Ministry+of+Science+and+ICT
-
Accurate Detection of Low-Level Somatic Mutation in Intractable Epilepsy
KAIST medical scientists have developed an advanced method for perfectly detecting low-level somatic mutation in patients with intractable epilepsy. Their study showed that deep sequencing replicates of major focal epilepsy genes accurately and efficiently identified low-level somatic mutations in intractable epilepsy.
According to the study, their diagnostic method could increase the accuracy up to 100%, unlike the conventional sequencing analysis, which stands at about 30% accuracy. This work was published in Acta Neuropathologica.
Epilepsy is a neurological disorder common in children. Approximately one third of child patients are diagnosed with intractable epilepsy despite adequate anti-epileptic medication treatment.
Somatic mutations in mTOR pathway genes, SLC35A2, and BRAF are the major genetic causes of intractable epilepsies. A clinical trial to target Focal Cortical Dysplasia type II (FCDII), the mTOR inhibitor is underway at Severance Hospital, their collaborator in Seoul, Korea. However, it is difficult to detect such somatic mutations causing intractable epilepsy because their mutational burden is less than 5%, which is similar to the level of sequencing artifacts. In the clinical field, this has remained a standing challenge for the genetic diagnosis of somatic mutations in intractable epilepsy.
Professor Jeong Ho Lee’s team at the Graduate School of Medical Science and Engineering analyzed paired brain and peripheral tissues from 232 intractable epilepsy patients with various brain pathologies at Severance Hospital using deep sequencing and extracted the major focal epilepsy genes.
They narrowed down target genes to eight major focal epilepsy genes, eliminating almost all of the false positive calls using deep targeted sequencing. As a result, the advanced method robustly increased the accuracy and enabled them to detect low-level somatic mutations in unmatched Formalin Fixed Paraffin Embedded (FFPE) brain samples, the most clinically relevant samples.
Professor Lee conducted this study in collaboration with Professor Dong Suk Kim and Hoon-Chul Kang at Severance Hospital of Yonsei University. He said, “This advanced method of genetic analysis will improve overall patient care by providing more comprehensive genetic counseling and informing decisions on alternative treatments.”
Professor Lee has investigated low-level somatic mutations arising in the brain for a decade. He is developing innovative diagnostics and therapeutics for untreatable brain disorders including intractable epilepsy and glioblastoma at a tech-startup called SoVarGen. “All of the technologies we used during the research were transferred to the company. This research gave us very good momentum to reach the next phase of our startup,” he remarked.
The work was supported by grants from the Suh Kyungbae Foundation, a National Research Foundation of Korea grant funded by the Ministry of Science and ICT, the Korean Health Technology R&D Project from the Ministry of Health & Welfare, and the Netherlands Organization for Health Research and Development.
(Figure: Landscape of somatic and germline mutations identified in intractable epilepsy patients. a Signaling pathways for all of the mutated genes identified in this study. Bold: somatic mutation, Regular: germline mutation. b The distribution of variant allelic frequencies (VAFs) of identified somatic mutations. c The detecting rate and types of identified mutations according to histopathology. Yellow: somatic mutations, green: two-hit mutations, grey: germline mutations.)
2019.08.14 View 26933 -
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 34450 -
Two Alumni Win the Korea Best Scientist and Technologist Awards
Vice Chairman Ki-Nam Kim (Left) and Distinguished Professor Sukbok Chang (Right)
<ⓒ Photo by MSIT and KOFST>
Distinguished KAIST Professor Sukbok Chang from the Department of Chemistry and Vice Chairman Ki-Nam Kim of Samsung Electronics were selected as the winners of the “2019 Korea Best Scientist and Technologist Awards” by the Ministry of Science and ICT (MSIT) and the Korean Federation of Science and Technology Societies (KOFST). The awards, which were first handed out in 2003, are the highest honor bestowed to the two most outstanding scientists in Korea every year, and this year’s awardees are of greater significance as they are both KAIST alumni.
