Biology subjects

Daniels, N.

Publications and source records attributed to Daniels, N..

4 recordsLinked to original sources

bioRxiv2025

Cell cycle dysregulation contributes to neurodegeneration in humanneurons from ALS/FTD-related C9orf72 repeat expansion carriers.

The C9orf72 hexanucleotide repeat expansion GGGGCC (G4C2) cause the most common genetic forms of ALS and frontotemporal dementia, affecting thousands of patients worldwide with uniformly fatal outcomes. C9orf72 ALS/FTD patients lack targeted treatments because druggable molecular vulnerabilities remain unidentified. Using iPSC-derived motor neurons from C9orf72 carriers and age-matched controls, we performed comprehensive cell cycle analysis, drug screening, and single-nucleus RNA sequencing validation in human brain tissue. C9orf72 neurons exhibit age-dependent cell cycle reentry with increased S-phase cells, elevated cyclin and CDK expression, and aberrant cell cycle gene signatures confirmed in patient brain excitatory neurons. Mechanistically, arginine-containing dipeptide repeat proteins (poly-GR, poly-PR) drive this cell cycle activation through CDK4/6 pathway stimulation, while C9orf72 loss-of-function alone shows no effect. Critically, the FDA-approved CDK4/6 inhibitor palbociclib normalizes cell cycle progression, reduces S-phase entry, and rescues neuronal survival with significant reduction in motor neuron death. Single-nucleus RNA-sequencing analyses from C9orf72 patient cortex reveals cell cycle-activated neuronal subclusters. Copy number variation, gene ontology and pathways analyses revealed alterations in DNA repair pathways, cell cycle regulation and cell cycle transition, validating our in vitro findings. These results identify cell cycle dysregulation as a therapeutic target in C9orf72 ALS/FTD with clinical translation potential using existing therapeutics.

neuroscience↗

bioRxiv2021

Transfer of Knowledge from Model Organisms to Evolutionarily Distant Non-Model Organisms: The Coral Pocillopora damicornis Membrane Signaling Receptome

With the ease of gene sequencing and the technology available to study and manipulate non-model organisms, the need to translate our understanding of model organisms to non-model organisms has become an urgent problem. For example, mining of large coral and their symbiont sequence data is a challenge, but also provides an opportunity for understanding functionality and evolution of these and other non-model organisms. Much more information than for any other eukaryotic species is available for humans, especially related to signal transduction and diseases. However, the coral cnidarian host and human have diverged over 700 million years ago and homologies between proteins are therefore often in the gray zone or undetectable with traditional BLAST searches. We introduce a two-stage approach to identifying putative coral homologues of human proteins. First, through remote homology detection using Hidden Markov Models, we identify candidate human homologues in the cnidarian genome. However, for many proteins, the human genome alone contains multiple family members with similar or even more divergence in sequence. In the second stage, therefore, we filter the remote homology results based on the functional and structural plausibility of each coral candidate, shortlisting the coral proteins likely to be true human homologues. We demonstrate our approach with a pipeline for mapping membrane receptors in humans to membrane receptors in corals, with specific focus on the stony coral, P. damicornis. More than 1000 human membrane receptors mapped to 335 coral receptors, including 151 G protein coupled receptors (GPCRs). To validate specific sub-families, we chose opsin proteins, representative GPCRs that confer light sensitivity, and Toll-like receptors, representative non-GPCRs, which function in the immune response, and their ability to communicate with microorganisms. Through detailed structure-function analysis of their ligand-binding pockets and downstream signaling cascades, we selected those candidate remote homologues likely to carry out related functions in the corals. This pipeline may prove generally useful for other non-model organisms, such as to support the growing field of synthetic biology.

bioinformatics↗

bioRxiv2017

Neural Representations Behind Social Norm Inferences In Humans

Humans are highly skilled in social reasoning, e.g., inferring thoughts of others. This mentalizing ability systematically recruits brain regions such as Temporo-Parietal Junction (TPJ), Precuneus (PC) and medial Prefrontal Cortex (mPFC). Further, posterior mPFC is associated with allocentric mentalizing and conflict monitoring while anterior mPFC is associated with self-related mentalizing. Here we extend this work to how we reason not just about what one person thinks but about the abstract shared social norm. We apply functional magnetic resonance imaging to investigate neural representations while participants judge the social congruency between emotional auditory in relation to visual scenes according to how most people would perceive it. Behaviorally, judging according to a social norm increased the similarity of response patterns among participants. Multivoxel pattern analysis revealed that social congruency information was not represented in visual and auditory areas, but was clear in most parts of the mentalizing network: TPJ, PC and posterior (but not anterior) mPFC. Furthermore, interindividual variability in anterior mPFC representations was inversely related to the behavioral ability to adjust to the social norm. Our results suggest that social norm inferencing is associated with a distributed and partially individually specific representation of social congruency in the mentalizing network.

neuroscience↗

bioRxiv2017

Multi-method brain imaging reveals impaired representations as well as altered connectivity in adults with dyscalculia

Two hypotheses have been proposed about the etiology of neurodevelopmental disorders: representation impairments versus disrupted access to representations. We implemented a multi-method brain imaging approach to directly compare the representation vs. access hypotheses in dyscalculia, a highly prevalent but understudied neurodevelopmental disorder in learning to calculate. We combined several magnetic resonance imaging methods and analyses, including multivariate analyses, functional and structural connectivity, and voxel-based morphometry analysis, in a sample of 24 adults with dyscalculia and 24 carefully matched controls. Results showed a clear deficit in the non-symbolic magnitude representations in parietal, temporal, and frontal regions in dyscalculia. We also observed hyper-connectivity in visual brain regions and increased grey matter volume in the default mode network in adults with dyscalculia. Hence, dyscalculia is related to a combination of diverse neural markers which are altogether distributed across a substantial portion of cerebral cortex, supporting a multifactorial model of this neurodevelopmental disorder.

neuroscience↗