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Deciphering Brain Somatic Mutations Associated with Alzheimer's Disease
Researchers have found a potential link between non-inherited somatic mutations in the brain and the progression of Alzheimer’s disease
Researchers have identified somatic mutations in the brain that could contribute to the development of Alzheimer’s disease (AD). Their findings were published in the journal Nature Communications last week.
Decades worth of research has identified inherited mutations that lead to early-onset familial AD. Inherited mutations, however, are behind at most half the cases of late onset sporadic AD, in which there is no family history of the disease. But the genetic factors causing the other half of these sporadic cases have been unclear.
Professor Jeong Ho Lee at the Graduate School of Medical Science and Engineering and colleagues analysed the DNA present in post-mortem hippocampal formations and in blood samples from people aged 70 to 96 with AD and age-matched controls. They specifically looked for non-inherited somatic mutations in their brains using high-depth whole exome sequencing.
The team developed a bioinformatics pipeline that enabled them to detect low-level brain somatic single nucleotide variations (SNVs) – mutations that involve the substitution of a single nucleotide with another nucleotide. Brain somatic SNVs have been reported on and accumulate throughout our lives and can sometimes be associated with a range of neurological diseases.
The number of somatic SNVs did not differ between individuals with AD and non-demented controls. Interestingly, somatic SNVs in AD brains arise about 4.8 times more slowly than in blood. When the team performed gene-set enrichment tests, 26.9 percent of the AD brain samples had pathogenic brain somatic SNVs known to be linked to hyperphosphorylation of tau proteins, which is one of major hallmarks of AD.
Then, they pinpointed a pathogenic SNV in the PIN1 gene, a cis/trans isomerase that balances phosphorylation in tau proteins, found in one AD patient’s brain. They found the mutation was 4.9 time more abundant in AT8-positive – a marker for hyper-phosphorylated tau proteins– neurons in the entorhinal cortex than the bulk hippocampal tissue. Furthermore, in a series of functional assays, they observed the mutation causing a loss of function in PIN1 and such haploinsufficiency increased the phosphorylation and aggregation of tau proteins.
“Our study provides new insights into the molecular genetic factors behind Alzheimer’s disease and other neurodegenerative diseases potentially linked to somatic mutations in the brain,” said Professor Lee.
The team is planning to expand their study to a larger cohort in order to establish stronger links between these brain somatic mutations and the pathogenesis of Alzheimer’s disease.
(Figure 1. Bioinformatic pipeline for detecting low-level brain somatic mutations in AD and non-AD.)
(Figure 2. Pathogenic brain somatic mutations associated with tau phosphorylation are significantly enriched in AD brains.)
(Figure 3. A pathogenic brain somatic mutation in PIN1 (c. 477 C>T) is a loss-of-function and related functional assays show its haploinsufficiency increases phosphorylation and aggregation of tau.)
2019.07.19 View 36202 -
Mathematical Modeling Makes a Breakthrough for a New CRSD Medication
PhD Candidate Dae Wook Kim (Left) and Professor Jae Kyoung Kim (Right)
- Systems approach reveals photosensitivity and PER2 level as determinants of clock-modulator efficacy -
Mathematicians’ new modeling has identified major sources of interspecies and inter-individual variations in the clinical efficacy of a clock-modulating drug: photosensitivity and PER2 level. This enabled precision medicine for circadian disruption.
A KAIST mathematics research team led by Professor Jae Kyoung Kim, in collaboration with Pfizer, applied a combination of mathematical modeling and simulation tools for circadian rhythms sleep disorders (CRSDs) to analyze the animal data generated by Pfizer. This study was reported in Molecular Systems Biology as the cover article on July 8.
Pharmaceutical companies have conducted extensive studies on animals to determine the candidacy of this new medication. However, the results of animal testing do not always translate to the same effects in human trials. Furthermore, even between humans, efficacy differs across individuals depending on an individual’s genetic and environmental factors, which require different treatment strategies.
To overcome these obstacles, KAIST mathematicians and their collaborators developed adaptive chronotherapeutics to identify precise dosing regimens that could restore normal circadian phase under different conditions.
