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George, N.

Publications and source records attributed to George, N..

At least 19 recordsLinked to original sources

Transcription factor co-occupancy shapes the somatic mutational landscapes across regulatory regions in liver cancer

Both global and local chromatin structure influence the heterogeneous distribution of somatic mutations across the cancer genome. For instance, at the local scale, DNA regions bound by transcription factors (TF) and other chromatin-associated proteins display elevated somatic mutation rates, due to variable DNA damage and repair at these protein-bound sites. However, the contribution of TF co-binding towards the variations in somatic mutation rates remains largely unexplored. Here, we combine somatic mutations from whole-genome sequencing of liver cancers with ChIP-seq profiles for over 150 TFs and chromatin-associated proteins in the human liver cancer cell line HepG2, to systematically examine how TF co-occupancy shapes local mutational landscapes. We show that somatic mutation rates at binding sites vary substantially across distinct TFs and co-binding combinations. Furthermore, the magnitude and spatial distribution of somatic mutation rates at TF binding sites differ across promoters and enhancers, likely influenced by the local chromatin accessibility and architecture. Finally, we identify NFIA (Nuclear Factor IA) as a distinct exception, maintaining elevated mutation rates across its binding sites independent of local co-binding context. Together, these findings reveal that combinatorial TF co-occupancy and local chromatin architecture are associated with differences in somatic mutation rates across regulatory regions in liver cancer.

genomics↗

Episodic memory ERPs reflect preclinical Alzheimers disease progression

Structured AbstractO_ST_ABSBackgroundC_ST_ABSAlzheimers disease (AD) neuropathology emerges decades before symptoms, requiring sensitive, non-invasive markers for early diagnosis. We investigated behavioural and EEG markers of episodic memory in cognitively normal older adults at-risk for AD. MethodsForty-five INSIGHT-preAD cohort participants (15 progressors to prodromal AD, 15 stable {beta}-amyloid positive [A{beta}+] participants, 15 controls [A{beta}-]) completed an Old/New word recognition task during high-density EEG. Behavioural performance and memory-related evoked-related potentials (ERPs; P3, FN400, P600, post-retrieval monitoring) were analysed longitudinally over 5 years. ResultsProgressors showed significantly reduced accuracy, sensitivity, and slower responses. They showed attenuated FN400, P600, and monitoring amplitudes over left parieto-occipital regions. Source analysis revealed hypoactivation in the left inferior frontal and right posterior cingulate cortex, across components with additional disruption during P600. Stable A{beta}+ individuals showed milder P600 hypoactivations. DiscussionBehavioural and ERP alterations preceded clinical decline, supporting EEG-based markers of episodic memory decline for preclinical AD risk stratification.

neuroscience↗

Distinct roles of the human cuneiform and pedunculopontine nuclei in gait initiation and freezing of gait

Freezing of gait in Parkinsons disease (PD) is a major cause of disability, often resistant to dopaminergic therapy and deep brain stimulation (DBS). Its underlying mechanisms remain unclear, mainly because the roles of the human mesencephalic locomotor region (MLR) nuclei are not well understood. Here, we combined rare local field potentials (LFP) recordings from the cuneiform (CuN) and pedunculopontine nuclei (PPN) with biomechanical markers of gait initiation (GI) in four PD patients. We identified functional differences: increases in CuN alpha-band activity precede anticipatory postural adjustments (APA) and correlate with the rhythm of upcoming steps, whereas decreases in PPN beta-band activity occur during APA just before the lead foot lifts off. Imminent freezing is characterized by a breakdown of this organization, marked by mistimed alpha-band surges across the MLR and abnormal PPN beta-band modulation. CuN stimulation selectively improved the stepping rhythm, while PPN stimulation worsened pace or forward vigor. Furthermore, exaggerated mesencephalic alpha-band power was associated with poor clinical responses. These results clarify the individual roles of MLR nuclei in human locomotion and identify pathological alpha dynamics as a biomarker for advancing adaptive neurostimulation.

neuroscience↗

Cortical beta coherence provides a stronger non-invasive predictor of movement vigor than local beta power

