Biology subjects

Yoo, H.

Publications and source records attributed to Yoo, H..

At least 19 recordsLinked to original sources

bioRxiv2026

Multiscale, Survey-and-Target Optical Super-Resolution Histology

Super-resolution microscopy reveals fine subcellular tissue architecture, yet extending this capability to histological screening requires balancing spatial resolution with imaging area, axial access, throughput, and instrumental complexity. Here we present multiscale optical super-resolution histology (MOSH), an integrated optical-computational platform that combines tissue-scale, extended-depth-of-focus super-resolution surveys with coordinate-guided three-dimensional interrogation of selected targets. MOSH leverages stationary multifocal excitation, continuous sample translation, tunable axial refocusing, and parallelized reconstruction within a shared spatial-coordinate framework in a conventional epi-fluorescence setting. This survey-and-target strategy preserves tissue-scale context, directs volumetric acquisition to selected subcellular structures, and generates virtual H&E images that retain resolution-enhanced structural information. Across cultured cells, cytological preparations, conventional tissue sections, and intact unsectioned biopsies, MOSH achieved approximately twofold resolution enhancement, continuous lateral coverage beyond the native field of view, and tunable axial survey ranges up to 20 m. Bridging tissue-scale histological screening and targeted, quantitative nanoscale interrogation, MOSH establishes a scalable framework for multiscale analysis of biological and clinical specimens.

bioengineering↗

bioRxiv2026

A cargo receptor entrapment complex is a therapeutic node for genetically and clinically distinct proteinopathies

Severe proteinopathies--such as retinitis pigmentosa, a form of inherited blindness--are driven by genetic mutations that overwhelm the quality control of the post-endoplasmic reticulum (post-ER) secretory pathway, causing toxic protein accumulation. Here, we identify a therapeutic node defined by a hetero-oligomeric cargo receptor complex consisting of TMED7, 2, 9, and 10. This "entrapment complex" anchors structurally and functionally diverse mutant clients within the early secretory pathway via TMED7 binding to the integral Golgi protein GRASP55. Disruption of the entrapment complex results in the clearance of accumulated protein cargoes. In vivo ablation of the entrapment node via inducible genetic deletion or via the small molecule BRD7635 reverses histopathological hallmarks and rescues functional deficits in clinically distinct proteinopathies of the kidney and the eye, including mitigating vision loss in a mouse model of retinitis pigmentosa.

cell biology↗

bioRxiv2026

Comparing Harmonization Approaches for Protocol-Related Variability in Multisite Diffusion MRI Data

Diffusion MRI (dMRI) enables assessment of white matter microstructural abnormalities in Alzheimers disease (AD), and multisite datasets enable more robust modeling of non-biological variation that can confound analyses. The Alzheimers Disease Neuroimaging Initiative (ADNI) includes over 10 dMRI protocols, necessitating robust methods to model protocol-related variability when pooling data. Here, we compared three harmonization approaches: (1) mixed-effects models, (2) ComBat-GAM, and (3) eHarmonize, a reference-based lifespan method. We assessed their ability to reduce protocol-related variability in diffusion tensor imaging fractional anisotropy (FA) and mean diffusivity (MD) while preserving associations with cognitive impairment (CI), and amyloid-beta (A{beta}) and tau PET burden in 1,086 ADNI3/4 participants. All approaches yielded more closely aligned FA/MD distributions across protocols. Associations with clinical indicators of CI were highly consistent across approaches, whereas PET associations were less widespread and more variable. Overall, multiple strategies effectively modeled protocol-related variability while preserving AD-related associations.

