Biology subjects

Schuck, R.

Publications and source records attributed to Schuck, R..

6 recordsLinked to original sources

bioRxiv2026

Resilience to neuronal hyperactivity and restoration of the neuroimmune interactome by blocking fibrin-induced microglia activation in Alzheimers disease

Cerebrovascular pathology and neuronal network dysfunction are early features of Alzheimers disease (AD) associated with neuroinflammation and cognitive decline, but the vascular and immune triggers of neuronal hyperactivity remain largely unknown. Here, we show that the blood coagulation protein fibrin disrupts microglia-neuron interactions, promoting neuronal hyperactivity in an AD mouse model. Genetic elimination of the fibrin inflammatory domain reduced neuronal hyperactivity, restored dynamic microglial interactions with active neurons and protected from high-risk decision making in 5XFAD mice. Leveraging the transcriptional signatures of microglia and inhibitory and excitatory neurons, a ligand-receptor atlas revealed fibrin-dependent disruption of innate immune and glutamatergic signaling between microglia and neurons in AD mice. Patients with AD also showed a correlation of cerebrospinal fluid (CSF) fibrinogen levels with biomarkers of inflammation, vascular and synaptic dysfunction. Thus, resilience to neuronal hyperactivity and restoration of the neuroimmune interactome by targeting fibrin may have therapeutic implications for Alzheimers disease and related conditions. There is a companion manuscript submitted to bioRxiv (Lauderdale et al., 2026) HighlightsO_LIVascular-microglia axis drives neuronal hyperactivity C_LIO_LIFibrin inflammatory activity disrupts the microglia-neuron interactome C_LIO_LIMicroglia activation by fibrin impairs decision-making in AD mice C_LIO_LISynaptic dysfunction and immune biomarkers correlate with CSF fibrinogen in AD patients C_LI

neuroscience↗

bioRxiv2026

Therapeutic targeting of fibrin-microglia interactions ameliorates Alzheimer disease-related hyperexcitability and brain network dysfunction

Brain network dysfunction--including hyperexcitability, altered oscillations, and sleep disruption--is prominent in Alzheimers disease (AD), but the contribution of vascular-neuroimmune processes to these alterations remains unclear. Here, we blocked the pro-inflammatory interaction of the blood protein fibrin with microglia using genetic (Fgg{gamma}390-396A mice) and antibody-based (5B8 and THN392) strategies to test its role in AD-related network dysfunction. The 5xFAD model of AD exhibited network hyperexcitability associated with oscillatory slowing, sleep states, and disrupted sleep-circadian rhythms. These deficits were largely attenuated by blocking fibrin-microglia interactions in 5xFAD;Fgg{gamma}390-396A mice. Notably, pharmacological interventions after disease onset with both anti-fibrin antibodies similarly attenuated these AD-related network deficits and behavioral abnormalities. We conclude that vascular-neuroimmune processes driven by fibrin-microglia interactions promote AD-related network dysfunction and that targeting the fibrin-microglia axis--currently under clinical evaluation with the humanized antibody THN391-- represents a promising therapeutic strategy for AD. There is a companion manuscript submitted to bioRxiv (Yan et al., 2026).110 HIGHLIGHTSO_LIFibrin promotes AD-related network hyperexcitability and oscillatory slowing in 5xFAD mice C_LIO_LIFibrin promotes AD-related disruption of sleep and circadian rhythms in 5xFAD mice C_LIO_LIGenetic blocking of fibrin-microglia interactions rescues AD-related brain network dysfunction C_LIO_LIAnti-fibrin antibodies (5B8 and THN392) show acute and chronic therapeutic benefit C_LI

neuroscience↗

bioRxiv2024

Cholesterol inhibits oncogenic EphA2 activation

The receptor tyrosine kinase EphA2 drives cancer malignancy by facilitating metastasis. EphA2 can be found in different self-assembly states: as a monomer, dimer, and oligomer. However, our understanding remains limited regarding which EphA2 state is responsible for driving pro-metastatic signaling. To address this limitation, we have developed SiMPull-POP, a single-molecule method for accurate quantification of membrane protein self-assembly. Our experiments revealed that a reduction of plasma membrane cholesterol strongly promoted EphA2 self-assembly. Indeed, low cholesterol caused a similar effect to the EphA2 ligand ephrinA1-Fc. These results indicate that cholesterol inhibits EphA2 assembly. Phosphorylation studies in different cell lines revealed that low cholesterol increased phospho-serine levels, the signature of oncogenic signaling. Investigation of the mechanism that cholesterol uses to inhibit the assembly and activity of EphA2 indicate an in-trans effect, where EphA2 is phosphorylated by protein kinase A downstream of beta-adrenergic receptor activity, which cholesterol also inhibits. Our study not only provides new mechanistic insights on EphA2 oncogenic function, but also suggests that cholesterol acts as a molecular safeguard mechanism that prevents uncontrolled self-assembly and activation of EphA2.

