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KAIST provides a comprehensive resource on microbial cell factories for sustainable chemical production
In silico analysis of five industrial microorganisms identifies optimal strains and metabolic engineering strategies for producing 235 valuable chemicals Climate change and the depletion of fossil fuels have raised the global need for sustainable chemical production. In response to these environmental challenges, microbial cell factories are gaining attention as eco-friendly platforms for producing chemicals using renewable resources, while metabolic engineering technologies to enhance these cell factories are becoming crucial tools for maximizing production efficiency. However, difficulties in selecting suitable microbial strains and optimizing complex metabolic pathways continue to pose significant obstacles to practical industrial applications. KAIST (President Kwang-Hyung Lee) announced on 27th of March that Distinguished Professor Sang Yup Lee’s research team in the Department of Chemical and Biomolecular Engineering comprehensively evaluated the production capabilities of various industrial microbial cell factories using in silico simulations and, based on these findings, identified the most suitable microbial strains for producing specific chemicals as well as optimal metabolic engineering strategies. Previously, researchers attempted to determine the best strains and efficient metabolic engineering strategies among numerous microbial candidates through extensive biological experiments and meticulous verification processes. However, this approach required substantial time and costs. Recently, the introduction of genome-scale metabolic models (GEMs), which reconstruct the metabolic networks within an organism based on its entire genome information, has enabled systematic analysis of metabolic fluxes via computer simulations. This development offers a new way to overcome limitations of conventional experimental approaches, revolutionizing both strain selection and metabolic pathway design. Accordingly, Professor Lee’s team at the Department of Chemical and Biomolecular Engineering, KAIST, evaluated the production capabilities of five representative industrial microorganisms—Escherichia coli, Saccharomyces cerevisiae, Bacillus subtilis, Corynebacterium glutamicum, and Pseudomonas putida—for 235 bio-based chemicals. Using GEMs, the researchers calculated both the maximum theoretical yields and the maximum achievable yields under industrial conditions for each chemical, thereby establishing criteria to identify the most suitable strains for each target compound. < Figure 1. Outline of the strategy for improving microbial cell factories using a genome-scale metabolic model (GEM) > The team specifically proposed strategies such as introducing heterologous enzyme reactions derived from other organisms and exchanging cofactors used by microbes to expand metabolic pathways. These strategies were shown to increase yields beyond the innate metabolic capacities of the microorganisms, resulting in higher production of industrially important chemicals such as mevalonic acid, propanol, fatty acids, and isoprenoids. Moreover, by applying a computational approach to analyze metabolic fluxes in silico, the researchers suggested strategies for improving microbial strains to maximize the production of various chemicals. They quantitatively identified the relationships between specific enzyme reactions and target chemical production, as well as the relationships between enzymes and metabolites, determining which enzyme reactions should be up- or down-regulated. Through this, the team presented strategies not only to achieve high theoretical yields but also to maximize actual production capacities. < Figure 2. Comparison of production routes and maximum yields of useful chemicals using representative industrial microorganisms > Dr. Gi Bae Kim, the first author of this paper from the KAIST BioProcess Engineering Research Center, explained, “By introducing metabolic pathways derived from other organisms and exchanging cofactors, it is possible to design new microbial cell factories that surpass existing limitations. The strategies presented in this study will play a pivotal role in making microbial-based production processes more economical and efficient.” In addition, Distinguished Professor Sang Yup Lee noted, “This research serves as a key resource in the field of systems metabolic engineering, reducing difficulties in strain selection and pathway design, and enabling more efficient development of microbial cell factories. We expect it to greatly contribute to the future development of technologies for producing various eco-friendly chemicals, such as biofuels, bioplastics, and functional food materials.” This research was conducted with the support from the Development of platform technologies of microbial cell factories for the next-generation biorefineries project and Development of advanced synthetic biology source technologies for leading the biomanufacturing industry project (Project Leader: Distinguished Professor Sang Yup Lee, KAIST) from National Research Foundation supported by the Korean Ministry of Science and ICT.
2025.03.27
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KAIST Captures Protein Reaction in Just Six Milliseconds
Understanding biological phenomena, including protein-protein interactions and enzyme-substrate reactions occurring in microseconds to milliseconds, is essential for comprehending life processes and advancing drug development. KAIST researchers have developed a method for freezing and analyzing biochemical reaction changes within a span of just a few milliseconds, a critical step towards better understanding these complex biological reactions. < Photo. (From left) Professor Jin Young Kang and Haerang Hwang of the Integrated Master's and Doctoral Program of the Department of Chemistry along with Professor Wonhee Lee of the Department of Physics > KAIST (represented by President Kwang Hyung Lee) announced on the 24th of March that a joint research team led by Professor Jin Young Kang from the Department of Chemistry and Professor Wonhee Lee from the Department of Physics has developed a parylene-based thin-film microfluidic mixing-and-spraying device for ultra-fast biochemical reaction studies. *Parylene: A key material for microfluidic devices used to observe protein reactions at ultra-high speeds. It can be fabricated into thin films, just a few micrometers thick, which can be used in making spray nozzles. This research overcomes the limitations of the existing time-resolved cryo-electron microscopy (TRCEM) method by reducing sample consumption to one-third of the conventional amount while improving the minimum analyzable reaction time by several orders of magnitude—down to just six milliseconds (6 ms). TRCEM is a technique that rapidly freezes protein complexes during intermediate reaction stages under cryogenic conditions, which allows researchers to analyze their structures. This approach has gained significant attention recently for its potential to capture fleeting biochemical events. < Figure 1. Time-resolved cryo-EM (TRCEM) technique using microfluidic channels. In order to capture the intermediate structure of biomolecules during a biochemical reaction over time, biomolecules and reaction substrates are mixed in a microfluidic channel, and then sprayed on a grid after a certain reaction time and frozen in liquid ethane to prepare a cryo-EM sample. This can then be analyzed by cryo-EM to observe the structural changes of proteins over time. > Traditional cryo-electron microscopy has struggled to capture transient intermediate states due to their extremely short lifespans. Although several TRCEM techniques have been developed to address this issue, previous methods were hindered by high sample consumption and limited time resolution. To overcome these challenges, the KAIST team developed a new mixing-and-spraying device using ultra-thin parylene films. The integrated design of the device further enhanced the precision and reproducibility of experiments. < Figure 2. TRCEM grid fabrication setup using a parylene-based thin-film microfluidic device and actual appearance of the device. You can see that a thin-film parylene channel is inserted into the injection nozzle. The integration of the reaction channel and the injection nozzle allowed the residence time in the device to be reduced to at least 0.5 ms. > “This research makes TRCEM more practical and paves the way for diverse applications of the parylene thin-film device in structural biology, drug development, enzyme reaction studies, and biosensor research.” Professor Jin Young Kang explained, emphasizing the significance of the study. Professor Wonhee Lee added, “The team aims to continue this research, focusing on further performance enhancements of the device and the application for various biochemical reaction analysis.” < Figure 3. Comparison of the spraying patterns of the parylene mixing-jet device and the conventional mixing-jet device and the filament length in the resulting RecA-ssDNA filament formation reaction. It was shown that the thin film spray nozzle structure affects the uniformity and accuracy of the final reaction time. > The research findings, with Haerang Hwang (a graduate student in the integrated master's and Ph.D. program in the Department of Chemistry) as the first author, were published online on January 28, 2025, in the international journal Advanced Functional Materials. (Paper Title: “Integrated Parylene-Based Thin-Film Microfluidic Device for Time-Resolved Cryo-Electron Microscopy”, DOI: doi.org/10.1002/adfm.202418224) This research was supported by the National Research Foundation of Korea (NRF), the Samsung Future Technology Development Program, and the CELINE consortium.
