Biology subjects

Lee, D.

Publications and source records attributed to Lee, D..

At least 181 records · Page 10Linked to original sources

bioRxiv2023

Molecular mechanisms for activation of the 26S proteasome

Various hormones, kinases, and stressors (fasting, heat shock) stimulate 26S proteasome activity. To understand how its capacity to degrade ubiquitylated protein can increase, we studied ZFAND5, which promotes protein degradation during muscle atrophy. Cryo-electron microscopy showed that ZFAND5 induces large conformational changes in the 19S regulatory particle. ZFAND5s AN1 Zn finger interacts with the Rpt5 ATPase and its C-terminus with Rpt1 ATPase and Rpn1, a ubiquitin-binding subunit. Surprisingly, these C-terminal interactions are sufficient to activate proteolysis. With ZFAND5 bound, entry into the proteasomes protein translocation channel is wider, and ZFAND5 dissociation causes opening of the 20S gate for substrate entry. Using single-molecular microscopy, we showed that ZFAND5 binds ubiquitylated substrates, prolongs their association with proteasomes, and increases the likelihood that bound substrates undergo degradation, even though ZFAND5 dissociates before substrate deubiquitylation. These changes in proteasome conformation and reaction cycle can explain the accelerated degradation and suggest how other proteasome activators may stimulate proteolysis.

molecular biology↗

bioRxiv2023

Evaluation and optimization of sequence-based gene regulatory deep learning models

Neural networks have emerged as immensely powerful tools in predicting functional genomic regions, notably evidenced by recent successes in deciphering gene regulatory logic. However, a systematic evaluation of how model architectures and training strategies impact genomics model performance is lacking. To address this gap, we held a DREAM Challenge where competitors trained models on a dataset of millions of random promoter DNA sequences and corresponding expression levels, experimentally determined in yeast, to best capture the relationship between regulatory DNA and gene expression. For a robust evaluation of the models, we designed a comprehensive suite of benchmarks encompassing various sequence types. While some benchmarks produced similar results across the top-performing models, others differed substantially. All top-performing models used neural networks, but diverged in architectures and novel training strategies, tailored to genomics sequence data. To dissect how architectural and training choices impact performance, we developed the Prix Fixe framework to divide any given model into logically equivalent building blocks. We tested all possible combinations for the top three models and observed performance improvements for each. The DREAM Challenge models not only achieved state-of-the-art results on our comprehensive yeast dataset but also consistently surpassed existing benchmarks on Drosophila and human genomic datasets. Overall, we demonstrate that high-quality gold-standard genomics datasets can drive significant progress in model development.

genomics↗

bioRxiv2023

3D structural human interactome reveals proteome-wide perturbations by disease mutations

Human genome sequencing studies have identified numerous loci associated with complex diseases. However, translating human genetic and genomic findings to disease pathobiology and therapeutic discovery remains a major challenge at multiscale interactome network levels. Here, we present a deep-learning-based ensemble framework, termed PIONEER (Protein-protein InteractiOn iNtErfacE pRediction), that accurately predicts protein binding partner-specific interfaces for all known protein interactions in humans and seven other common model organisms, generating comprehensive structurally-informed protein interactomes. We demonstrate that PIONEER outperforms existing state-of-the-art methods. We further systematically validated PIONEER predictions experimentally through generating 2,395 mutations and testing their impact on 6,754 mutation-interaction pairs, confirming the high quality and validity of PIONEER predictions. We show that disease-associated mutations are enriched in PIONEER-predicted protein-protein interfaces after mapping mutations from [~]60,000 germline exomes and [~]36,000 somatic genomes. We identify 586 significant protein-protein interactions (PPIs) enriched with PIONEER-predicted interface somatic mutations (termed oncoPPIs) from pan-cancer analysis of [~]11,000 tumor whole-exomes across 33 cancer types. We show that PIONEER-predicted oncoPPIs are significantly associated with patient survival and drug responses from both cancer cell lines and patient-derived xenograft mouse models. We identify a landscape of PPI-perturbing tumor alleles upon ubiquitination by E3 ligases, and we experimentally validate the tumorigenic KEAP1-NRF2 interface mutation p.Thr80Lys in non-small cell lung cancer. We show that PIONEER-predicted PPI-perturbing alleles alter protein abundance and correlates with drug responses and patient survival in colon and uterine cancers as demonstrated by proteogenomic data from the National Cancer Institutes Clinical Proteomic Tumor Analysis Consortium. PIONEER, implemented as both a web server platform and a software package, identifies functional consequences of disease-associated alleles and offers a deep learning tool for precision medicine at multiscale interactome network levels.

