Biology subjects

Kim, W. K.

Publications and source records attributed to Kim, W. K..

11 recordsLinked to original sources

bioRxiv2025

Inferring Spatially Varying Bending Stiffness of Biopolymers with Deep-Learning Approach

The bendability of biopolymers, including DNA, actin filaments, and microtubules, is crucial to diverse biological processes, such as cell motility and cytoskeletal organization. While conventional polymer models like the worm-like chain model assume uniform bending stiffness along the contour, biopolymers in reality often attain spatially varying bending stiffness as a result of complex cellular interactions. For instance, the bending stiffness of actin filaments and microtubules varies in response to associated binding proteins or chemical modifications. Despite its biological implications, measuring the position-dependent persistence length along polymer contours remains challenging. Here, we present a deep-learning-based method that quantitatively predicts spatially varying bending stiffness of biopolymers. Our framework segments a polymer chain into short over-lapping fragments, predicts local persistence lengths using a deep-learning model, and reconstructs full profiles. Using simulated data, we demonstrate that our approach achieves high accuracy and robustness even under data-scarce conditions. Applied to various biological systems, our method reveals a spatially varying stiffness from tip to base in filopodia as well as spatially heterogeneous stiffness in microtubules. Additionally, we investigate the internal mechanism of our deep-learning model and show that the model utilizes multiple physics-related features for persistence length estimation while adaptively adjusting its attention based on polymer stiffness.

biophysics↗

bioRxiv2024

An accelerated molecular dynamics study for investigating protein pathways using the bond-boost hyperdynamics method

Molecular dynamics (MD) simulation is an important tool for understanding protein dynamics and the thermodynamic properties of proteins. However, due to the high computational cost of MD simulations, it is still challenging to explore a wide conformational space. To solve this problem, a variety of accelerated MD schemes have been proposed over the past few decades. The bond-boost method (BBM) is one of such accelerated MD schemes, which expedites escape events from energy basins by adding a bias potential based on changes in bond length. In this paper, we present a new methodology based on the BBM for accelerating the conformational transition of proteins. In our modified BBM, the bias potential is constructed using the dihedral angle and hydrogen bond, which are more suitable variables to monitor the conformational change in proteins. Additionally, we have developed an efficient algorithm compatible with the LAMMPS package. The method is validated with the conformational change of Adenylate kinase (AdK) by comparing the conventional and accelerated MD simulation results. Based on the accelerated MD results, the characteristics of AdK are investigated by monitoring the conformational transition pathways and the behavior of interdomain salt bridges. Moreover, the free energy landscape calculated using umbrella sampling confirms all the states identified by the accelerated MD simulation are the free energy minima and the system makes transitions following the path indicated by the free energy landscape. Our efficient approach is expected to play a key role in investigating transition pathways in a wide range of protein simulations.

biophysics↗

bioRxiv2024

Kinetic model for the desensitization of G protein-coupled receptor

GPCR desensitization is a general regulatory mechanism adopted by biological organisms against overstimulation of G protein-coupled receptors. Although the details of mechanism aren extensively studied, it is not easy to gain an overarching understanding of the process constituted by a multitude of molecular events with vastly differing time scales. To offer a semi-quantitative yet predictive understanding of the mechanism, we formulate a kinetic model for the G protein signaling and desensitization by considering essential biochemical steps from ligand binding to receptor internalization. The internalization followed by the receptor depletion from the plasma membrane attenuates the downstream signal. Together with the kinetic model, an approximated form of expression derived for the dose-response clarifies the role played by the individual biochemical processes and allows us to identify three distinct regimes for the downregulation that emerge from the balance between phosphorylation, dephosphorylation and the cellular level of {beta}-arrestin.

biophysics↗

bioRxiv2023

Distinct modulation of calcium-activated chloride channel TMEM16A by a novel drug-binding site

TMEM16A is a calcium-activated chloride channel with significant role in multiple cellular processes. Several TMEM16A inhibitors have been identified; however, their binding sites and inhibitory mechanisms remain unclear. Using magnolol and honokiol, the two regioisomeric inhibitors, as chemical probes, we have identified a novel drug-binding site distinct from the pore region, in TMEM16A, which is described here. With electrophysiology, unbiased molecular docking and clustering, molecular dynamics simulations, and experimental validation with mutant cycle analysis, we show that magnolol and honokiol utilize different drug-binding sites, pore and non-pore pockets. The pore blocker utilizes amino acids crucial for chloride passage, whereas the non-pore blocker allosterically modulates the pore residues to hinder ion permeation. Among 17 inhibitors tested, 11 were pore blockers and six were non-pore blockers, indicating the importance of this newly identified non-pore pocket. Our study provides insights into drug-binding mechanism in TMEM16A together with a rationale for future drug development.

physiology↗

bioRxiv2023

Unveiling the Odor Representation in the Inner Brain of Drosophila through Compressed Sensing

