Biology subjects

Kim, R.

Publications and source records attributed to Kim, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Selectivity and dynamics of VAP family tether exchange across membrane contact sites

To integrate diverse cellular function and coordinate homeostasis, the endoplasmic reticulum (ER) communicates with all other intracellular compartments through physical interfaces termed membrane contact sites (MCSs). Given the sheer diversity of possible MCS pairings, how the ER discriminates between simultaneously available binding partners remains unclear. To explore this, we performed comparative endogenous contact site mapping for three closely related VAP family tethers and uncovered a unique set of FFAT motif selectivity and MCS footprints for each: VAPA at mitochondria and TGN, VAPB at mitochondria and peroxisomes, and MOSPD2 at mature endosomes, lysosomes and lipid droplets. In line with their MCS selectivity profiles, co-depletion of VAPA and VAPB, but not MOSPD2, caused systemic breakdown in mitochondrial integrity, while silencing of MOSPD2 alone was sufficient to disrupt the organization and transport of (endo)lysosomes. Unexpectedly, coincident loss of VAPA and VAPB instigated ER contact site rewiring by redirecting endogenous MOSPD2 to the collapsing mitochondrial network. Our findings define hierarchies of ER contact site formation and reveal compensation mechanisms exploited by cells to safeguard organelle homeostasis and crosstalk.

cell biology↗

bioRxiv2026

Hyperalignment Reveals Shared Information in Macaques' Idiosyncratic Fine-Grained Movie fMRI Patterns

Response hyperalignment (RHA) of fMRI patterns acquired during movie-viewing in 12 rhesus monkeys revealed shared representational spaces despite idiosyncratic functional topographies. RHA greatly improved inter-subject correlation of movie response time-series in occipital, temporal, and prefrontal cortices and afforded highly accurate between-subject decoding of movie time-points and estimation of idiosyncratic functional topographies. These results demonstrate that nonhuman primates share high-dimensional, high-capacity representational spaces encoded in idiosyncratic fine-grained functional topographies.

neuroscience↗

bioRxiv2026

Prenatal Alcohol Exposure Disrupts γ-Secretase Activity and Impairs Learning and Memory in Wild-Type and 3xTg-AD Mice

Although prenatal alcohol exposure (PAE) has been proposed as an early-life risk factor for Alzheimers disease and related dementias (AD/ADRD), the mechanistic underpinnings are underexplored. Mutations in the Presenilin genes contribute to AD/ADRD, with Presenilin 1 acting as the catalytic subunit of the {gamma}-secretase complex responsible for cleaving Notch and amyloid precursor protein (APP). We hypothesized that PAE disrupts {gamma}-secretase activity during brain development, which persists and is associated with behavioral deficits later in life. Pregnant wild-type B6129 and 3xTg-AD mice were fed an ethanol-containing liquid diet during gestational days 13-15. From birth to adulthood, PAE increased APP C-terminal fragments and Notch intracellular domain (NICD) levels in cortical lysates. These changes were associated with impaired hippocampal-dependent learning and memory in wild-type mice at 3 and 6 months of age and exacerbated behavioral deficits in 4-month-old 3xTg-AD mice. Our findings provide the first mechanistic insight linking PAE to AD/ADRD vulnerability.

neuroscience↗

bioRxiv2026

Learning induces activation-mechanism--dependent neural plasticity in an intracortical microstimulation task

Electrical microstimulation provides high-resolution control of neural circuits for causal studies and restoration of impaired functions, yet how responses to artificial activation evolve with learning remains unclear. Here, we deploy a detection task and pair ultraflexible electrodes for stable intracortical microstimulation (ICMS) with longitudinal imaging and recordings to track single-cell and population responses across weeks of learning. Detection thresholds decreased with learning, indicating plasticity. Chronic imaging showed that stimulus-evoked recruitment expanded at a fixed current, while a consistent number of neurons continued to underlie behavioral responses. A subset of learning-sensitive cells enhanced modulation and reduced latency. Electrophysiological recordings further distinguished two forms of adaptation: directly activated, pulse-locked neurons strengthened their excitability, whereas polysynaptically recruited neurons expanded in number and were predictive of behavioral outcomes. These results show that learning in an ICMS task reshapes cortical circuits through activation-mechanism-dependent plasticity, underscoring the need for stimulation paradigms that adapt to both cell-intrinsic and network dynamics. One-sentence summaryLearning alters neural responses to ICMS, revealing differences between direct activation and network activity linked to behavior.

