Biology subjects

Lee, D.

Publications and source records attributed to Lee, D..

At least 163 records · Page 9Linked to original sources

bioRxiv2023

TESOGENASE, An Engineered Nuclease Editor for Enhanced Targeted Genome Integration

Summary/AbstractNon-viral DNA donor template has been widely used for targeted genomic integration by homologous recombination (HR). This process has become more efficient with RNA guided endonuclease editor system such as CRISPR/Cas9. Circular single stranded DNA (cssDNA) has been harnessed previously as a genome engineering catalyst (GATALYST) for efficient and safe targeted gene knock-in. However, the engineering efficiency is bottlenecked by the nucleoplasm trafficking and genomic tethering of cssDNA donor, especially for extra-large transgene integration. Here we developed enGager, enhanced GATALYST associated genome editor system by fusion of nucleus localization signal (NLS) peptide tagged Cas9 with various single stranded DNA binding protein modules through a GFP reporter Knock-in screening. The enGager system assembles an integrative genome integration machinery by forming tripartite complex for engineered nuclease editors, sgRNA and ssDNA donors, thereby facilitate the nucleus trafficking of DNA donors and increase their active local concentration at the targeted genomic site. When applied for genome integration with cssDNA donor templates to diverse genomic loci in various cell types, these enGagers outperform unfused editors. The enhancement of integration efficiency ranges from 1.5- to more than 6-fold, with the effect being more prominent for > 4Kb transgene knock-in in primary cells. We further demonstrated that enGager mediated enhancement for genome integration is ssDNA, but less dsDNA dependent. Using one of the mini-enGagers, we demonstrated large chimeric antigen receptor (CAR) transgene integration in primary T cells with exceptional efficiency and anti-tumor function. These tripartite editors with ssDNA optimized genome engineering system (TESOGENASETM) add a set of novel endonuclease editors into the gene-editing toolbox for potential cell and gene therapeutic development based on ssDNA mediated non-viral genome engineering. HighlightO_LIA reporter Knock-in screening establishes enGager system to identify TESOGENASE editor to improving ssDNA mediated genome integration C_LIO_LIMini-TESOGENASEs developed by fusing Cas9 nuclease with novel ssDNA binding motifs C_LIO_LImRNA mini-TESOGENASEs enhance targeted genome integration via various non-viral delivery approaches C_LIO_LIEfficient functional CAR-T cell engineering by mini-TESOGENASE C_LI

bioengineering↗

bioRxiv2023

Modulation of cannabinoid receptor 2 alters neuroinflammation and reduces formation of alpha-synuclein aggregates in a rat model of nigral synucleinopathy

Research into the disequilibrium of microglial phenotypes has become an area of intense focus in neurodegenerative disease as a potential mechanism that contributes to chronic neuroinflammation and neuronal loss in Parkinsons disease (PD). There is growing evidence that neuroinflammation accompanies and may promote progression of alpha-synuclein (Asyn)-induced nigral dopaminergic (DA) degeneration. From a therapeutic perspective, development of immunomodulatory strategies that dampen overproduction of pro-inflammatory cytokines from chronically activated immune cells and induce a pro-phagocytic phenotype is expected to promote Asyn removal and protect vulnerable neurons. Cannabinoid receptor-2 (CB2) is highly expressed on activated microglia and peripheral immune cells, is upregulated in the substantia nigra of individuals with PD and in mouse models of nigral degeneration. Furthermore, modulation of CB2 protects against rotenone-induced nigral degeneration; however, CB2 has not been pharmacologically and selectively targeted in an Asyn model of PD. Here, we report that 7 weeks of peripheral administration of CB2 inverse agonist SMM-189 reduced phosphorylated (pSer129) alpha-synuclein in the substantia nigra compared to vehicle treatment. Additionally, SMM-189 delayed Asyn-induced immune cell infiltration into the brain as determined by flow cytometry, increased CD68 protein expression, and elevated wound-healing-immune-mediator gene expression. Additionally, peripheral immune cells increased wound-healing non-classical monocytes and decreased pro-inflammatory classical monocytes. In vitro analysis of RAW264.7 macrophages treated with lipopolysaccharide (LPS) and SMM-189 revealed increased phagocytosis as measured by the uptake of fluorescence of pHrodo E. coli bioparticles. Together, results suggest that targeting CB2 with SMM-189 skews immune cell function toward a phagocytic phenotype and reduces toxic aggregated species of Asyn. Our novel findings demonstrate that CB2 may be a target to modulate inflammatory and immune responses in proteinopathies.

