Biology subjects

Kim, J.-H.

Publications and source records attributed to Kim, J.-H..

At least 19 recordsLinked to original sources

bioRxiv2026

Microstructural heterogeneity of white-matter aging and its age-dependent coupling to cognition

Brain white matter (WM) microstructure undergoes extensive changes with age, yet the regional and cellular heterogeneity of age-related WM alterations and their impact on cognition remain unclear. Leveraging Neurite Orientation Dispersion and Density Imaging (NODDI), an advanced microstructural modelling to capture specific WM cellular properties, we investigated age-dependent relationships between advanced microstructural markers and cognitive performance, indexed by six cognitive domains derived from principal component analysis. Using a suite of standard diffusion tensor imaging (DTI) and NODDI techniques in eighty-six cognitively normal adults (Young: n=33, Older: n=53), we show that age group differences are widespread across whole brain white matter, with converging region-based and voxel-level evidence implicating commissural, association, and limbic pathways. Older adults exhibited significant and widespread reductions in global fractional anisotropy (FA) and neurite density index (NDI), concomitant with increases in mean diffusivity (MD), orientation density index (ODI), and free water fraction (FWF). Critically, age moderated WM-cognition associations in a domain- and tract-specific manner: younger adults exhibited stronger coupling between commissural and association tract microstructure and language and visual memory, whereas older adults showed greater dependence on projection and limbic tracts for executive and language function. The observed age-dependent coupling between specific microstructural metrics and cognition underscores the value of advanced diffusion models for capturing heterogeneity in brain aging, reveals age-specific biomarkers of cognitive health. These patterns align with phylogenetic and ontogenetic patterns of white matter vulnerability in callosal, long-range association, and limbic pathways, and suggest cellular specificity in white matter changes associated with cognitive decline.

neuroscience↗

bioRxiv2026

Intermediate phenotypic heterogeneity creates an optimal coexistence window in bacteria-phage communities

Phenotypic heterogeneity can expand ecological niche space even within a genetically homogeneous population. Recent experiments showed that growth-rate heterogeneity in a clonal bacterial host can stabilize coexistence among multiple phages. Yet this discovery leaves unresolved whether increasing host heterogeneity monotonically promotes coexistence. Here we show that it does not. Using a trait-based bacteria--phage coexistence framework, we find that phage richness is maximized at an intermediate scale of host growth-rate heterogeneity, determined by the match between host phenotypic dispersion and phage niche width. Our results show that optimal phage diversity emerges from an ecological trade-off between two competing effects: increasing phenotypic heterogeneity enables niche differentiation but eventually reduces the host abundance in the preferred niche of each phage. Therefore, our findings predict that experimentally increasing host growth-rate variance at a fixed mean growth rate should produce a nonmonotonic phage richness response, providing a quantitative principle for how intraspecific phenotypic variation shapes biodiversity in microbial ecosystems.

ecology↗

bioRxiv2026

Fundamentals on the Kinetic and Thermodynamic Analysis of Oligonucleotide DNA Hybridization by Surface Plasmon Resonance: A Guide for HIF1α Antisense Design.

Antisense oligonucleotides (ASO) are nucleotide polymers that hybridize to sense strands and have been successful in treating a variety of diseases. A wide range of strategies have been investigated to optimize and develop ASO for clinical studies. A key objective for this study was to provide an overview of the range of detailed data that get be obtained and provide an updated method review on how to design surface plasmon resonance (SPR) kinetic experiments for DNA oligonucleotide hybridization studies that can also be applied to other ASO including peptide nucleic acids (PNA). We describe many lessons learned from published literature and provide a state-of-the-art strategy and methods for generating not only kinetic but also thermodynamic characterizations of oligonucleotide hybridization. In this study we have performed an SPR kinetic and thermodynamic analysis for the hybridization of HIF1 antisense DNA strands to its immobilized Intron2-Exon3 splice site sense DNA strand to provide insight, in general, on the optimal length and insight into optimal design of DNA ASOs. We provide a process on how to design experiments to: 1.) obtain oligonucleotide-length dependent kinetics, 2.) analyze reactions to obtain association and dissociation rate kinetics (ka, kd), assess if hybridization follows a 2-state model and to obtain kinetic dissociation constants (Kd), 3.) perform temperature-dependent hybridization kinetics to obtain thermodynamic values ({Delta}H{degrees}, {Delta}S{degrees} and {Delta}G{degrees}) that can give insight into the molecular interactions driving hybridization, 4.) compare experimental thermodynamic values to values derived from nearest-neighbor prediction models to identify atypical reactions and importantly 5.) enable calculations to predict oligomer hybridization affinity at the physiological 37 {degrees}C temperature to asses if the design of the oligomer will have the required cellular activity for a therapeutic effect. The strategy and results presented throughout the paper are compared to previous SPR reports and suggestions made to optimize kinetic studies.