Professor Chang was recognized for his pioneering achievements and lifetime contributions to the development of carbon-hydrogen activation strategies, especially for carbon-carbon, carbon-nitrogen, and carbon-oxygen formations. His research group has also been actively involved in the development of highly selective catalytic systems allowing the controlled defunctionalization of bio-derived platform substrates under mild conditions, and opening a new avenue for the utilization of biomass-derived platform chemicals. The results of his study have been introduced worldwide through many prestigious journals including Science, Nature Chemistry, and Nature Catalysis, making him one of the world's top 1% researchers by the number of references made to his papers by his peers over four consecutive years from 2015 to 2018.
Vice Chairman Kim, who received his M.E. degree from KAIST’s School of Electrical Engineering in 1983, has been credited with playing a leading role in the development of system semiconductors.
The awards were conferred on July 4 at the opening ceremony of the 2019 Korea Science and Technology Annual Meeting.
(END)
2019.07.09 View 9698 -
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 57388 -
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 52712 -
Scientist of October, Professor Haeshin Lee
(Professor Haeshin Lee from the Department of Chemistry)
Professor Haeshin Lee from the Department of Chemistry received the ‘Science and Technology Award of October’ from the Ministry of Science and ICT and the National Research Foundation of Korea for his contribution to developing an antibleeding injection needle. This novel outcome will fundamentally prevent the problem of secondary infections of AIDS, Ebola and Hepatitis viruses transmitting from patients to medical teams.
This needle’s surface is coated with hemostatic materials. Its concept is simple and the key to this technology is to make materials that are firmly coated on the needle so that they can endure frictional force when being injected into skin and blood vessels. Moreover, the materials should be adhesive to skin and the interior of blood vessels, but harmless to humans.
Professor Lee found a solution from natural polymer ingredients. Catecholamine can be found in mussels. Professor Lee conjugated catechol groups on the chitosan backbone. He applied this mussel-inspired adhesive polymer Chitosan-catechol, which immediately forms an adhesive layer with blood, as a bioadhesion for the antibleeding injection needle.
Professor Lee said, “Chitosan-catechol, which copies the adhesive mechanism of mussels, shows high solubility in physiological saline as well as great mucoadhesion. Hence, it is perfectly suitable for coating the injection needle. Combining it with proteins allows for efficient drug delivery to the heart, which is a challenging injection location, so it will be also useful for treating incurable heart disease.”
2018.10.05 View 8400 -
Taming AI: Engineering, Ethics, and Policy
(Professor Lee, Professor Koene, Professor Walsh, and Professor Ema (from left))
Can AI-powered robotics could be adequate companions for humans? Will the good faith of users and developers work for helping AI-powered robots become the new tribe of the digital future?
AI’s efficiency is creating new socio-economic opportunities in the global market. Despite the opportunities, challenges still remain. It is said that efficiency-enforcing algorithms through deep learning will take an eventual toll on human dignity and safety, bringing out the disastrous fiascos featured in the Terminator movies.
A research group at the Korean Flagship AI Project for Emotional Digital Companionship at KAIST Institute for AI (KI4AI) and the Fourth Industrial Intelligence Center at KAIST Institute co-hosted a seminar, “Taming AI: Engineering, Ethics, and Policy” last week to discuss ways to better employ AI technologies in ways that upholds human values.
The KI4AI has been conducting this flagship project from the end of 2016 with the support of the Ministry of Science and ICT.
The seminar brought together three speakers from Australia, Japan, and the UK to better fathom the implications of the new technology emergence from the ethical perspectives of engineering and discuss policymaking for the responsible usage of technology.
Professor Toby Walsh, an anti-autonomous weapon activist from New South Wales University in Australia continued to argue the possible risk that AI poses to malfunction. He said that an independent ethics committee or group usually monitors academic institutions’ research activities in order to avoid any possible mishaps.
However, he said there is no independent group or committee monitoring the nature of corporations’ engagement of such technologies, while its possible threats against humanity are alleged to be growing. He mentioned that Google’s and Amazon’s information collecting also pose a potent threat. He said that ethical standards similar to academic research integrity should be established to avoid the possible restricting of the dignity of humans and mass destruction. He hoped that KAIST and Google would play a leading role in establishing an international norm toward this compelling issue.
