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A KAIST Research Team Identifies a Cancer Reversion Mechanism
Despite decades of intensive cancer research by numerous biomedical scientists, cancer still holds its place as the number one cause of death in Korea. The fundamental reason behind the limitations of current cancer treatment methods is the fact that they all aim to completely destroy cancer cells, which eventually allows the cancer cells to acquire immunity. In other words, recurrences and side-effects caused by the destruction of healthy cells are inevitable. To this end, some have suggested anticancer treatment methods based on cancer reversion, which can revert cancer cells back to normal or near-normal cells under certain conditions. However, the practical development of this idea has not yet been attempted. On June 8, a KAIST research team led by Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering reported to have successfully identified the fundamental principle of a process that can revert cancer cells back to normal cells without killing the cells. Professor Cho’s team focused on the fact that unlike normal cells, which react according to external stimuli, cancer cells tend to ignore such stimuli and only undergo uncontrolled cell division. Through computer simulation analysis, the team discovered that the input-output (I/O) relationships that were distorted by genetic mutations could be reverted back to normal I/O relationships under certain conditions. The team then demonstrated through molecular cell experiments that such I/O relationship recovery also occurred in real cancer cells. The results of this study, written by Dr. Jae Il Joo and Dr. Hwa-Jeong Park, were published in Wiley’s Advanced Science online on June 2 under the title, "Normalizing input-output relationships of cancer networks for reversion therapy." < Image 1. Input-output (I/O) relationships in gene regulatory networks > Professor Kwang-Hyun Cho's research team classified genes into four types by simulation-analyzing the effect of gene mutations on the I/O relationship of gene regulatory networks. (Figure A-J) In addition, by analyzing 18 genes of the cancer-related gene regulatory network, it was confirmed that when mutations occur in more than half of the genes constituting each network, reversibility is possible through appropriate control. (Figure K) Professor Cho’s team uncovered that the reason the distorted I/O relationships of cancer cells could be reverted back to normal ones was the robustness and redundancy of intracellular gene control networks that developed over the course of evolution. In addition, they found that some genes were more promising as targets for cancer reversion than others, and showed through molecular cell experiments that controlling such genes could revert the distorted I/O relationships of cancer cells back to normal ones. < Image 2. Simulation results of restoration of bladder cancer gene regulation network and I/O relationship of bladder cancer cells. > The research team classified the effects of gene mutations on the I/O relationship in the bladder cancer gene regulation network by simulation analysis and classified them into 4 types. (Figure A) Through this, it was found that the distorted input-output relationship between bladder cancer cell lines KU-1919 and HCT-1197 could be restored to normal. (Figure B) < Image 3. Analysis of survival of bladder cancer patients according to reversible gene mutation and I/O recovery experiment of bladder cancer cells. > As predicted through network simulation analysis, Professor Kwang-Hyun Cho's research team confirmed through molecular cell experiments that the response to TGF-b was normally restored when AKT and MAP3K1 were inhibited in the bladder cancer cell line KU-1919. (Figure A-G) In addition, it was confirmed that there is a difference in the survival rate of bladder cancer patients depending on the presence or absence of a reversible gene mutation. (Figure H) The results of this research show that the reversion of real cancer cells does not happen by chance, and that it is possible to systematically explore targets that can induce this phenomenon, thereby creating the potential for the development of innovative anticancer drugs that can control such target genes. < Image 4. Cancer cell reversibility principle > The research team analyzed the reversibility, redundancy, and robustness of various networks and found that there was a positive correlation between them. From this, it was found that reversibility was additionally inherent in the process of evolution in which the gene regulatory network acquired redundancy and consistency. Professor Cho said, “By uncovering the fundamental principles of a new cancer reversion treatment strategy that may overcome the unresolved limitations of existing chemotherapy, we have increased the possibility of developing new and innovative drugs that can improve both the prognosis and quality of life of cancer patients.” < Image 5. Conceptual diagram of research results > The research team identified the fundamental control principle of cancer cell reversibility through systems biology research. When the I/O relationship of the intracellular gene regulatory network is distorted by mutation, the distorted I/O relationship can be restored to a normal state by identifying and adjusting the reversible gene target based on the redundancy of the molecular circuit inherent in the complex network. After Professor Cho’s team first suggested the concept of reversion treatment, they published their results for reverting colorectal cancer in January 2020, and in January 2022 they successfully re-programmed malignant breast cancer cells back into hormone-treatable ones. In January 2023, the team successfully removed the metastasis ability from lung cancer cells and reverted them back to a state that allowed improved drug reactivity. However, these results were case studies of specific types of cancer and did not reveal what common principle allowed cancer reversion across all cancer types, making this the first revelation of the general principle of cancer reversion and its evolutionary origins. This research was funded by the Ministry of Science and ICT of the Republic of Korea and the National Research Foundation of Korea.