biochemistry↗

bioRxiv2026

AI-Driven Design of Nanobinders Targeting the TSLPR Heterodimer Interface to Suppress Type 2 Inflammatory Signaling

Aberrant thymic stromal lymphopoietin (TSLP) signaling is a central driver of type 2 inflammatory diseases, yet the only approved TSLP-targeted therapy is a 150 kDa monoclonal antibody whose bulky format limits tissue penetration and precludes inhaled delivery. Here, we report an AI-driven framework for designing ultra-compact de novo nanobinders that suppress TSLP signaling by sterically disrupting assembly of the TSLPR-IL-7R heterodimer. We compare two structure-guided strategies, namely purely de novo helical bundle generation and interface-mimetic grafting of native binding motifs onto designed scaffolds. Although both yield nanomolar binders, only orthosteric mimicry of the native cytokine geometry blocks receptor heterodimerization, showing that functional antagonism is governed by precise epitope geometry rather than affinity alone. After library-based maturation, the lead nanobinder TRB5.1 is a hyper-stable monomer (Tm [~]97.4 {degrees}C) with single-digit nanomolar affinity (KD = 9.7 nM) and strict selectivity over related -chain interleukin receptors. TRB5.1 suppresses TSLP-induced JAK1 and STAT5 phosphorylation across multiple cellular models and drives a transcriptome-wide reversal of the pathogenic type 2 program. This work delivers a developable, potentially inhalable non-antibody lead and a scalable blueprint for antagonizing heterodimeric cytokine receptors.

biochemistry↗

bioRxiv2026

The Intrinsic Manifold of Spontaneous Activity Constrains Cortical Responses to Naturalistic Stimuli

The cerebral cortex constrains its spontaneous activity to a low-dimensional manifold learnable from resting state functional magnetic resonance imaging (fMRI) data. However, it remains unclear whether this intrinsic manifold also captures cortical responses to complex, naturalistic stimuli. To test this, we pretrained a deep variational autoencoder model on 3-Tesla resting-state fMRI data to learn the latent structure of spontaneous activity, and then applied this model without finetuning to 7-Tesla fMRI data acquired during movie-watching. Despite the different field strengths, the model generalized robustly from resting to movie-watching states. The latent representation of stimulus-evoked responses was confined to a subspace that occupied about 13% of the latent space spanned by spontaneous activity, demonstrating that task-related neural responses do not require a distinct representational space. By representing cortical dynamics as an evolving latent trajectory, we found striking differences across individuals or between brain states. During movie watching, the velocity of the latent trajectory provided a reliable marker of cortical engagement, and its temporal structure was highly reliable and sensitive to naturalistic events. These findings suggest that the intrinsic manifold of spontaneous activity forms a full reservoir of cortical states that the brain can differentially engage when interacting with the external environment.

neuroscience↗

bioRxiv2026

Cellular Chemical Dynamics Governing Signal Transduction and Adaptive Gene Expression: Beyond Classical Kinetics

