Biology subjects

Choi, W.

Publications and source records attributed to Choi, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Distributed brain-spinal cord dynamics during micturition revealed by functional ultrasound imaging

Micturition relies on coordinated activity across distributed neural circuits spanning the brain and spinal cord, yet the spatiotemporal dynamics of these processes remain poorly understood. Disruption of these pathways in conditions such as spinal cord injury, Parkinson's disease, multiple sclerosis, and aging can lead to neurogenic bladder dysfunction. Here, we used functional ultrasound imaging (fUSI), a modality with high spatiotemporal resolution and single-trial sensitivity, to investigate central nervous system activity during micturition. In anesthetized rats undergoing controlled bladder filling and volitional voiding, we recorded power Doppler signals from either the brain or the lumbosacral spinal cord. We observed distinct, region-specific hemodynamic responses associated with micturition across multiple brain regions, including the thalamus, hypothalamus, midbrain, and neocortex - particularly sensorimotor and retrosplenial areas - as well as dorsal and ventral spinal cord circuits. Furthermore, population-level activity in these regions enabled accurate decoding of bladder pressure dynamics. These results provide a systems-level characterization of central nervous system activity during micturition and establish fUSI as a platform for developing neural interfaces to restore bladder control.

bioengineering↗

bioRxiv2026

Primate Gaze Behavior Reflects Change of Mind in a Naturalistic Navigation Task

Revising a decision while acting on it is a fundamental aspect of natural behavior, yet the underlying computations are difficult to track in real time. To explore how such belief updates unfold, we tested whether eye movements reveal a subject's change of mind during a naturalistic navigation task with a binary target choice. Humans and monkeys were required to navigate to one of two goal locations presented either simultaneously or sequentially in a virtual environment where explicit position cues were absent. Our findings reveal that gaze continuously tracks the latent variable, including changes of mind. We found that the target tracking accuracy before the second target is even presented during sequential target trials predicts whether the subject's navigational goal persists (first target choice) or changes (second target choice). These results underscore the importance of gaze in action planning and changes of mind, supporting the hypothesis that eye movements embody not only the current latent variable but also its uncertainty.

neuroscience↗

bioRxiv2026

Epithelial to mesenchymal transition and M2 macrophages drive aggressiveness in murine and human sarcomatoid urothelial carcinoma.

Patients with majority variant subtype histology including sarcomatoid urothelial carcinoma (SUC) have poor outcomes and limited treatment options, and there are few preclinical resources to investigate rare histologic subtypes. We developed three novel variant subtype histology bladder cancer (BC) cell lines by finding that basal BC tumor cells derived from mice treated with N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN) were initially not competent to grow in immune competent mice, but then acquired tumorigenicity following passaging (recycling) in mice lacking mature B and T cells. Three genitourinary oncology pathologists identified BBN966 as SUC, BBN964 as a hybrid between SUC and squamous, and BBN975 as squamous, and each had unique growth characteristics. Using a publicly available dataset and our spatial transcriptomics analysis of a cohort of human tumors with mixed SUC and UC as comparators, we found that consistent with human SUC, BBN966 lack expression of basal and luminal genes. Consistent with human SUC and spatial transcriptomics analysis of canine SUC, BBN966 had the highest epithelial to mesenchymal transition (EMT) upregulation, and all three recycled tumor cells had increased EMT pathway expression in recycled tumor cells. Moreover, increased expression of genes upregulated in all three recycled tumor cells associated with worse overall survival in patients with muscle invasive UC. Similar to human SUC, BBN966 tumors had higher proportion of M2 macrophage gene expression. Finally, we found in the largest cohort of PD-L1 IHC to date that 20 of 38 (52.6%) human SUC had CPS > 50, which was driven mostly by tumor proportion score. Consistent with this, we found anti-PD1 immune checkpoint inhibitor (ICI) significantly inhibited BBN966 tumor growth, while the hybrid BBN964 tumors had mixed response to ICI. Thus, the murine BBN966 tumors exhibited similarities to human SUC, and can be used to examine novel therapies for translation into future SUC clinical studies.

cancer biology↗

bioRxiv2026

CryoROLE: describing large inter-domain rotation in single particle cryo-EM

In single particle cryo-EM, analysis of continuous conformational heterogeneity has always been challenging. Both linear and deep learning-based methods treat conformational heterogeneity as perturbations to the consensus average conformation, limiting their capability in analyzing large protein motions. While classic conformational classifications are capable of handling large domain motion, they bin continuous protein dynamics into discrete static substates. Here, we present cryoROLE, a computational tool that extracts the continuous conformational dynamics embedded in the static composite map constructed from multi-body refinement into a landscape of relative orientation between the moving domains. Depicted in real space, the landscape allows intuitive interpretations of domain motion and the population of poses in the conformational space. Applying it to various biological systems reveals hidden conformational dynamics that are relevant to protein functions.