BackgroundMovement elicits a robust decrease in motor cortical beta-band ({beta}; 13-30 Hz) power contralateral to the moving limb. On this basis, studies have targeted contralateral motor cortical {beta} power to decode or modulate movement vigor (initiation and execution speed) non-invasively. Yet, reported behavioral effects and decoding accuracy remain modest. Considering that controlling vigor involves distributed brain regions, network-level metrics that capture interactions between cortical regions may track changes in vigor more accurately than local power. We therefore tested whether {beta} cortico-cortical coherence, measured as functional connectivity between contralateral motor cortex and other cortical areas, predicts movement vigor more reliably than {beta} power. MethodsThirty healthy participants performed right hand opening at two instructed speeds (Fast, Slow), while high-density electroencephalography (EEG) was recorded. EEG data were source-localized, and analyses were conducted at the sensor and source levels. We compared {beta} power and {beta} coherence in their ability to discriminate Fast from Slow condition. Effects were assessed across the whole scalp/cortex and using subject-specific selections of electrodes/parcels optimized for discrimination. ResultsFast trials exhibited shorter movement time (MT) and reaction time (RT) than Slow trials, indicating higher vigor. No electrodes cluster showed any significant {beta} power difference between Fast and Slow conditions. With subject-specific channel selection, {beta} power discriminated vigor above chance in most participants, but the polarity of the {beta} power contrast (Fast < Slow or Fast > Slow) varied across individuals. In contrast, with subject-specific parcel selection, {beta} coherence was consistently reduced during Fast relative to Slow in the majority of participants. Across participants, lower {beta} coherence, but not {beta} power, was significantly associated with larger Slow-Fast vigor difference. Conclusions{beta} cortico-cortical coherence between contralateral motor cortex and other cortical regions provided a more robust and consistent predictor of movement vigor than contralateral motor cortical {beta} power. {beta} coherence exhibited a sustained reduction during fast movements across trials and participants, supporting its use as target for non-invasive neuromodulation of vigor and as feature for decoding intended movement speed.

neuroscience↗

Planetary-scale metagenomic search reveals new patterns of CRISPR targeting

Interactions between microbes and their mobile genetic elements (MGEs), including viruses and plasmids, are critical drivers of microbiome structures and processes. CRISPR-Cas systems are important regulators of these host-MGE interactions, but a global understanding of CRISPR loci diversity, activity, and roles across Earths biomes is still lacking. Here, we use an optimized computational approach to search short-read data and collect [~]800 million CRISPR spacers across [~]450,000 public metagenomes. From this extensive CRISPR spacer dataset, we identified 1.18 billion hits between 41 million spacers and 2.5 million viruses and plasmids. Focusing on the role of CRISPR as anti-phage defense, we observed an over-representation of prevalent and conserved spacers consistent with a positive selection pressure associated with phage targeting. Identification of sustained CRISPR targeting by microbes not expected to be viable hosts suggested that some phage genomes may frequently enter non-host microbial cells. Taken together, these results outline the extensive diversity of CRISPR loci across microbiomes, and highlight key parameters driving CRISPR targeting patterns likely to influence strain-level diversification and selection processes within microbial populations.

microbiology↗

Motor cortical beta power reflects adaptation to task constraints

The amplitude of beta-band activity ({beta} power; 13-30 Hz) over motor cortical regions is used to assess and decode movement in clinical settings and brain-computer interfaces, as {beta} power is often assumed to predict the strength of the brains motor output, or "vigor". However, recent conflicting evidence challenges this assumption and underscores the need to clarify the relationship between {beta} power and movement. In this study, sixty participants were trained to self-regulate {beta} power using electroencephalography-based neurofeedback before performing different motor tasks. Results showed that {beta} power modulations can impact different motor variables, or the same variables in opposite directions, depending on task constraints. Importantly, downregulation of {beta} power was associated with better task performance regardless of whether performance implied increasing or decreasing motor vigor. These findings demonstrate that {beta} power should be interpreted as a measure of motor flexibility, which underlies adaptation to environmental constraints, rather than vigor.