Cellular adaptation is inherently nonstationary processes with complex stochastic dynamics1-5. Despite remarkable progress in quantitative biology6-11, a quantitative understanding of the cell adaptation dynamics in terms of the underlying cellular network remains elusive. Here, we present the next-generation chemical dynamics model and theory for cellular networks, providing an effective, quantitative description of the adaptive gene expression dynamics in living cells responding to external stimuli. Unlike conventional kinetics, chemical dynamics of cellular network modules are characterized by their reaction-time distributions, rather than by rate coefficients12. For a general model of cell signal transduction and adaptive gene expression, we derive exact analytical expressions for the time-dependent mean and variance of protein numbers produced in response to external stimuli, validated by accurate stochastic simulations. These results provide a unified, quantitative explanation of the stochastic responses of diverse E. coli genes to antibiotic stress and transcriptional induction. Our analysis reveals existence of a general quadratic relationship between the mean and variance of activation times across diverse genes. The gene activation process influences transient dynamics of downstream protein levels, but not their steady-state levels. In contrast, post-translational maturation process affects both transient dynamics and steady-state variability of mature protein levels. This finding indicates that the gene expression variability measured by fluorescent reporter proteins depends on the maturation time of the reporters. This work suggests a new direction for the development of digital twins of living cells.

biophysics↗

bioRxiv2026

Symmetric Fusion of fMRI and EEG for Spectrally Resolved Functional Neuroimaging

Simultaneous electroencephalography (EEG) and functional MRI (fMRI) offers complementary sensitivity to fast electrophysiological dynamics of EEG and spatially resolved hemodynamics of fMRI, yet previous joint-analysis approaches are confined to fixed task paradigms and struggle with continuous or naturalistic brain states. We FSINC (Fusing Source Imaging based on a Neurovascular Coupling) model, a unified EEG-fMRI source imaging framework that reconstructs cortical activity to simultaneously explain both modalities. FSINC integrates frequency-resolved EEG source activity with fMRI via a data-driven neurovascular coupling model that estimates band-specific coupling coefficients ({beta}) and accommodates a tunable spatial-temporal trade-off through hyperparameters ({lambda}2,{lambda} 3). In realistic simulations, FSINC outperformed conventional methods (wMNE, LORETA) in both spatial and temporal accuracy across EEG SNRs (-10 to 10dB) and numbers of concurrent sources (up to five), with optimal performance at{lambda} 2 = 102 and{lambda} 3=1 (e.g., LE: 0.51{+/-}0.24mm; SDI: 0.03{+/-}0.37mm; temporal accuracy: 0.95 {+/-} 0.05). Applied to simultaneous EEG-fMRI during contrast-reversing visual stimulation (=5.95Hz), FSINC revealed stimulus-locked responses localized to early visual cortex and stimulus-induced modulation of intrinsic alpha oscillations extending into visual and attention networks, patterns that conventional methods failed to capture. Estimated {beta}-weights were broadly consistent with prior reports of negative (theta/alpha) and positive (gamma) BOLD-electrophysiology associations. These findings demonstrate that FSINC enables high-spatiotemporal-resolution source imaging from EEG-fMRI recordings via data-driven hemodynamic modelling, and is expected to be well-suited for continuous and naturalistic brain states (e.g., resting state, natural moving-watching, and narrative listening) that are difficult to interrogate with either modality alone.

neuroscience↗

bioRxiv2025

FAM84B facilitates tau propagation via RYR3-mediated exocytosis in response to neuroinflammation

The increasing prevalence of dementia underscores the pressing need for effective therapeutic interventions. Despite extensive research into A{beta}, the limited efficacy of existing treatment modalities necessitates a paradigm shift toward tau pathology including tau propagation to slow dementia progression. Here, we identified a novel protein, FAM84B (also known as LRATD2), involved in tau propagation. Elevated FAM84B levels were detected in the postmortem cortex, cerebrospinal fluid, and induced pluripotent stem cell-derived cortical neurons of patients with tauopathy. FAM84B facilitates tau secretion through exosome assembly and RYR3-mediated exocytosis, followed by exosomal uptake into neighboring cells via clathrin-mediated endocytosis, thereby driving tau propagation. We confirmed that neuroinflammation induced by heightened STAT3 activity and cytokine treatment upregulated FAM84B expression, stimulating tau propagation, as evidenced by reduced propagation upon RYR3 inhibition. These findings provide invaluable insights into potential avenues for targeting tau propagation to ameliorate disease progression in tauopathies.

