Biology subjects

Yoo, S.

Publications and source records attributed to Yoo, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Mesoscale Soft Robotics for Mechanically Perturbing and Functionally Monitoring Responses in Human Organoids

Human organoids represent promising models for studies of significance to the biology and medical communities. Of the existing approaches for monitoring organoids, none offers the ability to apply programmable mechanical forces while simultaneously recording multi-modal physiological responses, of relevance to phenomena spanning from traumatic brain injuries to cardiac rhythm disorders. Here, we present a mesoscale soft robotic organoid interface that enables programmable delivery of forces to organoids of diverse shapes, and to map electrophysiological activity and mechanical responses. The platform combines actuation elements with integrated sensors for quantitative measurement and control. Studies using this technology reveal that spheroidal cortical organoids exhibit distinct responses to mechanical trauma, including silencing, recovery, and changes in neuronal firing patterns. Additional experiments on cardiac ring tissues demonstrate that sustained stretching induces beat-to-beat rhythm variability and altered conduction. The results establish a framework for investigating force-triggered transitions between physiological and disease-like states in human tissue models.

bioengineering↗

bioRxiv2026

A targeted plasma-proteomic axis separates autoimmune thyroid disease from growth-hormone deficiency

Targeted mass spectrometry (multiple-reaction monitoring, MRM) enables reproducible, multiplexed quantification of plasma proteins, but whether a fixed targeted panel can resolve endocrine disorders with overlapping systemic features is unknown. We analyzed a 256-protein targeted panel (1,894 peptides; 3,790 transitions) quantified in 57 participants spanning autoimmune thyroid disease (Hashimotos thyroiditis, n=7; Graves disease, n=5) and growth-hormone deficiency (GHD; partial, n=26; complete, n=19). Protein abundances were obtained by transition summation, log2 transformation, and per-sample median normalization. We applied unsupervised analysis (PCA, PERMANOVA), differential expression (limma), an ordered severity-trend test, and leave-one-out cross-validated classification with feature selection performed strictly inside each fold. All 256 proteins were quantified in every sample (median inter-sample r=0.875). PC1 (36% variance) separated autoimmune thyroid disease from GHD (p=0.016), whereas the global four-group structure was not significant (PERMANOVA p=0.17). No protein reached FDR<0.05, but the autoimmune-versus-GHD contrast was strongly enriched for low p-values (26 proteins at p<0.05; binomial p=5.4x10-4). The signal was biologically coherent: immunoglobulin/B-cell-receptor proteins, including CD79A, were lower, whereas proteasome subunits (PSMC5, PSMC3) and the NF-{kappa}B subunit RELA were higher in autoimmune disease. A cross-validated classifier separated the two classes (AUC 0.72; permutation p=0.05; eight proteins selected in all folds), whereas GHD severity was not predictable (AUC 0.31). A fixed 256-protein targeted panel reproducibly captures an immunoglobulin/B-cell-receptor and proteasome/NF-{kappa}B axis that distinguishes autoimmune thyroid disease from GHD but cannot resolve within-class severity.

systems biology↗

bioRxiv2026

Multimodal Human Scalp Atlas Defines Cell Landscape and Lineage Architecture In Situ

Human scalp hair has an extraordinary ability to grow continuously for years while maintaining structural and functional integrity. However, the cell states and lineage organization that enable this capacity and how they are disrupted in inflammatory hair loss disorders remain poorly defined in humans. Here we establish a high-resolution, multimodal atlas of human scalp by integrating deep-coverage spatial transcriptomics with single-cell RNA-seq and multiomics data. This reference resolves spatially organized epithelial and mesenchymal states and links in situ transcriptional programs to chromatin accessibility dynamics and lineage trajectories at single-cell resolution, revealing human-specific principles of tissue organization and previously unrecognized features of hair follicle architecture and lineage progression. We validate key aspects of matrix cell organization and cell activities using live imaging, connecting molecularly defined cell states to dynamic cell behaviors and lineage progression in the matrix. Leveraging the atlas as a spatial reference, we project patient scRNA-seq profiles from alopecia areata and lichen planopilaris onto defined cell compartments, resolving disease-specific perturbations in fibroblasts, epithelial and immune populations. This comparison delineates distinct cellular programs associated with non-scarring versus scarring hair loss and highlights compartment- and state-specific pathways with diagnostic and therapeutic potential. Together, this work provides a foundational resource for human hair biology and establishes a generalizable framework for spatially resolved, multimodal interrogation of tissue organization and disease in complex human tissues.