Professor Arisa Ema from the University of Tokyo provided very compelling arguments for thinking about the duplicity of technology and how technology should serve the public interest without any bias against gender, race, and social stratum. She pointed out the information dominated by several Western corporations like Google. She said that such algorithms for deep learning of data provided by several Western corporations will create very biased information, only applicable to limited races and classes.
Meanwhile, Professor Ansgar Koene from the University of Nottingham presented the IEEE’s global initiative on the ethics of autonomous and intelligence systems. He shared the cases of industry standards and ethically-aligned designs made by the IEEE Standards Association. He said more than 250 global cross-disciplinary thought leaders from around the world joined to develop ethical guidelines called Ethically Aligned Design (EAD) V2. EAD V2 includes methodologies to guide ethical research and design, embedding values into autonomous intelligence systems among others. For the next step beyond EAD V2, the association is now working for IEEE P70xx Standards Projects, detailing more technical approaches.
Professor Soo Young Lee at KAIST argued that the eventual goal of complete AI is to have human-like emotions, calling it a new paradigm for the relationship between humans and AI-robots. According to Professor Lee, AI-powered robots will serve as a good companion for humans. “Especially in aging societies affecting the globe, this will be a very viable and practical option,” he said.
He pointed out, “Kids learn from parents’ morality and social behavior. Users should have AI-robots learn morality as well. Their relationships should be based on good faith and trust, no longer that of master and slave. He said that liability issues for any mishap will need to be discussed further, but basically each user and developer should have their own responsibility when dealing with these issues.
2018.06.26 View 7742 -
KAIST Team Reaching Out with Appropriate Technology
(The gold prize winning team of KATT)
The KAIST Appropriate Technology Team (KATT) consisting of international students at KAIST won the gold and silver prizes at ‘The 10th Creative Design Competition for the Other 90 Percent.’
More than 218 students from 50 teams nationwide participated in the competition hosted by the Ministry of Science and ICT last month.
The competition was created to discover appropriate technology and sustainable design items to enhance the quality of life for those with no or few accessible technologies.
A team led by Juan Luis Gonzalez Bello, graduate student from the School of Electrical Engineering received the gold prize for presenting a prosthetic arm. Their artificial arm was highly recognized for its affordability and good manageability. The team said that it cost less than 10 US dollars to construct from materials available in underprivileged regions and was easy to assemble.
Sophomore Hutomo Calvin from the Department of Materials Science & Engineering also worked on the prosthetic arm project with freshmen Bella Godiva, Stephanie Tan, and Koptieuov Yearbola.
Alexandra Tran, senior from the School of Electrical Engineering led the silver prize winning team. Her team developed a portable weather monitor, ‘Breathe Easy’. She worked with Alisher Tortay, senior from the School of Computing, Ashar Alam, senior from the Department of Mechanical Engineering, Bereket Eshete, junior from the School of Computing, and Marthens Hakzimana, sophomore from the Department of Mechanical Engineering.
This weather monitor is a low-cost but efficient air quality monitor. The team said it just cost less than seven US dollars to construct the monitor.KAIST students have now won the gold prize for two consecutive years.
2018.06.19 View 9039 -
Professor Hee-Sung Park Named Scientist of May
(Professor Hee-Sung Park)
Professor Hee-Sung Park from the Department of Chemistry was named ‘Scientist of May’ sponsored by the Ministry of Science and ICT and the National Research Foundation of Korea. Professor Park was honored in recognition of his developing a tool to engineer designer proteins via diverse chemical modifications. This approach provides a novel platform for investigating numerous diseases such as cancer and dementia.
His research focuses on the production of synthetic proteins and the generation of diverse protein functions as well as the designing and engineering of new translation machinery for genetic code expansion, and the application of synthetic biology techniques for basic cell biology and applied medical science.