bioinformatics↗

bioRxiv2023

daf-42 is an evolutionarily young gene essential for dauer development in Caenorhabditis elegans

Under adverse environmental conditions, nematodes arrest into dauer, an alternative developmental stage for diapause. Dauer endures unfavorable environments and interacts with host animals to access favorable environments, thus playing a critical role in survival. Here, we report that in Caenorhabditis elegans, daf-42 is essential for development into the dauer stage, as the null mutant of daf-42 exhibited a "no viable dauer" phenotype in which no viable dauers were obtained in any dauer-inducing conditions. Long-term time lapse microscopy of synchonized larvae revealed that daf-42 is involved in developmental changes from the pre-dauer L2d stage to the dauer stage. daf-42 encodes large, disordered proteins of various sizes that are expressed in and secreted from the seam cells within a narrow time window shortly before the molt into dauer stage. Transcriptome analysis showed that the transcription of genes involved in larval physiology and dauer metabolism are highly affected by the daf-42 mutation. Contrary to the notion that essential genes that control the life and death of an organism may well be conserved across diverse species, daf-42 is an evolutionarily young gene conserved only in the Caenorhabditis genus. Our study shows that dauer formation is a vital process that is controlled not only by conserved genes but also by newly emerged genes, providing important insights into evolutionary mechanisms.

developmental biology↗

bioRxiv2023

Piperidine CD4-mimetic compounds expose vulnerable Env epitopes sensitizing HIV-1-infected cells to ADCC

The ability of HIV-1 accessory proteins Nef and Vpu to decrease CD4 levels contributes to the protection of infected cells from antibody-dependent cellular cytotoxicity (ADCC) by preventing the exposure of Env vulnerable epitopes. Small-molecule CD4 mimetics (CD4mc) based on the indane and piperidine scaffolds such as (+)-BNM-III-170 and (S)-MCG-IV-210 sensitize HIV-1 infected cells to ADCC by exposing CD4-induced (CD4i) epitopes recognized by non-neutralizing antibodies abundantly present in plasma from people living with HIV. Here, we characterize a new family of CD4mc, (S)-MCG-IV-210 derivatives, based on the piperidine scaffold which engage the gp120 within the Phe43 cavity by targeting the highly-conserved Asp368 Env residue. We utilized structure-based approaches and developed a series of piperidine analogs with improved activity to inhibit infection of difficult-to-neutralize tier-2 viruses and sensitize infected cells to ADCC mediated by HIV+ plasma. Moreover, the new analogs formed an H-bond with the -carboxylic acid group of Asp368, opening a new avenue to enlarge the breadth of this family of anti-Env small molecules. Overall, the new structural and biological attributes of these molecules make them good candidates for strategies aimed at the elimination HIV-1-infected cells.

immunology↗

bioRxiv2023

Efficient differential expression analysis of large-scale single cell transcriptomics data using dreamlet

Advances in single-cell and -nucleus transcriptomics have enabled generation of increasingly large-scale datasets from hundreds of subjects and millions of cells. These studies promise to give unprecedented insight into the cell type specific biology of human disease. Yet performing differential expression analyses across subjects remains difficult due to challenges in statistical modeling of these complex studies and scaling analyses to large datasets. Our open-source R package dreamlet (DiseaseNeurogenomics.github.io/dreamlet) uses a pseudobulk approach based on precision-weighted linear mixed models to identify genes differentially expressed with traits across subjects for each cell cluster. Designed for data from large cohorts, dreamlet is substantially faster and uses less memory than existing workflows, while supporting complex statistical models and controlling the false positive rate. We demonstrate computational and statistical performance on published datasets, and a novel dataset of 1.4M single nuclei from postmortem brains of 150 Alzheimers disease cases and 149 controls.

