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Mystery Solved with Math: Cytoplasmic Traffic Jam Disrupts Sleep-Wake Cycles
KAIST mathematicians and their collaborators at Florida State University have identified the principle of how aging and diseases like dementia and obesity cause sleep disorders. A combination of mathematical modelling and experiments demonstrated that the cytoplasmic congestion caused by aging, dementia, and/or obesity disrupts the circadian rhythms in the human body and leads to irregular sleep-wake cycles. This finding suggests new treatment strategies for addressing unstable sleep-wake cycles. Human bodies adjust sleep schedules in accordance with the ‘circadian rhythms’, which are regulated by our time keeping system, the ‘circadian clock’. This clock tells our body when to rest by generating the 24-hour rhythms of a protein called PERIOD (PER) (See Figure 1). The amount of the PER protein increases for half of the day and then decreases for the remaining half. The principle is that the PER protein accumulating in the cytoplasm for several hours enters the cell nucleus all at once, hindering the transcription of PER genes and thereby reducing the amount of PER. However, it has remained a mystery how thousands of PER molecules can simultaneously enter into the nucleus in a complex cell environment where a variety of materials co-exist and can interfere with the motion of PER. This would be like finding a way for thousands of employees from all over New York City to enter an office building at the same time every day. A group of researchers led by Professor Jae Kyoung Kim from the KAIST Department of Mathematical Sciences solved the mystery by developing a spatiotemporal and probabilistic model that describes the motion of PER molecules in a cell environment. This study was conducted in collaboration with Professor Choogon Lee’s group from Florida State University, where the experiments were carried out, and the results were published in the Proceedings of the National Academy of Sciences (PNAS) last month. The joint research team’s spatial stochastic model (See Figure 2) described the motion of PER molecules in cells and demonstrated that the PER molecule should be sufficiently condensed around the cell nucleus to be phosphorylated simultaneously and enter the nucleus together (See Figure 3 Left). Thanks to this phosphorylation synchronization switch, thousands of PER molecules can enter the nucleus at the same time every day and maintain stable circadian rhythms. However, when aging and/or diseases including dementia and obesity cause the cytoplasm to become congested with increased cytoplasmic obstacles such as protein aggregates and fat vacuoles, it hinders the timely condensation of PER molecules around the cell nucleus (See Figure 3 Right). As a result, the phosphorylation synchronization switch does not work and PER proteins enter into the nucleus at irregular times, making the circadian rhythms and sleep-wake cycles unstable, the study revealed. Professor Kim said, “As a mathematician, I am excited to help enable the advancement of new treatment strategies that can improve the lives of so many patients who suffer from irregular sleep-wake cycles. Taking these findings as an opportunity, I hope to see more active interchanges of ideas and collaboration between mathematical and biological sciences.” This work was supported by the National Institutes of Health and the National Science Foundation in the US, and the International Human Frontiers Science Program Organization and the National Research Foundation of Korea. Publication: Beesley, S. and Kim, D. W, et al. (2020) Wake-sleep cycles are severely disrupted by diseases affecting cytoplasmic homeostasis. Proceedings of the National Academy of Sciences (PNAS), Vol. 117, No. 45, 28402-28411. Available online at https://doi.org/10.1073/pnas.2003524117 Profile: Jae Kyoung Kim, Ph.D. Associate Professor email@example.com http://mathsci.kaist.ac.kr/~jaekkim @umichkim on Twitter Department of Mathematical Sciences Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea Profile: Choogon Lee, Ph.D. Associate Professor firstname.lastname@example.org https://med.fsu.edu/biosci/lee-lab Department of Biomedical Sciences Florida State University Florida, USA (END)
Drawing the Line to Answer Art’s Big Questions
- KAIST scientists show how statistical physics can reveal art trends across time and culture. - Algorithms have shown that the compositional structure of Western landscape paintings changed “suspiciously” smoothly between 1500 and 2000 AD, potentially indicating a selection bias by art curators or in art historical literature, physicists from the Korea Advanced Institute of Science and Technology (KAIST) and colleagues report in the Proceedings of the National Academy of Sciences (PNAS). KAIST statistical physicist Hawoong Jeong worked with statisticians, digital analysts and art historians in Korea, Estonia and the US to clarify whether computer algorithms could help resolve long-standing questions about design principles used in landscape paintings, such as the placement of the horizon and other primary features. “A foundational question among art historians is whether