research
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KAIST introduces eco-friendly technologies for plastic production and biodegradation
- A research team under Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering published a paper in Nature Microbiology on the overview and trends of plastic production and degradation technology using microorganisms.
- Eco-friendly and sustainable plastic production and degradation technology using microorganisms as a core technology to achieve a plastic circular economy was presented.
Plastic is one of the important materials in modern society, with approximately 460 million tons produced annually and with expected production reaching approximately 1.23 billion tons in 2060. However, since 1950, plastic waste totaling more than 6.3 billion tons has been generated, and it is believed that more than 140 million tons of plastic waste has accumulated in the aquatic environment. Recently, the seriousness of microplastic pollution has emerged, not only posing a risk to the marine ecosystem and human health, but also worsening global warming by inhibiting the activity of marine plankton, which play an important role in lowering the Earth's carbon dioxide concentration.
KAIST President Kwang-Hyung Lee announced on December 11 that a research team under Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering had published a paper titled 'Sustainable production and degradation of plastics using microbes', which covers the latest technologies for producing plastics and processing waste plastics in an eco-friendly manner using microorganisms.
As the international community moves to solve this plastic problem, various efforts are being made, including 175 countries participating to conclude a legally binding agreement with the goal of ending plastic pollution by 2024. Various technologies are being developed for sustainable plastic production and processing, and among them, biotechnology using microorganisms is attracting attention.
Microorganisms have the ability to naturally produce or decompose certain compounds, and this ability is maximized through biotechnologies such as metabolic engineering and enzyme engineering to produce plastics from renewable biomass resources instead of fossil raw materials and to decompose waste plastics.
Accordingly, the research team comprehensively analyzed the latest microorganism-based technologies for the sustainable production and decomposition of plastics and presented how they actually contribute to solving the plastic problem. Based on this, they presented limitations, prospects, and research directions of the technologies for achieving a circular economy for plastics.
Microorganism-based technologies for various plastics range from widely used synthetic plastics such as polyethylene (PE) to promising bioplastics such as natural polymers derived from microorganisms (polyhydroxyalkanoate (PHA)) that are completely biodegradable in the natural environment and do not pose a risk of microplastic generation. Commercialization statuses and latest technologies were also discussed. In addition, the technology to decompose these plastics using microorganisms and their enzymes and the upcycling technology to convert them into other useful compounds after decomposition were introduced, highlighting the competitiveness and potential of technology using microorganisms.
First author So Young Choi, a research assistant professor in the Department of Chemical and Biomolecular Engineering at KAIST, said, “In the future, we will be able to easily find eco-friendly plastics made using microorganisms all around us,” and corresponding author Distinguished Professor Sang Yup Lee said, “Plastic can be made more sustainable. It is important to use plastics responsibly to protect the environment and simultaneously achieve economic and social development through the new plastics industry, and we look forward to the improved performance of microbial metabolic engineering technology.”
This paper was published on November 30th in the online edition of Nature Microbiology.
※ Paper Title : Sustainable production and degradation of plastics using microbes
Authors: So Young Choi, Youngjoon Lee, Hye Eun Yu, In Jin Cho, Minju Kang & Sang Yup Lee
2023.12.11 View 3932 -
KAIST-UCSD researchers build an enzyme discovering AI
- A joint research team led by Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering and Bernhard Palsson of UCSD developed ‘DeepECtransformer’, an artificial intelligence that can predict Enzyme Commission (EC) number of proteins.
- The AI is tasked to discover new enzymes that have not been discovered yet, which would allow prediction for a total of 5,360 types of Enzyme Commission (EC) numbers
- It is expected to be used in the development of microbial cell factories that produce environmentally friendly chemicals as a core technology for analyzing the metabolic network of a genome.
While E. coli is one of the most studied organisms, the function of 30% of proteins that make up E. coli has not yet been clearly revealed. For this, an artificial intelligence was used to discover 464 types of enzymes from the proteins that were unknown, and the researchers went on to verify the predictions of 3 types of proteins were successfully identified through in vitro enzyme assay.
KAIST (President Kwang-Hyung Lee) announced on the 24th that a joint research team comprised of Gi Bae Kim, Ji Yeon Kim, Dr. Jong An Lee and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST, and Dr. Charles J. Norsigian and Professor Bernhard O. Palsson of the Department of Bioengineering at UCSD has developed DeepECtransformer, an artificial intelligence that can predict the enzyme functions from the protein sequence, and has established a prediction system by utilizing the AI to quickly and accurately identify the enzyme function.
Enzymes are proteins that catalyze biological reactions, and identifying the function of each enzyme is essential to understanding the various chemical reactions that exist in living organisms and the metabolic characteristics of those organisms. Enzyme Commission (EC) number is an enzyme function classification system designed by the International Union of Biochemistry and Molecular Biology, and in order to understand the metabolic characteristics of various organisms, it is necessary to develop a technology that can quickly analyze enzymes and EC numbers of the enzymes present in the genome.
Various methodologies based on deep learning have been developed to analyze the features of biological sequences, including protein function prediction, but most of them have a problem of a black box, where the inference process of AI cannot be interpreted. Various prediction systems that utilize AI for enzyme function prediction have also been reported, but they do not solve this black box problem, or cannot interpret the reasoning process in fine-grained level (e.g., the level of amino acid residues in the enzyme sequence).
The joint team developed DeepECtransformer, an AI that utilizes deep learning and a protein homology analysis module to predict the enzyme function of a given protein sequence. To better understand the features of protein sequences, the transformer architecture, which is commonly used in natural language processing, was additionally used to extract important features about enzyme functions in the context of the entire protein sequence, which enabled the team to accurately predict the EC number of the enzyme. The developed DeepECtransformer can predict a total of 5360 EC numbers.
The joint team further analyzed the transformer architecture to understand the inference process of DeepECtransformer, and found that in the inference process, the AI utilizes information on catalytic active sites and/or the cofactor binding sites which are important for enzyme function. By analyzing the black box of DeepECtransformer, it was confirmed that the AI was able to identify the features that are important for enzyme function on its own during the learning process.
