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KAIST Opens the Era of Industrial-Scale Microbial Foods, Proposing Growth Strategies for the Next-Generation Protein Market
The question is no longer whether microbial foods can be made. The question now is who can turn them into an industry first. KAIST researchers have comprehensively analyzed the conditions required for the microbial food industry to succeed across manufacturing, markets, and regulation, and have proposed growth strategies for the next-generation protein industry.
KAIST (President Choongsik Bae) announced on the 31st of July that a research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering, together with researchers from SilicoBio, a KAIST faculty startup, has comprehensively analyzed the conditions needed for the microbial food industry to succeed in terms of manufacturing, market entry, and regulatory readiness, and has presented an industrialization strategy and roadmap.
This study is significant in that it did not develop a new microorganism or production technology, but instead systematically analyzed the key challenges involved in connecting laboratory-based core technologies to real-world industry. In particular, by presenting an integrated perspective that encompasses manufacturing readiness, market entry strategies, and regulatory responses, the study proposes a direction for developing microbial foods beyond the next-generation protein industry into a future biomanufacturing platform. It is expected to serve as an important milestone for strengthening national biomanufacturing competitiveness and fostering the global sustainable food industry.
The researchers analyzed that competition in the microbial food industry is shifting from productivity at the laboratory level to manufacturing readiness. They identified stable raw material supply and quality control, control and safety assurance of non-model microorganisms, reduction of downstream processing costs, and regulatory compliance for byproduct recycling as key factors that will determine the pace of commercialization. Manufacturing Readiness refers to the level at which a laboratory technology can be reliably produced at industrial scale. Non-model microorganisms are microorganisms with high industrial potential but insufficient accumulated research infrastructure. Downstream processing refers to the processes of separating, purifying, concentrating, and drying target components after fermentation.
The researchers particularly emphasized that future competitiveness will depend less on the excellence of any single technology and more on the ability to build integrated manufacturing platforms. An Integrated Manufacturing Platform refers to a production system that operates the entire process as one connected framework, from strain development and large-scale fermentation to purification, quality control, and product formulation. Even for the same microbial food product, the choice of raw material can affect pretreatment costs and quality variability, while the choice of strain and fermentation process can greatly influence production cost, energy use, and product quality. The researchers therefore concluded that future industrial competitiveness will depend on how quickly companies can build manufacturing platforms that optimize these factors in an integrated way.
On the market side, the researchers also identified the conditions needed for the microbial food industry to succeed. Based on consumer surveys and industry cases, they found that microbial foods cannot spread simply by emphasizing environmental sustainability. Consumers place importance on taste, texture, familiarity, and safety, while food manufacturers value functionality that can be applied to actual products. Companies and investors, meanwhile, consider the predictability of regulatory approval procedures and speed of market entry to be especially important. In other words, the microbial food market has entered an industrial stage where not only technology, but also product development capability and regulatory readiness are evaluated together.
The researchers also argued that microbial foods should not be viewed merely as an alternative protein industry. They suggested that microbial foods have the potential to develop into a core platform for precision fermentation-based functional food ingredients, high-value biomaterials, and circular biomanufacturing. Precision Fermentation is a technology that uses microorganisms to selectively produce specific proteins or functional substances. Circular Biomanufacturing refers to a sustainable manufacturing system that uses byproducts and renewable resources to produce new bio-based products. This means that microbial foods could become not only a future food source, but also a new production system connecting the global food, materials, and biomanufacturing industries.
The industrialization strategy proposed in this study is also closely aligned with the business direction of SilicoBio, which participated in the joint research. Based on the manufacturing readiness strategy presented in the study, SilicoBio is working to build a platform that connects microbial proteins and functional food ingredients to industrial-scale fermentation, scale-up, and product development. Scale-up refers to the process of expanding production from laboratory scale to industrial scale.
Distinguished Professor Sang Yup Lee of KAIST said, “As global competition surrounding synthetic biology and biomanufacturing intensifies, microbial foods are growing into a key industry that will shape national biomanufacturing competitiveness beyond future food.” He added, “Going forward, competitiveness will be determined by how quickly we can build an industrialization ecosystem that connects core technologies to real production and markets.”
A SilicoBio representative said, “Our goal is to connect the industrialization strategy proposed in this study to actual production and commercialization,” adding, “We will build a platform capable of stably producing microbial-based next-generation foods and functional biomaterials.”
This study, with Seok Yeong Jung, a doctoral student in the Department of Chemical and Biomolecular Engineering, as first author and researchers from SilicoBio participating as co-authors, was published on July 17 in the international journal One Earth (Impact Factor 15.3, JCR top 2.07%).
Paper title: Microbial foods as scalable platforms toward a circular protein economy for sustainable nutrition
DOI: https://doi.org/10.1016/j.oneear.2026.101772
Authors: Sang Yup Lee (KAIST, corresponding author), Seok Yeong Jung (KAIST, first author), Sol Choi (SilicoBio, second author), Jun-Woo Kim (SilicoBio and Inha University, third author), and two others
SilicoBio is a KAIST faculty startup founded in June 2025 by Distinguished Professor Sang Yup Lee, a world-renowned scholar in synthetic biology. The company focuses on connecting laboratory-level achievements in systems metabolic engineering to real industrialization. By combining KAIST’s core technologies with the industrialization experience of personnel from CJ BIO, SilicoBio has built a team capable of reviewing not only strain design, but also industrial-scale fermentation and scale-up, material purification and product development, pilot production, and process validation. Based on this foundation, SilicoBio is pursuing a phased commercialization strategy, starting with next-generation protein products and expanding into functional ingredients and eventually new drug and novel material candidates.