genomics↗

bioRxiv2023

Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data

Sample-wise deconvolution methods have been developed to estimate cell-type proportions and gene expressions in bulk-tissue samples. However, the performance of these methods and their biological applications has not been evaluated, particularly on human brain transcriptomic data. Here, nine deconvolution methods were evaluated with sample-matched data from bulk-tissue RNAseq, single-cell/nuclei (sc/sn) RNAseq, and immunohistochemistry. A total of 1,130,767 nuclei/cells from 149 adult postmortem brains and 72 organoid samples were used. The results showed the best performance of dtangle for estimating cell proportions and bMIND for estimating sample-wise cell-type gene expression. For eight brain cell types, 25,273 cell-type eQTLs were identified with deconvoluted expressions (decon-eQTLs). The results showed that decon-eQTLs explained more schizophrenia GWAS heritability than bulk-tissue or single-cell eQTLs alone. Differential gene expression associated with multiple phenotypes were also examined using the deconvoluted data. Our findings, which were replicated in bulk-tissue RNAseq and sc/snRNAseq data, provided new insights into the biological applications of deconvoluted data.

genomics↗

bioRxiv2023

Genetic regulation of cell-type specific chromatin accessibility shapes the etiology of brain diseases

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are major risk factors of human disease. We measured chromatin accessibility in sorted neurons and glia from 1,932 samples of human postmortem brain and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTL). Only 10.4% of caQTL are shared between neurons and glia, supporting the cell type specificity of genetic regulation of the brain regulome. Incorporating allele specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms underlying disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs, identifying the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides novel insights into brain disease etiology. One sentence summaryCell-type specific chromatin accessibility QTL reveals regulatory mechanisms underlying brain diseases.

genomics↗

bioRxiv2023

AMLs harboring DNMT3A-destabilizing variants show increased intratumor DNA methylation heterogeneity at bivalent chromatin domains

The mechanistic link between the complex mutational landscape of de novo methyltransferase DNMT3A and the pathology of acute myeloid leukemia (AML) has not been clearly elucidated so far. A recent discovery on the catalogue of DNMT3A-destabilizing mutations throughout the DNMT3A gene as well as the oligomerization-dependent catalytic property of DNMT3A prompted us to investigate the common effect of DNMT3A-destabilizing mutations (DNMT3AINS) on the genomewide methylation patterns of AML cells. In this study, we describe the characteristics of DNMT3AINS AML methylomes through the comprehensive computational analyses on three independent AML cohorts. As a result, we show that methylomes of DNMT3AINS AMLs are considerably different from those of DNMT3AR882 AMLs in that they exhibit both locally disordered DNA methylation states and increased across-cell DNA methylation heterogeneity in bivalent chromatin domains. This increased epigenetic heterogeneity was functionally associated with heterogeneous expression of membrane-associated factors shaping stem cell niche, implying the diversification of the modes of leukemic stem cell-niche interactions. We also present that the level of methylation disorder at bivalent domains predicts the response of AML cells to hypomethylating agents through cell line- and patient-level analyses, which supports that the survival of AML cells depends on stochastic DNA methylations at bivalent domains. Altogether, our work provides a novel mechanistic model suggesting the genomic origin of the aberrant epigenomic heterogeneity in disease conditions.

cancer biology↗

bioRxiv2023

Stochastic Modeling of Tinnitus Loudness

There has been no study on the relationship between chronic tinnitus and harmonic templates. Harmonic templates are harmonically structured receptive fields in the auditory system in which all frequency components are integer multiples of a common fundamental frequency (F0). In this study, data from 19 harmonic templates from each of 196 chronic tinnitus patients were analyzed and mathematical modeling was performed to quantify the loudness of chronic tinnitus. High-resolution hearing threshold data were obtained by algorithmic pure tone audiometry (PTA) conducting automated PTA at 134 frequency bands with 1/24 octave resolution from 250 Hz to 12,000 Hz. The result showed that there is an intriguing relationship between the auditory instability of harmonic templates and simplified tinnitus severity score (STSS). This study provides several mathematical models to estimate tinnitus severity and the precise quantification of the loudness of chronic tinnitus. Our computational models and analysis of the behavioral hearing threshold fine structure suggest that the cause of severe chronic tinnitus could be a severe disparity between different temporal capacities of each neural oscillator in a certain harmonic template.

