Biology subjects

Lee, D.

Publications and source records attributed to Lee, D..

At least 199 records · Page 11Linked to original sources

bioRxiv2022

Multi-omic profiling of the developing human cerebral cortex at the single cell level

The cellular complexity of the human brain is established via dynamic changes in gene expression throughout development that is mediated, in part, by the spatiotemporal activity of cis-regulatory elements. We simultaneously profiled gene expression and chromatin accessibility in 45,549 cortical nuclei across 6 broad developmental time-points from fetus to adult. We identified cell-type specific domains in which chromatin accessibility is highly correlated with gene expression. Differentiation pseudotime trajectory analysis indicates that chromatin accessibility at cis-regulatory elements precedes transcription and that dynamic changes in chromatin structure play a critical role in neuronal lineage commitment. In addition, we mapped cell-type and temporally specific genetic loci implicated in neuropsychiatric traits, including schizophrenia and bipolar disorder. Together, our results describe the complex regulation of cell composition at critical stages in lineage determination, serve as a developmental blueprint of the human brain and shed light on the impact of spatiotemporal alterations in gene expression on neuropsychiatric disease. One-Sentence SummarySimultaneous profiling of gene expression and chromatin accessibility in single nuclei from 6 developmental time-points sheds light on cell fate determination in the human cerebral cortex and on the molecular basis of neuropsychiatric disease.

neuroscience↗

bioRxiv2022

Development of SARS-CoV-2 mRNA vaccines encoding spike N-terminal and receptor binding domains

With the success of mRNA vaccines against coronavirus disease 2019 (COVID-19), strategies can now focus on improving vaccine potency, breadth, and stability. We present the design and preclinical evaluation of domain-based mRNA vaccines encoding the wild-type spike-protein receptor-binding (RBD) and/or N-terminal domains (NTD). An NTD-RBD linked candidate vaccine, mRNA-1283, showed improved antigen expression, antibody responses, and stability at refrigerated temperatures (2-8{degrees}C) compared with the clinically available mRNA-1273, which encodes the full-length spike protein. In mice administered mRNA-1283 as a primary series, booster, or variant-specific booster, similar or greater immune responses and protection from viral challenge were observed against wild-type, beta, delta, or omicron (BA. 1) compared with mRNA-1273 immunized mice, especially at lower vaccine dosages. These results support clinical assessment of mRNA-1283 (NCT05137236). One Sentence SummaryA domain-based mRNA vaccine, mRNA-1283, is immunogenic and protective against SARS-CoV-2 and emerging variants in mice.

immunology↗

bioRxiv2022

A critical period for neurogenesis loss and cognitive decline in patients with mesial temporal lobe epilepsy patients

Mesial temporal lobe epilepsy (MTLE) is a syndromic disorder presenting with seizures and cognitive comorbidities. While seizure etiology is increasingly understood, the pathophysiological mechanisms contributing to cognitive decline and epilepsy progression remain less recognized. We have previously shown that adult hippocampal neurogenesis, a process contributing to visual spatial learning and memory in rodents, dramatically declines in MTLE patients with increased disease duration. Here, we investigate when multiple cognitive domains become effected by epilepsy disease duration and how human neurogenesis levels contribute to it. We find that intelligence, and verbal learning and memory decline at a critical period of 20 years disease duration. Surprisingly, the number of human immature neurons positively associate with auditory verbal, rather than visuospatial, learning and memory. Moreover, we uncover cognitive functions enriched to either immature or mature granule neurons and functions shared between them. Our study provides cellular evidence of how adult neurogenesis contributes to human cognition, and signifies an opportunity to advance regenerative medicine for patients with MTLE and other cognitive disorders. O_FIG O_LINKSMALLFIG WIDTH=108 HEIGHT=200 SRC="FIGDIR/small/507339v2_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@12d6c9forg.highwire.dtl.DTLVardef@13670aborg.highwire.dtl.DTLVardef@11efda3org.highwire.dtl.DTLVardef@19de537_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Bivalent SARS-CoV-2 mRNA vaccines increase breadth of neutralization and protect against the BA.5 Omicron variant