Post-translational modifications (PTMs) are constantly taking place during or after protein biosynthesis. PTMs play a vital role in expanding protein functional diversity and, as a result, critically affect numerous biological processes. Abnormal PTMs have been known to trigger various diseases including cancer and dementia. Therefore, this technology enables proteins to reproduce with specific modifications at selected residues and will significantly help establish experimental strategies to investigate fundamental biological mechanisms including the development of targeted cancer therapies.
Professor Park also received 10 million KRW in prize money.
2018.05.04 View 8159 -
Scientist of March, Professor Hee-Seung Lee
(Professor Hee-Seung Lee)
Professor Hee-Seung Lee from the Department of Chemistry at KAIST received the ‘Science and Technology Award of the Month’ awarded by the Ministry of ICT and Science, and the National Research Foundation of Korea for March 2018.
Professor Lee has been recognized for successfully producing peptide-based molecular machines, which used to be made of metals.
The methodology can be translated into magnetotactic behavior at the macroscopic scale, which is reminiscent of magnetosomes in magnetotactic bacteria.
The team employed foldectures, self-assembled molecular architectures of β-peptide foldamers, to develop the peptide-based molecular machines that uniformly align with respect to an applied static magnetic field.
Professor Lee said, “Molecular machines are widely used in the field of medical engineering or material science; however, there were limitations for developing the machines using magnetic fields. By developing peptide-based molecular machines, we were able to develop body-friendly molecular machines.”
Every month, the Ministry of ICT and Science and the National Research Foundation of Korea award a cash prize worth 10,000,000 KRW to a scientist who has contributed to science and technology with outstanding research and development performance.
2018.03.15 View 7795 -
KAIST, First to Win the Cube Satellite Competition
Professor Hyochoong Bang from the Department of Aerospace Engineering and his team received the Minister of Science and ICT Award at the 1st Cube Satellite Competition.
The team actually participated in the competition in 2012, but it took several years for the awarding ceremony since it took years for the satellites to be designed, produced, and launched.
The KAIST team successfully developed a cube satellite, named ‘Little Intelligent Nanosatellite of KAIST (LINK)’ and completed its launch in April 2017.
LINK (size: 20cmx10cmx10cm, weight: 2kg) mounted mass spectrometry and Langmuir probe for Earth observation. The Langmuir probe was developed by Professor Kyoung Wook Min from the Department of Physics, KAIST.
Yeerang Lim, a PhD student from the Department of Aerospace Engineering said, “I still remember the feeling that I had on the day when LINK launched into orbit and sent back signals. I hope that space exploration is not something far away but attainable for us in near future.”
2018.02.22 View 9276 -
First Female Grand Prize Awardee of Samsung Humantech
Yeunhee Huh, PhD candidate (Professor Gyu-Hyeong Cho) from the School of Electrical Engineering received the grand prize of the 24th Humantech Paper Award. She is the first female recipient of this prize since its establishment in 1994. The Humantech Paper Award is hosted by Samsung Electronics and sponsored by the Ministry of Science and ICT with JoongAng Daily Newspaper. Her paper is titled, ‘A Hybrid Structure Dual-Path Step-Down Converter with 96.2％ Peak Efficiency using 250mΩ Large-DCR Inductor’. Electronic devices require numerous chips and have a power converter to supply energy adequately. She proposed a new structure to enhance energy efficiency by combining inductors and capacitors. Enhancing energy efficiency can reduce energy loss, which prolongs battery hours and solves overheating of devices; for instance, energy loss leads to the overheating issue affecting phone chargers. This technology can be applied to various electronic devices, such as cell phones, laptops, and drones. Huh said, “Power has to go up in order to meet customers’ needs; however the overheating problem emerges during this process. This problem affects surrounding circuits and causes other issues, such as malfunctions of electronic devices. This technology may vary according to the conditions, but it can enhance energy efficiency up to 4%.”During the ceremony, about eight hundred million KRW worth cash prizes was conferred to 119 papers. KAIST (44 papers) and Gyeonggi Science High School (6 papers) received special awards given to the schools.
2018.02.12 View 7555