A circadian rhythm is a 24-hour cycle in the physiological processes of living creatures, including humans. A biological clock in the hypothalamic suprachiasmatic nucleus in the human brain sets the time for various human behaviors such as sleep.
A disruption of the endogenous timekeeping system caused by changes in one’s life pattern leads to advanced or delayed sleep-wake cycle phase and a desynchronization between sleep-wake rhythms, resulting in CRSDs. To restore the normal timing of sleep, timing of the circadian clock could be adjusted pharmacologically.
Pfizer identified PF-670462, which can adjust the timing of circadian clock by inhibiting the core clock kinase of the circadian clock (CK1d/e). However, the efficacy of PF-670462 significantly differs between nocturnal mice and diurnal monkeys, whose sleeping times are opposite.
The research team discovered the source of such interspecies variations in drug response by performing thousands of virtual experiments using a mathematical model, which describes biochemical interactions among clock molecules and PF-670462. The result suggests that the effect of PF-670462 is reduced by light exposure in diurnal primates more than in nocturnal mice. This indicates that the strong counteracting effect of light must be considered in order to effectively regulate the circadian clock of diurnal humans using PF-670462.
Furthermore, the team also found the source of inter-patients variations in drug efficacy using virtual patients whose circadian clocks were disrupted due to various mutations. The degree of perturbation in the endogenous level of the core clock molecule PER2 affects the efficacy.
This explains why the clinical outcomes of clock-modulating drugs are highly variable and certain subtypes are unresponsive to treatment. Furthermore, this points out the limitations of current treatment strategies tailored to only the patient’s sleep and wake time but not to the molecular cause of sleep disorders.
PhD candidate Dae Wook Kim, who is the first author, said that this motivates the team to develop an adaptive chronotherapy, which identifies a personalized optimal dosing time of day by tracking the sleep-wake up time of patients via a wearable device and allows for a precision medicine approach for CRSDs.
Professor Jae Kyoung Kim said, "As a mathematician, I am excited to help enable the advancement of a new drug candidate, which can improve the lives of so many patients. I hope this result promotes more collaborations in this translational research.”
This research was supported by a Pfizer grant to KAIST (G01160179), the Human Frontiers Science Program Organization (RGY0063/2017), and a National Research Foundation (NRF) of Korea Grant (NRF-2016 RICIB 3008468 and NRF-2017-Fostering Core Leaders of the Future Basic Science Program/ Global Ph.D. Fellowship Program).
Figure 1. Interspecies and Inter-patients Variations in PF-670462 Efficacy
Figure 2. Journal Cover Page
Publication:
Dae Wook Kim, Cheng Chang, Xian Chen, Angela C Doran, Francois Gaudreault, Travis Wager, George J DeMarco, and Jae Kyoung Kim. 2019. Systems approach reveals photosensitivity and PER2 level as determinants of clock-modulator efficacy. Molecular Systems Biology. EMBO Press, Heidelberg, Germany, Vol. 15, Issue No. 7, Article, 16 pages. https://doi.org/10.15252/msb.20198838
Profile: Prof. Jae Kyoung Kim, PhD
jaekkim@kaist.ac.kr
http://mathsci.kaist.ac.kr/~jaekkim
Associate Professor
Department of Mathematical Sciences
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
Profile: Dae Wook Kim, PhD Candidate
0308kdo@kaist.ac.kr
http://mathsci.kaist.ac.kr/~jaekkim
PhD Candidate
Department of Mathematical Sciences
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
Profile: Dr. Cheng Chang, PhD
cheng.chang@pfizer.com
Associate Director of Clinical Pharmacology
Clinical Pharmacology, Global Product Development
Pfizer
https://www.pfizer.com/ Groton 06340, USA
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2019.07.09 View 35791 -
Deep Learning-Powered 'DeepEC' Helps Accurately Understand Enzyme Functions
(Figure: Overall scheme of DeepEC)
A deep learning-powered computational framework, ‘DeepEC,’ will allow the high-quality and high-throughput prediction of enzyme commission numbers, which is essential for the accurate understanding of enzyme functions.