neuroscience↗

bioRxiv2025

Multilevel Regulation of Skeletal Muscle Ferroptosis in Aging: Sex- and Exercise-Dependent Effects on Histological, Molecular, and Genetic Markers

BackgroundFerroptosis, an iron-dependent form of regulated cell death, is increasingly recognized as a key contributor to aging-associated skeletal muscle degeneration and dysfunction. However, the interactive effects of aging, sex, and exercise modality on ferroptosis regulatory markers at the histological, protein, and gene expression levels remain poorly understood. MethodsMale (n = 23) and female (n = 23) mice aged 7 (young) and 17 (aged) months were assigned to sedentary control, voluntary wheel running, or forced treadmill exercise. Ferroptosis in the quadriceps muscle was assessed using histological markers (e.g., fibrosis, Fe3 accumulation, 4-HNE, MDA), protein-level markers (e.g., GPX4, SLC7A11, p-AMPK, MDA, GSH/GSSG), and gene expression markers (e.g., SLC7A11, GSS, ACSL4, POR). ResultsAging significantly elevated histological indicators of ferroptosis--fibrosis, lipid peroxidation, and iron overload--regardless of sex. At the protein and gene levels, sex-dependent differences were evident: aged females exhibited lower MDA and GSSG levels and upregulation of antioxidant-related genes, compared with aged males. Both exercise interventions modulated ferroptosis markers, with forced exercise exerting more pronounced effects than voluntary exercise. Notably, aged females demonstrated the most substantial reductions in ferroptosis-related markers in response to forced exercise, indicating a significant sex-by-exercise interaction. ConclusionAging markedly increases ferroptosis-related changes in skeletal muscle, with partial sex-specific differences at the molecular level. Forced exercise provides more robust regulatory effect against ferroptosis than voluntary exercise, especially in aged females. These findings underscore the therapeutic potential of sex-specific, targeted exercise interventions for mitigating ferroptosis-mediated muscle deterioration during aging.

physiology↗

bioRxiv2025

Telomere-to-Telomere Accurate and Gapless Korean Standard Reference Genome

We present KOREF1-G-TTAGGA, the first Telomere-to-Telomere Accurate and Gapless Genome Assembly, standing as the Korean standard reference genome. The paternal and maternal haplotypes spanned 2.91 and 3.03 Gb. Genome-wide, at least 99.15% of assembled sequences were reliably haplotype-resolved, and over 95% remained accurate even in the most error-prone loci, including centromeric satellite arrays and segmental duplications. Rare-k-mer copy-number concordance within satellite arrays held up 98.9% and 98.8% per haplotype. Bionano optical maps fully spanned all canonical rDNA arrays on the five acrocentric chromosomes. The assembly quality index (AQI) of 99.77 and 99.69 exceeded the reference-quality threshold of 90, and more than 99.99% of gene and cCRE sequence was free of structural error. Both haplotypes further showed high base-level accuracy, with consensus quality value (QV) of 81.19 and 79.03, corresponding to one error per 131 and 80 Mb. KOREF1-G-TTAGGA is among the highest-quality East Asian telomere-to-telomere assemblies. It moreover anchors a decade-spanning multi-ome reference dataset for defining individual molecular states. Together, these resources define the personal referenceome as a foundation for individual biology and precision medicine, with the assemblies, annotations, and all multi-omic data openly available at https://koreanreference.org.

genomics↗

bioRxiv2025

10,239 whole genomes with multiomic and clinical health information as the Korean population multiomic reference dataset

