Biology subjects

Negwer, M.

Publications and source records attributed to Negwer, M..

9 recordsLinked to original sources

bioRxiv2025

Whole-brain clearing reveals region- and cell type-specific imbalances in inhibitory neurons in a mouse model for Kleefstra Syndrome

GABAergic inhibition is essential for balanced brain function and is frequently disrupted in neurodevelopmental disorders such as autism spectrum disorder (ASD). The inhibition is generated by a diverse population of GABAergic interneurons, whose composition and density differs throughout the brain. Here, we applied an unbiased whole-brain clearing and light-sheet imaging approach to systematically map the distribution of the three major GABAergic neuron classes - Parvalbumin-positive (PV), Somatostatin-positive (SST), and Vasoactive Intestinal Polypeptide-positive (VIP) cells - across the mouse brain in a model of Kleefstra Syndrome (Ehmt1+/-), a monogenic intellectual disability disorder with a strong ASD component. Analyzing 895 brain regions we identified widespread, cell type- and region-specific alterations in GABAergic classes. Notably, we observed increased VIP neuron density in the Ehmt1+/- cortex and decreased SST neuron density in sensory cortical and subcortical regions. In the basolateral amygdala (BLA), PV neurons exhibited precocious maturation already at the juvenile stage, which persisted into adulthood and was associated with enhanced inhibitory input onto BLA principal neurons. We here demonstrate that Ehmt1 haploinsufficiency results in region- and cell-type specific changes throughout the brain. These results underscore the value of whole-brain, high-resolution mapping approaches in uncovering previously unrecognized patterns of neural vulnerability in neurodevelopmental disorders.

neuroscience↗

bioRxiv2024

The Neural Blueprint of Stress Susceptibility: Brain-wide neuronal activity associated with the consequences of stress

Understanding the neurobiological mechanisms of stress susceptibility is key to advancing our insight into stress-related psychopathology like post-traumatic stress disorder (PTSD). Preclinical animal models however typically lack translationally relevant brain readouts. Here, we used a mouse model for severe stress, segregating mice into stress-susceptible and resilient groups. We analyzed and contrasted their whole-brain neuronal activity pre-, peri- and post-stress exposure and compared functional connectivity of the salience (SN), default mode (DMN) and executive control network (lateral cortical network (LCN) in rodents). We found that stress-susceptible mice exhibited pre-existing hyperactivity in the lateral orbital area, a potential risk factor for stress vulnerability, and heightened retrosplenial cortex activity peri- and post-stress, potentially contributing to maladaptive fear memory. Upon stress exposure, susceptible mice showed strong recruitment of visual and memory-related areas, whereas resilient mice displayed marked reductions in retrosplenial activity and increased activation in the agranular insula and ventral striatum. Observations of enhanced intra-SN and SN-DMN connectivity in susceptible mice mirrored those observed in individuals with PTSD. Moreover, susceptible mice displayed aberrant DMN-LCN network pre- and peri-stress. These findings highlight the importance of dynamic network interactions in stress susceptibility and suggest novel brain region targets for (early) intervention.

neuroscience↗

bioRxiv2024

Neuronal autophagosomes are transported to astrocytes for degradation

Autophagy is a vital catabolic process responsible for the degradation of cytosolic components, playing a key role in cellular homeostasis and survival. At synapses, autophagy is crucial for regulating neuronal activity and utilizes a specialized machinery. While considerable progress has been made in understanding the initiation of autophagy and autophagosome formation, the mechanisms governing the clearance of autophagosomes from synaptic sites remain poorly understood. Here, we identify a novel pathway in which astrocytes actively participate in the clearance of pre-synaptic autophagosomes. Using neurons derived from human induced pluripotent stem cell (hiPSC) lines expressing fluorescent autophagy markers and chimeric mouse models, we demonstrate that neuronal autophagosomal vesicles are physically transferred to astrocytes, a process that is enhanced when synaptic activity is suppressed. Autophagosome transfer does not require direct physical cellular contact, but it does require Dynamin and cholesterol-dependent endocytosis for the internalized neuronal autophagosomes to ultimately fuse with astrocytic lysosomes. Our findings reveal a previously unrecognized mechanism of neuronal autophagosome clearance that does not require slow axonal retrograde transport but their transfer to nearby astrocytes.

neuroscience↗

bioRxiv2024

Fc-engineered large molecules targeting blood-brain barrier transferrin receptor and CD98hc have distinct central nervous system and peripheral biodistribution compared to standard antibodies