neuroscience↗

bioRxiv2026

MINA: linear probes reveal coding-sequence family signal in frozen DNA encoders

Frozen DNA encoders are widely used as feature extractors, but fine-tuning hides what their fixed embeddings already make linearly accessible. We introduce MINA (Model Interrogation of Nucleotide Architectures), a lightweight benchmark testing whether frozen DNA embeddings can recover (i) a 5-way protein-family label and (ii) the 1,536-d GenePT natural-language embedding for each gene, comparing coding-sequence (CDS) and transcription-start-site (TSS) contexts under a homology-aware split, against translated-composition and protein-language-model baselines. Across 3,244 human genes from five families, the best DNA encoder recovers CDS family labels above 4-mer composition (NT-v2 macro-F1 0.727 vs. 0.633) but only reaches translated amino-acid composition (AA 2-mer 0.735), far below ESM-2 on translated proteins (0.960). GenePT recovery is weak (best DNA R2 = 0.077), and TSS family recovery collapses under homology control (NT-v2 0.447 [->] 0.313). Pooling and encoder choice matter as much, so encoders are not interchangeable: frozen DNA encoders expose coding-sequence protein-compositional signal from raw nucleotides, not robust gene-function signal from arbitrary genomic context.

bioinformatics↗

bioRxiv2026

SPECTRA: Spatial Inference for Tractometry Toward Precision Mapping of White Matter Microstructure

Diffusion MRI tractometry characterizes white matter microstructure along fiber bundles, but standard along-tract profiling collapses measurements across the bundle cross-section, obscuring radial heterogeneity and producing spatially inconsistent units of inference. We present SPECTRA (Spatial Inference for Tractometry), a framework designed to address these limitations through a unified design of parameterization and statistical inference. First, we propose a 2D bundle parameterization that extends along-tract profiling to include a radial dimension defined on the atlas bundle. Second, we develop a two-stage hierarchical false discovery rate (hFDR) procedure for multi-bundle inference, which aggregates evidence at a coarser spatial scale before proceeding to finer-grained inference, with spatial scales derived from a Matern kernel. Across extensive simulation conditions, we found that hFDR improves statistical power and reduces the sample size required to detect effects compared to global FDR correction, while maintaining appropriate error control. We further characterized how sensitivity-specificity tradeoffs depend on sample size, the magnitude, spatial extent, and configurations of effects, thereby providing practical guidance for tractometry study design. In an empirical analysis of mild cognitive impairment and dementia in more than 4,000 subjects across 63 bundles, SPECTRA revealed spatially localized patterns that were absent in 1D profiles. Together, these results demonstrate that spatially resolved parameterization and adaptive error control jointly enable precise mapping of white matter microstructure in large-scale tractometry studies. SPECTRA is openly available as a Python package.

neuroscience↗

bioRxiv2026

A self-limiting orexin-habenula circuit for stress resilience

Resilience requires neural systems that mobilise active coping during stress while limiting its persistence to preserve homeostasis under sustained challenge1-4. Here we identify a self-limiting orexin-habenula circuit in which lateral hypothalamic orexin neurons engage aromatic L-amino acid decarboxylase-expressing D-neurons (encoded by Ddc) in the lateral habenula via orexin receptor type 2 (OX2R)5-7. Activation of this pathway increased nucleus accumbens dopamine and promoted active coping and positive valence. Optotagging revealed rapid stress-evoked recruitment followed by post-stress suppression. In lateral habenula neurons, orexin peptides exerted dissociable effects: orexin-A engaged an OX2R-dependent inhibitory programme superimposed on a parallel inward current, whereas orexin-B did not reproduce this inhibitory profile and instead exerted a distinct membrane effect. Chronic stress disrupted this buffering system through coordinated inflammatory activation, promoter methylation and erosion of D-neuron identity and orexin responsiveness. Restoring orexin-A reversed behavioural and molecular deficits through OX2R-dependent suppression of nuclear factor kappa B signalling, preservation of Tet2 expression, and demethylation-linked maintenance of the Ddc programme. Together, these findings define a self-limiting orexin-habenula resilience circuit that enables adaptive coping while constraining stress-induced vulnerability.

neuroscience↗

bioRxiv2026

An underlying bistability sets amplitude and explains temperature compensation in the cyanobacterial circadian clock

