Biology subjects

Urbani, A.

Publications and source records attributed to Urbani, A..

4 recordsLinked to original sources

bioRxiv2026

STRmie-HD enables interruption-aware HTT repeat genotyping and somatic mosaicism profiling across sequencing platforms

Short tandem repeat expansions in exon 1 of the HTT gene drive Huntingtons disease (HD) pathogenesis, with disease onset and progression heavily influenced by somatic mosaicism and sequence interruptions. While sequencing technologies enable repeat sizing, many computational tools lack the resolution to capture subtle interruption motifs and allele-specific somatic variation. We present STRmie-HD, an alignment-free, de novo framework for interruption-aware genotyping and quantitative profiling of somatic mosaicism at single-read resolution. The tool parses individual reads to quantify uninterrupted CAG tract length, CCG repeat content, and critical interruption variants, including Loss of Interruption (LOI) and Duplication of Interruption (DOI). Validated across Illumina, PacBio SMRT, and Oxford Nanopore platforms, STRmie-HD demonstrates high concordance with reference genotypes and superior sensitivity in identifying rare interruption patterns that conventional tools often overlook. Furthermore, it implements somatic mosaicism metrics to characterize repeat dynamics, successfully distinguishing the higher somatic expansion burden in brain tissues compared to peripheral blood. STRmie-HD offers a comprehensive and extensible solution for high-resolution molecular characterization of HTT variation, providing a robust framework for patient stratification and genetic research in HD. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/713334v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@17a54aforg.highwire.dtl.DTLVardef@4dcfc5org.highwire.dtl.DTLVardef@8398edorg.highwire.dtl.DTLVardef@1acefde_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract: STRmie-HD flowchart. STRmie-HD is a comprehensive analytical framework that processes sequencing reads to analyze CAG/CCG trinucleotide repeats, interruption variants, and somatic mosaicism in the HTT gene. The workflow begins with sequencing reads (FASTA/FASTQ) that can undergo optional custom processing eq]based on the sequencing design. These reads are then fed into a regular expression-based engine (STRmie-HD) to identify CAG and CCG motifs. The identified motifs lead to the estimation of CAG/CCG alleles, visualized as distinct peaks representing different allele sizes, interruption variant assessment, and somatic mosaicism quantification. STRmie-HD produces an HTML output that wraps this information into a report. C_FIG

bioinformatics↗

bioRxiv2025

nAPOGEE: A machine-learning platform for clinically actionable pathogenicity assessment of all mitochondrial noncoding variants

Mitochondrial noncoding variants, particularly those in tRNA and rRNA genes, pose significant challenges for clinical interpretation due to heteroplasmy, broad phenotypic heterogeneity where symptoms can overlap with other conditions, and the limited availability of well-established genotype-phenotype correlations. Despite their central role in mitochondrial translation, these variants have remained largely unexplored by the existing variant-effect predictors. Here, we present nAPOGEE, a novel machine-learning framework specifically designed to assess the pathogenicity of all possible single-nucleotide variants in human mitochondrial noncoding RNAs. nAPOGEE integrates two specialized predictors: tAPOGEE, which outperforms existing tools for tRNAs, and rAPOGEE, the first dedicated classifier for mitochondrial rRNA variants. Using curated training datasets, phylogenetic conservation metrics, secondary structure modeling, RNA-specific embeddings, and thermodynamic features, nAPOGEE provides biologically interpretable predictions and posterior probabilities aligned with the ACMG/AMP guidelines. Applied to both curated variant sets and population-scale data, nAPOGEE revealed consistent spatial correlation of the predicted pathogenicity, reflecting underlying structural and evolutionary constraints. This study addresses a longstanding gap in mitochondrial genomics and offers a clinically applicable tool for variant prioritization, reclassification, and research into mitochondrial disease mechanisms.

bioinformatics↗

bioRxiv2025

Ultra-performance liquid chromatography-mass spectrometry analysis of post-mortem brain tissue reveals specific amino acid profile dysregulation in Parkinson's Disease and Alzheimer's Disease patients

BackgroundCombined metabolomic and HPLC-based analyses have identified significant metabolic alterations in serum and plasma amino acid levels of Parkinsons disease (PD) patients, underscoring their potential as biomarkers. However, it remains unclear whether these biochemical changes also manifest within the central nervous system or are confined to peripheral metabolism, reflecting systemic metabolic disturbances. MethodsTo address this issue, here we measured the levels of 44 different amino acids in post-mortem brain samples from MPTP-intoxicated, L-DOPA-treated monkeys and PD patients at different Braak Lewy body (LB) stages, compared to their respective controls, through targeted Ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). ResultsIn MPTP-intoxicated monkeys, UPLC-MS revealed significant elevations in GABA, citrulline, threonine, isoleucine, phenylalanine, valine, glycine, and serine in the putamen, whereas we failed to detect alterations in the superior frontal gyrus (SFG). In PD patients, caudate-putamen (CPu) analysis demonstrated consistent serine upregulation across Braak LB stages 3-4 and 6, with stage 6 specifically showing additional proline increases and phosphoethanolamine decreases. Notably, serine was the sole amino acid significantly altered in both the putamen of MPTP-intoxicated monkeys and the CPu of PD patients. No significant amino acid alterations were observed in the SFG of PD patients, mirroring the findings in monkeys. In contrast, Alzheimers disease (AD) patient SFG samples showed significant increases in tryptophan, phenylalanine, threonine, tyrosine, and methionine relative to controls. ConclusionsThese findings demonstrate that cerebral amino acid alterations in PD are region-specific and primarily localized to brain areas receiving nigrostriatal dopaminergic innervation. Moreover, the cortical amino acid profile in AD differs substantially from that in PD, suggesting disease-specific metabolic signatures in distinct neurodegenerative conditions.

neuroscience↗

bioRxiv2021

TRAP1 and cyclophilin D compete at OSCP subunit to regulate enzymatic activity and permeability transition pore opening by F-ATP synthase

Binding of the mitochondrial chaperone TRAP1 to client proteins shapes cell bioenergetic and proteostatic adaptations, but the panel of TRAP1 clients is only partially defined. Here we show that TRAP1 interacts with F-ATP synthase, the protein complex that provides most cellular ATP. TRAP1 competes with the peptidyl-prolyl cis-trans isomerase cyclophilin D (CyPD) for binding to the oligomycin sensitivity-conferring protein (OSCP) subunit of F-ATP synthase, increasing its catalytic activity and counteracting the inhibitory effect of CyPD. Moreover, TRAP1 inhibits opening of the permeability transition pore (PTP) formed by F-ATP synthase and effectively antagonizes the PTP-inducing effect of CyPD, which elicits mitochondrial depolarization and cell death. Consistently, electrophysiological measurements indicate that TRAP1 and CyPD compete in the modulation of channel activity of purified F-ATP synthase, resulting in PTP inhibition and activation, respectively, and outcompeting each other effect on the channel. Moreover, TRAP1 counteracts PTP induction by CyPD, whereas CyPD reverses TRAP1-mediated PTP inhibition. Our data identify TRAP1 as a F-ATP synthase regulator that can influence cell bioenergetics and survival and can be targeted in pathological conditions where these processes are dysregulated, such as cancer.

cell biology↗