"By utilizing the prediction system we developed, we were able to predict the functions of enzymes that had not yet been identified and verify them experimentally," said Gi Bae Kim, the first author of the paper. "By using DeepECtransformer to identify previously unknown enzymes in living organisms, we will be able to more accurately analyze various facets involved in the metabolic processes of organisms, such as the enzymes needed to biosynthesize various useful compounds or the enzymes needed to biodegrade plastics." he added.
"DeepECtransformer, which quickly and accurately predicts enzyme functions, is a key technology in functional genomics, enabling us to analyze the function of entire enzymes at the systems level," said Professor Sang Yup Lee. He added, “We will be able to use it to develop eco-friendly microbial factories based on comprehensive genome-scale metabolic models, potentially minimizing missing information of metabolism.”
The joint team’s work on DeepECtransformer is described in the paper titled "Functional annotation of enzyme-encoding genes using deep learning with transformer layers" written by Gi Bae Kim, Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering of KAIST and their colleagues. The paper was published via peer-review on the 14th of November on “Nature Communications”.
This research was conducted with the support by “the Development of next-generation biorefinery platform technologies for leading bio-based chemicals industry project (2022M3J5A1056072)” and by “Development of platform technologies of microbial cell factories for the next-generation biorefineries project (2022M3J5A1056117)” from National Research Foundation supported by the Korean Ministry of Science and ICT (Project Leader: Distinguished Professor Sang Yup Lee, KAIST).
< Figure 1. The structure of DeepECtransformer's artificial neural network >
2023.11.24 View 3168 -
An intravenous needle that irreversibly softens via body temperature on insertion
- A joint research team at KAIST developed an intravenous (IV) needle that softens upon insertion, minimizing risk of damage to blood vessels and tissues.
- Once used, it remains soft even at room temperature, preventing accidental needle stick injuries and unethical multiple use of needle.
- A thin-film temperature sensor can be embedded with this needle, enabling real-time monitoring of the patient's core body temperature, or detection of unintended fluid leakage, during IV medication.
Intravenous (IV) injection is a method commonly used in patient’s treatment worldwide as it induces rapid effects and allows treatment through continuous administration of medication by directly injecting drugs into the blood vessel. However, medical IV needles, made of hard materials such as stainless steel or plastic which do not mechanically match the soft biological tissues of the body, can cause critical problems in healthcare settings, starting from minor tissue damages in the injection sites to serious inflammations.
The structure and dexterity of rigid medical IV devices also enable unethical reuse of needles for reduction of injection costs, leading to transmission of deadly blood-borne disease infections such as human immunodeficiency virus (HIV) and hepatitis B/C viruses. Furthermore, unintended needlestick injuries are frequently occurring in medical settings worldwide, that are viable sources of such infections, with IV needles having the greatest susceptibility of being the medium of transmissible diseases. For these reasons, the World Health Organization (WHO) in 2015 launched a policy on safe injection practices to encourage the development and use of “smart” syringes that have features to prevent re-use, after a tremendous increase in the number of deadly infectious disease worldwide due to medical-sharps related issues.
KAIST announced on the 13th that Professor Jae-Woong Jeong and his research team of its School of Electrical Engineering succeeded in developing the Phase-Convertible, Adapting and non-REusable (P-CARE) needle with variable stiffness that can improve patient health and ensure the safety of medical staff through convergent joint research with another team led by Professor Won-Il Jeong of the Graduate School of Medical Sciences.
The new technology is expected to allow patients to move without worrying about pain at the injection site as it reduces the risk of damage to the wall of the blood vessel as patients receive IV medication. This is possible with the needle’s stiffness-tunable characteristics which will make it soft and flexible upon insertion into the body due to increased temperature, adapting to the movement of thin-walled vein. It is also expected to prevent blood-borne disease infections caused by accidental needlestick injuries or unethical re-using of syringes as the deformed needle remains perpetually soft even after it is retracted from the injection site.
The results of this research, in which Karen-Christian Agno, a doctoral researcher of the School of Electrical Engineering at and Dr. Keungmo Yang of the Graduate School of Medical Sciences participated as co-first authors, was published in Nature Biomedical Engineering on October 30. (Paper title: A temperature-responsive intravenous needle that irreversibly softens on insertion)
< Figure 1. Disposable variable stiffness intravenous needle. (a) Conceptual illustration of the key features of the P-CARE needle whose mechanical properties can be changed by body temperature, (b) Photograph of commonly used IV access devices and the P-CARE needle, (c) Performance of common IV access devices and the P-CARE needle >
“We’ve developed this special needle using advanced materials and micro/nano engineering techniques, and it can solve many global problems related to conventional medical needles used in healthcare worldwide”, said Jae-Woong Jeong, Ph.D., an associate professor of Electrical Engineering at KAIST and a lead senior author of the study.
The softening IV needle created by the research team is made up of liquid metal gallium that forms the hollow, mechanical needle frame encapsulated within an ultra-soft silicone material. In its solid state, gallium has sufficient hardness that enables puncturing of soft biological tissues. However, gallium melts when it is exposed to body temperature upon insertion, and changes it into a soft state like the surrounding tissue, enabling stable delivery of the drug without damaging blood vessels. Once used, a needle remains soft even at room temperature due to the supercooling phenomenon of gallium, fundamentally preventing needlestick accidents and reuse problems.
Biocompatibility of the softening IV needle was validated through in vivo studies in mice. The studies showed that implanted needles caused significantly less inflammation relative to the standard IV access devices of similar size made of metal needles or plastic catheters. The study also confirmed the new needle was able to deliver medications as reliably as commercial injection needles.
< Photo 1. Photo of the P-CARE needle that softens with body temperature. >
Researchers also showed possibility of integrating a customized ultra-thin temperature sensor with the softening IV needle to measure the on-site temperature which can further enhance patient’s well-being. The single assembly of sensor-needle device can be used to monitor the core body temperature, or even detect if there is a fluid leakage on-site during indwelling use, eliminating the need for additional medical tools or procedures to provide the patients with better health care services.