This research was supported by the “Development of Next-Generation Biorefinery Core Technologies to Lead the Biochemical Industry” project under the Petroleum-Alternative Eco-Friendly Chemical Technology Development Program funded by the Ministry of Science and ICT, and by the “Advancement of a Synthetic Biology-Based Industrial Cell Factory Platform and Commercialization of High-Value Functional Biomaterials” project under the Deep Science Startup Activation Support Program funded by the Commercialization Promotion Agency for R&D Outcome.
2026.08.31 View 311 -
KAIST Professor Sooel Son Selected for Microsoft Funding for AI Safety and Security Research
KAIST (President Choongsik Bae) announced on the 28th of July that Professor Sooel Son has been selected as the only researcher in Korea to receive funding from Microsoft for research on artificial intelligence safety and security.
The funding was awarded through the External Red Team Alliance (EXTRA), a new program established by Microsoft’s AI Red Team, which examines the safety and security vulnerabilities of AI systems. EXTRA is a global initiative designed to strengthen AI safety and security research capabilities by supporting researchers at universities and technology experts around the world.
Microsoft noted that most AI safety testing is still conducted internally by individual companies or organizations. However, assessing the major risks posed by increasingly advanced AI systems requires expertise across a broad range of fields, including cybersecurity, multilingual environments, regional and cultural contexts, AI alignment, and potential misuse. EXTRA was launched in recognition of the difficulty a single internal organization faces when comprehensively evaluating these diverse risks.
Through the program, Microsoft will provide KAIST with an unrestricted gift of USD 25,000, approximately KRW 37 million, with no prescribed project period, to support research related to AI safety, security, alignment, and responsible AI development. The funding will be used to support Professor Son’s research team in its work on AI security and safety.
More than a dozen universities across six continents are participating in EXTRA, with KAIST being the only university selected from Korea. Through the program, Microsoft plans to expand the ecosystem for independent AI safety research and strengthen collaboration between academia and industry.
Professor Son’s research team has been conducting research on the security and privacy of AI systems that use machine-learning models and large language models. In particular, the team analyzes adversarial attacks against deep neural networks and language models—including model extraction, membership inference, personal information extraction, model inversion, machine unlearning, and prompt injection—and develops defense methodologies to assess and improve model safety.
Building on these technologies, the team is also focusing on establishing systematic defense methodologies that enable the safe and trustworthy deployment of agentic AI systems operating in real-world service environments, including web agents and agentic browsers.
“As AI systems rapidly spread throughout society, research that verifies the security and reliability of increasingly advanced AI is becoming more important,” said Professor Son. “Our participation in Microsoft AI Red Team’s EXTRA program will provide an opportunity to further advance our research on the safe development and use of AI systems.”
“AI safety research has never been more important, and universities have a critical role to play in advancing the field,” said Ram Shankar Siva Kumar, who leads the Microsoft AI Red Team. “Through EXTRA, we aim to support researchers working to deepen our understanding of how increasingly powerful AI systems can be evaluated, protected, and governed responsibly.”
“Competition in AI technology is expanding beyond performance to encompass safety and trustworthiness,” said KAIST President Choongsik Bae. “KAIST’s participation as the only Korean research institution in Microsoft’s global AI safety research network is a meaningful achievement that demonstrates Korea’s competitiveness in AI research. We will continue to lead the advancement of responsible AI technologies that everyone can trust and use by pursuing world-class research in AI safety and security.”
2026.07.28 View 1826 -
KAIST Brings the Era of Microbial Cell Factories One Step Closer
The era of "biomanufacturing", in which microbes, not petroleum, produce chemical products, is one step closer. A KAIST research team has analyzed the key challenges limiting the commercialization of biomanufacturing and proposed an AI-driven strategy for industrialization.
KAIST (President Choongsik Bae) announced on the 14th of July that a research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering has comprehensively analyzed the key bottlenecks to commercializing biomanufacturing and proposed an industrialization strategy and a roadmap for future growth to address them.
Most chemical products today — including plastics, textiles, and pharmaceutical raw materials — are produced from petroleum. But as concerns over carbon emissions and environmental pollution grow, biomanufacturing, which uses microbes to produce chemicals, is drawing attention as a next-generation manufacturing technology. Still, scaling up lab-developed technologies into economically viable mass production at actual factories remains a major challenge.
Systems metabolic engineering, a core technology in biomanufacturing, designs and optimizes microbial metabolic pathways to build "microbial cell factories" that produce desired chemicals. But technologies that show high productivity in the lab often perform worse once moved to industrial settings — productivity drops, production costs rise, and many fail to achieve price competitiveness, ultimately failing to commercialize.
The research team analyzed succinic acid, a bio-based chemical feedstock, and polyhydroxyalkanoate (PHA), a biodegradable plastic, as representative cases illustrating this "gap between the lab and industry," often called the "valley of death."
Succinic acid is a key raw material for producing eco-friendly plastics and various chemical materials. The team explained that for succinic acid to compete with existing petrochemical products, competitiveness depends not just on production volume, but also on raw material and separation/purification costs, the fermentation process, and market size — all of which must be weighed together. The team also suggested that a phased strategy — entering high-value markets such as pharmaceuticals, cosmetics, and food ingredients first — could be a realistic solution.
