCA): diagnostic application of long-read sequencing.

Unbalanced Structural Variants (uSVs) play important roles in the pathogenesis of several genetic syndromes. Traditional and molecular karyotyping are considered the first-tier diagnostic tests to detect macroscopic and cryptic deletions/duplications. However, their time-consuming and laborious experimental protocols protract diagnostic times from three to fifteen days. Long read sequencing approaches, such as Oxford Nanopore Technologies (ONT), have the ability to reduce time to results for the detection of uSVs with the same resolution of current state-of-the-art diagnostic tests. Here we compared ONT to molecular karyotyping for the detection of pathogenic uSVs of 7 patients with previously diagnosed causative CNVs of different sizes and allelic fractions. Larger chromosomal anomalies included trisomy 21 and mosaic tetrasomy 12p. Among smaller CNVs we tested two reciprocal genomic imbalances in 7q11.23 (1.367 Mb), a 170 kb deletion encompassing NRXN1 and mosaic 6q27 (1.231 Mb) and 2q23.1 (408 kb) deletions. DNA libraries were prepared following ONT standard protocols and sequenced on the GridION device for 48 h. Data generated during runs were analysed in online mode, using NanoGLADIATOR. We were capable to identify all pathogenic CNVs with detection time inversely proportional to size and allelic fraction. Aneuploidies were called after only 30 minutes of sequencing, while 30 hours were needed to call CNVs < 500 kb also in mosaic state (44%). These results demonstrate the clinical utility of our approach that allows the molecular diagnosis of genomic disorders within a 30 minutes to 30 hours time-frame.

genomics↗

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↗

bioRxiv2020

Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients

Alterations in the genetic content, such as Copy Number Variations (CNVs) is one of the hallmarks of cancer and their detection is used to recognize tumoral DNA. Analysis of cell-free DNA from plasma is a powerful tool for non-invasive disease monitoring in cancer patients. Here we exploit third generation sequencing (Nanopore) to obtain a CNVs profile of tumoral DNA from plasma, where cancer-related chromosomal alterations are readily identifiable. Compared to Illumina sequencing -the only available alternative- Nanopore sequencing represents a viable approach to characterize the molecular phenotype, both for its ease of use, costs and rapid turnaround (6 hours).

cancer biology↗

bioRxiv2019

MAtCHap: an ultra fast algorithm for solving the single individual haplotype assembly problem.

BackgroundHuman genomes are diploid, which means they have two homologous copies of each chromosome and the assignment of heterozygous variants to each chromosome copy, the haplotype assembly problem, is of fundamental importance for medical and population genetics. While short reads from second generation sequencing platforms drastically limit haplotype reconstruction as the great majority of reads do not allow to link many variants together, novel long reads from third generation sequencing can span several variants along the genome allowing to infer much longer haplotype blocks. However, the great majority of haplotype assembly algorithms, originally devised for short sequences, fail when they are applied to noisy long reads data, and although novel algorithm have been properly developed to deal with the properties of this new generation of sequences, these methods are capable to manage only datasets with limited coverages. ResultsTo overcome the limits of currently available algorithms, I propose a novel formulation of the single individual haplotype assembly problem, based on maximum allele co-occurrence (MAC) and I develop an ultra-fast algorithm that is capable to reconstruct the haplotype structure of a diploid genome from low- and high-coverage long read datasets with high accuracy. I test my algorithm (MAtCHap) on synthetic and real PacBio and Nanopore human dataset and I compare its result with other eight state-of-the-art algorithms. All the results obtained by these analyses show that MAtCHap outperforms other methods in terms of accuracy, contiguity, completeness and computational speed. AvailabilityMAtCHap is publicly available at https://sourceforge.net/projects/matchap/.

bioinformatics↗

bioRxiv2019

NanoR: An user-friendly R package to analyze and compare nanopore sequencing data

MinION and GridION X5 from Oxford Nanopore Technologies are devices for real-time DNA and RNA sequencing. On the one hand, MinION is the only real-time, low cost and portable sequencing device and, thanks to its unique properties, is becoming more and more popular among biologists; on the other, GridION X5, mainly for its costs, is less widespread but highly suitable for researchers with large sequencing projects. Despite the fact that Oxford Nanopore Technologies devices have been increasingly used in the last few years, there is a lack of high-performing and user-friendly tools to handle the data outputted by both MinION and GridION X5 platforms. Here we present NanoR, a cross-platform R package designed with the purpose to simplify and improve nanopore data visualization. Indeed, NanoR is built on few functions but overcomes the capabilities of existing tools to extract meaningful informations from MinION sequencing data; in addition, as exclusive features, NanoR can deal with GridION X5 sequencing outputs and allows comparison of both MinION and GridION X5 sequencing data in one command. NanoR is released as free package for R at https://github.com/davidebolo1993/NanoR.

bioinformatics↗