2025.03.24
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KAIST Develops World-Leading Ammonia Catalyst for Hydrogen Economy
Hydrogen production using renewable energy is a key technology for eco-friendly energy and chemical production. However, storing and transporting hydrogen remains a challenge. To address this, researchers worldwide are investigating methods to store hydrogen in the form of ammonia (NH₃), which is carbon-free and easier to liquify. A research team at KAIST has successfully developed a high-performance catalyst that enables ammonia synthesis at very low temperatures and pressures without energy loss. KAIST (represented by President Kwang Hyung Lee) announced on the 11th of March that a research team led by Professor Minkee Choi from the Department of Chemical and Biomolecular Engineering has developed an innovative catalytic system that significantly enhances ammonia production while drastically reducing energy consumption and CO₂ emissions. < (From left) Baek Ye-jun, Ph.D. candidate in the Department of Biochemical Engineering, Professor Choi Min-ki > Currently, ammonia is produced using the Haber-Bosch process, a technology over a century old that relies on iron (Fe)-based catalysts. This method requires extreme conditions—temperatures above 500°C and pressures exceeding 100 atmospheres—resulting in enormous energy consumption and contributing significantly to global CO₂ emissions. Additionally, ammonia is primarily produced in large-scale industrial plants, leading to high distribution costs. As an alternative, there is growing interest in an eco-friendly process that synthesizes ammonia using green hydrogen—produced via water electrolysis—under mild conditions (300°C, 10 atmospheres). However, developing catalysts that can achieve high ammonia productivity at such low temperatures and pressures is essential, as current technologies struggle to maintain efficiency under these conditions. The research team developed a novel catalyst by incorporating ruthenium (Ru) nanoparticles and highly basic barium oxide (BaO) particles onto a conductive carbon surface, allowing it to function like a chemical capacitor*. *Capacitor: A device that stores electrical energy by separating positive and negative charges. During ammonia synthesis, hydrogen molecules (H₂) first dissociate into hydrogen atoms (H) on the ruthenium catalyst. These hydrogen atoms are further split into protons (H⁺) and electrons (e⁻). The study revealed that the acidic protons are stored in the strongly basic BaO, while the remaining electrons are separated and stored in ruthenium and carbon. This unique chemical capacitor effect significantly enhances the ruthenium catalyst's electron density, accelerating nitrogen (N₂) dissociation—the rate-limiting step of ammonia synthesis—thereby dramatically increasing catalytic activity. Furthermore, the team discovered that optimizing the nanostructure of the carbon material further boosts the electron density of ruthenium, maximizing catalytic performance. As a result, the new catalyst demonstrated over seven times higher ammonia synthesis performance compared to state-of-the-art catalysts under mild conditions (300°C, 10 atm). < Schematic diagram showing the mechanism of ruthenium catalyst activity enhancement by barium oxide cocatalyst > Professor Minkee Choi stated, “This research has garnered significant attention for demonstrating that catalytic activity can be greatly enhanced by controlling electron transfer within a thermal catalytic reaction system, not just in electrochemical processes.” He further explained, “Our findings confirm that high-performance catalysts can enable efficient ammonia synthesis under low-temperature and low-pressure conditions. This could shift ammonia production from centralized, large-scale industrial plants to decentralized, small-scale production, making the hydrogen economy more sustainable and flexible.” The study was led by Professor Minkee Choi as corresponding author and Yaejun Baik, a Ph.D. candidate, as first author. The research findings were published in Nature Catalysis on February 24. (Paper title: “Electron and proton storage on separate Ru and BaO domains mediated by conductive low-work-function carbon to accelerate ammonia synthesis,” https://doi.org/10.1038/s41929-025-01302-z) This research was supported by the Korea Institute of Energy Research and the National Research Foundation of Korea.