Developmental Biology↗

bioRxiv2026

Whole-brain protein profiling using organ-scale multiplexed immunolabeling and image co-registration

Proteins are major drivers of biological functions. Single-cell, organ-scale multiplexed protein imaging can reveal high-dimensional molecular and structural features of individual cells and their interactions, enabling an in-depth understanding of complex biological systems. However, achieving such imaging has remained elusive due to hurdles in multiplexed immunolabeling (mIF) of intact organs and integrative image analysis. Here, we present 3D CYCLIC, an organ-scale multiplexed immunolabeling technique, and TACTIC, a single-cell-level, organ-scale image co-registration algorithm. 3D CYCLIC combines ultrafast, versatile 3D immunolabeling with a cleavable crosslinker that preserves signals by protecting bound antibodies during optical clearing while enabling their detachment for subsequent rounds of immunolabeling. TACTIC uses deep warping networks coupled with a propagation-based cell-pair search to co-register individual cells across whole-brain images acquired from multiple rounds of 3D CYCLIC labeling. 3D CYCLIC enabled 6-plex protein profiling of a mouse brain hemisphere, with images that can be combined with TACTIC for integrative analysis. 3D CYCLIC and TACTIC are versatile techniques and will therefore enable a holistic, unbiased understanding of diverse organs.

neuroscience↗

bioRxiv2026

PEACE: Prototype-aware Effector Analysis via Contrastive Embeddings

Pathogenic fungi and oomycetes secrete effector proteins that manipulate host defenses and physiology to facilitate infection. However, in a typical secretome, effectors represent only a small fraction of proteins, creating extreme class imbalance and making deep-learning-based effector prediction prone to false positives. Here, we introduce PEACE (Prototype-aware Effector Analysis via Contrastive Embeddings), a lightweight pipeline that integrates ProtTrans (ProtT5) sequence embeddings with prototype-aware contrastive training to enhance effector identification. We benchmark PEACE against EffectorP 3.0 on two datasets with realistic class ratios: a fungal-only dataset and a combined fungi+oomycete dataset. PEACE outperforms EffectorP 3.0 on both datasets, while maintaining highly competitive recall. Post-hoc analysis shows that PEACE forms compact effector clusters against a well-dispersed non-effector background, which improves precision in the high-recall regime. These findings demonstrate that prototype-aware objectives, combined with curated data, can improve effector discovery for high-throughput screening in plant pathology and biotechnology.

bioinformatics↗

bioRxiv2026

Simulating Neutron Protein Crystallography Experiments: Applications to the Development of the NMX Instrument at ESS

Monte Carlo neutron ray-tracing simulations of time-of-flight (TOF)-Laue neutron macromolecular crystal diffraction (n-MX) using the McStas software package were done for the upcoming NMX Macromolecular Diffractometer at the European Spallation Source. Splitting neutron rays that arrive at the crystal lead to dramatic improvements in event formation with minimal computational overhead. The simulated event probability data was sampled using a new single-pass weighted reservoir sampling method, and processed like real n-MX data using DIALS. The effects of air and beamstop scatter on simulated data was investigated. SynopsisMonte Carlo simulations of neutron protein diffraction experiments provide useful data that models instrumental components that interact with neutrons, as well as the crystal diffraction itself. These data can be applied to instrument development, such as the commissioning of the NMX Macromolecular Diffractometer at ESS.

biophysics↗

bioRxiv2026

The Spatiotemporal Proteome Landscape of Aging: Structural determinants of age-sensitive proteome remodeling

Aging is marked by a decline in cellular functions accompanied by widespread changes in mRNA and protein abundance, yet whether aging broadly remodels subcellular protein localization and concentration--and why some proteins change while others remain stable--remains unclear. This gap matters because cellular function depends not only on expression levels but also on correct spatial organization. Using yeast replicative aging as a model, we built a robotic pipeline to enrich old cells from 5,661 strains, acquired 90 million single-cell 3D images, and applied machine learning to map proteome-wide changes in localization, concentration, and aggregation throughout aging. This age-resolved single-cell atlas uncovers widespread proteome remodeling and rewiring of protein interaction networks. Moreover, structural analysis reveals biophysical determinants of age-sensitive proteome remodeling across ages and species. Together, these results reveal a structure-encoded intrinsic principle underlying spatial proteome breakdown during aging and provide a resource to dissect mechanistic links among aging hallmarks.

systems biology↗

bioRxiv2026

Single-Cell Spatial Proteomics Uncovers Molecular Interconnectivity among Hallmarks of Aging