The emergence of SARS-CoV-2 variants in the Omicron lineage with large numbers of substitutions in the spike protein that can evade antibody neutralization has resulted in diminished vaccine efficacy and persistent transmission. One strategy to broaden vaccine-induced immunity is to administer bivalent vaccines that encode for spike proteins from both historical and newly-emerged variant strains. Here, we evaluated the immunogenicity and protective efficacy of two bivalent vaccines that recently were authorized for use in Europe and the United States and contain two mRNAs encoding Wuhan-1 and either BA.1 (mRNA-1273.214) or BA.4/5 (mRNA-1273.222) spike proteins. As a primary immunization series in BALB/c mice, both bivalent vaccines induced broader neutralizing antibody responses than the constituent monovalent vaccines (mRNA-1273 [Wuhan-1], mRNA-1273.529 [BA.1], and mRNA-1273-045 [BA.4/5]). When administered to K18-hACE2 transgenic mice as a booster at 7 months after the primary vaccination series with mRNA-1273, the bivalent vaccines induced greater breadth and magnitude of neutralizing antibodies compared to an mRNA-1273 booster. Moreover, the response in bivalent vaccine-boosted mice was associated with increased protection against BA.5 infection and inflammation in the lung. Thus, boosting with bivalent Omicron-based mRNA-1273.214 or mRNA-1273.222 vaccines enhances immunogenicity and protection against currently circulating SARS-CoV-2 strains.

microbiology↗

bioRxiv2022

Comparison of visual quantities in untrained deep neural networks

The ability to compare quantities of visual objects with two distinct measures, proportion and difference, is observed in newborn animals. Nevertheless, how this function originates in the brain, even before training, remains unknown. Here, we show that neuronal tuning for quantity comparison can arise spontaneously in completely untrained deep neural networks. Using a biologically inspired model neural network, we found that units selective to proportions and differences between visual quantities emerge in randomly initialized networks and that they enable the network to perform quantity comparison tasks. Further analysis shows that two distinct tunings to proportion and difference both originate from a random summation of monotonic, nonlinear responses to changes in relative quantities. Notably, we found that a slight difference in the nonlinearity profile determines the type of measure. Our results suggest that visual quantity comparisons are primitive types of functions that can emerge spontaneously in random feedforward networks. One sentence summaryThe ability to compare visual quantities arises spontaneously in untrained deep neural networks. Research HighlightsO_LIThe ability to compare visual quantity arises spontaneously in untrained networks C_LIO_LIDistinct tunings to measure proportion and difference of quantities are observed C_LIO_LIRandom wiring of monotonic, nonlinear activity induces quantity-comparison units C_LIO_LIThe nonlinearity pattern of the source unit determines the type of target measure C_LI

neuroscience↗

bioRxiv2022

Engineering a Single Extracellular Vesicle Protein and RNA Assay (siEVPRA) via In Situ Fluorescence Microscopy in a UV Micropatterned Array

The physical and molecular heterogeneity of extracellular vesicles (EVs) confounds bulk biomarker characterization, thus encouraging the development of novel assays capable of profiling EVs at a single-vesicle resolution. Here, we present a single EV (siEV) protein and RNA assay (siEVPRA) to simultaneously detect proteins, messenger RNAs (mRNAs), and microRNAs (miRNAs) in siEVs. The siEVPRA consists of an array of microdomains embedded on a polyethylene glycol (PEG)-coated glass surface produced via UV photopatterning, functionalized with antibodies to target siEV subpopulations. Fluorescently labeled antibodies and RNA-targeting molecular beacons (MBs) were used to generate signals for proteins, mRNAs, and miRNAs on siEVs detected by total internal reflection fluorescence microscopy (TIRFM), outperforming the sensitivities of ELISA and PCR by three orders of magnitude. Using the siEVPRA, we analyzed EVs harvested from glioblastoma (GBM) cell lines and demonstrated vesicular heterogeneity in protein, mRNA, and miRNA expression through colocalization analyses, and validated the results by bulk RNA sequencing. We further demonstrated the clinical utility of the siEVPRA by detecting different mRNAs and miRNAs associated with GBM in patient samples. Together, these results indicate that the siEVPRA provides an effective platform to investigate the heterogeneity of proteins and RNAs in subpopulations of EVs.