biophysics↗

bioRxiv2026

Multi-timescale learning signals in Drosophila dopaminergic neurons

Learning often requires inference over hidden task structure, including features that predict outcomes. In mammals, prediction-error signaling by midbrain dopamine neurons is considered central to learning, but how these neurons reflect the progression and stability of learning remains unclear. Using Drosophila to monitor calcium activity at trial-by-trial resolution during aversive conditioning, we found that PPM3 dopaminergic neurons exhibit hallmark prediction-error responses in which activity shifted from the unconditioned stimulus (US) to the conditioned stimulus (CS), was suppressed when an expected US was omitted, and increased when the US exceeded expectations. Strikingly, the same neurons also exhibited slower state-like dynamics across trials, including tonic activity transitions that emerged with learning and tracked the acquisition of learned behavior, and perturbation-related dynamics that were briefly disrupted when expectations were violated. Increasing task demands by inserting a temporal gap between the CS and US (trace conditioning) delayed both response types to later trials, accompanied by corresponding delays in behavior acquisition. In addition, dopaminergic activity developed an anticipatory response that tracked the expected timing of the US during the gap. These findings reveal that a single dopaminergic neuron type integrates moment-to-moment prediction errors, expected outcome timing, and a longer-timescale signal reflecting learning stabilization, establishing Drosophila as a bona fide model for dissecting the neural mechanisms that shape learning under changing task demands.

neuroscience↗

bioRxiv2026

Single-chip End-to-End Ingestible Electronics for Gut Neurotransmitter Sensing

Neurotransmitters in the gut play a vital role in human health and neuroscience, and their real-time monitoring is essential for understanding underlying physiological mechanisms. However, bioelectronic systems capable of measuring neurotransmitters in vivo at the anatomical site of interest remain underdeveloped and largely depend on bulky, off-the-shelf electronic components, thereby constraining the development of systems that are both practical and minimally invasive. Here, we report a miniature ingestible pill that is capable of real-time in vivo sensing of two key neurotransmitters: serotonin (5-HT) and dopamine (DA). The system incorporates a fully printed three-electrode-based electrochemical sensor for neurotransmitter sensing and a custom application-specific integrated circuit (ASIC) that integrates all major functional blocks on a single chip, enabling a platform for fully wireless monitoring of gut neurotransmitters. The pill, measuring 5.8 mm in diameter and 19 mm in length, supports multiple electrochemical sensing techniques, including amperometry and voltammetry, with only 42 A of average current consumption. We demonstrate the ingestible platform through in vivo studies in rat animal models, enabling real-time monitoring of gut neurotransmitters.

bioengineering↗

bioRxiv2026

AbiOmics: An End-to-End Pipeline to Train Machine Learning Models for Discrimination of Plant Abiotic Stresses Using Transcriptomic Profiling Data

Abiotic stresses are primary constraints on global crop productivity, reducing yields by up to 80%. While traditional phenotypic sensing detects stress only after physiological symptoms emerge and often fails to discriminate specific stressor types, transcriptomic profiling offers a high-dimensional solution, capturing rapid and sensitive molecular shifts. In this study, we developed AbiOmics, the first end-to-end machine learning pipeline specifically designed to identify and discriminate among multiple stressors. This approach represents a previously undocumented method for stress specification using large-scale transcriptomic big data. We identified 320 stress-specific marker genes using a curated collection of 1,243 transcriptomes of Arabidopsis samples treated with four major abiotic stresses, salt, cold, heat, and drought. A single-layer perceptron model trained on these features achieved 91% accuracy during five-fold cross-validation and 93% accuracy on an independent test set. The model demonstrated an unprecedented capacity to generalize to multi-stress conditions, identifying concurrent signatures in combinatorial salt-and-heat treatments. By integrating marker identification with SHAP-based biological interpretation, AbiOmics provides a rigorously validated diagnostic tool superior to conventional sensing. This framework establishes a high-confidence labeling strategy for AI-driven crop management and precision breeding to mitigate climate change impacts. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=73 SRC="FIGDIR/small/707868v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@573cb5org.highwire.dtl.DTLVardef@152a0b0org.highwire.dtl.DTLVardef@1b389a5org.highwire.dtl.DTLVardef@11c60d_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