immunology↗

bioRxiv2023

Enhanced functionalities of immune cells separated by microfludic lattice: assessment based on holotomography

The isolation of white blood cells (WBCs) from whole blood constitutes a pivotal process for immunological studies, diagnosis of hematologic disorders, and the facilitation of immunotherapy. Despite the ubiquity of density gradient centrifugation in WBC isolation, its influence on WBC functionality remains inadequately understood. This research employs holotomography to explore the effects of two distinct WBC separation techniques, namely conventional centrifugation and microfluidic separation, on the functionality of the isolated cells. We utilize three-dimensional refractive index distribution and time-lapse dynamics to conduct an in-depth analysis of individual WBCs, focusing on their morphology, motility, and phagocytic capabilities. Our observations highlight that centrifugal processes negatively impacts WBC motility and phagocytic capacity, whereas microfluidic separation yields a more favorable outcome in preserving WBC functionality. These findings emphasize the potential of microfluidic separation techniques as a viable alternative to traditional centrifugation for WBC isolation, potentially enabling more precise analyses in immunology research and improving the accuracy of hematologic disorder diagnoses.

biophysics↗

bioRxiv2023

Transformation of value signaling in a striatopallidal circuit

The ways in which sensory stimuli acquire motivational valence through association with other stimuli is one of the simplest forms of learning. Though we have identified many brain nuclei that play various roles in reward processing, a significant gap remains in understanding how valence encoding transforms through the layers of sensory processing. To address this gap, we carried out a comparative investigation of the anteromedial olfactory tubercle (OT), and the ventral pallidum (VP) - 2 connected nuclei of the basal ganglia which have both been implicated in reward processing. First, using anterograde and retrograde tracing, we show that both D1 and D2 neurons of the anteromedial OT project primarily to the VP and minimally elsewhere. Using 2-photon calcium imaging, we then investigated how the identity of the odor and reward contingency of the odor are differently encoded by neurons in either structure during a classical conditioning paradigm. We find that VP neurons robustly encode reward contingency, but not identity, in low-dimensional space. In contrast, the OT neurons primarily encode odor identity in high-dimensional space. Although D1 OT neurons showed larger responses to rewarded odors than other odors, consistent with prior findings, we interpret this as identity encoding with enhanced contrast. Finally, using a novel conditioning paradigm that decouples reward contingency and licking vigor, we show that both features are encoded by non-overlapping VP neurons. These results provide a novel framework for the striatopallidal circuit in which a high-dimensional encoding of stimulus identity is collapsed onto a low-dimensional encoding of motivational valence.

neuroscience↗

bioRxiv2023

ESQmodel: biologically informed evaluation of 2-D cell segmentation quality in multiplexed tissue images

MotivationSingle cell segmentation is critical in the processing of spatial omics data to accurately perform cell type identification and analyze spatial expression patterns. Segmentation methods often rely on semi-supervised annotation or labeled training data which are highly dependent on user expertise. To ensure the quality of segmentation, current evaluation strategies quantify accuracy by assessing cellular masks or through iterative inspection by pathologists. While these strategies each address either the statistical or biological aspects of segmentation, there lacks an unified approach to evaluating segmentation accuracy. ResultsIn this paper, we present ESQmodel, a Bayesian probabilistic method to evaluate single cell segmentation using expression data. By using the extracted cellular data from segmentation and a prior belief of cellular composition as input, ESQmodel computes per cell entropy to assess segmentation quality by how consistent cellular expression profiles match with cell type expectations. Availability and implementationSource code is available on Github at: https://github.com/Roth-Lab/ESQmodel under the MIT license.

