Dong-Kyun Kim’s research while affiliated with Pohang University of Science and Technology and other places

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Publications (7)


Method for the Rapid Screening of Drug Candidates Using Single‐Protein Tracking in a Living Cell
  • Article

December 2020

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9 Reads

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4 Citations

Bulletin of the Korean Chemical Society

Dong‐Kyun Kim

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Young Sook Kim

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Chan Sik Kim

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Nam Ki Lee

Screening drug candidates rapidly is the first step for developing new pharmaceutical drugs. One of the most promising ways to reduce the number of screening steps and cost is to directly use living cells for screening instead of using purified target proteins. Compounds screened using living cells will have increased biological activity compared to those screened with in vitro assays. Here, we report a robust method for screening drug candidates in living cells based on single‐protein imaging. We employed single‐protein tracking to observe the variation in the diffusion coefficient of membrane proteins treated with the candidate compounds. The diffusion coefficient shift was introduced as a criterion for selecting the potential candidate compounds. We tested three different membrane proteins, epidermal growth factor receptor, ErbB2, and ErbB3, and found effective natural compounds for each protein. The screening method we introduce will be widely used for screening potential drug candidates using living cells.


Fig. 4 Translation-dependent gene loci movement toward the nucleoid periphery in E. coli RNAP transcription. a 5′ UTR sequence of the mutated strains. The underlined AGGAAA in the WT strain (lacZ-12xTetO) was mutated to TCTCTC (red letters) (ΔRBS, lacZ-12xTetO_ΔRBS) for RBS substitution. The start codon of the lacZ gene (underlined) was mutated to TAA (ΔRBSΔATG, lacZ-12xTetO_ΔRBS_ΔATG). b β-galactosidase assay showing that LacZ expression in the strain in which the start codon in the ΔRBS strain was replaced by a stop codon (ΔRBSΔATG) decreased to ~20% of that in the ΔRBS strain (blue bars, 1 mM IPTG induction of each strain). The LacZ expression level in ΔRBSΔATG cells was lower than that in WT cells under repressed conditions (no IPTG, gray bar). c Average x-positions of the lacZ gene locus were determined in the absence (repressed, gray bars) and presence of IPTG (induced, blue bars). d The degree of gene movement is the difference in the average position before (repressed) and after (induced) induction in c. Bar and error bars represent mean ± s.d. from three independent experiments. Each point represents independent measurement
Fig. 6 Model of gene locus movement by transcription in E. coli cells. Transcription starts inside the nucleoid with formation of the RNAP-promoter complex. As soon as the ribosome binding site of mRNA is generated, free ribosomal subunits in the nucleoid region bind the mRNA. The DNA-RNAP-mRNA-ribosome complex moves further outside the nucleoid for easy ribosome access
Transcription by T7 RNAP in living E. coli cells was observed by single-protein detection. a A schematic illustration of the gene system used to visualize single eYFP-T7 RNAPs during transcription. eYFP-T7 RNAP is expressed from an l-rhamnose inducible plasmid (pNL003). The left panel represents the repressed condition, in which the binding of LacI proteins on two Lac operators (O1) blocks transcription by RNAP. The right panel represents the induced condition, in which LacI proteins dissociate from their operators with the addition of 1 mM IPTG and RNAP thus binds to the T7 promoter and generates mRNAs. b, c Representative images of eYFP-T7 RNAPs in E. coli cells. Scale bar, 2 μm. b No IPTG. Blurred fluorescent signals from the rapidly diffusing eYFP-T7 RNAP molecules were detected. c With 1 mM IPTG. The image was acquired at 303 s after adding IPTG. Diffraction-limited fluorescent foci of eYFP-T7 RNAP were clearly observed. d A kinetic model of in vivo transcription. kon denotes the transcriptional on-rate, and koff denotes the transcriptional off-rate (Supplementary Note 1). e Average number of transcribing eYFP-T7 RNAPs during transcription per cell after IPTG induction, including cells that exhibit no bright spots. The blue filled squares and the red filled circles denote data from the induction of the T7p_4.5 kb and T7p_3.3 kb strains, respectively. The data were fitted to a single exponential function, a(1−exp(−bt)), where a = k’on × [RNAPtotal]/koff and b = koff. The elongation rate of RNAP equals Lgene length × koff. The average total number of T7 RNAPs, [RNAPtotal], in a cell was 35. The data represent mean ± s.d. (standard deviation) obtained from three independent experiments