Circadian clocks create free-running biological rhythms with a period close to 24 hours. A universal property of these systems is temperature compensation, where the period of oscillation remains nearly invariant even as the amplitude changes with temperature. In the cyanobacterial system, where the core oscillator can be reconstituted from purified KaiABC proteins, we identify a key temperature-dependent positive feedback process: antagonism between KaiA and KaiB creates a bistable switch in protein-protein interaction. The region of bistability is strongly temperature dependent and correlated with oscillator amplitude. Combining this bistable mechanism with the temperature scaling of phosphorylation and dephosphorylation rates in a mathematical model recapitulates the overall temperature compensation of the oscillator. This capacity for history-dependent switching suggests that bistable dynamics underpin the generation of circadian rhythms. Significance StatementCircadian clocks are biological oscillators that anticipate the day-night cycle. The 24-hour time scale of the clock is remarkably insensitive to temperature owing to compensatory changes in amplitude and speed with temperature. In the cyanobacterial clock, we identify a bistability of the protein interaction network which determines oscillator amplitude and depends strongly on temperature, balancing the temperature dependence of dephosphorylation rates. This bistability indicates that oscillations arise from a combination of positive and negative feedback loops, a design principle used to maintain temperature compensation.

biophysics↗

bioRxiv2026

Tractometry-Based Quantification of Along-Tract White-Matter Hemispheric Asymmetry in Alzheimer's Disease

White-matter hemispheric asymmetry is a fundamental property of human brain organization and is known to change in aging, neurodevelopment, and neurodegenerative disorders. Tractometry analyzes diffusion-derived microstructural measures along the full length of tracts, localizing changes to specific tract-segments rather than collapsing tracts into a single value. Yet, existing frameworks lack a principled way to quantify left-right hemispheric asymmetries along homologous tracts. Here, we introduce an asymmetry-aware tractometry framework that integrates a symmetric white-matter atlas with BUAN (Bundle Analytics) to enable anatomically consistent, along-tract comparison of homologous pathways. By defining homologous bundles with a shared template and consistent orientation, each left-hemisphere segment is directly matched to its right-hemisphere counterpart, enabling principled, segment-wise comparison and revealing spatially localized asymmetries along-tract. Applying this framework to diffusion MRI data from the Alzheimers Disease Neuroimaging Initiative (ADNI) comprising 1,215 subjects, we demonstrate how this approach reveals systematic left-right asymmetries across major white-matter pathways and show how these patterns differentiate cognitively normal (CN) individuals from those with mild cognitive impairment (MCI) and dementia. This method provides a sensitive and anatomically grounded tool for studying hemispheric specialization and its disruption in aging and disease, and establishes a general approach for asymmetry-aware tractometry in population neuroimaging studies.

neuroscience↗

bioRxiv2026

Nevermore: Target-Conditioned Protein-Ligand Representation Learning for Multi-Objective Lead Optimization with Database-Grounded Retrieval

Target-conditioned molecular design requires optimizing binding affinity to a proposed therapeutic protein target while balancing competing developability constraints (e.g., absorption, distribution, metabolism, excretion, and toxicity; ADMET). Yet many computational pipelines either optimize a single objective or rely on fully de novo generation that can be difficult to control and interpret. We present Nevermore, a target-conditioned, database-grounded framework that combines a geometry-aware protein-ligand affinity oracle with Pareto-aware multi-objective search over an explicit molecular feature space. A central design choice is to optimize in count-based Morgan fingerprint space, where each feature corresponds to a chemically meaningful substructure count, enabling discrete, interpretable "bucket-level" edits. Nevermore learns target-conditioned scores by aligning protein and ligand representations under contrastive objectives and using a similarity-based prediction head; the resulting affinity oracle improves over previously reported benchmark baselines, providing a stronger scoring signal for downstream optimization. Nevermore then steers candidate selection by proposing sparse fingerprint edits, re-ranking candidates under multiple objectives, and projecting edited fingerprints back to valid molecules via nearest-neighbor retrieval from a large compound library. This yields efficient screening without exhaustive enumeration and provides transparent attributions that connect optimization steps to concrete chemical motifs. We evaluate Nevermore on two target case studies (Menin and SARS-CoV-2 Mpro). Across targets, the closed-loop search consistently retrieves candidate sets with improved affinity-property trade-offs compared with random sampling and similarity-only retrieval baselines, while maintaining explicit control and interpretability through discrete feature-space edits. These results support database-grounded, feature-space steering as a practical route to target-conditioned multi-objective lead refinement without relying on fully de novo generation.