bioinformatics↗

bioRxiv2023

Anti-muscle Atrophy Effects of Lactobacillus reuteri ATG-F4 and Its Impact on Intestinal Microbiota and Metabolites: Implications for Prophylaxis and Therapy

Lactobacillus reuteri ATG-F4, human gut-derived bacteria, was orally administrated in a model of hindlimb immobilization and confirmed the muscular performance, muscle mass and mechanism on anti-atrophy study. Concomitantly, the changes in the intestinal flora, the metabolites and cytokines were investigated. In the stapled immobilization mice model, ATG- F4 treated group had significantly increased muscle mass, myofiber size, running time to be exhausted and grip strength. The cytokine levels in serum and muscle tissues were reduced by ATG-F4 treatment. Furthermore, the phosphorylation of proteins involved in muscle synthesis such as mTOR, p70S6K, rpS6 and 4E-BP1 increased and MuRF1 related to muscle atrophy factor reduced in the TA and GA muscles. ATG-F4 treatment changed the ratio of main intestinal microflora by increasing the family Muribaculaceae (phylum Bacteroidetes) and decreasing the family Lachnospiraceae (phylum Firmicutes) and Lactobacillaceae (phylum Firmicutes). Also, the level of short chain fatty acids (SCFAs) including butyric acid and acetic acid in the serum of ATG-F4 group were increased. These results suggest that L. reuteri ATG- F4 can inhibit muscle atrophy and it is associated with the microbiota and its metabolites with the anti-inflammation effect. ATG-F4 may be a potential prophylactic or therapeutic composition for muscle atrophy.

physiology↗

bioRxiv2023

Generation of Super-resolution Images from Barcode-based Spatial Transcriptomics Using Deep Image Prior

Spatial transcriptomics (ST) has revolutionized the field of biology by providing a powerful tool for analyzing gene expression in situ. However, current ST methods, particularly barcode-based methods, have limitations in reconstructing high-resolution images from barcodes sparsely distributed in slides. Here, we present SuperST, a novel algorithm that enables the reconstruction of dense matrices from low-resolution ST libraries. SuperST based on deep image prior reconstructs spatial gene expression patterns as image matrices. SuperST allows gene expression mapping to better reflect immunofluorescence (IF) images. Compared with previous methods, SuperST generated output images that more closely resembled IF images for given gene expression maps. Additionally, SuperST overcomes the limitations inherent in IF images, highlighting its potential applications in the realm of spatial biology. By providing a more detailed understanding of gene expression in situ, SuperST has the potential to contribute to comprehensively understanding biology from various tissues.

bioinformatics↗

bioRxiv2023

SpatialSPM: Statistical parametric mapping for the comparison of gene expression pattern images in multiple spatial transcriptomic datasets

Spatial transcriptomic (ST) techniques help us understand the gene expression levels in specific parts of tissues and organs, providing insights into their biological functions. Even though ST dataset provides information on the gene expression and its location for each sample, it is challenging to compare spatial gene expression patterns across tissue samples with different shapes and coordinates. Here, we propose a method that reconstructs ST data into multi-dimensional image matrices to ensure comparability across different samples through spatial registration process. We demonstrated the applicability of this method by using two mouse brain ST datasets to investigate and directly compare gene expression in a specific anatomical region of interest, pixel by pixel, across various biological statuses. It can produce statistical parametric maps to find specific regions with differentially expressed genes across tissue samples. Our approach provides an efficient way to analyze ST datasets and may offer detailed insights into various biological conditions.

bioinformatics↗

bioRxiv2023

Deep learning-based survival prediction using DNA methylation-derived 3D genomic information