Aging is accompanied by conserved hallmarks including genomic instability, epigenetic alterations, loss of proteostasis, and mitochondrial dysfunction, but how these processes emerge and become mechanistically linked remains unclear. Here we leverage a proteome-wide, single-cell, subcellular atlas of protein expression, localization, and aggregation across yeast replicative aging to map hallmark-linked remodeling in its spatial context. We identify hundreds of previously unappreciated molecular changes that underlie major hallmarks of aging and show that hallmark phenotypes frequently manifest as compartment-specific erosion of spatial confinement, relocalization, and aggregation. 91.6% human orthologs of these hallmark-linked yeast proteins also change during human aging. Integrating these spatial phenotypes reveals many molecular connections linking different hallmarks. Temporal analysis suggests that disorganization of nucleolar ribosome biogenesis, proteostasis decline, and mitochondrial dysfunction precede other hallmarks. Together, our findings substantially deepen the molecular underpinnings of aging hallmarks and provide a framework for linking them into a hierarchical sequence of cellular failures.

systems biology↗

bioRxiv2026

Fine-tuning STEAP1 protein expression and purification to preserve its conformation and function

Six-transmembrane Epithelial Antigen of the Prostate 1 (STEAP1) has emerged as a promising therapeutic target for prostate cancer. We have optimized the expression and purification conditions of human STEAP1 to maximize the production of its homotrimeric form, which is crucial for metal ion reduction and maintaining cellular redox balance. Proteins obtained from these optimized conditions were complexed with both heme and flavin-adenine dinucleotide (FAD), two cofactors that are fundamental to STEAP functionality, suggesting native folding and interactions of the protein. In addition, we compared the impact of stable and transient expression systems on the protein quality of STEAP1. We found that stable expression promoted heme incorporation, improved expression homogeneity, and ensured correct protein orientation on cell surfaces. Our findings present effective strategies for optimizing the recombinant production of STEAP1, with potential applicability to other STEAP family proteins to facilitate therapeutic discovery.

biochemistry↗

bioRxiv2025

Organelle-Aware Representation Learning Enables Label-Free Detection of Mitochondrial Dysfunction in Live Human Neurons

Mitochondrial dysfunction is a convergent hallmark of neurodegenerative diseases and represents a promising biomarker for early diagnosis and therapy. However, current in vitro assays rely on fluorescence or electron microscopy, which are invasive, low-throughput, and incompatible with longitudinal analysis. Here, we present a noninvasive framework by integrating label-free optical diffraction tomography (ODT) with organelle-aware representation learning to detect subtle mitochondrial dysfunction in live human induced pluripotent stem cell (hiPSC)-derived neurons. Through virtual staining of the nuclei, lysosomes, and mitochondria, we establish two complementary and interpretable classification pipelines: a deep learning model with organelle-aware encoder and a logistic regression model on morphometric descriptors. Both models achieve approximately 85% accuracy: the deep model provides end-to-end prediction with minimal feature engineering, whereas the logistic regression model offers a more interpretable, feature-based approach. To our knowledge, this is the first demonstration of ODT-based organelle-resolved virtual staining in live human neurons, establishing a scalable, non-invasive platform for mitochondrial disease modeling, drug discovery, and neurodegeneration research.

neuroscience↗

bioRxiv2025

Autonomous neuronal resilience under metabolic stress highlights fundamental differences between hESC and hiPSC-derived neurons

Human induced pluripotent stem cells (hiPSCs) aim to replicate the developmental and functional capacity of human embryonic stem cells (hESCs). Here, we identify neuronal resilience under metabolic stress as a critical parameter for benchmarking equivalence. Without medium replenishment, hESC-derived cortical neurons underwent neural resurrection--a spontaneous recovery marked by increased cell density, preserved morphology, and sustained calcium signaling and mitochondrial function for 23 days. In contrast, hiPSC-derived neurons survived but showed reduced adaptability, deteriorating within 10-14 days despite higher initial densities. Our findings introduce a physiologically relevant assay for stress resilience and highlight the need to optimize hiPSC differentiation to achieve hESC-like performance, improving their translational value for disease modeling and regenerative therapy.

