Biology subjects

Lee, K.

Publications and source records attributed to Lee, K..

At least 19 recordsLinked to original sources

bioRxiv2018

Subcellular Time Series Modeling of Heterogeneous Cell Protrusion

In this paper, a new biological modeling approach is proposed for predicting complex heterogeneous subcellular behaviors. Cell protrusion which initiates cell migration has a significant amount of subcellular heterogeneity in micrometer length and minute time scales. It is driven by actin polymerization, e.g., pushing the plasma membrane forward, and then regulated by a multitude of actin regulators. While mathematical modeling is central to system-level understandings of cell protrusion, most of the modeling is based on the ensemble average of actin regulator dynamics at the cellular or population levels, preventing from capturing the heterogeneous cellular activities. With these in mind, a systematic modeling framework is proposed in this paper for predicting velocities of heterogeneous protrusion of migrating cells driven by multiple molecular mechanisms. The modeling framework is developed through the integration of the multiple AutoRegressive eXogenous (ARX) models employing probability density input variables. Unlike conventional ARX models, it provides an effective framework for modeling heterogeneous subcellular behaviors with complex nonlinearities and uncertainties of dynamic systems. To train and validate the proposed model, numerous subcellular time series are extracted from time-lapse movies of migrating PtK1 cells using spinning disk confocal microscope: The current edge velocities and fluorescent intensities of mDia1, actin at the leading edge are used as the input while the future cell edge velocities are selected as an output. It is demonstrated that the proposed approach is highly effective in predicting the future trends of heterogeneous cell protrusion. In particular, by capturing the various multiple activities from the dataset, it is expected that it would improve the understanding of the molecular mechanism underlying cellular and subcellular heterogeneity.

systems biology↗

bioRxiv2018

Genetic Diversity Patterns and Domestication Origin of Soybean

Understanding diversity and evolution of a crop is an essential step to implement a strategy to expand its germplasm base for crop improvement research. Samples intensively collected from Korea, which is a small but central region in the distribution geography of soybean, were genotyped to provide sufficient data to underpin genome-wide population genetic questions. After removing natural hybrids and duplicated or redundant accessions, we obtained a non-redundant set comprising 1,957 domesticated and 1,079 wild accessions to perform population structure analyses. Our analysis demonstrates that while wild soybean germplasm will require additional sampling from diverse indigenous areas to expand the germplasm base, the current domesticated soybean germplasm is saturated in terms of genetic diversity. We then showed that our genome-wide polymorphism map enabled us to detect genetic loci underling flower color, seed-coat color, and domestication syndrome. A representative soybean set consisting of 194 accessions were divided into one domesticated subpopulation and four wild subpopulations that could be traced back to their geographic collection areas. Population genomics analyses suggested that the monophyletic group of domesticated soybeans was originated in eastern Japan. The results were further substantiated by a phylogenetic tree constructed from domestication-associated single nucleotide polymorphisms identified in this study.

plant biology↗

bioRxiv2018

What you predict, not what you do, updates memories in visuomotor adaptation

Sensory prediction errors are thought to update memories in motor 1 adaptation, but the role of performance errors is largely unknown. To dissociate these errors, we manipulated visual feedback during fast shooting movements under visuomotor rotation. Participants were instructed to strategically correct for performance errors by shooting to a neighboring target in one of four conditions: following the movement onset, the main target, the neighboring target, both targets, or none of the targets disappeared. Participants in all conditions experienced a drift away from the main target following the strategy. In conditions where the main target was shown, participants often tried to minimize performance errors caused by the drift by generating corrective movements. However, despite differences in performance during adaptation between conditions, memory decay in a delayed washout block was indistinguishable between conditions. Our results thus suggest that, in visuomotor adaptation, sensory predictions errors, but not performance errors, update the slow, temporally stable, component of motor memory.

neuroscience↗

bioRxiv2018

Propagation of information along the cortical hierarchy as a function of attention while reading and listening to stories

How does attention route information from sensory to high-order areas as a function of task, within the relatively fixed topology of the brain? In this study, participants were simultaneously presented with two unrelated stories - one spoken and one written - and asked to attend one while ignoring the other. We used fMRI and a novel inter-subject correlation analysis to track the spread of information along the processing hierarchy as a function of task. Processing the unattended spoken (written) information was confined to auditory (visual) cortices. In contrast, attending to the spoken (written) story enhanced the stimulus-selective responses in early sensory regions and allowed it to spread into higher-order areas. Surprisingly, we found that the story-specific spoken (written) responses for the attended story also reached the opposite secondary visual (auditory) regions. These results demonstrate how attention enhances the processing of attended input and allows it to propagate across brain areas.

