research
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One-Step Production of Aromatic Polyesters by E. coli Strains
KAIST systems metabolic engineers defined a novel strategy for microbial aromatic polyesters production fused with synthetic biology from renewable biomass. The team of Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering produced aromatic polyesters from Escherichia coli (E. coli) strains by applying microbial fermentation, employing direct microbial fermentation from renewable feedstock carbohydrates.
This is the first report to determine a platform strain of engineered E. coli capable of producing environmentally friendly aromatic polyesters. This engineered E. coli strain, if desired, has the potential to be used as a platform strain capable of producing various high-valued aromatic polyesters from renewable biomass. This research was published in Nature Communications on January 8.
Conventionally, aromatic polyesters boast solid strength and heat stability so that there has been a great deal of interest in fermentative production of aromatic polyesters from renewable non-food biomass, but without success.
However, aromatic polyesters are only made by feeding the cells with corresponding aromatic monomers as substrates, and have not been produced by direct fermentation from renewable feedstock carbohydrates such as glucose.
To address this issue, the team prescribed the detailed procedure for aromatic polyester production through identifying CoA-transferase that activates phenylalkanoates into their corresponding CoA derivatives. In this process, researchers employed metabolic engineering of E. coli to produce phenylalkanoates from glucose based on genome-scale metabolic flux analysis. In particular, the KAIST team made a modulation of gene expression to produce various aromatic polyesters having different monomer fractions.
The research team successfully produced aromatic polyesters, a non-natural polymer using the strategy that combines systems metabolic engineering and synthetic biology. They succeeded in biosynthesis of various kinds of aromatic polyesters through the system, thus proving the technical excellence of the environmentally friendly biosynthetic system of this research. Furthermore, his team also proved the potential of expanding the range of aromatic polyesters from renewable resources, which is expected to play an important role in the bio-plastic industry.
Professor Lee said, “An eco-friendly and sustainable chemical industry is the key global agenda every nation faces. We are making a research focus to a biochemical industry free from petroleum dependence, and conducting diverse research activities to address the issue. This novel technology we are presenting will serve as an opportunity to advance the biochemical industry moving forward.”
This work was supported by the Intelligent Synthetic Biology Center through the Global Frontier Project (2011-0031963) and also by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557) from the Ministry of Science and ICT through the National Research Foundation of Korea.
Figure: Biosynthesis of aromatic polyesters by metabolically engineered E. coli.This schematic diagram shows the overall conceptualization of how metabolically engineered E. coli produced aromatic polyesters from glucose.
2018.01.09 View 6779 -
Fiber OLEDs, Thinner Than a Hair
(Seonil Kwon, PhD Candidate)
Professor Kyung Cheol Choi from the School of Electrical Engineering and his team succeeded in fabricating highly efficient Organic Light-Emitting Diodes (OLEDs) on an ultra-thin fiber.
The team expects the technology, which produces high-efficiency, long-lasting OLEDs, can be widely utilized in wearable displays.
Existing fiber-based wearable displays’ OLEDs show much lower performance compared to those fabricated on planar substrates. This low performance caused a limitation for applying it to actual wearable displays.
In order to solve this problem, the team designed a structure of OLEDs compatible to fiber and used a dip-coating method in a three-dimensional structure of fibers. Through this method, the team successfully developed efficient OLEDs that are designed to last a lifetime and are still equivalent to those on planar substrates.
The team identified that solution process planar OLEDs can be applied to fibers without any reduction in performance through the technology. This fiber OLEDs exhibited luminance and current efficiency values of over 10,000 cd/m^2(candela/square meter) and 11 cd/A (candela/ampere).
The team also verified that the fiber OLEDs withstood tensile strains of up to 4.3% while retaining more than 90% of their current efficiency. In addition, they could be woven into textiles and knitted clothes without causing any problems.
Moreover, the technology allows for fabricating OLEDs on fibers with diameters ranging from 300㎛ down to 90㎛, thinner than a human hair, which attests to the scalability of the proposed fabrication scheme.