The researchers believe that this transformative IV needle can open new opportunities for wide range of applications particularly in clinical setups, in terms of redesigning other medical needles and sharp medical tools to reduce muscle tissue injury during indwelling use. The softening IV needle may become even more valuable in the present times as there is an estimated 16 billion medical injections administered annually in a global scale, yet not all needles are disposed of properly, based on a 2018 WHO report.
< Figure 2. Biocompatibility test for P-CARE needle: Images of H&E stained histology (the area inside the dashed box on the left is provided in an expanded view in the right), TUNEL staining (green), DAPI staining of nuclei (blue) and co-staining (TUNEL and DAPI) of muscle tissue from different organs. >
< Figure 3. Conceptual images of potential utilization for temperature monitoring function of P-CARE needle integrated with a temperature sensor. >
(a) Schematic diagram of injecting a drug through intravenous injection into the abdomen of a laboratory mouse (b) Change of body temperature upon injection of drug (c) Conceptual illustration of normal intravenous drug injection (top) and fluid leakage (bottom) (d) Comparison of body temperature during normal drug injection and fluid leakage: when the fluid leak occur due to incorrect insertion, a sudden drop of temperature is detected.
This work was supported by grants from the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT.
2023.11.13 View 5820 -
KAIST proposes alternatives to chemical factories through “iBridge”
- A computer simulation program “iBridge” was developed at KAIST that can put together microbial cell factories quickly and efficiently to produce cosmetics and food additives, and raw materials for nylons
- Eco-friendly and sustainable fermentation process to establish an alternative to chemical plants
As climate change and environmental concerns intensify, sustainable microbial cell factories garner significant attention as candidates to replace chemical plants. To develop microorganisms to be used in the microbial cell factories, it is crucial to modify their metabolic processes to induce efficient target chemical production by modulating its gene expressions. Yet, the challenge persists in determining which gene expressions to amplify and suppress, and the experimental verification of these modification targets is a time- and resource-intensive process even for experts. The challenges were addressed by a team of researchers at KAIST (President Kwang-Hyung Lee) led by Distinguished Professor Sang Yup Lee.
It was announced on the 9th by the school that a method for building a microbial factory at low cost, quickly and efficiently, was presented by a novel computer simulation program developed by the team under Professor Lee’s guidance, which is named “iBridge”. This innovative system is designed to predict gene targets to either overexpress or downregulate in the goal of producing a desired compound to enable the cost-effective and efficient construction of microbial cell factories specifically tailored for producing the chemical compound in demand from renewable biomass.
Systems metabolic engineering is a field of research and engineering pioneered by KAIST’s Distinguished Professor Sang Yup Lee that seeks to produce valuable compounds in industrial demands using microorganisms that are re-configured by a combination of methods including, but not limited to, metabolic engineering, synthetic biology, systems biology, and fermentation engineering.
In order to improve microorganisms’ capability to produce useful compounds, it is essential to delete, suppress, or overexpress microbial genes. However, it is difficult even for the experts to identify the gene targets to modify without experimental confirmations for each of them, which can take up immeasurable amount of time and resources.
The newly developed iBridge identifies positive and negative metabolites within cells, which exert positive and/or negative impact on formation of the products, by calculating the sum of covariances of their outgoing (consuming) reaction fluxes for a target chemical. Subsequently, it pinpoints "bridge" reactions responsible for converting negative metabolites into positive ones as candidates for overexpression, while identifying the opposites as targets for downregulation.
The research team successfully utilized the iBridge simulation to establish E. coli microbial cell factories each capable of producing three of the compounds that are in high demands at a production capacity that has not been reported around the world. They developed E. coli strains that can each produce panthenol, a moisturizing agent found in many cosmetics, putrescine, which is one of the key components in nylon production, and 4-hydroxyphenyllactic acid, an anti-bacterial food additive. In addition to these three compounds, the study presents predictions for overexpression and suppression genes to construct microbial factories for 298 other industrially valuable compounds.
Dr. Youngjoon Lee, the co-first author of this paper from KAIST, emphasized the accelerated construction of various microbial factories the newly developed simulation enabled. He stated, "With the use of this simulation, multiple microbial cell factories have been established significantly faster than it would have been using the conventional methods. Microbial cell factories producing a wider range of valuable compounds can now be constructed quickly using this technology."
Professor Sang Yup Lee said, "Systems metabolic engineering is a crucial technology for addressing the current climate change issues." He added, "This simulation could significantly expedite the transition from resorting to conventional chemical factories to utilizing environmentally friendly microbial factories."
< Figure. Conceptual diagram of the flow of iBridge simulation >
The team’s work on iBridge is described in a paper titled "Genome-Wide Identification of Overexpression and Downregulation Gene Targets Based on the Sum of Covariances of the Outgoing Reaction Fluxes" written by Dr. Won Jun Kim, and Dr. Youngjoon Lee of the Bioprocess Research Center and Professors Hyun Uk Kim and Sang Yup Lee of the Department of Chemical and Biomolecular Engineering of KAIST. The paper was published via peer-review on the 6th of November on “Cell Systems” by Cell Press.
This research was conducted with the support from the Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project (Project Leader: Distinguished Professor Sang Yup Lee, KAIST) and Development of Platform Technology for the Production of Novel Aromatic Bioplastic using Microbial Cell Factories Project (Project Leader: Research Professor So Young Choi, KAIST) of the Korean Ministry of Science and ICT.
2023.11.09 View 4385 -
A KAIST Research Team Produces Eco-Friendly Nylon with Engineered Bacterium
With worsening climate change and environmental issues, in recent years, there has been increased interest in the eco-friendly production of polymers like nylon.
On August 10, Dr. Taehee Han from a KAIST research team led by Distinguished Professor Sang Yup Lee in the Department of Chemical and Biomolecular Engineering revealed the successful development of a microbial strain that produces valerolactam, a monomer of nylon-5.
Valerolactam is an important monomer that constitutes nylon-5 and nylon-6,5. Nylon is the oldest synthetic polymer, and nylon-5 is one of its derivatives composed of monomers with five carbons, while nylon-5,6 is composed of two types of monomers with either five or six carbons. They not only have excellent processability, but are also light and tough, which allows them to be applied in a wide range of industrial sectors including clothing, badminton rackets, fishing nets, tents, and gear parts. Monomers are materials that can be built into polymers, and synthetic processes are what connects them into a polymer.
