Biology subjects

Choi, H. J.

Publications and source records attributed to Choi, H. J..

16 recordsLinked to original sources

bioRxiv2024

OmniSegger: A time-lapse image analysis pipeline for bacterial cells

Time-lapse microscopy is a powerful tool for studying the cell biology of bacterial cells. The development of pipelines that facilitate the automated analysis of these datasets is a long-standing goal of the field. In this paper, we describe OmniSegger, an updated version of our SuperSegger pipeline, developed as an open-source, modular, and holistic suite of algorithms whose input is raw microscopy images and whose output is a wide range of quantitative cellular analyses, including dynamical cell cytometry data and cellular visualizations. The updated version described in this paper introduces two principal refinements: (i) robustness to cell morphologies and (ii) support for a range of common imaging modalities. To demonstrate robustness to cell morphology, we present an analysis of the proliferation dynamics of Escherichia coli treated with a drug that induces filamentation. To demonstrate extended support for new image modalities, we analyze cells imaged by five distinct modalities: phase-contrast, two brightfield modalities, and cytoplasmic and membrane fluorescence. Together, this pipeline should greatly increase the scope of tractable analyses for bacterial microscopists.

biophysics↗

bioRxiv2023

A Normative Framework Dissociates Need and Motivation in Hypothalamic Neurons

Physiological needs evoke motivational drives to produce natural behaviours for survival. However, the temporally intertwined dynamics of need and motivation have made it challenging to differentiate these two components in previous experimental paradigms. Based on classic homeostatic theories, we established a normative framework to derive computational models of neural activity and behaviours for need-encoding and motivation-encoding neurons during events that induce predicted gain or loss. We further developed simple and intuitive experimental paradigms that enabled us to distinguish the distinct roles of subpopulations of neurons in the hypothalamus. Our results show that AgRP neurons and LHLepR neurons are consistent with need and motivation, respectively. Our study provides a parsimonious understanding of how distinct hypothalamic neurons separately encode need and motivation to produce adaptive behaviours for maintaining homeostasis.

neuroscience↗

bioRxiv2023

Hypothalamic neuronal activation in primates drives naturalistic goal-directed eating behavior

Eating addiction is the primary cause of modern obesity. Although the causal role of the lateral hypothalamic area (LHA) for eating is demonstrated in rodents, there is no evidence in primates regarding naturalistic eating behaviors. We investigated the role of LHA GABAergic (LHAGABA) neurons in eating by chemogenetics in three macaques. LHAGABA neuron activation significantly increased naturalistic goal-directed behaviors and food motivation, which was specific for palatable food. PET and MRS validated the chemogenetic activation. Rs-fMRI result revealed that functional connectivity (FC) between the LHA and frontal areas was increased, while the FC between the frontal cortices was decreased after the LHAGABA neuron activation. Thus, our study elucidates the role of LHAGABA neurons in eating and obesity therapeutics for primates and humans.

neuroscience↗

bioRxiv2023

Translational approach to social isolation during a global pandemic: Hippocampal somatic mutation

The coronavirus disease 2019 (COVID-19) pandemic has attributed to stress not only by the infection itself but also by social isolation owing to self-quarantine and social distancing. Stress has adverse effects on the mental health and chronic medical diseases; the potential of stress-induced somatic mutations in the brain to cause psychiatric disorders is being studied. Here we conducted behavioral studies, protein expression studies, single-nucleus sequencing (snRNAseq), and whole-genome sequencing (WGS) of the hippocampus of mice that underwent early maternal separation and social isolation, and a demographic study of community populations who had been self-quarantined owing to COVID-19 exposure to investigate the link between somatic mutations and stress due to social isolation. The demographic study demonstrated more negative mental health findings among individuals who live alone or are single. Mice subjected to early maternal separation and social isolation demonstrated increased anxiety-like behaviors and stress-related corticotropin-releasing hormone receptor 1, and neurogenesis-related sex-determining region Y-box 2 and doublecortin expression. In snRNA-seq, differences, such as transthyretin increase, were observed in the maternal separation group, and somatic mutations, including insertion in the intron site of Tmem267, were observed in the social isolation group on WGS. The results of this study suggest that stress, such as social isolation, can cause changes at the genetic level, as well as behavioral and brain protein changes.