A family portrait of lanmodulin selectivity for enhanced rare-earth separations

Proteins offer a molecular design space to create bespoke ligands for the separation of critical metals, like rare earth elements (REs). However, data-intensive approaches to fine-tune metalloprotein selectivity are bottlenecked by the low-throughput nature of existing characterization methods. Here we invented an assay called SpyTag-Catcher Immobilization of Lanmodulin for Assaying Metal-Binding Selectivity (SpyCI-LAMBS) to measure metalloprotein selectivity en masse. This 96-format workflow was used to study the selectivity of 621 lanmodulin (LanM) orthologs for 15 REs, revealing eight distinct selectivity profiles based on sequence-to-function analyses. We discovered >200 LanMs with dampened selectivity for low-value LaIII relative to the prototypical LanM. This includes a LanM that can perform a challenging one-stage separation of PrIII from LaIII with up to >99.9 mol% purity and 83% yield. SpyCI-LAMBS is a powerful tool that can rapidly collect high-fidelity selectivity data to inform metal ion separations and machine learning-assisted metalloprotein design.

bioengineering↗

bioRxiv2025

Exploring the intrinsic and extrinsic determinants of heterogeneity in a β-cell network

Pancreatic islets are micro-organs composed of multiple endocrine cell types. {beta}-cells are the most common of these and are highly heterogeneous in both their intrinsic properties, such as ion channel conductances and metabolic activity, and extrinsic properties, including gap junction coupling and paracrine signaling. Capturing these diverse sources of heterogeneity is essential for computational models that aim to reproduce islet function. We evaluate two established multicellular models, the coupled Cha-Noma model of the mouse {beta}-cell network, and the Riz human model. Prior work with these two models suggest that the Cha-Noma model involves minimal intrinsic heterogeneity and therefore bursts with highly synchronized activity, whereas heterogeneity in the Riz model prescribed from in vitro patch-clamp results in highly unsynchronized behavior of the coupled network. We hypothesize that adjusting the number of bursting cells in both model formulations may invoke more physiologically realistic network coordination. We applied a categorical sensitivity analysis to establish which parameters are most important for determining bursting in single cells of the Riz model. We also introduced new heterogeneity (based on single-cell gene expression) in parameters that had previously been treated as invariant among {beta}-cells. We hypothesized that introducing heterogeneity in the small conductance Ca2+ K+ channel in particular could promote a higher proportion of bursting cells. Lastly, both models fail to incorporate the influences of non-{beta}-cells. We introduced paracrine signaling between and {beta}-cells into the coupled Cha-Noma model and showed it plays a role in accelerating the response time of {beta}-cells to acute glucose stimulation (i.e. promotes a 1st responder phenotype).

bioengineering↗

bioRxiv2025

A Physically-Realistic Simulator and Cosine-Based Decoder for MERFISH Spatial Transcriptomics

Imaging-based spatial transcriptomics technologies have opened new avenues for studying cellular organization and gene expression within intact tissues. However, the accuracy of downstream analyses depends critically on the decoding step that reconstructs barcodes from fluorescence patterns and maps them to gene identities. Despite a growing number of decoding methods, systematic benchmarking has been limited. Here, we introduce Serval, a modular framework for developing and benchmarking decoding methods across diverse spatial transcriptomics platforms. Serval separates key decoding stages into independently configurable modules, enabling flexible integration of alternative algorithms. Using this framework, we develop the Cosine decoder, a novel method that improves transcript recovery by optimizing cosine similarity to known barcodes. We evaluate Cosine and baseline methods on synthetic and real MERFISH datasets, showing that Cosine achieves higher transcript recovery and superior correlation with expression references compared to existing methods. Furthermore, we demonstrate that the Serval framework generalizes beyond MERFISH. By extending to the DART-FISH platform, we show that Cosine improves transcript recovery, clustering stability and supports more direct annotation of complex biological structures such as the human primary motor cortex. These results establish that modular decoding frameworks facilitate robust, platformagnostic benchmarking, ultimately supporting more accurate spatial transcriptomics analysis across diverse biological samples.

bioinformatics↗

bioRxiv2025

The genitals of rhinoceros beetles: a general overview of the endophallus in the tribe Agaocephalini (Coleoptera: Scarabaeidae: Dynastinae)

The endophallus is the intromittent, membranous structure inside the aedeagus. It provides unique information for distinguishing taxa: species and genera. In addition to taxonomy, this organ is also useful to get insights about the evolution of the studied taxa, thus informing their classification. Despite the extensive reports on the structure and function of insect genitalia, the endophallus has received less attention than the sclerotized structures of the aedeagus. Several genera in the Agaocephalini rhinoceros beetles can be classified in three distinct groups based on the morphology of their endophalli. By examining the genitals of about 60% of the currently recognized species in this morphologically heterogeneous tribe, we provide for the first time a general overview of this structure. Furthermore, based on existing differences between genera, we discuss about the potential implications for the internal tribal systematics, as currently accepted. Novel information about endophalli structures will shed light on the missing links to other dynastine tribes.