The chemical production of valerolactam, however, is based on petrochemistry, where extreme reaction conditions are required and toxic waste is produced. To solve these problems, efforts are being made to develop environmentally friendly and highly efficient microbial cell factories for lactam production. Systems metabolic engineering, a key strategy for effective microbial strain development, is a research field pioneered by Professor Sang Yup Lee.
Professor Lee’s team used metabolic engineering, a technique for manipulating microbial metabolic pathways, to construct a synthetic metabolic pathway for valerolactam production in Corynebacteriam glutamicum, a bacterium commonly used for amino acid production. With this, they successfully developed a microbial strain that utilizes biomass-derived glucose as a carbon source to produce high-value valerolactam.
In 2017, the team suggested a novel method that metabolically manipulates Escherichia coli to produce valerolactam. However, there were several limitations at the time including low producibility and the generation of harmful byproducts.
< Figure 1. Schematic graphical representation of the development of microorganisms that produce valerolactam, a nylon-5 monomer >
In this research, the team improved valerolactam producibility and incorporated an additional systems metabolic strategy to the developed microbial strain while eliminating the harmful byproducts. By removing the gene involved in the production of the main byproduct and through gene screening, the team successfully converted 5-aminovaleric acid, a byproduct and a precursor, into valerolactam.
Furthermore, by employing a strategy where the 5-aminovaleric acid-converting gene is inserted multiple times into the genome, the team strengthened the metabolic flux for valerolactam production. As a result, they reached a world-record concentration of 76.1 g/L, which is 6.17 times greater than what was previously reported.
This study was published in Metabolic Engineering on July 12, under the title, “Metabolic engineering of Corynebacterium glutamicum for the high-level production of valerolactam, a nylon-5 monomer”.
Dr. Taehee Han, the first author of the paper, said, “The significance of this research lies in our development of an environmentally friendly technology that efficiently produces monomer lactam for nylon production using microorganisms.” She added, “Through this technology, we will be able to take a step forward in replacing the petrochemical industry with a microorganism-based biopolymer industry.”
This work was supported by the “Development of Next-Generation Biofinery Platform Technologies for Leading Bio-based Chemicals Industry Project” funded by the Korean Ministry of Science and ICT.
2023.08.24 View 3629 -
KAIST Research Team Develops World’s First Humanoid Pilot, PIBOT
In the Spring of last year, the legendary, fictional pilot “Maverick” flew his plane in the film “Top Gun: Maverick” that drew crowds to theatres around the world. This year, the appearance of a humanoid pilot, PIBOT, has stolen the spotlight at KAIST.
< Photo 1. Humanoid pilot robot, PIBOT >
A KAIST research team has developed a humanoid robot that can understand manuals written in natural language and fly a plane on its own. The team also announced their plans to commercialize the humanoid pilot.
< Photo 2. PIBOT on flight simulator (view from above) >
The project was led by KAIST Professor David Hyunchul Shim, and was conducted as a joint research project with Professors Jaegul Choo, Kuk-Jin Yoon, and Min Jun Kim. The study was supported by Future Challenge Funding under the project title, “Development of Human-like Pilot Robot based on Natural Language Processing”. The team utilized AI and robotics technologies, and demonstrated that the humanoid could sit itself in a real cockpit and operate the various pieces of equipment without modifying any part of the aircraft. This is a fundamental difference that distinguishes this technology from existing autopilot functions or unmanned aircrafts.
< Photo 3. PIBOT operating a flight simulator (side) >
The KAIST team’s humanoid pilot is still under development but it can already remember Jeppeson charts from all around the world, which is impossible for human pilots to do, and fly without error. In particular, it can make use of recent ChatGPT technology to remember the full Quick Reference Handbook (QRF) and respond immediately to various situations, as well as calculate safe routes in real time based on the flight status of the aircraft, with emergency response times quicker than human pilots.
Furthermore, while existing robots usually carry out repeated motions in a fixed position, PIBOT can analyze the state of the cockpit as well as the situation outside the aircraft using an embedded camera. PIBOT can accurately control the various switches in the cockpit and, using high-precision control technology, it can accurately control its robotic arms and hands even during harsh turbulence.
< Photo 4. PIBOT on-board KLA-100, Korea’s first light aircraft >
The humanoid pilot is currently capable of carrying out all operations from starting the aircraft to taxiing, takeoff and landing, cruising, and cycling using a flight control simulator. The research team plans to use the humanoid pilot to fly a real-life light aircraft to verify its abilities. Prof. Shim explained, “Humanoid pilot robots do not require the modification of existing aircrafts and can be applied immediately to automated flights. They are therefore highly applicable and practical. We expect them to be applied into various other vehicles like cars and military trucks since they can control a wide range of equipment. They will particularly be particularly helpful in situations where military resources are severely depleted.”
This research was supported by Future Challenge Funding (total: 5.7 bn KRW) from the Agency for Defense Development. The project started in 2022 as a joint research project by Prof. David Hyunchul Shim (chief of research) from the KAIST School of Electrical Engineering (EE), Prof. Jaegul Choo from the Kim Jaechul Graduate School of AI at KAIST, Prof. Kuk-Jin Yoon from the KAIST Department of Mechanical Engineering, and Prof. Min Jun Kim from the KAIST School of EE. The project is to be completed by 2026 and the involved researchers are also considering commercialization strategies for both military and civil use.
2023.08.03 View 10057 -
KAIST presents a microbial cell factory as a source of eco-friendly food and cosmetic coloring
Despite decades of global population growth, global food crisis seems to be at hand yet again because the food productivity is cut severely due to prolonged presence of abnormal weather from intensifying climate change and global food supply chain is deteriorated due to international conflicts such as wars exacerbating food shortages and nutritional inequality around the globe. At the same time, however, as awareness of the environment and sustainability rises, an increase in demand for more eco-friendly and high-quality food and beauty products is being observed not without a sense of irony. At a time like this, microorganisms are attracting attention as a key that can handle this couple of seemingly distant problems.
