Jong-Seo Kim

Proximity labeling has transformed spatial proteomics by enabling compartment-resolved mapping of protein environments in living cells, yet its extension to small-molecule metabolites has not been demonstrated, probably due to limitations in labeling chemistry and labeled metabolites identification. Here, we introduce DESTNI, an engineered desthiobiotin (DTB) ligase derived from TurboID through directed evolution, and establish a platform for spatially resolved profiling of amine-containing metabolites. A directed evolution strategy based on a yeast display system yielded DESTNI with efficient DTB-dependent reactivity, enabling robust and compartment-specific proximity labeling across diverse subcellular environments. To identify the DTB-modified amino metabolome, we developed an integrated analytical framework combining DTB-modified amino metabolite standards, in vitro DESTNI profiling, and in silico MS/MS prediction, enabling systematic annotation of DTB-modified amino metabolites. To extend this chemistry to metabolites, we combined synthetic DTB-conjugated metabolite reference standards, in vitro DESTNI-reactive metabolite discovery, and machine-learning prediction of DTB-derivatized metabolites and oligopeptides. Organelle-targeted DESTNI recovered reproducible compartment-enriched amino metabolite signatures, including mitochondrial matrix-enriched glycine, 5-aminolevulinic acid, ornithine and spermidine adducts, as well as nuclear-enriched γ-aminobutyric acid and 5-aminovaleric acid adducts. Together, this work establishes DESTNI as a proximity labeling platform that bridges spatial proteomics and metabolomics and provides a general strategy for mapping subcellular biochemical environments in living cells.

Exercise enhances learning and memory, not only through improved cardiometabolic but also through body-brain interactions mediated by secreted factors. Given the prominent role of skeletal muscle during exercise, muscle-derived factors, myokines, are believed to mediate the exercise-induced cognitive enhancements. Here, we demonstrate that intramuscular Serpina1e is upregulated following exercise in male mice. Systemic delivery of recombinant Serpina1e or intramuscular overexpression of Serpina1e reproduces exercise-induced memory enhancements in sedentary male mice. Conversely, muscle-specific depletion of Serpina1e abolishes hippocampal memory enhancement, indicating a requirement of muscle-derived Serpina1e for these cognitive benefits. Mechanistically, elevated plasma Serpina1e stimulates neurogenesis, brain-derived neurotrophic factor (BDNF) expression, and neurite growth in the hippocampus by crossing the blood–cerebrospinal fluid (CSF) and blood–brain barrier. Our findings identify Serpina1e as a key mediator of skeletal muscle-brain interaction that enables the beneficial effects of exercise on cognitive function.

RNA modifications (RMs) are critical for diverse biological processes, but the lack of accurate, quantitative detection methods has limited their study. A large-scale and high-quality training dataset is an essential component for accurate deep learning, but such dataset has been absent for RM detection, resulting in low accuracies. We developed DeepRM (Deep learning for RNA Modification), a sophisticated deep learning framework powered by Nanopore sequencing. DeepRM dataset is a massive-scale, three orders of magnitude larger than the comparable previous ones, and unprecedentedly high-quality dataset that closely mirrors endogenous transcript environments. Accordingly, DeepRM detects RM sites and measures their modification stoichiometries with a near-perfect accuracy. Using DeepRM, we constructed a comprehensive, human m⁶A atlas at single-molecule resolution that reveals a large number of previously underappreciated non-canonical m⁶A sites and differentially modified transcripts, highlighting the complexity and dynamic nature of the human epitranscriptome. DeepRM is freely available, providing a unique, powerful opportunity for understanding the biological functions of RMs. DeepRM can also be expanded to various other RMs and organisms, potentially becoming a future standard for investigating the epitranscriptome.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the loss of dopaminergic neurons (DN) in the substantia nigra and disruption of cellular maintenance. Here, we demonstrate that NDST3‐mediated epigenetic reprogramming halts neuronal degeneration and restores motor function in an animal model of PD. Following NDST3 administration, the DN and its associated circuits in the substantia nigra and striatum showed marked revitalization, accompanied by a considerable alleviation of PD‐like motor deficits. Integrative single‐cell and spatial RNA sequencing with CUT&RUN revealed that NDST3‐driven reactivation of pathways is linked to neuronal survival, synaptic integrity, and steering of compromised cells toward a resilient phenotype. By recalibrating the epigenetic landscape, NDST3 promotes cellular maintenance and functional recovery in key motor circuits. These findings highlight NDST3's therapeutic potential as an epigenetic modulator of PD. These findings provide insights into the mechanisms underlying neuronal revitalization and highlight the potential of NDST3 as a novel agent for restoring brain function in neurodegenerative conditions.