bioinformatics↗

bioRxiv2025

Primary metabolism determines the outcome of salicylic acid-mediated immune induction

Controlling the deleterious effects of immune responses is as vital as fighting infection. In plants, this is achieved, in part, by circadian clock-mediated regulation, such as the synthesis of and response to the immune hormone salicylic acid (SA)1,2. Application of SA at the same concentration under light/dark cycles induces immunity with minimal impact on growth, however, prolonged darkness leads to plant death2. To uncover what determines this life-or-death outcome, we identified twenty survival of SA-induced death (ssd) mutants through genetic screening. These mutants are defective in starch, glucose, and nitrate metabolism, and circadian regulation, and accumulate excessive starch and/or glucose. Likewise, glucose application rescues SA-treated plants in prolonged darkness. Surprisingly, SA treatment does not deplete glucose, but instead, induces amino acid and fatty acid catabolism. Through transcriptomic analyses of glucose-rescued WT plants and ssd mutants for shared pathways, we found that SA triggers plant death in darkness by inducing oxidative stress, and water loss, while glucose antagonizes these processes, boosts ER protein processing and re-establishes the anabolism-catabolism balance. Interestingly, the programmed cell death induced by effector-triggered immunity shares common transcriptomic patterns with those observed during SA-induced cell death in darkness and could also be attenuated by glucose treatment. Therefore, coordination with the cellular metabolic context plays a central role in determining immune outcomes and optimizing plant health.

plant biology↗

bioRxiv2025

DTI versus NODDI White Matter Microstructural Biomarkers of Alzheimer's Disease

Diffusion MRI (dMRI) is a powerful tool to assess white matter (WM) microstructural abnormalities in Alzheimers disease (AD). The fourth phase of the Alzheimers Disease Neuroimaging Initiative (ADNI) now includes multiple multishell dMRI protocols, enabling both traditional and advanced dMRI model analyses. There is a need to evaluate whether multishell data offer deeper insights into WM pathology in AD than more widely available single-shell data by overcoming single-shell model limitations. Here, we fit single-shell DTI and multishell NODDI to dMRI data from 533 ADNI3/4 participants to assess their sensitivity to key clinical indicators of AD such as cognitive impairment, amyloid-beta and tau PET burden. Overall, we found that NODDI offered no major advantages in detecting cognitive impairment and tau pathology, but NODDI was marginally more sensitive to amyloid pathology.

neuroscience↗

bioRxiv2025

Cis-regulatory variation in ISOCHORISMATE SYNTHASE 1 modulates systemic salicylic acid biosynthesis and systemic acquired resistance in plants

Systemic acquired resistance (SAR) is a long-distance immune response that protects uninfected plant tissues following a localized pathogen attack. In the model plant Arabidopsis thaliana, SAR depends on the systemic accumulation of salicylic acid (SA), mediated by the transcription factor CCA1 HIKING EXPEDITION (CHE), which activates the SA biosynthetic gene ISOCHORISMATE SYNTHASE1 (ICS1). However, the conservation and functional significance of the CHE-ICS1 regulatory module across plant species remain poorly understood, particularly in the Brassicaceae, where ICS1 is the major contributor to SA biosynthesis among two known pathways: the ICS1 and PHENYLALANINE AMMONIA-LYASE (PAL) routes. Here, we identify natural variation in cis-regulatory elements within the ICS1 promoter that affects CHE binding across species. In multiple Brassicaceae species with divergent cis-element sequences, CHE fails to regulate ICS1, leading to the absence of systemic ICS1 induction and SA accumulation following pathogen infection. Despite this deficiency, SAR still occurs in these species, albeit to a lesser extent than in species with successful systemic induction of SA mediated by an intact CHE-ICS1 regulatory module. Interestingly, introducing the CHE-ICS1 module into species lacking this interaction confers systemic SA accumulation, highlighting the potential to enhance systemic immunity through cis-element modification. Our findings demonstrate that sequence variation in a cis-regulatory element underlies the interspecies diversification of SAR regulatory mechanisms and highlight the evolutionary plasticity of plant immune signaling. This study provides a molecular framework for engineering enhanced systemic immunity in crops, particularly within the Brassicaceae, through the targeted modification of cis-regulatory elements that regulate SA biosynthesis.