PHA is a biodegradable plastic that microbes accumulate inside their cells, an eco-friendly material that breaks down naturally in the environment after use. But PHA is currently less price-competitive than conventional plastics due to high production and recovery costs, and its intrinsic material properties pose a separate barrier: the archetypal polymer P(3HB) is highly crystalline, becomes brittle with age, and has a narrow window between its melting and decomposition temperatures, meaning PHAs are generally not suitable as direct "drop-in" replacements.The team found that a phased approach is needed — simplifying the production process and first applying it to high-value fields such as medical applications and food packaging before expanding into general-purpose markets.
The team predicted that artificial intelligence will become a key to industrializing biomanufacturing going forward. AI can optimize the entire biomanufacturing process — from enzyme and microbial design to digital twins that virtually simulate production processes, and technologies that simultaneously analyze economic feasibility and environmental impact. The team explained that this can shorten development timelines, reduce production costs, and increase the likelihood of successful commercialization.
The team also proposed that techno-economic analysis (TEA) and life cycle assessment (LCA) should be applied as design criteria from the earliest stages of research, rather than as evaluations conducted only after research is complete. The team further emphasized that supply chain resilience — accounting for raw material availability and shifts in the international landscape — should be considered a new design standard for biomanufacturing.
This study is significant not for developing a new production technology, but for comprehensively analyzing the conditions for successful biomanufacturing industrialization and presenting an industrialization roadmap spanning the entire cycle — from securing raw materials to microbial design, fermentation, separation and purification, and market entry. The team expects the study to accelerate the commercialization of the bio-based chemical industry and, over the long term, contribute to shifting the petroleum-centered chemical industry toward an eco-friendly bioeconomy.
The paper, with Ji Yeon Kim and Hye Eun Yu as co-first authors, both Ph.D. candidates in KAIST's Department of Chemical and Biomolecular Engineering, was published online on May 30 in the international journal Nature Communications.
※ Paper title: Beyond petrochemicals: challenges and opportunities in industrial-scale biomanufacturing
※ DOI: 10.1038/s41467-026-73835-1
※ Authors: Ji Yeon Kim (KAIST, co-first author), Hye Eun Yu (KAIST, co-first author), Min Ho Kim (KAIST), Sang Yup Lee (KAIST, corresponding author)
This research was supported by the National Research Foundation of Korea, funded by the Ministry of Science and ICT, through the “Development of Platform Technologies of Microbial Cell Factories for Next-Generation Biorefineries” project (Project No. 2022M3J5A1056117) and the “Development of Advanced Synthetic Biology Source Technologies for Leading the Biomanufacturing Industry” project (Project No. RS-2024-00399424).
2026.07.14 View 1287 -
European Academy of Microbiology welcomes 95 new Fellows
<KAIST Distinguished Professor Sang Yup Lee>
The European Academy of Microbiology (EAM) is pleased to announce the election of 95 new Fellows, recognising scientific excellence and long-standing contributions to microbiology.
The newly elected Fellows represent a diverse range of expertise across microbiology and related disciplines, spanning institutions across Europe and beyond. Their work reflects the breadth and dynamism of the field, from fundamental microbial research to applied innovations addressing global challenges in health, environment, and biotechnology.
Election to the EAM Fellowship recognises outstanding scientific achievement and leadership in microbiology. Fellows are selected through a rigorous nomination and evaluation process by existing members of the Academy.
With the addition of these new Fellows in different areas of microbiology from Europe and beyond, the EAM continues to strengthen its network of leading microbiologists. As Fellows of the Academy, members are committed to advancing knowledge, fostering collaboration, and supporting the next generation of scientists. Together they promote the visibility, impact and rapid progress of microbiology across the world.
Reflecting strength and diversity of microbiology
Commenting on the election, the EAM President Prof. Cecília M. Arraiano said:
“We are delighted to welcome this new group of Fellows to the European Academy of Microbiology. Their achievements and expertise reflect the strength and diversity of microbiology. The Academy thrives through the engagement of its Fellows, and we look forward to the perspectives and contributions they will bring to shape the future of microbial science.”
See the full list of the newly elected Fellows.
About the European Academy of Microbiology (EAM)
The European Academy of Microbiology, is part of the Federation of European Microbiological Societies (FEMS) network, and brings together eminent microbiologists whose work has significantly advanced the field. Through the collective expertise of its Fellows, the Academy contributes to scientific dialogue, supports emerging priorities in microbiology, and helps amplify the impact of microbiological research for society.
2026.03.20 View 1975 -
KAIST Proposes AI-Driven Strategy to Solve Long-Standing Mystery of Gene Function
<(From Left) Distinguisehd Professor Sang Yup Lee, Dr. Gi Bae Kim, Professor Bernhard O. Palsson>
“We know the genes, but not their functions.” To resolve this long-standing bottleneck in microbial research, a joint research team has proposed a cutting-edge research strategy that leverages Artificial Intelligence (AI) to drastically accelerate the discovery of microbial gene functions.
KAIST announced on January 12th that a research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering, in collaboration with Professor Bernhard Palsson from the Department of Bioengineering at UCSD, has published a comprehensive review paper. The study systematically analyzes and organizes the latest AI-based research approaches aimed at revolutionizing the speed of gene function discovery.
