Biology subjects

Lin, L.-C.

Publications and source records attributed to Lin, L.-C..

8 recordsLinked to original sources

bioRxiv2023

Disease-specific selective vulnerability and neuroimmune pathways in dementia revealed by single cellgenomics

Summary/AbstractThe development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNAseq and ATACseq in Alzheimer disease (AD), Frontotemporal degeneration (FTD), and Progressive Supranuclear Palsy (PSP), analyzing 40 participants, yielding over 1.4M cells from three brain regions ranging in vulnerability and pathological burden. We identify 35 shared disease-associated cell types and 14 that are disease-specific, replicating those previously identified in AD. Disease-specific cell states represent molecular features of disease-specific glial-immune mechanisms and neuronal vulnerability in each disorder, layer 4/5 intra-telencephalic neurons in AD, layer 2/3 intra-telencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We infer intrinsic disease-associated gene regulatory networks, which we empirically validate by chromatin footprinting. We find that causal genetic risk acts in specific neuronal and glial cells that differ across disorders, primarily non-neuronal cells in AD and specific neuronal subtypes in FTD and PSP. These data illustrate the heterogeneous spectrum of glial and neuronal composition and gene expression alterations in different dementias and identify new therapeutic targets by revealing shared and disease-specific cell states.

neuroscience↗

bioRxiv2023

Activity-induced gene expression in the human brain

Direct electrical stimulation (eSTIM) is widely used clinically, from neurosurgical mapping to therapeutic interventions for neurological and neuropsychiatric disorders1-10. Despite over a century of application, its molecular and cellular underpinnings remain unknown. Here, using state-of-the-art single-nuclei multiomic profiling, we map changes in cell-type-specific gene expression and chromatin accessibility in vivo in the human cortex following eSTIM of neurosurgery patients. eSTIM impacts a network of cells that extends beyond excitatory neurons to include inhibitory neurons, astrocytes, oligodendrocytes and microglia. We observed an upregulation of canonical immediate-early genes (IEGs: FOS, NPAS4, EGR4) in excitatory and inhibitory neurons and induction of cytokine-related genes CCL3 and CCL4 in microglia. The cross-species conservation of this gene signature, together with our examination of a cohort of both epilepsy and cancer patients, underscores the fundamental role of these changes in stimulation-driven plasticity while controlling for disease and environmental confounds. Our study of changes in chromatin accessibility reveals a common code that involves a cell-type specific signature of transcription factor binding motifs for members of the EGR family. By addressing these previously unexplored questions about activity-induced gene expression in vivo in the human brain, our findings challenge the long-standing neuron-centric view of eSTIM, highlighting the broader role of non-neuronal cells, including microglia, in mediating the impact of brain stimulation.

neuroscience↗

bioRxiv2023

GENE EXPRESSION WITHIN A HUMAN CHOROIDAL NEOVASCULAR MEMBRANE USING SPATIAL TRANSCRIPTOMICS

Macular neovascularization is a relatively common and potentially visually devastating complication of age-related macular degeneration. In macular neovascularization, pathologic angiogenesis can originate from either the choroid or the retina, but we have limited understanding of how different cell types become dysregulated in this dynamic process. In this study, we performed spatial RNA sequencing on a human donor eye with macular neovascularization as well as a healthy control donor. We identified genes enriched within the area of macular neovascularization and used deconvolution algorithms to predict the originating cell type of these dysregulated genes. Within the area of neovascularization, endothelial cells were predicted to increase expression of genes related to Rho family GTPase signaling and integrin signaling. Likewise, VEGF and TGFB1 were identified as potential upstream regulators that could drive the observed gene expression changes produced by endothelial and retinal pigment epithelium cells in the macular neovascularization donor. These spatial gene expression profiles were compared to previous single-cell gene expression experiments in human age-related macular degeneration as well as a model of laser-induced neovascularization in mice. As a secondary aim, we also investigated spatial gene expression patterns within the macular neural retina and between the macular and peripheral choroid. We recapitulated previously described regional-specific gene expression patterns across both tissues. Overall, this study spatially analyzes gene expression across the retina, retinal pigment epithelium, and choroid in health and describes a set of candidate molecules that become dysregulated in macular neovascularization.

genomics↗

bioRxiv2023

Spatial transcriptomics reveals unique gene expression changes in different brain regions after sleep deprivation

Sleep deprivation has far-reaching consequences on the brain and behavior, impacting memory, attention, and metabolism. Previous research has focused on gene expression changes in individual brain regions, such as the hippocampus or cortex. Therefore, it is unclear how uniformly or heterogeneously sleep loss affects the brain. Here, we use spatial transcriptomics to define the impact of a brief period of sleep deprivation across the brain. We find that sleep deprivation induced pronounced differences in gene expression across the brain, with the greatest changes in the hippocampus, neocortex, hypothalamus, and thalamus. Both the differentially expressed genes and the direction of regulation differed markedly across regions. Importantly, we developed bioinformatic tools to register tissue sections and gene expression data into a common anatomical space, allowing a brain-wide comparison of gene expression patterns between samples. Our results suggest that distinct molecular mechanisms acting in discrete brain regions underlie the biological effects of sleep deprivation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/524406v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@86d135org.highwire.dtl.DTLVardef@1110670org.highwire.dtl.DTLVardef@bdaddeorg.highwire.dtl.DTLVardef@e1d268_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LISpatial transcriptomics using the Visium platform reveals the transcriptional signature across the brain, recapitulating the anatomy of the mouse brain C_LIO_LISleep deprivation induces transcriptomic changes unique to each brain region C_LIO_LIThe hippocampus is the brain region impacted the most by acute sleep deprivation, with most differentially regulated genes significantly downregulated C_LIO_LIThe neocortex exhibits layer-specific changes in gene expression, with most differentially regulated genes significantly upregulated C_LIO_LIRegistration of spatial transcriptomic data to a common anatomical reference space (Allen Common Coordinate Framework) allows statistical analysis of gene expression across regions of the brain and for multi-sample analysis C_LI

