Biology subjects

Hyeon, C.

Publications and source records attributed to Hyeon, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Formation of homolog pairing-induced domains in early Drosophila embryo genome

Somatic homolog pairing is a defining feature of the diploid genome organization in Drosophila and underlies its transvection-based gene regulation. Here, to understand the physical effect of homolog pairing on the resulting three-dimensional (3D) organization, we employ the heterogeneous loop model and reconstruct 3D structures of the Drosophila embryo genome based on its haplotype-resolved Hi-C data. The resulting structures reveal robust end-to-end juxtaposition between homologous chromosomes amid substantial cell-to-cell variability. On sub-megabase scales, tight pairing between homologous loci at domain boundaries give rise to significant coincidence between cis and trans-homolog domain boundaries in the Hi-C map, while interior regions remain loosely associated. To uncover the physical origin of this organization, we compare the contact maps resulting from the polymer models implementing specific and non-specific button-mediated pairing mechanisms with Hi-C, finding that the intra-chromosomal contacts constrained by specifically paired inter-chromosomal buttons give rise to pairing-induced domains (PIDs). Our study suggests specific adhesive interactions as a central organizing principle of the diploid genome in Drosophila embryos. SignificanceSomatic homolog pairing distinguishes Drosophila from most eukaryotes; yet how the homolog pairing organizes Drosophila genome has remained elusive due to the lack of explicit model. By analyzing 3D structures reconstructed from haplotype-resolved Hi-C data, we clarify that specific homolog-recognizing buttons should generate pairing-induced domains that simultaneously organize cis and trans-homolog contacts. Our study provides a physical explanation on how a single molecular mechanism can simultaneously coordinate homolog pairing and architecture of chromatin domain in the diploid genome.

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

Glycolytic oscillations under periodic drivings

In many living organisms displaying circadian rhythms, the intake of energy often occurs in a periodic manner. Glycolysis is a prototypical biochemical reaction that exhibits a self-sustained oscillation under continuous injection of glucose. Here we study the effect of periodic injection of glucose on the glycolytic oscillation from a dynamical systems perspective. In particular, we employ the Goldbeters allosteric model of phosphofructokinase (PFK) as a model system for glycolytic oscillations, and explore the effect of periodic substrate influx of varying frequencies and amplitudes by building the phase diagrams of Lyapunov exponents and oscillatory periods. When the frequency of driving is tuned around the harmonic and sub/super-harmonic conditions of the natural frequency, the system is entrained to a frequency-locked state, forming an entrainment band that broadens with an increasing amplitude of driving. On the other hand, if the amplitude is substantial, the system may transition, albeit infrequent, to a chaotic state which defies prediction of dynamical behavior. Our study offers in-depth understandings into the controllability of glycolytic oscillation as well as explains physical underpinnings that enable the synchronous oscillations among a dense population of cells.

biophysics↗

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↗

bioRxiv2022

Moderate activity of RNA chaperone maximizes the yield of self-spliced pre-RNA in vivo

CYT-19 is a DEAD-box protein whose ATP-dependent helicase activity facilitates the folding of group I introns in precursor RNA (pre-RNA) of Neurospora crassa. In the process they consume a substantial amount of ATP. While much of the mechanistic insights into CYT-19 activity has been gained through the studies on the folding of Tetrahymena group I intron ribozyme, the more biologically relevant issue, namely the effect of CYT-19 on the self-splicing of pre-RNA, remains largely unexplored. Here, we employ a kinetic network model, based on the generalized iterative annealing mechanism, to investigate the relation between CYT-19 activity, rate of ribozyme folding, and the kinetics of the self-splicing reaction. The network rate parameters are extracted by analyzing the recent biochemical data for CYT-19-facilitated folding of T. ribozyme. We then build extended models to explore the metabolism of pre-RNA. We show that the timescales of chaperone-mediated folding of group I ribozyme and self-splicing reaction compete with each other. As a consequence, in order to maximize the self-splicing yield of group I introns in pre-RNA, the chaperone activity must be sufficiently large to unfold the misfolded structures, but not too large to unfold the native structures prior to the self-splicing event. We discover that despite the promiscuous action on structured RNAs, the helicase activity of CYT-19 on group I ribozyme gives rise to self-splicing yields that are close to the maximum. Significance StatementIn cells, RNA chaperones assist misfolding-prone ribozymes to fold correctly to carry out its biological function. CYT-19 is an ATP-consuming RNA chaperone that accelerates the production of native group I intron ribozyme by partially unfolding the kinetically trapped structures. Using the theoretical framework based on the iterative annealing mechanism, we establish that to maximize the processing of pre-RNA, an optimal balance should exist between the timescales of self-splicing activity and CYT-19-mediated production of the native ribozyme. Remarkably, the activity of CYT-19 has been optimized to unfold the misfolded structures but is not so high that it disrupts the native ribozyme, which ensures that the yield of the self-splicing reaction is maximized in a biologically relevant time scale.