Connecting the Dots to Find New Treatments for Breast Cancer
Systems biologists uncovered new ways of cancer cell reprogramming to treat drug-resistant cancers Scientists at KAIST believe they may have found a way to reverse an aggressive, treatment-resistant type of breast cancer into a less dangerous kind that responds well to treatment. The study involved the use of mathematical models to untangle the complex genetic and molecular interactions that occur in the two types of breast cancer, but could be extended to find ways for treating many others. The study’s findings were published in the journal Cancer Research. Basal-like tumours are the most aggressive type of breast cancer, with the worst prognosis. Chemotherapy is the only available treatment option, but patients experience high recurrence rates. On the other hand, luminal-A breast cancer responds well to drugs that specifically target a receptor on their cell surfaces, called estrogen receptor alpha (ERα). KAIST systems biologist Kwang-Hyun Cho and colleagues analyzed the complex molecular and genetic interactions of basal-like and luminal-A breast cancers to find out if there might be a way to switch the former to the latter and give patients a better chance to respond to treatment. To do this, they accessed large amounts of cancer and patient data to understand which genes and molecules are involved in the two types. They then input this data into a mathematical model that represents genes, proteins and molecules as dots and the interactions between them as lines. The model can be used to conduct simulations and see how interactions change when certain genes are turned on or off. “There have been a tremendous number of studies trying to find therapeutic targets for treating basal-like breast cancer patients,” says Cho. “But clinical trials have failed due to the complex and dynamic nature of cancer. To overcome this issue, we looked at breast cancer cells as a complex network system and implemented a systems biological approach to unravel the underlying mechanisms that would allow us to reprogram basal-like into luminal-A breast cancer cells.” Using this approach, followed by experimental validation on real breast cancer cells, the team found that turning off two key gene regulators, called BCL11A and HDAC1/2, switched a basal-like cancer signalling pathway into a different one used by luminal-A cancer cells. The switch reprograms the cancer cells and makes them more responsive to drugs that target ERα receptors. However, further tests will be needed to confirm that this also works in animal models and eventually humans. “Our study demonstrates that the systems biological approach can be useful for identifying novel therapeutic targets,” says Cho. The researchers are now expanding its breast cancer network model to include all breast cancer subtypes. Their ultimate aim is to identify more drug targets and to understand the mechanisms that could drive drug-resistant cells to turn into drug-sensitive ones. This work was supported by the National Research Foundation of Korea, the Ministry of Science and ICT, Electronics and Telecommunications Research Institute, and the KAIST Grand Challenge 30 Project. -Publication Sea R. Choi, Chae Young Hwang, Jonghoon Lee, and Kwang-Hyun Cho, “Network Analysis Identifies Regulators of Basal-like Breast Cancer Reprogramming and Endocrine TherapyVulnerability,” Cancer Research, November 30. (doi:10.1158/0008-5472.CAN-21-0621) -ProfileProfessor Kwang-Hyun ChoLaboratory for Systems Biology and Bio-Inspired EngineeringDepartment of Bio and Brain EngineeringKAIST
3D Visualization and Quantification of Bioplastic PHA in a Living Bacterial Cell
3D holographic microscopy leads to in-depth analysis of bacterial cells accumulating the bacterial bioplastic, polyhydroxyalkanoate (PHA) A research team at KAIST has observed how bioplastic granule is being accumulated in living bacteria cells through 3D holographic microscopy. Their 3D imaging and quantitative analysis of the bioplastic ‘polyhydroxyalkanoate’ (PHA) via optical diffraction tomography provides insights into biosynthesizing sustainable substitutes for petroleum-based plastics. The bio-degradable polyester polyhydroxyalkanoate (PHA) is being touted as an eco-friendly bioplastic to replace existing synthetic plastics. While carrying similar properties to general-purpose plastics such as polyethylene and polypropylene, PHA can be used in various industrial applications such as container packaging and disposable