Biology subjects

Chun, C.

Publications and source records attributed to Chun, C..

12 recordsLinked to original sources

bioRxiv2026

Ryanodine receptor 1 ( RYR1 ) patient-derived muscle cells recapitulate disease phenotypes in 2D and 3D culture models

The Ryanodine Receptor 1 (RyR1) is the major Ca2+ release channel in skeletal muscle and plays a crucial role in excitation-contraction coupling. Pathogenic variants in RYR1 are the most common cause of congenital myopathy, for which there are no approved treatments. Patient-centric disease models may help to facilitate the design and screening of novel therapeutics in a human genomic context. In this report, we describe the differentiation of five dominant RYR1-related myopathy patient-derived induced pluripotent stem cell (iPSC) lines into muscle progenitor cells (MPCs), and subsequently into multinucleated myotubes in 2- and 3- Dimensional (D) culture models. In 2D, we show significantly reduced Ca2+ release in a patient line compared to a healthy control following stimulation with caffeine. In 3D engineered muscle tissues (EMTs), patient-relevant phenotypes including reduced twitch amplitude, delayed relaxation and altered force-frequency relationships were observed in a patient line compared to two healthy controls. We also show that the 2D cultures are a suitable platform for screening the efficacy and cellular toxicity of antisense oligonucleotide therapeutics. Together, these results suggest that iPSC-derived skeletal muscle cultures are useful models for understanding the pathobiology of RYR1-related myopathies and as a testbed for emerging treatments.

Cell Biology↗

bioRxiv2026

Landscape-scale navigation unlocks antibody CDR structural logic for AI-guided rescue and therapeutic optimization

While AI offers transformative potential for therapeutic antibody design, the lack of ground-truth data fundamentally constrains our ability to model the epistatic topology of fitness landscapes. Here, we establish a high-throughput workflow to characterize tens of thousands of antibody variants per week with gold-standard biophysical precision. By combinatorially assembling functional variants from deep mutational scanning, we charted antibody fitness landscapes comprising over 17,000 data points, which revealed an extremely rugged, non-navigable epistatic topology. Yet, navigating at this unprecedented scale enabled the discovery of rare peak clusters exhibiting simultaneous enhancements in affinity and productivity. Strikingly, ProteinMPNN predicted the CDR-dependent productivity landscape with remarkable accuracy, suggesting that sequence-structure compatibility within CDRs gates cellular productivity. This insight enabled a structure-guided rescue strategy combining AlphaFold3 and ProteinMPNN, which successfully restored the cellular productivity of high-affinity, low-productivity clones via single amino acid substitutions. Two elite variants drawn directly from peak clusters further demonstrated 20- to 100-fold in vivo efficacy gains in a murine psoriasis model. Our findings establish CDR structural fitness as a fundamental determinant of antibody cellular productivity and validate landscape-scale navigation as a powerful framework for therapeutic antibody optimization.

bioengineering↗

bioRxiv2024

Mapping and Engineering Antibody-Antigen Interaction Landscapes for Systematic Affinity Enhancement

Antibodies, crucial in adaptive immunity, recognize antigens through specific interactions facilitated by Complementarity Determining Regions (CDRs), diversified via Variable-Diversity-Joining (VDJ) recombination. Traditional antibody development, limited by the scope of animal models and phage display libraries, captures a fraction of the potential antibody-antigen interactions. This underscores a gap in understanding antibody specificity and the relationship between antibody sequence and binding affinity. Here we introduce an approach using the Single-Protein Interaction Detection (SPID) platform, repurposed to systematically map local landscapes of antibody-antigen interactions with unprecedented depth and speed, aiming to rival the precision of methods like Surface Plasmon Resonance (SPR) and Bio-Layer Interferometry (BLI) while significantly boosting throughput. By editing CDR sequences and measuring effects on dissociation constants, we elucidated pathways for optimizing antibody affinity, enhancing predictive models for interactions. Our findings demonstrate the capability of the SPID platform to characterize thousands of variants weekly, offering a deeper insight into antibody-antigen interactions and advancing antibody development with finely-tuned affinities.

bioengineering↗

bioRxiv2024

Structure-guided engineering of a fast genetically encoded sensor for real-time H2O2 monitoring.