biophysics↗

bioRxiv2022

Dissecting the co-segregation probability from genome architecture mapping

The genome architecture mapping (GAM) is a recently developed methodology that offers the co-segregation probability of two genomic segments from an ensemble of thinly sliced nuclear profiles, enabling to probe and decipher the 3D chromatin organization. The co-segregation probability from GAM, which typically probes the length scale associated with the genomic separation greater than 1 MB, is, however, not identical to the contact probability obtained in Hi-C, and its correlation with inter-locus distance measured with FISH is not so good as the contact probability. In this study, by using a polymer-based model of chromatins, we derive a theoretical expression of the co-segregation probability as well as that of the contact probability, and carry out quantitative analyses of how they differ from each other. The results from our study, validated with in-silico GAM analysis on 3D genome structures from FISH, suggest that to attain strong correlation with the inter-locus distance, a properly normalized version of co-segregation probability needs to be calculated based on a large number of nuclear slices (n > 103). SIGNIFICANCEBy leveraging a polymer model of chromatin, we critically assess the utility of co-segregation probability captured from GAM analysis. Our polymer model, which offers analytical expressions for the co-segregation probability as well as for the contact probability and inter-locus distance, enables quantitative comparison between the data from GAM, Hi-C, and FISH. Although the plain co-segregation probabilities from GAM are not well correlated with inter-locus distances measured from FISH, properly normalized versions of the probability calculated from a large number of nuclear profiles can still reasonably represent the inter-locus distance. Our study offers instructions of how to take full advantage of GAM analysis in deciphering 3D genome organization.

biophysics↗

bioRxiv2022

TMAO Destabilizes RNA Secondary Structurevia Direct Hydrogen Bond Interactions

Trimethylamine N-oxide (TMAO) is an osmolyte that accumulates in cells in response to osmotic stress. TMAO stabilizes proteins by the entropic stabilization mechanism, which pictures TMAO as a nano-crowder that predominantly destabilizes the unfolded state. However, the mechanism of action of TMAO on RNA is much less understood. Here, we use all atom molecular dynamics simulations to investigate how TMAO interacts with a 12-nt RNA hairpin with a high melting temperature, and an 8-nt RNA hairpin, which has a relatively fluid native basin in the absence of TMAO. The use of the two hairpins with different free energy of stabilization allows us to probe the origin of the destabilization effect of TMAO on RNA molecules without the possibility of forming tertiary interactions. We generated multiple trajectories using allatom molecular dynamics (MD) simulations in explicit water by employing AMBER and CHARMM force fields, both in the absence and presence of TMAO. We observed qualitatively similar RNA-TMAO interaction profiles from the simulations using the two force fields. TMAO hydrogen bond interactions are largely depleted around the paired RNA bases and ribose sugars. In contrast, we show that the oxygen atom in TMAO, the hydrogen bond acceptor, preferentially interacts with the hydrogen bond donors in the solvent exposed bases, such as those in the stem-loop, the destabilized base stacks in the unfolded state, especially in the marginally stable 8-nt RNA hairpin. The predicted destabilization mechanism through TMAO-RNA hydrogen bond interactions could be tested using two-dimensional IR spectroscopy. Since TMAO does not significantly interact with the hydroxyl group of the ribose sugars, we predict that similar results must also hold for DNA.