Noting that every process is carried out at a low temperature (~105℃), fibers vulnerable to high temperatures can also employ this fabrication scheme.
Professor Choi said, “Existing fiber-based wearable displays had limitations for applicability due to their low performance. However, this technology can fabricate OLEDs with high performance on fibers. This simple, low-cost process opens a way to commercialize fiber-based wearable displays.”
This research led by a PhD candidate Seonil Kwon was published online in the international journal for nanoscience, Nano Letters, on December 6.
(Fiber-based OLEDs woven into knitted clothes)
This work was funded by the Engineering Research Center of Excellence Program (Grant No. NRF-2017R1A5A1014708) and Nano-Material Technology Development Program (Grant No. NRF-2016M3A7B4910635) by the National Research Foundation of Korea, the Ministry of Science and ICT of Korea.
2018.01.09 View 13415 -
Controlling Superconductivity Using Spin Currents
(Professor Jhinhwan Lee and Dr. Seokhwan Choi)
A KAIST research team led by Professor Jhinhwan Lee of the Department of Physics has discovered a method to flip between superconducting and non-superconducting states within an iron-based superconductor using a type of electron microscopy. The team applied spin-polarized and non-polarized currents to locally change the magnetic order in the sample.
The team identified a basic physical principle required to develop transistors that control superconductivity and to implement novel magnetic memory at the atomic level. This study is the first report of a direct real-space observation of this type of control. In addition, this is the first direct atomic-scale demonstration of the correlation between magnetism and superconductivity.
The team controlled and observed the magnetic and electronic properties with a spin-polarized scanning tunneling microscope (SPSTM), a device that passes an atomically-sharp metal tip over the surface of a sample. The team introduced new ways to perform SPSTM using an antiferromagnetic chromium tip. An antiferromagnet is a material in which the magnetic fields of its atoms are ordered in an alternating up-down pattern such that it has a minimal stray magnetic field that can inadvertently kill the local superconductivity of the sample when used as an SPSTM tip.
To study the connection between the C4 magnetic order and the suppression of superconductivity, the team performed high-resolution SPSTM scans of the C4 state with chromium tips and compared them with simulations. The results led them to suggest that the low-energy spin fluctuations in the C4 state cannot mediate pairing between electrons in the typical FeAs band structure. This is critical because this paring of electrons, defying their natural urge to repel each other, leads to superconductivity.
Professor Lee said, “Our findings may be extended to future studies where magnetism and superconductivity are manipulated using spin-polarized and unpolarized currents, leading to novel antiferromagnetic memory devices and transistors controlling superconductivity.”
This study was published in Physical Review Letters (PRL) on November 27 as the Editor’s Suggestion. It was also featured in Viewpoint in Physics, in which the top 3% of PRL papers are presented with a commentary. It was also featured on Phys.org, which is a science news website led by the US national research institutes. Furthermore, the equipment designed and manufactured by Professor Lee’s team and used for the research was selected for the cover of Review of Scientific Instruments (RSI) in the October 2017 issue.
Professor Lee said, “When designing the experiment, we attempted to implement some decisive features. For instance, we included a spin control function using an antiferromagnetic probe, wide range variable temperature functions that were thought to be impossible in high-magnetic field structures, and multiple sample storage functions at low temperatures for systematic spin control experiments, rather than using simpler scanning probe microscopes with well-known principles or commercial microscopes. As a result, we were able to conduct systematic experiments on controlling magnetism and superconductivity, which competing groups would take years to replicate.”
He continued, “There were some minor difficulties in the basic science research environment such as the lack of a shared helium liquefier on campus and insufficient university-scale appreciation for large scale physics that inevitably takes time. We will do our best to lead the advancement of cutting-edge science through research projects expanding on this achievement in physical knowledge to practical devices and various technological innovations in measurements.” This research was funded by National Research Foundation of Korea.