cell biology↗

bioRxiv2025

Dietary restriction promotes neuronal resilience via ADIOL

The steroid hormone 5-androstene-3{beta},17{beta}-diol (ADIOL) was discovered in humans nearly a century ago, yet its physiological roles remain poorly defined. Here, we show that fasting and caloric restriction, two forms of dietary restriction, induce transcriptional upregulation of genes encoding CYP11A1, CYP17A1, and 17{beta}-hydroxysteroid dehydrogenase family enzymes, promoting ADIOL biosynthesis. ADIOL, in turn, acts on the nervous system to reduce levels of kynurenic acid, a neuroactive metabolite linked to cognitive decline and neurodegeneration. This effect requires NHR-91, the C. elegans homolog of estrogen receptor {beta}, specifically in the RIM neuron, a key site of kynurenic acid production. Consistent with the known benefits of fasting and caloric restriction on healthspan, enhancing ADIOL signaling improves multiple healthspan indicators during aging. Conversely, animals deficient in ADIOL signaling exhibit reduced healthspan under normal conditions and in genetic models of caloric restriction, underscoring the functional significance of this pathway. Notably, ADIOL does not significantly impact lifespan, indicating that its healthspan benefits are not simply a byproduct of lifespan extension. Together, these findings establish a physiological role for ADIOL in mediating the neuroprotective and pro-healthspan effects of fasting and caloric restriction and suggest that boosting ADIOL signaling may help narrow the gap between lifespan and healthspan. This positions ADIOL as a promising mimetic of dietary restriction effects on healthspan that could be used as a therapeutic strategy for age-related neurodegenerative conditions. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/661551v2_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@3246f7org.highwire.dtl.DTLVardef@d13dbaorg.highwire.dtl.DTLVardef@12b86f6org.highwire.dtl.DTLVardef@a98d62_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

Predict metal-binding proteins and structuresthrough integration of evolutionary-scale andphysics-based modeling

Metals are essential elements in all living organisms, binding to approximately 50% of proteins. They serve to stabilize proteins, catalyze reactions, regulate activities, and fulfill various physiological and pathological functions. While there have been many advancements in determining the structures of protein-metal complexes, numerous metal-binding proteins still need to be identified through computational methods and validated through experiments. To address this need, we have developed the ESMBind workflow, which combines evolutionary scale modeling (ESM) for metal-binding prediction and physics-based protein-metal modeling. Our approach utilizes the ESM-2 and ESM-IF models to predict metal-binding probability at the residue level. In addition, we have designed a metal-placement method and energy minimization technique to generate detailed 3D structures of protein-metal complexes. Our workflow outperforms other models in terms of residue and 3D-level predictions. To demonstrate its effectiveness, we applied the workflow to 142 uncharacterized fungal pathogen proteins and predicted metal-binding proteins involved in fungal infection and virulence.

bioinformatics↗

bioRxiv2024

Single-nucleus and spatial transcriptomic analysis identified molecular features of neuronal heterogeneity and distinct glial responses in Parkinson's disease.

The heterogeneity of Parkinsons disease (PD) is increasingly recognized as an important aspect of understanding the disorder. Among the factors contributing to this heterogeneity, ethnic differences are primary sources, significantly influencing the likelihood of PD developing and its initial symptoms nature. While there have been numerous reports related to PD in East Asia, there has been a lack of contribution from single-cell (or nucleus) transcriptome studies, which have been making significant contributions to understanding PD. In this study, a total of 33,293 nuclei obtained from the substantia nigra (SN) of confirmed pathological PD and control patients in South Korea were profiled, revealing 8 different cell types through cluster analysis. Monocle-based pseudotime analysis identified two disease-associated trajectories for each astrocyte and microglia and identified genes that differentiate them. Interestingly, we uncovered the inflammatory intervention in the early PD-associated transition in microglia and identified the molecular features of this intermediate state of microglia. In addition, gene regulatory networks (GRNs) based on TENET analysis revealed the detrimental effect of an HSPA5-led module in microglia and MSRB3- and HDAC8- led modules specifying the two different astrocyte trajectories. In SN neurons, we observed population changes, a decrease in dopaminergic and glutamatergic neurons and a proportional increase in GABAergic neurons. By deconvolution in spatial transcriptome obtained the PD sample, we confirmed spatiotemporal heterogeneity of neuronal subpopulations and PD-associated progressive gliosis specific to dopaminergic nuclei, SN and ventral tegmental areas (VTAs). In conclusion, our approach has enabled us to identify the genetic and spatial characterization of neurons and to demonstrate different glial fates in PD. These findings advance our molecular understanding of cell type-specific changes in the progression of Korean PD, providing an important foundation for predicting and validating interventions or drug effects for future treatments.

neuroscience↗

bioRxiv2024

Single cell RNA-sequencing reveals GINIP-expressing neurons as the main targets of focused ultrasound