A team of Dr. Jae Yong Ryu, Professor Hyun Uk Kim, and Distinguished Professor Sang Yup Lee at KAIST reported the computational framework powered by deep learning that predicts enzyme commission (EC) numbers with high precision in a high-throughput manner.
DeepEC takes a protein sequence as an input and accurately predicts EC numbers as an output. Enzymes are proteins that catalyze biochemical reactions and EC numbers consisting of four level numbers (i.e., a.b.c.d) indicate biochemical reactions. Thus, the identification of EC numbers is critical for accurately understanding enzyme functions and metabolism.
EC numbers are usually given to a protein sequence encoding an enzyme during a genome annotation procedure. Because of the importance of EC numbers, several EC number prediction tools have been developed, but they have room for further improvement with respect to computation time, precision, coverage, and the total size of the files needed for the EC number prediction.
DeepEC uses three convolutional neural networks (CNNs) as a major engine for the prediction of EC numbers, and also implements homology analysis for EC numbers if the three CNNs do not produce reliable EC numbers for a given protein sequence. DeepEC was developed by using a gold standard dataset covering 1,388,606 protein sequences and 4,669 EC numbers.
In particular, benchmarking studies of DeepEC and five other representative EC number prediction tools showed that DeepEC made the most precise and fastest predictions for EC numbers. DeepEC also required the smallest disk space for implementation, which makes it an ideal third-party software component.
Furthermore, DeepEC was the most sensitive in detecting enzymatic function loss as a result of mutations in domains/binding site residue of protein sequences; in this comparative analysis, all the domains or binding site residue were substituted with L-alanine residue in order to remove the protein function, which is known as the L-alanine scanning method.
This study was published online in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on June 20, 2019, entitled “Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers.”
“DeepEC can be used as an independent tool and also as a third-party software component in combination with other computational platforms that examine metabolic reactions. DeepEC is freely available online,” said Professor Kim.
Distinguished Professor Lee said, “With DeepEC, it has become possible to process ever-increasing volumes of protein sequence data more efficiently and more accurately.”
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT through the National Research Foundation of Korea. This work was also funded by the Bio & Medical Technology Development Program of the National Research Foundation of Korea funded by the Korean government, the Ministry of Science and ICT.
Profile:
-Professor Hyun Uk Kim (ehukim@kaist.ac.kr)
https://sites.google.com/view/ehukim
Department of Chemical and Biomolecular Engineering
-Distinguished Professor Sang Yup Lee (leesy@kaist.ac.kr)
Department of Chemical and Biomolecular Engineering
http://mbel.kaist.ac.kr
2019.07.09 View 37732 -
Three Professors Receive Han Sung Science Awards
Three KAIST professors swept the 2nd Han Sung Science Awards. Professor Bum-Ki Min from the Departments of Mechanical Engineering and Physics, Professor Sun-Kyu Han from the Department of Chemistry, and Professor Seung-Jae Lee from the Department of Biological Sciences won all three awards presented by the Han Sung Scholarship Foundation, which recognizes promising mid-career scientists in the fields of physics, chemistry, and biological sciences. The awards ceremony will take place on August 16 in Hwaseong.
Professor Min was declared as the winner of the physics field in recognition of his outstanding research activities including searching for new application areas for metamaterials and investigating their unexplored functionalities. The metamaterials with a high index of refraction developed by Professor Min’s research team have caught the attention of scientists worldwide, as they can help develop high-resolution imaging systems and ultra-small, hyper-sensitive optical devices.
The chemistry field winner, Professor Han, is the youngest awardee so far at 36 years of age. He is often described as one of the most promising next-generation Korean scientists in the field of the total synthesis of complex natural products. Given the fact that this field takes very long-term research, he is making unprecedented research achievements. He is focusing on convergent and flexible synthetic approaches that enable access to not only a single target but various natural products with structural and biosynthetic relevance as well as unnatural products with higher biological potency.