KAIST (President Kwang-Hyung Lee) announced on the 26th that Kyeong Rok Choi, a research professor of the Bioprocess Research Center and Sang Yup Lee, a Distinguished Professor of the Department of Chemical and Biomolecular Engineering, published a paper titled “Metabolic Engineering of Microorganisms for Food and Cosmetics Production” upon invitation by “Nature Reviews Bioengineering” to be published online published by Nature after peer review.
※ Paper title: Systems metabolic engineering of microorganisms for food and cosmetics production
※ Author information: Kyeong Rok Choi (first author) and Sang Yup Lee (corresponding author)
Systems metabolic engineering is a research field founded by Distinguished Professor Sang Yup Lee of KAIST to more effectively develop microbial cell factories, the core factor of the next-generation bio industry to replace the existing chemical industry that relies heavily on petroleum. By applying a systemic metabolic engineering strategy, the researchers have developed a number of high-performance microbial cell factories that produce a variety of food and cosmetic compounds including natural substances like heme and zinc protoporphyrin IX compounds which can improve the flavor and color of synthetic meat, lycopene and β-carotene which are functional natural pigments that can be widely used in food and cosmetics, and methyl anthranilate, a grape-derived compound widely used to impart grape flavor in food and beverage manufacturing.
In this paper written upon invitation by Nature, the research team covered remarkable cases of microbial cell factory that can produce amino acids, proteins, fats and fatty acids, vitamins, flavors, pigments, alcohols, functional compounds and other food additives used in various foods and cosmetics and the companies that have successfully commercialized these microbial-derived materials Furthermore, the paper organized and presents systems metabolic engineering strategies that can spur the development of industrial microbial cell factories that can produce more diverse food and cosmetic compounds in an eco-friendly way with economic feasibility.
< Figure 1. Examples of production of food and cosmetic compounds using microbial cell factories >
For example, by producing proteins or amino acids with high nutritional value through non-edible biomass used as animal feed or fertilizer through the microbial fermentation process, it will contribute to the increase in production and stable supply of food around the world. Furthermore, by contributing to developing more viable alternative meat, further reducing dependence on animal protein, it can also contribute to reducing greenhouse gases and environmental pollution generated through livestock breeding or fish farming.
In addition, vanillin or methyl anthranilate, which give off vanilla or grape flavor, are widely added to various foods, but natural products isolated and refined from plants are low in production and high in production cost, so in most cases, petrochemicals substances derived from vanillin and methylanthranilic acid are added to food. These materials can also be produced through an eco-friendly and human-friendly method by borrowing the power of microorganisms.
Ethical and resource problems that arise in producing compounds like Calmin (cochineal pigment), a coloring added to various cosmetics and foods such as red lipstick and strawberry-flavored milk, which must be extracted from cochineal insects that live only in certain cacti. and Hyaluronic acid, which is widely consumed as a health supplement, but is only present in omega-3 fatty acids extracted from shark or fish livers, can also be resolved when they can be produced in an eco-friendly way using microorganisms.
KAIST Research Professor Kyeong Rok Choi, the first author of this paper, said, “In addition to traditional fermented foods such as kimchi and yogurt, foods produced with the help of microorganisms like cocoa butter, a base ingredient for chocolate that can only be obtained from fermented cacao beans, and monosodium glutamate, a seasoning produced through microbial fermentation are already familiar to us”. “In the future, we will be able to acquire a wider variety of foods and cosmetics even more easily produced in an eco-friendly and sustainable way in our daily lives through microbial cell factories.” he added.
< Figure 2. Systems metabolic engineering strategy to improve metabolic flow in microbial cell factories >
Distinguished Professor Sang Yup Lee said, “It is engineers’ mission to make the world a better place utilizing science and technology.” and added, “Continuous advancement and active use of systems metabolic engineering will contribute greatly to easing and resolving the problems arising from both the food crisis and the climate change."
This research was carried out as a part of the “Development of Protein Production Technology from Inorganic Substances through Control of Microbial Metabolism System Project” (Project Leader: Kyeong Rok Choi, KAIST Research Professor) of the the Center for Agricultural Microorganism and Enzyme (Director Pahn-Shick Chang) supported by the Rural Development Administration and the “Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project” (Project Leader: Sang Yup Lee, KAIST Distinguished Professor) of the Petroleum-Substitute Eco-friendly Chemical Technology Development Program supported by the Ministry of Science and ICT.
2023.07.28 View 5032 -
KAIST researchers find sleep delays more prevalent in countries of particular culture than others
Sleep has a huge impact on health, well-being and productivity, but how long and how well people sleep these days has not been accurately reported. Previous research on how much and how well we sleep has mostly relied on self-reports or was confined within the data from the unnatural environments of the sleep laboratories.
So, the questions remained: Is the amount and quality of sleep purely a personal choice? Could they be independent from social factors such as culture and geography?
< From left to right, Sungkyu Park of Kangwon National University, South Korea; Assem Zhunis of KAIST and IBS, South Korea; Marios Constantinides of Nokia Bell Labs, UK; Luca Maria Aiello of the IT University of Copenhagen, Denmark; Daniele Quercia of Nokia Bell Labs and King's College London, UK; and Meeyoung Cha of IBS and KAIST, South Korea >
A new study led by researchers at Korea Advanced Institute of Science and Technology (KAIST) and Nokia Bell Labs in the United Kingdom investigated the cultural and individual factors that influence sleep. In contrast to previous studies that relied on surveys or controlled experiments at labs, the team used commercially available smartwatches for extensive data collection, analyzing 52 million logs collected over a four-year period from 30,082 individuals in 11 countries. These people wore Nokia smartwatches, which allowed the team to investigate country-specific sleep patterns based on the digital logs from the devices.