Hydrogen Peroxide (H2O2) is a central oxidant in redox biology due to its pleiotropic role in physiology and pathology. However, real-time monitoring of H2O2 in living cells and tissues remains a challenge. We address this gap with the development of an optogenetic hydRogen perOxide Sensor (oROS), leveraging the bacterial peroxide binding domain OxyR. Previously engineered OxyR-based fluorescent peroxide sensors lack the necessary sensitivity or response speed for effective real-time monitoring. By structurally redesigning the fusion of Escherichia coli (E. coli) ecOxyR with a circularly permutated green fluorescent protein (cpGFP), we created a novel, green-fluorescent peroxide sensor oROS-G. oROS-G exhibits high sensitivity and fast on-and-off kinetics, ideal for monitoring intracellular H2O2 dynamics. We successfully tracked real-time transient and steady-state H2O2 levels in diverse biological systems, including human stem cell-derived neurons and cardiomyocytes, primary neurons and astrocytes, and mouse neurons and astrocytes in ex vivo brain slices. These applications demonstrate oROSs capabilities to monitor H2O2 as a secondary response to pharmacologically induced oxidative stress, G-protein coupled receptor (GPCR)-induced cell signaling, and when adapting to varying metabolic stress. We showcased the increased oxidative stress in astrocytes via A{beta}-putriscine-MAOB axis, highlighting the sensors relevance in validating neurodegenerative disease models. oROS is a versatile tool, offering a window into the dynamic landscape of H2O2 signaling. This advancement paves the way for a deeper understanding of redox physiology, with significant implications for diseases associated with oxidative stress, such as cancer, neurodegenerative disorders, and cardiovascular diseases.

bioengineering↗

bioRxiv2024

Profiling multi-body interactions of BCL2 with single-molecule co-immunoprecipitation reveals the molecular mechanism of ABT-199 resistance

A capability to characterize protein-protein interactions (PPIs) in a quantitative manner with an increased speed would form a technical basis for accelerating drug discovery targeting the PPI network. We here used the single-molecule pull-down and co-IP platform to examine PPI between BCL2 and BH3-only proteins in crude extract environments. We focused on how the PPI strengths changed with single-point BCL2 mutations found in relapsed chronic lymphocytic leukemia showing ABT-199 resistance, where we took a mix-and-match approach to examine various pairs of baits and preys while titrating their concentrations. This allowed us to examine total 21 PPI reactions and 420 data points, forming a high-resolution large data set of the dissociation constants (Kd) and the drug inhibitory constants (Ki). Our data suggest that the different BCL2 mutants take different routes to acquire resistance to ABT-199, demonstrating how large-scale, quantitative PPI data sets reveal insights into the evolving dynamics of PPI networks.

biochemistry↗

bioRxiv2023

Comparing neural models using their perceptual discriminability predictions

Internal representations are not uniquely identifiable from perceptual measurements: different representations can generate identical perceptual predictions, and similar representations may predict dissimilar percepts. Here, we generalize a previous method ("Eigendistortions" - Berardino et al., 2017) to enable comparison of models based on their metric tensors, which can be verified perceptually. Metric tensors characterize sensitivity to stimulus perturbations, reflecting both the geometric and stochastic properties of the representation, and providing an explicit prediction of perceptual discriminability. Brute force comparison of model-predicted metric tensors would require estimation of human perceptual thresholds along an infeasibly large set of stimulus directions. To circumvent this "perceptual curse of dimensionality", we compute and measure discrimination capabilities for a small set of most-informative perturbations, reducing the measurement cost from thousands of hours (a conservative estimate) to a single trial. We show that this single measurement, made for a variety of different test stimuli, is sufficient to differentiate models, select models that better match human perception, or generate new models that combine the advantages of existing models. We demonstrate the power of this method in comparison of (1) two models for trichromatic color representation, with differing internal noise; and (2) two autoencoders trained with different regularizers.

neuroscience↗

bioRxiv2023

A High-Throughput Microfluidic Quantitative PCR Platform for the Simultaneous Quantification of Pathogens, Fecal Indicator Bacteria, and Microbial Source Tracking Markers