neuroscience↗

bioRxiv2023

GeneDART: Extending gene coverage in image-based spatial transcriptomics by deep learning-based domain adaptation with barcode-based RNA-sequencing data

Spatial transcriptomics (ST) technologies provide comprehensive biological insights regarding cell-cell interactions and peri-cellular microenvironments. ST technologies are divided into two categories: imaging-based (I-B) and barcode-based (B-B). I-B ST technologies provide high resolution and sensitivity but have limited gene coverage. B-B ST technologies can analyze the whole transcriptome but have lower spatial resolution. To address these limitations, we propose a deep learning-based model that integrates I-B and B-B ST technologies to increase gene coverage while preserving high resolution. A model, trained by a neural network with an adversarial loss based on I-B and B-B datasets from human breast cancer tissue, was able to extend gene coverage to whole transcripts-level and accurately predict gene expression patterns in the I-B dataset with a high resolution. This novel methodology, named GeneDART, could enable researchers to utilize B-B and I-B ST datasets in a complementary way.

bioinformatics↗

bioRxiv2023

Robust single membrane protein tweezers

Single-molecule tweezers, such as magnetic tweezers, are powerful mechanical manipulation tools that can probe nm-scale structural changes in a single membrane protein under force. However, the weak molecular tethers used in the tweezers limit a long time, repetitive mechanical manipulation because of their force-induced bond breakage. Here, using the metal-free click chemistry of dibenzocyclooctyne (DBCO) cycloaddition and the rapid, strong binding of traptavidin to dual biotins (2xbiotin), we developed robust single-molecule tweezers that can perform thousands of force applications on a single membrane protein. By applying up to 50 pN for each cycle, which is sufficiently high for most biological processes, we were able to observe repetitive forced unfolding for a designer membrane protein up to approximately 1000 times on average. Monte Carlo simulations showed that the average error of the unfolding kinetic values rapidly decays to 1.8% at 200-time pulling, indicating that our method can quickly produce reliable statistics. The approach established here is also applicable to highly polar DNA molecules, permitting the nanomechanical manipulation of diverse biomolecular systems.

biophysics↗

bioRxiv2023

KOMPUTE: Imputing summary statistics of missing phenotypes in high-throughput model organism data

MotivationThe International Mouse Phenotyping Consortium (IMPC) is striving to build a comprehensive functional catalog of mammalian protein-coding genes by systematically producing and phenotyping gene-knockout mice for almost every protein-coding gene in the mouse genome and by testing associations between gene loss-of-function and phenotype. To date, the IMPC has identified over 90,000 gene-phenotype associations, but many phenotypes have not yet been measured for each gene, resulting in largely incomplete data; about 75.6% of association summary statistics are still missing in the latest IMPC summary statistics dataset (IMPC release version 16). ResultsTo overcome these challenges, we propose KOMPUTE, a novel method for imputing missing summary statistics in the IMPC dataset. Using conditional distribution properties of multivariate normal, KOMPUTE estimates association Z-scores of unmeasured phenotypes for a particular gene as a conditional expectation given the Z-scores of measured phenotypes. We evaluate the efficacy of the proposed method for recovering missing Z-scores using simulated and real-world data sets and compare it to a singular value decomposition (SVD) matrix completion method. Our results show that KOMPUTE outperforms the comparison method across different scenarios. Availability and implementationAn R package for KOMPUTE is publicly available at https://github.com/statsleelab/kompute, along with usage examples and results for different phenotype domains at https://statsleelab.github.io/komputeExamples. Contactleed13@miamioh.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2022