zoology↗

bioRxiv2025

Intestinal catabolism of dietary fructose promotes obesity and insulin resistance via ileal lacteal remodeling

High-fructose corn syrup (HFCS) consumption is a risk factor for obesity and metabolic syndrome, yet the underlying mechanisms are incompletely understood. Catabolism of dietary fructose primarily occurs in the small intestine and liver, with fructose breakdown in the liver being pathological, while small intestinal fructose clearance protects the liver. Here, we unexpectedly found that inhibition of fructose catabolism specifically in the small intestine mitigates fructose-induced obesity and insulin resistance. Mechanistically, blocking intestinal fructose catabolism reduces dietary fat absorption, which is associated with a decrease in the surface area of the ileal lacteals and alterations in gut microbiome. Fecal transplantation experiments revealed that such a microbiome stimulates the intestine-resident macrophages, promoting lacteal growth and boosting dietary fat absorption. Given the preclinical and clinical studies reporting the effect of fructose catabolism suppression on mitigating diet-induced obesity, our data suggest that such effects are partly mediated by intestinal lacteal remodeling. Significance StatementHere, we uncover a previously unappreciated link between intestinal fructose catabolism and ileal lacteal remodeling, suggesting the mechanisms by which fructose intake promotes obesity. Using mice lacking the fructose-processing enzyme specifically in the intestine, we show that blocking intestinal fructose metabolism protects against diet-induced obesity by reducing fat absorption. Changes in gut microbiome and immune cell interactions drive this effect.

physiology↗

bioRxiv2025

Cardiac metabolite exchange measured in pigs during myocardial ischemia and reperfusion

Myocardial ischemia and reperfusion (I/R) injury are the primary contributors to death in patients with cardiovascular disease. While decades of research have elucidated the molecular players and biochemical mechanisms underlying I/R injury, how these pathologies influence the metabolic activities of the heart remains incompletely understood. Such a knowledge gap hampers the development of therapies aimed at mitigating the metabolic stresses of the heart during injury. Using comprehensive arteriovenous metabolomics in a highly relevant porcine I/R model, we report the metabolic landscape of cardiac metabolic changes after ischemia and during the reperfusion time course. Paradoxically, ischemia increases the cardiac uptake of circulating fatty acids while reperfusion for 60 minutes reverses this activity. By 120 minutes of reperfusion, the hearts resume the uptake of fatty acids, suggesting restoration of their metabolism. On the other hand, we found a strong release of amino acids by the heart only after 60-minute reperfusion, but not after 120-minute reperfusion, implicating I/R-induced transient protein degradation. In addition to these findings, we identified several previously unrecognized changes in cardiac metabolic inputs and outputs during I/R, including nucleotides, TCA cycle intermediates and creatine/creatinine. These data highlight the dynamic alterations in cardiac metabolism in response to I/R, providing insights into how to mitigate myocardial I/R injury.

biochemistry↗

bioRxiv2025

Inhibition of NF-κB Signaling by the Reactive Glycolytic Metabolite Methylglyoxal

The NF-{kappa}B family of transcription factor complexes are central regulators of inflammation, and their dysregulation contributes to the pathology of multiple inflammatory disease conditions. Accordingly, identifying pharmacological mechanisms that restrain NF-{kappa}B overactivation remains an area of key importance. Here, we demonstrate that inhibition of the glycolytic enzyme phosphoglycerate kinase 1 (PGK1) with the small molecule inhibitor CBR-470-2 results in attenuated NF-{kappa}B signaling, decreasing transcriptional output in response to several canonical NF-{kappa}B activating stimuli. Mechanistically, PGK1 inhibition promotes the accumulation of the glycolytic metabolite methylglyoxal, which crosslinks and inactivates NF-{kappa}B proteins, limiting the phosphorylation and nuclear translocation of these transcription factor complexes. This work establishes a key connection between central carbon metabolism and immune signaling and further supports the notion that PGK1 inhibition may be a viable strategy to increase cellular survival and dampen inflammation in disease.