2025.03.11
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AI-Driven Wearable Blood Pressure Sensor for Continuous Health Monitoring – Published in Nature Reviews Cardiology
A KAIST research team led by Professor Keon Jae Lee has proposed an innovative theoretical framework and research strategies for AI-based wearable blood pressure sensors, paving the way for continuous and non-invasive cardiovascular monitoring. Hypertension is a leading chronic disease affecting over a billion people worldwide and is a major risk factor for severe cardiovascular conditions such as myocardial infarction, stroke, and heart failure. Traditional blood pressure measurement relies on intermittent, cuff-based methods, which fail to capture real-time fluctuations and present challenges in continuous patient monitoring. Wearable blood pressure sensors offer a non-invasive solution for continuous blood pressure monitoring, enabling real-time tracking and personalized cardiovascular health management. However, current technologies lack the accuracy and reliability required for medical applications, limiting their practical use. To address these challenges, advancements in high-sensitivity sensor technology and AI signal processing algorithms are essential. Building on their previous study in Advanced Materials (doi.org/10.1002/adma.202301627), which validated the clinical feasibility of flexible piezoelectric blood pressure sensors, Professor Lee’s team conducted an in-depth review of the latest advancements in cuffless wearable sensors, focusing on key technical and clinical challenges. Their review highlights clinical aspects of clinical implementation, real-time data transmission, signal quality degradation, and AI algorithm accuracy. Professor Keon Jae Lee said, “This paper systematically demonstrates the feasibility of medical-grade wearable blood pressure sensors, overcoming what was previously considered an insurmountable challenge. We propose theoretical strategies to address technical barriers, opening new possibilities for future innovations in this field. With continued advancements, we expect these sensors to gain trust and be commercialized soon, significantly improving quality of life.” This review entitled “Wearable blood pressure sensors for cardiovascular monitoring and machine learning algorithms for blood pressure estimation” was published in the February 18 issue of Nature Reviews Cardiology (Impact Factor: 41.7). (doi.org/10.1038/s41569-025-01127-0) < Figure 1. Overview of wearable blood pressure sensor technologies for cardiovascular health care > [Reference] Min S. et al., (2025) “Wearable blood pressure sensors for cardiovascular monitoring and machine learning algorithms for blood pressure estimation.” Nature Reviews Cardiology (doi.org/10.1038/s41569-025-01127-0) [Main Author] Seongwook Min (Korea Advanced Institute of Science and Technology), Jaehun An (Korea Advanced Institute of Science and Technology), Jae Hee Lee (Northwestern University), * Contact email : Professor Keon Jae Lee (keonlee@kaist.ac.kr)
2025.03.04
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KAIST perfectly reproduces Joseon-era Irworobongdo without pigments
Typically, chemical pigments that absorb specific wavelengths of light within the visible spectrum are required to produce colors. However, KAIST researchers have successfully reproduced the Joseon-era Irworobongdo [일월오봉도] painting using ultra-precise color graphics without any chemical pigments, allowing for the permanent and eco-friendly preservation of color graphics without fading or discoloration. < (From left) Chaerim Son, a graduate of the Department of Biochemical Engineering (lead author), Seong Kyeong Nam, a graduate of the PhD program, Jiwoo Lee, a PhD student, and Professor Shin-Hyun Kim > KAIST (represented by President Kwang Hyung Lee) announced on the 26th of February that a research team led by Professor Shinhyun Kim from the Department of Biological and Chemical Engineering had developed a technology that enables high-resolution color graphics without using any chemical pigments by employing hemisphere-shaped microstructures. Morpho butterflies that are brilliant blue in color or Panther chameleons that change skin color exhibit coloration without chemical pigments, as ordered nanostructures within a material reflect visible light through optical interference. Since structural colors arise from physical structures rather than chemical substances, a single material can produce a wide range of colors. However, the artificial implementation of structural coloration is highly challenging due to the complexity of creating ordered nanostructures. Additionally, it is difficult to produce a variety of colors and to pattern them precisely into complex designs. < Figure 1. Principle of structural color expression using micro-hemispheres (left) and method of forming micro-hemisphere patterns based on photolithography (right) > Professor Kim’s team overcame these challenges by using smooth-surfaced hemispherical microstructures instead of ordered nanostructures, enabling the high-precision patterning of diverse structural colors. When light enters the inverted hemispherical microstructures, the portion of light entering from the sides undergoes total internal reflection along the curved surface, creating retroreflection. When the hemisphere diameter is approximately 10 micrometers (about one-tenth the thickness of a human hair), light traveling along different reflection paths interferes within the visible spectrum, producing structural coloration. < Figure 2. “Irworobongdo”, the Painting of the Sun, Moon, and the Five Peaks, reproduced in fingernail size without pigment using approximately 200,000 micro-hemispheres > The structural color can be tuned by adjusting the size of the hemispheres. By arranging hemispheres of varying sizes, much like mixing paints on a palette, an infinite range of colors can be generated. To precisely pattern microscale hemispheres of different sizes, the research team employed photolithography* using positive photoresists** commonly used in semiconductor processing. They first patterned photoresists into micropillar structures, then induced reflow*** by heating the material, forming hemispherical microstructures. *Photolithography: A technique used in semiconductor fabrication to pattern microscale structures. **Positive photoresist: A photosensitive polymer that dissolves more easily in a developer solution after exposure to ultraviolet light. ***Reflow: A process in which a polymer material softens and reshapes into a curved structure when heated. This method enables the formation of hemisphere-shaped microstructures with the desired sizes and colors in a single-step fabrication process. It also allows for the reproduction of arbitrary color graphics using a single material without any pigments. The ultra-precise color graphics created with this technique can exhibit color variations depending on the angle of incident light or the viewing perspective. The pattern appears colored from one direction while remaining transparent from the opposite side, exhibiting a Janus effect. These structural color graphics achieve resolution comparable to cutting-edge LED displays, allowing complex color images to be captured within a fingernail-sized area and projected onto large screens. < Figure 3. “Irworobongdo” that displays different shades depending on the angle of light and viewing direction > Professor Shinhyun Kim, who led the research, stated, “Our newly developed pigment-free color graphics technology can serve as an innovative method for artistic expression, merging art with advanced materials. Additionally, it holds broad application potential in optical devices and sensors, anti-counterfeiting materials, aesthetic photocard printing, and many other fields.” This research, with KAIST researcher Chaerim Son as the first author, was published in the prestigious materials science journal Advanced Materials on February 5. (Paper title: “Retroreflective Multichrome Microdome Arrays Created by Single-Step Reflow”, DOI: 10.1002/adma.202413143 ) < Figure 4. Famous paintings reproduced without pigment: “Impression, Sunrise” (left), “Girl with a Pearl Earring” (right) > The study was supported by the National Research Foundation of Korea through the Pioneer Converging Technology R&D Program and the Mid-Career Researcher Program.
2025.02.26
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KAIST Research Team Develops an AI Framework Capable of Overcoming the Strength-Ductility Dilemma in Additive-manufactured Titanium Alloys
<(From Left) Ph.D. Student Jaejung Park and Professor Seungchul Lee of KAIST Department of Mechanical Engineering and , Professor Hyoung Seop Kim of POSTECH, and M.S.–Ph.D. Integrated Program Student Jeong Ah Lee of POSTECH. > The KAIST research team led by Professor Seungchul Lee from Department of Mechanical Engineering, in collaboration with Professor Hyoung Seop Kim’s team at POSTECH, successfully overcame the strength–ductility dilemma of Ti 6Al 4V alloy using artificial intelligence, enabling the production of high strength, high ductility metal products. The AI developed by the team accurately predicts mechanical properties based on various 3D printing process parameters while also providing uncertainty information, and it uses both to recommend process parameters that hold high promise for 3D printing. Among various 3D printing technologies, laser powder bed fusion is an innovative method for manufacturing Ti-6Al-4V alloy, renowned for its high strength and bio-compatibility. However, this alloy made via 3D printing has traditionally faced challenges in simultaneously achieving high strength and high ductility. Although there have been attempts to address this issue by adjusting both the printing process parameters and heat treatment conditions, the vast number of possible combinations made it difficult to explore them all through experiments and simulations alone. The active learning framework developed by the team quickly explores a wide range of 3D printing process parameters and heat treatment conditions to recommend those expected to improve both strength and ductility of the alloy. These recommendations are based on the AI model’s predictions of ultimate tensile strength and total elongation along with associated uncertainty information for each set of process parameters and heat treatment conditions. The recommended conditions are then validated by performing 3D printing and tensile tests to obtain the true mechanical property values. These new data are incorporated into further AI model training, and through iterative exploration, the optimal process parameters and heat treatment conditions for producing high-performance alloys were determined in only five iterations. With these optimized conditions, the 3D printed Ti-6Al-4V alloy achieved an ultimate tensile strength of 1190 MPa and a total elongation of 16.5%, successfully overcoming the strength–ductility dilemma. Professor Seungchul Lee commented, “In this study, by optimizing the 3D printing process parameters and heat treatment conditions, we were able to develop a high-strength, high-ductility Ti-6Al-4V alloy with minimal experimentation trials. Compared to previous studies, we produced an alloy with a similar ultimate tensile strength but higher total elongation, as well as that with a similar elongation but greater ultimate tensile strength.” He added, “Furthermore, if our approach is applied not only to mechanical properties but also to other properties such as thermal conductivity and thermal expansion, we anticipate that it will enable efficient exploration of 3D printing process parameters and heat treatment conditions.” This study was published in Nature Communications on January 22 (https://doi.org/10.1038/s41467-025-56267-1), and the research was supported by the National Research Foundation of Korea’s Nano & Material Technology Development Program and the Leading Research Center Program.
