Biology subjects

Hornstein, E.

Publications and source records attributed to Hornstein, E..

12 recordsLinked to original sources

bioRxiv2025

Ubiquitination regulates granulostasis and DRiP accumulation in SGs under heat stress via the E3 ligase MKRN2

Stress granules (SGs) are transient cytoplasmic biomolecular condensates that play a role in the cellular response to proteotoxic stress. It has been previously shown that ubiquitination regulates SG dynamics; however, the specific mechanisms by which ubiquitin affects SGs are not fully understood. Here, using proximity proteomics, we discover that the engagement of several E3 ubiquitin ligases in SGs is dependent on UBA1 activity. A detailed study of the E3 ubiquitin-protein ligase Makorin 2 (MKRN2) demonstrated that it is localized to SGs in a manner dependent on active ubiquitination. MKRN2 promotes both the proper formation of SGs and their disassembly following stress recovery, by preventing the accumulation of defective ribosomal products (DRiPs) within SGs. Therefore, MKRN2 is a novel regulator of SGs that mediates the maintenance of granulostasis, suggesting that the localization of a subset of E3 ligases into SGs is linked to their capacity to ubiquitinate target proteins.

cell biology↗

bioRxiv2025

TDP-43 pathology triggers SRRM4-dependent cryptic splicing of G3BP1 in ALS/FTD

Loss of nuclear TDP-43 is a defining feature of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), yet how this leads to selective neuronal vulnerability is poorly understood. Here, using human iPSC-derived neurons and a large multi-omics dataset of ALS/FTD patients, we demonstrate that TDP-43 pathology induces the inclusion of an in-frame cryptic exon in human G3BP1. The resulting CRYPTIC G3BP1 protein contains an additional 10-amino acids within the highly conserved NTF2L domain, which acts as a dominant negative and disrupts stress granule dynamics. We further show that cryptic exon inclusion in G3BP1 upon TDP-43 loss is enriched in neurons. Mechanistically, the loss of TDP-43 unmasks a binding site for the neuron-specific splicing regulator SRRM4 within intron 2 of G3BP1, enabling the inclusion of the cryptic exon. Collectively, our findings reveal that neuron-specific regulatory mechanisms intersect with TDP-43 -mediated splicing and suggest a mechanistic basis for the increased neuronal vulnerability observed in ALS/FTD.

neuroscience↗

bioRxiv2025

Extracellular Vesicles Mediate Glucose Regulation by GLUT4-Overexpressing Engineered Muscle Tissue in T2D Mice

1Type 2 diabetes (T2D) is characterized by impaired glucose uptake in skeletal muscle and adipose tissues, which contributes to systemic hyperglycemia. GLUT4 is a crucial component in insulin-stimulated glucose uptake and its expression as well as translocation are impaired in T2D onset. This study explored the role of extracellular vesicles (EVs) derived from GLUT4-overexpressing engineered muscle constructs (G4OE-EMC) in glucose metabolism. G4OE-EMC-derived EVs enhanced glucose uptake and insulin sensitivity both in vitro, when tested on wild-type (WT) engineered muscle constructs, and in vivo using the diet-induced obesity (DIO) mouse model. Proteomic and transcriptomic analyses revealed that the EVs were enriched in IGF1 and contained reduced levels of miRNAs, such as miR-122-5p, miR-16-5p, and miR-486-5p, which target IGF1R. The multi-omic approach used here suggests a mechanism whereby G4OE-EMC-derived EVs enhance glucose metabolism via IGF1 signaling and miRNA-mediated regulation of IGF1R expression, offering a potential therapeutic strategy for T2D.

bioengineering↗

bioRxiv2025

TDP-43 toxic gain of function links ALS/FTLD-TDP and Alzheimer's Disease through splicing