Professor Lee was recognized for his contributions to the advancement of biological sciences, especially in aging research. Professor Lee’s team is taking a novel approach by further investigating complex interactions between genetic and environmental factors that affect aging, and identifying genes that mediate the effects. The team has been conducting large-scale gene discovery efforts by employing RNA sequencing analysis, RNAi screening, and chemical mutagenesis screening. They are striving to determine the functional significance of candidate genes obtained from these experiments and mechanistically characterize these genes.
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2019.07.03 View 9981 -
Efficiently Producing Fatty Acids and Biofuels from Glucose
Researchers have presented a new strategy for efficiently producing fatty acids and biofuels that can transform glucose and oleaginous microorganisms into microbial diesel fuel, with one-step direct fermentative production.
The newly developed strain, created by Distinguished Professor Sang Yup Lee and his team, showed the highest efficiency in producing fatty acids and biodiesels ever reported. It will be expected to serve as a new platform to sustainably produce a wide array of fatty acid-based products from glucose and other carbon substrates.
Fossil fuels, which have long been energy resources for our daily lives, are now facing serious challenges: depletion of their reserves and their role in global warming. The production of sustainable bio-based renewable energy has emerged as an essential alternative and many studies to replace fossil fuels are underway. One of the representative examples is biodiesel. Currently, it is mainly being produced through the transesterification of vegetable oils or animal fats.
The research team engineered oleaginous microorganisms, Rhodococcus opacus, to produce fatty acids and their derivatives that can be used as biodiesel from glucose, one of the most abundant and cheap sugars derived from non-edible biomass.
Professor Lee’s team has already engineered Escherichia coli to produce short-chain hydrocarbons, which can be used as gasoline (published in Nature as the cover paper in 2013). However, the production efficiency of the short-chain hydrocarbons using E. coli (0.58 g/L) fell short of the levels required for commercialization.
To overcome these issues, the team employed oil-accumulating Rhodococcus opacus as a host strain in this study. First, the team optimized the cultivation conditions of Rhodococcus opacus to maximize the accumulation of oil (triacylglycerol), which serves as a precursor for the biosynthesis of fatty acids and their derivatives. Then, they systematically analyzed the metabolism of the strain and redesigned it to enable higher levels of fatty acids and two kinds of fatty acid-derived biodiesels (fatty acid ethyl esters and long-chain hydrocarbons) to be produced.
They found that the resulting strains produced 50.2, 21.3, and 5.2 g/L of fatty acids, fatty acid ethyl esters, and long-chain hydrocarbons, respectively. These are all the highest concentrations ever reported by microbial fermentations. It is expected that these strains can contribute to the future industrialization of microbial-based biodiesel production.
“This technology creates fatty acids and biodiesel with high efficiency by utilizing lignocellulose, one of the most abundant resources on the Earth, without depending on fossil fuels and vegetable or animal oils. This will provide new opportunities for oil and petroleum industries, which have long relied on fossil fuels, to turn to sustainable and eco-friendly biotechnologies,” said Professor Lee.
This paper titled “Engineering of an oleaginous bacterium for the production of fatty acids and fuels” was published in Nature Chemical Biology on June 17.
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT through the National Research Foundation (NRF) of Korea (NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557).
(Figure: Metabolic engineering for the production of free fatty acids (FFAs), fatty acid ethyl esters (FAEEs), and long-chain hydrocarbons (LCHCs) in Rhodococcus opacus PD630. Researchers have presented a new strategy for efficiently producing fatty acids and biofuels that can transform glucose and oleaginous microorganisms into microbial diesel fuel, with one-step direct fermentative production.)
# # #
Source:
Hye Mi Kim, Tong Un Chae, So Young Choi, Won Jun Kim and Sang Yup Lee. Engineering of an oleaginous bacterium for the production of fatty acids and fuels. Nature Chemical Biology ( https://www.nature.com/nchembio/ ) DOI: 10.1038/s41589-019-0295-5
Profile
Dr. Sang Yup Lee
leesy@kaist.ac.kr
Distinguished Professor at the Department of Chemical and Biomolecular Engineering
KAIST
2019.06.19 View 49592 -
Novel Via-Hole-Less Multilevel Metal Interconnection Methods
Forming reliable multi-level metal interconnections is a key technology for integrating devices into organic integrated circuits (ICs). The conventional approach, called “via-hole,” locally removes the insulator and utilizes metal interconnects through the holes. Due to the high sensitivity of organic materials to chemical solvents, heat, and photo-radiation used in conventional “via-hole” methods, alternative printing methods or laser drilling methods have been developed. However, finding a reliable and practical metal interconnection for organic ICs is still challenging.