bioengineering↗

bioRxiv2022

Metheor: Ultrafast DNA methylation heterogeneity calculation from bisulfite read alignments

MotivationPhased DNA methylation states within bisulfite sequencing reads are valuable source of information that can be used to estimate epigenetic diversity across cells as well as epigenomic instability in individual cells. Various measures capturing the heterogeneity of DNA methylation states have been proposed for a decade. However, in routine analyses on DNA methylation, this heterogeneity is often overlooked by computing average methylation levels at CpG sites. In this study, to facilitate the application of the DNA methylation heterogeneity measures in downstream epigenomic analyses, we present a Rust-based, extremely fast and lightweight bioinformatics toolkit called Metheor. ResultsWe benchmark the performance of Metheor against existing code implementation for DNA methylation heterogeneity measures in three different scenarios of simulated bisulfite sequencing datasets. Metheor was shown to dramatically reduce the execution time up to 300-fold and memory footprint up to 60-fold, while producing the same results with the original implementation. AvailabilitySource code for Metheor is at https://github.com/dohlee/metheor and is freely available for non-commercial users. Contactsunkim.bioinfo@snu.ac.kr

bioinformatics↗

bioRxiv2022

Antisense oligonucleotide therapy rescues disturbed brain rhythms and sleep in juvenile and adult mouse models of Angelman syndrome

UBE3A encodes ubiquitin protein ligase E3A, and in neurons its expression from the paternal allele is repressed by the UBE3A antisense transcript (UBE3A-ATS). This leaves neurons susceptible to loss-of-function of maternal UBE3A. Indeed, Angelman syndrome, a severe neurodevelopmental disorder, is caused by maternal UBE3A deficiency. A promising therapeutic approach to treating Angelman syndrome is to reactivate the intact paternal UBE3A by suppressing UBE3A-ATS. Prior studies show that many neurological phenotypes of maternal Ube3a knockout mice can only be rescued by reinstating Ube3a expression in early development, indicating a restricted therapeutic window for Angelman syndrome. Here we report that reducing Ube3a-ATS by antisense oligonucleotides in juvenile or adult maternal Ube3a knockout mice rescues the abnormal electroencephalogram rhythms and sleep disturbance, two prominent clinical features of Angelman syndrome. Importantly, the degree of phenotypic improvement correlates with the increase of Ube3a protein levels. These results indicate that the therapeutic window of genetic therapies for Angelman syndrome is broader than previously thought, and electroencephalogram power spectrum and sleep architecture should be used to evaluate the clinical efficacy of therapies.

neuroscience↗

bioRxiv2022

Linearization Autoencoder: an autoencoder-based regression model with latent space linearization

Regression analysis is one of the most widely applied methods in many fields including bio-medical study. Dimensionality reduction is also widely used for data preprocessing and feature selection analysis, to extract high-impact features from the predictions. As the complexity of both data and prediction models increases, it becomes important and difficult to interpret the model. We suggested a novel method, linearizing autoencoder, for regression analysis with high-dimensional data. Based on the autoencoder model, we introduce a novel loss function to make data points aggregate corresponding to their known labels and align them preserving linear relations of the known feature. This model can align data points to the linear relations of labels, and achieve both the prediction and feature selection performances by extracting features that are important to the label we want to predict. Also, we applied this method to the real-world data and the result indicates that this method can successfully disentangle the latent space with given centroids in a supervised manner. This method can be applied to various prediction problems in biomedical fields.

bioinformatics↗

bioRxiv2022

Mapping genomic regulation of kidney disease and traits through high-resolution and interpretable eQTLs