Modulation of lysosomal Cl- mediates migration and apoptosis through the TRPML1 as a lysosomal Cl- sensor

Lysosomes are responsible for protein degradation and clearance in cellular recycling centers. It has been known that the lysosomal chloride level is enriched and involved in intrinsic lysosomal function. However, the mechanism by which chloride levels can be sensed and the chloride-mediated lysosomal function is unknown. In this study, we verified that reduced chloride levels acutely induced lysosomal calcium release through TRPML1 and lysosomal repositioning toward juxtanuclear region. Functionally, low chloride-induced lysosomal calcium release attenuated cellular migration. In addition, spontaneous exposure to low chloride levels dysregulated lysosomal biogenesis and subsequently induced the delayed migration and promoted apoptosis. Two chloride-sensing GXXXP motifs in the TRPML1 were identified. Mutations in the GXXXP motif of TRPML1 did not affect chloride levels and no changes in migratory ability. In this study, we demonstrated that the depleted chloride approach induces reformation of the lysosomal calcium pool, and subsequent dysregulated cancer progression will assist in improving therapeutic strategies for lysosomal accumulation-associated diseases or cancer cell apoptosis.

molecular biology↗

bioRxiv2022

Circular single-stranded DNA is a superior homology-directed repair donor template for efficient genome engineering

The toolbox for genome editing in basic research and therapeutic applications is rapidly expanding. While efficient targeted gene ablation using nuclease editors has been demonstrated from bench to bedside, precise transgene integration remains a technical challenge. AAV6 has been a prevalent donor carrier for homology-directed repair (HDR) mediated genome engineering but has reported safety issues, manufacturing constraints, and restricted applications due to its 4.5 Kb packaging limit. Non-viral targeted genetic knock-ins rely primarily on double-stranded DNA (dsDNA) and linear single-stranded DNA (lssDNA) donors. Both dsDNA and lssDNA have been previously demonstrated to have low efficiency and cytotoxicity. Here, we developed a non-viral genome writing catalyst (GATALYST) system which allows production of ultrapure, minicircle single-stranded DNAs (cssDNAs) up to [~]20 Kb as donor templates for highly efficient precision transgene integration. cssDNA donors enable knock-in efficiency of up to 70% in induced pluripotent stem cells (iPSCs), superior efficiency in multiple clinically relevant primary cell types, and at multiple genomic loci implicated for clinical applications with various nuclease editor systems. When applied to immune cell engineering, cssDNA engineered CAR-T cells exhibit more potent and durable anti-tumor efficacy than those engineered from AAV6 viral vectors. The exceptional precision and efficiency, improved safety, payload flexibility, and scalable manufacturability of cssDNA unlocks the full potential of genome engineering with broad applications in therapeutic development, disease modeling and other research areas. HighlightsO_LIScalable production of minicircle ssDNA (cssDNA) with highly engineered phagemid system C_LIO_LIGenome writing catalyst (GATALYST) system with cssDNA donor template demonstrates superior efficiency and safety in various cell types and genomic loci C_LIO_LIGATALYST gene writing system enables ultra-large transgene integration C_LIO_LIcssDNA engineered CAR-T outperforms AAV engineered CAR-T with superior anti-tumor function C_LI

bioengineering↗

bioRxiv2022

Natural genetic variation in the pheromone production of C. elegans

From bacterial quorum sensing to human language, communication is essential for social interactions. Nematodes produce and sense pheromones to communicate among individuals and respond to environmental changes. These signals are encoded by different types and mixtures of ascarosides, whose modular structures further enhance the diversity of this nematode pheromone language. Interspecific and intraspecific differences in this ascaroside pheromone language have been described previously, but the genetic basis and molecular mechanisms underlying the variation remain largely unknown. Here, we analyzed natural variation in the production of 44 ascarosides across 95 wild Caenorhabditis elegans strains using high-performance liquid chromatography coupled to high-resolution mass spectrometry (HPLC-HRMS). By cross-analyzing genomes and exo-metabolomes of wild strains, we discovered quantitative trait loci (QTL) that underlie the natural differences in pheromone bouquet composition. Fine mapping of the QTL further uncovered associations between mitochondrial metabolism and pheromone production. Our findings demonstrate how natural genetic variation in core metabolic pathways can affect the production of social signals.