artwork contains organizing principles that transcend culture and time and, if yes, how these principles evolved over time,” explains Jeong. “We developed an information-theoretic approach that can capture compositional proportion in landscape paintings and found that the preferred compositional proportion systematically evolved over time.” Digital versions of almost 15,000 canonical landscape paintings from the Western renaissance in the 1500s to the more recent contemporary art period were run through a computer algorithm. The algorithm progressively divides artwork into horizontal and vertical lines depending on the amount of information in each subsequent partition. It allows scientists to evaluate how artists and various art styles compose landscape artwork, in terms of placement of a piece’s most important components, in addition to how high or low the landscape’s horizon is placed. The scientists started by analysing the first two partitioning lines identified by the algorithm in the paintings and found they could be categorized into four groups: an initial horizontal line followed by a second horizontal line (H-H); an initial horizontal line followed by a second vertical line (H-V); a vertical followed by horizontal line (V-H); or a vertical followed by a vertical line (V-V) (see image 1 and 2). They then looked at the categorizations over time. They found that before the mid-nineteenth century, H-V was the dominant composition type, followed by H-H, V-H, and V-V. The mid-nineteenth century then brought change, with the H-V composition style decreasing in popularity with a rise in the H-H composition style. The other two styles remained relatively stable. The scientists also looked at how the horizon line, which separates sky from land, changed over time. In the 16th century, the dominant horizon line of the painting was above the middle of the canvas, but it gradually descended to the lower middle of the canvas by the 17th century, where it remained until the mid-nineteenth century. After that, the horizon line began gradually rising again. Interestingly, the algorithm showed that these findings were similar across cultures and artistic periods, even through periods dominated by a diversity in art styles. This similarity may well be a function, then, of a bias in the dataset. “In recent decades, art historians have prioritized the argument that there is great diversity in the evolution of artistic expression rather than offering a relatively smoother consensus story in Western art,” Jeong says. “This study serves as a reminder that the available large-scale datasets might be perpetuating severe biases.” The scientists next aim to broaden their analyses to include more diverse artwork, as this particular dataset was ultimately Western and male biased. Future analyses should also consider diagonal compositions in paintings, they say. This work was supported by the National Research Foundation (NRF) of Korea. Publication: Lee, B, et al. (2020) Dissecting landscape art history with information theory. Proceedings of the National Academy of Sciences (PNAS), Vol. 117, No. 43, 26580-26590. Available online at https://doi.org/10.1073/pnas.2011927117 Profile: Hawoong Jeong, Ph.D. Professor email@example.com https://www.kaist.ac.kr Department of Physics Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea (END)
To Talk or Not to Talk: Smart Speaker Determines Optimal Timing to Talk
A KAIST research team has developed a new context-awareness technology that enables AI assistants to determine when to talk to their users based on user circumstances. This technology can contribute to developing advanced AI assistants that can offer pre-emptive services such as reminding users to take medication on time or modifying schedules based on the actual progress of planned tasks. Unlike conventional AI assistants that used to act passively upon users’ commands, today’s AI assistants are evolving to provide more proactive services through self-reasoning of user circumstances. This opens up new opportunities for AI assistants to better support users in their daily lives. However, if AI assistants do not talk at the right time, they could rather interrupt their users instead of helping them. The right time for talking is more difficult for AI assistants to determine than it appears. This is because the context can differ depending on the state of the user or the surrounding environment. A group of researchers led by Professor Uichin Lee from the KAIST School of Computing identified key contextual factors in user circumstances that determine when the AI assistant should start, stop, or resume engaging in voice services in smart home environments. Their findings were published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) in September. The group conducted this study in collaboration with Professor Jae-Gil Lee’s group in the KAIST School of Computing, Professor Sangsu Lee’s group in the KAIST Department of Industrial Design, and Professor Auk Kim’s group at Kangwon National University. After developing smart speakers equipped with AI assistant function for experimental use, the researchers installed them in the rooms of 40 students who live in double-occupancy