Biology subjects

Wang, W. X.

Publications and source records attributed to Wang, W. X..

8 recordsLinked to original sources

bioRxiv2025

Spatially resolved translational dysregulation in Grin2a+/- mouse model of schizophrenia

Loss-of-function (LoF) mutations of GRIN2A, encoding the GluN2A subunit of N-methyl-D-aspartate receptor (NMDAR), confer a high risk for schizophrenia (SCZ)1-3, yet how they affect diverse brain cell types remains poorly understood. Here, we combined subcellular-resolution spatial omics technologies, STARmap4 and RIBOmap5, to jointly resolve single-cell transcriptomes and translatomes for 3,447 genes in the brains of Grin2a+/- mice and their wild-type littermates across 538,188 cells. Translational dysregulation was markedly more prominent than transcriptional changes in neurons. Across neuronal subtypes, a set of genes including Camk2a, Arc, Egr1, Egr3, Chmp2b, and Pja2 exhibited translational reduction in a Grin2a gene dose-dependent fashion, suggesting a connection between NMDAR hypofunction and reduced protein synthesis of downstream synaptic plasticity effectors. In interneurons (particularly parvalbumin interneurons), a strong reduction of Gad2 translation implies loss of inhibitory function in cortical microcircuits, which has long been hypothesized for SCZ pathophysiology. Non-neuronal cell types including astrocytes, oligodendrocytes, and vascular cells also exhibited region-specific translational changes in neurotransmitter transport, lipid synthesis, myelination, and stress response pathways, some of which co-varied with regional neuron state. Together, our study reveals brain-wide translation dysregulation as a critical mechanism underlying SCZ pathophysiology.

neuroscience↗

bioRxiv2025

Title: Cell-autonomous and non-cell-autonomous effects of TRIM72 on ALS disease progression

Dysfunction of RNA-binding proteins, including TDP-43 and FUS, has been associated with amyotrophic lateral sclerosis (ALS); however, the underlying mechanisms are largely unknown. Here, we reported that a neuronal upregulation of TRIM72 (Tripartite Motif Containing 72) in FUS mutation knockin ALS models slows disease progression. TRIM72 interacts with Commander, a protein complex for recycling of membrane proteins, facilitating membrane repair and antioxidation. Exosomal TRIM72 is detected in ALS patient cerebrospinal fluid (CSF) and extracellular application of exosomal TRIM72 protects cell from membrane damage. In a sporadic ALS cohort, CSF TRIM72 level associates ALS disease progression. AAV-mediated neuronal expression of TRIM72 slows down the disease progressions in ALS models and in an ALS patient without adverse effects over a year treatment course. Taken together, our results suggest a universal neuronal protection of a TRIM family protein in cell-autonomous and non-cell-autonomous manners in ALS.

neuroscience↗

bioRxiv2024

Scalable spatial single-cell transcriptomics and translatomics in 3D thick tissue blocks

Characterizing the transcriptional and translational gene expression patterns at the single-cell level within their three-dimensional (3D) tissue context is essential for revealing how genes shape tissue structure and function in health and disease. However, most existing spatial profiling techniques are limited to 5-20 {micro}m thin tissue sections. Here, we developed Deep-STARmap and Deep-RIBOmap, which enable 3D in situ quantification of thousands of gene transcripts and their corresponding translation activities, respectively, within 200-{micro}m thick tissue blocks. This is achieved through scalable probe synthesis, hydrogel embedding with efficient probe anchoring, and robust cDNA crosslinking. We first utilized Deep-STARmap in combination with multicolor fluorescent protein imaging for simultaneous molecular cell typing and 3D neuron morphology tracing in the mouse brain. We also demonstrate that 3D spatial profiling facilitates comprehensive and quantitative analysis of tumor-immune interactions in human skin cancer.

genomics↗

bioRxiv2024

Towards a universal spatial molecular atlas of the mouse brain

Spatially mapping a comprehensive brain at the single-cell level with molecular resolution is crucial for understanding its biological structure, mechanisms, and functions. Recent scalable spatial transcriptomics technologies1-7 have revolutionized our ability to examine millions of cells within the complex brain network, allowing for the generation of multiple mouse brain atlases that illuminate diverse transcriptomic and spatial cell types. However, despite enormous efforts, these spatial transcriptomics atlases still face challenges in providing a comprehensive brain representation: each atlas only captures a fraction of the vast cellular population of the brain and is limited in one or more aspects of spatial resolution, gene detection sensitivity, and gene throughput8. Here, we introduce FuseMap, a deep-learning-based framework for spatial transcriptomics that bridges single-cell or single-spot gene expression with spatial contexts and consolidates various gene panels across spatial transcriptomics atlases. By training on an extensive spatial transcriptomics atlas corpus of the mouse brain1-7, comprising over 18.6 million cells or spots and 26,665 genes from 434 tissue sections across seven datasets in a self-supervised way, FuseMap gains a fundamental understanding of cell identities and gene characteristics. We thus create a comprehensive molecular spatial reference atlas of the whole mouse brain with transcriptome-wide information, achieving multiple tasks including nomenclature harmonization of molecular cell types and tissue regions, identification of novel molecular brain regions, spatial gene imputation, targeted gene-panel selection, and region-specific cell-type interactions inference. Furthermore, the pretrained brain FuseMap model enables mapping new query data to the molecular spatial reference brain through transfer learning, allowing for automated cell and tissue annotations and replacing laborious and suboptimal manual annotations. Overall, we offer FuseMap as a novel computational framework for integration across various spatial transcriptomics platforms and provide a molecular common coordinate framework (molCCF) with pretrained FuseMap brain model for exploration of the brain molecular and cellular landscape with harmonized annotations and coordinates.