neuroscience↗

bioRxiv2026

Accurate estimation of canine inbreeding using ultra low-coverage whole genomesequencing

The measurement of inbreeding has gained significance across diverse fields, including population and conservation genetics, agricultural genetics, breeding programs for animals and plants, and wildlife management. This is due to the fact that inbreeding leads to increased homozygosity and results in lower genetic diversity, rendering populations more vulnerable to environmental changes, diseases, and other stressors. High or mid-coverage whole genome sequencing (WGS) has been widely used for inbreeding estimation, but it is resource-intensive. We aimed to investigate the use of ultra low-coverage whole genome sequencing (ulcWGS) as a cost-effective alternative for inbreeding analysis. Domestic dogs were used for our study as their extensive breeding histories lead to populations with a wide range of inbreeding levels. We constructed a multi-breed reference panel from high-coverage WGS samples. Inbreeding in independent ulcWGS samples was then estimated using runs of homozygosity (RoH) and inbreeding coefficients (F). We modeled the relationship between these measures and sequencing depth using nonlinear regression, to generate inbreeding estimates relative to sequencing depth. Resulting relative RoH and F measurements were significantly correlated, with purebred dogs exhibiting more runs of homozygosity and higher inbreeding coefficients compared to mixed-breed dogs. Our findings demonstrate that ulcWGS can provide reliable and economical estimations of inbreeding, expanding accessibility to genetic monitoring.

bioinformatics↗

bioRxiv2026

Rapid CRISPR-Cas9 Genome Editing in S. cerevisiae

This protocol enables rapid CRISPR-Cas9 genome editing in Saccharomyces cerevisiae by replacing restriction/ligation guide cloning with PCR-based protospacer installation and seamless plasmid recircularization. It describes in silico HDR donor and SgRNA design, install guide sequences into cas9 plasmid by PCR and seamless assembly, plasmid cloning and sequence verification in E. coli, and LiAc/PEG co-transformation of yeast with Cas9-sgRNA plasmid plus HDR donor. The workflow selects yeast colonies on G418 and confirms edits by PCR and sequencing.

cell biology↗

bioRxiv2026

Heterotrimeric G Protein and RasGAP Coupling Drives Adaptation During Chemotaxis

Chemotaxis enables eukaryotic cells to detect and migrate along extracellular chemoattractant gradients spanning several orders of magnitude. This remarkable dynamic range relies on adaptation, a process that allows cells to reset their signaling machinery while preserving sensitivity to incremental changes in stimulus intensity. Although numerous actin-dependent feedback mechanisms have been characterized, the molecular basis of adaptation within the actin-independent core gradient-sensing module remains poorly understood. Here we identify the Ras GTPase-activating protein C2GAP1 as a critical F-actin-independent effector of the heterotrimeric G protein G2 in Dictyostelium discoideum. Using cytoskeleton-free gradient-sensing cells, quantitative imaging, biochemical assays, FRET-based G-protein activation measurements, and structural modeling, we demonstrate that C2GAP1 controls concentration-dependent adaptation during gradient sensing. Mechanistically, C2GAP1 directly associates with G2 in both GDP- and GTP-bound states, with preferential binding to activated G2, thereby sustaining membrane recruitment and locally attenuating signaling. Loss of C2GAP1 enhances G-protein activation, disrupts front-specific inhibition, and impairs rapid reorientation in dynamic gradients. These findings define a direct coupling between heterotrimeric G proteins and a RasGAP as a core adaptive module that calibrates gradient sensing across wide concentration ranges. HighlightsChemotaxis, the directional migration of cells along chemoattractant gradients, underlies processes such as neuron patterning, lymphocyte recruitment, cancer metastasis, and Dictyostelium discoideum development. The hallmark of eukaryotic chemotaxis is the ability to sense and respond to gradients spanning wide concentration ranges through cellular adaptation. This process involves three interconnected modules: gradient sensing, cell polarity, and migration, with gradient sensing as the foundation. While many components of GPCR-mediated signaling are known, the molecular mechanisms driving adaptation remain unclear. Here, we show that the heterotrimeric G protein subunit interacts with RasGAP C2GAP1 to mediate adaptation during gradient sensing and chemotaxis.

cell biology↗

bioRxiv2026

Task goals reorganize visual codes in human ventral temporal cortex via medial frontal modulation