The blood-brain barrier (BBB) poses a significant challenge drug delivery to the brain. BBB-crossing molecules are emerging as a new class of therapeutics with significant potential for central nervous system (CNS) indications. In particular, transferrin receptor (TfR)- and CD98 heavy chain (CD98hc)-targeting molecules have been demonstrated to cross the BBB for enhanced brain delivery. Previously, we reported TfR and CD98hc antibody transport vehicles (ATVTfR and ATVCD98hc) that utilize these BBB receptors to improve CNS drug delivery1,2. Here, we provide a comprehensive and unbiased biodistribution characterization of ATVTfR and ATVCD98hc compared to a standard IgG at a multiscale level, ranging from whole-body to brain region- and cell type-targeting specificity. Mouse whole-body tissue clearing revealed distinct organ localization for each molecule. In the CNS, ATVTfR and ATVCD98hc not only achieves enhanced brain delivery but importantly, much broader parenchymal distribution in contrast to the severely limited distribution observed with a standard antibody that was not able to be improved even at very high dose levels. Using cell sorting and single-cell RNA sequencing of mouse brain, we revealed that standard IgG predominantly localizes to perivascular and leptomeningeal cells and reaches the CNS by entering the CSF, rather than crossing the BBB. In contrast, ATVTfR and ATVCD98hc enables broad parenchymal cell-specific distribution via transcytosis through brain endothelial cells (BECs) along the neurovasculature. Finally, we extended the translational relevance of our findings by revealing enhanced and broad brain and spinal cord biodistribution of ATVTfR compared to standard IgG in cynomolgus monkey. Taken together, this multiscale analysis reveals in-depth biodistribution differences between ATVTfR, ATVCD98hc, and standard IgG. These results may better inform platform selection for specific therapeutic targets of interest, optimally matching platforms to desired CNS target engagement, peripheral organ exposures, and predict or potentially reduce off-target effects.

neuroscience↗

bioRxiv2023

Virtual reality empowered deep learning analysis of brain activity

Tissue clearing and fluorescent microscopy are powerful tools for unbiased organ-scale protein expression studies. Critical for interpreting expression patterns of large imaged volumes are reliable quantification methods. Here, we present DELiVR a deep learning pipeline that uses virtual reality (VR)-generated training data to train deep neural networks, and quantify c-Fos as marker for neuronal activity in cleared mouse brains and map its expression at cellular resolution. VR annotation significantly accelerated the speed of generating training data compared to conventional 2D slice based annotation. DELiVR detects cells with much higher precision than current threshold-based pipelines, and provides an extensive toolbox for data visualization, inspection and comparison. We applied DELiVR to profile cancer-related mouse brain activity, and discovered a novel activation pattern that distinguishes between weight-stable cancer and cancer-associated weight loss. Thus, DELiVR provides a robust mouse brain analysis pipeline at cellular scale that can be used to study brain activity patterns in health and disease. The DELiVR software, Fiji plugin and documentation can be found at https://www.DISCOtechnologies.org/DELiVR/. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=169 SRC="FIGDIR/small/540970v1_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@172d5bforg.highwire.dtl.DTLVardef@2f1d80org.highwire.dtl.DTLVardef@139e7a0org.highwire.dtl.DTLVardef@95dce1_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDELiVR detects labelled cells in cleared brains with deep learning C_LIO_LIDELiVR is trained by annotating ground-truth data in virtual reality (VR) C_LIO_LIDELiVR is launched via a FIJI plugin anywhere from PCs to clusters C_LIO_LIUsing DELiVR, we found new brain activity patterns in weight-stable vs. cachectic cancer C_LI Supplementary Videos can be seen at: https://www.DISCOtechnologies.org/DELiVR/

bioinformatics↗

bioRxiv2023

FriendlyClearMap: An optimized toolkit for mouse brain mapping and analysis

Tissue clearing is currently revolutionizing neuroanatomy by enabling organ-level imaging with cellular resolution. However, currently available tools for data analysis require a significant time investment for training and adaptation to each laboratorys use case, which limits productivity. Here, we present FriendlyClearMap, an integrated toolset that makes ClearMap1 and ClearMap2s CellMap pipeline easier to use, extends its functions, and provides Docker Images from which it can be run with minimal time investment. We also provide detailed tutorials for each step of the pipeline. For more precise alignment, we add a landmark-based atlas registration to ClearMaps functions as well as include young mouse reference atlases for developmental studies. We provide alternative cell segmentation method besides ClearMaps threshold-based approach: Ilastiks Pixel Classification, importing segmentations from commercial image analysis packages and even manual annotations. Finally, we integrate BrainRender, a recently released visualization tool for advanced 3D visualization of the annotated cells. As a proof-of-principle, we use FriendlyClearMap to quantify the distribution of the three main GABAergic interneuron subclasses (Parvalbumin+, Somatostatin+, and VIP+) in the mouse fore- and midbrain. For PV+ neurons, we provide an additional dataset with adolescent vs. adult PV+ neuron density, showcasing the use for developmental studies. When combined with the analysis pipeline outlined above, our toolkit improves on the state-of-the-art packages by extending their function and making them easier to deploy at scale.