2025.02.21
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Ultralight advanced material developed by KAIST and U of Toronto
< (From left) Professor Seunghwa Ryu of KAIST Department of Mechanical Engineering, Professor Tobin Filleter of the University of Toronto, Dr. Jinwook Yeo of KAIST, and Dr. Peter Serles of the University of Toronto > Recently, in advanced industries such as automobiles, aerospace, and mobility, there has been increasing demand for materials that achieve weight reduction while maintaining excellent mechanical properties. An international joint research team has developed an ultralight, high-strength material utilizing nanostructures, presenting the potential for various industrial applications through customized design in the future. KAIST (represented by President Kwang Hyung Lee) announced on the 18th of February that a research team led by Professor Seunghwa Ryu from the Department of Mechanical Engineering, in collaboration with Professor Tobin Filleter from the University of Toronto, has developed a nano-lattice structure that maximizes lightweight properties while maintaining high stiffness and strength. In this study, the research team optimized the beam shape of the lattice structure to maintain its lightweight characteristics while maximizing stiffness and strength. Particularly, using a multi-objective Bayesian optimization algorithm*, the team conducted an optimal design process that simultaneously considers tensile and shear stiffness improvement and weight reduction. They demonstrated that the optimal lattice structure could be predicted and designed with significantly less data (about 400 data points) compared to conventional methods. *Multi-objective Bayesian optimization algorithm: A method that finds the optimal solution while considering multiple objectives simultaneously. It efficiently collects data and predicts results even under conditions of uncertainty. < Figure 1. Multi-objective Bayesian optimization for generative design of carbon nanolattices with high compressive stiffness and strength at low density. The upper is the illustration of process workflow. The lower part shows top four MBO CFCC geometries with their 2D Bézier curves. (The optimized structure is predicted and designed with much less data (approximately 400) than the conventional method > Furthermore, to maximize the effect where mechanical properties improve as size decreases at the nanoscale, the research team utilized pyrolytic carbon* material to implement an ultralight, high-strength, high-stiffness nano-lattice structure. *Pyrolytic carbon: A carbon material obtained by decomposing organic substances at high temperatures. It has excellent heat resistance and strength, making it widely used in industries such as semiconductor equipment coatings and artificial joint coatings, where it must withstand high temperatures without deformation. For this, the team applied two-photon polymerization (2PP) technology* to precisely fabricate complex nano-lattice structures, and mechanical performance evaluations confirmed that the developed structure simultaneously possesses strength comparable to steel and the lightness of Styrofoam. *Two-photon polymerization (2PP) technology: An advanced optical manufacturing technique based on the principle that polymerization occurs only when two photons of a specific wavelength are absorbed simultaneously. Additionally, the research team demonstrated that multi-focus two-photon polymerization (multi-focus 2PP) technology enables the fabrication of millimeter-scale structures while maintaining nanoscale precision. Professor Seunghwa Ryu explained, "This technology innovatively solves the stress concentration issue, which has been a limitation of conventional design methods, through three-dimensional nano-lattice structures, achieving both ultralight weight and high strength in material development." < Figure 2. FESEM image of the fabricated nano-lattice structure and (bottom right) the macroscopic nanolattice resting on a bubble > He further emphasized, "By integrating data-driven optimal design with precision 3D printing technology, this development not only meets the demand for lightweight materials in the aerospace and automotive industries but also opens possibilities for various industrial applications through customized design." This study was led by Dr. Peter Serles of the Department of Mechanical & Industrial Engineering at University of Toronto and Dr. Jinwook Yeo from KAIST as co-first authors, with Professor Seunghwa Ryu and Professor Tobin Filleter as corresponding authors. The research was published on January 23, 2025 in the international journal Advanced Materials (Paper title: “Ultrahigh Specific Strength by Bayesian Optimization of Lightweight Carbon Nanolattices”). DOI: https://doi.org/10.1002/adma.202410651 This research was supported by the Multiphase Materials Innovation Manufacturing Research Center (an ERC program) funded by the Ministry of Science and ICT, the M3DT (Medical Device Digital Development Tool) project funded by the Ministry of Food and Drug Safety, and the KAIST International Collaboration Program.