< Figure comparing survey and smartwatch logs on average sleep-time, wake-time, and sleep durations. Digital logs consistently recorded delayed hours of wake- and sleep-time, resulting in shorter sleep durations. >
Digital logs collected from the smartwatches revealed discrepancies in wake-up times and sleep-times, sometimes by tens of minutes to an hour, from the data previously collected from self-report assessments. The average sleep-time overall was calculated to be around midnight, and the average wake-up time was 7:42 AM. The team discovered, however, that individuals' sleep is heavily linked to their geographical location and cultural factors. While wake-up times were similar, sleep-time varied by country. Individuals in higher GDP countries had more records of delayed bedtime. Those in collectivist culture, compared to individualist culture, also showed more records of delayed bedtime. Among the studied countries, Japan had the shortest total sleep duration, averaging a duration of under 7 hours, while Finland had the longest, averaging 8 hours.
Researchers calculated essential sleep metrics used in clinical studies, such as sleep efficiency, sleep duration, and overslept hours on weekends, to analyze the extensive sleep patterns. Using Principal Component Analysis (PCA), they further condensed these metrics into two major sleep dimensions representing sleep quality and quantity. A cross-country comparison revealed that societal factors account for 55% of the variation in sleep quality and 63% of the variation in sleep quantity.
Countries with a higher individualism index (IDV), which placed greater emphasis on individual achievements and relationships, had significantly longer sleep durations, which could be attributed to such societies having a norm of going to bed early. Spain and Japan, on the other hand, had the bedtime scheduled at the latest hours despite having the highest collectivism scores (low IDV). The study also discovered a moderate relationship between a higher uncertainty avoidance index (UAI), which measures implementation of general laws and regulation in daily lives of regular citizens, and better sleep quality.
Researchers also investigated how physical activity can affect sleep quantity and quality to see if individuals can counterbalance cultural influences through personal interventions. They discovered that increasing daily activity can improve sleep quality in terms of shortened time needed in falling asleep and waking up. Individuals who exercise more, however, did not sleep longer. The effect of exercise differed by country, with more pronounced effects observed in some countries, such as the United States and Finland. Interestingly, in Japan, no obvious effect of exercise could be observed. These findings suggest that the relationship between daily activity and sleep may differ by country and that different exercise regimens may be more effective in different cultures.
This research published on the Scientific Reports by the international journal, Nature, sheds light on the influence of social factors on sleep. (Paper Title "Social dimensions impact individual sleep quantity and quality" Article number: 9681)
One of the co-authors, Daniele Quercia, commented: “Excessive work schedules, long working hours, and late bedtime in high-income countries and social engagement due to high collectivism may cause bedtimes to be delayed.”
Commenting on the research, the first author Shaun Sungkyu Park said, "While it is intriguing to see that a society can play a role in determining the quantity and quality of an individual's sleep with large-scale data, the significance of this study is that it quantitatively shows that even within the same culture (country), individual efforts such as daily exercise can have a positive impact on sleep quantity and quality."
"Sleep not only has a great impact on one’s well-being but it is also known to be associated with health issues such as obesity and dementia," said the lead author, Meeyoung Cha. "In order to ensure adequate sleep and improve sleep quality in an aging society, not only individual efforts but also a social support must be provided to work together," she said. The research team will contribute to the development of the high-tech sleep industry by making a code that easily calculates the sleep indicators developed in this study available free of charge, as well as providing the benchmark data for various types of sleep research to follow.
2023.07.07 View 4929 -
Synthetic sRNAs to knockdown genes in medical and industrial bacteria
Bacteria are intimately involved in our daily lives. These microorganisms have been used in human history for food such as cheese, yogurt, and wine, In more recent years, through metabolic engineering, microorganisms been used extensively as microbial cell factories to manufacture plastics, feed for livestock, dietary supplements, and drugs. However, in addition to these bacteria that are beneficial to human lives, pathogens such as Pneumonia, Salmonella, and Staphylococcus that cause various infectious diseases are also ubiquitously present. It is important to be able to metabolically control these beneficial industrial bacteria for high value-added chemicals production and to manipulate harmful pathogens to suppress its pathogenic traits.
KAIST (President Kwang Hyung Lee) announced on the 10th that a research team led by Distinguished Professor Sang Yup Lee of the Department of Biochemical Engineering has developed a new sRNA tool that can effectively inhibit target genes in various bacteria, including both Gram-negative and Gram-positive bacteria. The research results were published online on April 24 in Nature Communications.
※ Thesis title: Targeted and high-throughput gene knockdown in diverse bacteria using synthetic sRNAs
※ Author information : Jae Sung Cho (co-1st), Dongsoo Yang (co-1st), Cindy Pricilia Surya Prabowo (co-author), Mohammad Rifqi Ghiffary (co-author), Taehee Han (co-author), Kyeong Rok Choi (co-author), Cheon Woo Moon (co-author), Hengrui Zhou (co-author), Jae Yong Ryu (co-author), Hyun Uk Kim (co-author) and Sang Yup Lee (corresponding author).
sRNA is an effective tool for synthesizing and regulating target genes in E. coli, but it has been difficult to apply to industrially useful Gram-positive bacteria such as Bacillus subtilis and Corynebacterium in addition to Gram-negative bacteria such as E. coli.
To address this issue, a research team led by Distinguished Professor Lee Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST developed a new sRNA platform that can effectively suppress target genes in various bacteria, including both Gram-negative and positive bacteria. The research team surveyed thousands of microbial-derived sRNA systems in the microbial database, and eventually designated the sRNA system derived from 'Bacillus subtilis' that showed the highest gene knockdown efficiency, and designated it as “Broad-Host-Range sRNA”, or BHR-sRNA.
A similar well-known system is the CRISPR interference (CRISPRi) system, which is a modified CRISPR system that knocks down gene expression by suppressing the gene transcription process. However, the Cas9 protein in the CRISPRi system has a very high molecular weight, and there have been reports growth inhibition in bacteria. The BHR-sRNA system developed in this study did not affect bacterial growth while showing similar gene knockdown efficiencies to CRISPRi.