Gene locus moves to the nucleoid periphery by T7 RNAP-driven transcription. a Representative images of T7p_4.5kb cells acquired late (>270 s) after adding IPTG. Fluorescent foci denote the locations of gene loci actively transcribed by T7 RNAP. Scale bar, 2 μm. b Analysis of the subcellular localization of gene locus under transcription. Left panel of b is a reproduction of Fig. 1e, blue line, for convenience. The green box indicates the time window for the cells at the initial transcription stage, <50 s. The purple box indicates the time window for the cells between 300 and 350 s after IPTG induction. The right panel in b shows normalization of the cell size. The location of each fluorescent spot was determined as relative coordinates (x, y) to take into account differences in cell size. The x-axis corresponds to the short axis of the cell. c, d Distributions of the subcellular localization of transcribing eYFP-T7 RNAP foci along the short axis. c The distribution of the locations of transcribing RNAP spots within 50 s after induction (total of 363 fluorescent foci). d The distribution of the locations of transcribing RNAP spots between 300 and 350 s after induction (total of 360 fluorescent foci). e Simulation of gene loci movements. A total of 100,000 random spots with a 70-nm localization error were generated in the cylindrical coordinates (blue spots). Red spots indicate the final locations of each spot randomly moved in the radial direction by 61 nm on average. f, g Comparison of the simulated and experimental results. f The distribution obtained by the simulation (blue bar) was similar to the distribution of the initial transcription stage (green bar, same as Fig. 2c). g The spots obtained by the simulation in Fig. 2e were randomly moved in the radial direction by 61 nm on average (cyan bar). The distribution following these movements is comparable with the distribution in Fig. 2d (purple bar). h The average relative position of the transcribing gene loci after induction. The distance in 3D geometry is presented. Data represent mean ± s.d. obtained from three independent experiments (red). Each point represents independent measurement (black)
Direct observation of the movement of a non-membrane protein gene locus by transcription of E. coli RNAP. a A schematic of the gene system used to detect location of the lacZ gene locus transcribed by E. coli RNAP (left panel). Six repeats of TetO (6xTetO) were inserted downstream of the lacZ gene or mCherry gene transcribed by E. coli RNAP. TetR-eYFPs bound to the TetO array were detected as a fluorescent spot (middle panel). The localization error was 30 nm. Scale bar, 1 μm. b Quantitative analysis of the movement of the lacZ gene locus. The lacZ gene locus moved to the nucleoid periphery after IPTG induction (lacZ-6xTetO strain, blue squares) (>1500 spots). Movement of the lacZ gene locus following the RBS deletion (lacZ-6xTetO_ΔRBS strain, gray circles) was not observed (>800 spots). Data represent mean ± s.d. obtained from three independent experiments. Each point represents independent measurement. c Quantitative analysis of mCherry gene locus movement. Movement of the mCherry gene to the nucleoid periphery was observed after IPTG induction (mCherry-6xTetO, red squares) (>940 spots). Data represent mean ± s.d. obtained from three independent experiments. Each point represents independent measurement. d, e Comparison of gene locus movement with and without the RBS at 24°C (d) and 37°C (e). Average relative x-positions of gene loci were obtained without IPTG (repressed) and 5 min after adding IPTG (induced). Blue bar, lacZ-6xTetO, and gray bar, lacZ-6xTetO_ΔRBS. Bar and error bars represent mean ± s.d. from three independent experiments. Each point represents independent measurement

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Transcription and translation contribute to gene locus relocation to the nucleoid periphery in E. coli
  • Article
  • Full-text available

November 2019

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175 Reads

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30 Citations

Sora Yang

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Seunghyeon Kim

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Dong-Kyun Kim

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[...]

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Nam Ki Lee

Transcription by RNA polymerase (RNAP) is coupled with translation in bacteria. Here, we observe the dynamics of transcription and subcellular localization of a specific gene locus (encoding a non-membrane protein) in living E. coli cells at subdiffraction-limit resolution. The movement of the gene locus to the nucleoid periphery correlates with transcription, driven by either E. coli RNAP or T7 RNAP, and the effect is potentiated by translation. Transcription and translation are coupled in bacteria. Here, the authors show that the movement of a gene locus to the nucleoid periphery correlates with transcription, and the effect is potentiated by translation.