We present Korea10K, the largest genomic dataset of the Korean population, comprising 10,239 high-coverage whole genomes (mean depth 30x) with matched multiomic profiles and phenotype data. Korea10K achieves complete and near-complete discovery of very rare and ultra-rare alleles, respectively, at 9,000 Korean genomes. This dataset provides the high-quality population-specific imputation panel, enabling accurate inference of low-frequency variants. Admixture analyses confirm the genetic homogeneity of the Korean population, despite its diverse Y-chromosomal, mitochondrial, and HLA repertoires. This pattern reflects a long and continuous lineage history characterized by persistent internal admixture and genomic homogenization over thousands of years on the Korean peninsula. We also identified 16.8 million genomic variants that directly modify CG sites by creating or abolishing CG dinucleotides, providing the population-scale evidence of coordinated genomic-epigenomic regulatory mechanism in Koreans.

genomics↗

bioRxiv2025

Biomarker Discovery via Integrative Multi-omics for Children exposed to Humidifier Disinfectant

RationaleExposure to humidifier disinfectants has been linked to an array of pulmonary disorders and diminished lung functionality particularly reduced Forced Vital Capacity (FVC). ObjectivesThis investigation sought to identify diagnostic biomarkers for early detection of children at elevated risk of developing chronic respiratory conditions following such exposure. MethodsOur research employed a comprehensive multi-omics strategy analyzing 70 pediatric patients alongside 10 controls, seamlessly integrating clinical assessments with transcriptomics, methylomics, proteomics, and metabolomics data. The analytical framework utilized a sophisticated combination of Non-negative Matrix Factorization (NMF), Multi-Omics Factor Analysis (MOFA), and advanced machine learning algorithms. Measurements and Main ResultsNMF clustering uncovered distinctive protein expression patterns associated with integrin-mediated signaling pathways and immune response mechanisms. Complementarily, MOFA identified latent factors correlating with lung function metrics, highlighting critical molecular pathways involved in integrin cell surface interactions and lipid metabolism regulation. Machine learning-based analysis facilitated the development of a multi-marker panel-comprising IGHV2-70, LysoPC (16:0), and hexadecyl ferulate-which achieved 81.46% accuracy in identifying pulmonary dysfunction cohort. ConclusionsThese findings suggest that alterations in integrin-related signaling networks and dysregulation of lipid metabolism play pivotal roles in mediating the long-term pulmonary consequences of humidifier disinfectant exposure. The proposed multi-marker panel offers significant potential for enhanced risk stratification and timely therapeutic intervention. At a Glance CommentaryO_ST_ABSScientific Knowledge on the SubjectC_ST_ABSExtensive epidemiological evidence has established the causal relationship between humidifier disinfectant exposure and pulmonary dysfunction; however, clinically validated biomarkers for predicting chronic lung disease progression remain limited. Pediatric populations demonstrate unique pathophysiological mechanisms distinct from adults, highlighting the critical necessity for biomarker identification grounded in comprehensive molecular understanding. Despite advances in omics technologies, recent investigations have encountered significant obstacles in achieving deeper mechanistic insights, predominantly attributable to methodological constraints in harmonizing clinical phenotypes with high-dimensional molecular datasets. What This Study Adds to the FieldThis investigation elucidates the fundamental contributions of integrin-mediated signaling cascades and lipid metabolic networks to persistent pulmonary dysfunction following humidifier disinfectant exposure. Our analyses revealed coordinated regulation of integrin signaling pathways and immune response networks through NMF clustering, indicating dynamic temporal evolution of inflammatory responses during chronic disease progression, with temporally distinct molecular signatures identified across discrete observation intervals. Multi-omics factor analysis (MOFA) corroborated integrin pathway dysregulation while additionally uncovering systematic suppression of lipid metabolic processes. Furthermore, machine learning algorithms enabled development of a robust three-component biomarker panel--encompassing IGHV2-70, LysoPC (16:0), and hexadecyl ferulate--demonstrating 81.46% classification accuracy for pulmonary dysfunction phenotypes. Collectively, these findings substantially advance mechanistic understanding of chronic lung injury in vulnerable pediatric cohorts and identify clinically relevant biomarkers with translational potential for risk stratification and therapeutic targeting in clinical practice.

systems biology↗

bioRxiv2025

Rejuvenation-Responsive and Senolytic-Sensitive Muscle Stem Cells Unveiled by CD200 and CD63 in Geriatric Muscle