Loss of nuclear TDP-43 splicing activity is a common feature across neurodegenerative diseases including amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD), but its relevance to Alzheimers disease (AD) remains unclear. Here, we show that TDP-43 pathology in AD is broadly associated with splicing abnormalities, including aberrant splicing of amyloid precursor protein (APP). TDP-43 drives the formation of elongated APP isoforms, disrupting alternative splicing across ALS, FTLD-TDP and AD, providing a compelling mechanism for a long-standing observation of APP isoform dysregulation. We further establish a mechanistic link between TDP-43, APP splicing, and A{beta} pathology. Surprisingly, the disruption to alternative APP splicing is mediated by a toxic gain of cytoplasmic TDP-43 function, rather than loss of its nuclear role. Using proximity proteomics and base editing in human iPSC-derived neurons, we show that TDP-43 pathology causes cytoplasmic co-sequestration of splicing regulators SCAF11, SRSF5, and TIAL1. Knockdown of these regulators also results in APP mis-splicing and increased A{beta} burden, without affecting other TDP-43 targets such as STMN2 or UNC13A. Together, our findings suggest that TDP-43-mediated splicing dysfunction upstream of APP contributes to the pathogenesis of seemingly disparate neurodegenerative diseases, uniting AD and ALS/FTLD-TDP through a shared molecular mechanism.

neuroscience↗

bioRxiv2024

predicTTE: An accessible and optimal tool for time-to-event prediction in neurological diseases

Time-to-event prediction is a key task for biological discovery, experimental medicine, and clinical care. This is particularly true for neurological diseases where development of reliable biomarkers is often limited by difficulty visualising and sampling relevant cell and molecular pathobiology. To date, much work has relied on Cox regression because of ease-of-use, despite evidence that this model includes incorrect assumptions. We have implemented a set of deep learning and spline models for time-to-event modelling within a fully customizable app and accompanying online portal, both of which can be used for any time-to-event analysis in any disease by a non-expert user. Our online portal includes capacity for end-users including patients, Neurology clinicians, and researchers, to access and perform predictions using a trained model, and to contribute new data for model improvement, all within a data-secure environment. We demonstrate a pipeline for use of our app with three use-cases including imputation of missing data, hyperparameter tuning, model training and independent validation. We show that predictions are optimal for use in downstream applications such as genetic discovery, biomarker interpretation, and personalised choice of medication. We demonstrate the efficiency of an ensemble configuration, including focused training of a deep learning model. We have optimised a pipeline for imputation of missing data in combination with time-to-event prediction models. Overall, we provide a powerful and accessible tool to develop, access and share time-to-event prediction models; all software and tutorials are available at www.predictte.org.

neuroscience↗

bioRxiv2024

Organellomics: AI-driven deep organellar phenotyping of human neurons

Systematic assessment of organelle architectures, termed the organellome, offers valuable insights into cellular states and pathomechanisms, but remains largely uncharted. Here, we present a deep phenotypic learning based on vision transformers, resulting in the Neuronal Organellomics Vision Atlas (NOVA) model that studies confocal images of more than 30 markers of distinct membrane-bound and membraneless organelles in 11.5 million images of human neurons. Organellomics analysis quantifies perturbation-induced changes in organelle localization and morphology using a rigorous mixed-effects meta-analytic framework that accounts for sampling variance and experimental heterogeneity. Applying this approach, we delineate phenotypic alterations in neurons carrying ALS-associated mutations and uncover a physical and functional crosstalk between cytoplasmic mislocalized TDP-43, a hallmark of ALS, and processing bodies (P-bodies), membraneless organelles regulating mRNA stability. These findings are validated in patient-derived neurons and human neuropathology. NOVA establishes a scalable framework for quantitative mapping of subcellular phenotypes and provides a new avenue for investigating the neurocellular basis of disease.

systems biology↗

bioRxiv2021

Non-Coding Genetic Analysis Implicates Interleukin 18 Receptor Accessory Protein 3'UTR in Amyotrophic Lateral Sclerosis