neuroscience↗

Development of a p62 biodegrader for autophagy targeted degradation

Harnessing autophagy for targeted degradation is a promising extension to proteasome-based targeted protein degradation because of the capacity and versatility of lysosomes to degrade large and complex cargo, thus broadening the scope of therapeutic targets. While small-molecule degraders recruiting the autophagy machinery to targets are starting to emerge, it remains unclear which component of the autophagy lysosomal pathway is most efficacious to induce selective target degradation. Here, we describe two orthogonal induced-proximity strategies to identify and prioritize autophagy effectors that are sufficient to degrade organelles as well as soluble targets. We show that induced proximity of different effectors such as autophagy cargo receptors, ATG8-like proteins or the kinases ULK1 and TBK1 are sufficient to trigger mitophagy. In contrast, self-oligomerizing autophagy cargo receptors outperform ATG8- like effectors and autophagy-related kinases in clearing a soluble cytosolic protein. We further explore the importance of avidity for targeted degradation via autophagy and reveal that the PB1 domain of p62 fused to a LIR peptide is a minimal degron to induce the degradation of mitochondria as well as cytosolic proteins. By developing a novel and highly selective intrabody against the autophagy cargo receptor p62 into a heterobifunctional degrader, we demonstrate that recruitment of endogenous p62 is sufficient to clear mitochondria. This biodegrader, however, is unable to induce degradation of soluble cytosolic proteins due to its inhibitory effect on p62 self-oligomerization. Our study highlights the importance of avidity and suggests that autophagy cargo receptors are attractive entry points for the development of heterobifunctional degraders for complex targets such as organelles or protein aggregates.

synthetic biology↗

Agency accounts for the effect of FB transparency onmotor imagery neurofeedback performance

ObjectiveNeurofeedback (NF) is a cognitive training procedure based on real-time feedback (FB) of a participants brain activity that they must learn to self-regulate. A classical visual FB delivered in a NF task is a filling gauge reflecting a measure of brain activity. This abstract visual FB is not transparently linked--from the subjects perspective--to the task performed (e.g., motor imagery). This may decrease the sense of agency, that is, the participants reported control over FB. Here, we assessed the influence of FB transparency on NF performance and the role of agency in this relationship. ApproachParticipants performed a NF task using motor imagery to regulate brain activity measured using electroencephalography. In separate blocks, participants experienced three different conditions designed to vary transparency: FB was presented as either 1) a swinging pendulum, 2) a clenching virtual hand, 3) a clenching virtual hand combined with a motor illusion induced by tendon vibration. We measured self-reported agency and user experience after each NF block. Main resultsWe found that FB transparency influences NF performance. Transparent visual FB provided by the virtual hand resulted in significantly better NF performance than the abstract FB of the pendulum. Surprisingly, adding a motor illusion to the virtual hand significantly decreased performance relative to the virtual hand alone. When introduced in incremental linear mixed effect models, self-reported agency was significantly associated with NF performance and it captured the variance related to the effect of FB transparency on NF performance. SignificanceOur results highlight the relevance of transparent FB in relation to the sense of agency. This is likely an important consideration in designing FB to improve NF performance and learning outcomes.

neuroscience↗

Measuring brain critical dynamics to inform Brain-Computer Interfaces

Large-scale interactions among multiple brain regions manifest as bursts of activations called neuronal avalanches, which reconfigure according to the task at hand and, hence, might constitute natural candidates to design brain-computer interfaces (BCI). To test this hypothesis, we used source-reconstructed magneto/electroencephalography, during resting state and a motor imagery task performed within a BCI protocol. To track the probability that an avalanche would spread across any two regions we built an avalanche transition matrix (ATM) and demonstrated that the edges whose transition probabilities significantly differed between conditions hinged selectively on premotor regions in all subjects. Furthermore, we showed that the topology of the ATMs allows task-decoding above the current gold standard. Hence, our results suggest that Neuronal Avalanches might capture interpretable differences between tasks that can be used to inform brain-computer interfaces.