Three-dimensional (3D) genome states are closely related to cancer development. Nonetheless, the 3D genome information has not been clinically utilized to the best of our knowledge, due to the costly production of Hi-C data which is a manifest source of 3D genome information. Therefore, there is a need for a novel metric computable from a 3D genome-related data which is more easily accessible for the clinical utilization of 3D genome information. We here propose a method to extract 3D genome-aware epigenetic features from DNA methylation data and use these features for a deep learning-based survival prediction. These features are derived from the 3D genome structures which are rebuilt from the DNA methylation data in an individual level. The results showed that usage of 3D genome-aware features contributed to more accurate risk prediction across seven cancer types, suggesting the effectiveness of the knowledge about 3D genome structure embedded in these features. The deeper biological investigation revealed that altered DNA methylation level in risk-high group could be related to the anomalously activated genes involved in cancer-related pathways. Altogether, the risks predicted from 3D genome-aware epigenetic features showed its significance as a survival predictor in seven cancer types, along with its biological importance.

bioinformatics↗

bioRxiv2023

Multi-scale models reveal hypertrophic cardiomyopathy MYH7 G256E mutation drives hypercontractility and elevated mitochondrial respiration

RationaleOver 200 mutations in the sarcomeric protein {beta}-myosin heavy chain (MYH7) have been linked to hypertrophic cardiomyopathy (HCM). However, different mutations in MYH7 lead to variable penetrance and clinical severity, and alter myosin function to varying degrees, making it difficult to determine genotype-phenotype relationships, especially when caused by rare gene variants such as the G256E mutation. ObjectiveThis study aims to determine the effects of low penetrant MYH7 G256E mutation on myosin function. We hypothesize that the G256E mutation would alter myosin function, precipitating compensatory responses in cellular functions. MethodsWe developed a collaborative pipeline to characterize myosin function at multiple scales (protein to myofibril to cell to tissue). We also used our previously published data on other mutations to compare the degree to which myosin function was altered. ResultsAt the protein level, the G256E mutation disrupts the transducer region of the S1 head and reduces the fraction of myosin in the folded-back state by 50.9%, suggesting more myosins available for contraction. Myofibrils isolated from hiPSC-CMs CRISPR-edited with G256E (MYH7WT/G256E) generated greater tension, had faster tension development and slower early phase relaxation, suggesting altered myosin-actin crossbridge cycling kinetics. This hypercontractile phenotype persisted in single-cell hiPSC-CMs and engineered heart tissues. Single-cell transcriptomic and metabolic profiling demonstrated upregulation of mitochondrial genes and increased mitochondrial respiration, suggesting altered bioenergetics as an early feature of HCM. ConclusionsMYH7 G256E mutation causes structural instability in the transducer region, leading to hypercontractility across scales, perhaps from increased myosin recruitment and altered crossbridge cycling. Hypercontractile function of the mutant myosin was accompanied by increased mitochondrial respiration, while cellular hypertrophy was modest in the physiological stiffness environment. We believe that this multi-scale platform will be useful to elucidate genotype-phenotype relationships underlying other genetic cardiovascular diseases.

molecular biology↗

bioRxiv2023

Reference-free multiplexed single-cell sequencing identifies genetic modifiers of the human immune response

Multiplexed single-cell sequencing (mux-seq) using single-nucleotide polymorphisms (SNPs) has emerged as an efficient approach to perform expression quantitative trait loci (eQTL) studies that map interactions between genetic variants and cell types, cell states, or experimental perturbations. Here we introduce the clue framework, a novel approach to encode mux-seq experiments that eliminates the need for reference genotypes and experimental barcoding. The clue framework is made possible by the development of freemuxlet, an algorithm that clusters cells based on SNPs called from single-cell RNA-seq or ATAC-seq data. To demonstrate the feasibility of clue, we profiled the surface protein and RNA abundances of peripheral blood mononuclear cells from 64 individuals, stimulated with 5 distinct extracellular stimuli -- all within a single day. Our analysis of the demultiplexed data identified rare immune cell types and cell type-specific responses to interferon and toll-like receptor stimulation. Furthermore, by integrating genotyping data, we mapped response eQTLs specific to certain cell types. These findings showcase the potential and scalability of the clue framework for reference-free multiplexed single-cell sequencing studies.

genomics↗

bioRxiv2023

Single cell-guided prenatal derivation of primary epithelial organoids from the human amniotic and tracheal fluids.