The putative dimension of a space spanned by chemical stimuli is deemed enormous; however, when odorant molecules are bound to a finite number of receptor types and their information is transmitted and projected to a perceptual odor space in the brain, a substantial reduction in dimensionality is made. Compressed sensing (CS) is an algorithm that enables recovery of high-dimensional signals from the data compressed in a lower dimension when the representation of such signals is sufficiently sparse. By analyzing the recent Drosophila connectomics data, we find that the Drosophila olfactory system effectively meets the prerequisites for CS to work. The neural activity profile of projection neurons (PNs) can be faithfully recovered from a low-dimensional response profile of mushroom body output neurons (MBONs) which can be reconstructed using the electro-physiological recordings to a wide range of odorants. By leveraging the residuals calculated between the measured and the predicted MBON responses, we visualize the perceptual odor space by means of residual spectrum and discuss the differentiability of an odor from others. Our study highlights the sparse coding of odor to the receptor space as an essential component for odor identifiability, clarifying the concentration-dependent odor percept. Further, a simultaneous exposure of the olfactory system to many different odorants saturates the neural activity profile of PNs, significantly degrading the capacity of signal recovery, resulting in a perceptual state analogous to "olfactory white." Our study applying the CS to the connectomics data provides novel and quantitative insights into the odor representation in the inner brain of Drosophila.

neuroscience↗

bioRxiv2023

Darapladib, an inhibitor of Lp-PLA2, sensitizes cancer cells to ferroptosis by remodeling lipid metabolism

Arachidonic and adrenic acids in the membrane play key roles in ferroptosis, but how these fatty acids are manipulated in cells is largely unknown. Here, we reveal that lipoprotein-associated phospholipase A2 (Lp-PLA2) controls intracellular phospholipid metabolism and contributes to ferroptosis resistance. A metabolic drug screen identified that darapladib (SB-480848), an inhibitor of Lp-PLA2, synergistically induced ferroptosis with GPX4 inhibitors. Notably, darapladib was able to enhance ferroptosis under lipoprotein-deficient or serum-free conditions. Furthermore, Lp-PLA2 was located in the membrane and cytoplasm and suppressed ferroptosis, suggesting the critical role of intracellular Lp-PLA2. Lipidomic analysis showed that phosphatidylethanolamine (PE) species were generally enriched, while lysophosphatidylethanolamine (lysoPE) and free fatty acid levels were reduced, upon darapladib treatment. Finally, combination treatment with darapladib and PACMA31, a GPX4 inhibitor, efficiently inhibited tumor growth in a xenograft model. Our study suggests that inhibition of Lp-PLA2 is a potential therapeutic strategy to enhance ferroptosis in cancer treatment.

cancer biology↗

bioRxiv2022

Polymer physics-based classification of neurons

Recognizing that diverse morphologies of neurons are reminiscent of structures of branched polymers, we put forward a principled and systematic way of classifying neurons that employs the ideas of polymer physics. In particular, we use 3D coordinates of individual neurons, which are accessible in recent neuron reconstruction datasets from electron microscope images. We numerically calculate the form factor, F (q), a Fourier transform of the distance distribution of particles comprising an object of interest, which is routinely measured in scattering experiments to quantitatively characterize the structure of materials. For a polymer-like object consisting of n monomers spanning over a length scale of r, F (q) scales with the wavenumber q(= 2{pi}/r) as F (q) [~] q-[D] at an intermediate range of q, where [D] is the fractal dimension or the inverse scaling exponent ([D] ={nu} -1) characterizing the geometrical feature (r [~] n{nu}) of the object. F (q) can be used to describe a neuron morphology in terms of its size (Rn) and the extent of branching quantified by [D]. By defining the distance between F (q)s as a measure of similarity between two neuronal morphologies, we tackle the neuron classification problem. In comparison with other existing classification methods for neuronal morphologies, our F (q)-based classification rests solely on 3D coordinates of neurons with no prior knowledge of morphological features. When applied to publicly available neuron datasets from three different organisms, our method not only complements other methods but also offers a physical picture of how the dendritic and axonal branches of an individual neuron fill the space of dense neural networks inside the brain.

neuroscience↗

bioRxiv2022

Olfactory responses of Drosophila are encoded in the organization of projection neurons

The projection neurons (PNs), reconstructed from electron microscope (EM) images of the Drosophila olfactory system, offer a detailed view of neuronal anatomy, providing glimpses into information flow in the brain. About 150 uPNs constituting 58 glomeruli in the antennal lobe (AL) are bundled together in the axonal extension, routing the olfactory signal received at AL to mushroom body (MB) calyx and lateral horn (LH). Here we quantify the neuronal organization by inter-PN distances and examine its relationship with the odor types sensed by Drosophila. The homotypic uPNs that constitute glomeruli are tightly bundled and stereotyped in position throughout the neuropils, even though the glomerular PN organization in AL is no longer sustained in the higher brain center. Instead, odor-type dependent clusters consisting of multiple homotypes innervate the MB calyx and LH. Pheromone-encoding and hygro/thermo-sensing homotypes are spatially segregated in MB calyx, whereas two distinct clusters of food-related homotypes are found in LH in addition to the segregation of pheromone-encoding and hygro/thermo-sensing homotypes. We find that there are statistically significant associations between the spatial organization among a group of homotypic uPNs and certain stereotyped olfactory responses. Additionally, the signals from some of the tightly bundled homotypes converge to a specific group of lateral horn neurons (LHNs), which indicates that homotype (or odor type) specific integration of signals occurs at the synaptic interface between PNs and LHNs. Our findings suggest that before neural computation in the inner brain, some of the olfactory information are already encoded in the spatial organization of uPNs, illuminating that a certain degree of labeled-line strategy is at work in the Drosophila olfactory system.