neuroscience↗

bioRxiv2021

Differential ion dehydration energetics explains selectivity in the non-canonical lysosomal K+ channel TMEM175

Structures of the human lysosomal K+ channel TMEM175 in open and closed states revealed a novel architecture lacking the canonical K+ selectivity filter motif present in previously known K+ channel structures. A hydrophobic constriction composed of four isoleucine residues was resolved in the pore and proposed to serve as the gate in the closed state, and to confer ion selectivity in the open state. Here, we achieve higher-resolution structures of the open and closed states and employ molecular dynamics simulations to analyze the conducting properties of the putative open state, demonstrating that it is capable of permeating K+ ions at the expected rate. Monovalent cations must dehydrate significantly to penetrate the narrow hydrophobic constriction, but ion flow is assisted by a favorable electrostatic field generated by the protein that spans the length of the pore. The balance of these opposing energetic factors explains why permeation is feasible, and why TMEM175 is selective for K+ over Na+, despite the absence of the canonical selectivity filter. Accordingly, mutagenesis experiments reveal an exquisite sensitivity of the channel to perturbations that mitigate the constriction. Together, these data reveal a novel mechanism for selective permeation of ions by TMEM175 that is unlike that of other K+ channels.

biophysics↗

bioRxiv2021

A Standardized Protocol for Quantifying the Behavioral Dynamics of Food-seeking in Mice

Food is generally hidden in a natural environment and require free-living animals to search for it. Although such food-seeking behaviors involve motivation and exploration, previous studies examined food-seeking simply by measuring the time spent in the food zone or the frequency of pursuing food-cued context. Moreover, after discovering food, animals need to taste and smell it in order to evaluate their nutritional value or possible toxicity. However, researchers could not easily distinguish food-seeking from food-evaluating behaviors because food was visible or accessible throughout each test. Herein, we describe a behavioral protocol that triggers animals to show the behavioral dynamics of food-seeking (e.g., navigation, nose-digging, and paw-digging) and that exclusively elicits food-seeking without provoking any other food-evaluating behaviors. First, we prepared an open-field box with the floor covered with bedding. After we hid foods under the bedding of each corner, the test mice were habituated in this arena for four days (pre-test phase). On the next day (test phase), they were placed under the same conditions, but the foods previously hidden were removed. This process enabled the mice to perceive their surroundings as a food-hidden environment, which induced the animal to exhibit sustained food-seeking. In conclusion, the protocol presented here is a powerful method for provoking multiple forms of food-seeking and quantifies food-seeking independently from other food-related behavioral stages.

neuroscience↗

bioRxiv2021

Deep Learning-based Subcellular Phenotyping of Protrusion Dynamics Reveals Fine Differential Drug Responses at Subcellular and Single-Cell Levels

Live cell imaging provides unparallel insights into dynamic cellular processes across spatiotemporal scales. Despite its potential, the inherent spatiotemporal heterogeneity within live cell imaging data often obscures critical mechanical details underlying cellular dynamics. Uncovering fine-grained phenotypes of live cell dynamics is pivotal for precise understandings of the heterogeneity of physiological and pathological processes. However, this endeavor introduces formidable technical challenges to unsupervised machine learning, demanding the extraction of features that can faithfully preserve heterogeneity, effectively discriminate between different molecularly perturbed states, and provide interpretability. While deep learning shows promise in extracting useful features from large datasets, it often falls short in producing such high-fidelity features, especially in unsupervised learning settings. To tackle these challenges, we present DeepHACX (Deep phenotyping of Heterogeneous Activities of Cellular dynamics with eXplanations), a self-training deep learning framework designed for fine-grained and interpretable phenotyping. This framework seamlessly integrates an unsupervised teacher model with interpretable features to facilitate feature learning in a student deep neural network (DNN). Significantly, it incorporates an autoencoder-based regularizer, termed SENSER (SENSitivity-enhancing autoEncoding Regularizer), designed to prompt the student DNN to maximize the heterogeneity associated with molecular perturbations. This approach enables the acquisition of features that not only discriminate between different molecularly perturbed states but also faithfully preserve the heterogeneity linked to these perturbations. In our study, DeepHACX successfully delineated fine-grained phenotypes within the heterogeneous protrusion dynamics of migrating epithelial cells, uncovering specific responses to pharmacological perturbations. Remarkably, DeepHACX adeptly captured a minimal number of highly interpretable features uniquely linked to these fine-grained phenotypes, each corresponding to specific temporal intervals crucial for their manifestation. This unique capability positions DeepHACX as a valuable tool for investigating diverse cellular dynamics and comprehensively studying their heterogeneity.