biophysics↗

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

Location of the TEMPO moiety of TEMPO-PC in phosphatidylcholine bilayers is membrane phase-dependent

The (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO) moiety tethered to the headgroup of phosphatidylcholine (PC) lipid is employed in spin labeling electron paramagnetic resonance (EPR) spectroscopy to probe the water dynamics near lipid bilayer interfaces. Due to its amphiphilic character, however, TEMPO spin label could partition between aqueous and lipid phases, and may even be stabilized in the lipid phase. Accurate assessment of the TEMPO-PC configuration in bilayer membranes is essential for correctly interpreting the data from measurements. Here, we carry out all-atom molecular dynamics (MD) simulations of TEMPO-PC probe in single-component lipid bilayers at varying temperatures, using two standard MD force fields. We find that for DPPC membrane whose gel-to-fluid lipid phase transition occurs at 314 K, TEMPO is stabilized above (below) the bilayer interface if the membrane is in the gel (fluid) phase. For bilayers made of unsaturated lipids, DOPC and POPC, which adopt the fluid phase at ambient temperature, TEMPO is unequivocally stabilized inside the bilayers. Our finding of membrane phase-dependent positioning of TEMPO moiety highlights the importance of assessing the packing order and fluidity of lipids under a given measurement condition.

biophysics↗

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↗

bioRxiv2021

Extracting multi-way chromatin contacts from Hi-C data

There is a growing realization that multi-way chromatin contacts formed in chromosome structures are fundamental units of gene regulation. However, due to the paucity and complexity of such contacts, it is challenging to detect and identify them using experiments. Based on an assumption that chromosome structures can be mapped onto a network of Gaussian polymer, here we derive analytic expressions for n-body contact probabilities (n > 2) among chromatin loci based on pairwise genomic contact frequencies available in Hi-C, and show that multi-way contact probability maps can in principle be extracted from Hi-C. The three-body (triplet) contact probabilities, calculated from our theory, are in good correlation with those from measurements including Tri-C, MC-4C and SPRITE. Maps of multi-way chromatin contacts calculated from our analytic expressions can not only complement experimental measurements, but also can offer better understanding of the related issues, such as cell-line dependent assemblies of multiple genes and enhancers to chromatin hubs, competition between long-range and short-range multi-way contacts, and condensates of multiple CTCF anchors. Author summaryThe importance of DNA looping is often mentioned as the initiation step of gene expression. However, there are growing evidences that chromatin hubs comprised of multiple genes and enhancers play vital roles in gene expressions and regulations. Currently a number of experimental techniques to detect and identify multi-way chromosome interactions are available; yet detection of such multi-body interactions is statistically challenging. This study proposes a method to predict multi-way chromatin contacts from pair-wise contact frequencies available in Hi-C dataset. Since chromosomes are made of polymer chains, the pairwise contact probabilities are not entirely independent from each other, but certain types of correlations are present reflecting the underlying chromosome structure. We extract these correlations hidden in Hi-C dataset by leveraging theoretical argument based on polymer physics.

biophysics↗

bioRxiv2021

Cost-precision trade-off relation determines the optimal morphogen gradient for accurate biological pattern formation

Spatial boundaries growing into macroscopic structures through animal development originate from the pre-patterning of tissues by signaling molecules, called morphogens. To establish accurate boundaries, the morphogen concentration which thresholds the expression of target gene at the boundary should be precise enough, exhibiting large gradient and small fluctuations. Producing more morphogens would better serve to shape more precise target boundaries; however, it incurs more thermodynamic cost. In the classical diffusion-degradation model of morphogen profile formation, the morphogens synthesized from a local source display an exponentially decaying concentration profile with a characteristic length {lambda}. Our theory suggests that in order to attain a precise morphogen profile with the minimal cost, {lambda} should be roughly half the distance to the target boundary position from the source, so that the boundary is formed at the position where the morphogen concentration is [~]10 % of the value at the source. Remarkably, we find that the well characterized morphogens that pattern the fruit fly embryo and wing imaginal disk form profiles with nearly optimal {lambda}, which underscores the thermodynamic cost as a key physical constraint in the morphogen profile formation.