products. PHA is synthesized by numerous bacteria as an energy and carbon storage material under unbalanced growth conditions in the presence of excess carbon sources. PHA exists in the form of insoluble granules in the cytoplasm. Previous studies on investigating in vivo PHA granules have been performed by using fluorescence microscopy, transmission electron microscopy (TEM), and electron cryotomography. These techniques have generally relied on the statistical analysis of multiple 2D snapshots of fixed cells or the short-time monitoring of the cells. For the TEM analysis, cells need to be fixed and sectioned, and thus the investigation of living cells was not possible. Fluorescence-based techniques require fluorescence labeling or dye staining. Thus, indirect imaging with the use of reporter proteins cannot show the native state of PHAs or cells, and invasive exogenous dyes can affect the physiology and viability of the cells. Therefore, it was difficult to fully understand the formation of PHA granules in cells due to the technical limitations, and thus several mechanism models based on the observations have been only proposed. The team of metabolic engineering researchers led by Distinguished Professor Sang Yup Lee and Physics Professor YongKeun Park, who established the startup Tomocube with his 3D holographic microscopy, reported the results of 3D quantitative label-free analysis of PHA granules in individual live bacterial cells by measuring the refractive index distributions using optical diffraction tomography. The formation and growth of PHA granules in the cells of Cupriavidus necator, the most-studied native PHA (specifically, poly(3-hydroxybutyrate), also known as PHB) producer, and recombinant Escherichia coli harboring C. necator PHB biosynthesis pathway were comparatively examined. From the reconstructed 3D refractive index distribution of the cells, the team succeeded in the 3D visualization and quantitative analysis of cells and intracellular PHA granules at a single-cell level. In particular, the team newly presented the concept of “in vivo PHA granule density.” Through the statistical analysis of hundreds of single cells accumulating PHA granules, the distinctive differences of density and localization of PHA granules in the two micro-organisms were found. Furthermore, the team identified the key protein that plays a major role in making the difference that enabled the characteristics of PHA granules in the recombinant E. coli to become similar to those of C. necator. The research team also presented 3D time-lapse movies showing the actual processes of PHA granule formation combined with cell growth and division. Movies showing the living cells synthesizing and accumulating PHA granules in their native state had never been reported before. Professor Lee said, “This study provides insights into the morphological and physical characteristics of in vivo PHA as well as the unique mechanisms of PHA granule formation that undergo the phase transition from soluble monomers into the insoluble polymer, followed by granule formation. Through this study, a deeper understanding of PHA granule formation within the bacterial cells is now possible, which has great significance in that a convergence study of biology and physics was achieved. This study will help develop various bioplastics production processes in the future.” This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (Grants NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557) and the Bio & Medical Technology Development Program (Grant No. 2021M3A9I4022740) from the Ministry of Science and ICT (MSIT) through the National Research Foundation (NRF) of Korea to S.Y.L. This work was also supported by the KAIST Cross-Generation Collaborative Laboratory project. -PublicationSo Young Choi, Jeonghun Oh, JaeHwang Jung, YongKeun Park, and Sang Yup Lee. Three-dimensional label-free visualization and quantification of polyhydroxyalkanoates in individualbacterial cell in its native state. PNAS(https://doi.org./10.1073/pnas.2103956118) -ProfileDistinguished Professor Sang Yup LeeMetabolic Engineering and Synthetic Biologyhttp://mbel.kaist.ac.kr/ Department of Chemical and Biomolecular Engineering KAIST Endowed Chair Professor YongKeun ParkBiomedical Optics Laboratoryhttps://bmokaist.wordpress.com/ Department of PhysicsKAIST
E. coli Engineered to Grow on CO₂ and Formic Acid as Sole Carbon Sources