bioinformatics↗

bioRxiv2020

In-vivo histology of iron and myelin in the brain using magnetic susceptibility source separation in MRI

Obtaining a histological fingerprint from the in-vivo brain has been a long-standing target of magnetic resonance imaging (MRI). In particular, non-invasive imaging of iron and myelin, which are involved in normal brain functions and are histopathological hallmarks in neurodegenerative diseases, has practical utilities in neuroscience and medicine. Here, we propose a biophysical model that describes the individual contribution of paramagnetic (e.g., iron) and diamagnetic (e.g., myelin) susceptibility sources to the frequency shift and transverse relaxation of MRI signals. Using this model, we develop a method,{chi} -separation, that generates the voxel-wise distributions of the two sources. The method is validated using computer simulation and phantom experiments, and applied to ex-vivo and in-vivo brains. The results delineate the well-known histological features of iron and myelin in the specimen, healthy volunteers, and multiple sclerosis patients. This new technology may serve as a practical tool for exploring the microstructural information of the brain.

neuroscience↗

bioRxiv2020

LH LepR neurons directly drive sustained food seeking behavior after AgRP neuronal deactivation via neuromodulation of NPY

The physiological need for energy evokes motivated feeding behaviours that help to ensure survival. However, the neural mechanisms underlying the generation of food motivation remain poorly understood. We investigated these mechanisms by subdividing feeding-related motivated behaviours into food-seeking, evaluating, and swallowing. Micro-endoscopic results indicated that neurons containing leptin receptors (LepRs) in the lateral hypothalamus (LH) are the major food-specific subpopulation of LHGABA neurons. Optogenetic manipulation of LHLepR neurons bidirectionally regulated both food-seeking and evaluating. Furthermore, micro-endoscope data revealed that distinct LHLepR neurons encode seeking and evaluating. Computational modelling analysis demonstrated that LHLepR neurons encode motivation, whereas neurons containing agouti-related peptide and neuropeptide Y (AgRP/NPY) encode the need for food. Additionally, slice studies revealed that NPY decreases inhibitory input to LHLepR neurons via LHGABA interneurons. This mechanism explains the permissive gate role of hunger (food need) in seeking/evaluating motivation. Together, the present study provides a comprehensive neural mechanism of how physiological needs drive distinct motivated behaviours.

neuroscience↗

bioRxiv2019

High-phytate/low-calcium diet is a risk factor for crystal nephropathies, renal phosphate wasting, and bone loss

Phosphate overload contributes to mineral bone disorders associated with crystal nephropathies. Phytate, the major form of phosphorus in plant seeds, is known as an indigestible and negligible in humans. However, the mechanism and adverse effects of high-phytate intake on Ca2+ and phosphate absorption and homeostasis are unknown. Here we show that excessive intake of phytate with a low-Ca2+ diet fed to rats contributed to the development of crystal nephropathies, renal phosphate wasting, and bone loss through tubular dysfunction secondary to dysregulation of intestinal calcium and phosphate absorption. Moreover, Ca2+ supplementation alleviated the detrimental effects of excess dietary phytate on bone and kidney through excretion of undigested Ca2+-phytate, which prevented a vicious cycle of intestinal phosphate overload and renal phosphate wasting while improving intestinal Ca2+ bioavailability. Thus, we demonstrate that phytate is digestible without a high-Ca2+ diet and a risk factor for phosphate overloading and developing crystal nephropathies and bone disease.

physiology↗

bioRxiv2019

Mechanistic insights into the deleterious role of nasu-hakola disease associated TREM2 variants