The research team of KAIST Professor Sung Gap Im and Postech Professor Kim Jae-Joon reported a new interconnection method that does not require via-hole formation, “via-hole-less metal interconnection,” in Nature Communications on June 3.
Metal electrodes in different layers can be isolated from each other by patterned dielectric layers, where they then can be interconnected to others in the open area where the dielectric layer is not present. See the images below. Vapor phase deposition and in-situ patterning of dielectric layer using iCVD (initiated chemical vapor deposition), used in the “via-hole-less” method, ensure a damage-free process for organic semiconductor materials and result in outstanding performance of the organic devices as multilevel metal interconnects are reliably formed. The team successfully demonstrated three-dimensional (3D) stacking of five organic transistors and integrated circuits using the proposed via-hole-less interconnect method. See the image below.
Vapor phase deposition and in-situ patterning of dielectric layer using iCVD (initiated chemical vapor deposition), used in the “via-hole-less” method, ensure a damage-free process for organic semiconductor materials and result in outstanding performance of the organic devices as multilevel metal interconnects are reliably formed. The team successfully demonstrated three-dimensional (3D) stacking of five organic transistors and integrated circuits using the proposed via-hole-less interconnect method. See the image below.
Professor Kim explained, “Our proposed via-hole-less interconnect method using a selectively patterned dielectric overcomes the limitations of the previous time-consuming, one-by-one via-hole formation process and provides reliable methods for creating metal interconnects in organic ICs. We expect the via-hole-less scheme to bring advances to organic IC technology.”
2019.06.18 View 44340 -
5 Biomarkers for Overcoming Colorectal Cancer Drug Resistance Identified
< Professor Kwang-Hyun Cho's Team >
KAIST researchers have identified five biomarkers that will help them address resistance to cancer-targeting therapeutics. This new treatment strategy will bring us one step closer to precision medicine for patients who showed resistance.
Colorectal cancer is one of the most common types of cancer worldwide. The number of patients has surpassed 1 million, and its five-year survival rate significantly drops to about 20 percent when metastasized. In Korea, the surge of colorectal cancer has been the highest in the last 10 years due to increasing Westernized dietary patterns and obesity. It is expected that the number and mortality rates of colorectal cancer patients will increase sharply as the nation is rapidly facing an increase in its aging population.
Recently, anticancer agents targeting only specific molecules of colon cancer cells have been developed. Unlike conventional anticancer medications, these selectively treat only specific target factors, so they can significantly reduce some of the side-effects of anticancer therapy while enhancing drug efficacy.
Cetuximab is the most well-known FDA approved anticancer medication. It is a biomarker that predicts drug reactivity and utilizes the presence of the ‘KRAS’ gene mutation. Cetuximab is prescribed to patients who don’t carry the KRAS gene mutation.
However, even in patients without the KRAS gene mutation, the response rate of Cetuximab is only about fifty percent, and there is also resistance to drugs after targeted chemotherapy. Compared with conventional chemotherapy alone, the life expectancy only lasts five months on average.
In research featured in the FEBS Journal as the cover paper for the April 7 edition, the KAIST research team led by Professor Kwang-Hyun Cho at the Department of Bio and Brain Engineering presented five additional biomarkers that could increase Cetuximab responsiveness using systems biology approach that combines genomic data analysis, mathematical modeling, and cell experiments. The experimental inhibition of newly discovered biomarkers DUSP4, ETV5, GNB5, NT5E, and PHLDA1 in colorectal cancer cells has been shown to overcome Cetuximab resistance in KRAS-normal genes. The research team confirmed that when suppressing GNB5, one of the new biomarkers, it was shown to overcome resistance to Cetuximab regardless of having a mutation in the KRAS gene.