2025.02.18
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Formosa Group of Taiwan to Establish Bio R&D Center at KAIST Investing 12.5 M USD
KAIST (President Kwang-Hyung Lee) announced on February 17th that it signed an agreement for cooperation in the bio-medical field with Formosa Group, one of the three largest companies in Taiwan. < Formosa Group Chairman Sandy Wang and KAIST President Kwang-Hyung Lee at the signing ceremony > Formosa Group Executive Committee member and Chairman Sandy Wang, who leads the group's bio and eco-friendly energy sectors, decided to establish a bio-medical research center within KAIST and invest approximately KRW 18 billion or more over 5 years. In addition, to commercialize the research results, KAIST and Formosa Group will establish a joint venture in Korea with KAIST Holdings, a KAIST-funded company. The cooperation between the two organizations began in early 2023 when KAIST signed a comprehensive exchange and cooperation agreement (MOU) with Ming Chi University of Science and Technology (明志科技大學), Chang Gung University (長庚大學), and Chang Gung Memorial Hospital (長庚記念醫院), which are established and supported by Formosa Group. Afterwards, Chairman Sandy Wang visited KAIST in May 2024 and signed a more specific business agreement (MOA). KAIST Holdings is a holding company established by KAIST, a government-funded organization, to attract investment and conduct business, and will pursue the establishment of a joint venture with a 50:50 equity structure in cooperation with Formosa Group. KAIST Holdings will invest KAIST’s intellectual property rights, and Formosa Group will invest a corresponding amount of funds. The KAIST-Formosa joint venture will provide research funds to the KAIST-Formosa Bio-Medical Research Center to be established in the future, secure the right to implement the intellectual property rights generated, and promote full-scale business. The KAIST-Formosa Bio-Medical Research Center will establish a ‘brain organoid bank’ created by obtaining tissues from hundreds of patients with degenerative brain diseases, thereby securing high-dimensional data that will reveal the fundamental causes of aging and disease. It is expected that KAIST’s world-class artificial intelligence technology will analyze large-scale patient data to find the causes of aging and disease. Through this business, it is expected that by 2030, five years from now, it will discover more than 10 types of intractable brain disease treatments and expand to more than 20 businesses, including human cell-centered diagnostics and preclinical businesses, and secure infrastructure and intellectual property rights that can create value worth approximately KRW 250 billion. The Chang Gung Memorial Hospital in Taiwan has 10,000 beds and handles 35,000 patients per day, and systematically accumulates patient tissue and clinical data. Chang Gung Memorial Hospital will differentiate the tissues of patients with degenerative brain diseases and send them to the KAIST-Formosa Bio-Medical Research Center, which will then produce brain organoids to be used for disease research and new drug development. This will allow the world’s largest patient tissue data bank to be established. Dean Daesoo Kim of the College of Life Science and Bioengineering at KAIST said, “This collaboration between KAIST and Formosa Group is a new research collaboration model that goes beyond joint research to establish a joint venture and global commercialization of developed technologies, and it is significant in that it can serve as an opportunity to promote biomedical research and development.” With this agreement, KAIST, which has been promoting the KAIST Advanced Regenerative Medicine Engineering Center in Osong K-Bio Square, has secured a practical global partner. < Representatives of the Formosa Group and KAIST > KAIST’s Senior Vice President for Planning and Budget, Professor Kyung-Soo Kim emphasized, “KAIST has made great efforts to secure an edge in state-of-the-art biomedical fields such as stem cells and gene editing technology, by attracting the world’s best experts and discovering global cooperation partners, and these results can ultimately be linked to the Osong K-Bio Square project.” SVP Kim then predicted, “In particular, the practical cooperation with Taiwan’s best Formosa Chang Gung Memorial Hospital, which has abundant clinical experience in stem cell treatment, will be an important axis of KAIST’s bio innovation strategy.” Formosa Chairman Sandy Wang emphasized that this investment and cooperation is built on trust in KAIST’s R&D capabilities and the passion of its researchers. And added that through this, the Formosa Group will practice corporate social responsibility and take an important first step together with KAIST to protect the welfare and health of humanity. She also went on the say that she expects to see the cooperation expanded to various fields such as mobility and semiconductors based on the successes begotten from the cooperation in the bio field. KAIST President Kwang-Hyung Lee said, “I evaluate this agreement as one of the most important events that will spearhead KAIST into overseas biotechnology stages,” and added, “I expect that this cooperation will be an opportunity for Taiwan and Korea, both of which have IT industry-centered structures, to create new growth engines in the bio industry.” Meanwhile, Formosa Group is a company founded by Chairman Sandy Wang’s father, Chairman Yung-Ching Wang. It is the world’s No. 1 plastic PVC producer and is leading core industries of the Taiwanese economy, including semiconductors, steel, heavy industry, bio, and batteries. Chairman Yung-Ching Wang was respected by the Taiwanese people for his exemplary return of wealth to society under the belief that the companies and assets he founded “belong to the people.”
2025.02.17
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KAIST Holds 2025 Commencement Ceremony
KAIST (President Kwang-Hyung Lee) held its 2025 Commencement Ceremony at the Lyu Keun-Chul Sports Complex on the Daejeon Main Campus at 2 p.m. on the 14th of February. < A scene from KAIST Commencement 2025 - Guests of Honor and Administrative Professors Entering the Stage headed by the color guards of the ELKA (Encouraging Leaders of KAIST) > At this ceremony, a total of 3,144 degrees were conferred, including 785 doctorates, 1,643 masters, and 716 bachelors. With this, KAIST has produced a total of 81,156 advanced science and technology personnel, including 17,313 doctorates, 41,566 masters, and 22,277 bachelors since its establishment in 1971. Changyu Lee from the School of Computing received the Minister of Science and ICT Award, and the Chairman of the KAIST Board of Trustees Award went to Lance Khizner Dabu Gragasin, an international student from the Philippines of the Department of Chemical and Biological Engineering. The President’s Award was given to Seoyeong Yang of the Department of Biological Sciences, and the Alumni Association President’s Award and the Development Foundation Chairman’s Award was given to Gahyeon Bae of the Department of Industrial Design and Buyeon Kim of the Department of Mechanical Engineering, respectively. Minister of Science and ICT Sang-Im Yoo joined the ceremony to deliver a congratulatory speech and to present the awards to outstanding graduates. < Minister Sang-Im Yoo of the Ministry of Science, Technology and ICT giving his congratulatory message at KAIST Commencement 2025 > The valedictorian speeches were given by Minjae Kim of the School of Computing, who has practiced the value of sharing that learning is not competition but cooperation, and Mohammed Haruna Hamza of the Department of Aerospace Engineering, a Nigerian international student. Mr. Hamza is the first foreign student to represent the graduating class as valedictorian since the founding of KAIST. Hamza lost his home and school in his home country due to a terrorist group’s bombing and moved south, but despite the adversity, he continued his studies while pursuing his dream of becoming an aerospace engineer. As a result of his efforts, Hamza was invited by the Korean government to study at KAIST. He expressed his determination to pursue his dream by saying, “I am grateful for the people and experiences that helped me overcome