biochemistry↗

bioRxiv2025

Convergent Agonist and Heat Activation of Nociceptor TRPM3

Detecting noxious heat is vital for survival, triggering pain responses that protect against harm1,2. The TRPM3 channel is a key nociceptor for sensing noxious heat and a promising therapeutic target for pain treatment and neurological disorders such as epilepsy3-11. Here, we functionally and structurally characterized TRPM3 in response to diverse stimuli: the synthetic superagonist CIM0216 Ref12, the anticonvulsant antagonist primidone13,14, and heat1,10,15. Our findings reveal that TRPM3 is intrinsically dynamic, with its intracellular domain (ICD) sampling both resting and activated states, though strongly favoring the resting state without stimulation. CIM0216 binds to the S1-S4 domain, inducing conformational changes in the ICD and shifting the equilibrium toward activation. Remarkably, heat induces similar ICD rearrangements, revealing a converged activation mechanism driven by chemical compounds and temperature. This mechanism is supported by functional data showing that mutations facilitating the ICD movement markedly increase the sensitivity of TRPM3 to both chemical and thermal signals. These findings establish a critical role of the ICD in temperature sensing in TRPM3, a mechanism likely conserved across the TRPM family. Finally, we show that primidone binds to the same site as CIM0216 but acts as an antagonist. This study provides a framework for understanding the thermal sensing mechanisms of temperature-sensitive ion channels and offers a structural foundation for developing TRPM3-target therapeutics for pain and neurological disorders.

biophysics↗

bioRxiv2025

Deciphering Features of Metalloprotease Cleavage Targets Using Protein Structure Prediction

IntroductionADAM10 (A Disintegrin and Metalloproteinase 10) cleaves specific substrates, influencing diverse physiological and pathological processes. However, its substrate specificity and cleavage sites remain insufficiently characterized. This study aimed to identify and classify substrate features and elucidate cleavage sites using computational approaches. MethodsProtein structure prediction was performed on 13 substrates with experimentally defined cleavage sites to analyze ADAM10-substrate interactions and assess their structural and spatial characteristics. ResultsBased on protein structure prediction of experimentally validated substrates, we identified four recurrent structural features associated with ADAM10-mediated cleavage. First, most substrates were predicted to interact with the proteolytically active form of ADAM10 (92.3%). Second, interaction sites were typically located in the extracellular region rather than intracellular or transmembrane domains (76.9%). Third, cleavage sites predominantly resided in unstructured or extended loop regions, corresponding to linear secondary structures ([~]70%). Lastly, cleavage sites were spatially enriched in octants (1, 4, 5, and 8) relative to the catalytic Zn{superscript 2}{square} ion in the active site (84.0%). These percentages were calculated per determinant. On the basis of these determinants, we developed a classification algorithm and organized 51 substrates accordingly. As a result, 82.4% of the substrates were assigned to either Group 1 (51.0%) or Group 2 (31.4%). DiscussionThis study presents a structure-informed classification approach for predicting ADAM10 cleavage substrates, enabling candidate identification without direct experimental validation. ConclusionsWe present a novel structure-based framework for classifying the substrates of ADAM10 and demonstrate its applicability to other Metalloproteases.

bioinformatics↗

bioRxiv2024

Striatal Astrocytes Influence Dopamine Dynamics and Behavioral State Transitions

We demonstrate here that astrocytes in the striatum interact with striatal dopamine in bidirectional signaling with dopamine release actively driving surges in astrocytic Ca++, which in turn modulate and reduce subsequent dopamine release. These Ca++ surges accurately predict behavioral state changes from task-engaged to task-disengaged states, but fail to predict detailed action parameters. We propose that interactions between striatal astrocytes and dopamine are strong candidates to modulate nigro-striato-nigral loop function underlying on-going behavioral state dynamics.

neuroscience↗

bioRxiv2024

Proximity proteomics provides a new resource for exploring the function of Afadin and the complexity of cell-cell adherens junctions

The network of proteins at the interface between cell-cell adherens junctions and the actomyosin cytoskeleton provides robust yet dynamic connections that facilitate cell shape change and motility. While this was initially thought to be a simple linear connection via classic cadherins and their associated catenins, we now have come to appreciate that many more proteins are involved, providing robustness and mechanosensitivity. Defining the full network of proteins in this network remains a key objective in our field. Proximity proteomics provides a means to define these networks. Mammalian Afadin and its Drosophila homolog Canoe are key parts of this protein network, facilitating diverse cell shape changes during gastrulation and other events of embryonic morphogenesis. Here we report results of several proximity proteomics screens, defining proteins in the neighborhood of both the N- and C-termini of mammalian Afadin in the premier epithelial model, MDCK cells. We compare our results with previous screens done in other cell types, and with proximity proteomics efforts with other junctional proteins. These reveal the value of multiple screens in defining the full network of neighbors and offer interesting insights into the overlap in protein composition between different epithelial cell junctions. Summary StatementAfadin BioID reveals new adherens junction proteins.

cell biology↗