biophysics↗

bioRxiv2019

Heterogeneous loop model to infer 3D chromosome structures from Hi-C

Adapting a well-established formalism in polymer physics, we develop a minimalist approach to infer threedimensional (3D) folding of chromatin from Hi-C data. The 3D chromosome structures generated from our heterogeneous loop model (HLM) are used to visualize chromosome organizations that can substantiate the measurements from FISH, ChIA-PET, and RNA-Seq signals. We demonstrate the utility of HLM with several case studies. Specifically, the HLM-generated chromosome structures, which reproduce the spatial distribution of topologically associated domains (TADs) from FISH measurement, show the phase segregation between two types of TADs explicitly. We discuss the origin of cell-type dependent gene expression level by modeling the chromatin globules of -globin and SOX2 gene loci for two different cell lines. We also use HLM to discuss how the chromatin folding and gene expression level of Pax6 loci, associated with mouse neural development, is modulated by interactions with two enhancers. Finally, HLM-generated structures of chromosome 19 of mouse embryonic stem cells (mESCs), based on single-cell Hi-C data collected over each cell cycle phase, visualize changes in chromosome conformation along the cell cycle. Given a contact frequency map between chromatic loci supplied from Hi-C, HLM is a computationally efficient and versatile modeling tool to generate chromosome structures, which can complement interpreting other experimental data.

biophysics↗

bioRxiv2019

Multi-CD: Multi-scale discovery of Chromatin Domains

Identifying chromatin domains (CDs) from high-throughput chromosome conformation capture (Hi-C) data is currently a central problem in genome research. Here we present a unified algorithm, Multi-CD, which infers CDs at various genomic scales by leveraging the information from Hi-C. By integrating a model of the chromosome from polymer physics, statistical physics-based clustering analysis, and Bayesian inference, Multi-CD identifies the CDs that best represent the global pattern of correlation manifested in Hi-C. The multi-scale intra-chromosomal structures compared across different cell types allow us to glean the principles of chromatin organization: (i) Sub-TADs, TADs, and meta-TADs constitute a robust hierarchical structure. (ii) The assemblies of compartments and TAD-based domains are governed by different organizational principles. (iii) Sub-TADs are the common building blocks of chromosome architecture. CDs obtained from Multi-CD applied to Hi-C data enable a quantitative and comparative analysis of chromosome organization in different cell types, providing glimpses into structure-function relationship in genome.

biophysics↗

bioRxiv2019

Modular structure of human olfactory receptor codes reflects the bases of odor perception

The circuits of olfactory signaling are reminiscent of complex computational devices. The olfactory receptor code, which represents the responses of receptors elicited by olfactory stimuli, is effectively an input code for the neural computation of odor sensing. Here, analyzing a recent dataset of the odorant-dependent responses of human olfactory receptors (ORs), we show that the space of human olfactory receptor codes is partitioned into a modular structure where groups of receptors are \"labeled\" for key olfactory features. Our analysis reveals a low-dimensional structure in the space of human odor perception, with the receptor groups as the bases to represent major features in the perceptual odor space. These findings provide a novel evidence that some fundamental olfactory features are already hard-coded at the level of ORs, separately from the higher-level neural circuits.

neuroscience↗

bioRxiv2018

Implications for human odor sensing revealed from the statistics of the odorant-receptor interactions