Since the early 2000s, when whole-genome sequencing became a reality, there were high expectations that the genetic blueprint of life would be fully decoded. However, even twenty years later, the roles of a significant portion of genes within microbial genomes remain unknown.
While various experimental methods—such as gene deletion, analysis of gene expression profiles, and in vitro activity assays—have been employed, discovering gene functions remains a time-consuming and costly endeavor. This is primarily due to the limitations of large-scale experimentation, complex biological interactions, and the discrepancy between laboratory results and actual in vivo responses.
To overcome these hurdles, the research team emphasized that an AI-driven approach combining computational biology with experimental biology is essential.
In this paper, the team provides a comprehensive overview of computational biology approaches that have facilitated gene function discovery, ranging from traditional sequence similarity analysis to the latest deep-learning-based AI models.
Notably, 3D protein structure prediction technologies such as AlphaFold (developed by Google DeepMind) and RoseTTAFold (developed by the University of Washington) have opened new doors. These tools go beyond simple functional estimation, offering the potential to understand the underlying mechanisms of how gene functions operate. Furthermore, generative AI is now extending research boundaries toward designing proteins with specifically desired functions.
Focusing on transcription factors (proteins that act as genetic switches) and enzymes (proteins that catalyze chemical reactions), the team presented various application cases and future research directions that integrate gene sequence analysis, protein structure prediction, and diverse metagenomic analyses.
<Schematic illustration of computational biology methods for enzyme function prediction>
2026.01.12 View 3899 -
KAIST Unlocks the Secret of Next-Generation Memory
<(From Left) Professor Sang-Hee Ko Park, Ph.D candidate Sunghwan Park, Ph.D candidate Chaewon Gong, Professor Seungbum Hong>
Resistive Random Access Memory (ReRAM), which is based on oxide materials, is gaining attention as a next-generation memory and neuromorphic computing device. Its fast speeds, data retention ability, and simple structure make it a promising candidate to replace existing memory technologies. KAIST researchers have now clarified the operating principle of this memory, which is expected to provide a key clue for the development of high-performance, high-reliability next-generation memory.
KAIST (President Kwang Hyung Lee) announced on the 2nd of September that a research team led by Professor Seungbum Hong from the Department of Materials Science and Engineering, in collaboration with a research team led by Professor Sang-Hee Ko Park from the same department, has for the first time in the world precisely clarified the operating principle of an oxide-based memory device, which is drawing attention as a core technology for next-generation semiconductors.
Using a 'Multi-modal Scanning Probe Microscope (Multi-modal SPM)' that combines several types of microscopes*, the research team succeeded in simultaneously observing the electron flow channels inside the oxide thin film, the movement of oxygen ions, and changes in surface potential (the distribution of charge on the material's surface). Through this, they clarified the correlation between how current changes and how oxygen defects change during the process of writing and erasing information in the memory.
*Several types of microscopes: Conductive atomic force microscopy (C-AFM) for observing current flow, electrochemical strain microscopy (ESM) for observing oxygen ion movement, and Kelvin probe force microscopy (KPFM) for observing potential changes.
With this special equipment, the research team directly implemented the process of writing and erasing information in the memory by applying an electrical signal to a titanium dioxide (TiO2) thin film, confirming at the nano-level that the reason for the current changes was the variation in the distribution of oxygen defects.
In this process, they confirmed that the current flow changes depending on the amount and location of oxygen defects. For example, when there are more oxygen defects, the electron pathway widens, and the current flows well, but conversely, when they scatter, the current is blocked. Through this, they succeeded in precisely visualizing that the distribution of oxygen defects within the oxide determines the on/off state of the memory.
<Overview of the Research Process. By using one of the SPM modes, C-AFM (Conductive Atomic Force Microscopy), resistive switching corresponding to the electroforming and reset processes is induced in a 10 nm-thick TiO₂ thin film, and the resulting local current variations caused by the applied electric field are observed. Subsequently, at the same location, ESM (Electrochemical Strain Microscopy) and KPFM (Kelvin Probe Force Microscopy) signals are comprehensively analyzed to investigate and interpret the spatial correlation of ion-electronic behaviors that influence the resistive switching phenomenon>
This research was not limited to the distribution at a single point but comprehensively analyzed the changes in current flow, the movement of oxygen ions, and the surface potential distribution after applying an electrical signal over a wide area of several square micrometers (µm2). As a result, they clarified that the process of the memory's resistance changing is not solely due to oxygen defects but is also closely intertwined with the movement of electrons (electronic behavior).
In particular, the research team confirmed that when oxygen ions are injected during the 'erasing process (reset process)', the memory can stably maintain its off state (high resistance state) for a long time. This is a core principle for increasing the reliability of memory devices and is expected to provide an important clue for the future development of stable, next-generation non-volatile memory.
Professor Seungbum Hong of KAIST, who led the research, said, "This is an example that proves we can directly observe the spatial correlation of oxygen defects, ions, and electrons through a multi-modal microscope." He added, "It is expected that this analysis technique will open a new chapter in the research and development of various metal oxide-based next-generation semiconductor devices in the future."