- An E. coli strain that can grow to a relatively high cell density solely on CO₂ and formic acid was developed by employing metabolic engineering. - Most biorefinery processes have relied on the use of biomass as a raw material for the production of chemicals and materials. Even though the use of CO₂ as a carbon source in biorefineries is desirable, it has not been possible to make common microbial strains such as E. coli grow on CO₂. Now, a metabolic engineering research group at KAIST has developed a strategy to grow an E. coli strain to higher cell density solely on CO₂ and formic acid. Formic acid is a one carbon carboxylic acid, and can be easily produced from CO₂ using a variety of methods. Since it is easier to store and transport than CO₂, formic acid can be considered a good liquid-form alternative of CO₂. With support from the C1 Gas Refinery R&D Center and the Ministry of Science and ICT, a research team led by Distinguished Professor Sang Yup Lee stepped up their work to develop an engineered E. coli strain capable of growing up to 11-fold higher cell density than those previously reported, using CO₂ and formic acid as sole carbon sources. This work was published in Nature Microbiology on September 28. Despite the recent reports by several research groups on the development of E. coli strains capable of growing on CO₂ and formic acid, the maximum cell growth remained too low (optical density of around 1) and thus the production of chemicals from CO₂ and formic acid has been far from realized. The team previously reported the reconstruction of the tetrahydrofolate cycle and reverse glycine cleavage pathway to construct an engineered E. coli strain that can sustain growth on CO₂ and formic acid. To further enhance the growth, the research team introduced the previously designed synthetic CO₂ and formic acid assimilation pathway, and two formate dehydrogenases. Metabolic fluxes were also fine-tuned, the gluconeogenic flux enhanced, and the levels of cytochrome bo3 and bd-I ubiquinol oxidase for ATP generation were optimized. This engineered E. coli strain was able to grow to a relatively high OD600 of 7~11, showing promise as a platform strain growing solely on CO₂ and formic acid. Professor Lee said, “We engineered E. coli that can grow to a higher cell density only using CO₂ and formic acid. We think that this is an important step forward, but this is not the end. The engineered strain we developed still needs further engineering so that it can grow faster to a much higher density.” Professor Lee’s team is continuing to develop such a strain. “In the future, we would be delighted to see the production of chemicals from an engineered E. coli strain using CO₂ and formic acid as sole carbon sources,” he added. -Profile:Distinguished Professor Sang Yup Leehttp://mbel.kaist.ac.krDepartment of Chemical and Biomolecular EngineeringKAIST
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 (firstname.lastname@example.org) https://sites.google.com/view/ehukim Department of Chemical and Biomolecular Engineering -Distinguished Professor Sang Yup Lee (email@example.com) Department of Chemical and Biomolecular Engineering http://mbel.kaist.ac.kr
Three Professors Named KAST Fellows
(Professor Dan Keun Sung at the center) (Professor Y.H. Cho at the center) (Professor K.H. Cho at the center) The Korean Academy of Science and Technology (KAST) inducted three KAIST professors as fellows at the New Year’s ceremony held at KAST on January 12. They were among the 24 newly elected fellows of the most distinguished academy in Korea. The new fellows are Professor Dan Keun Sung of the School of Electrical Engineering, Professor Kwang-Hyun Cho of the Department of Bio and Brain Engineering, and Professor Yong-Hoon Cho of the Department of Physics. Professor Sung was recognized for his lifetime academic achievements in fields related with network protocols and energy ICT. He also played a crucial role in launching the Korean satellites KITSAT-1,2,3 and the establishment of the Satellite Technology Research Center at KAIST. Professor Y.H.Cho has been a pioneer in the field of low-dimensional semiconductor-powered quantum photonics that enables quantum optical research in solid state. He has been recognized as a renowned scholar in this field internationally. Professor K.H.Cho has conducted original research that combines IT and BT in systems biology and has applied novel technologies of electronic modeling and computer simulation analysis for investigating complex life sciences. Professor Cho, who is in his 40s, is the youngest fellow among the newly inducted fellows.