Binding of odorants to olfactory receptors (ORs) elicits downstream chemical and neural signals, which are further processed to odor perception in the brain. Recently, Mainland et al. [Sci. data, (2015) 2:sdata20152] have measured {gtrsim} 500 pairs of odorant-OR interaction by a high-throughput screening assay method, opening a new avenue to understanding the principles of human odor coding. Here, using a recently developed minimal model for OR activation kinetics [J. Phys. Chem. B (2017) 121, 1304-1311], we characterize the statistics of OR activation by odorants in terms of three empirical parameters: the half-maximum effective concentration EC50, the efficacy, and the basal activity. While the data size of odorants is still limited, the statistics offer meaningful information on the breadth and optimality of the tuning of human ORs to odorants, and allow us to relate the three parameters with the microscopic rate constants and binding affinities that define the OR activation kinetics. Despite the stochastic nature of the response expected at individual OR-odorant level, we assess that the confluence of signals in a neuron released from the multitude of ORs is effectively free of noise and deterministic with respect to changes in odorant concentration. Thus, setting a threshold to the fraction of activated OR copy number for neural spiking binarizes the electrophysiological signal of olfactory sensory neuron, thereby making an information theoretic approach a viable tool in studying the principles of odor perception.

systems biology↗

bioRxiv2017

Architecture of human interphase chromosome determines the spatiotemporal dynamics of chromatin loci

By incorporating the information of human chromosome inferred from Hi-C experiments into a heteropolymer model of chromatin chain, we generate a conformational ensemble to investigate its spatiotemporal dynamics. The heterogeneous loci interactions result in hierarchical organization of chromatin chain, which obeys compact space-filling (SF) statistics at intermediate length scale. Remarkably, the higher order architecture of the chromatin, characterized by the single universal Flory exponent ({nu} = 1/3) for condensed homopolymers, provides quantitative account of the dynamical properties of the chromosome. The local chromosome structures, exemplified by topologically associated domains (~ 0.1 - 1 Mb), display dynamics with fast relaxation time ([lsim] 50 sec), whereas the long-range spatial reorganization of the entire chromatin [Formula] occurs on a much longer time scale ({gtrsim} hour), suggestive of glass-like behavior. This key finding provides the dynamic basis of cell-to-cell variability. Active forces, modeled using stronger isotropic white noises, accelerate the relaxation dynamics of chromatin domain described by the low frequency modes. Surprisingly, they do not significantly change the local scale dynamics from those under passive condition. By linking the spatiotemporal dynamics of chromosome with its organization, our study highlights the importance of physical constraints in chromosome architecture on the sluggish dynamics.\n\nSignificance StatementChromosomes are giant chain molecules made of hundreds of megabase-long DNA intercalated with proteins. Structure and dynamics of interphase chromatin in space and time hold the key to understanding the cell type-dependent gene regulation. In this study, we establish that the crumpled and space-filling organization of chromatin fiber in the chromosome territory, characterized by a single universal exponent used to describe polymer sizes, is sufficient to explain the complex spatiotemporal hierarchy in chromatin dynamics as well as the subdiffusive motion of the chromatin loci. While seemingly a daunting problem at a first glance, our study shows that relatively simple principles, rooted in polymer physics, can be used to grasp the essence of dynamical properties of the interphase chromatin.

biophysics↗

bioRxiv2017

Signaling Networks and Dynamics of Allosteric Transitions in Bacterial Chaperonin GroEL: Implications for Iterative Annealing of Misfolded Proteins

Signal transmission at the molecular level in many biological complexes occurs through allosteric transitions. They describe the response a complex to binding of ligands at sites that are spatially well separated from the binding region. We describe the Structural Perturbation Method (SPM), based on phonon propagation in solids, that can be used to determine the signal transmitting allostery wiring diagram (AWD) in large but finite-sized biological complexes. Applications to the bacterial chaperonin GroEL-GroES complex shows that the AWD determined from structures also drive the allosteric transitions dynamically. Both from a structural and dynamical perspective these transitions are largely determined by formation and rupture of salt-bridges. The molecular description of allostery in GroEL provides insights into its function, which is quantitatively described by the Iterative Annealing Mechanism. Remarkably, in this complex molecular machine, a deep connection is established between the structures, reaction cycle during which GroEL undergoes a sequence of allosteric transitions, and function in a self-consistent manner.

biophysics↗