Professor Cho said, “There has not been an example of colorectal cancer treatment involving regulation of the GNB5 gene.” He continued, “Identifying the principle of drug resistance in cancer cells through systems biology and discovering new biomarkers that could be a new molecular target to overcome drug resistance suggest real potential to actualize precision medicine.”
This study was supported by the National Research Foundation of Korea (NRF) and funded by the Ministry of Science and ICT (2017R1A2A1A17069642 and 2015M3A9A7067220).
Image 1. The cover of FEBS Journal for April 2019
2019.05.27 View 59701 -
Engineered Microbial Production of Grape Flavoring
(Image 1: Engineered bacteria that produce grape flavoring.)
Researchers report a microbial method for producing an artificial grape flavor. Methyl anthranilate (MANT) is a common grape flavoring and odorant compound currently produced through a petroleum-based process that uses large volumes of toxic acid catalysts.
Professor Sang-Yup Lee’s team at the Department of Chemical and Biomolecular Engineering demonstrated production of MANT, a naturally occurring compound, via engineered bacteria. The authors engineered strains of Escherichia coli and Corynebacetrium glutamicum to produce MANT through a plant-based engineered metabolic pathway.
The authors tuned the bacterial metabolic pathway by optimizing the levels of AAMT1, the key enzyme in the process. To maximize production of MANT, the authors tested six strategies, including increasing the supply of a precursor compound and enhancing the availability of a co-substrate. The most productive strategy proved to be a two-phase extractive culture, in which MANT was extracted into a solvent. This strategy produced MANT on the scale of 4.47 to 5.74 grams per liter, a significant amount, considering that engineered microbes produce most natural products at a scale of milligrams or micrograms per liter.
According to the authors, the results suggest that MANT and other related molecules produced through industrial processes can be produced at scale by engineered microbes in a manner that would allow them to be marketed as natural one, instead of artificial one.
This study, featured at the Proceeding of the National Academy of Sciences of the USA on May 13, was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT.
(Image 2. Overview of the strategies applied for the microbial production of grape flavoring.)
2019.05.15 View 55625 -
Distinguished Professor Sang Yup Lee Honored with the 23rd NAEK Award
(Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering)
Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering was honored to be the laureate of the 23rd NAEK Award.
The NAEK (National Academy of Engineering of Korea) Award was instituted in 1997 to honor and recognize engineers who have made significant contributions to the development of the engineering and technology field at universities, industries, and institutions. Every year, it is conferred to only one person who has achieved original and world-leading research that has led to national development.
Distinguished Professor Lee is a pioneering scholar of the field of systems metabolic engineering and he was recognized for his significant achievements in the biochemical industry by developing novel microbial bioprocesses. In particular, he is globally renowned for biological plastic synthesis, making or decomposing polymers with microorganisms instead of using fossil resources.
He has produced numerous high-quality research breakthroughs in metabolic and systems engineering. In 2016, he produced an easily degradable plastic with Escherichia coli (E. coli). In 2018, he successfully produced aromatic polyesters, the main material for PET (poly ethylene terephthalate) from E. coli strains. He also identified microorganism structures for PET degradation and improved its degradability with a novel variant.
His research was ranked number one in the research and development division of Top Ten Science and Technology News 2018 announced by Korean Federation of Science & Technology Societies. He is one of highly cited researchers (HCR) ranked in the top 1% by citations for their field by the Clarivate Analytics.
2019.03.21 View 8748 -
A Comprehensive Metabolic Map for Bio-Based Chemicals Production
A KAIST research team completed a metabolic map that charts all available strategies and pathways of chemical reactions that lead to the production of various industrial bio-based chemicals.
The team was led by Distinguished Professor Sang Yup Lee, who has produced high-quality metabolic engineering and systems engineering research for decades, and made the hallmark chemicals map after seven years of studies.
The team presented a very detailed analysis on metabolic engineering for the production of a wide range of industrial chemicals, fuels, and materials. Surveying the current trends in the bio-based production of chemicals in industrial biotechnology, the team thoroughly examined the current status of industrial chemicals produced using biological and/or chemical reactions.