Coronaviruses establish replication organelles (ROs) to synthesize their RNA while evading host defenses. To systematically profile the host factors and the dynamic interplay between viral and host factors during viral replication, we developed an antibody-based proximity labeling strategy tailored to profile the proteome at the coronavirus RO. Applying this to SARS-CoV-2 and HCoV-OC43, we revealed both conserved requirements and unique adaptations in each virus. Temporal profiling further uncovered dynamic recruitment patterns: an early enrichment of ER proteins, mitochondrial proteins and RNA processing factors, and a progressive exclusion of stress granule components. Functional analyses of RNA-binding proteins revealed regulatory host factors, including the double-stranded RNA-binding protein STAU1, which plays a pro-viral role on SARS-CoV-2 at the early infection stage. Collectively, these findings establish a robust proteomic framework for investigating coronavirus replication organelle biology and uncover virus-specific strategies to manipulate host cellular machinery.

Proximity labeling with engineered ascorbate peroxidase (APEX) has been widely used to identify proteomes within various membrane-enclosed subcellular organelles. However, constructing protein distribution maps between two non-partitioned proximal spaces remains challenging with the current proximity labeling tools. Here, we introduce a proximity labeling approach using isotope-coded phenol probes for APEX labeling (ICAX) that enables the quantitative analysis of the spatial proteome at nanometer resolution between two distinctly localized APEX enzymes. Using this technique, we identify the spatial proteomic architecture of the mitochondrial intracristal space (ICS), which is not physically separated from the peripheral space. ICAX analysis further reveals unexpected dynamics of the mitochondrial spatiome under mitochondrial contact site and cristae organizing system (MICOS) complex inhibition and mitochondrial uncoupling, respectively. Overall, these findings highlight the importance of ICS for mitochondrial quality control under dynamic stress conditions.

The SARS-CoV-2 genome encodes 16 nonstructural proteins (Nsps), with Nsp2 being the least conserved and understood. This study highlights a crucial role for Nsp2 in the early phase of the viral life cycle, particularly its interaction with GIGYF2, which relocates near double-membrane vesicles (DMVs) and enhances viral protein production. Deletion of the Nsp2-coding region from the viral genome led to a drastic reduction in viral RNA synthesis early in infection (3–4 h after infection). Interactome analysis in virus-infected cells identified GIGYF2, a host-encoded translational regulation protein, as a key Nsp2 partner. This interaction was confirmed for both SARS-CoV-1 and SARS-CoV-2. Depletion of GIGYF2 or its cofactor ZNF598 phenocopied the replication defects observed with Nsp2 deletion, suggesting their critical roles in viral reproduction. Upon infection, GIGYF2 and ZNF598 relocate to areas near DMVs, viral replication sites. This relocation does not occur with the Nsp2-deleted virus, indicating Nsp2’s role in directing GIGYF2 to DMVs. Formaldehyde crosslinking and immunoprecipitation sequencing (fCLIP-seq) identified regions within viral RNAs that potentially interact with GIGYF2, including those encoding M and Orf6. Depletion of GIGYF2 resulted in decreased protein expression of M and Orf6. Our findings reveal the function of Nsp2 in supporting viral protein production by exploiting GIGYF2 as a host factor.

GCN5-related N -acetyltransferases (GNATs) are essential for regulating bacterial metabolism by acetylating specific target proteins. Despite their importance in bacterial physiology, the mechanisms behind their enzymatic and regulatory functions remain poorly understood. In this study, we investigated the structures of Escherichia coli protein acetyltransferase Z (PatZ), a Type I GNAT, and examined its ligand interactions, catalytic mechanism, and allosteric regulation. PatZ functions as a homotetramer, with each subunit comprising a catalytic and a regulatory domain. Our results demonstrate that the regulatory domain is vital for acetyltransferase activity, as it triggers cooperative conformational changes in the catalytic domain and directly aids in the formation of substrate-binding pockets. Additionally, a protein structure-based evolutionary analysis of bacterial GNAT types revealed a distinct regulatory domain pattern across phyla, highlighting its crucial role in responding to cellular energy levels.