Muscle stem cells (MuSCs) are parenchymal cells in skeletal muscle regeneration and maintenance. With aging, MuSCs experience a decline in their regenerative function and reduction in their number. However, recent evidence points to substantial heterogeneity within the aged MuSC population, raising questions about the underlying mechanisms of age-associated dysfunction. Here, we used Pax7CreERT2;RosaYFP mice (MuSCYFP) to label Pax7-expressing MuSCs and chronologically traced MuSCs until geriatric age. Genetic labeling and chronological tracing revealed that the number of YFP+ MuSC remained comparable between young, middle and geriatric ages. At geriatric age, YFP+ MuSCs exhibited reduced expression of traditional MuSC markers such as VCAM1 and PAX7. A previously unrecognized subpopulation emerged, characterized by loss of VCAM1 and low or absent PAX7. Despite their altered marker profile, these cells retained transcriptional signatures of quiescence and myogenic potential, but displayed significantly reduced proliferative and regenerative capacities. They displayed gene expression patterns indicative of senescence-like state and were selectively ablated by senolytic treatment. DHT restored regenerative function in aged mice and re-induced VCAM1 expression in YFP+/Pax7-/low/VCAM1- cells, indicating responsiveness to rejuvenation. Based on their emergence with aging, functional impairment and responsiveness to rejuvenation, we termed this population GERI-MuSCs (Geriatric Emerging Rejuvenation-responsive and Impaired MuSCs). CD63 and CD200 were identified as novel surface markers that together with VCAM1, reliably detect GERI-MuSCs as well as classical Pax7+/VCAM1High MuSCs, providing a tool for comprehensive isolation of MuSCs from aged wild-type mice. Together, our findings provide a refined framework for studying MuSC aging and offer new tools for isolating functionally distinct MuSC subsets from aged skeletal muscle.

developmental biology↗

bioRxiv2025

Influenza A Virus infection is associated with TDP-43 pathology and neuronal damage in the brain

Viral pandemics such as COVID-19 have demonstrated long-term neurological consequences, including memory impairment and depression, emphasizing the importance of understanding virus-brain interactions [1]. Similar concerns have been raised for Influenza A virus (IAV), which has been implicated in neurodegenerative disorders [2, 3]. In this study, we investigated the neuropathological effects of highly pathogenic avian influenza (HPAI) H5N1 and H5N8 strains in a mouse model. Although viral RNA was detected in the brain post-infection, no viral proteins were found, suggesting limited or transient brain replication. Despite this, infected brains showed significant neuronal damage, including axonal loss and nuclear condensation, as evidenced by immunofluorescence and Nissl staining. We also observed pathological changes in TDP-43, including conformational alterations and increased phosphorylation, which required antigen retrieval for detection--features reminiscent of those found in frontotemporal dementia and amyotrophic lateral sclerosis [4, 5]. Transcriptomic analysis further revealed strain-specific host responses, including activation of interferon-related genes and downregulation of microtubule-associated pathways. These findings suggest that IAV infection can trigger hallmarks of neurodegeneration in the absence of persistent viral protein expression, possibly through host-driven mechanisms. Our results underscore the need for further investigation into virus-induced molecular pathways contributing to neurodegenerative disease.

neuroscience↗

bioRxiv2025

Phytoplankton recruitment of specific microbial assemblages and phylosymbiotic patterns

Phytoplankton and bacteria represent two major pillars of the carbon cycle in marine ecosystems. While their interactions are known to be tightly linked, the specific mechanisms underlying these interactions remain largely unexplored. Evidence of host-specific microbial assemblages could serve as a foundation for studies of detailed host-microbe interactions, yet such research remains limited in phytoplankton. Here, we not only investigate the microbial assemblages of six phytoplankton species, including multiple strains of dinoflagellates and diatoms, but also samples of phytoplankton blooms from the field. Our results reveal the presence of host-specific microbial assemblages in phytoplankton, with members of the core microbial lineages (MCGs) playing pivotal roles in shaping host-specific microbial assemblages and contributing to network structures. Deterministic processes, particularly host genotypes, were the dominant factors shaping microbial assemblages, overriding environmental influences. Consequently, microbial composition reflected the evolutionary relationships of the host species, demonstrating phylosymbiotic patterns. These findings suggest that studying MCGs will be a crucial foundation for investigating specific phytoplankton-microbe interactions and highlight the ecological and evolutionary importance of host-microbial specificity in phytoplankton.