This comprehensive map is expected to serve as a blueprint for the visual and intuitive inspection of biological and/or chemical reactions for the production of interest from renewable resources. The team also compiled an accompanying poster to visually present the synthetic pathways of chemicals in the context of their microbial metabolism.
As metabolic engineering has become increasing powerful in addressing limited fossil resources, climate change, and other environmental issues, the number of microbially produced chemicals using biomass as a carbon source has increased substantially. The sustainable production of industrial chemicals and materials has been explored with micro-organisms as cell factories and renewable nonfood biomass as raw materials for alternative petroleum. The engineering of these micro-organism has increasingly become more efficient and effective with the help of metabolic engineering – a practice of engineering using the metabolism of living organisms to produce a desired metabolite.
With the establishment of systems metabolic engineering – the integration of metabolic engineering with tools and strategies from systems biology, synthetic biology and evolutionary engineering – the speed at which micro-organisms are being engineered has reached an unparalleled pace.
In order to evaluate the current state at which metabolically engineered micro-organisms can produce a large portfolio of industrial chemicals, the team conducted an extensive review of the literature and mapped them out on a poster. This resulting poster, termed the bio-based chemicals map, presents synthetic pathways for industrial chemicals, which consist of biological and/or chemical reactions.
Industrial chemicals and their production routes are presented in the context of central carbon metabolic pathways as these key metabolites serve as precursors for the chemicals to be produced. The resulting biochemical map allows the detection and analysis of optimal synthetic pathways for a given industrial chemical. In addition to the poster, the authors have compiled a list of chemicals that have successfully been produced using micro-organisms and a list of the corresponding companies producing them commercially. This thorough review of the literature and the accompanying analytical summary will be an important resource for researchers interested in the production of chemicals from renewable biomass sources.
Metabolically engineered micro-organisms have already made a huge contribution toward the sustainable production of chemicals using renewable resources. Professor Lee said he wanted a detailed survey of the current state and capacity of bio-based chemicals production.
“We are so excited that this review and poster will expand further discussion on the production of important chemicals through engineered micro-organisms and also combined biological and chemical means in a more sustainable manner,” he explained.
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biofineries from the Ministry of Science and ICT through the National Research Foundation of Korea.
For further information, Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST ( leesy@kaist.ac.kr , Tel: +82-42-350-3930)
Figure: Bio-based chemicals production through biological and chemical routes. This metabolic map describes representative chemicals that can be produced either by biological and/or chemical means. Red arrows represent chemical routes and blue arrows represent biological routes. Intermediate metabolites in the metabolism of a living organism can serve as a platform toward the production of industrially relevant chemicals. A more comprehensive map presented by the team can be found as a poster in the review.
2019.01.15 View 7484 -
KAIST Presents Innovations at CES 2019
Ten of the most innovative technologies spun off from KAIST made a debut at the Consumer Electronics Show (CES) 2019, the world’s largest consumer electronics and IT exhibition being held in Las Vegas from January 8 to 11. The KAIST booth at the CES featured technologies made by KAIST research teams and five startup companies including LiBEST, Memslux, and Green Power. In particular, the KAIST Alumni Association invited 33 aspiring alumni entrepreneurs selected from the KAIST Startup Competition to the show.
At the exhibition, KAIST is presenting innovations in the fields of AI and Bio-IT convergence for the Fourth Industrial Revolution. These include real-time upscaling from Full HD to 4K UHD using AI deep learning-based convolutional neural networks (Professor Munchurl Kim, School of Electrical Engineering) and an AI conversation agent that responds to user’s emotions (Professor Soo-Young Lee, School of Electrical Engineering).
Other technologies include optimal drug target identification by cancer cell type through drug response prediction to be used in personalized cancer treatments (Professor Kwang-Hyun Cho, Department of Bio and Brain Engineering), a nanofiber-based color changing gas sensor with greater sensitivity than conventional paper-based color changing sensors (Professor Il-Doo Kim, Department of Materials Science and Engineering), and functional near-infrared spectroscopy (fNIRS) for brain imaging and muscle fatigue measurement (Professor Hyeonmin Bae, School of Electrical Engineering).