neuroscience↗

bioRxiv2020

Phenotypic plasticity and partial EMT underlie local invasion and distant metastasis in colon cancer

Phenotypic plasticity represents the most relevant hallmark of the carcinoma cell as it bestows it with the capacity of transiently altering its morphologic and functional features while en route to the metastatic site. However, the study of phenotypic plasticity is hindered by the rarity of these events within primary lesions and by the lack of experimental models. Here, we identified a subpopulation of phenotypic plastic colon cancer cells: EpCAMlo cells are motile, invasive, chemo-resistant, and highly metastatic. EpCAMlo bulk and single-cell RNAseq analysis indicated 1. enhanced Wnt/{beta}-catenin signaling, 2. a broad spectrum of degrees of EMT activation including hybrid E/M states (partial EMT) with highly plastic features, and 3. high correlation with the CMS4 subtype, accounting for colon cancer cases with poor prognosis and a pronounced stromal component. Of note, a signature of genes specifically expressed in EpCAMlo cancer cells is highly predictive of overall survival in tumors other than CMS4, thus highlighting the relevance of quasi-mesenchymal tumor cells across the spectrum of colon cancers. Enhanced Wnt and the downstream EMT activation represent key events in eliciting phenotypic plasticity along the invasive front of primary colon carcinomas. Distinct sets of epithelial and mesenchymal genes define transcriptional trajectories through which state transitions arise. pEMT cells, often earmarked by the extracellular matrix glycoprotein SPARC together with nuclear ZEB1 and {beta}-catenin along the invasive front of primary colon carcinomas, are predicted to represent the origin of these (de)differentiation routes through biologically-distinct cellular states, and to underlie the phenotypic plasticity of colon cancer cells.

cancer biology↗

bioRxiv2020

Efficacy and safety of decompressive craniectomy with non-suture duraplasty in patients with traumatic brain injury

BackgroundDecompressive craniectomy is an important surgical treatment for patients with severe traumatic brain injury (TBI). Several reports have been published on the efficacy of non-watertight sutures in duraplasty performed in decompressive craniectomy. This study aims to evaluate the effectiveness of dura closure without sutures (non-suture duraplasty) in decompressive craniectomy for TBI. MethodsOne hundred and six patients were enrolled at a single trauma center between January 2017 and December 2018. We retrospectively collected the data and classified the patients into non-suture and suture duraplasty craniectomy groups. We compared the characteristics of patients and their intra/post- operative findings such as operative time, blood loss, imaging findings, complications, and Glasgow outcome scale. ResultsThere were 37 patients in the non-suture group and 69 in the suture craniectomy group. There were no significant differences between the two groups with regard to general characteristics. The operative time was 205 min for the suture duraplasty group and 150 min for the non-suture duraplasty group, and that for the non-suture duraplasty group was significantly lesser (p=0.002). Blood loss was significantly lesser in the non-suture duraplasty group (1000 mL) than in the suture duraplasty group (1500 mL, p=0.028). There were no other significant differences. ConclusionNon-suture duraplasty involved shorter operative time and lesser blood loss when compared to suture duraplasty. Other complications and prognosis were similar in both groups. Therefore, it can be concluded that decompressive craniectomy with non-suture duraplasty is a safe and useful surgical technique in patients with TBI.

neuroscience↗

bioRxiv2019

Noncoding de novo mutations contribute to autism spectrum disorder via chromatin interactions

Three-dimensional chromatin structures regulate gene expression across genome. The significance of de novo mutations (DNMs) affecting chromatin interactions in autism spectrum disorder (ASD) remains poorly understood. We generated 931 whole-genome sequences for Korean simplex families to detect DNMs and identified target genes dysregulated by noncoding DNMs via long-range chromatin interactions between regulatory elements. Notably, noncoding DNMs that affect chromatin interactions exhibited transcriptional dysregulation implicated in ASD risks. Correspondingly, target genes were significantly involved in histone modification, prenatal brain development, and pregnancy. Both noncoding and coding DNMs collectively contributed to low IQ in ASD. Indeed, noncoding DNMs resulted in alterations, via chromatin interactions, in target gene expression in primitive neural stem cells derived from human induced pluripotent stem cells from an ASD subject. The emerging neurodevelopmental genes, not previously implicated in ASD, include CTNNA2, GRB10, IKZF1, PDE3B, and BACE1. Our results were reproducible in 517 probands from MSSNG cohort. This work demonstrates that noncoding DNMs contribute to ASD via chromatin interactions.

neuroscience↗