neuroscience↗

bioRxiv2018

Functional repair after ischemic injury through high efficiency in situ astrocyte-to-neuron conversion

Mammalian brains have largely lost internal neural regeneration capability except for a few discrete neurogenic niches. After brain injury, the cerebral cortex is especially difficult to repair due to its extremely low rate of adult neurogenesis. Previous studies have converted glial cells into neurons, but the total number of neurons generated is rather limited, casting doubt about its therapeutic potential. Here, we demonstrate that high-efficiency neuroregeneration can be achieved in adult mammalian brains by making use of an engineered AAV Cre-FLEX system to convert a large number of reactive astrocytes into functional neurons. Specifically, using a combination of GFAP::Cre and FLEX-NeuroD1 AAV system, we were able to regenerate enough new neurons from astrocytes to cover about 40% of the neurons lost from an ischemic injury (400 NeuN+ new neurons/mm2), compared to previously reported an average of <1% of cortical neurons (2-8 NeuN+ neurons/mm2) in an ischemic-injured adult mammalian cortex. Importantly, this in situ astrocyte-to-neuron conversion process also improved survival of injured pre-existing neurons, (additional 400 neurons/mm2), leading to a repaired motor cortex with layered cortical structures. Moreover, NeuroD1-converted neurons not only form functional neural circuits but also rescue motor and memory deficits after ischemic injury. Our results establish the proof-of-principle that a highly efficient in situ astrocyte-to-neuron conversion approach provides a novel treatment for neurological disorders that are in need of new neurons.

neuroscience↗

bioRxiv2018

Constructing and visualizing cancer genomic maps in 3D spatial context by phenotype-based high-throughput laser-aided isolation and sequencing (PHLI-seq)

A spatially resolved analysis of the heterogeneous cancer genome, in which the data are connected to the three-dimensional space of a tumour, is crucial to understand cancer biology and the clinical impact of cancer heterogeneity on patients. However, despite recent progress in spatially resolved transcriptomics, spatial mapping of genomic data in a high-throughput and high-resolution manner has been challenging due to current technical limitations. Here, we describe a novel approach, phenotype-based high-throughput laser-aided isolation and sequencing (PHLI-seq), which enables high-throughput isolation of a single-cell or a small number of cells and their genome-wide sequence analysis to construct genomic maps within cancer tissue in relation to the phenotypes of the cells. By applying PHLI-seq, we reveal the heterogeneity of breast cancer tissues at a high resolution and map the genomic landscape of the cells to their corresponding spatial locations and phenotypes in the tumour mass. Additionally, with different staining modalities, the genotypes of the cells can be connected to corresponding phenotypic information of the tissue. Together with the spatially resolved genomic analysis, we can infer the histories of heterogeneous cancer cells in two or three dimensions, providing significant insight into cancer biology and precision medicine.

genomics↗

bioRxiv2018

Soil microbial habitats in an extreme desert Mars-analogue environment

Sediments in the hyper-arid core of the Atacama Desert are a terrestrial analogue to Mars regolith. Understanding the distribution and drivers of microbial life in the sediment may give critical clues on how to search for biosignatures on Mars. Here, we identify the spatial distribution of highly specialised bacterial communities in previously unexplored depth horizons of subsurface sediments. We deployed an autonomous rover in a mission-relevant Martian drilling scenario with manual sample validation. Subsurface communities were delineated by depth related to sediment moisture. Geochemical analysis indicated soluble salts and minerology that influenced water bio-availability, particularly in deeper sediments. Colonization was also patchy and uncolonized sediment was associated with indicators of extreme osmotic challenge. The study identifies linkage between biocomplexity, moisture and geochemistry in Mars-like sediments at the limit of habitability and demonstrates feasibility of the rover-mounted drill for future Mars sample recovery.