my adversity. The future is the result of the decisions we make today.” A Pakistani international student was chosen as one of this year's "Most Talked about Graduates of the Year". It is Ali Syed Sheraz who wore his doctoral cap at this year’s commencement ceremony. Ali, a single father who left his one-year-old son behind in his home country, working as a university lecturer. He joined the Ph.D. program in mechanical engineering in 2019 with a passion for mechanical energy. Ali’s academic journey was full of challenges and growth. Due to COVID-19, his research was suspended for six months, and he had difficulty continuing his studies undergoing three surgeries after a bicycle accident, including a surgery for a fractured elbow, a nose surgery, and removal of kidney stones. However, he accepted these failure and hardship as a process of growth and participated in the ‘Failed Project Showcase’ and ‘Failure Essay Contest’ held by the KAIST Failure Society, sharing his experiences and growing into a more solid researcher. < Most Talked about Graduate Graduate of the Year - Syed Sheraz Ali > Despite experiencing various hardships, he found lessons to learn from them and changed his perspective, which made him unafraid of taking on new challenges. He showed through his own example that failure is not just stumbling blocks but can be a stepping stone to success by looking at his studies and personal life positively. Furthermore, after becoming the president of the Muslim Student Association, Ali introduced halal menus to the cafeteria on campus so that more Muslim students could eat comfortably. Thanks to this change, his time at KAIST has become an opportunity to understand and experience various cultures more. Ali is researching artificial muscles (soft actuators) with the world's highest bending strain using MXene, an artificial muscle nanomaterial that can move smoothly, in Professor Il-kwon Oh's lab. Ali said, "After completing my Ph.D., I plan to develop soft robots, healthcare electronics, and next-generation tactile technology based on MXene, a next-generation 2D material. It is important for my juniors not to be afraid of failure and to have a challenging attitude." Another 'Most Talked about Graduate of the Year', Mr. Sung-Hyun Jung, who graduated with a master's degree from the Graduate School of Bio Innvation Management, is the CEO of Promedius, a medical AI startup, and has commercialized an osteoporosis diagnosis software based on chest X-rays using AI, and grown it into a leading company in the bone health field. CEO Jung's challenge shows that KAIST's management education is not just theoretical but practical enough to be applied immediately in the field. CEO Jung, who is also the father of three daughters, experienced business failure in China during the period when the conflict between Korea and China was intensifying. He moved to Silicon Valley in the United States to revive his business and tried to acquire even small businesses, but the reality was not easy. He worked hard, standing 14 hours a day in a kimchi factory and a restaurant kitchen to make a living. After finishing his life in the United States, CEO Jung returned to Korea and had the opportunity to join Lunit, a global medical AI leader founded by KAIST graduates. CEO Jung experienced the growth of the global medical AI market firsthand with unit Chairman Seungwook Paek. When he entered the Master's Program at the Graduate School of Bio Innvation Management in 2023 to acquire more specialized knowledge, CEO Jung had just transferred to Promedius and was in a crisis situation with only about 6 months left before the company's funds were exhausted. While considering a change in business direction because he judged that it would be difficult to survive with existing business items, he learned keywords and investment review perspectives that venture capital (VC) pays attention to in Professor Hoonje Cho’s ‘Bio-innovation Business Startup Strategy and Practice’ class. He attracted 11.4 billion won in investment by applying the investment proposal he wrote based on what he learned from the class to actual practice. < Most Talked about Graduate of the Year - Sung-Hyun Jung > In addition, he applied the innovation strategy in the medical field he learned in Professor Kihwan Park’s ‘Innovation and Marketing in Bio and Pharmaceutics’ to the field of osteoporosis, and achieved the result of being selected as the first Asian company to be a corporate advisory committee member of the International Osteoporosis Foundation (IOF). Through this, he established the company as a representative global entity in the osteoporosis field in just one year. CEO Jung, who applied what he learned from KAIST to actual management and achieved results in the global market in a short period of time, said, “I want to prove that KAIST education is not limited to theory, but is very practical.” He said, “I want to let people know that my life, once full of hardship, got on the track toward success after encountering KAIST,” and expressed his ambition, saying, “My long-term goal is to create a world-class company that is recognized globally.” In addition, an honorary doctorate was awarded to Chairman Joong Keun Lee of Booyoung Group at the commencement ceremony. Chairman Joong Keun Lee, who is an entrepreneur that led Booyoung Group, a leading general construction company, received the honorary doctorate in business administration, for leading the development of domestic housing welfare, education, and culture. KAIST Provost Gyunmin Lee said, “Chairman Joong Keun Lee spared no effort in providing dedicated support for the development of domestic science and technology and the cultivation of future talents. He is awarded the honorary doctorate in recognition of his social responsibility in various fields, including scholarships and support for educational facilities, as well as domestic and international education, culture, veterans affairs, and overseas support.” Since founding Booyoung Group in 1983, Chairman Lee has boldly entered the rental housing business, a field that large construction companies had avoided, and has played a significant role in improving the quality of life of ordinary citizens by supplying 230,000 households out of 383 complexes and approximately 300,000 households nationwide as rental housing, thereby contributing greatly to the stability of national housing. < Chairman Joong Keun Lee giving his acceptance speech for his honorary Doctorate > Chairman Joong Keun Lee, who has been offering hope for a sustainable future, said, “I am honored to receive an honorary doctorate from KAIST, and I hope that KAIST students will nurture their dreams and talents and grow into global talents who will contribute to national development.” President Kwang-Hyung Lee said, “Chairman Joong Keun Lee has been carrying out various social contribution activities, and in particular, through supporting academic infrastructure, which is the core of national competitiveness, we can see his deep interest in and sense of responsibility for the development of science and technology in our country.” He added, “I am truly delighted to have him as a member of the KAIST family, and I congratulate him on behalf of all members, including our students.” President Kwang-Hyung Lee also delivered a message of encouragement at the ceremony to charge the graduates to, “Find and keep a dream of your own, be on the lookout for opportunities, don’t be afraid of making mistakes, and do not shy away from taking on challenging tasks.” He added, “Even if you fail, don’t give up. Keep on trying so that you will get to that stage of radiate your own light on the stages where anything is possible.” (End)
2025.02.14
View 2397
KAIST Develops Wearable Carbon Dioxide Sensor to Enable Real-time Apnea Diagnosis
