Biology subjects

Kim, D. N.

Publications and source records attributed to Kim, D. N..

5 recordsLinked to original sources

bioRxiv2026

Multiomics dissection of the CO2-dependent fast growth of Picochlorum celeri

With a sub-3-micrometer cell and a 27-Mbp diploid genome, the small but mighty Picochlorum celeri doubles within three hours and exceeds 30 g m-2 d-1 outdoors with CO2 supplied. In climate-simulating photobioreactors, productivity declined from 39 g m-2 d-1 under 2.25% CO2 to near zero in air and resumed within hours of CO2 restoration with photosystem II photochemistry largely retained. We profiled the transcriptome, proteome, phosphoproteome, ubiquitinome, acetylome, metabolome and lipidome, including the first site-resolved green-algal ubiquitinome. In air, the Rubisco large subunit tripled to 7.6% of protein while its two small-subunit isoforms, 70% identical, exchanged near-reciprocally, a novel CO2-dependent switch that we propose retunes Rubisco to low CO2. Photorespiratory enzymes increased in abundance whereas proteins involved in external nitrogen assimilation decreased, consistent with increased reliance on internal nitrogen recycling as carbon fixation became limiting. Transcript and protein responses were nearly uncoupled, with cytosolic ribosomal proteins declining despite increased transcripts and plastid ribosomal proteins spared. Phosphorylation was extensively remodeled, as were the lysine modifications ubiquitination, acetylation and CO2-dependent carbamylation, where a CO2-competition assay identified 86 bicarbonate-protected lysines, including RbcL K252. CO2 limitation therefore imposes a reversible growth arrest that reduces cytosolic translational investment while preserving photosynthetic capacity for rapid recovery.

plant biology↗

bioRxiv2026

Spatiotemporal 4D Whole-cell Modeling of a Minimal Autotroph Reveals Central Carbon Metabolism Regulated Locally by Protein Megacomplexes via Post-translational Modifications under Light Disturbance

Photosynthetic microorganisms rely on multiple pathways in central carbon metabolism to adapt to fluctuating light and energy availability across diel cycles. Mechanistic insight into the regulatory dynamics of this adaptation requires integrating processes spanning disparate timescales, from rapid redox-dependent post-translational modifications (PTMs) to slower changes in protein expression and metabolic pathway usage. To address this complexity beyond genome-based inference and traditional modeling, we develop a whole-cell four-dimensional (3D + time) model of the marine cyanobacterium Prochlorococcus marinus MED4 that explicitly represents the spatial organization of enzymatic and molecular processes in central carbon metabolism under light perturbation. We employ a perturbation-based research design to experimentally generate time-series, multi-omics measurements that provide molecular descriptors and cryo-ET images as constraints for this dynamic 4D framework. The integration of experiments and modeling across defined light regimes enables quantitative validation of system-level responses and forecasting under distinct light disturbances. We test the hypothesis that light-dependent redox PTMs regulating the structural assembly of a protein megacomplex, the "dark complex," modulate metabolic flux at a conserved regulatory node of the Calvin-Benson cycle (CBC) in cyanobacteria. Our model shows that subcellular spatial organization buffers rapid light-induced changes in thylakoid reaction rates, which are followed by redox-PTM-mediated sequestration or release of CBC enzymes in the dark complex, ultimately impacting carbon fixation dynamics within carboxysomes. Comparison with an equivalently parameterized well-mixed stochastic model demonstrates that post-translational regulation not only buffers transcriptional noise and diffusion-driven fluctuations but also stabilizes phenotypic outcomes, underscoring the importance of spatial heterogeneity in phenotypic robustness. This ability to probe adaptive, spatiotemporally resolved mechanisms in photosynthetic machinery and central carbon metabolism addresses a critical gap in genotype-to-phenotype inference and expands modeling and design capabilities for understudied or genetically intractable autotrophs such as P. marinus MED4. Significance StatementThis work advances 4D whole-cell modeling by presenting the first spatiotemporal simulation of a photosynthetic autotroph using the Lattice Microbes platform. Using Prochlorococcus marinus MED4, we show that subcellular spatial organization of organelles, diffusion constraints, and redox regulation collectively shape central carbon metabolism across orders of magnitude in space and time. Through a perturbation-based strategy that generates multi-omics data sets over time, we construct and validate a spatially and temporally resolved model of MED4, constrained by high-resolution (10 nm) cryo-electron tomography. Our results highlight the importance of localized biochemical reactions and redox-dependent post-translational modification of enzymes in regulating carbon fixation in a noisy environment under light disturbance. This study establishes a spatiotemporal, whole-cell physiology modeling framework as a transformative tool for uncovering multiscale regulatory responses to environmental gradients.