Expression quantitative trait locus (eQTL) studies illuminate genomic variants that regulate specific genes and contribute to fine-mapped loci discovered via genome-wide association studies (GWAS). Efforts to maximize their accuracy are ongoing. Using 240 glomerular (GLOM) and 311 tubulointerstitial (TUBE) micro-dissected samples from human kidney biopsies, we discovered 5,371 GLOM and 9,787 TUBE eQTLs by incorporating kidney single-nucleus open chromatin data and transcription start site distance as an "integrative prior" for Bayesian statistical fine mapping. The use of an integrative prior resulted in higher resolution eQTLs illustrated by (1) smaller numbers of variants in credible sets with greater confidence, (2) increased enrichment of partitioned heritability for GWAS of two kidney traits, (3) an increased number of variants colocalized with the GWAS loci, and (4) enrichment of computationally predicted functional regulatory variants. A subset of variants and genes were validated experimentally in vitro and using a Drosophila nephrocyte model. More broadly, this study demonstrates that tissue-specific eQTL maps informed by single-nucleus open chromatin data have enhanced utility for diverse downstream analyses.

genomics↗

bioRxiv2022

High-fidelity optical diffraction tomography of live organisms using non-toxic tunable refractive index media

Optical diffraction tomography (ODT) enables the three-dimensional (3D) refractive index (RI) reconstruction. However, when the RI difference between a sample and a medium increases, effects of light scattering become significant, preventing the acquisition of high-quality and accurate RI reconstructions. Herein, we present a method for high-fidelity ODT by introducing non-toxic RI matching media. Optimally reducing the RI contrast enhances the fidelity and accuracy of 3D RI reconstruction, enabling visualization of the morphology and intra-organization of live biological samples without producing toxic effects. We validate our method using various biological organisms, including C. albicans and C. elegans. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/492426v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@a6b4d4org.highwire.dtl.DTLVardef@a9ec7borg.highwire.dtl.DTLVardef@1e4a795org.highwire.dtl.DTLVardef@b663aa_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2022

Modeling clonal evolution and oncogenic dependency in vivo in the context of hematopoietic transformation

Cancer evolution is a multifaceted process involving the acquisition of somatic mutations and progressive epigenetic dysregulation of cellular fate. Both cell-intrinsic mechanisms and environmental interactions provide selective pressures capable of promoting clonal evolution and expansion, with single-cell and bulk DNA sequencing offering increased resolution into this process1-4. Advances in genome editing, single-cell biology and expressed lentiviral barcoding have enabled new insights into how transcriptional/epigenetic states change with clonal evolution5,6. Despite the extensive catalog of genomic alterations revealed by resequencing studies7,8, there remain limited means to functionally model and perturb this evolutionary process in experimental systems9. Here we integrated multi-recombinase (Cre, Flp, and Dre) tools for modeling reversible, sequential mutagenesis from premalignant clonal hematopoiesis to acute myeloid leukemia. We demonstrate that somatic acquisition of Flt3 activating mutations elicits distinct phases of acute and chronic activation resulting in differential cooperativity with Npm1 and Dnmt3a disease alleles. We next developed a generalizable allelic framework allowing for the reversible expression of oncogenic mutations at their endogenous loci. We found that reversal of mutant Flt3 resulted in rapid leukemic regression with distinct alterations in cellular compartments depending upon co-occurring mutations. These studies provide a path to model sequential mutagenesis and deterministically investigate mechanisms of transformation and oncogenic dependency in the context of clonal evolution.