<By combining C-AFM and ESM techniques, the correlation between local conductivity and variations in oxygen vacancy concentration after resistive switching is analyzed. After the electroforming process, regions with increased conductivity exhibit an enhancement in the ESM amplitude signal, which can be interpreted as an increase in defect ion concentration. Conversely, after the reset process, regions with reduced conductivity show a corresponding decrease in this signal. Through these observations, it is spatially demonstrated that changes in conductivity and local defect ion concentration after resistive switching exhibit a positive correlation>
This research, in which Ph.D. candidate Chaewon Gong from the KAIST Department of Materials Science and Engineering participated as the first author, was published on July 20 in 'ACS Applied Materials and Interfaces', a prestigious academic journal in the field of new materials and chemical engineering published by the American Chemical Society (ACS).
※ Paper Title: Spatially Correlated Oxygen Vacancies, Electrons and Conducting Paths in TiO2 Thin Films
This research was carried out with the support of the Ministry of Science and ICT and the National Research Foundation of Korea.
2025.09.02 View 3899 -
A KAIST Team Engineers a Microbial Platform for Efficient Lutein Production
<(From Left) Ph.D. Candidate Hyunmin Eun, Distinguished Professor Sang Yup Lee, , Dr. Cindy Pricilia Surya Prabowo>
The application of systems metabolic engineering strategies, along with the construction of an electron channeling system, has enabled the first gram-per-liter scale production of lutein from Corynebacterium glutamicum, providing a viable alternative to plant-derived lutein production.
A research group at KAIST has successfully engineered a microbial strain capable of producing lutein at industrially relevant levels. The team, led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering, developed a novel C. glutamicum strain using systems metabolic engineering strategies to overcome the limitations of previous microbial lutein production efforts. This research is expected to be beneficial for the efficient production of other industrially important natural products used in food, pharmaceuticals, and cosmetics.
Lutein is a xanthophyll carotenoid found in egg yolk, fruits, and vegetables, known for its role in protecting our eyes from oxidative stress and reducing the risk of macular degeneration and cataracts. Currently, commercial lutein is predominantly extracted from marigold flowers; however, this approach has several drawbacks, including long cultivation times, high labor costs, and inefficient extraction yields, making it economically unfeasible for large-scale production. These challenges have driven the demand for alternative production methods.
To address these issues, KAIST researchers, including Ph.D. Candidate Hyunmin Eun, Dr. Cindy Pricilia Surya Prabowo, and Distinguished Professor Sang Yup Lee, applied systems metabolic engineering strategies to engineer C. glutamicum, a GRAS (Generally Recognized As Safe) microorganism widely used in industrial fermentation. Unlike Escherichia coli, which was previously explored for microbial lutein production, C. glutamicum lacks endotoxins, making it a safer and more viable option for food and pharmaceutical applications.
The team’s work, entitled “Gram-per-litre scale production of lutein by engineered Corynebacterium,” was published in Nature Synthesis on 04 July , 2025.
This research details the high-level production of lutein using glucose as a renewable carbon source via systems metabolic engineering. The team focused on eliminating metabolic bottlenecks that previously limited microbial lutein synthesis. By employing enzyme scaffold-based electron channeling strategies, the researchers improved metabolic flux towards lutein biosynthesis while minimizing unwanted byproducts.
<Lutein production metabolic pathway engineering>
To enhance productivity, bottleneck enzymes within the metabolic pathway were identified and optimized. It was determined that electron-requiring cytochrome P450 enzymes played a major role in limiting lutein biosynthesis. To overcome this limitation, an electron channeling strategy was implemented, where engineered cytochrome P450 enzymes and their reductase partners were spatially organized on synthetic scaffolds, allowing more efficient electron transfer and significantly increasing lutein production.
The engineered C. glutamicum strain was further optimized in fed-batch fermentation, achieving a record-breaking 1.78 g/L of lutein production within 54 hours, with a content of 19.51 mg/gDCW and a productivity of 32.88 mg/L/h—the highest lutein production performance in any host reported to date. This milestone demonstrates the feasibility of replacing plant-based lutein extraction with microbial fermentation technology.
“We can anticipate that this microbial cell factory-based mass production of lutein will be able to replace the current plant extraction-based process,” said Ph.D. Candidate Hyunmin Eun. He emphasized that the integrated metabolic engineering strategies developed in this study could be broadly applied for the efficient production of other valuable natural products used in pharmaceuticals and nutraceuticals.
<Schematic diagram of microbial-based lutein production platform>
“As maintaining good health in an aging society becomes increasingly important, we expect that the technology and strategies developed here will play pivotal roles in producing other medically and nutritionally significant natural products,” added Distinguished Professor Sang Yup Lee.
This work is supported by the Development of Next-generation Biorefinery Platform Technologies for Leading Bio-based Chemicals Industry project 2022M3J5A1056072 and the Development of Platform Technologies of Microbial Cell Factories for the Next-Generation Biorefineries project 2022M3J5A1056117 from the National Research Foundation supported by the Korean Ministry of Science and ICT.
Source:
Hyunmin Eun (1st), Cindy Pricilia Surya Prabowo (co-1st), and Sang Yup Lee (Corresponding). “Gram-per-litre scale production of lutein by engineered Corynebacterium”. Nature Synthesis (Online published)
For further information:
Sang Yup Lee, Distinguished Professor of Chemical and Biomolecular Engineering, KAIST (leesy@kaist.ac.kr, Tel: +82-42-350-3930)
2025.07.14 View 7217 -
KAIST Enhances Immunotherapy for Difficult-to-Treat Brain Tumors with Gut Microbiota
< Photo 1.(From left) Prof. Heung Kyu Lee, Department of Biological Sciences,
and Dr. Hyeon Cheol Kim>
Advanced treatments, known as immunotherapies that activate T cells—our body's immune cells—to eliminate cancer cells, have shown limited efficacy as standalone therapies for glioblastoma, the most lethal form of brain tumor. This is due to their minimal response to glioblastoma and high resistance to treatment.