neuroscience↗

Theta band-power shapes amyloid-driven longitudinal EEG changes in pre-clinical Alzheimer's Disease

Alzheimers Disease (AD) includes progressive symptoms spread along a continuum of pre-clinical (pre-AD) and clinical stages. Pre-AD refers to cognitively healthy individuals with presence of positive pathophysiological biomarkers of AD (i.e., markers of amyloidopathy and tauopathy). Although numerous studies uncovered the neuro-cognitive changes of AD, very little is known on the natural history of brain lesions and modifications of brain networks of pre-AD. To address this issue, we analysed resting-state EEG data of 318 cognitively healthy individuals with subjective memory complains from the INSIGHT-preAD cohort at the time of their first visit (M0) and two-years later (M24). Using 18F-florbetapir PET-scanner, subjects were stratified between amyloid positive (A-; n=230) and amyloid negative (A+; n=88) groups. Differences between A+ and A- individuals were estimated at source level in each band of the EEG power spectrum. At M0, we found an increase of theta-band power in the mid-frontal cortex in A+ compared to A-. No significant association was found between mid-frontal theta power and the individuals cognitive performance. While the very same effect was not replicated at M24, theta-band power increased in A+ relative to A- individuals in the posterior cingulate cortex and the pre-cuneus. Furthermore, alpha band revealed a peculiar decremental trend in posterior brain regions in the A+ relative to the A- group only at M24. These results provide the first source-level longitudinal evidence on the impact of brain amyloidosis on the EEG dynamics of a large-scale, monocentric cohort of pre-AD. Theta-band power increase over the mid-frontal and mid-posterior cortices suggests an hypoactivation of the default-mode network in individuals at-risk of AD and a non-linear longitudinal progression of the AD-spectrum.

neuroscience↗

Why Are Alzheimer's Disease Patients Unaware of their Memory Deficits?

Anosognosia, or the lack of awareness of ones own impairment, is frequent for memory deficits in patients with Alzheimers disease (AD). Although often related to frontal dysfunctions, the neural mechanisms of anosognosia remain largely unknown. We hypothesized that anosognosia in AD may result from a failure in the error-monitoring system, thus preventing patients from being aware of and learning from their own errors. We therefore investigated the event-related potentials evoked by erroneous responses during a memory task in two groups of amyloid positive individuals who had only subjective memory complaints at study entry: 1) those who progressed to AD; and 2) those who remained cognitively normal after five years of follow-up. Our findings revealed direct evidence of a failure in the error-monitoring system at early stages of AD, suggesting that it may be the critical neural substrate of anosognosia in this neurodegenerative disorder.

neuroscience↗

Integrated view and comparative analysis of baseline protein expression in mouse and rat tissues

The increasingly large amount of proteomics data in the public domain enables, among other applications, the combined analyses of datasets to create comparative protein expression maps covering different organisms and different biological conditions. Here we have reanalysed public proteomics datasets from mouse and rat tissues (14 and 9 datasets, respectively), to assess baseline protein abundance. Overall, the aggregated dataset contained 23 individual datasets, including a total of 211 samples coming from 34 different tissues across 14 organs, comprising 9 mouse and 3 rat strains, respectively. In all cases, we studied the distribution of canonical proteins between the different organs. The number of canonical proteins per dataset ranged from 273 (tendon) and 9,715 (liver) in mouse, and from 101 (tendon) and 6,130 (kidney) in rat. Then, we studied how protein abundances compared across different datasets and organs for both species. As a key point we carried out a comparative analysis of protein expression between mouse, rat and human tissues. We observed a high level of correlation of protein expression among orthologs between all three species in brain, kidney, heart and liver samples, whereas the correlation of protein expression was generally slightly lower between organs within the same species. Protein expression results have been integrated into the resource Expression Atlas for widespread dissemination. Author summaryWe have reanalysed 23 baseline mass spectrometry-based public proteomics datasets stored in the PRIDE database. Overall, the aggregated dataset contained 211 samples, coming from 34 different tissues across 14 organs, comprising 9 mouse and 3 rat strains, respectively. We analysed the distribution of protein expression across organs in both species. We also studied how protein abundances compared across different datasets and organs for both species. Then we performed gene ontology and pathway enrichment analyses to identify enriched biological processes and pathways across organs. We also carried out a comparative analysis of baseline protein expression across mouse, rat and human tissues, observing a high level of expression correlation among orthologs in all three species, in brain, kidney, heart and liver samples. To disseminate these findings, we have integrated the protein expression results into the resource Expression Atlas.