How sensory representations in the sensory cortex are dynamically and rapidly modulated to support flexible, goal-directed behavior remains a fundamental open question. Using rare simultaneous single-neuron recordings across multiple human brain regions, including the ventral temporal cortex (VTC), a high-level visual area not traditionally associated with context-dependent coding, we show that visual representations in VTC are rapidly reconfigured by the presence or absence of preceding verbal task instructions. Identical visual stimuli evoked distinct responses in VTC depending on whether task instructions were provided or not, with categorical representations sharpened when goals were specified in advance. In contrast, dorsal anterior cingulate cortex (dACC) and the hippocampus carried strong signals related to instruction timing, consistent with known regional specialization in top-down control. Coupling between dACC and VTC increased during periods of instructional uncertainty and high cognitive demand on a rapid timescale during stimulus presentation, and its strength predicted correct performance. Together, these findings uncover a rapid, online feedback mechanism through which the medial frontal cortex dynamically reorganizes sensory population codes in VTC, linking flexible cortical coordination to successful goal-directed computation.

neuroscience↗

bioRxiv2026

In vivo isogenic modelling unveils a TP53-mediated relapse phenotype in T-cell acute lymphoblastic leukemia

Many patients with T-cell acute lymphoblastic leukemia (T-ALL) relapse into a treatment-resistant disease. The mechanisms driving relapse remain largely elusive, in part due to the lack of faithful experimental models. Here, we leveraged patient-derived xenograft (PDX) pairs generated from diagnosis and relapse T-ALLs to functionally address the cellular mechanisms driving TP53-altered relapse. Beyond inter-T-ALL variability, comparative analyses revealed a unique, cell-intrinsic relapse phenotype that includes greater leukemia-initiating capacity and that can be conferred to diagnosis cells by TP53 silencing. Transcriptomic profiling linked the relapse phenotype to deregulated OXPHOS metabolism and MYC signaling. Integration of single-cell profilings uncovered TP53-wildtype cell populations at diagnosis expressing a relapse profile, possibly reflecting a pre-existing modulation of TP53 signaling. These cells sequentially evolved towards biallelic TP53 inactivation at relapse. Collectively, our findings support a model in which T-ALL relapses emerge from a selected pre-existing transcriptional state characterized by deregulated metabolism that favors subsequent TP53 inactivation.

cancer biology↗

bioRxiv2025

Template-based RNA structure prediction advanced through a blind code competition

Automatically predicting RNA 3D structure from sequence remains an unsolved challenge in biology and biotechnology. Here, we describe a Kaggle code competition engaging over 1700 teams and 43 previously unreleased structures to tackle this challenge. The top three submitted algorithms achieved scores within statistical error of the winners of the recent CASP16 competition. Unexpectedly, the top Kaggle strategy involved a pipeline for discovering 3D templates, without the use of deep learning. We integrated this template-modeling pipeline and other Kaggle strategies to develop a single model RNAPro that retrospectively outperformed individual Kaggle models on the same test set. These results suggest a growing importance of template-based modeling in RNA structure prediction.

biophysics↗

bioRxiv2025

A Biologically Grounded Structural Causal Model Enables cfRNA Specific In-Context Learning

Cell-free RNA (cfRNA) in human plasma provides a minimally invasive readout of tissue physiology, yet its extreme sparsity, heavy-tailed abundance distributions, and weak but structured correlation patterns create major challenges for machine learning. Conventional tabular foundation models are typically trained on synthetic datasets that assume generic statistical properties, and as a result, they fail to capture the distinctive characteristics of cfRNA. These limitations become even more pronounced in settings where labeled data are scarce. We introduce cfRNA-ICL, a cfRNA-specific in-context learning model trained entirely on tasks generated from a biologically grounded structural causal model (SCM). The SCM produces realistic cfRNA-like scenarios by incorporating empirical measurements of gene-level dropout, overdispersion, tissue-mixture-driven latent factors, compositional variability, and sequencing noise. This synthetic task universe enables cfRNA-ICL to acquire inductive biases that closely reflect the geometry of real cfRNA data. Across multiple cancer classification benchmarks, cfRNA-ICL demonstrates consistently higher performance than tabular ICL models trained on generic synthetic data. The gains are most sub-stantial in few-shot settings, where the model benefits from its exposure to cfRNA-specific statistical regimes during meta-training. Representation-level analyses further show that cfRNA-ICL organizes samples into biologically coherent manifolds, preserving cancer-type identity without the use of supervised constraints. This finding indicates strong alignment between the synthetic prior and real cfRNA structure. Taken together, these results show that domain-aware generative priors can meaningfully enhance in-context learning for biological tabular data. cfRNA-ICL provides a generalizable framework for cfRNA modeling and establishes a practical path toward foundation-scale models that are intrinsically adapted to the statistical landscape of plasma cfRNA.