The non-coding genome is substantially larger than the protein-coding genome but is largely unexplored by genetic association studies. Here, we performed region-based burden analysis of >25,000 variants in untranslated regions of 6,139 amyotrophic lateral sclerosis (ALS) whole-genomes and 70,403 non-ALS controls. We identified Interleukin-18 Receptor Accessory Protein (IL18RAP) 3'UTR variants significantly enriched in non-ALS genomes, replicated in an independent cohort, and associated with a five-fold reduced risk of developing ALS. Variant IL18RAP 3'UTR reduces mRNA stability and the binding of RNA-binding proteins. Variant IL18RAP 3'UTR further dampens neurotoxicity of human iPSC-derived C9orf72-ALS microglia that depends on NF-{kappa}B signaling. Therefore, the variant IL18RAP 3'UTR provides survival advantage for motor neurons co-cultured with C9-ALS microglia. The study reveals direct genetic evidence and therapeutic targets for neuro-inflammation, and emphasizes the importance of non-coding genetic association studies. One Sentence SummaryNon-coding genetic variants in IL-18 receptor 3UTR decrease ALS risk by modifying IL-18-NF-{kappa}B signaling in microglia.

neuroscience↗

bioRxiv2021

Physically interacting beta-delta pairs in the regenerating pancreas revealed by single cell sequencing

The endocrine pancreas is able to regenerate in response to insult, including by driving beta-cells into the cell division cycle. Until recently, communication between neighboring cells in islets of Langerhans was overlooked by single-cell genomic technologies, which require rigorous tissue dissociation into single cells. Here, we utilize sorting of physically interacting cells (PICs) with single-cell RNA-sequencing to systematically map cellular interactions in the regenerating endocrine pancreas. The cellular landscape of the regenerated pancreas features regeneration-associated endocrine populations. We explore the unexpected heterogeneity of beta-cells in regeneration, including an interaction-specific program between paired beta and delta-cells. Our analysis suggests that the particular cluster of beta-cells that pair with delta-cells benefits from stress protection, implying that the interaction between beta and delta-cells safeguards against regeneration-associated challenges.

cell biology↗

bioRxiv2020

A nuclear role for ARGONAUTE-2 in regulation of neuronal alternative polyadenylation

Argonaute 2 (AGO2), the effector protein partner of microRNAs (miRNAs) in the cytoplasmic RNA induced silencing complex, is further involved in nuclear RNA processing. However, a role for AGO2 in regulation of alternative polyadenylation was not yet demonstrated. Here, we reveal unexpected abundance of AGO2 in mouse neuronal nuclei and characterize nuclear AGO2 interactors by mass spectrometry. We discover that AGO2 broadly regulated alternative polyadenylation (APA) in neuronal cells. Specifically, we demonstrate how two isoforms of Ret mRNA, which encodes a receptor tyrosine kinase are regulated by AGO2-depenent APA, affecting downstream GDNF signaling in primary motor neurons.

cell biology↗

bioRxiv2020

Genome-wide Identification of the Genetic Basis of Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is an archetypal complex disease centered on progressive death of motor neurons. Despite heritability estimates of 52%, GWAS studies have discovered only seven genome-wide significant hits, which are relevant to <10% of ALS patients. To increase the power of gene discovery, we integrated motor neuron functional genomics with ALS genetics in a hierarchical Bayesian model called RefMap. Comprehensive transcriptomic and epigenetic profiling of iPSC-derived motor neurons enabled RefMap to systematically fine-map genes and pathways associated with ALS. As a significant extension of the known genetic architecture of ALS, we identified a group of 690 candidate ALS genes, which is enriched with previously discovered risk genes. Extensive conservation, transcriptome and network analyses demonstrated the functional significance of these candidate genes in motor neurons and disease progression. In particular, we observed a genetic convergence on the distal axon, which supports the prevailing view of ALS as a distal axonopathy. Of the new ALS genes we discovered, we further characterized KANK1 that is enriched with coding and noncoding, common and rare ALS-associated genetic variation. Modelling patient mutations in human neurons reduced KANK1 expression and produced neurotoxicity with disruption of the distal axon. RefMap can be applied broadly to increase the discovery power in genetic association studies of human complex traits and diseases.