plant biology↗

bioRxiv2025

Phase Separation Oppositely Modulates G-quadruplex and i-Motif DNA Folding in the Nuclei of Living Cells

G-quadruplexes and i-motifs are non-canonical DNA structures that are important not only as targets of gene regulation in cancer therapy, but also as nanotools with biomedical applications. However, their apparent in vitro stabilities and dynamics cast doubt upon their physiological relevance and utility in vivo. Here we investigate folding of the thrombin-binding aptamer G-quadruplex and the TAA(C5TAA)4 i-motif. We use fast relaxation imaging, which couples fluorescence microscopy with laser-induced temperature jumps, to quantify the stability and dynamics of FRET-labelled constructs in vitro and in the nuclei of living cells. Our work suggests that the stability and kinetics of i-motif and G-quadruplex DNA are carefully tuned by phase separation to fit the seconds-to-minutes timescales of key regulatory processes inside cells. Taken together, our findings underscore the importance of studying the folding of DNA structures under near-physiological conditions to their mechanistic understanding as well as for the development of DNA-targeted drugs. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/661982v2_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@e76eedorg.highwire.dtl.DTLVardef@23aefforg.highwire.dtl.DTLVardef@b6117aorg.highwire.dtl.DTLVardef@135736a_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2025

Regularized Deep Neural Networks for Combining Heterogeneous Features of Peptides in Data Independent Acquisition Mass Spectrometry

AbstractData-independent acquisition (DIA) has gained much attention in mass spectrometry (MS)-based proteomics for its improved reproducibility and unbiased data acquisition. In DIA-MS, the spectral library is crucial in peptide identification. However, this method is limited to peptides previously identified via data-dependent acquisition (DDA) MS experiments. This study proposes a deep learning approach for generating spectral libraries, even for previously unseen peptides. While most deep learning-based methods rely on one-hot encoding representation for peptides, the proposed method incorporates physicochemical features, including atomic composition, hydrophobicity, flexibility, fractional surface probability, and aromaticity. We introduce sparsity regu-larized neural network layers to facilitate the selection and combination of important high-dimensional physicochemical features and improve prediction performance. Fur-thermore, we suggest a transfer learning strategy for training the proposed deep neural networks having multiple heterogeneous input channels. Numerical experiments using benchmark DDA-MS data demonstrated that the proposed deep learning model out-performed existing benchmark models, such as Prosit and DeepDIA, particularly in predicting retention times. And it was demonstrated that the proposed models with sparsity regularization identified more peptides from HeLa cell DIA data compared to the other deep learning models.

bioinformatics↗

bioRxiv2025

Serine activates defense mechanisms via glutamate receptor-like channel 3.4 and calcium-dependent protein kinase 5 signaling in plants.

Amino acids are fundamental building blocks of proteins, as well as essential metabolites for plant growth and development. Beyond their metabolic roles, amino acids have been increasingly recognized as regulators of plant immunity. However, the molecular mechanisms by which amino acids modulate defense responses remain unclear. In this study, we identify a novel function for serine as a defense-priming signal. Serine pretreatment enhances immune gene expression and primes plants for a more rapid and robust response to pathogen infection, resulting in a significant delay in programmed cell death (PCD) during effector-triggered immunity (ETI). We further demonstrate that serine-induced defense activation is mediated by glutamate receptor-like calcium channel 3.4 (GLR3.4), which subsequently activates calcium-dependent protein kinase 5 (CPK5). CPK5 in turn phosphorylates WRKY transcription factors, including WRKY33, to induce key immune genes. Our findings uncover a previously unrecognized serine-initiated signaling pathway that primes plant defense, highlighting both its mechanistic novelty and its potential application in sustainable agriculture. Given that serine is a naturally occurring metabolite, its exogenous application--or the use of structurally similar analogs--may offer a cost-effective, environmentally friendly, and non-genetic strategy to enhance disease resistance in crops.