Figure 1. Research concept illustration
The spin-polarized chromium (Cr) tip being scanned over the pristine superconducting area of the C2 magnetic order, represented in the background with electron pairs shown as coupled red spheres. The spin current through the tip induces the C4 magnetic order (yellow and blue plaquettes) with suppressed superconductivity in the sample because its spin fluctuations cannot mediate electron pairing, represented as decoupled red spheres in the plaquette area.
2018.01.05 View 5547 -
Ultra-Low Power Flexible Memory Using 2D Materials
(Professor Choi and Ph.D. candidate Jang)
KAIST research team led by Professor Sung-Yool Choi at School of Electrical Engineering and Professor Sung Gap Im at the Department of Chemical and Biomolecular Engineering developed high-density, ultra-low power, non-volatile, flexible memory technology using 2D materials. The team used ultrathin molybdenum disulfide (MoS2) with atomic-scale thickness as the channel material and high-performance polymeric insulator film as the tunneling dielectric material. This research was published on the cover of Advanced Functional Materials on November 17. KAIST graduate Myung Hun Woo, a researcher at Samsung Electronics and Ph.D. candidate Byung Chul Jang are first authors.
The surge of new technologies such as Internet of Things (IoT), Artificial Intelligence (AI), and cloud server led to the paradigm shift from processor-centric computing to memory-centric computing in the industry, as well as the increase in demand of wearable devices. This led to an increased need for high-density, ultra-low power, non-volatile flexible memory. In particular, ultrathin MoS2 as semiconductor material has been recently regarded as post-silicon material. This is due to its ultrathin thickness of atomic-scale which suppresses short channel effect observed in conventional silicon material, leading to advantages in high- density and low-power consumption. Further, this thickness allows the material to be flexible, and thus the material is applicable to wearable devices.
However, due to the dangling-bond free surface of MoS2 semiconductor material, it is difficult to deposit the thin insulator film to be uniform and stable over a large area via the conventional atomic layer deposition process. Further, the currently used solution process makes it difficult to deposit uniformly low dielectric constant (k) polymeric insulator film with sub-10 nm thickness on a large area, thus indicating that the memory device utilizing the conventional solution-processed polymer insulator film cannot be operated at low-operating voltage and is not compatible with photolithography.
The research team tried to overcome the hurdles and develop high-density, ultra-low power, non-volatile flexible memory by employing a low-temperature, solvent-free, and all-dry vapor phase technique named initiated chemical vapor deposition (iCVD) process. Using iCVD process, tunneling polymeric insulator film with 10 nm thickness was deposited uniformly on MoS2 semiconductor material without being restricted by the dangling bond-free surface of MoS2. The team observed that the newly developed MoS2-based non-volatile memory can be operated at low-voltage (around 10V), in contrast to the conventional MoS2-based non-volatile memory that requires over 20V.
Professor Choi said, “As the basis for the Fourth Industrial revolution technologies including AI and IoT, semiconductor device technology needs to have characteristics of low-power and flexibility, in clear contrast to conventional memory devices.” He continued, “This new technology is significant in developing source technology in terms of materials, processes, and devices to contribute to achieve these characteristics.”
This research was supported by the Global Frontier Center for Advanced Soft Electronics and the Creative Materials Discovery Program by funded the National Research Foundation of Korea of Ministry of Science and ICT.
( Figure 1. Cover of Advanced Functional Materials)
(Figure 2. Concept map for the developed non-volatile memory material and high-resolution transmission electron microscopy image for material cross-section )
2018.01.02 View 7988 -
Non-Adiabatic Reaction Mechanism Identified at Conical Intersection
(Professor Kim(center) and Ph.D. candidates Kyung Chul Woo (left) and Kang Do Hyung)
Research team led by Professor Sang Kyu Kim at KAIST Department of Chemistry observed two distinct reaction pathways that occur at conical intersection where two different adiabatic potential energy surfaces cross at the same nuclear configuration.
Professor Kim previously identified the existence and molecular structure of conical intersection in 2010. In this following study, the team accurately measured reaction rates of two totally different reaction pathways activated only at conical intersection where the seminal Born-Oppenheimer approximation breaks down.