Contamination of water with bacterial, viral, and protozoan pathogens can cause human diseases. Both humans and non-humans can release these pathogens through their feces. To identify the sources of fecal contamination in the water environment, microbial source tracking (MST) approaches have been developed; however, the relationship between MST markers and pathogens is still not well understood most likely due to the lack of comprehensive datasets of pathogens and MST marker concentrations. In this study, we developed a novel microfluidic quantitative PCR (MFQPCR) platform for the simultaneous quantification of MST markers, fecal indicator bacteria (FIB), and bacterial, viral, and protozoan pathogens in many samples. A total of 80 previously validated TaqMan probe assays were applied on the MFQPCR chips, including those for two FIB, 22 bacterial pathogens, 11 viral pathogens, five protozoan pathogens, 37 MST markers for various host species, and three process controls. Specific and sensitive detection was verified for most assays on the MFQPCR platform. The MFQPCR chip was applied to analyze pathogen removal rates during the wastewater treatment processes. In addition, multiple host-specific MST markers, FIB, and pathogens were successfully quantified in human and avian-impacted surface waters. While the genes for pathogens were relatively infrequently detected, positive correlations were observed between some potential pathogens such as Clostridium perfringens and Mycobacterium spp., and human MST markers. The MFQPCR chips developed in this study, therefore, can provide useful information to monitor and improve water quality.

microbiology↗

bioRxiv2023

Predicting the efficacy of BH3 mimetics through the profiling of multiple protein complexes

BH3 mimetics are protein-protein interaction (PPI) inhibitors that saturate anti-apoptotic proteins in the BCL2 family to induce apoptosis in cancer cells, a prominent example of protein complex-targeting therapies. Despite the remarkable success of the BH3 mimetic ABT-199 in treating hematological malignancies, only a fraction of patients respond to ABT-199 and eventually develop resistance, necessitating the predictive biomarkers for both initial responses and resistance development. We here used the single-molecule pull-down and co-immunoprecipitation platform to quantify more than 20 different types of PPI complexes using [~]1.2x106 cells in total, revealing the rewired status of the BCL2 family PPI network. By comparing the obtained multi-dimensional data with BH3 mimetic efficacies determined ex vivo, we constructed an analysis model for ABT-199 efficacy that designates the BCL2-BAX and BCLxL-BAK complexes as the primary mediators of drug effectiveness and resistance. We then applied this model to assist in therapeutic decision-making for acute myeloid leukemia patients in a prospective manner. Our work demonstrates a capability for the extensive characterization of PPI complexes in clinical specimens, potentially opening a new avenue of precision medicine for protein complex-targeting therapies.

molecular biology↗

bioRxiv2022

Interferon-gamma Elicits Pathological Hallmarks of ALS in Human Motor Neurons

Neuroinflammation is an established factor contributing to amyotrophic lateral sclerosis (ALS) pathology, implicating the possible detrimental effects of inflammatory cytokines on motor neurons. The RNA/DNA-binding protein TDP-43 has emerged as a pivotal actor in ALS, because TDP-43 mutations cause familial ALS and loss of nuclear TDP-43, associated with its redistribution into cytoplasmic aggregates (TDP-43 proteinopathy) in motor neurons occurs in 97% of ALS cases. However, mechanisms linking neuroinflammation to TDP-43 mislocalization have not been described. Programmed death-ligand 1 (PD-L1) is an immune-modulatory protein, highly expressed on cell surfaces following acute inflammatory stress. To determine which inflammatory cytokines might impact motor neuron function, seven cytokines known to be elevated in ALS patients cerebrospinal fluid were tested for their effects on PD-L1 expression in human iPSC-derived motor neurons. Among the tested cytokines, only interferon-{gamma} (IFN-{gamma}) was found to strongly promote PD-L1 expression. Thus, we hypothesized that excessive exposure to IFN-{gamma} may contribute to motor neuron degeneration in ALS. We observed that neuronal populations exposed to IFN-{gamma} exhibited severe TDP-43 cytoplasmic aggregation and excitotoxic behavior correlated with impaired neural firing activity, hallmarks of ALS pathology, in both normal and ALS mutant (TARDB1K+/-) neurons. Single-cell RNA sequencing revealed possible mechanisms for these effects. Motor neurons exposed to IFN-{gamma} exhibited an extensive shift of their gene expression profile toward a neurodegenerative phenotype. Notably, IFN-{gamma} treatment induced aberrant expression levels for 70 genes that are listed in the recent literature as being dysregulated in various ALS subtypes. Additionally, we found that genes related to neuronal electrophysiology, protein aggregation, and TDP-43 misregulation were abnormally expressed in IFN-{gamma} treated cells. Moreover, IFN-{gamma} induced a significant reduction in the expression of genes that encode indispensable proteins for neuromuscular synapse development and maintenance, implying that the continuous cytokine exposure could directly impair signal transmission between motor axons and muscle membranes. Our findings suggest that IFN-{gamma} could be a potent upstream pathogenic driver of ALS and provide potential candidates for future therapeutic targets to treat sporadic forms of ALS, which account for roughly 90% of reported cases.