microbiology↗

bioRxiv2018

Gradual repression of selenoprotein W ensures physiological bone remodelling

Selenoproteins containing selenium in the form of selenocysteine are critical for bone remodelling. However, their mechanism of action is not well understood. Here, we report the identification of selenoprotein W (SELENOW) through large-scale mRNA profiling of receptor activator of nuclear factor (NF)-{kappa}B ligand (RANKL)-induced osteoclast differentiation, as a protein that is downregulated via RANKL/RANK/tumour necrosis factor receptor-associated factor 6/p38 signalling. RNA sequencing analysis revealed that SELENOW regulates osteoclastogenic genes. SELENOW overexpression enhanced osteoclastogenesis in vitro via nuclear translocation of NF-{kappa}B and nuclear factor of activated T-cells cytoplasmic 1, whereas its loss suppressed osteoclast formation. SELENOW-deficient and SELENOW-overexpressing mice exhibited osteopetrosis and osteoporosis, respectively. Ectopic SELENOW expression stimulated cell-cell fusion critical for osteoclast maturation as well as bone resorption. Thus, RANKL-dependent repression of SELENOW maintains proper osteoclast differentiation and blocks osteoporosis caused by overactive osteoclasts. These findings demonstrate a biological link between selenium and bone metabolism.

physiology↗

bioRxiv2017

Directed evolution of CRISPR-Cas9 to increase its specificity

The use of CRISPR-Cas9 as a therapeutic reagent is hampered by its off-target effects. Although rationally designed S. pyogenes Cas9 (SpCas9) variants that display higher specificities than the wild-type SpCas9 protein are available, these attenuated Cas9 variants are often poorly efficient in human cells. Here, we have used a directed evolution approach in E. coli to obtain Sniper-Cas9, which shows high specificities without sacrificing on-target activities in human cells.

biochemistry↗

bioRxiv2017

The molecular basis for Pompe disease revealed by the structure of human acid α-glucosidase

Pompe disease results from a defect in human acid -glucosidase (GAA), a lysosomal enzyme that cleaves terminal 1-4 and 1-6 glucose from glycogen. In Pompe disease (also known as Glycogen Storage Disorder type II), the accumulation of undegraded glycogen in lysosomes leads to cellular dysfunction, primarily in muscle and heart tissues. Pompe disease is an active candidate of clinical research, with pharmacological chaperone therapy tested and enzyme replacement therapy approved. Despite production of large amounts of recombinant GAA annually, the structure of GAA has not been reported until now. Here, we describe the first structure of GAA, at 1.7[A] resolution. Three structures of GAA complexes reveal the molecular basis for the hundreds of mutations that lead to Pompe disease and for pharmacological chaperoning in the protein. The GAA structure reveals a surprising second sugar-binding site 34[A] from the active site, suggesting a possible mechanism for processing of large glycogen substrates. Overall, the structure will assist in the design of next-generation treatments for Pompe disease.

biochemistry↗

bioRxiv2017

Molecular structure of human KATP in complex with ATP and ADP

In many excitable cells KATP channels respond to intracellular adenosine nucleotides: ATP inhibits while ADP activates. We present two structures of the human pancreatic KATP channel, containing the ABC transporter SUR1 and the inward-rectifier K+ channel Kir6.2, in the presence of Mg2+ and nucleotides. These structures, referred to as quatrefoil and propeller forms, were determined by single-particle cryo-EM at 3.9 [A] and 5.6 [A], respectively. In both forms ATP occupies the inhibitory site in Kir6.2. The nucleotide-binding domains of SUR1 are dimerized with Mg2+-ATP in the degenerate site and Mg2+-ADP in the consensus site. A lasso extension forms an interface between SUR1 and Kir6.2 adjacent to the ATP site in the propeller form, and is disrupted in the quatrefoil form. These structures support the role of SUR1 as an ADP sensor and highlight the lasso extension as a key regulatory element in ADPs ability to override ATP inhibition.