bioinformatics↗

Time course of EEG power during creative problem-solving with insight or remote thinking

Problem-solving often requires creativity and is critical in everyday life. However, the neurocognitive mechanisms underlying creative problem-solving remain poorly understood. Two mechanisms have been highlighted: forming new connections from and between the problem elements and insight solving (with a sudden realization of a solution). We examined EEG activity during an adapted version of a classical insight problem task, the Remote Associates Test, that requires finding a word connecting three words. It allowed us to explore remoteness in semantic connections (by varying the remoteness of the solution word across trials) and insight solving (identified as a "Eureka" moment reported by the participants). Semantic remoteness was associated with a power increase in alpha band (8-12Hz) in a left parieto-temporal cluster, beta band (13-30Hz) in a right fronto-temporal cluster in the early phase of the task, and theta band (3-7Hz) in frontal cluster before the participants responded. Insight solving was associated with power increase preceding the response in alpha and gamma band (31-60Hz) in left temporal clusters and theta band in a frontal cluster. Source reconstructions show the brain regions associated with these clusters. Overall, our findings shed new light on the dynamic of some of the mechanisms involved in creative problem-solving.

neuroscience↗

An integrated view of baseline protein expression in human tissues

The availability of proteomics datasets in the public domain, and in the PRIDE database in particular, has increased dramatically in recent years. This unprecedented large-scale availability of data provides an opportunity for combined analyses of datasets to get organism-wide protein abundance data in a consistent manner. We have reanalysed 24 public proteomics datasets from healthy human individuals, to assess baseline protein abundance in 31 organs. We defined tissue as a distinct functional or structural region within an organ. Overall, the aggregated dataset contains 67 healthy tissues, corresponding to 3,119 mass spectrometry runs covering 498 samples, coming from 489 individuals. We compared protein abundances between the different organs and studied the distribution of proteins across organs. We also compared the results with data generated in analogous studies. We also performed gene ontology and pathway enrichment analyses to identify organ-specific enriched biological processes and pathways. As a key point, we have integrated the protein abundance results into the resource Expression Atlas, where it can be accessed and visualised either individually or together with gene expression data coming from transcriptomics datasets. We believe this is a good mechanism to make proteomics data more accessible for life scientists.

bioinformatics↗

Implementing the re-use of public DIA proteomics datasets: from the PRIDE database to Expression Atlas

The number of mass spectrometry (MS)-based proteomics datasets in the public domain keeps increasing, particularly those generated by Data Independent Acquisition (DIA) approaches such as SWATH-MS. Unlike Data Dependent Acquisition datasets, the re-use of DIA datasets has been rather limited to date, despite its high potential, due to the technical challenges involved. We introduce a (re-)analysis pipeline for public SWATH-MS datasets which includes a combination of metadata annotation protocols, automated workflows for MS data analysis, statistical analysis, and the integration of the results into the Expression Atlas resource. Automation is orchestrated with Nextflow, using containerised open analysis software tools, rendering the pipeline readily available and reproducible. To demonstrate its utility, we reanalysed 10 public DIA datasets from the PRIDE database, comprising 1,278 SWATH-MS runs. The robustness of the analysis was evaluated, and the results compared to those obtained in the original publications. The final expression values were integrated into Expression Atlas, making SWATH-MS experiments more widely available and combining them with expression data originating from other proteomics and transcriptomics datasets.

bioinformatics↗

A proteomics sample metadata representation for multiomics integration, and big data analysis.