genomics↗

bioRxiv2020

Spatio-temporal Proteomic Analysis of Stress Granule disassembly using APEX Reveals Regulation by SUMOylation and links to ALS pathogenesis

Cytoplasmic stress granules (SG) form in response to a variety of cellular stresses by phase-separation of proteins associated with non-translating mRNAs. SG provide insight into the biology of neurodegeneration, including amyotrophic lateral sclerosis (ALS) because they approximate some of the molecular conditions for nucleation of insoluble aggregates in neuropathological inclusions. Whereas much has been learned about SG formation, a major gap remains in understanding the compositional changes SG undergo during normal disassembly and under disease conditions. Here, we address this gap by proteomic dissection of SG temporal disassembly sequence, using multi-bait APEX proximity-proteomics. We discover 109 novel SG-proteins and characterize at proteomic resolution two biophysically distinct SG substructures. We further demonstrate that dozens of additional proteins are recruited to SG specifically during disassembly, indicating that it is a highly regulated process. The involved proteins link SG disassembly, to mitochondrial biology and the cytoskeleton. Parallel analysis with C9ORF72-associated dipeptides, which are found in patients with ALS and frontotemporal dementia, demonstrated compositional changes in SG during the course of disassembly and focused our attention on the roles SUMOylation in SG disassembly. We demonstrate that broad SUMOylation of SG-proteins is required for SG disassembly and is impaired by C9ORF72-associated dipeptides, representing an unexplored potential molecular mechanism of neurodegeneration. Altogether, out study fundamentally increases the knowledge about SG composition in human cells by dissecting the SG spatio-temporal proteomic landscape, provides an in-depth resource for future work on SG function and reveals basic and disease-relevant mechanisms of SG disassembly. HighlightsO_LIMulti bait APEX proximity labelling reveals 109 novel SG proteins and two distinct SG substructures. C_LIO_LIProteomic dissection of SG temporal disassembly under basal conditions and with a model of neurodegeneration. C_LIO_LIDisassembly-engaged proteins (DEPs) include SUMO ligases that are recruited during normal disassembly and dysregulated in ALS-like conditions. C_LIO_LIPervasive SG protein SUMOylation during SG disassembly is impaired by ALS-like conditions. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=168 SRC="FIGDIR/small/830133v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@15899daorg.highwire.dtl.DTLVardef@1dcd399org.highwire.dtl.DTLVardef@c7ef12org.highwire.dtl.DTLVardef@20c096_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2019

Circulating miR-181 is a prognostic biomarker for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a relentless neurodegenerative syndrome of the human motor neuron system, for which no effective treatment exists. Variability in the rate of disease progression limits the efficacy of ALS clinical trials, suggesting that developing of better biomarkers for prognosis will facilitate therapeutic progress. Here, we applied unbiased next-generation sequencing to investigate the potential of plasma cell-free microRNAs as biomarkers of ALS prognosis, in 252 patients with detailed clinical-phenotyping. First, we identified miRNAs, whose plasma levels remain stable over the course of disease in a longitudinal cohort of 22 patients. Next, we demonstrated that high levels of miR-181, a miRNA enriched in neurons of the brain and spinal cord, predicts a >2 fold risk of death in discovery cohort (126 patients) and an independent replication cohort (additional 122 patients). miR-181 performance is comparable with the established neurofilament light chain (NfL) biomarker and when combined together, miR-181+NfL establish a novel RNA-protein biomarker pair with superior prediction capacity of ALS prognosis. Therefore, plasma miR-181 predicts ALS disease course, and a novel miRNA-protein biomarker approach, based on miR-181+NfL, boosts precision of patient stratification and may greatly enhance the power of clinical trials. One Sentence Summaryplasma miR-181 levels indicate high mortality risk in ALS patients.

neuroscience↗