Professor Kwang-Hyun Cho Recognzied by "Scientist of the Month" Award
Professor Kwang-Hyun Cho of KAIST’s Department of Bio and Brain Engineering received the “Scientist of the Month” award in February 2015 from the Ministry of Science, ICT, and Future Planning of the Republic of Korea and the National Research Foundation of Korea. The award was in recognition of Professor Cho’s contribution to the advanced technique of controlling the death of cancer cells based on systems biology, a convergence research in information technology (IT) and biotechnology. Professor Cho has published around 140 articles in international journals, including 34 papers in renowned science journals such as Nature, Science, and Cell in the past three years. His work also includes systems biology textbooks and many entries in international academic encyclopaedia. His field, systems biology, is a new biological research paradigm that identifies and controls the fundamental principles of organisms on a systems level. A well-known tumour suppressor protein, p53, is known to suppress abnormal cell growth and promote apoptosis of can cells, and thus was a focus of research by many scientists, but its effect has been insignificant and brought many side effects. This was due to the complex function of p53 that controls various positive and negative feedbacks. Therefore, there was a limit to understanding the protein with the existing biological approach. However, Professor Cho found the kinetic change and function of p53 via a systems biology approach. By applying IT technology to complex biological networks, he also identified the response to stress and the survival and death signal transduction pathways of cardiomyocytes and developed new control methods for cancer cells. Professor Cho said, “This award served as a momentum to turn over a new leaf.” He added, “I hope convergence research such as my field will bring more innovative ideas on the boundaries of academia.”
Professor Kwang-Hyun Cho publishes Encyclopaedia of Systems Biology
Professor Kwang-Hyun Cho KAIST Biological and Brain Engineering Department’s Professor Kwang-Hyun Cho edited the Encyclopaedia of Systems Biology with three scholars, all experts of Systems Biology in England, Germany and the United States. It is rare that a Korean scientist edits a world renowned academic science encyclopaedia. The Encyclopaedia, published by the New York office of Springer Verlag, was a grand international project five years in the making by 28 editors and 391 scientists with expertise in Systems Biology from around the world. The Encyclopaedia compiles various research areas of Systems Biology, the new academic paradigm of the 21st century through the integration of IT and BT, comprehensively on 3,000 pages in 4 four volumes. Professor Kwang-Hyun Cho, who led this international project, majored in electrical engineering and pioneered the field of Systems Biology, the integrated study of biological sciences and engineering, as a new integrated field of IT since the 1990s. The professor has achieved various innovative research results since then. Recently he has investigated “kernel,” an evolutionary core structure in complex biological networks and developed a new cancer treatment through the state space analysis of the molecular network of cancer cells. His work was published in Science Signalling, a sister journal of Science, as a cover story several times, and contributed to foundational research as well as commercialisation of the integrated fields of IT and BT.
Future of Petrochemical Industry: The Age of Bio-Refineries
The concept of bio-refinery is based on using biomass from seaweeds and non-edible plant sources to produce various materials. Bio-refineries has been looked into with increasing interest in modern times due to the advent of global warming (and the subsequent changes in the atmosphere) and the exhaustion of natural resources. However past 20 years of research in metabolic engineering had a crucial limitation; the need to improve the efficiency of the microorganisms that actually go about converting biomass into biochemical materials. In order to compensate for the inefficiency, Professor Lee Sang Yeop combined systems biology, composite biology, evolutionary engineering to form ‘systems metabolic engineering’. This allows combining various data to explain the organism’s state in a multi-dimensional scope and respond accordingly by controlling the metabolism. The result of the experiment is set as the cover dissertation of ‘Trends in Biotechnology’ magazine’s August edition.