neuroscience↗

bioRxiv2022

Defensive and offensive behaviors in social interaction settings in a Kleefstra syndrome mouse model

Kleefstra syndrome in humans is characterized by general delay in development, intellectual disability and autistic features. The mouse model of this disease (Ehmt1+/-) expresses anxiety, autistic-like traits, and aberrant social interactions with non-cagemates. To investigate how Ehmt1+/- mice behave with unfamiliar conspecifics, we allowed adult, male animals to freely interact for 10 minutes in a neutral, novel environment within a host-visitor setting. In 17 out of 74 trials there were defensive and offensive behaviors. Our key finding was that Ehmt1+/- mice displayed defensive postures, attacking and biting; in contrast, wild-type (WT) interacting with other WT did not enact such behaviors. Further, if there was a fight between an Ehmt1+/- and a WT mouse, it was always the Ehmt1+/- who initiated these behaviors.

neuroscience↗

bioRxiv2019

The Object Space Task reveals a dissociation between semantic-like and episodic-like memory in a mouse model of Kleefstra Syndrome

Kleefstra syndrome is a disorder caused by a mutation in the EHMT1 gene characterized in humans by general developmental delay, mild to severe intellectual disability and autism. Here, we characterized semantic- and episodic-like memory in the Ehmt1+/- mouse model using the Object Space Task. We combined conventional behavioral analysis with automated analysis by deep-learning networks, a session-based computational learning model and a trial-based classifier. Ehmt1 +/- mice showed more anxiety-like features and generally explored objects less, but the difference decreased over time. Interestingly, when analyzing memory-specific exploration, Ehmt1 +/- show increased expression of semantic-like memory, but a deficit in episodic-like memory. A similar dissociation of semantic and episodic memory performance has been previously reported in humans with autism. Using our automatic classifier to differentiate between genotypes, we found that semantic-like memory features are better suited for classification than general exploration differences. Thus, detailed behavioral classification with the Object Space Task produced a more detailed behavioral phenotype of the Ehmt1 +/- mouse model.\n\nOne Sentence SummaryEhmt1 +/- mice show decreased exploration and episodic-like memory but increased semantic-like memory In the Object Space Task. (143 of 150)

neuroscience↗

bioRxiv2019

Neuronal network dysfunction in a human model for Kleefstra syndrome mediated by enhanced NMDAR signaling

Epigenetic regulation of gene transcription plays a critical role in neural network development and in the etiology of Intellectual Disability (ID) and Autism Spectrum Disorder (ASD). However, little is known about the mechanisms by which epigenetic dysregulation leads to neural network defects. Kleefstra syndrome (KS), caused by mutation in the histone methyltransferase EHMT1, is a neurodevelopmental disorder with the clinical features of both ID and ASD. To study the impact of decreased EHMT1 function in human cells, we generated excitatory cortical neurons from induced pluripotent stem (iPS) cells derived from KS patients. In addition, we created an isogenic set by genetically editing healthy iPS cells. Characterization of the neurons at the single-cell and neuronal network level revealed consistent discriminative properties that distinguished EHMT1-mutant from wildtype neurons. Mutant neuronal networks exhibited network bursting with a reduced rate, longer duration, and increased temporal irregularity compared to control networks. We show that these changes were mediated by the upregulation of the NMDA receptor (NMDAR) subunit 1 and correlate with reduced deposition of the repressive H3K9me2 mark, the catalytic product of EHMT1, at the GRIN1 promoter. Furthermore, we show that EHMT1 deficiency in mice leads to similar neuronal network impairments and increased NMDAR function. Finally, we could rescue the KS patient-derived neuronal network phenotypes by pharmacological inhibition of NMDARs. Together, our results demonstrate a direct link between EHMT1 deficiency in human neurons and NMDAR hyperfunction, providing the basis for a more targeted therapeutic approach to treating KS.

neuroscience↗