< Figure 1. a) Schematic illustration demonstrating the mechanism of syntetic sRNA b) Phylogenetic tree of the 16 Gram-negative and Gram-positive bacterial species tested for gene knockdown by the BHR-sRNA system. >
To validate the versatility of the BHR-sRNA system, 16 different gram-negative and gram-positive bacteria were selected and tested, where the BHR-sRNA system worked successfully in 15 of them. In addition, it was demonstrated that the gene knockdown capability was more effective than that of the existing E. coli-based sRNA system in 10 bacteria. The BHR-sRNA system proved to be a universal tool capable of effectively inhibiting gene expression in various bacteria.
In order to address the problem of antibiotic-resistant pathogens that have recently become more serious, the BHR-sRNA was demonstrated to suppress the pathogenicity by suppressing the gene producing the virulence factor. By using BHR-sRNA, biofilm formation, one of the factors resulting in antibiotic resistance, was inhibited by 73% in Staphylococcus epidermidis a pathogen that can cause hospital-acquired infections. Antibiotic resistance was also weakened by 58% in the pneumonia causing bacteria Klebsiella pneumoniae. In addition, BHR-sRNA was applied to industrial bacteria to develop microbial cell factories to produce high value-added chemicals with better production performance. Notably, superior industrial strains were constructed with the aid of BHR-sRNA to produce the following chemicals: valerolactam, a raw material for polyamide polymers, methyl-anthranilate, a grape-flavor food additive, and indigoidine, a blue-toned natural dye.
The BHR-sRNA developed through this study will help expedite the commercialization of bioprocesses to produce high value-added compounds and materials such as artificial meat, jet fuel, health supplements, pharmaceuticals, and plastics. It is also anticipated that to help eradicating antibiotic-resistant pathogens in preparation for another upcoming pandemic. “In the past, we could only develop new tools for gene knockdown for each bacterium, but now we have developed a tool that works for a variety of bacteria” said Distinguished Professor Sang Yup Lee.
This work was supported by the Development of Next-generation Biorefinery Platform Technologies for Leading Bio-based Chemicals Industry Project and the Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project from NRF supported by the Korean MSIT.
2023.05.10 View 4970 -
A biohybrid system to extract 20 times more bioplastic from CO2 developed by KAIST researchers
As the issues surrounding global climate change intensify, more attention and determined efforts are required to re-grasp the issue as a state of “crisis” and respond to it properly. Among the various methods of recycling CO2, the electrochemical CO2 conversion technology is a technology that can convert CO2 into useful chemical substances using electrical energy. Since it is easy to operate facilities and can use the electricity from renewable sources like the solar cells or the wind power, it has received a lot of attention as an eco-friendly technology can contribute to reducing greenhouse gases and achieve carbon neutrality.
KAIST (President Kwang Hyung Lee) announced on the 30th that the joint research team led by Professor Hyunjoo Lee and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering succeeded in developing a technology that produces bioplastics from CO2 with high efficiency by developing a hybrid system that interlinked the electrochemical CO2 conversion and microbial bio conversion methods together. The results of the research, which showed the world's highest productivity by more than 20 times compared to similar systems, were published online on March 27th in the "Proceedings of the National Academy of Sciences (PNAS)".
※ Paper title: Biohybrid CO2 electrolysis for the direct synthesis of polyesters from CO2
※ Author information: Jinkyu Lim (currently at Stanford Linear Accelerator Center, co-first author), So Young Choi (KAIST, co-first author), Jae Won Lee (KAIST, co-first author), Hyunjoo Lee (KAIST, corresponding author), Sang Yup Lee (KAIST, corresponding author)
For the efficient conversion of CO2, high-efficiency electrode catalysts and systems are actively being developed. As conversion products, only compounds containing one or up to three carbon atoms are produced on a limited basis. Compounds of one carbon, such as CO, formic acid, and ethylene, are produced with relatively high efficiency. Liquid compounds of several carbons, such as ethanol, acetic acid, and propanol, can also be produced by these systems, but due to the nature of the chemical reaction that requires more electrons, there are limitations involving the conversion efficiency and the product selection.
Accordingly, a joint research team led by Professor Hyunjoo Lee and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST developed a technology to produce bioplastics from CO2 by linking electrochemical conversion technology with bioconversion method that uses microorganisms.
This electrochemical-bio hybrid system is in the form of having an electrolyzer, in which electrochemical conversion reactions occur, connected to a fermenter, in which microorganisms are cultured. When CO2 is converted to formic acid in the electrolyzer, and it is fed into the fermenter in which the microbes like the Cupriavidus necator, in this case, consumes the carbon source to produce polyhydroxyalkanoate (PHA), a microbial-derived bioplastic.
According to the research results of the existing hybrid concepts, there was a disadvantage of having low productivity or stopping at a non-continuous process due to problems of low efficiency of the electrolysis and irregular results arising from the culturing conditions of the microbes.
In order to overcome these problems, the joint research team made formic acid with a gas diffusion electrode using gaseous CO2. In addition, the team developed a 'physiologically compatible catholyte' that can be used as a culture medium for microorganisms as well as an electrolyte that allows the electrolysis to occur sufficiently without inhibiting the growth of microorganisms, without having to have a additional separation and purification process, which allowed the acide to be supplied directly to microorganisms.
Through this, the electrolyte solution containing formic acid made from CO2 enters the fermentation tank, is used for microbial culture, and enters the electrolyzer to be circulated, maximizing the utilization of the electrolyte solution and remaining formic acid. In addition, a filter was installed to ensure that only the electrolyte solution with any and all microorganisms that can affect the electrosis filtered out is supplied back to the electrolyzer, and that the microorganisms exist only in the fermenter, designing the two system to work well together with utmost efficiency.
Through the developed hybrid system, the produced bioplastic, poly-3-hydroxybutyrate (PHB), of up to 83% of the cell dry weight was produced from CO2, which produced 1.38g of PHB from a 4 cm2 electrode, which is the world's first gram(g) level production and is more than 20 times more productive than previous research. In addition, the hybrid system is expected to be applied to various industrial processes in the future as it shows promises of the continuous culture system.
The corresponding authors, Professor Hyunjoo Lee and Distinguished Professor Sang Yup Lee noted that “The results of this research are technologies that can be applied to the production of various chemical substances as well as bioplastics, and are expected to be used as key parts needed in achieving carbon neutrality in the future.”