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Membrane protein interactions are directly visualized using co-immunoimmobilization (Co-II)
(A) Schematic of the Co-II assay. The interaction between a fluorescently labeled prey protein and a bait protein is specifically probed by the co-immobilized prey produced after antibody-induced immobilization of the bait protein, which is visualized using sptPALM in single living cells. (B) Comparison between a diffusivity-based method (Co-II) and a proximity-based method (e.g., FRET). In the crowded membrane of living cells, Co-II specifically detects genuine interactions between membrane proteins, while the proximity-based methods are vulnerable to producing false positive signals because a prey and a bait are located nearby. Co-II captures membrane protein interactions independent of tag orientation, while the proximity-based methods require a careful design for donor–acceptor orientation. (C) The bait-specific immobilization using a surface-coated antibody in living cells. The immobilized fractions of PMT, EGFR, ErbB2, ErbB3, InsR, and β2-AR in multiple cells before (NT) and after anti-EGFR antibody treatment. Examined membrane proteins were expressed at a level at least 10 times higher than the expression level of EGFR to avoid the specific co-immobilization resulting from the genuine interaction with EGFR. Each dot represents single-cell data, and the red solid lines indicate the average of the immobilized fraction obtained from multiple cells (n > 10). (D–E) Illustration and trajectory maps for validation of molecule-specific immobilization in the plasma membrane of a living cell. A total of 400 trajectories are shown in each trajectory map. Scale bar, 2 μm. SNAP-EGFR was specifically and almost completely immobilized by anti-EGFR antibody treatment, whereas the immobilized fraction of β2-AR-mEos3.2 was not altered (D). Specific immobilization of β2-AR against EGFR was confirmed vice versa using SNAP-β2-AR and EGFR-mEos3.2 with anti-SNAP antibody (E). β2-AR, beta-2 adrenergic receptor; EGFR, epidermal growth factor receptor; ErbB2, erb-b2 receptor tyrosine kinase 2; ErbB3, erb-b2 receptor tyrosine kinase 3; FRET, fluorescence resonance energy transfer; InsR, insulin receptor; mEos3.2, monomeric Eos fluorescent protein variant 3.2; NT, not treated; PMT, plasma membrane targeting; SNAP, SNAP-tag; sptPALM, single-particle tracking photoactivated localization microscopy.
Equilibrium dissociation constant of EGFR pre-dimerization is determined using Co-II
(A) Schematic representation of the KD measurement of EGFR homodimerization using Co-II. EGFR-mEos3.2 becomes co-immobilized only when interacting with the surface-immobilized SNAP-EGFR by an anti-SNAP antibody; otherwise, it remains in a mobile state. (B) Trajectory map of CF660R-labeled SNAP-EGFR and EGFR-mEos3.2 before and after anti-SNAP antibody treatment in the same single COS7 cell growing with 10% FBS. A total of 200 trajectories are shown in each trajectory map. Scale bar, 3 μm. (C) Diffusion-coefficient distribution of SNAP-EGFR and EGFR-mEos3.2 before (black line) and after anti-SNAP antibody treatment (red line). The immobilization criteria are presented as a blue dashed line. (D) The immobilized fractions of SNAP-EGFR and EGFR-mEos3.2 before and after anti-SNAP antibody treatment. (E) Fluorescence images of total expression and single-molecule–level expression of SNAP-EGFR. Scale bars, 5 μm and 2 μm, respectively. A fluorescence intensity profile of single SNAP-EGFR shows a single bleaching step. (F) KD analysis using a binding curve of prey EGFR to bait EGFR (y-axis) with respect to the density of the antibody-induced immobilized bait EGFR (x-axis). The bound/unbound ratio of the prey with respect to the density is shown (left inset) with a linear fit (red solid line) and a 95% confidence interval (red dashed lines). Scatchard plot for EGFR pre-homodimerization is shown (right inset). The KD was determined in DMEM supplemented with 10% FBS at 37 °C. Each dot indicates data obtained from individual cells. (G) KD of EGFR pre-homodimerization measured in various cell lines. The error bars represent the SEM at the single-cell level (n > 4). (H) A spatial KD map of EGFR pre-homodimerization and the log-normal distribution of the KD values obtained from different regions of plasma membrane in a single living cell. Scale bar, 5 μm. (I) The KD profiles obtained from the cross sections corresponding to the red dashed lines in panel H. (J) The box plots displaying the distributions of KD values obtained from periphery or center regions of each single cell. n = 10. *p < 0.05 (Student t test). A.U., arbitrary unit; DMEM, Dulbecco's Modified Eagle Medium; EGFR, epidermal growth factor receptor; FBS, fetal bovine serum; mEos3.2, monomeric Eos fluorescent protein variant 3.2; SNAP, SNAP-tag.
EGFR dimerization is distinctively regulated by various molecular perturbations in the membrane of living cells
(A–B) KD values of EGFR homodimerization measured with and without EGF under the treatment of nonnatural ligands, including a Fab fragment of cetuximab and two types of tyrosine kinase inhibitors, erlotinib and lapatinib, in serum-starved COS7 cells. (C) KD values of homodimerization for EGFR WT (the same data for NT in panel A), EGFRvIII, and EGFR L858R. The error bars represent the SEM at the single-cell level (n > 10). All the measurements were performed in a serum-free DMEM at 37 °C. *p < 0.05 (Student t test). (D) A scale mapping KD values of EGFR homodimerization under various molecular perturbations. The yellow and green dots indicate the perturbations to EGFR ECD and ICD, respectively, and a black dot indicates no perturbation. Each perturbation site is displayed in the illustration, representing the reaction of EGFR pre-homodimerization with log2 fold change values compared with the KD without perturbation. DMEM, Dulbecco's Modified Eagle Medium; ECD, extracellular domain; EGF, epidermal growth factor; EGFR, epidermal growth factor receptor; Fab, fragment antigen-binding; ICD, intracellular domain; NT, not treated; WT, wild type.
Comparison of equilibrium dissociation constants of EGFR and β2-AR homodimerization under ligand treatment and cholesterol sequestration
KD values of EGFR and β2-AR homodimerizations were determined by Co-II under the existence of their ligands (EGF and ISO, respectively) and the sequestration of cholesterol in a plasma membrane. The scale mapping KD values for their homodimerizations are displayed for direct comparisons. β2-AR, beta-2 adrenergic receptor; EGF, epidermal growth factor; EGFR, epidermal growth factor receptor; ISO, isoproterenol; NT, not treated; SNAP, SNAP-tag.
Direct visualization of single-molecule membrane protein interactions in living cells