- Professor Seunghyup Yoo’s research team of the School of Electrical Engineering developed an ultralow-power carbon dioxide (CO2) sensor using a flexible and thin organic photodiode, and succeeded in real-time breathing monitoring by attaching it to a commercial mask - Wearable devices with features such as low power, high stability, and flexibility can be utilized for early diagnosis of various diseases such as chronic obstructive pulmonary disease and sleep apnea < Photo 1. From the left, School of Electrical Engineering, Ph.D. candidate DongHo Choi, Professor Seunghyup Yoo, and Department of Materials Science and Engineering, Bachelor’s candidate MinJae Kim > Carbon dioxide (CO2) is a major respiratory metabolite, and continuous monitoring of CO2 concentration in exhaled breath is not only an important indicator for early detection and diagnosis of respiratory and circulatory system diseases, but can also be widely used for monitoring personal exercise status. KAIST researchers succeeded in accurately measuring CO2 concentration by attaching it to the inside of a mask. KAIST (President Kwang-Hyung Lee) announced on February 10th that Professor Seunghyup Yoo's research team in the Department of Electrical and Electronic Engineering developed a low-power, high-speed wearable CO2 sensor capable of stable breathing monitoring in real time. Existing non-invasive CO2 sensors had limitations in that they were large in size and consumed high power. In particular, optochemical CO2 sensors using fluorescent molecules have the advantage of being miniaturized and lightweight, but due to the photodegradation phenomenon of dye molecules, they are difficult to use stably for a long time, which limits their use as wearable healthcare sensors. Optochemical CO2 sensors utilize the fact that the intensity of fluorescence emitted from fluorescent molecules decreases depending on the concentration of CO2, and it is important to effectively detect changes in fluorescence light. To this end, the research team developed a low-power CO2 sensor consisting of an LED and an organic photodiode surrounding it. Based on high light collection efficiency, the sensor, which minimizes the amount of excitation light irradiated on fluorescent molecules, achieved a device power consumption of 171 μW, which is tens of times lower than existing sensors that consume several mW. < Figure 1. Structure and operating principle of the developed optochemical carbon dioxide (CO2) sensor. Light emitted from the LED is converted into fluorescence through the fluorescent film, reflected from the light scattering layer, and incident on the organic photodiode. CO2 reacts with a small amount of water inside the fluorescent film to form carbonic acid (H2CO3), which increases the concentration of hydrogen ions (H+), and the fluorescence intensity due to 470 nm excitation light decreases. The circular organic photodiode with high light collection efficiency effectively detects changes in fluorescence intensity, lowers the power required light up the LED, and reduces light-induced deterioration. > The research team also elucidated the photodegradation path of fluorescent molecules used in CO2 sensors, revealed the cause of the increase in error over time in photochemical sensors, and suggested an optical design method to suppress the occurrence of errors. Based on this, the research team developed a sensor that effectively reduces errors caused by photodegradation, which was a chronic problem of existing photochemical sensors, and can be used continuously for up to 9 hours while existing technologies based on the same material can be used for less than 20 minutes, and can be used multiple times when replacing the CO2 detection fluorescent film. < Figure 2. Wearable smart mask and real-time breathing monitoring. The fabricated sensor module consists of four elements (①: gas-permeable light-scattering layer, ②: color filter and organic photodiode, ③: light-emitting diode, ④: CO2-detecting fluorescent film). The thin and light sensor (D1: 400 nm, D2: 470 nm) is attached to the inside of the mask to monitor the wearer's breathing in real time. > The developed sensor accurately measured CO2 concentration by being attached to the inside of a mask based on the advantages of being light (0.12 g), thin (0.7 mm), and flexible. In addition, it showed fast speed and high resolution that can monitor respiratory rate by distinguishing between inhalation and exhalation in real time. < Photo 2. The developed sensor attached to the inside of the mask > Professor Seunghyup Yoo said, "The developed sensor has excellent characteristics such as low power, high stability, and flexibility, so it can be widely applied to wearable devices, and can be used for the early diagnosis of various diseases such as hypercapnia, chronic obstructive pulmonary disease, and sleep apnea." He added, "In particular, it is expected to be used to improve side effects caused by rebreathing in environments where dust is generated or where masks are worn for long periods of time, such as during seasonal changes." This study, in which KAIST's Department of Materials Science and Engineering's undergraduate student Minjae Kim and School of Electrical Engineering's doctoral student Dongho Choi participated as joint first authors, was published in the online version of Cell's sister journal, Device, on the 22nd of last month. (Paper title: Ultralow-power carbon dioxide sensor for real-time breath monitoring) DOI: https://doi.org/10.1016/j.device.2024.100681 < Photo 3. From the left, Professor Seunghyup Yoo of the School of Electrical Engineering, MinJae Kim, an undergraduate student in the Department of Materials Science and Engineering, and Dongho Choi, a doctoral student in the School of Electrical Engineering > This study was supported by the Ministry of Trade, Industry and Energy's Materials and Components Technology Development Project, the National Research Foundation of Korea's Original Technology Development Project, and the KAIST Undergraduate Research Participation Project. This work was supported by the (URP) program.
2025.02.13
View 2470
KAIST Develops AI-Driven Performance Prediction Model to Advance Space Electric Propulsion Technology
< (From left) PhD candidate Youngho Kim, Professor Wonho Choe, and PhD candidate Jaehong Park from the Department of Nuclear and Quantum Engineering > Hall thrusters, a key space technology for missions like SpaceX's Starlink constellation and NASA's Psyche asteroid mission, are high-efficiency electric propulsion devices using plasma technology*. The KAIST research team announced that the AI-designed Hall thruster developed for CubeSats will be installed on the KAIST-Hall Effect Rocket Orbiter (K-HERO) CubeSat to demonstrate its in-orbit performance during the fourth launch of the Korean Launch Vehicle called Nuri rocket (KSLV-2) scheduled for November this year. *Plasma is one of the four states of matter, where gases are heated to high energies, causing them to separate into charged ions and electrons. Plasma is used not only in space electric propulsion but also in semiconductor manufacturing, display processes, and sterilization devices. On February 3rd, the research team from the KAIST Department of Nuclear and Quantum Engineering’s Electric Propulsion Laboratory, led by Professor Wonho Choe, announced the development of an AI-based technique to accurately predict the performance of Hall thrusters, the engines of satellites and space probes. Hall thrusters provide high fuel efficiency, requiring minimal propellant to achieve significant acceleration of spacecrafts or satellites while producing substantial thrust relative to power consumption. Due to these advantages, Hall thrusters are widely used in various space missions, including the formation flight of satellite constellations, deorbiting maneuvers for space debris mitigation, and deep space missions such as asteroid exploration. As the space industry continues to grow during the NewSpace era, the demand for Hall thrusters suited to diverse missions is increasing. To rapidly develop highly efficient, mission-optimized Hall thrusters, it is essential to predict thruster performance accurately from the design phase. However, conventional methods have limitations, as they struggle to handle the complex plasma phenomena within Hall thrusters or are only applicable under specific conditions, leading to lower prediction accuracy. The research team developed an AI-based performance prediction technique with high accuracy, significantly reducing the time and cost associated with the iterative design, fabrication, and testing of thrusters. Since 2003, Professor Wonho Choe’s team has been leading research on electric propulsion development in