plant biology↗

bioRxiv2024

iSeqsSearch: Incremental Protein Search for iBlast/iMMSeqs2/iDiamond

BackgroundThe advancement of sequencing technology has led to a rapid increase in the amount of DNA and protein sequence data; consequently, the size of genomic and proteomic databases is constantly growing. As a result, database searches need to be continually updated to account for the new data being added. Continually re-searching the entire existing dataset, however, wastes resources. Incremental database search can address this problem. MethodsOne recently introduced incremental search method is iBlast, which wraps the BLAST sequence search method with an algorithm to reuse previously processed data and thereby increase search efficiency. The iBlast wrapper, however, must be generalized to support more performant DNA/protein sequence search methods that have been developed, namely MMseqs2 and Diamond. Moreover, the previously published iBlast wrapper has to be revised to be more robust and usable by the general community. ResultsiMMseqs2 and iDiamond, which apply the incremental approach, obtain results nearly identical to those achieved using only MMseqs2 and Diamond. Notably, when comparing ranking comparison methods such as the Pearson correlation, we observe a high concordance of over 0.9, indicating similar results. Moreover, in some cases, our incremental approach applying iBlast merge function and using m8 formats including the new m8e format provides more hits compared to the conventional MMseqs2 and Diamond. ConclusionThe incremental approach using iMMseqs2 and iDiamond demonstrates efficiency in terms of reusing previously processed data while maintaining high accuracy and concordance in search results. This method can reduce resource waste in continually growing genomic and proteomic database searches. The sample codes are made available at GitHub: https://github.com/EESI/Incremental-Protein-Search.

bioinformatics↗

bioRxiv2024

Scorpio : Enhancing Embeddings to Improve Downstream Analysis of DNA sequences

Analysis of genomic and metagenomic sequences is inherently more challenging than that of amino acid sequences due to the higher divergence among evolutionarily related nucleotide sequences, variable k-mer and codon usage within and among genomes of diverse species, and poorly understood selective constraints. We introduce Scorpio, a versatile framework designed for nucleotide sequences that employs contrastive learning to improve embeddings. By leveraging pre-trained genomic language models and k-mer frequency embeddings, Scorpio demonstrates competitive performance in diverse applications, including taxonomic and gene classification, antimicrobial resistance (AMR) gene identification, and promoter detection. A key strength of Scorpio is its ability to generalize to novel DNA sequences and taxa, addressing a significant limitation of alignment-based methods. Scorpio has been tested on multiple datasets with DNA sequences of varying lengths (long and short) and shows robust inference capabilities. Additionally, we provide an analysis of the biological information underlying this representation, including correlations between codon adaptation index as a gene expression factor, sequence similarity, and taxonomy, as well as the functional and structural information of genes.

genomics↗

bioRxiv2024

Infant vocal category exploration as a foundation for speech development

Non-random exploration of infant speech-like vocalizations (e.g., squeals, growls, and vowel- like sounds or "vocants") is pivotal in speech development. This type of vocal exploration, often noticed when infants produce particular vocal types in clusters, serves two crucial purposes: it establishes a foundation for speech because speech requires formation of new vocal categories, and it serves as a basis for vocal signaling of wellness and interaction with caregivers. Despite the significance of clustering, existing research has largely relied on subjective descriptions and anecdotal observations regarding early vocal category formation. In this study, we aim to address this gap by presenting the first large-scale empirical evidence of vocal category exploration and clustering throughout the first year of life. We observed infant vocalizations longitudinally using all-day home recordings from 130 typically developing infants across the entire first year of life. To identify clustering patterns, we conducted Fishers exact tests to compare the occurrence of squeals versus vocants, as well as growls versus vocants. We found that across the first year, infants demonstrated clear clustering patterns of squeals and growls, indicating that these categories were not randomly produced, but rather, it seemed, infants actively engaged in practice of these specific categories. The findings lend support to the concept of infants as manifesting active vocal exploration and category formation, a key foundation for vocal language.

developmental biology↗