biophysics↗

bioRxiv2017

Interferon-inducible miR-128 modulates HIV-1 replication by targeting TNPO3 mRNA

The HIV/AIDS pandemic remains an important threat to human health. We have recently demonstrated that a novel microRNA (miR-128) represses retrotransposon (LINE-1 or L1) by a dual mechanism, by directly targeting the coding region of the L1 RNA and by repressing a required nuclear import factor (TNPO1). We have further determined that miR-128 represses the expression of all three isoforms of TNPO proteins (transportins, TNPO1,-2 and TNPO3). Here, we establish that miR-128 also controls HIV-1 replication by repressing TNPO3. TNPO3 is well established to regulate HIV-1 nuclear import and viral replication. Here, we report that the type I interferon inducible miR-128 directly targets two sites in the TNPO3 mRNA, significantly down-regulating TNPO3 mRNA and protein expression levels. Manipulation of miR-128 levels in HIV target cell lines and in primary human CD4 T-cells by over-expression or knockdown showed that modulation of TNPO3 by miR-128 affects HIV-1 replication but not MLV infection. In addition, we found that miR-128 modulation of HIV-1 replication is reduced with TNPO3-independent HIV-1 virus and in cells depleted of CPSF6, suggesting that miR-128-indued TNPO3 repression is partly required for miR-128-induced inhibition of HIV-1 replication. Finally, challenging miR-modulated Jurkat cells or primary CD4 T-cells with wildtype, replication-competent HIV-1 shows that miR-128 significantly delays spreading infection. Thus, we have established a novel role of miR-128 in anti-viral defense in human cells, inhibiting HIV-1 replication partly by targeting TNPO3.

cell biology↗

bioRxiv2017

Deep-learning based hologram classification for molecular diagnostics

Lens-free digital in-line holography (LDIH) is a promising microscopic tool that overcomes several drawbacks (e.g., limited field of view) of traditional lens-based microcopy. However, extensive computation is required to reconstruct object images from the complex diffraction patterns produced by LDIH, which limits LDIH utility for point-of-care applications, particularly in resource limited settings. Here, we describe a deep transfer learning (DTL) based approach to process LDIH images in the context of cellular analyses. Specifically, we captured holograms of cells labeled with molecular-specific microbeads and trained neural networks to classify these holograms without reconstruction. Using raw holograms as input, the trained networks were able to classify individual cells according to the number of cell-bound microbeads. The DTL-based approach including a VGG19 pretrained network showed robust performance even with noisy experimental data. Combined with the developed DTL approach, LDIH could be realized as a low-cost, portable tool for point-of-care diagnostics.

bioengineering↗

bioRxiv2017

vU-net: accurate cell edge segmentation in time-lapse fluorescence live cell images based on convolutional neural network

Quantitative studies of cellular morphodynamics rely on extracting leading-edge velocity time-series based on accurate cell segmentation from live cell imaging. However, live cell imaging has numerous challenging issues about accurate edge localization. Here, we develop a deep learning-based pipeline, termed MARS-Net (Multiple-microscopy- type-based Accurate and Robust Segmentation Network), that utilizes transfer learning and the datasets from multiple types of microscopy to localize cell edges with high accuracy, allowing quantitative profiling of cellular morphodynamics. For effective training with the datasets from multiple types of live cell microscopy, we integrated the pretrained VGG-19 encoder with U-Net decoder and added dropout layers. Using this structure, we were able to train one neural network model that can accurately segment various live cell movies from phase contrast, spinning disk confocal, and total internal reflection fluorescence microscopes. Intriguingly, MARS-Net produced more accurate edge localization than the neural network models trained with single microscopy type datasets, whereas the standard U-Net could not increase the overall accuracy. We expect that MARS-Net can accelerate the studies of cellular morphodynamics by providing accurate segmentation of challenging live cell images.

bioinformatics↗

bioRxiv2017

Edge Detection of Cryptic Lamellipodia Assisted by Deep Learning

Cell protrusion plays important roles in cell migration by pushing plasma membrane forward. Cryptic lamellipodia induce the protrusion of submarginal cells in collective cell migration where cells are attached and move together. Although computational image analysis of cell protrusion has been done extensively, the study on protrusion activities of cryptic lamellipodia is limited due to difficulties in image segmentation. This study seeks to aid in the computational analysis of submarginal cell protrusion in collective cell migration by using deep learning to detect the cryptic lamellipodial edges from fluorescence time-lapse movies. Due to the noisy features within overlapping cells, the conventional image analysis algorithms such as Canny edge detector and intensity thresholding are limited. By combining Canny edge detector, Convolutional Neural Networks (CNNs), and local intensity thresholding, we were able to detect cryptic lamellipodial edges of submarginal cells with high accuracy from the fluorescence time-lapse movies of PtK1 cells stained with a plasma membrane marker. We used relatively small effort to prepare the training set to train the CNN to detect the cryptical lamellipodial edges in fluorescence time-lapse movies. This work demonstrates that deep learning can be combined with the conventional image analysis algorithms to facilitate the computational analysis of highly complex time-lapse movies of collective cell migration.

bioinformatics↗

bioRxiv2017

Heterogeneous Responses of Hematopoietic Stem Cells to Inflammatory Stimuli are Altered with Age