cancer biology↗

bioRxiv2022

ATP6AP2-to-MMP14, a key pathway for osteoblast to osteocyte transition

Osteocytes, derived from osteoblast (OB)-lineage, occupy lacunae within bone matrix and exhibit unique morphology with dendrite-like projections to form an inter-connected network. Such a network is essential for osteocytes to monitor and orchestrate bone homeostasis. Thus, it is of considerable interest to investigate how osteocytes are formed and how they built the network. Here we provide evidence for ATP6AP2, an accessory subunit of V-ATPase, in OB-lineage cells to be critical for OB-to-osteocyte transition, and osteocyte distribution, maturation, and morphogenesis. Mice (ATP6AP2Ocn-Cre) that selectively deplete ATP6AP2 in OB-lineage cells results in altered osteocyte distribution and morphology, impaired osteocyte maturation and dendrite-like processes, increased osteocyte cell death and cortical woven bone formation. Further mechanistic studies identify MMP14 (matrix metalloproteinase-14) as a critical downstream of ATP6AP2 for osteocyte differentiation. ATP6AP2 interacts with MMP14 and promotes MMP14 surface distribution largely in immature- or osteoid-osteocytes, where this pathway regulates bone matrix remodeling and osteocyte differentiation. Expression of MMP14 into ATP6AP2 knock out OB-lineage cells in the mouse cortical bone could diminish the deficits in osteocyte maturation, dendrite-like process formation, and survival. These results thus demonstrate an un-recognized function of ATP6AP2 in promoting OB-to-osteocyte transition and uncover a pathway from ATP6AP2-to-MMP14 in osteocyte differentiation.

developmental biology↗

bioRxiv2022

Tissue-specific and tissue-agnostic effects of genome sequence variation modulating blood pressure

Genome-wide association studies (GWAS) have mapped thousands of variants for numerous polygenic traits and diseases. However, with some exceptions, mechanistic understanding of which precise variants affect which genes in which tissues to modulate trait variation is still lacking. To this end, we introduce a novel class of genomic analyses applicable to any complex trait using GWAS together with gene expression and chromatin accessibility data from multiple tissues. Here we identify the transcription factors (TFs) and regulatory variants within active enhancers regulating specific genes in individual tissues to explain trait heritability of blood pressure (BP), a classical polygenic trait. We show that kidney-, adrenal-, heart-, and arterial-specific regulatory variants contribute to 2.5%, 5.3%, 7.7%, and 11.8% of variant heritability, respectively. Collectively, [~]500,000 predicted regulatory variants across these four tissues explain 33.4% of variant heritability. We demonstrate that these variants are enriched in enhancers binding specific TFs in each tissue. Our findings suggest that gene regulatory networks perturbed by common regulatory variants in a tissue relevant to a phenotype are the primary source of interindividual variation of BP. These studies provide an approach to scan each human tissue for its physiological contribution to a trait.

genetics↗

bioRxiv2022

Silent recognition of flagellins from human gut commensal bacteria by Toll-like receptor 5

Flagellin, the protein unit of the bacterial flagellum, stimulates the innate immune receptor Toll-like receptor (TLR)5 following pattern recognition, or evades TLR5 through lack of recognition. This binary response fails to explain the weak agonism of flagellins from commensal bacteria, raising the question of how TLR5 response is tuned. Here, we describe a novel class of flagellin-TLR5 interaction, termed silent recognition. Silent flagellins are weak agonists despite high affinity binding to TLR5. This dynamic response is tuned by TLR5-flagellin interaction distal to the site of pattern recognition. Silent flagellins are produced primarily by the abundant gut bacteria Lachnospiraceae and are enriched in non-Western populations. These findings provide a mechanism for the innate immune system to tolerate commensal-derived flagellins. One-Sentence SummaryTLR5 sensitively recognizes, but responds weakly to, flagellins from gut commensal bacteria.

microbiology↗

bioRxiv2022

Intercellular CRISPR Screens Enhance the Discovery of Cancer Immunotherapy Targets

