Biology subjects

Sella, F.

Publications and source records attributed to Sella, F..

6 recordsLinked to original sources

bioRxiv2025

Early overactivation of non-muscle myosin II during adaptation to combined BRAF and MEK inhibitors in dedifferentiating cutaneous melanomas

Cutaneous melanoma is a very aggressive type of skin cancer with remarkable phenotypic plasticity that contributes to adaptation and resistance to targeted therapies against the MAPK pathway. Previous research described that non-muscle myosin II (NMII) of the actomyosin cytoskeleton, which is essential for cell migration and metastasis, is overactivated in BRAF inhibitor-resistant melanomas. Since the combination of BRAF and MEK inhibitors (BMi) is the current standard of care, we investigated if and how NMII activity is regulated during adaptation to BMi. Here, we find that most dedifferentiating BMi-resistant melanomas overactivate NMII compared to their parental counterparts. NMII activity generally increases during the first 2 weeks of BMi treatment, and it is followed by elevated total NMII levels due partly to transcriptional modulation. Although ERK activity rebounds with similar kinetics, NMII overactivation is not prevented by ERK inhibition but by blockade of ROCK. In melanomas that hyperdifferentiate during adaptation to BMi, NMII activity is not increased upon BMi treatment due, in part, to MITF. We also find that co-targeting NMII along BMi in some melanomas reduces survival of drug-tolerant persister cells, which would delay the development of resistance. Therefore, our study identifies elevated NMII activity as a potential marker of adaptation to MAPK in some melanoma subpopulations, and also provide an approach to delay the emergence of resistance to MAPK-targeted therapy.

cancer biology↗

bioRxiv2024

In vivo single-cell ribosome profiling reveals cell-type-specific translational programs during aging

Somatic stem cells are characterized by their low overall protein synthesis rates, a feature implicated in driving their stemness. However, how aging reshapes the translational landscape of stem cells and how these changes impact their regenerative capacity remains poorly understood. Here, we present an in vivo single-cell ribosome profiling strategy to monitor tissue-wide translational landscapes of the young and aged mouse epidermis. By implementing ribosomal elongation-inhibited cell isolation and switching to RNase I ribonuclease for generating ribosomal footprints, we expand the applicability of single-cell ribosome profiling to in vivo systems and facilitate the evaluation of triplet periodicity, a hallmark of high-quality ribosome profiling data. Leveraging this strategy and integrating ribosome profiling with single-cell RNA sequencing, we document the in vivo translational landscapes of the major epidermal cell types, outline cell-type-specific translational efficiencies and capture heterogeneity in differentiation commitment within stem cell populations. Notably, we identify a pronounced translational reprogramming of AP-1 subunits specifically in aged epidermal stem cells, with functional consequences for keratinocyte behavior. Our study illustrates the power of in vivo single-cell ribosome profiling to map cell-type-specific translational programs and offers a scalable strategy for tissue-wide interrogation of translational landscapes at single-cell resolution.

genomics↗

bioRxiv2022

Dissecting the chain of information processing and its interplay with neurochemicals and fluid intelligence across development

Previous research has highlighted the role of glutamate and gamma-aminobutyric acid (GABA) in perceptual, cognitive, and motor tasks. However, the exact involvement of these neurochemical mechanisms in the chain of information processing, and across human development, are unclear. In a cross-sectional longitudinal design, we used a computational approach to dissociate cognitive, decision, and visuomotor processing in 293 individuals spanning early childhood to adulthood. We found that glutamate and GABA within the intraparietal sulcus (IPS) explained unique variance in visuomotor processing, with higher glutamate predicting poorer visuomotor processing in younger participants but better visuomotor processing in mature participants, while GABA showed the opposite pattern. These findings were functionally, neuroanatomically, and neurochemically specific, and were replicated ~1.5 years later and were generalized in two further different behavioral tasks. Using resting fMRI, we revealed that the relationship between IPS neurochemicals and visuomotor processing is mediated by functional connectivity in the visuomotor network. We then extended our findings to high-level cognitive behavior by predicting fluid intelligence performance. We showed that fluid intelligence performance is explained by IPS GABA and glutamate and is mediated by visuomotor processing, and moderated by the developmental stage. These results provide an integrative biological and psychological mechanistic explanation that links cognitive processes and neurotransmitters across human development and establishes their involvement in intelligent behavior.