neuroscience↗

bioRxiv2023

Mapping the spatial transcriptomic signature of the hippocampus during memory consolidation

Memory consolidation involves discrete patterns of transcriptional events in the hippocampus. Despite the emergence of single-cell transcriptomic profiling techniques, defining learning-responsive gene expression across subregions of the hippocampus has remained challenging. Here, we utilized unbiased spatial sequencing to elucidate transcriptome-wide changes in gene expression in the hippocampus following learning, enabling us to define molecular signatures unique to each hippocampal subregion. We find that each subregion of the hippocampus exhibits distinct yet overlapping transcriptomic signatures. Although the CA1 region exhibited increased expression of genes related to transcriptional regulation, the DG showed upregulation of genes associated with protein folding. We demonstrate the functional relevance of subregion-specific gene expression by genetic manipulation of a transcription factor selectively in the CA1 hippocampal subregion, leading to long-term memory deficits. This work demonstrates the power of using spatial molecular approaches to reveal transcriptional events during memory consolidation.

neuroscience↗

bioRxiv2022

Volumetric bioluminescence imaging of cellular dynamics with deep learning based light-field reconstruction

The application of genetically encoded fluorophores for microscopy has afforded one of the biggest revolutions in the biosciences. Bioluminescence microscopy is an appealing alternative to fluorescence microscopy, because it does not depend on external illumination, and consequently does neither produce spurious background autofluorescence, nor perturb intrinsically photosensitive processes in living cells and animals. The low quantum yield of known luciferases, however, limit the acquisition of high signal-noise images of fast biological dynamics. To increase the versatility of bioluminescence microscopy, we present an improved low-light microscope in combination with deep learning methods to increase the signal to noise ratio in extremely photon-starved samples at millisecond exposures for timelapse and volumetric imaging. We apply our method to image subcellular dynamics in mouse embryonic stem cells, the epithelial morphology during zebrafish development, and DAF-16 FoxO transcription factor shuttling from the cytoplasm to the nucleus under external stress. Finally, we concatenate neural networks for denoising and light-field deconvolution to resolve intracellular calcium dynamics in three dimensions of freely moving Caenorhabditis elegans with millisecond exposure times. This technology is cost-effective and has the potential to replace standard optical microscopy where external illumination is prohibitive.

bioengineering↗

bioRxiv2022

NEUROeSTIMator: Using Deep Learning to Quantify Neuronal Activation from Single-Cell and Spatial Transcriptomic Data

Neuronal activity-dependent transcription directs molecular processes that regulate synaptic plasticity, brain circuit development, behavioral adaptation, and long-term memory. Single cell RNA-sequencing technologies (scRNAseq) are rapidly developing and allow for the interrogation of activity-dependent transcription at cellular resolution. Here, we present NEUROeSTIMator, a deep learning model that integrates transcriptomic signals to estimate neuronal activation in a way that we demonstrate is associated with Patch-seq electrophysiological features and that is robust against differences in species, cell type, and brain region. We demonstrate this methods ability to accurately detect neuronal activity in previously published studies of single cell activity-induced gene expression. Further, we applied our model in a spatial transcriptomic study to identify unique patterns of learning-induced activity across different brain regions. Altogether, our findings establish NEUROeSTIMator as a powerful and broadly applicable tool for measuring neuronal activation, whether as a critical covariate or a primary readout of interest.

bioinformatics↗

bioRxiv2021

Mechanical Stretch Inhibition SensitizesProprioceptors to Compressive Stresses

A repetitive gait cycle is an archetypical component within the behavioural repertoire of many if not all animals including humans. It originates from mechanical feedback within proprioceptors to adjust the motorprogram during locomotion and thus leads to a periodic orbit in a low dimensional space. Here, we investigate the mechanics, molecules and neurons responsible for proprioception in Caenorhabditis (C.) elegans to gain insight into how mechanosensation shapes the orbital trajectory to a well-defined limit cycle. We used genome editing, force spectroscopy and multiscale modeling and found that alternating tension and compression with the spectrin network of a single proprioceptor encodes body posture and informs TRP-4/NOMPC and TWK-16/TREK2 homologs of mechanosensitive ion channels during locomotion. In contrast to a widely accepted model of proprioceptive stretch reception, we found that proprioceptors activated under compressive stresses in vivo and in vitro, and speculate that this property is conserved across function and species.

neuroscience↗