This study led by Kyung Chul Woo (1st author) and Do Hyung Kang, both Ph.D. candidates at KAIST, was published in Journal of the American Chemical Society in November 7th, 2017.
Chemical reaction induced by light occurs in excited electronic states where the reaction outcome is often destined by coupling among different electronic states mediated by nuclear motions during chemical reaction. Such a coupling is most critical and important at the conical intersection as nonadiabtic surface-hopping is most probable at situation where the Born-Oppenheimer approximation fails.
Professor Kim used spectroscopic methods in 2010 to experimentally observe conical intersection of polyatomic molecule. And yet, it was not possible to disentangle complex dynamic processes with frequency-domain study only.
The research team used pico-second time-resolution kinetic energy resolved mass spectrometry to identify two possible distinct reaction pathways in both energy and time domains.,.
The research team demonstrated that the reactive flux prepared at the conical intersection is bifurcated into adiabatic or non-adiabatic reaction pathways. These two pathways are quite distinct in terms of reaction rates, energy releases, and product branching ratios.
This is the first study to capture the moment of bifurcation dynamics at the conical intersection for complex polyatomic molecular system. The study could contribute to conceptual improvement in understanding complicated nonadiabatic dynamics in general.
Professor Kim said, “Basic science research is essential in understanding and wisely using the nature. New technological advances cannot be made without the advancement in basic science.” He continued, “I hope this study could lead to growth in many young academic talents in basic sciences.”
(Figure 1. Reaction graph starting from reaction intersection that divides into adiabatic reaction pathway (red) and non-adiabatic pathway (blue))
2017.12.19 View 5678 -
Technology to Find Optimum Drug Target for Cancer Developed
(Professor Kwang-Hyun Cho (right) and lead author Dr. Minsoo Choi)
A KAIST research team led by Professor Kwang-Hyun Cho of the Department of Bio and Brain Engineering developed technology to find the optimum drug target according to the type of cancer cell. The team used systems biology to analyze molecular network dynamics that reflect genetic mutations in cancer cells and to predict drug response. The technology could contribute greatly to future anti-cancer drug development.
There are many types of genetic variations found in cancer cells, including gene mutations and copy number variations. These variations differ in cancer cells even within the same type of cancer, and thus the drug response varies cell by cell. Cancer researchers worked towards identifying frequently occurring genetic variations in cancer patients and, in particular, the mutations that can be used as an index for specific drugs. Previous studies focused on identifying a single genetic mutation or creating an analysis of the structural characteristics of a gene network. However, this approach was limited in its inability to explain the biological properties of cancer which are induced by various gene and protein interactions in cancer cells, which result in differences in drug response.
Gene mutations in cancer cells not only affect the function of the affected gene, but also other genes that interact with the mutated gene and proteins. As a consequence, one mutation could lead to changes in the dynamical properties of the molecular network. Therefore, the responses to anti-cancer drugs by cancer cells differ. The current treatment approach that ignores molecular network dynamics and targets a few cancer-related genes is only effective on a fraction of patients, while many other patients exhibit resistance to the drug.
Professor Cho’s team integrated a large-scale computer simulation using super-computing and cellular experiments to analyze changes in molecular network dynamics in cancer cells.
This led to development of technology to find the optimum drug target according to the type of cancer cells by predicting drug response. This technology was applied to the molecular network of known tumor suppressor p53. The team used large-scale cancer cell genomic data available from The Cancer Cell Line Encyclopedia (CCLE) to construct different molecular networks specific to the characteristics of genetic variations.
Perturbation analysis on drug response in each molecular network was used to quantify changes in cancer cells from drug response and similar networks were clustered. Then, computer simulations were used to analyze the synergetic effects in terms of efficacy and combination to predict the level of drug response. Based on the simulation results from various cancer cell lines including lung, breast, bone, skin, kidney, and ovary cancers were used in drug response experiments for compare analysis.
This technique can be applied in any molecular network to identify the optimum drug target for personalized medicine.
