Biology subjects

Ruffini, N.

Publications and source records attributed to Ruffini, N..

3 recordsLinked to original sources

bioRxiv2026

Performance-impacting brain state maladaptation driving disease progression in early mouse and human neuroinflammation

The neuronal mechanisms driving progression in neuroinflammatory disorders from early relapse-remitting phases to later neurodegenerative phases remain largely elusive. Functional brain state shifts towards hyperactivity, persisting beyond relapses, represent an early maladaptive response. Here, in remission stage of an experimental autoimmune encephalitis (EAE) mouse model of RRMS, we identified a reduced excitability upon optogenetic stimulation in the brain stem, the area of active disease, while in the cortex a persistent cortical neuronal hyperactivity and synaptic remodeling emerged, accompanied with an increase of markers of early apoptosis. In contrast, hippocampal circuits, which undergo a functional state shift without hyperactivity, do not show increased apoptosis. Visual cortical networks showed a deterioration of the accuracy of encoding visual information and a decrease in the behavioural visual discrimination ability in mice. In RRMS patients in remission, we identified a reduced visual colour discrimination, indicating both the presence and the clinical relevance of early brain state maladaptation that may contribute to progression independent from relapse activity (PIRA). SummaryIn a RRMS model and in patients, impaired visual processing was reported, indicating brain state maladaptations, associated with persistent cortical hyperactivity, brain stem hypoactivity, synaptic remodeling, and apoptosis. These maladaptations might contribute to relapse-independent disease progression through sustained network dysfunction.

neuroscience↗

bioRxiv2026

Benchmarking ambient RNA removal across droplet and well-plate platforms reveals artificial count generation as a critical failure mode of scAR and CellClear

BackgroundAmbient RNA contamination is a pervasive artifact of single-cell and single-nucleus RNA sequencing (sxRNA-seq), yet no consensus exists on which computational removal tool performs best across experimental platforms. ResultsWe present a systematic benchmark of six tools: CellBender, DecontX, SoupX, scCDC, scAR, and CellClear - evaluated across six human-mouse cell line mixing (hgmm) datasets (1k-20k cells) providing partial ground truth, two droplet-based complex tissue datasets (PBMC scRNA-seq; prefrontal cortex snRNA-seq), and a well-plate-based dataset (BD Rhapsody WBC). Using inter-species counts as partial ground truth, we quantify sensitivity, specificity, precision, and removal consistency per tool. We further apply a count-integrity criterion quantifying gene-cell positions where corrected values exceed raw counts. This reveals that scAR and CellClear do not merely denoise but fundamentally restructure count matrices: CellClear replaces >93% of counts with values derived from matrix factorization, while scAR generates spurious cell types absent from uncorrected data, including three spurious coarse cell types in the BD Rhapsody dataset and up to eight novel cell types in the prefrontal cortex. CellBender and SoupX exhibit reliable contamination removal with minimal count distortion. DecontX and scCDC are the only tools operable on non-droplet platforms without raw count matrix access. Runtime benchmarking at atlas scale (up to 172,000 nuclei) further demonstrates that CellClear fails to scale. ConclusionsCount matrix integrity, not removal sensitivity alone, must be a primary criterion when selecting ambient RNA correction tools. We provide platform-specific recommendations and a decision framework to guide tool selection across experimental contexts.

bioinformatics↗

bioRxiv2023

N1-methylation of adenosine (m1A) in ND5 mRNA leads to complex I dysfunction in Alzheimer's disease

One mechanism of particular interest to regulate mRNA fate post-transcriptionally is mRNA modification. Especially the extent of m1A mRNA methylation is highly discussed due to methodological differences. However, one single m1A site in mitochondrial ND5 mRNA was unanimously reported by different groups. ND5 is a subunit of complex I of the respiratory chain. It is considered essential for the coupling of oxidation and proton transport. Here we demonstrate that this m1A site might be involved in the pathophysiology of Alzheimers disease (AD). One of the pathological hallmarks of this neurodegenerative disease is mitochondrial dysfunction, mainly induced by Amyloid {beta} (A{beta}). A{beta} mainly disturbs functions of complex I and IV of the respiratory chain. However, the molecular mechanism of complex I dysfunction is still not fully understood. We found enhanced m1A methylation of ND5 mRNA in an AD cell model as well as in AD patients. Formation of this m1A methylation is catalyzed by increased TRMT10C protein levels, leading to translation repression of ND5. As a consequence, here demonstrated for the first time, TRMT10C induced m1A methylation of ND5 mRNA leads to mitochondrial dysfunction. Our findings suggest that this newly identified mechanism might be involved in A{beta}-induced mitochondrial dysfunction.

neuroscience↗