New drug targeting method for microbial pathogens developed using in silico cell
A ripple effect is expected on the new antibacterial discovery using “in silico” cells Featured as a journal cover paper of Molecular BioSystems A research team of Distinguished Professor Sang Yup Lee at KAIST recently constructed an in silico cell of a microbial pathogen that is resistant to antibiotics and developed a new drug targeting method that could effectively disrupt the pathogen"s growth using the in silico cell. Hyun Uk Kim, a graduate research assistant at the Department of Chemical and Biomolecular Engineering, KAIST, conducted this study as a part of his thesis research, and the study was featured as a journal cover paper in the February issue of Molecular BioSystems this year, published by The Royal Society of Chemistry based in Europe. It was relatively easy to treat infectious microbes using antibiotics in the past. However, the overdose of antibiotics has caused pathogens to increase their resistance to various antibiotics, and it has become more difficult to cure infectious diseases these days. A representative microbial pathogen is Acinetobacter baumannaii. Originally isolated from soils and water, this microorganism did not have resistance to antibiotics, and hence it was easy to eradicate them if infected. However, within a decade, this miroorganism has transformed into a dreadful super-bacterium resistant to antibiotics and caused many casualties among the U.S. and French soldiers who were injured from the recent Iraqi war and infected with Acinetobacter baumannaii. Professor Lee’s group constructed an in silico cell of this A. baumannii by computationally collecting, integrating, and analyzing the biological information of the bacterium, scattered over various databases and literatures, in order to study this organism"s genomic features and system-wide metabolic characteristics. Furthermore, they employed this in silico cell for integrative approaches, including several network analysis and analysis of essential reactions and metabolites, to predict drug targets that effectively disrupt the pathogen"s growth. Final drug targets are the ones that selectively kill pathogens without harming human body. Here, essential reactions refer to enzymatic reactions required for normal metabolic functioning in organisms, while essential metabolites indicate chemical compounds required in the metabolism for proper functioning, and their removal brings about the effect of simultaneously disrupting their associated enzymes that interact with them. This study attempted to predict highly reliable drug targets by systematically scanning biological components, including metabolic genes, enzymatic reactions, that constitute an in silico cell in a short period of time. This research achievement is highly regarded as it, for the first time, systematically scanned essential metabolites for the effective drug targets using the concept of systems biology, and paved the way for a new antibacterial discovery. This study is also expected to contribute to elucidating the infectious mechanism caused by pathogens. "Although tons of genomic information is poured in at this moment, application research that efficiently converts this preliminary information into actually useful information is still lagged behind. In this regard, this study is meaningful in that medically useful information is generated from the genomic information of Acinetobacter baumannii," says Professor Lee. "In particular, development of this organism"s in silico cell allows generation of new knowledge regarding essential genes and enzymatic reactions under specific conditions," he added. This study was supported by the Korean Systems Biology Project of the Ministry of Education, Science and Technology, and the patent for the development of in silico cells of microbial pathogens and drug targeting methods has been filed. [Picture 1 Cells in silico] [Picture 2 A process of generating drug targets without harming human body while effectively disrupting the growth of a pathogen, after predicting metabolites from in silico cells]
Prof. Cho Elected Editor-in-Chief of Systems Biology
Prof. Kwang-Hyun Cho of Department of Bio and Brain Engineering at KAIST has been recently elected editor-in-chief of the Systems Biology, an international journal published by the London-based Institution of Engineering and Technology (IET), the university authorities said on Wednesday (Sept. 23) By the year 2012, Cho will oversee the editorial process of the journal covering intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. IET, one of the world"s leading professional societies for the engineering and technology community, has a worldwide membership of more than 150,000. Prof. Cho"s research interests cover the areas of systems science with bio-medical applications including systems biology and bio-inspired engineering based on molecular systems biology. He is currently an editorial board member of Systems and Synthetic Biology (Springer, Netherlands, from 2006), BMC Systems Biology (BMC, London, U.K., from 2007), Gene Regulation and Systems Biology (Libertas Academica, New Zealand, from 2007), and Bulletin of Mathematical Biology (Springer, New York, from 2008), and an editorial advisory board member of Molecular BioSystems (The Royal Society of Chemistry, U.K.).
Prof. Cho Appointed Editor-in-Chief of Systems Biology Encyclopedia
Prof. Kwang-Hyun Cho of the Department of Bio and Brain Engineering, KAIST, has been appointed as the editor-in-chief of the Encyclopedia of Systems Biology which is currently in development by Springer, a New York-based publishing company, university authorities said on Monday (July 6). Prof. Cho will share the position with three other eminent scholars from Britain, Germany and the United States. Cho will be responsible for selecting editorial members for each section of the Encyclopedia and overseeing the overall editorial process. The Encyclopedia of Systems Biology is a multi-volume reference compilation of the research outcomes in the field of systems biology all over the world. The ESB will consist of alphabetically ordered description of systems biology concepts and is envisaged to ultimately comprise 6-12 volumes. Publication of the Encyclopedia is scheduled for 2011.
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