The research team suggests that the technology can analyze varying drug response due to the heterogeneity of cancer cells by considering the overall modulatory interactions rather than focusing only on a specific gene or protein. Further, the technology aids the prediction of causes of drug resistance and thus the identification of the optimum drug target to inhibit the resistance. This could be core source technology that can be used in drug repositioning, a process of applying existing drugs to new disease targets.
Professor Cho said, “Genetic variations in cancer cells are the cause of diverse drug response, but a complete analysis had not yet been made.” He continued, “Systems biology allowed the simulation of drug responses by cancer cell molecular networks to identify fundamental principles of drug response and optimum drug targets using a new conceptual approach.”
This research was published in Nature Communications on December 5 and was funded by Ministry of Science and ICT and National Research Foundation of Korea.
(Figure 1. Drug response prediction for each cancer cell type from computer simulation and cellular experiment verification for comparison)
(Figure 2. Drug response prediction based on cancer cell molecular network dynamics and clustering of cancer cells by their molecular networks)
(Figure 3. Identification of drug target for each cancer cell type by cellular molecular network analysis and establishment for personalized medicine strategy for each cancer patient)
2017.12.15 View 6413 -
New Quantum Mechanical States Observed
(Professor Han (far right) and his research team)
A KAIST research team observed a new quantum mechanical magnetic state ‘Jeff = 3/2.’ This first observation of ‘Jeff=3/2’ could be the foundation for future research on superconductivity and quantum magnetism.
In quantum mechanics, total angular momentum is defined as the sum of spin and orbital angular momenta and is denoted with the ‘J.’ The newly identified magnetic moment can be described as a kind of angular momentum that occurs when specific conditions are met and has been denoted ‘Jeff’ with the meaning ‘effective angular momentum’ in the field. Jeff=3/2 has been a topic of discussion but was yet to be observed.
The research was co-led by Professor Myung Joon Han of the Department of Physics at Chung-Ang University in Korea, RIKEN in Japan, and the Argonne National Laboratory in the US. This research was published in Nature Communications on October 14, 2017.
In academia, spin-orbital coupling was known to lead to a unique quantum state and has been an active area of recent research. In contrast to magnetic moment by electron spin and orbital, the effective magnetic moment Jeff, formed from the coupling of the two, shows a unique ground state and interaction patterns, which could lead to new phenomena and properties.
Most studies in the last decade focused on ‘Jeff=1/2’, but there has not been any observation of ‘Jeff=3/2’, which led to slow progress. In 2014, the research team led by Prof. Han theoretically predicted the possibility of the ‘Jeff=3/2’ state in a certain type of materials based on molecular orbital, instead of atomic orbital. In the current study, the team applied the Selection Rule of quantum mechanics for the ‘Jeff=3/2’ state, which differs to the general spin moment, in order to experimentally detect this moment.
When electrons near the atomic nucleus are excited by X-rays, the excited electrons can be absorbed or re-emitted through interactions with other electrons. Here, the Selection Rule is applied to electrons. According to quantum mechanics, this rule is very unique in the ‘Jeff=3/2’ state and ‘Jeff=3/2’ is predicted to be distinguishable from general spin states. The prediction that was made using this idea was verified through the experiment using electrons extracted from tantalum at two different energy levels. In this material, the unique quantum mechanical interference by the ‘Jeff=3/2’ moment can be taken as direct evidence for its existence.
The new quantum state is very unique from any of the previously known magnetic states and this study could be the starting point for future research on the ‘Jeff=3/2’ moment. Further, this finding could contribute to future research on various properties of the magnetic states and its interactions.
(Figure 1: Crystal structure, MO levels, and RIXS process in GaTa4Se8.)
(Figure 2: Cluster model calculations of the L3 and L2 RIXS spectra)
2017.12.14 View 5372 -
A New Spin Current Generating Material Developed
(Professor Park(left) and Ph.D. candidate Kim)
Magnetic random-access memory (MRAM) is a non-volatile device made of thin magnetic film that can maintain information without an external power supply, in contrast to conventional silicon-based semiconductor memory. It also has the potential for high-density integration and high-speed operation.
