Biology subjects

Yun, D. H.

Publications and source records attributed to Yun, D. H..

4 recordsLinked to original sources

bioRxiv2024

The noncoding circular RNA circHomer1 regulates developmental experience-dependent plasticity in mouse visual cortex

Circular RNAs (circRNAs) are a class of closed-loop, single stranded RNAs whose expression is particularly enriched in the brain. Despite this enrichment and evidence that the expression of circRNAs are altered by synaptic development and in response to synaptic plasticity in vitro, the regulation by and function of the majority of circRNAs in experience-dependent plasticity in vivo remain unexplored. Here, we employed transcriptome-wide analysis comparing differential expression of both mRNAs and circRNAs in juvenile mouse primary visual cortex (V1) following monocular deprivation (MD), a model of experience-dependent developmental plasticity. Among the differentially expressed mRNAs and circRNAs following 3-day MD, the circular and the activity-dependent mRNA forms of the Homer1 gene, circHomer1 and Homer1a respectively, were of interest as their expression changed in opposite directions: circHomer1 expression increased while the expression of Homer1a decreased following 3-day MD. Knockdown of circHomer1 delayed the depression of closed-eye responses normally observed after 3-day MD. circHomer1-knockdown also led to a reduction in average dendritic spine size prior to MD but critically there was no further reduction after 3-day MD, consistent with impaired structural plasticity. circHomer1-knockdown also prevented the reduction of surface AMPA receptors after 3-day MD. Synapse-localized puncta of the AMPA receptor endocytic protein Arc increased in volume after MD but were smaller in circHomer1-knockdown neurons, suggesting that circHomer1 knockdown impairs experience-dependent AMPA receptor endocytosis. Thus, the expression of multiple circRNAs are regulated by experience-dependent developmental plasticity, and our findings highlight the essential role of circHomer1 in V1 synaptic development and experience-dependent plasticity. Significance StatementCircular RNAs (circRNAs) are a class of closed-loop RNAs formed through back-splicing of exon and/or intron junctions. Initially considered as byproducts of aberrant RNA splicing with limited function, recent studies have implicated circRNAs in various neurological disorders. Despite their abundant expression in the brain, the role of circRNAs in experience-dependent plasticity remains poorly understood. We conducted an in vivo transcriptome analysis of circRNAs whose expression was regulated by experience-dependent plasticity in the mouse visual cortex and highlight circHomer1, a circRNA derived from the Homer1 gene, as a circRNA critical for synaptic development and experience-dependent plasticity in vivo.

neuroscience↗

bioRxiv2022

Integrated platform for multi-scale molecular imaging andphenotyping of the human brain

Understanding cellular architectures and their connectivity is essential for interrogating system function and dysfunction. However, we lack technologies for mapping the multi-scale details of individual cells in the human organ-scale system. To address this challenge, we developed a platform that simultaneously extracts spatial, molecular, morphological, and connectivity information of individual cells from the same human brain, by integrating novel chemical, mechanical, and computational tools. The platform includes three key tools: (i) a vibrating microtome for ultra-precision slicing of large-scale tissues without losing cellular connectivity (MEGAtome), (ii) a polymer hydrogel-based tissue processing technology for multiplexed multiscale imaging of human organ-scale tissues (mELAST), and (iii) a computational pipeline for reconstructing 3D connectivity across multiple brain slabs (UNSLICE). We demonstrated the transformative potential of our platform by analyzing human Alzheimers disease pathology at multiple scales and demonstrating scalable neural connectivity mapping in the human brain. One-Sentence SummaryWe developed an integrated, scalable platform for highly multiplexed, multi-scale phenotyping and connectivity mapping in the same human brain tissue, which incorporated novel tissue processing, labeling, imaging, and computational technologies.

bioengineering↗

bioRxiv2019

Ultrafast immunostaining of organ-scale tissues for scalable proteomic phenotyping

Studying the function and dysfunction of complex biological systems necessitates comprehensive understanding of individual cells. Advancements in three-dimensional (3D) tissue processing and imaging modalities have enabled rapid visualization and phenotyping of cells in their spatial context. However, system-wide interrogation of individual cells within large intact tissue remains challenging, low throughput, and error-prone owing to the lack of robust labeling technologies. Here we introduce a rapid, versatile, and scalable method, eFLASH, that enables complete and uniform labeling of organ-scale tissue within one day. eFLASH dynamically modulates chemical transport and reaction kinetics to establish system-wide uniform labeling conditions throughout the day-long labeling period. This unique approach enables the same protocol to be compatible with a wide range of tissue types and probes, enabling combinatorial molecular phenotyping across different organs and species. We applied eFLASH to generate quantitative maps of various cell types in mouse brains. We also demonstrated multidimensional cell profiling in a marmoset brain block. We envision that eFLASH will spur holistic phenotyping of emerging animal models and disease models to help assess their functions and dysfunctions.

bioengineering↗

bioRxiv2019

Scalable image processing techniques for quantitative analysis of volumetric biological images from light-sheet microscopy

Here we describe an image processing pipeline for quantitative analysis of terabyte-scale volumetric images of SHIELD-processed mouse brains imaged with light-sheet microscopy. The pipeline utilizes open-source packages for destriping, stitching, and atlas alignment that are optimized for parallel processing. The destriping step removes stripe artifacts, corrects uneven illumination, and offers over 100x speed improvements compared to previously reported algorithms. The stitching module builds upon Terastitcher to create a single volumetric image quickly from individual image stacks with parallel processing enabled by default. The atlas alignment module provides an interactive web-based interface that automatically calculates an initial alignment to a reference image which can be manually refined. The atlas alignment module also provides summary statistics of fluorescence for each brain region as well as region segmentations for visualization. The expected runtime of our pipeline on a whole mouse brain hemisphere is 1-2 d depending on the available computational resources and the dataset size.

bioengineering↗