genomics↗

bioRxiv2025

A Reference Atlas of the Human Dorsal Root Ganglion

Somatosensory perception largely emerges from diverse peripheral sensory neurons whose cell bodies reside in dorsal root ganglia (DRG). Damage or dysfunction of DRG neurons is a major cause of chronic pain and sensory loss. In mice, deep single-cell transcriptomic profiling and genetically defined models have offered important clues into DRG function, but in humans, the cellular and molecular landscape of DRG neurons remains less understood. Here, we constructed a reference cell atlas of the human DRG by profiling transcriptomes of cells and nuclei from 126 donors sampled across cervical, thoracic, and lumbar DRGs. This atlas resolves 22 neuronal subtypes, including known and previously unrecognized subtypes linked to nociception, mechanosensation, thermosensation, and proprioception, as well as 10 types of non-neuronal cells. Cross-species integration, spatial transcriptomics, and microneurography enabled cell-type-specific comparisons of soma size and conduction velocity between species. Human DRG somata are larger across all cell types than their mouse counterparts, and the conduction velocities of human hair follicle innervating A-fibers are faster than in mice, suggesting a functional shift in rapid mechanical detection in humans. This integrated human DRG reference cell atlas provides a resource for exploring new molecular and physiological features of human DRG, which could help identify new strategies for treating chronic pain and other diseases of the peripheral nervous system.

neuroscience↗

bioRxiv2025

Neural heterogeneity shapes the temporal structure of human working memory

Working memory (WM) enables temporary retention of information essential for flexible cognition. Although persistent population activity has long been regarded as a principal mechanism of memory maintenance, continuous single-neuron firing is energetically demanding and difficult to reconcile with the heterogeneous firing properties of cortical neurons. Applying single-trial analyses to a dataset of 902 neurons recorded from 21 neurosurgical patients performing a WM task, we found that maintenance was supported by transient, burst-like episodes of coordinated activity rather than sustained firing. Cross-temporal decoding exhibited localized generalization, and decoding accuracy increased with wider temporal windows, indicating that apparent persistence can emerge from temporally interleaved activity across neurons. We further developed a feature-based, putative cell-type classifier that revealed distinct circuit contributions: pyramidal neurons expressed content in burst-aligned events during maintenance, whereas interneurons were strongly modulated by memory load and behavior. Together, these findings reconcile dynamic and persistent accounts, indicating that human WM can emerge from temporally interleaved, cell-type-specific dynamics that provide a flexible and potentially metabolically efficient substrate for maintaining information over time.

neuroscience↗

bioRxiv2025

Clonal dynamics of monozygotic twinning in early human embryogenesis

Monozygotic twins are derived from the split of a single zygote early in embryogenesis. Although it was hypothesized that the timing of twining is overall associated with fetal membrane configuration of twins, i.e., chorionicity and amnionicity, our understanding of early embryonic clonal dynamics underlying human twinning is limited. Here we explored the segregations of early embryonic lineages in 7 dichorionic diamniotic (DCDA), 7 monochorionic diamniotic (MCDA), 8 monochorionic monoamniotic (MCMA) monozygotic twins, and 1 dichorionic triamniotic (DCTA) monozygotic triplets, using post-zygotic early embryonic mutations (EEMs) as endogenous lineage barcodes. Patterns of the early lineage distributions among monozygotic twins revealed three apparent clonal categories, referred to as para-identical, sub-identical, and full-identical twins, which largely correlated with the amnionicity of the twins. Rather, despite conventional wisdom, chorionicity was not substantially associated with early clonal compositions, but with blood exchanges in utero. In sub-identical twins, where one co-twin was clonally a part of the other, our data suggested that the foundation of the latter co-twin was established after acquisition of a median of 6 additional post-zygotic mutations (range: 2-13), corresponding to [~]5 early cell divisions. Additional in-depth analysis on the matched placenta from an MCDA twin suggested that separation of two co-twins can precede the separation of the placenta and embryonic proper, and a single chorion can be formed even with multiclonal origin. Our findings provide insights into the clonal dynamics, twinning processes, and cell fate decisions in early human embryogenesis.