The operation of MRAM involves the control of the magnetization direction by exerting spin current-induced torque on a magnetic material. Spin current is generated using electricity in conventional MRAM, but this study developed materials technology that generates spin current using heat.
A KAIST research team led by Professor Byong-Guk Park of the Department of Materials Science and Engineering developed a material that generates spin current from heat, which can be utilized for a new operation principle for MRAM.
There have been theoretical reports on the spin Nernst effect, the phenomenon of the thermal generation of spin current, but is yet to have been experimentally proven due to technological limitations. However, the research team introduced a spin Nernst magnetoresistance measurement method using tungsten (W) and platinum (Pt) with high spin orbit coupling which allows for the experimental identification of the spin Nernst effect. They also demonstrated that the efficiency of spin current generation from heat is similar to that of spin current generated from electricity.
Professor Park said, “This research has great significance in experimentally proving spin current generation from heat, a new physical phenomenon. We aim to develop the technology as a new operational method for MRAM through further research. This can lower power consumption, and is expected to contribute to the advancement of electronics requiring low power requirement such as wearable, mobile, and IOT devices”.
This research was conducted as a joint research project with Professor Kyung-Jin Lee at Korea University and Professor Jong-Ryul Jeong at Chungnam National University. It was published in Nature Communications online on November 9 titled “Observation of transverse spin Nernst magnetoresistance induced by thermal spin current in ferromagnet/non-magnet bilayers.” Ph.D. candidate Dong-Jun Kim at KAIST is the first author. This research was funded by the Ministry of Science and ICT.
(Schematic diagram of spin Nernst magnetoresistance)
(Research result of new spin current generating materials)
2017.12.08 View 7236 -
Expanding Gas Storage Capacity of Nanoporous Materials
A KAIST research team led by Professor Jihan Kim of the Department of Chemical and Biomolecular Engineering has successfully proposed a rational defect engineering methodology that can greatly enhance the gas storage capacity of nanoporous materials. The team conducted a high-throughput computational screening of a large experimental metal-organic framework database to identify 13 candidate materials that could experience significant methane uptake enhancement with only a small proportion of linker vacancy defects.
This research was published online on November 16 in Nature Communications, with M.S. candidate Sanggyu Chong from KAIST as the first author and post-doctorate researcher Günther Thiele from the Department of Chemistry at UC Berkeley as a contributing author.
Metal-organic frameworks, hereinafter MOF, are crystalline nanoporous materials that are comprised of metal clusters and organic linkers continuously bound together by coordination bonds. Due to their ultrahigh surface areas and pore volumes, they have been widely studied for various energy and environment applications.
Similar to other crystalline materials, MOFs are never perfectly crystalline and are likely to contain several different types of defects within their crystalline structures. Among these defects, linker vacancy defects, or the random absence of linker vacancies in their designated bonding positions, are known to be controllable by practicing careful control over the synthesis conditions.
The research team combined the concepts of rational defect engineering over the linker vacancy defects and the potential presence of inaccessible pores within MOFs to propose a methodology where controlled the introduction of linker vacancy defects could lead to a dramatic enhancement in gas adsorption and storage capacities.
The study utilized a Graphic Processing Unit (GPU) code developed by Professor Kim in a high-throughput computational screening of 12,000 experimentally synthesized MOFs to identify the structures with significant amounts of pores that were inaccessible for methane. In determining the presence of inaccessible pores, a flood-fill algorithm was performed over the energy-low regions of the structure, which is the same algorithm used for filling an area with color in Microsoft Paint.
For the MOFs with significant amounts of inaccessible pores, as determined from the screening, the research team emulated linker vacancy defects in their crystalline structures so that the previously inaccessible pores would be newly merged into the main adsorption channel with the introduction of defects for additional surface area and pore volume available for adsorption. The research team successfully identified 13 structures that would experience up to a 55.56% increase in their methane uptake with less than 8.33% of the linker vacancy defects.
The research team believes that this rational defect engineering scheme can be further utilized for many other applications in areas such as selective adsorption of an adsorbate from a gas mixture and the semi-permanent capture of gas molecules.