Now, a KAIST research team has now demonstrated a new therapeutic strategy that can enhance the efficacy of immunotherapy for brain tumors by utilizing gut microbes and their metabolites. This also opens up possibilities for developing microbiome-based immunotherapy supplements in the future.
KAIST (President Kwang Hyung Lee) announced on July 1 that a research team led by Professor Heung Kyu Lee of the Department of Biological Sciences discovered and demonstrated a method to significantly improve the efficiency of glioblastoma immunotherapy by focusing on changes in the gut microbial ecosystem.
The research team noted that as glioblastoma progresses, the concentration of ‘tryptophan’, an important amino acid in the gut, sharply decreases, leading to changes in the gut microbial ecosystem. They discovered that by supplementing tryptophan to restore microbial diversity, specific beneficial strains activate CD8 T cells (a type of immune cell) and induce their infiltration into tumor tissues. Through a mouse model of glioblastoma, the research team confirmed that tryptophan supplementation enhanced the response of cancer-attacking T cells (especially CD8 T cells), leading to their increased migration to tumor sites such as lymph nodes and the brain.
In this process, they also revealed that ‘Duncaniella dubosii’, a beneficial commensal bacterium present in the gut, plays a crucial role. This bacterium helped T cells effectively redistribute within the body, and survival rates significantly improved when used in combination with immunotherapy (anti-PD-1).
Furthermore, it was demonstrated that even when this commensal bacterium was administered alone to germ-free mice (mice without any commensal microbes), the survival rate for glioblastoma increased. This is because the bacterium utilizes tryptophan to regulate the gut environment, and the metabolites produced in this process strengthen the ability of CD8 T cells to attack cancer cells.
Professor Heung Kyu Lee explained, "This research is a meaningful achievement, showing that even in intractable brain tumors where immune checkpoint inhibitors had no effect, a combined strategy utilizing gut microbes can significantly enhance treatment response."
Dr. Hyeon Cheol Kim of KAIST (currently a postdoctoral researcher at the Institute for Biological Sciences) participated as the first author. The research findings were published online in Cell Reports, an international journal in the life sciences, on June 26.
This research was conducted as part of the Basic Research Program and Bio & Medical Technology Development Program supported by the Ministry of Science and ICT and the National Research Foundation of Korea.
※Paper Title: Gut microbiota dysbiosis induced by brain tumor modulates the efficacy of immunotherapy
※DOI: https://doi.org/10.1016/j.celrep.2025.115825
2025.07.02 View 9038 -
KAIST-UIUC researchers develop a treatment platform to disable the ‘biofilm’ shield of superbugs
< (From left) Ph.D. Candidate Joo Hun Lee (co-author), Professor Hyunjoon Kong (co-corresponding author) and Postdoctoral Researcher Yujin Ahn (co-first author) from the Department of Chemical and Biomolecular Engineering of the University of Illinois at Urbana-Champaign and Ju Yeon Chung (co-first author) from the Integrated Master's and Doctoral Program, and Professor Hyun Jung Chung (co-corresponding author) from the Department of Biological Sciences of KAIST >
A major cause of hospital-acquired infections, the super bacteria Methicillin-resistant Staphylococcus aureus (MRSA), not only exhibits strong resistance to existing antibiotics but also forms a dense biofilm that blocks the effects of external treatments. To meet this challenge, KAIST researchers, in collaboration with an international team, successfully developed a platform that utilizes microbubbles to deliver gene-targeted nanoparticles capable of break ing down the biofilms, offering an innovative solution for treating infections resistant to conventional antibiotics.
KAIST (represented by President Kwang Hyung Lee) announced on May 29 that a research team led by Professor Hyun Jung Chung from the Department of Biological Sciences, in collaboration with Professor Hyunjoon Kong's team at the University of Illinois, has developed a microbubble-based nano-gene delivery platform (BTN MB) that precisely delivers gene suppressors into bacteria to effectively remove biofilms formed by MRSA.
The research team first designed short DNA oligonucleotides that simultaneously suppress three major MRSA genes, related to—biofilm formation (icaA), cell division (ftsZ), and antibiotic resistance (mecA)—and engineered nanoparticles (BTN) to effectively deliver them into the bacteria.
< Figure 1. Effective biofilm treatment using biofilm-targeting nanoparticles controlled by microbubbler system. Schematic illustration of BTN delivery with microbubbles (MB), enabling effective permeation of ASOs targeting bacterial genes within biofilms infecting skin wounds. Gene silencing of targets involved in biofilm formation, bacterial proliferation, and antibiotic resistance leads to effective biofilm removal and antibacterial efficacy in vivo. >
In addition, microbubbles (MB) were used to increase the permeability of the microbial membrane, specifically the biofilm formed by MRSA. By combining these two technologies, the team implemented a dual-strike strategy that fundamentally blocks bacterial growth and prevents resistance acquisition.
This treatment system operates in two stages. First, the MBs induce pressure changes within the bacterial biofilm, allowing the BTNs to penetrate. Then, the BTNs slip through the gaps in the biofilm and enter the bacteria, delivering the gene suppressors precisely. This leads to gene regulation within MRSA, simultaneously blocking biofilm regeneration, cell proliferation, and antibiotic resistance expression.