December 2018

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152 Reads

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30 Citations

Interactions between membrane proteins are poorly understood despite their importance in cell signaling and drug development. Here, we present a co-immunoimmobilization assay (Co-II) enabling the direct observation of membrane protein interactions in single living cells that overcomes the limitations of currently prevalent proximity-based indirect methods. Using Co-II, we investigated the transient homodimerizations of epidermal growth factor receptor (EGFR) and beta-2 adrenergic receptor (β2-AR) in living cells, revealing the differential regulation of these receptors’ dimerizations by molecular conformations and microenvironment in a plasma membrane. Co-II should provide a simple, rapid, and robust platform for visualizing both weak and strong protein interactions in the plasma membrane of living cells.


Single Particle Tracking-Based Reaction Progress Kinetic Analysis Reveals a Series of Molecular Mechanisms of Cetuximab-Induced EGFR Processes in a Single Living Cell

April 2017

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447 Reads

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31 Citations

Cellular processes occur through the orchestration of multi-step molecular reactions. Reaction progress kinetic analysis (RPKA) can provide the mechanistic details to elucidate the multi-step molecular reactions. However, current tools have limited ability to simultaneously monitor dynamic variations in multiple complex states at the single molecule level to apply RPKA in living cells. In this research, a single particle tracking-based reaction progress kinetic analysis (sptRPKA) was developed to simultaneously determine the kinetics of multiple states of protein complexes in the membrane of a single living cell. The subpopulation ratios of different states were quantitatively (and statistically) reliably extracted from the diffusion coefficient distribution rapidly acquired by single particle tracking at constant and high density over a long period of time using super-resolution microscopy. Using sptRPKA, a series of molecular mechanisms of epidermal growth factor receptor (EGFR) cellular processing induced by cetuximab were investigated. By comprehensively measuring the rate constants and cooperativity of the molecular reactions involving four EGFR complex states, a previously unknown intermediate state was identified that represents the rate limiting step responsible for the selectivity of cetuximab-induced EGFR endocytosis to cancer cells.


High-resolution pluronic-filled microchip CE-SSCP analysis system via channel width control

November 2015

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24 Reads

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2 Citations

Electrophoresis

Although the resolution of capillary electrophoresis-single strand conformation polymorphism (CE-SSCP) has been significantly improved by using a poly(ethyleneoxide)-poly(propyleneoxide)-poly(ethyleneoxide) (PEO-PPO-PEO; Pluronic(®) ) triblock copolymer as a separation medium, CE-SSCP on a microchip format is not widely applicable because their resolution is limited by short channel length. Therefore, a strategy to improve the resolution in channels of limited lengths is highly required for enabling microchip-based CE-SSCP. In this study, we developed a high-resolution CE-SSCP microchip system by controlling the width of the Pluronic-filled channel. We tested four different channel widths of 180, 240, 300, and 400 μm, and found that 300 μm showed the highest resolution in the separation of two pathogen specific markers. Potential applications of our method in various genetic analyses were also shown by using single nucleotide polymorphism markers for spinal muscular atrophy. This article is protected by copyright. All rights reserved.