genomics↗

bioRxiv2023

High-throughput, label-free detection of DNA origami in single-cell suspensions using origamiFISH-Flow

Structural DNA nanotechnology enables custom fabrication of nanoscale devices and promises diverse biological applications. However, the effects of design on DNA nanostructure (DN)-cell interactions in vitro and in vivo are not yet well-characterized. origamiFISH is a recently developed technique for imaging DNs in cells and tissues. Compared to the use of fluorescent tags, origamiFISH offers label-free and structure-agnostic detection of DNs with significantly improved sensitivity. Here, we extend the origamiFISH technique to quantifying DNs in single-cell suspensions, including nonadherent cells such as subsets of immune cells, via readout by flow cytometry. This method, referred to as origamiFISH-Flow, is high-throughput (e.g., 10,000 cells per second) and compatible with immunostaining for concurrent cell-type and -state characterization. We demonstrate that origamiFISH-Flow enhances signal-to-noise ratio by up to 20-fold compared to dye labeling approaches, leading to the capture of >25-fold more DN+ cells at low, single-picomolar DN uptake concentrations. We additionally show the use of origamiFISH-Flow to profile cell-type and shape-specific DN uptake patterns across cell lines and splenocytes and quantify in vivo DN accumulation in lymphoid organs. Together, origamiFISH-Flow offers a new tool to interrogate DN interactions with cells and tissues, while providing insights for tailoring their designs in bio-applications.

bioengineering↗

bioRxiv2022

origamiFISH allows universal, label-free, single molecule visualization of DNA origami nanodevices across biological samples

Structural DNA nanotechnology enables user-prescribed design of DNA nanostructures (DNs) for biological applications, but how DN design determines their bio-distribution and cellular interactions remain poorly understood. One challenge is that current methods for tracking DN fates in situ, including fluorescent-dye labeling, suffer from low sensitivity and dye-induced artifacts. Here we present origamiFISH, a label-free and universal method for single-molecule fluorescence detection of DNA origami nanostructures in cells and tissues. origamiFISH targets pan-DN scaffold sequences with hybridization chain reaction (HCR) probes to achieve thousand-fold signal amplification. We identify cell-type and shape-specific spatiotemporal uptake patterns within 1 minute of uptake and at picomolar DN concentrations, 10,000x lower than field standards. We additionally optimized compatibility with immunofluorescence and tissue clearing to visualize DN distribution within tissue cryo/vibratome-sections, slice cultures, and whole-mount organoids. Together, origamiFISH enables faithful mapping of DN interactions across subcellular and tissue barriers for guiding the development of DN-based therapeutics.

synthetic biology↗

bioRxiv2020

Morphological pseudotime ordering and fate mapping reveals diversification of cerebellar inhibitory interneurons

Understanding how diverse neurons are assembled into circuits requires a framework for describing cell types and their developmental trajectories. Here, we combined genetic fate mapping and pseudo-temporal profiling to resolve the diversification of cerebellar inhibitory interneurons based on morphology. The molecular layer interneurons (MLIs) derive from a common progenitor but comprise a diverse population of dendritic-, somatic-, and axon initial segment-targeting interneurons. MLIs are classically divided into two types. However, their morphological heterogeneity suggests an alternate model of one continuously varying population. Through clustering and trajectory inference of 811 MLI reconstructions at maturity and during development, we show that MLIs divide into two discrete classes but also present significant within-class heterogeneity. Pseudotime trajectory mapping uncovered the emergence of distinct phenotypes during migration and axonogenesis, well before neurons reach their final positions. Our study illustrates the utility of quantitative single-cell methods to morphology for defining the diversification of neuronal subtypes.

neuroscience↗

bioRxiv2020

The gamma-Protocadherins regulate the survival of GABAergic interneurons during developmentally-regulated cell death.

Inhibitory interneurons integrate into developing circuits in specific ratios and distributions. In the cortex, the formation of inhibitory networks occurs concurrently with the apoptotic elimination of a third of GABAergic interneurons. The molecular mechanisms that select GABAergic interneurons to survive or die are unknown. Here we report that the clustered Protocadherins regulate GABAergic cell survival in the developing brain. Deletion of the Pcdh-gamma genes (Pcdhgs) from GABAergic neurons in mice causes a severe loss of inhibitory neurons in multiple brain regions and results in motor deficits and seizure activities. By focusing on the neocortex and cerebellar cortex, we demonstrate that GABAergic interneuron loss results from elevated apoptosis during the postnatal wave of Bax-dependent programmed cell death. Pro-survival AKT signals are reduced in Pcdhg-deficient interneurons, diminishing the intrinsic capacity of interneurons to compete and incorporate into developing networks. We propose that the Pcdhgs mediate selective GABAergic interneuron survival to contribute to the formation of balanced inhibitory networks.

neuroscience↗