Long-term hematopoietic stem cells (LT-HSCs) maintain hematopoietic output throughout an animal's lifespan. With age, however, they produce a myeloid-biased output that may lead to poor immune responses to infectious challenge and the development of myeloid leukemias. Here, we show that young and aged LT-HSCs respond differently to inflammatory stress, such that aged LT-HSCs produce a cell-intrinsic, myeloid-biased expression program. Using single-cell RNA-seq, we identify a myeloid-biased subset within the LT-HSC population (mLT-HSCs) that is much more common amongst aged LT-HSCs and is uniquely primed to respond to acute inflammatory challenge. We predict several transcription factors to regulate differentially expressed genes between mLT-HSCs and other LT-HSC subsets. Among these, we show that Klf5, Ikzf1 and Stat3 play important roles in age-related inflammatory myeloid bias. These factors may regulate myeloid versus lymphoid balance with age, and can potentially mitigate the long-term deleterious effects of inflammation that lead to hematopoietic pathologies.\n\nHighlightsO_LILT-HSCs from young and aged mice have differential responses to acute inflammatory challenge.\nC_LIO_LIHSPCs directly sense inflammatory stimuli in vitro and have a robust transcriptional response.\nC_LIO_LIAged LT-HSCs demonstrate a cell-intrinsic myeloid bias during inflammatory challenge.\nC_LIO_LISingle-cell RNA-seq unmasked the existence of two subsets within the LT-HSC population that was apparent upon stimulation but not steady-state. One of the LT-HSC subsets is more prevalent in young and the other in aged mice.\nC_LIO_LIKlf5, Ikzf1 and Stat3 regulate age- and inflammation-related LT-HSC myeloid-bias.\nC_LI\n\nOne sentence summaryMurine hematopoietic stem cells display transcriptional heterogeneity that is quantitatively altered with age and leads to the age-dependent myeloid bias evident after inflammatory challenge.

immunology↗

bioRxiv2017

Deconvolution Of Subcellular Protrusion Heterogeneity And The Underlying Actin Regulator Dynamics From Live Cell Imaging

Cell protrusion is morphodynamically heterogeneous at the subcellular level. However, the mechanistic understanding of protrusion activities is usually based on the ensemble average of actin regulator dynamics at the cellular or population levels. Here, we establish a machine learning-based computational framework called HACKS (deconvolution of Heterogeneous Activity Coordination in cytosKeleton at a Subcellular level) to deconvolve the subcellular heterogeneity of lamellipodial protrusion in migrating cells. HACKS quantitatively identifies distinct subcellular protrusion phenotypes from highly heterogeneous protrusion activities and reveals their underlying actin regulator dynamics at the leading edge. Furthermore, it can identify specific subcellular protrusion phenotypes susceptible to pharmacological perturbation and reveal how actin regulator dynamics are changed by the perturbation. Using our method, we discovered accelerating protrusion phenotype in addition to fluctuating and periodic protrusions. Intriguingly, the accelerating protrusion was driven by the temporally coordinated actions between Arp2/3 and VASP: initiated by Arp2/3-mediated actin nucleation, and then accelerated by VASP-mediated actin elongation. We were able to confirm it by pharmacological perturbations using CK666 and Cytochalasin D, which specifically reduced strong accelerating protrusion activities. Taken together, we have demonstrated that HACKS allows us to discover the fine differential coordination of molecular dynamics underlying subcellular protrusion heterogeneity via a machine learning analysis of live cell imaging data.

cell biology↗

bioRxiv2017

Natural Genetic Variation Can Independently Tune The Induced Fraction And Induction Level Of A Bimodal Signaling Response

Bimodal gene expression by genetically identical cells is a pervasive feature of signaling networks. In the galactose-utilization (GAL) pathway of Saccharomyces cerevisiae, induction can be unimodal or bimodal depending on natural genetic variation and pre-induction conditions. Here, we find that this variation of modality is regulated by an interplay between two features of the pathway response, the fraction of cells that are in the induced subpopulation and their expression level. Combined, the variations in these features are sufficient to explain the observed effects of natural variation and pre-induction conditions on the modality of induction in both mechanistic and phenomenological models. Both natural variation and pre-induction conditions act by modulating the expression and function of the galactose sensor GAL3. The ability to alter modality may allow organisms to adapt their level of "bet hedging" to the conditions they experience, and thus help optimize fitness in complex, fluctuating natural environments.

genetics↗