biochemistry↗

bioRxiv2021

SARS-CoV-2 spike protein induces abnormal inflammatory blood clots neutralized by fibrin immunotherapy

Blood clots are a central feature of coronavirus disease-2019 (COVID-19) and can culminate in pulmonary embolism, stroke, and sudden death. However, it is not known how abnormal blood clots form in COVID-19 or why they occur even in asymptomatic and convalescent patients. Here we report that the Spike protein from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to the blood coagulation factor fibrinogen and induces structurally abnormal blood clots with heightened proinflammatory activity. SARS-CoV-2 Spike virions enhanced fibrin-mediated microglia activation and induced fibrinogen-dependent lung pathology. COVID-19 patients had fibrin autoantibodies that persisted long after acute infection. Monoclonal antibody 5B8, targeting the cryptic inflammatory fibrin epitope, inhibited thromboinflammation. Our results reveal a procoagulant role for the SARS-CoV-2 Spike and propose fibrin-targeting interventions as a treatment for thromboinflammation in COVID-19. One-Sentence SummarySARS-CoV-2 spike induces structurally abnormal blood clots and thromboinflammation neutralized by a fibrin-targeting antibody.

immunology↗

bioRxiv2017

Multiphoton minimal inertia scanning for fast acquisition of neural activity signals

Multi-photon laser scanning microscopy provides a powerful tool for monitoring the spatiotemporal dynamics of neural circuit activity. It is, however, intrinsically a point scanning technique. Standard raster scanning enables imaging at subcellular resolution; however, acquisition rates are limited by the size of the field of view to be scanned. Recently developed scanning strategies such as Travelling Salesman Scanning (TSS) have been developed to maximize cellular sampling rate by scanning only regions of interest in the field of view corresponding to locations of interest such as somata. However, such strategies are not optimized for the mechanical properties of galvanometric scanners. We describe here the Adaptive Spiral Scanning (SSA) algorithm, which fits a set of near-circular trajectories to the cellular distribution to avoid inertial drifts of galvanometer position. We compare its performance to raster scanning and TSS in terms of cellular sampling frequency and signal-to-noise ratio (SNR). Using surrogate neuron spatial position data, we show that SSA acquisition rates are an order of magnitude higher than those for raster scanning and generally exceed those achieved by TSS for neural densities comparable with those found in the cortex. We show that this result also holds true for in vitro hippocampal mouse brain slices bath loaded with the synthetic calcium dye Cal-520 AM. The ability of TSS to \"park\" the laser on each neuron along the scanning trajectory, however, enables higher SNR than SSA when all targets are precisely scanned. Raster scanning has the highest SNR but at a substantial cost in number of cells scanned. To understand the impact of sampling rate and SNR on functional calcium imaging, we used the Cramer-Rao Bound on evoked calcium traces recorded simultaneously with electrophysiology traces to calculate the lower bound estimate of the spike timing occurrence. The results show that TSS and SSA achieve comparable accuracy in spike time estimates compared to raster scanning despite their lower SNR. SSA is an easily implementable way for standard multi-photon laser scanning systems to gain temporal precision in the detection of action potentials while scanning hundreds of active cells.

neuroscience↗

bioRxiv2017

ABLE: an Activity-Based Level Set Segmentation Algorithm for Two-Photon Calcium Imaging Data

We present an algorithm for detecting the location of cells from two-photon calcium imaging data. In our framework, multiple coupled active contours evolve, guided by a model-based cost function, to identify cell boundaries. An active contour seeks to partition a local region into two subregions, a cell interior and ex-terior, in which all pixels have maximally similar time courses. This simple, local model allows contours to be evolved predominantly independently. When contours are sufficiently close, their evolution is coupled, in a manner that permits overlap. We illustrate the ability of the proposed method to demix overlapping cells on real data. The proposed framework is flexible, incorporating no prior information regarding a cells morphology or stereotypical temporal activity, which enables the detection of cells with diverse properties. We demonstrate algorithm performance on a challenging mouse in vitro dataset, containing synchronously spiking cells, and a manually labelled mouse in vivo dataset, on which ABLE achieves a 67.5% success rate.\n\nSignificance statementTwo-photon calcium imaging enables the study of brain activity during learning and behaviour at single-cell resolution. To decode neuronal spiking activity from the data, algorithms are first required to detect the location of cells in the video. It is still common for scientists to perform this task manually, as the heterogeneity in cell shape and frequency of cellular overlap impede automatic segmentation algorithms. We developed a versatile algorithm based on a popular image segmentation approach (the Level Set Method) and demonstrated its capability to overcome these challenges. We include no assumptions on cell shape or stereotypical temporal activity. This lends our framework the flexibility to be applied to new datasets with minimal adjustment.

neuroscience↗