genomics↗

bioRxiv2025

CloneCoordinate: Open-source software for collaborative DNA construction

Custom DNA constructs have never been more common or important in the life sciences. Many researchers therefore devote substantial time and effort to molecular cloning, aided by abundant computer-aided design tools. However, support for managing and documenting the construction process, and for effectively handling and reducing the frequency of setbacks, is lacking. To address this need, we developed CloneCoordinate, a free, open-source electronic laboratory notebook specifically designed for cloning and fully implemented in Google Sheets. By maintaining a real-time, automatically prioritized task list, a uniform physical sample inventory, and standardized data structures, CloneCoordinate enables productive, collaborative cloning for individuals or teams. We demonstrate how the information captured by CloneCoordinate can be leveraged to troubleshoot assembly problems and provide data-driven insights into cloning efficiency. CloneCoordinate offers a new and uniquely accessible model for how to carry out, and iteratively improve on, real-world DNA assembly.

synthetic biology↗

bioRxiv2025

Realistic coupling enables flexible macroscopic traveling waves in the mouse cortex

Traveling waves are ubiquitous in neuronal systems across different spatial scales. While microscopic and mesoscopic waves are relatively well studied, the emergence of macroscopic traveling waves remains less understood. Here, by modeling the mouse cortex using spatial transcriptomic and connectivity data, we show that realistic cortical connectivity can generate a significantly higher level of macroscopic traveling waves than artificial local and uniform connectivity across multiple oscillation frequency bands, with the strongest advantage appearing in the theta, alpha, and beta frequency bands. By probing the model in different dynamic regimes, we find that macroscopic wave activity depends on both network connectivity and excitatory coupling strength, with a non-monotonic dependence on coupling. Together, our work shows how flexible macroscopic traveling waves can emerge in the mouse cortex and offers a computational framework to further study traveling waves in the mouse brain at the single-cell level.

neuroscience↗

bioRxiv2025

Differential roles for the spindle assembly checkpoint in error surveillance and mitotic timing

The Spindle Assembly Checkpoint (SAC) plays critical roles in regulating mitotic fidelity and progression. Here, we utilized a SAC-deficient cell line lacking the full-length Cdc20 translational protein isoform (Cdc20 {Delta}FL) to define its differential genetic interactions using CRISPR/Cas9-based gene targeting. Cdc20 {Delta}FL cells display synthetic lethal relationships with gene targets required for proper chromosome segregation, highlighting the critical role of the SAC in error surveillance. Surprisingly, we found that the checkpoint component Mad2 becomes dispensable for viability in Cdc20 {Delta}FL cells. Prior work suggested that Mad2 acts as an essential mitotic "timer" to control mitotic duration in unperturbed cells. Instead, our functional analysis indicates that the mitotic timer depends on the interdependent and overlapping actions of: (1) Mad2 inhibition of APC/C-Cdc20, (2) Cdk1-mediated phosphorylation of Cdc20, and (3) total Cdc20 protein levels. Simultaneously perturbing these pathways results in near immediate mitotic exit and catastrophic chromosome mis-segregation.

cell biology↗

bioRxiv2025

Single-cell metabolome and RNA-seq multiplexing on single plant cells

Plants produce valuable natural products used for a wide variety of industrial applications. Since these molecules have important applications in a variety of industrial sectors, there is enormous interest in elucidating the biosynthetic pathways that are responsible for the production of these compounds. Identification of the genes that comprise these biosynthetic pathways has been enabled by gene-to-metabolite networks that are generated from transcriptomic and metabolomic datasets. Recent advances in both single-cell RNA-seq (scRNA-seq) and single-cell mass spectrometry metabolomics (scMS) have enabled the measurement of either gene expression or metabolite levels in individual cells. However, these individual datasets can only be used to indirectly correlate gene expression levels with metabolite concentrations at the single cell level. Here we demonstrate that both scRNA-seq and scMS can be applied to the same plant cell, thereby enabling direct comparisons between gene expression and metabolite levels. This multiplexing approach reveals both qualitative and quantitative correlations between metabolite levels and biosynthetic gene expression in individual cells. This integrated approach sheds light on the underlying processes driving complex plant biosynthesis.

plant biology↗