This research was received and performed with the supports from the CO2 Reduction Catalyst and Energy Device Technology Development Project, the Heterogeneous Atomic Catalyst Control Project, and the Next-generation Biorefinery Source Technology Development Project to lead the Biochemical Industry of the Oil-replacement Eco-friendly Chemical Technology Development Program by the Ministry of Science and ICT.
Figure 1. Schematic diagram and photo of the biohybrid CO2 electrolysis system.
(A) A conceptual scheme and (B) a photograph of the biohybrid CO2 electrolysis system. (C) A detailed scheme of reaction inside the system. Gaseous CO2 was converted to formate in the electrolyzer, and the formate was converted to PHB by the cells in the fermenter. The catholyte was developed so that it is compatible with both CO2 electrolysis and fermentation and was continuously circulated.
2023.03.30 View 6672 -
KAIST leads AI-based analysis on drug-drug interactions involving Paxlovid
KAIST (President Kwang Hyung Lee) announced on the 16th that an advanced AI-based drug interaction prediction technology developed by the Distinguished Professor Sang Yup Lee's research team in the Department of Biochemical Engineering that analyzed the interaction between the PaxlovidTM ingredients that are used as COVID-19 treatment and other prescription drugs was published as a thesis. This paper was published in the online edition of 「Proceedings of the National Academy of Sciences of America」 (PNAS), an internationally renowned academic journal, on the 13th of March.
* Thesis Title: Computational prediction of interactions between Paxlovid and prescription drugs (Authored by Yeji Kim (KAIST, co-first author), Jae Yong Ryu (Duksung Women's University, co-first author), Hyun Uk Kim (KAIST, co-first author), and Sang Yup Lee (KAIST, corresponding author))
In this study, the research team developed DeepDDI2, an advanced version of DeepDDI, an AI-based drug interaction prediction model they developed in 2018. DeepDDI2 is able to compute for and process a total of 113 drug-drug interaction (DDI) types, more than the 86 DDI types covered by the existing DeepDDI.
The research team used DeepDDI2 to predict possible interactions between the ingredients (ritonavir, nirmatrelvir) of Paxlovid*, a COVID-19 treatment, and other prescription drugs. The research team said that while among COVID-19 patients, high-risk patients with chronic diseases such as high blood pressure and diabetes are likely to be taking other drugs, drug-drug interactions and adverse drug reactions for Paxlovid have not been sufficiently analyzed, yet. This study was pursued in light of seeing how continued usage of the drug may lead to serious and unwanted complications.
* Paxlovid: Paxlovid is a COVID-19 treatment developed by Pfizer, an American pharmaceutical company, and received emergency use approval (EUA) from the US Food and Drug Administration (FDA) in December 2021.
The research team used DeepDDI2 to predict how Paxrovid's components, ritonavir and nirmatrelvir, would interact with 2,248 prescription drugs. As a result of the prediction, ritonavir was predicted to interact with 1,403 prescription drugs and nirmatrelvir with 673 drugs.
Using the prediction results, the research team proposed alternative drugs with the same mechanism but low drug interaction potential for prescription drugs with high adverse drug events (ADEs). Accordingly, 124 alternative drugs that could reduce the possible adverse DDI with ritonavir and 239 alternative drugs for nirmatrelvir were identified.
Through this research achievement, it became possible to use an deep learning technology to accurately predict drug-drug interactions (DDIs), and this is expected to play an important role in the digital healthcare, precision medicine and pharmaceutical industries by providing useful information in the process of developing new drugs and making prescriptions.
Distinguished Professor Sang Yup Lee said, "The results of this study are meaningful at times like when we would have to resort to using drugs that are developed in a hurry in the face of an urgent situations like the COVID-19 pandemic, that it is now possible to identify and take necessary actions against adverse drug reactions caused by drug-drug interactions very quickly.”
This research was carried out with the support of the KAIST New-Deal Project for COVID-19 Science and Technology and the Bio·Medical Technology Development Project supported by the Ministry of Science and ICT.
Figure 1. Results of drug interaction prediction between Paxlovid ingredients and representative approved drugs using DeepDDI2
2023.03.16 View 5197 -
Overview of the 30-year history of metabolic engineering
< Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering at KAIST >
A research team comprised of Gi Bae Kim, Dr. So Young Choi, Dr. In Jin Cho, Da-Hee Ahn, and Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering at KAIST reported the 30-year history of metabolic engineering, highlighting examples of recent progress in the field and contributions to sustainability and health. Their paper “Metabolic engineering for sustainability and health” was published online in the 40th anniversary special issue of Trends in Biotechnology on January 10, 2023.
Metabolic engineering, a discipline of engineering that modifies cell phenotypes through molecular and genetic-level manipulations to improve cellular activities, has been studied since the early 1990s, and has progressed significantly over the past 30 years. In particular, metabolic engineering has enabled the engineering of microorganisms for the development of microbial cell factories capable of efficiently producing chemicals and materials as well as degrading recalcitrant contaminants.
This review article revisited how metabolic engineering has advanced over the past 30 years, from the advent of genetic engineering techniques such as recombinant DNA technologies to recent breakthroughs in systems metabolic engineering and data science aided by artificial intelligence. The research team highlighted momentous events and achievements in metabolic engineering, providing both trends and future directions in the field. Metabolic engineering’s contributions to bio-based sustainable chemicals and clean energy, health, and bioremediation were also reviewed. Finally, the research team shared their perspectives on the future challenges impacting metabolic engineering than must be overcome in order to achieve advancements in sustainability and health.
Distinguished Professor Sang Yup Lee said, “Replacing fossil resource-based chemical processes with bio-based sustainable processes for the production of chemicals, fuels, and materials using metabolic engineering has become our essential task for the future. By looking back on the 30+ years of metabolic engineering, we aimed to highlight the contributions of metabolic engineering to achieve sustainability and good health.” He added, “Metabolic engineering will play an increasingly important role as a key solution to the climate crisis, environmental pollution, food and energy shortages, and health problems in aging societies.”
< Figure: Metabolic Engineering Timeline >
2023.01.25 View 7605