Analysis of Interactions between the Epidermal Growth Factor Receptor and Soluble Ligands on the Basis of Single-Molecule Diffusivity in the Membrane of Living Cells

May 2015

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101 Reads

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15 Citations

Angewandte Chemie

We present a single-molecule diffusional-mobility-shift assay (smDIMSA) for analyzing the interactions between membrane and water-soluble proteins in the crowded membrane of living cells. We found that ligand-receptor interactions decreased the diffusional mobility of ErbB receptors and β-adrenergic receptors, as determined by single-particle tracking with super-resolution microscopy. The shift in diffusional mobility was sensitive to the size of the water-soluble binders that ranged from a few tens of kilodaltons to several hundred kilodaltons. This technique was used to quantitatively analyze the dissociation constant and the cooperativity of antibody interactions with the epidermal growth factor receptor and its mutants. smDIMSA enables the quantitative investigation of previously undetected ligand-receptor interactions in the intact membrane of living cells on the basis of the diffusivity of single-molecule membrane proteins without ligand labeling. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


Citations (5)


... Both leucine-rich domains are critical for the peptide bonding sites, while the cysteine-rich domains are pivotal in the activation of EGFR. Therefore, EGFR has been well-known as one of the most targeted proteins in the early evaluation of anticancer agents [16]. Choe et al. [17] reported that EGFR protein has also been employed in the clinical trials of Tarceva® and Iressa® on non-small cell lung cancer patients. ...

Reference:

Molecular Docking and Molecular Dynamic Investigations of Xanthone-Chalcone Derivatives against Epidermal Growth Factor Receptor for Preliminary Discovery of Novel Anticancer Agent
Method for the Rapid Screening of Drug Candidates Using Single‐Protein Tracking in a Living Cell
  • Citing Article
  • December 2020

Bulletin of the Korean Chemical Society

... ; https://doi.org/10.1101/2024.10.10.617531 doi: bioRxiv preprint poles [62,63], and it has been suggested that chromosome organization could be linked to transcription or translation [64,65]. Additionally, the information stored in gene positions could be used to guide intra-cellular processes [66]. ...

Transcription and translation contribute to gene locus relocation to the nucleoid periphery in E. coli

... By utilizing photoactivatible and/or photoswitchable fluorophores, including mEos proteins or AF647 with oxygen scavenging systems and primary thiols, the low density of labeled molecules in a bright state was maintained, enabling multiple rounds of acquisition of single-molecule data in the same single live cell 32,33 . The large amount of single-molecule data collected was sufficient for statistical analysis to infer the transitions of various diffusional states, including free, confined and immobilized states 34 . ...

Direct visualization of single-molecule membrane protein interactions in living cells

... We estimate the clathrin entry rate k c ≈ 0.1 s −1 , which is substantially slower than the estimated diffusion-limited entry rate [43] of ≈1 s −1 (for EGFR with diffusivity 0.2 µm 2 s −1 [8,9,[44][45][46][47] to clathrin domains of 50 nm radius representing 1% of the plasma membrane surface [48]). k −c ≈ 0.05 s −1 and k i ≈ 0.05 s −1 are estimated from clathrin domain dynamics [48]. ...

Single Particle Tracking-Based Reaction Progress Kinetic Analysis Reveals a Series of Molecular Mechanisms of Cetuximab-Induced EGFR Processes in a Single Living Cell

... To quantitatively analyze changes in membrane mobility in response to α-Syn mutant oligomeric mixtures, we measured the diffusion coefficient (D) of Rhod-PE before and 30 min after treatment with α-Syn mutant oligomeric mixtures. The change in mobility of Rhod-PE was indicated by the diffusion coefficient shift, which was calculated as follows: diffusion coefficient shift (%) = 100 [(D 30 min after treatment -D before treatment )/ D before treatment ] (Kim et al., 2015). A diffusion coefficient shift lower than zero indicates the reduced mobility of Rhod-PE. ...

Analysis of Interactions between the Epidermal Growth Factor Receptor and Soluble Ligands on the Basis of Single-Molecule Diffusivity in the Membrane of Living Cells
  • Citing Article
  • May 2015

Angewandte Chemie