Korea. The team applied a neural network ensemble model to predict thruster performance using 18,000 Hall thruster training data points generated from their in-house numerical simulation tool. The in-house numerical simulation tool, developed to model plasma physics and thrust performance, played a crucial role in providing high-quality training data. The simulation’s accuracy was validated through comparisons with experimental data from ten KAIST in-house Hall thrusters, with an average prediction error of less than 10%. < Figure 1. This research has been selected as the cover article for the March 2025 issue (Volume 7, Issue 3) of the AI interdisciplinary journal, Advanced Intelligent Systems. > The trained neural network ensemble model acts as a digital twin, accurately predicting the Hall thruster performance within seconds based on thruster design variables. Notably, it offers detailed analyses of performance parameters such as thrust and discharge current, accounting for Hall thruster design variables like propellant flow rate and magnetic field—factors that are challenging to evaluate using traditional scaling laws. This AI model demonstrated an average prediction error of less than 5% for the in-house 700 W and 1 kW KAIST Hall thrusters and less than 9% for a 5 kW high-power Hall thruster developed by the University of Michigan and the U.S. Air Force Research Laboratory. This confirms the broad applicability of the AI prediction method across different power levels of Hall thrusters. Professor Wonho Choe stated, “The AI-based prediction technique developed by our team is highly accurate and is already being utilized in the analysis of thrust performance and the development of highly efficient, low-power Hall thrusters for satellites and spacecraft. This AI approach can also be applied beyond Hall thrusters to various industries, including semiconductor manufacturing, surface processing, and coating, through ion beam sources.” < Figure 2. The AI-based prediction technique developed by the research team accurately predicts thrust performance based on design variables, making it highly valuable for the development of high-efficiency Hall thrusters. The neural network ensemble processes design variables, such as channel geometry and magnetic field information, and outputs key performance metrics like thrust and prediction accuracy, enabling efficient thruster design and performance analysis. > Additionally, Professor Choe mentioned, “The CubeSat Hall thruster, developed using the AI technique in collaboration with our lab startup—Cosmo Bee, an electric propulsion company—will be tested in orbit this November aboard the K-HERO 3U (30 x 10 x 10 cm) CubeSat, scheduled for launch on the fourth flight of the KSLV-2 Nuri rocket.” This research was published online in Advanced Intelligent Systems on December 25, 2024 with PhD candidate Jaehong Park as the first author and was selected as the journal’s cover article, highlighting its innovation. < Figure 3. Image of the 150 W low-power Hall thruster for small and micro satellites, developed in collaboration with Cosmo Bee and the KAIST team. The thruster will be tested in orbit on the K-HERO CubeSat during the KSLV-2 Nuri rocket’s fourth launch in Q4 2025. > This research was supported by the National Research Foundation of Korea’s Space Pioneer Program (200mN High Thrust Electric Propulsion System Development). (Paper Title: Predicting Performance of Hall Effect Ion Source Using Machine Learning, DOI: https://doi.org/10.1002/aisy.202400555 ) < Figure 4. Graphs of the predicted thrust and discharge current of KAIST’s 700 W Hall thruster using the AI model (HallNN). The left image shows the Hall thruster operating in KAIST Electric Propulsion Laboratory’s vacuum chamber, while the center and right graphs present the prediction results for thrust and discharge current based on anode mass flow rate. The red lines represent AI predictions, and the blue dots represent experimental results, with a prediction error of less than 5%. >
2025.02.03
View 2615
KAIST Uncovers the Principles of Gene Expression Regulation in Cancer and Cellular Functions
< (From left) Professor Seyun Kim, Professor Gwangrog Lee, Dr. Hyoungjoon Ahn, Dr. Jeongmin Yu, Professor Won-Ki Cho, and (below) PhD candidate Kwangmin Ryu of the Department of Biological Sciences> A research team at KAIST has identified the core gene expression networks regulated by key proteins that fundamentally drive phenomena such as cancer development, metastasis, tissue differentiation from stem cells, and neural activation processes. This discovery lays the foundation for developing innovative therapeutic technologies. On the 22nd of January, KAIST (represented by President Kwang Hyung Lee) announced that the joint research team led by Professors Seyun Kim, Gwangrog Lee, and Won-Ki Cho from the Department of Biological Sciences had uncovered essential mechanisms controlling gene expression in animal cells. Inositol phosphate metabolites produced by inositol metabolism enzymes serve as vital secondary messengers in eukaryotic cell signaling systems and are broadly implicated in cancer, obesity, diabetes, and neurological disorders. The research team demonstrated that the inositol polyphosphate multikinase (IPMK) enzyme, a key player in the inositol metabolism system, acts as a critical transcriptional activator within the core gene expression networks of animal cells. Notably, although IPMK was previously reported to play an important role in the transcription process governed by serum response factor (SRF), a representative transcription factor in animal cells, the precise mechanism of its action was unclear. SRF is a transcription factor directly controlling the expression of at least 200–300 genes, regulating cell growth, proliferation, apoptosis, and motility, and is indispensable for organ development, such as in the heart. The team discovered that IPMK binds directly to SRF, altering the three-dimensional structure of the SRF protein. This interaction facilitates the transcriptional activity of various genes through the SRF activated by IPMK, demonstrating that IPMK acts as a critical regulatory switch to enhance SRF's protein activity. < Figure 1. The serum response factor (SRF) protein, a key transcription factor in animal cells, directly binds to inositol polyphosphate multikinase (IPMK) enzyme and undergoes structural change to acquire DNA binding ability, and precisely regulates growth and differentiation of animal cells through transcriptional activation. > The team further verified that disruptions in the direct interaction between IPMK and SRF lead to the reduced functionality and activity of SRF, causing severe impairments in gene expression. By highlighting the significance of the intrinsically disordered region (IDR) in SRF, the researchers underscored the biological importance of intrinsically disordered proteins (IDPs). Unlike most proteins that adopt distinct structures through folding, IDPs, including those with IDRs, do not exhibit specific structures but play crucial biological roles, attracting significant attention in the scientific community. Professor Seyun Kim commented, "This study provides a vital mechanism proving that IPMK, a key enzyme in the inositol metabolism system, is a major transcriptional activator in the core gene expression network of animal cells. By understanding fundamental processes such as cancer development and metastasis, tissue differentiation from stem cells, and neural activation through SRF, we hope this discovery will lead to the broad application of innovative therapeutic technologies." The findings were published on January 7th in the international journal Nucleic Acids Research (IF=16.7, top 1.8% in Biochemistry and Molecular Biology), under the title “Single-molecule analysis reveals that IPMK enhances the DNA-binding activity of the transcription factor SRF" (DOI: 10.1093/nar/gkae1281). This research was supported by the National Research Foundation of Korea's Mid-career Research Program, Leading Research Center Program, and Global Research Laboratory Program, as well as by the Suh Kyungbae Science Foundation and the Samsung Future Technology Development Program.
2025.01.24
View 6355
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