Dorsal root ganglion (DRG) neurons have a wide range of functions, including touch, pain and itch. These neurons have emerged as promising targets for non-invasive focused ultrasound (FUS) neuromodulation. However, our knowledge of the molecular and physical mechanisms underlying FUS-evoked responses in DRG neurons is limited. Here, we investigate the neuromodulatory capabilities of FUS in cultured DRG neurons in combination with calcium imaging. We find that a 20-MHz FUS burst of 1-ms duration at an acoustic pressure of 5 MPa elicited calcium responses in 52% of DRG neurons. Single-cell RNA sequencing reveals that the majority of FUS-sensitive neurons belong to three subsets of DRG neurons; C-LTMRs, the MRGPRD-expressing C-HTMRs and A6-LTMRs. FUS excites all these neuronal subtypes by membrane deformation, suggesting a mechanism mediated by mechanosensitive ion channels. Our results identify FUS parameters that activate distinct subsets of DRG neurons and open new avenues for using FUS stimulation to modulate DRG neuron function.

neuroscience↗

bioRxiv2024

Predicting task-related brain activity from resting-state brain dynamics with fMRI Transformer

Accurate prediction of the brains task reactivity from resting-state functional magnetic resonance imaging (fMRI) data remains a significant challenge in neuroscience. Traditional statistical approaches often fail to capture the complex, nonlinear spatiotemporal patterns of brain function. This study introduces SwiFUN (Swin fMRI UNet Transformer), a novel deep-learning framework designed to predict 3D task activation maps directly from resting-state fMRI scans. SwiFUN leverages advanced techniques such as shifted window-based self-attention, which helps to understand complex patterns by focusing on varying parts of the data sequentially, and a contrastive learning strategy to better capture individual differences among subjects. When applied to predicting emotion-related task activation in adults (UK Biobank, n=7,038) and children (ABCD, n=4,944), SwiFUN consistently achieved higher overall prediction accuracy than existing methods across all contrasts; it demonstrated an improvement of up to 27% for the FACES-PLACES contrast in ABCD data. The resulting task activation maps revealed individual differences across cortical and subcortical regions associated with sex, age, and depressive symptoms. This scalable, transformer-based approach potentially reduces the need for task-based fMRI in clinical settings, marking a promising direction for future neuroscience and clinical research that enhances our ability to understand and predict brain function.

neuroscience↗

bioRxiv2024

FAM19A5 Deficiency Mitigates the Aβ Plaque Burden and Improves Cognition in Mouse Models of Alzheimer's Disease

FAM19A5, a novel secretory protein highly expressed in the brain, is potentially associated with the progression of Alzheimers disease (AD). However, its role in the AD brain remains unclear. Here, we investigated the potential function of FAM19A5 in the context of AD. We generated APP/PS1 mice with partial FAM19A5 deficiency, termed APP/PS1/FAM19A5+/LacZ mice. Compared to control APP/PS1 mice, APP/PS1/FAM19A5+/LacZ mice exhibited significantly lower A{beta} plaque density, suggesting that FAM19A5 reduction mitigates A{beta} plaque formation. Notably, partial FAM19A5 depletion also prolonged the lifespan of the APP/PS1 mice. To further explore the therapeutic potential of targeting FAM19A5, we developed an anti-FAM19A5 antibody. Administration of this antibody to APP/PS1 mice significantly improved their performance in the novel object recognition test, demonstrating enhanced cognitive function. This effect was reproduced in 5XFAD mice, a model of early-onset AD characterized by rapid A{beta} accumulation. Additionally, anti-FAM19A5 antibody treatment in 5XFAD mice led to increased spontaneous alternation behavior in the Y-maze test, indicating improved spatial working memory. These findings suggest that anti-FAM19A5 antibodies may be a promising therapeutic strategy for AD by reducing A{beta} plaques and improving cognitive function.

neuroscience↗

bioRxiv2024

Partial FAM19A5 Deficiency in Mice Leads to Disrupted Spine Maturation, Hyperactivity and Altered Fear Response

The FAM19A5 polypeptide, encoded by the TAFA5 gene, is evolutionarily conserved among vertebral species. This protein is predominantly expressed in the brain, highlighting its crucial role in the central nervous system. Here, we investigated the potential roles of FAM19A5 in brain development and behavior using a FAM19A5-LacZ KI mouse model. This model exhibited a partial reduction in the FAM19A5 protein level. FAM19A5-LacZ KI mice displayed no significant alterations in gross brain structure but alterations in dendritic spine distribution, with a bias toward immature forms. These mice also had lower body weights. Behavioral tests revealed that compared with their wild-type littermates, FAM19A5-LacZ KI mice displayed hyperactivity and a delayed innate fear response. These findings suggest that FAM19A5 plays a role in regulating spine formation and maintenance, thereby contributing to neural connectivity and behavior.

neuroscience↗