The KAIST booth also features startups founded by KAIST alumni including LiBEST with a flexible lithium polymer secondary cell optimized for smart wearable devices and Rempus with a high-performance lithium ion cell packaging technology for outstanding safety, high capacity, long life, and fast charging.
Green Power and Smart Radar Systems are also joining the booth with a highly efficient and eco-friendly wireless charging system for electrical cars, and a 4D image radar sensor that detects 3D images and speed in real time for applications in self-driving cars, drones, and security systems respectively.
Faculty-founded startup Memslux (CEO Jun-Bo Yoon, School of Electrical Engineering) is presenting a transparent surface light source solution for next-generation display devices.
Associate Vice President of Office of University-Industry Cooperation Kyung Cheol Choi said, “I believe that universities should play a role in connecting technological innovations to business startups for creating value at a global level. In that sense, it is a great opportunity to present innovative technologies from KAIST and promote outstanding KAIST startups at CES 2019. Hopefully, this experience will lead to joint R&D, investment, cooperation, and international technology transfer contracts with leading companies from around the world.”
Here are the five key technologies presented by KAIST at CES 2019.
2019.01.10 View 8505 -
OUIC Presents the Six Most Promising Techs Transferrable to Local SMEs
KAIST will showcase the six most promising technologies for small and medium enterprises (SMEs) on November 14 in the Academic Cultural Complex. To strengthen the competitive edge of local SMEs in Daejeon, the Office of University-Industry made a survey of their technological needs and came up with the six most promising technologies. Developers will introduce their technologies during the session.Besides the introduction of the promising technologies, the session will also provide a program named University to Business (U2B) to match up technologies according to the SMEs’ needs. SMEs who wish to engage in technology transfers can receive counseling and other support programs during the session.First, Professor Seok-Hyung Bae from the Department of Industrial Design will present a technology for controlling cooperation robots. Professor Bae inserted flexible materials between the controllers to allow robots to use both hands stably and operate more accurately and swiftly. It can be applied to automatic robots, industrial robots, and service robots.Professor Hyun Myung from the Department of Civil & Environmental Engineering will demonstrate a robot navigation system in a dynamic indoor and outdoor environment, which can be applied to robotics in logistics, smart factories, and autonomous vehicles. Providing robust simultaneous localization and mapping systems, this technology shows high-performing navigation with low-cost sensors.Meanwhile, Professor Siyoung Choi from the Department of Chemical and Biomolecular Engineering will introduce a technology for forming stable adhesive emulsions. An emulsion is a stable mixture of water and oil. Conventionally, a small amount of surfactant is added to stabilize an emulsion. Here, Professor Choi developed a stable emulsion system without using any chemical substances. This technology can be applied to various fields, including the cosmetics, pharmaceutical, semiconductor, and painting industries. The session will also present smart IoTs platform technology developed by Professor Jinhong Yang from the KAIST Institute for IT Convergence. His technology minimizes errors occurring when multiple IoT devices are connected simultaneously. Professor Yong Keun Park from the Department of Physics will introduce a technology for measuring glycated hemoglobin by using the optical properties of red blood cells. This technology can be applied to make low-cost, small-sized measuring equipment. It can also be used for vitro diagnoses including diabetes, cardiovascular disorders, tumors, kidney disease, and infectious diseases. Professor Yong Man Ro from the School of Electrical Engineering will show technology for biometric access control. Conventional technologies for face recognition fall behind other biometrics. Professor Ro and his team developed a facial dynamics interpreting network which allows very accurate facial recognition by interpreting the relationships between facial local dynamics and estimating facial traits. This technology can be applied to security and communication in finance, computers, and information system.KAIST President Sung-Chul Shin said, “KAIST will continue to support SMEs to have stronger competitiveness in the market. Through technology transfer, we will drive innovation in technological commercialization where a university’s research and development creates economic value.”
2018.11.13 View 9348