systems biology↗

bioRxiv2025

Discovery of non-opioid receptor protein targets of fentanyl across tissues from animal models and humans using photoaffinity probes

Synthetic opioids such as fentanyl and related analogs have been widely used for pain management. However, their negative side effects, including respiratory depression and high potential for addiction, underscore the need for a deeper understanding of fentanyls interactions with proteins throughout the human body. Fentanyl analogs bind and activate opioid receptors in the central and peripheral nervous systems, triggering numerous downstream signaling pathways. Increasingly, fentanyl has been shown to interact with non-opioid receptors, and elucidation of these non-canonical fentanyl-protein interactions may provide insights into the mechanisms contributing to fentanyls adverse effects and illuminate novel countermeasure strategies. To identify proteins in mammalian tissues that may interact with fentanyl, we designed and synthesized three affinity-based probes (AfBPs) that include the fentanyl core and feature a diazirine photoaffinity group and alkyne handle for click chemistry at different positions. Molecular docking simulations predicted that these AfBPs bind the mu opioid receptor similarly to fentanyl. Affinity-based protein profiling using the FA-T1 probe in vitro in tissues from six animal species identified histamine N-methyltransferase (HNMT), endophilin-B1 (SH3GLB1), fructosamine-3-kinase (FN3K), cutA divalent cation tolerance analog (CUTA), and monoamine oxidase B (MAOB) among the top proteins that bind fentanyl in multiple species and tissue types. Molecular docking of fentanyl and remifentanil with these protein structures identified putative binding sites. The interaction of fentanyl with specific proteins was empirically assessed through protein structural analyses. These findings highlight potential fentanyl-protein interactions that may contribute to the acute and long-term impacts of fentanyl exposures.

pharmacology and toxicology↗

bioRxiv2024

Synergy and antagonism in a genome-scale model of metabolic hijacking by bacteriophage

Bacteriophage auxiliary metabolic genes (AMGs) alter host metabolism by hijacking reactions. Previous studies used functional annotations to infer AMG impacts but neglected propagation effects on global metabolism and phage production. We demonstrate the first integration of AMGs and phage assembly into a genome-scale metabolic model, using a general method applied to the infection of Prochloroccocus marinus MED4 by P-HM2. We experimentally validate our approach to predicting AMG impact on growth using cp12 mutations in Syne-chococcus elongatus. We predict that 17 directly hijacked reactions substantially impact over 30% of the metabolism, including carbon fixation, photosynthesis, and nucleotide synthesis. We find that indirect impacts are synergistically and antagonistically coupled and are either phage-aligned--shifting feasible reaction velocities in accordance with maximal phage production--or phage-antialigned. Pareto optimization reveals that phage-aligned reactions limit host growth, while phage-antialigned reactions do not. We provide systems-level insight into AMG perturbations, highlighting how nontrivial cascading effects shape microbial functions.

systems biology↗

bioRxiv2021

AutoMicroED: A semi-automated MicroED processing pipeline

Despite rapid adaptation of micro-electron diffraction (MicroED) for protein and small molecule structure determination to sub-angstrom resolution, the lack of automation tools for easy MicroED data processing remains a challenge for expanding to the broader scientific community. In particular, automation tools, which are novice user friendly, compatible with heterogenous datasets and can be run in unison with data collection to judge the quality of incoming data (similar to cryosparc LIVE for single particle cryoEM) do not exist. Here, we present AutoMicroED, a cohesive and semi-automatic MicroED data processing pipeline that runs through image conversion, indexing, integration and scaling of data, followed by merging of successful datasets that are pushed through phasing and final structure determination. AutoMicroED is compatible with both small molecule and protein datasets and creates a straightforward and reproducible method to solve single structures from pure samples, or multiple structures from mixed populations. The immediate feedback on data quality, data completeness and more parameters, aids users to identify whether they have collected enough data for their needs. Overall, AutoMicroED permits efficient structure elucidation for both novice and experienced users with comparable results to more laborious manual processing.

biophysics↗