neuroscience↗

bioRxiv2021

Seizures initiate in zones of relative hyperexcitation in a zebrafish epilepsy model

Seizures are thought to arise from an imbalance of excitatory and inhibitory neuronal activity. While most classical studies suggest excessive excitatory neural activity plays a generative role, some recent findings challenge this view and instead argue that excessive activity in inhibitory neurons initiates seizures. We investigated this question of imbalance in a zebrafish seizure model with multi-regional two-photon imaging of excitatory and inhibitory neuronal activity using a nuclear-localized calcium sensor. We found that seizures consistently initiated in circumscribed zones of the midbrain before propagating to other brain regions. Excitatory neurons were both more prevalent and more likely to be recruited than inhibitory neurons in initiation as compared with propagation zones. These findings support a mechanistic picture whereby seizures initiate in a region of hyper-excitation, then propagate more broadly once inhibitory restraint in the surround is overcome. TeaserWe uncover the roles of excitation and inhibition during seizures, thus opening a path to more targeted therapy of epilepsy.

neuroscience↗

bioRxiv2019

Spring-loaded inverted pendulum goes through two contraction-extension cycles during the single stance phase of walking

Despite the overall complexity of legged locomotion, the motion of the center of mass (COM) itself is relatively simple, and can be qualitatively described by simple mechanical models. The spring-loaded inverted pendulum (SLIP) is one such model, and describes both the COM motion and the ground reaction forces (GRFs) during running. Similarly, walking can be modeled by two SLIP-like legs (double SLIP or DSLIP). However, DSLIP has many limitations and is unlikely to serve as a quantitative model for walking. As a first step to obtaining a quantitative model for walking, we explored the ability of SLIP to model the single stance phase of walking across the entire range of walking speeds. We show that SLIP can be employed to quantitatively model the single stance phase except for two exceptions: first, it predicts larger horizontal GRFs than empirically observed. A new model - angular and radial spring-loaded inverted pendulum (ARSLIP) can overcome this deficit. Second, even the single stance phase has active elements, and therefore a quantitative model of locomotion would require active elements. Surprisingly, the leg spring undergoes a contraction-extension-contraction-extension (CECE) during walking; this cycling is partly responsible for the M-shaped GRFs produced during walking. The CECE cycle also lengthens the stance duration allowing the COM to travel passively for a longer time, and decreases the velocity redirection between the beginning and end of a step. A combination of ARSLIP along with active mechanisms during transition from one step to the next is necessary to describe walking.

bioengineering↗

bioRxiv2018

Kinematic and biomechanical analyses in Drosophila suggests that most legged locomotion in insects can be understood within a single framework.

Despite the fact that all insects have six legs, they display considerable differences in their legged locomotion. Are these differences irreconcilable, or simply different domains of the same system? In this study, we investigate walking in Drosophila. We find that despite the fact that flies walk extremely slowly relative to their size, they predominantly employ an alternating tripod gait, a gait typically associated with high-speed locomotion. The kinematics of their center of mass (CoM) is diametrically opposite to the CoM kinematics observed in insect runners such as cockroach. We resolve this tension between similar gaits, and differing kinematics in slow and high-speed locomotion by showing that the mechanics of a tripod gait naturally reduces to a simple biomechanical model which can support a range of kinematic patterns including both fly-like and cockroach-like patterns. These findings suggest that legged locomotion in different insects might represent different domains of the same system.

neuroscience↗