Cancer immunotherapy works through the interplay between immune and cancer cells. Particularly, interactions between cytotoxic T lymphocytes (CTLs) and cancer cells, such as PDCD1 (PD-1) and CD274 (PD-L1), are crucial for removing cancer cells. However, immune checkpoint inhibitors targeting these interactions are effective only to a subset of patients, requiring the development of novel immunotherapy drugs with novel targets. Genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) screening in either cancer or immune cells has been used to discover regulators of immune cell function as immunotherapeutic targets. However, the method has two main limitations. First, performing CRISPR screens in one cell type alone makes it difficult to identify essential intercellular interactions due to the focus on single genes instead of interactions. Second, pooled screening is associated with high noise levels. Therefore, we propose intercellular CRISPR screens, which perform genome-wide CRISPR screening in every interacting cell type to discover intercellular interactions as immunotherapeutic targets. Intercellular CRISPR screens use two individual genome-wide CRISPR screens one each in immune and cancer cells to evaluate intercellular interactions that are crucial for killing cancer cells. We used two publicly available genome-wide CRISPR screening datasets obtained while triple-negative breast cancer (TNBC) cells and CTLs were interacting. We analyzed 4825 interactions between 1391 ligands and receptors on TNBC cells and CTLs to assess the effects of intercellular interactions on CTL function by incorporating both CRISPR datasets and the expression levels of ligands and receptors. Our results showed that intercellular CRISPR screens discovered targets of approved drugs, a few of which were not identifiable using single datasets. To quantitatively evaluate the methods performance, we used data for cytokines and costimulatory molecules because they constitute the majority of immunotherapeutic targets. Combining both CRISPR datasets improved the F1 score of discovering these genes relative to using single CRISPR datasets by more than twice. Our results indicate that intercellular CRISPR screens can identify novel immune-oncology targets that were not obtained using individual CRISPR screens. The pipeline can be extended to other cancer and immune cell types, such as natural killer cells, to identify important intercellular interactions as potential immunotherapeutic targets.

immunology↗

bioRxiv2022

Quality assessment and refinement of chromatin accessibility data using a sequence-based predictive model

Chromatin accessibility assays are central to the genome-wide identification of gene regulatory elements associated with transcriptional regulation. However, the data have highly variable quality arising from several biological and technical factors. To surmount this problem, we use the predictability of open-chromatin peaks from DNA sequence-based machine-learning models to evaluate and refine chromatin accessibility data. Our framework, gapped k-mer SVM quality check (gkmQC), provides the quality metrics for a sample based on the prediction accuracy of the trained models. We tested 886 samples with DNase-seq from the ENCODE/Roadmap projects to demonstrate that gkmQC can effectively identify high-quality samples underperforming owing to marginal read depths. Peaks identified in high-quality samples by gkmQC are more accurately aligned at functional regulatory elements, show greater enrichment of regulatory elements harboring functional variants from genome-wide association studies (GWAS), and explain greater heritability of phenotypes from their relevant tissues. Moreover, gkmQC can optimize the peak-calling threshold to identify additional peaks, especially for single-cell chromatin accessibility data as well as bulk data. Here we provide a standalone open-source toolkit (https://github.com/Dongwon-Lee/gkmQC) for such analyses and share improved regulatory maps using gkmQC. These resources will contribute to the functional interpretation of disease-associated regulatory genetic variation.

genomics↗

bioRxiv2022

An atlas of gene expression variation across the Caenorhabditis elegans species

Phenotypic variation in diverse organism-level traits have been studied in Caenorhabditis elegans wild strains, but differences in gene expression and the underlying variation in regulatory mechanisms are largely unknown. Here, we use natural variation in gene expression to connect genetic variants to differences in organismal- level traits, including drug and toxicant responses. We performed transcriptomic analysis on 207 genetically distinct C. elegans wild strains to study natural regulatory variation of gene expression. Using this massive dataset, we performed genome-wide association mappings to investigate the genetic basis underlying gene expression variation and revealed complex genetic architectures. We found a large collection of hotspots enriched for expression quantitative trait loci across the genome. We further used mediation analysis to understand how gene expression variation could underlie organism-level phenotypic variation for a variety of complex traits. These results reveal the natural diversity in gene expression and possible regulatory mechanisms in this keystone model organism, highlighting the promise of gene expression variation in shaping phenotypic diversity.

genetics↗