This research was conducted with the support of the Mid-career Research Program of the National Research Foundation of Korea.
Figure1. A diagram for flood fill algorithm and example of identification of inaccessible regions within the MOFs, using the flood fill algorithm
Figure2. Methane energy contours before and after detect introduction
2017.12.04 View 7138 -
Technology Detecting RNase Activity
(Ph.D. candidate Chang Yeol Lee)
A KAIST research team of Professor Hyun Gyu Park at Department of Chemical and Biomolecular Engineering developed a new technology to detect the activity of RNase H, a RNA degrading enzyme. The team used highly efficient signal amplification reaction termed catalytic hairpin assembly (CHA) to effectively analyze the RNase H activity. Considering that RNase H is required in the proliferation of retroviruses such as HIV, this research finding could contribute to AIDS treatments in the future, researchers say.
This study led by Ph.D. candidates Chang Yeol Lee and Hyowon Jang was chosen as the cover for Nanoscale (Issue 42, 2017) published in 14 November.
The existing techniques to detect RNase H require expensive fluorophore and quencher, and involve complex implementation. Further, there is no way to amplify the signal, leading to low detection efficiency overall. The team utilized CHA technology to overcome these limitations. CHA amplifies detection signal to allow more sensitive RNase H activity assay.
The team designed the reaction system so that the product of CHA reaction has G-quadruplex structures, which is suitable to generate fluorescence. By using fluorescent molecules that bind to G-quadruplexes to generate strong fluorescence, the team could develop high performance RNase H detection method that overcomes the limitations of existing techniques. Further, this technology could screen inhibitors of RNase H activity.
The team expects that the research finding could contribute to AIDS treatment. AIDS is disease caused by HIV, a retrovirus that utilizes reverse transcription, during which RNA is converted to DNA. RNase H is essential for reverse transcription in HIV, and thus inhibition of RNase H could in turn inhibit transcription of HIV DNA.
Professor Park said, “This technology is applicable to detect various enzyme activities, as well as RNase H activity.” He continued, “I hope this technology could be widely used in research on enzyme related diseases.”
This study was funded by Global Frontier project and Mid-career Researcher Support project of the Ministry of Science and ICT.
2017.11.28 View 6194 -
New Photocatalyst Converts Carbon Dioxide to 99% Pure Fuel
(Professor Song, Ph.D. candidates Kim, and Lim (from left))
A KAIST research team led by Professor Hyunjoon Song of the Department of Chemistry developed a metal oxide nanocatalyst that converts carbon dioxide to 99% pure methane. This technology directly uses sunlight to convert carbon dioxide into methane, which is more efficient in terms of energy storage capacity, compared to the conventional way of storing the electricity produced by solar cells in batteries. The research team used cheap catalytic materials to significantly enhance the reaction efficiency and selectivity of the chemical energy storage method.
This research was conducted as a joint research project with Professor Ki Min Nam at Mokpo National University with co-first authors Dr. Kyung-Lyul Bae and Ph.D. candidates Jinmo Kim and Chan Kyu Lim. The study was published in Nature Communications on November 7.
Although there is growing interest in sunlight as an energy resource, its usage has been limited to daytime and the power output varies with the weather. If sunlight could be directly converted to chemical energy, such as fuel, the limitations of energy storage and its usage could be overcome. In particular, the usage of sunlight to convert carbon dioxide, a main cause of the greenhouse effect in our atmosphere, is of great interest since both energy and environmental issues can be addressed. However, the stability of carbon dioxide made it difficult to convert it to other molecules. Thus, there was a need for a catalyst with enhanced efficiency and selectivity.
Professor Song’s team synthesized zinc oxide nanoparticles, often used in sun cream. The nanoparticles were then bound to copper oxide as single particles, forming a colloidal form of zinc oxide-copper oxide nanoparticles. Zinc oxides produce high energy electrons using light, and this energy is used to convert carbon dioxide into methane. Further, zinc oxide can also produce electrons with light and transfer the electrons to copper oxide. Similar to the principles of photosynthesis in leaves, the electron transfer reaction could be maintained for a long time. As a consequence, although the reaction was conducted in aqueous solution, methane of 99% purity could be obtained from carbon dioxide.