In experiments conducted in a porcine skin model and a mouse wound model infected with MRSA biofilm, the BTN MB treatment group showed a significant reduction in biofilm thickness, as well as remarkable decreases in bacterial count and inflammatory responses.
< Figure 2. (a) Schematic illustration on the evaluation of treatment efficacy of BTN-MB gene therapy. (b) Reduction in MRSA biofilm mass via simultaneous inhibition of multiple genes. (c, d) Antibacterial efficacy of BTN-MB over time in a porcine skin infection biofilm model. (e) Schematic of the experimental setup to verify antibacterial efficacy in a mouse skin wound infection model. (f) Wound healing effects in mice. (g) Antibacterial effects at the wound site. (h) Histological analysis results. >
These results are difficult to achieve with conventional antibiotic monotherapy and demonstrate the potential for treating a wide range of resistant bacterial infections.
Professor Hyun Jung Chung of KAIST, who led the research, stated, “This study presents a new therapeutic solution that combines nanotechnology, gene suppression, and physical delivery strategies to address superbug infections that existing antibiotics cannot resolve. We will continue our research with the aim of expanding its application to systemic infections and various other infectious diseases.”
< (From left) Ju Yeon Chung from the Integrated Master's and Doctoral Program, and Professor Hyun Jung Chung from the Department of Biological Sciences >
The study was co-first authored by Ju Yeon Chung, a graduate student in the Department of Biological Sciences at KAIST, and Dr. Yujin Ahn from the University of Illinois. The study was published online on May 19 in the journal, Advanced Functional Materials.
※ Paper Title: Microbubble-Controlled Delivery of Biofilm-Targeting Nanoparticles to Treat MRSA Infection ※ DOI: https://doi.org/10.1002/adfm.202508291
This study was supported by the National Research Foundation and the Ministry of Health and Welfare, Republic of Korea; and the National Science Foundation and National Institutes of Health, USA.
2025.05.29 View 11781 -
KAIST's Pioneering VR Precision Technology & Choreography Tool Receive Spotlights at CHI 2025
Accurate pointing in virtual spaces is essential for seamless interaction. If pointing is not precise, selecting the desired object becomes challenging, breaking user immersion and reducing overall experience quality. KAIST researchers have developed a technology that offers a vivid, lifelike experience in virtual space, alongside a new tool that assists choreographers throughout the creative process.
KAIST (President Kwang-Hyung Lee) announced on May 13th that a research team led by Professor Sang Ho Yoon of the Graduate School of Culture Technology, in collaboration with Professor Yang Zhang of the University of California, Los Angeles (UCLA), has developed the ‘T2IRay’ technology and the ‘ChoreoCraft’ platform, which enables choreographers to work more freely and creatively in virtual reality. These technologies received two Honorable Mention awards, recognizing the top 5% of papers, at CHI 2025*, the best international conference in the field of human-computer interaction, hosted by the Association for Computing Machinery (ACM) from April 25 to May 1.
< (From left) PhD candidates Jina Kim and Kyungeun Jung along with Master's candidate, Hyunyoung Han and Professor Sang Ho Yoon of KAIST Graduate School of Culture Technology and Professor Yang Zhang (top) of UCLA >
T2IRay: Enabling Virtual Input with Precision
T2IRay introduces a novel input method that allows for precise object pointing in virtual environments by expanding traditional thumb-to-index gestures. This approach overcomes previous limitations, such as interruptions or reduced accuracy due to changes in hand position or orientation.
The technology uses a local coordinate system based on finger relationships, ensuring continuous input even as hand positions shift. It accurately captures subtle thumb movements within this coordinate system, integrating natural head movements to allow fluid, intuitive control across a wide range.
< Figure 1. T2IRay framework utilizing the delicate movements of the thumb and index fingers for AR/VR pointing >
Professor Sang Ho Yoon explained, “T2IRay can significantly enhance the user experience in AR/VR by enabling smooth, stable control even when the user’s hands are in motion.”
This study, led by first author Jina Kim, was supported by the Excellent New Researcher Support Project of the National Research Foundation of Korea under the Ministry of Science and ICT, as well as the University ICT Research Center (ITRC) Support Project of the Institute of Information and Communications Technology Planning and Evaluation (IITP).
▴ Paper title: T2IRay: Design of Thumb-to-Index Based Indirect Pointing for Continuous and Robust AR/VR Input▴ Paper link: https://doi.org/10.1145/3706598.3713442
▴ T2IRay demo video: https://youtu.be/ElJlcJbkJPY
ChoreoCraft: Creativity Support through VR for Choreographers
In addition, Professor Yoon’s team developed ‘ChoreoCraft,’ a virtual reality tool designed to support choreographers by addressing the unique challenges they face, such as memorizing complex movements, overcoming creative blocks, and managing subjective feedback.
ChoreoCraft reduces reliance on memory by allowing choreographers to save and refine movements directly within a VR space, using a motion-capture avatar for real-time interaction. It also enhances creativity by suggesting movements that naturally fit with prior choreography and musical elements. Furthermore, the system provides quantitative feedback by analyzing kinematic factors like motion stability and engagement, helping choreographers make data-driven creative decisions.
< Figure 2. ChoreoCraft's approaches to encourage creative process >
Professor Yoon noted, “ChoreoCraft is a tool designed to address the core challenges faced by choreographers, enhancing both creativity and efficiency. In user tests with professional choreographers, it received high marks for its ability to spark creative ideas and provide valuable quantitative feedback.”