Despite advances in prenatal diagnosis, it is still difficult to predict severity and outcomes of many congenital malformations. New patient-specific prenatal disease modelling may optimise personalised prediction. We and others have described the presence of mesenchymal stem cells in amniotic fluid (AFSC) that can generate induced pluripotent stem cells (iPSCs). The lengthy reprogramming processes, however, limits the ability to define individual phenotypes or plan prenatal treatment. Therefore, it would be advantageous if fetal stem cells could be obtained during pregnancy and expanded without reprogramming. Using single cell analysis, we characterised the cellular identities in amniotic fluid (AF) and identified viable epithelial stem/progenitor cells of fetal intestinal, renal and pulmonary origin. With relevance for prenatal disease modelling, these cells could be cultured to form clonal epithelial organoids manifesting small intestine, kidney and lung identity. To confirm this, we derived lung organoids from AF and tracheal fluid (TF) cells of Congenital Diaphragmatic Hernia (CDH) fetuses and found that they show differences to non-CDH controls and can recapitulate some pathological features of the disease. Amniotic Fluid Organoids (AFO) allow investigation of fetal epithelial tissues at clinically relevant developmental stages and may enable the development of therapeutic tools tailored to the fetus, as well as to predicting the effects of such therapies.

cell biology↗

bioRxiv2023

A Spatial Transcriptomics based Label-Free Method for Assessment of Human Stem Cell Distribution and Effects in a Mouse Model of Lung Fibrosis

Recently, cell therapy has emerged as a promising treatment option for various disorders. Given the intricate mechanisms of action (MOA) and heterogenous distribution in target tissues inherent to cell therapy, it is necessary to develop more sophisticated, unbiased approaches to evaluate the distribution of administered cells and the molecular changes at a microscopic level. In this study, we present a label-free approach for assessing the tissue distribution of administered human mesenchymal stem cells (hMSCs) and their MOA, leveraging spatially resolved transcriptomics (ST) analysis. We administered hMSCs to mouse model of lung fibrosis and utilized ST to visualize the spatial distribution of hMSCs within the tissue. This was achieved by capitalizing on interspecies transcript differences between human and mouse. Furthermore, we could examine molecular changes associated with the spatial distribution of hMSCs. We suggest that our method has the potential to serve as an effective tool for various cell-based therapeutic agents.

bioinformatics↗

bioRxiv2023

IAMSAM : Image-based Analysis of Molecular signatures using the Segment-Anything Model

Spatial transcriptomics is a cutting-edge technique that combines gene expression data with spatial information, allowing researchers to study gene expression patterns within tissue architecture. Here, we present IAMSAM, a user-friendly web-based tool for analyzing spatial transcriptomics data focusing on morphological features. IAMSAM accurately segments tissue images using the Segment-anything model, allowing for the semi-automatic selection of regions of interest based on morphological signatures. Furthermore, IAMSAM provides downstream analysis, such as identifying differentially expressed genes, enrichment analysis, and cell type prediction within the selected regions. With its simple interface, IAMSAM empowers researchers to explore and interpret heterogeneous tissues in a streamlined manner.

bioinformatics↗

bioRxiv2023

Frequency- and circuit- specific effects of septohippocampal deep brain stimulation in mice as measured by functional ultrasound imaging.