evolutionary biology↗

bioRxiv2022

Engineered molecular sensors of cell surface crowding

Cells mediate interactions with the extracellular environment through a crowded assembly of transmembrane proteins, glycoproteins and glycolipids on their plasma membrane. The extent to which surface crowding modulates the biophysical interactions of ligands, receptors, and other macromolecules is poorly understood due to the lack of methods to quantify surface crowding on native cell membranes. In this work, we demonstrate that physical crowding on reconstituted membranes and live cell surfaces attenuates the effective binding affinity of macromolecules such as IgG antibodies in a surface crowding-dependent manner. We combine experiment and simulation to design a crowding sensor based on this principle that provides a quantitative readout of cell surface crowding. Our measurements reveal that surface crowding decreases IgG antibody binding by 2-20 fold in live cells compared to a bare membrane surface, resulting in a cell surface osmotic pressure opposing binding of 1 - 4 kPa. Our sensors show that sialic acid, a negatively charged monosaccharide, contributes disproportionately to red blood cell surface crowding via electrostatic repulsion, despite occupying only ~1% of the total cell membrane by mass. We also observe significant differences in surface crowding for different cell types and find that expression of single oncogenes can both increase and decrease crowding, suggesting that surface crowding may be an indicator of both cell type and state. Our high-throughput, single-cell measurement of cell surface osmotic pressure may be combined with functional assays to enable further biophysical dissection of the cell surfaceome. Significance StatementCells interact with each other and the extracellular environment through a crowded assembly of polymers on their plasma membranes. The high density of these surface polymers can generate physical crowding that impacts cell function. However, tools to quantify the extent and effect of surface crowding on live cell membranes are lacking. In this work, we design macromolecular sensors that act as direct reporters of cell surface crowding. We combine experiments on reconstituted and live cell surfaces with molecular dynamics simulations to provide a mechanistic understanding of how cell surface crowding reduces binding of soluble molecules, and we show that crowding varies significantly with cell type and is affected by oncogene expression.

biophysics↗

bioRxiv2022

Anti-Inflammatory Tension-Activated Repair Patches Improve Repair After Intervertebral Disc Herniation

Conventional treatment for intervertebral disc herniation alleviates pain but does not repair the annulus fibrosus (AF), resulting in a high incidence of recurrent herniation and persistent disfunction. The lack of repair and the acute inflammation that arise after injury further compromises the disc and can result in disc-wide degeneration in the long term. To address this clinical need, we developed tension-activated repair patches (TARPs) for annular repair and the local delivery of bioactive anti-inflammatory factors. TARPs transmit physiologic strains to mechanically-activated microcapsules (MAMCs) embedded within, which activate and release encapsulated biomolecules in response to physiologic loading. Here, we demonstrate that the TARP design modulates implant biomechanical properties and regulates MAMC mechano-activation. Next, the FDA-approved anti-inflammatory molecule, interleukin 1 receptor antagonist, Anakinra, was loaded in TARPs and the effects of TARP-mediated annular repair and Anakinra delivery was evaluated in a model of annular injury in the goat cervical spine. TARPs showed robust integration with the native tissue and provided structural reinforcement at the injury site that prevented disc-wide aberrant remodeling resulting from AF detensioning. The delivery of Anakinra via TARP implantation improved the retention of disc biochemical composition through increased matrix deposition and retention at the site of annular injury. Anakinra delivery additionally attenuated the inflammatory response associated by scaffold implantation, decreasing osteolysis in adjacent vertebrae and preserving disc cellularity and matrix organization throughout the AF. These results demonstrate the translational and therapeutic potential of this novel TARP system for the treatment of intervertebral disc herniations. One Sentence SummaryTension-activated repair patches delivering bioactive anti-inflammatory factors improve healing in an in vivo goat cervical disc injury model.

bioengineering↗