Conventional heterogeneous photocatalysts were in solid powder form with irregular structures and were not dispersed in water. Professor Song’s team used a nanochemical synthesis method to control the structure of the catalyst particles to be regular and maintained over a large surface area. This led to increasing carbon dioxide conversion activity by hundreds of fold in solution compared to existing catalysts.
Professor Song said, “A long time will be needed for the commercialization of the direct conversion reaction of carbon dioxide using sunlight. However, the precise control of catalyst structures at nanoscale would enhance the efficiency of photocatalyst reactions.” He continued, “Applying this method to various phtocatalysts will maximize the catalysts performance.”
(Figure 1. Scheme for carbon dioxide conversion reaction using nano photocatalyst in aqueous solution)
(Figure 2. Structure, photocatalytic CO2 conversion, and stability of ZnO-Cu2O nanocatalyst )
2017.11.13 View 7861 -
Mutant Gene Network in Colon Cancer Identified
The principles of the gene network for colon tumorigenesis have been identified by a KAIST research team. The principles will be used to find the molecular target for effective anti-cancer drugs in the future. Further, this research gained attention for using a systems biology approach, which is an integrated research area of IT and BT.
The KAIST research team led by Professor Kwang-Hyun Cho for the Department of Bio and Brain Engineering succeeded in the identification. Conducted by Dr. Dongkwan Shin and student researchers Jonghoon Lee and Jeong-Ryeol Gong, the research was published in Nature Communications online on November 2.
Human cancer is caused by genetic mutations. The frequency of the mutations differs by the type of cancer; for example, only around 10 mutations are found in leukemia and childhood cancer, but an average of 50 mutations are found in adult solid cancers and even hundreds of mutations are found in cancers due to external factors, such as with lung cancer.
Cancer researchers around the world are working to identify frequently found genetic mutations in patients, and in turn identify important cancer-inducing genes (called ‘driver genes’) to develop targets for anti-cancer drugs. However, gene mutations not only affect their own functions but also affect other genes through interactions. Therefore, there are limitations in current treatments targeting a few cancer-inducing genes without further knowledge on gene networks, hence current drugs are only effective in a few patients and often induce drug resistance.
Professor Cho’s team used large-scale genomic data from cancer patients to construct a mathematical model on the cooperative effects of multiple genetic mutations found in gene interaction networks. The basis of the model construction was The Cancer Genome Atlas (TCGA) presented at the International Cancer Genome Consortium. The team successfully quantified the effects of mutations in gene networks to group colon cancer patients by clinical characteristics.
Further, the critical transition phenomenon that occurs in tumorigenesis was identified using large-scale computer simulation analysis, which was the first hidden gene network principle to be identified. Critical transition is the phenomenon in which the state of matter is suddenly changed through phase transition. It was not possible to identify the presence of transition phenomenon in the past, as it was difficult to track the sequence of gene mutations during tumorigenesis.
The research team used a systems biology-based research method to find that colon cancer tumorigenesis shows a critical transition phenomenon if the known driver gene mutations follow sequentially. Using the developed mathematical model, it can be possible to develop a new anti-cancer targeting drug that most effectively inhibits the effects of many gene mutations found in cancer patients. In particular, not only driver genes, but also other passenger genes affected by the gene mutations, could be evaluated to find the most effective drug targets.
Professor Cho said, “Little was known about the contribution of many gene mutations during tumorigenesis.” He continued, “In this research, a systems biology approach identified the principle of gene networks for the first time to suggest the possibility of anti-cancer drug target identification from a new perspective.”
This research was funded by the Ministry of Science and ICT and the National Research Foundation of Korea.
Figure1. Formation of giant clusters via mutation propagation
Figure2. Critical transition phenomenon by cooperative effect of mutations in tumorigenesis
2017.11.10 View 7329