The amount of public proteomics data is increasing at an extraordinary rate. Hundreds of datasets are submitted each month to ProteomeXchange repositories, representing many types of proteomics studies, focusing on different aspects such as quantitative experiments, post-translational modifications, protein-protein interactions, or subcellular localization, among many others. For every proteomics dataset, two levels of data are captured: the dataset description, and the data files (encoded in different file formats). Whereas the dataset description and data file formats are supported by all ProteomeXchange partner repositories, there is no standardized format to properly describe the sample metadata and their relationship with the dataset files in a way that fully allows their understanding or re-analysis. It is left to the users choice whether to provide or not an ad hoc document containing this information. Therefore, in many cases, understanding the study design and data requires going back to the associated publication. This can be tedious and may be restricted in the case of non-open access publications. In many cases, this problem limits the generalization and reuse of public proteomics data. Here we present a standard representation for sample metadata tailored to proteomics datasets produced by the HUPO Proteomics Standards Initiative and supported by ProteomeXchange resources. We repurposed the existing data format MAGE-TAB used routinely in the transcriptomics field to represent and annotate proteomics datasets. MAGETAB-Proteomics defines a set of annotation rules that the datasets submitted to ProteomeXchange should follow, ranging from sample properties to data analysis protocols. We also introduce a crowdsourcing project that enabled the manual curation of over 200 public datasets using MAGE-TAB-Proteomics. In addition, we describe an ecosystem of tools and libraries that were developed to validate and submit sample metadata-related information to ProteomeXchange. We expect that these tools will improve the reproducibility of published results and facilitate the reanalysis and integration of public proteomics datasets.

bioinformatics↗

Selective neuromodulation induced by alpha-based neurofeedback learning: A double-blind randomized study

The neuromodulation induced by neurofeedback training (NFT) remains a matter of debate. Investigating the modulation of brain activity specifically associated with NF requires controlling for multiple factors, such as reward, performance, congruency between task and targeted brain activity. This can be achieved using sham feedback (FB) control condition, equating all aspects of the experiment but the link between brain activity and FB. We aimed at investigating the modulation of individual alpha EEG activity induced by NFT in a double-blind, randomized, sham-controlled study. Forty-eight healthy participants were assigned to either NF (n=25) or control (n=23) group and performed alpha upregulation training (over 12 weeks) with a wearable EEG device. Participants of the NF group received FB based on their individual alpha activity. The control group received the auditory FB of participants of the NF group. An increase of alpha activity across training sessions was observed in the NF group only (p<0.001). This neuromodulation was selective in that it was not observed for theta (4-8Hz) and low beta (13-18Hz) activities. While alpha upregulation was found in the NF group only, psychological outcome variables showed increased feeling of control, decreased anxiety level and increased relaxation feeling in both the NF and control groups, without any significant difference between groups. This is interpreted in terms of learning context and placebo effects. Our results pave the way to self-learnt, NF-based neuromodulation with light-weighted, wearable EEG systems.

neuroscience↗

Visual information routes in the posterior dorsal and ventral face network studied with intracranial neurophysiology, and white matter tract endpoints

Occipito-temporal regions within the face network process perceptual and socio-emotional information, but the dynamics and information flow between different nodes of this network is still debated. Here, we analyzed intracerebral EEG from 11 epileptic patients viewing a stimulus sequence beginning with a neutral face with direct gaze. The gaze could avert or remain direct, while the emotion changed to fearful or happy. N200 field potential peak latencies indicated that face processing begins in inferior occipital cortex and proceeds anteroventrally to fusiform and inferior temporal cortices, in parallel. The superior temporal sulcus responded preferentially to gaze changes with augmented field potential amplitudes for averted versus direct gaze, and large effect sizes relative to other network regions. An overlap analysis of posterior white matter tractography endpoints (from 1066 healthy brains) relative to active intracerebral electrodes in the 11 patients showed likely involvement of both dorsal and ventral posterior white matter pathways. Overall, our data provide new insight on the timing of face and social cue processing in the occipito-temporal brain and anchor the superior temporal cortex in dynamic gaze processing.

animal behavior and cognition↗