This research was conducted in collaboration with doctoral candidate Kyungeun Jung and master’s candidate Hyunyoung Han, alongside the Electronics and Telecommunications Research Institute (ETRI) and One Million Co., Ltd. (CEO Hye-rang Kim), with support from the Cultural and Arts Immersive Service Development Project by the Ministry of Culture, Sports and Tourism.
▴ Paper title: ChoreoCraft: In-situ Crafting of Choreography in Virtual Reality through Creativity Support Tools▴ Paper link: https://doi.org/10.1145/3706598.3714220
▴ ChoreoCraft demo video: https://youtu.be/Ms1fwiSBjjw
*CHI (Conference on Human Factors in Computing Systems): The premier international conference on human-computer interaction, organized by the ACM, was held this year from April 25 to May 1, 2025.
2025.05.13 View 14887 -
KAIST Accelerates Synthetic Microbe Design by Discovering Novel Enzymes Using AI
< (From left) Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering (top), Hongkeun Ji, PhD candidate of the Department of Chemical and Biomolecular Engineering (top), Ha Rim Kim, PhD candidate of the Department of Chemical and Biomolecular Engineering, and Dr. Gi Bae Kim of the BioProcess Engineering Research Center >
Enzymes are proteins that catalyze biochemical reactions within cells and play a pivotal role in metabolic processes. Accordingly, identifying the functions of novel enzymes is a critical task in the construction of microbial cell factories.
A KAIST research team has leveraged artificial intelligence (AI) to design novel enzymes that do not exist in nature, significantly accelerating microbial cell factory development and boosting the potential for next-generation biotechnological applications such as drug development and biofuel production.
KAIST (represented by President Kwang-Hyung Lee) announced on the 21st of April that Distinguished Professor Sang Yup Lee and his team from the Department of Chemical and Biomolecular Engineering have published a review titled “Enzyme Functional Classification Using Artificial Intelligence,” which outlines the advancement of AI-based enzyme function prediction technologies and analyzes how AI has contributed to the discovery and design of new enzymes.
Professor Lee’s team systematically reviewed the development of enzyme function prediction technologies utilizing machine learning and deep learning, offering a comprehensive analysis.
From sequence similarity-based prediction methods to the integration of convolutional neural networks (CNNs), recurrent neural networks (RNNs), graph neural networks (GNNs), and transformer-based large language models, the paper covers a broad range of AI applications. It analyzes how these technologies extract meaningful information from protein sequences and enhance prediction accuracy.
In particular, enzyme function prediction using deep learning goes beyond simple sequence similarity analysis. By automatically extracting structural and evolutionary features embedded in amino acid sequences, deep learning enables more precise predictions of catalytic functions.
This highlights the unique advantages of AI models compared to traditional bioinformatics approaches.
Moreover, the review suggests that the advancement of generative AI will move future research beyond predicting existing functions to generating entirely new enzymes with functions not found in nature. This shift is expected to profoundly impact the trajectory of biotechnology and synthetic biology.
< Figure 1. Extraction of enzyme characteristics and function prediction using various deep learning structures >
Ha Rim Kim, a Ph.D. candidate and co-first author from the Department of Chemical and Biomolecular Engineering, stated, “AI-based enzyme function prediction and enzyme design are highly important across various fields including metabolic engineering, synthetic biology, and healthcare.”
Distinguished Professor Sang Yup Lee added, “AI-powered enzyme function prediction shows the potential to solve diverse biological problems and will significantly contribute to accelerating research across the entire field.”
The review was published on March 28 in Trends in Biotechnology, a leading biotechnology journal issued by Cell Press.
※ Title: Enzyme Functional Classification Using Artificial Intelligence
※DOI: https://doi.org/10.1016/j.tibtech.2025.03.003
※ Author Information: Ha Rim Kim (KAIST, Co-first author), Hongkeun Ji (KAIST, Co-first author), Gi Bae Kim (KAIST, Third author), Sang Yup Lee (KAIST, Corresponding author)
This research was supported by the Ministry of Science and ICT under the project Development of Core Technologies for Advanced Synthetic Biology to Lead the Bio-Manufacturing Industry (aimed at replacing petroleum-based chemicals), and also by joint support from the Ministry of Science and ICT and the Ministry of Health and Welfare for the project Development of Novel Antibiotic Structures Using Deep Learning-Based Synthetic Biology.
2025.04.07 View 12826 -
KAIST Captures Protein Reaction in Just Six Milliseconds
Understanding biomolecular processes - such as protein-protein interactions and enzyme-substrate reactions that occur on the microseconds to millisecond time scale is essential for comprehending life processes and advancing drug development. KAIST researchers have developed a method for freezing and analyzing biochemical reaction dynamics within a span of just a few milliseconds, marking a significant step forward in better understanding 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 dynamics at ultra-high speeds. It can be fabricated into a few micrometer-thick films, which can be used in making a spray nozzle for microfluidic devices.
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 time resolution—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 ability to capture transient 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. >
Transient intermediate structures of protein complexes could not be captured by traditional cryo-electron microscopy due to their extremely short lifespans. Although several TRCEM techniques have been developed to address this issue, previous methods were hindered by large 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 improvement of the technique to achieve higher time resolution with minimal sample consumption.”
< 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 View 11562