Korea University · 生化学・遺伝学・分子生物学
Professor Jae Kyoung Kim's research lab specializes in systems and synthetic biology, focusing on understanding and engineering complex regulatory networks in cellular systems. The lab investigates circadian rhythms, gene regulatory circuits, and enzyme kinetics using a combination of mathematical modeling, systems biology approaches, and synthetic biology tools. Key research directions include the design of synthetic microbial consortia with emergent population-level behaviors, the molecular mechanisms of circadian timekeeping, and the accurate modeling of enzyme kinetics to overcome limitations of classical Michaelis-Menten kinetics. The lab integrates computational modeling with experimental validation to uncover principles of robustness and regulation in biological systems.
Figures are computed from collected data and may differ slightly.
A challenge of synthetic biology is the creation of cooperative microbial systems that exhibit population-level behaviors. Such systems use cellular signaling mechanisms to regulate gene expression across multiple cell types. We describe the construction of a synthetic microbial consortium consisting of two distinct cell types—an "activator" strain and a "repressor" strain. These strains produced two orthogonal cell-signaling molecules that regulate gene expression within a synthetic circuit spa
Circadian (∼24 h) timekeeping is essential for the lives of many organisms. To understand the biochemical mechanisms of this timekeeping, we have developed a detailed mathematical model of the mammalian circadian clock. Our model can accurately predict diverse experimental data including the phenotypes of mutations or knockdown of clock genes as well as the time courses and relative expression of clock transcripts and proteins. Using this model, we show how a universal motif of circadian timekee
Circadian rhythms are controlled by a system of negative and positive genetic feedback loops composed of clock genes. Although many genes have been implicated in these feedback loops, it is unclear whether our current list of clock genes is exhaustive. We have recently identified Chrono as a robustly cycling transcript through genome-wide profiling of BMAL1 binding on the E-box. Here, we explore the role of Chrono in cellular timekeeping. Remarkably, endogenous CHRONO occupancy around E-boxes sh
The circadian clock and cell cycle networks are interlocked on the molecular level, with the core clock loop exerting a multilevel regulatory role over cell cycle components. This is particularly relevant to the circadian factor Period 2 (Per2), which modulates the stability of the tumor suppressor p53 in unstressed cells and transcriptional activity in response to genotoxic stress. Per2 binding prevents Mdm2-mediated ubiquitination of p53 and, therefore, its degradation, and oscillations in the
For over a century, the Michaelis-Menten (MM) rate law has been used to describe the rates of enzyme-catalyzed reactions and gene expression. Despite the ubiquity of the MM rate law, it accurately captures the dynamics of underlying biochemical reactions only so long as it is applied under the right condition, namely, that the substrate is in large excess over the enzyme-substrate complex. Unfortunately, in circumstances where its validity condition is not satisfied, especially so in protein int
The stochastic QSSA is one of the most popular multi-scale stochastic simulation methods. While the use of QSSA, and the resulting non-elementary functions has been justified in the deterministic case, it is not clear when their stochastic counterparts are accurate. In this study, we show how the accuracy of the stochastic QSSA can be tested using their deterministic counterparts providing a concrete method to test when non-elementary rate functions can be used in stochastic simulations.
The tumor suppressor p53 protein shows various dynamic responses depending on the types and extent of cellular stresses. In particular, in response to DNA damage induced by c-irradiation, cells generate a series of p53 pulses. Recent research has shown the importance of sustaining repeated p53 pulses for recovery from DNA damage. However, far too little attention has been paid to understanding how cells can sustain p53 pulses given the complexities of genetic heterogeneity and intrinsic noise. H
Chronotherapy is a pharmaceutical intervention that considers the patient's internal circadian time to adjust dosing time. Although it can dramatically improve drug efficacy and reduce toxicity, the large variability in internal time across and within individuals has prevented chronotherapies from progressing beyond clinical trials. To translate chronotherapy developments into a real-world outpatient clinical scenario, a personalized characterization and analysis of a patient's internal time is
Circadian rhythms can be entrained by a light-dark (LD) cycle and can also be reset pharmacologically, for example, by the CK1δ/ε inhibitor PF-670462. Here, we determine how these two independent signals affect circadian timekeeping from the molecular to the behavioral level. By developing a systems pharmacology model, we predict and experimentally validate that chronic CK1δ/ε inhibition during the earlier hours of a LD cycle can produce a constant stable delay of rhythm. However, chronic dosing
The circadian clock is based on a transcriptional feedback loop with an essential time delay before feedback inhibition. Previous work has shown that PERIOD (PER) proteins generate circadian time cues through rhythmic nuclear accumulation of the inhibitor complex and subsequent interaction with the activator complex in the feedback loop. Although this temporal manifestation of the feedback inhibition is the direct consequence of PER's cytoplasmic trafficking before nuclear entry, how this spatia
Unsupervised clustering models have been widely used for multimetric phenotyping of complex and heterogeneous diseases such as diabetes and obstructive sleep apnea (OSA) to more precisely characterize the disease beyond simplistic conventional diagnosis standards. However, the number of clusters and key phenotypic features have been subjectively selected, reducing the reliability of the phenotyping results. Here, to minimize such subjective decisions for highly confident phenotyping, we develop
Biochemical reaction networks (BRNs) in a cell frequently consist of reactions with disparate timescales. The stochastic simulations of such multiscale BRNs are prohibitively slow due to high computational cost for the simulations of fast reactions. One way to resolve this problem uses the fact that fast species regulated by fast reactions quickly equilibrate to their stationary distribution while slow species are unlikely to be changed. Thus, on a slow timescale, fast species can be replaced by
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