neuroscience↗

bioRxiv2022

Explaining and Predicting the Effects of Neurostimulation via Neuronal Excitation/Inhibition

Previous research has highlighted the role of the excitation/inhibition ratio (E/I) for typical and atypical development, mental health, cognition, and learning. Other research has highlighted the benefits of high-frequency random noise stimulation (tRNS)--an excitatory form of neurostimulation--on learning. We examined the E/I as a potential mechanism and studied whether tRNS effect on learning depends on E/I as measured by the aperiodic exponent as its putative marker. In addition to manipulating E/I using tRNS, we also manipulated the level of learning (learning/overlearning) that has been shown to influence E/I. Participants (n=102) received either sham stimulation or 20 min tRNS over the dorsolateral prefrontal cortex (DLPFC) during a mathematical learning task. We showed that tRNS increased E/I, as reflected by the aperiodic exponent, and that lower E/I predicted greater benefit from tRNS specifically for the learning task. In contrast to previous Magnetic Resonance Spectroscopy-based E/I studies, we found no effect of the level of learning on E/I. A further analysis using a different data set suggest that both measures of E/I (EEG vs MRS) may reflect, at least partly, different biological mechanisms. Our results highlight the role of E/I as a marker for neurostimulation efficacy and learning. This mechanistic understanding provides better opportunities for augmented learning and personalized interventions.

neuroscience↗

bioRxiv2020

How can noise alter neurophysiology in order to improve human behaviour? A combined transcranial random noise stimulation and electroencephalography study

Random noise has been shown to improve the detection of suboptimal signals in humans and machines. Based on that, transcranial random noise stimulation (tRNS) has aimed to improve human behaviour by targeting neuronal activity. To uncover the poorly understood mechanistic underpinnings of tRNS, we recorded electroencephalography data during arithmetic training while delivering active or sham tRNS above the dorsolateral prefrontal cortex (dlPFC). By successfully removing the tRNS artefact in the time and frequency domains, we examined the mechanisms that underlie its behavioural improvement. We found that active tRNS improved arithmetic performance and impacts specific ERPs components that are associated with attentional mechanisms. Furthermore, the tRNS effect was maximal in individuals with suboptimal arithmetic ability and neurophysiological measures of top-down control and excitation/inhibition ratio. These results providing a novel mechanistic explanation for the effect of tRNS on human behaviour and highlight how suboptimal task-specific behaviour and neurophysiology predicts its effect.

neuroscience↗

bioRxiv2017

The Neurocognitive Architecture of Individual Differences in Math Anxiety in Typical Children

Math Anxiety (MA) is characterized by a negative emotional response when facing math-related situations. MA is distinct from general anxiety and can emerge during primary education. Prior studies typically comprise adults and comparisons between high-versus low-MA, where neuroimaging work has focused on differences in network activation between groups when completing numerical tasks. The present study used voxel-based morphometry to identify the structural brain correlates of MA in a sample of 79 healthy children aged 7-12 years. Given that MA is thought to develop in later primary education, the study focused on the level of MA, rather than categorically defining it as present or absent. Using a battery of cognitive- and numerical-function tasks, this study identified that increased MA was associated with reduced attention, working memory and math achievement. Increased MA was associated with reduced grey matter in the left anterior intraparietal sulcus. This region was also associated with attention, suggesting that baseline differences in morphology may underpin attentional differences. Future studies should clarify whether poorer attentional capacity due to reduced grey matter density results in the later emergence of MA. Further, our data highlight the role of working memory in propagating reduced math achievement in children with higher MA.

neuroscience↗