BackgroundDeep brain stimulation (DBS) has shown remarkable success in treating neurological and psychiatric disorders such as Parkinsons disease, dystonia, epilepsy, and obsessive-compulsive disorder. Despite this success, the underlying mechanism of action remains unknown. DBS is now being explored to improve functional outcomes in other psychiatric conditions, such as those characterized by reduced N-methyl-D-aspartate (NMDA) function (i.e. schizophrenia). While DBS for movement disorders requires high-frequency continuous stimulation, there is evidence that intermittent low-frequency stimulation in neuropsychiatric conditions may have persisting cognitive benefits, necessitating a broader exploration of how DBS alters brain networks. ObjectiveWe characterize the effects of pharmacologic NMDA antagonism on the septohippocampal network and the impact of high- and low-frequency MSN DBS on cerebral blood volume (CBV) in brain structures within and outside of the septohippocampal network. MethodsIn this study, we utilize a novel technology, functional ultrasound imaging (fUSI), to characterize the cerebrovascular impact of medial septal nucleus (MSN) DBS under conditions of NMDA antagonism (pharmacologically using Dizocilpine [MK-801]) in anesthetized male mice. ResultsImaging from a sagittal plane across a variety of brain regions, we find that MSN theta-frequency (7.7Hz) DBS has a larger effect on hippocampal CBV after stimulation offset. This is observed following an intraperitoneal (i.p.) injection of either saline vehicle or MK-801 (1 mg/kg). This effect is not present using standard high-frequency DBS stimulation parameters (i.e. gamma [100Hz]). ConclusionThese results indicate the MSN DBS increases circuit-specific hippocampal neurovascular activity in a frequency-dependent manner that continues beyond the period of electrical stimulation.

neuroscience↗

bioRxiv2023

Information Geometry of the Retinal Representation Manifold

The ability for the brain to discriminate among visual stimuli is constrained by their retinal representations. Previous studies of visual discriminability have been limited to either low-dimensional artificial stimuli or pure theoretical considerations without a realistic encoding model. Here we propose a novel framework for understanding stimulus discriminability achieved by retinal representations of naturalistic stimuli with the method of information geometry. To model the joint probability distribution of neural responses conditioned on the stimulus, we created a stochastic encoding model of a population of salamander retinal ganglion cells based on a three-layer convolutional neural network model. This model not only accurately captured the mean response to natural scenes but also a variety of second-order statistics. With the model and the proposed theory, we computed the Fisher information metric over stimuli to study the most discriminable stimulus directions. We found that the most discriminable stimulus varied substantially across stimuli, allowing an examination of the relationship between the most discriminable stimulus and the current stimulus. By examining responses generated by the most discriminable stimuli we further found that the most discriminative response mode is often aligned with the most stochastic mode. This finding carries the important implication that under natural scenes, retinal noise correlations are information-limiting rather than increasing information transmission as has been previously speculated. We additionally observed that sensitivity saturates less in the population than for single cells and that as a function of firing rate, Fisher information varies less than sensitivity. We conclude that under natural scenes, population coding benefits from complementary coding and helps to equalize the information carried by different firing rates, which may facilitate decoding of the stimulus under principles of information maximization.

neuroscience↗

bioRxiv2023

Hierarchical gradient of timescales in the mammalian forebrain

Many anatomical and physiological features of cortical circuits, ranging from the biophysical properties of synapses to the connectivity patterns among different neuron types, exhibit consistent variation along the hierarchical axis from sensory to association areas. Notably, the scale of temporal correlation of neural activity at rest, known as the intrinsic timescale, increases systematically along this hierarchy in both primates and rodents, analogous to the growing scale and complexity of spatial receptive fields. However, how the timescales for task-related activity vary across brain regions and whether their hierarchical organization appears consistently across different mammalian species remain unexplored. Here, we show that both the intrinsic timescale and the timescales of task-related activity follow a similar hierarchical gradient in the cortices of monkeys, rats, and mice. We also found that these timescales covary similarly in both the cortex and basal ganglia, whereas the timescales of thalamic activity are shorter than cortical timescales and do not conform to the hierarchical order predicted by their cortical projections. These results suggest that the hierarchical gradient of cortical timescales might be a universal feature of intra-cortical circuits in the mammalian brain. Significance StatementA gradual increase in the intrinsic timescales of cortical activity along the anatomical hierarchy reflects the functional specialization of cortical circuits. However, it is unknown whether this gradient of timescales is a common feature across distinct mammalian species in both intrinsic and task-related timescales and whether it is also observed in subcortical areas. This study reveals that the hierarchical gradient of multiple cortical timescales is conserved across multiple mammalian species. By contrast, thalamic timescales were shorter than cortical timescales and did not follow the hierarchical order inferred from their cortical projections. These findings imply a crucial role of intra-cortical connections in structuring distinct temporal dynamics observed across the cortex.

neuroscience↗

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↗