ecology↗

bioRxiv2025

Deep-learning based Embedding of Functional Connectivity Profiles for Precision Functional Mapping

Spatial correlation of functional connectivity profiles across matching anatomical locations in individuals is often calculated to delineate individual differences in functional networks. Likewise, spatial correlation is assessed across average functional connectivity profiles of groups to evaluate the maturity of functional networks during development. Despite its widespread use, spatial correlation is limited to comparing two samples at a time. In this study, we employed a variational autoencoder to embed functional connectivity profiles from various anatomical locations, individuals, and group averages for simultaneous comparison. We demonstrate that our variational autoencoder, with pre-trained weights, can project new functional connectivity profiles from the vertex space to a latent space with as few as two dimensions, yet still retain meaningful global and local structures in the data. Functional connectivity profiles from various functional networks occupy distinct compartments of the latent space. Moreover, the variability of functional connectivity profiles from the same anatomical location is readily captured in the latent space. We believe that this approach could be useful for visualization and exploratory analyses in precision functional mapping.

neuroscience↗

bioRxiv2024

Genetically Labeled Premyelinating Oligodendrocytes: Bridging Oligodendrogenesis and Neuronal Activity

To myelinate axons, oligodendrocyte precursor cells (OPCs) must stop dividing and differentiate into premyelinating oligodendrocytes (preOLs). PreOLs are thought to survey and begin ensheathing nearby axons, and their maturation is often stalled at human demyelinating lesions. Lack of genetic tools to visualize and manipulate preOLs has left this critical differentiation stage woefully understudied. Here, we generated a knock-in mouse line that specifically labels preOLs across the central nervous system. Genetically labeled preOLs exhibit distinct morphology, unique transcriptomic and electrophysiological features, and do not overlap with OPCs. PreOL lineage tracing revealed that subsets of them undergo prolonged maturation and that different brain regions initiate oligodendrogenesis with the spatiotemporal specificity. Lastly, by fate mapping preOLs under sensory deprivation, we find that neuronal activity functions within a narrow time window of preOL maturation to promote their survival and successful integration. Our work provides a new tool to probe this critical cell stage during axon ensheathment, allowing for fine dissection of axon-oligodendrocyte interactions.

neuroscience↗

bioRxiv2024

APOBEC3A, not APOBEC3B, drives deaminase mutagenesis in human gastric epithelium

Cancer genomes frequently carry APOBEC (apolipoprotein B mRNA editing catalytic polypeptide-like)-associated DNA mutations, suggesting APOBEC enzymes as innate mutagens during cancer initiation and evolution. However, the pure mutagenic impacts of the specific enzymes among this family that are responsible for APOBEC-associated mutagenesis remain unclear in human normal cell lineage, particularly the comparative mutagenic activities of APOBEC3A and APOBEC3B. Here, we investigated the mutagenic contributions of these enzymes through whole-genome sequencing of human normal gastric organoid lines carrying doxycycline-inducible APOBEC3A or APOBEC3B cassettes. Our findings demonstrated that transcriptional APOBEC3A upregulation led to the acquisition of a massive number of genomic mutations in a few cell cycles. By contrast, APOBEC3B upregulation did not generate a substantial number of mutations in gastric epithelium. APOBEC3B-associated mutagenesis remained insignificant even after a combined inactivation of TP53. Based on the spectrum of acquired mutations after APOBEC3A upregulation, we further analyzed APOBEC3A-associated mutational signatures, encompassing indels mainly composed of 1bp deletions, characteristics of clustered mutations, and selective pressures operative on cells carrying the mutations. Our observations provide a clear foundation for understanding the mutational impact of APOBEC enzymes in human cells.

genomics↗