Recently, critical roles of genetic variants in Triggering Receptor Expressed on Myeloid cells 2 (TREM2) for myeloid cells to Alzhimers disease have been aggressively highlighted. However, little studies focused to the deleterious role of Nasu-Hakola disease (NHD) associated TREM2 variants. In order to get insights into the contributions of these variants in neurodegeneration, we investigated the influences of three well-known NHD associated TREM2 mutations (Y38C, T66M and V126G) on the loss-of-function by using conventional molecular dynamics simulation. Compared to the wild type, the mutants produced substantial differences in the collective motions in the loop regions, which not only promotes structural remodelling in complementarity-determining region 2 (CDR2) loop but also in CDR1 loop, through changing the inter and intra-loop hydrogen bonding network. In addition, the structural studies from free energy landscape showed that Y38, T66 and V126 are crucial for maintaining structural features of CDR1 and CDR2 loops, while their mutation at this position produced steric clash and thus contributes to the structural impact and loss of ligand binding. These results revealed that the presence of the mutations in TREM2 ectodomain induced flexibility and promotes structural alterations. Dynamical scenarios, which are provided by the present study, may be critical to our understanding of the role of the three TREM2 mutations in neurodegenerative diseases.

biochemistry↗

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

The Effect of Aldehyde Dehydrogenase Activator, Alda-1(R), on the Ethanol-induced Brain Damage in a Rat of Binge Ethanol Intoxication.

AimsThis study aimed to investigate whether an aldehyde dehydrogenase (ALDH) activator (Alda-1(R)) reduces neuronal damage in a rat model of binge ethanol exposure.\n\nMethodsThirty-six adolescent male rats (130-150 g) were randomly assigned into three groups: sham, ethanol-only group (25% ethanol intragastrically thrice daily for four days, approximately 10 g/kg/day) and ethanol with Alda-1(R) group (10 mg/kg thrice daily for four days). The ALDH activity at baseline and 90 min after the last infusion in each group was measured. Brain damage was investigated using Luxol fast blue-Cresyl violet staining in the hippocampus, CA1 and CA2/3. The activation of astrocytes and microglia was examined using immunohistochemistry for antiglial fibrillary acidic protein (GFAP) and anti-ionized calcium-binding adapter molecule 1 (Iba-1).\n\nResultsAfter a four-day binge, the ALDH activity level was doubled in the ethanol with Alda-1(R) group (mean: 7.87, SD: 0.67), whereas the levels in the sham group (mean: 4.07, SD: 0.53) and ethanol-only group (mean: 3.77, SD: 0.36) were slightly decreased. More significant neuronal shrinkage, fewer neurons, and loss of Nissl in the hippocampus were observed in the ethanol-only group compared to the ethanol with Alda-1(R) group. Astrocytosis and microgliosis of the hippocampus also showed increased activation in the ethanol only group compared with the ethanol with Alda-1(R) group.\n\nConclusionAlda-1(R) administration reduces cytotoxic damage to the hippocampus in adolescent rats with binge ethanol exposure.

neuroscience↗

bioRxiv2018

Co-option of neurotransmitter signaling for inter-organismal communication in C. elegans

Biogenic amine neurotransmitters play a central role in metazoan biology, and both their chemical structures and cognate receptors are evolutionarily conserved. Their primary roles are in intra-organismal signaling, whereas biogenic amines are not normally recruited for communication between separate individuals. Here, we show that in C. elegans, a neurotransmitter-sensing G protein-coupled receptor, TYRA-2, is required for avoidance responses to osas#9, an ascaroside pheromone that incorporates the neurotransmitter octopamine. Neuronal ablation, cell-specific genetic rescue, and calcium imaging show that tyra-2 expression in the nociceptive neuron ASH is necessary and sufficient to induce osas#9 avoidance. Ectopic expression in the AWA neuron, which is generally associated with attractive responses, reverses the response to osas#9, resulting in attraction instead of avoidance behavior, confirming that TYRA-2 partakes in sensing osas#9. The TYRA-2/osas#9 signaling system thus represents an inter-organismal communication channel that evolved via co-option of a neurotransmitter and its cognate receptor.

neuroscience↗

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

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↗