campus dormitories and collected a total of 3,500 in-situ user response data records over a period of a week. The smart speakers repeatedly asked the students a question, “Is now a good time to talk?” at random intervals or whenever a student’s movement was detected. Students answered with either “yes” or “no” and then explained why, describing what they had been doing before being questioned by the smart speakers. Data analysis revealed that 47% of user responses were “no” indicating they did not want to be interrupted. The research team then created 19 home activity categories to cross-analyze the key contextual factors that determine opportune moments for AI assistants to talk, and classified these factors into ‘personal,’ ‘movement,’ and ‘social’ factors respectively. Personal factors, for instance, include: 1. the degree of concentration on or engagement in activities, 2. the degree urgency and busyness, 3. the state of user’s mental or physical condition, and 4. the state of being able to talk or listen while multitasking. While users were busy concentrating on studying, tired, or drying hair, they found it difficult to engage in conversational interactions with the smart speakers. Some representative movement factors include departure, entrance, and physical activity transitions. Interestingly, in movement scenarios, the team found that the communication range was an important factor. Departure is an outbound movement from the smart speaker, and entrance is an inbound movement. Users were much more available during inbound movement scenarios as opposed to outbound movement scenarios. In general, smart speakers are located in a shared place at home, such as a living room, where multiple family members gather at the same time. In Professor Lee’s group’s experiment, almost half of the in-situ user responses were collected when both roommates were present. The group found social presence also influenced interruptibility. Roommates often wanted to minimize possible interpersonal conflicts, such as disturbing their roommates' sleep or work. Narae Cha, the lead author of this study, explained, “By considering personal, movement, and social factors, we can envision a smart speaker that can intelligently manage the timing of conversations with users.” She believes that this work lays the foundation for the future of AI assistants, adding, “Multi-modal sensory data can be used for context sensing, and this context information will help smart speakers proactively determine when it is a good time to start, stop, or resume conversations with their users.” This work was supported by the National Research Foundation (NRF) of Korea. Publication: Cha, N, et al. (2020) “Hello There! Is Now a Good Time to Talk?”: Opportune Moments for Proactive Interactions with Smart Speakers. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Vol. 4, No. 3, Article No. 74, pp. 1-28. Available online at https://doi.org/10.1145/3411810 Link to Introductory Video: https://youtu.be/AA8CTi2hEf0 Profile: Uichin Lee Associate Professor firstname.lastname@example.org http://ic.kaist.ac.kr Interactive Computing Lab. School of Computing https://www.kaist.ac.kr Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea (END)
X-ray Scattering Shines Light on Protein Folding
- Multiple forms of a non-functional, unfolded protein follow different pathways and timelines to reach its folded, functional state, a study reveals. - KAIST researchers have used an X-ray method to track how proteins fold, which could improve computer simulations of this process, with implications for understanding diseases and improving drug discovery. Their findings were reported in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on June 30. When proteins are translated from their DNA codes, they quickly transform from a non-functional, unfolded state into their folded, functional state. Problems in folding can lead to diseases like Alzheimer’s and Parkinson’s. “Protein folding is one of the most important biological processes, as it forms the functioning 3D protein structure,” explained the physical chemist Hyotcherl Ihee of the Department of Chemistry at KAIST. Dr. Tae Wu Kim, the lead author of this research from Ihee’s group, added, “Understanding the mechanisms of protein folding is important, and could pave the way for disease study and drug development.” Ihee’s team developed an approach using an X-ray scattering technique to uncover how the protein cytochrome c folds from its initial unfolded state. This protein is composed of a chain of 104 amino acids with an iron-containing heme molecule. It is often used for protein folding studies. The researchers placed the protein in a solution and shined ultraviolet light on it. This process provides electrons to cytochrome c, reducing the iron within it from the ferric to the ferrous form, which initiates folding. As this was happening, the researchers beamed X-rays at very short intervals onto the sample. The X-rays scattered off all the atomic pairs in the sample and a detector continuously recorded the X-ray scattering patterns. The X-ray scattering patterns provided direct information regarding the 3D protein structure and the changes made in these patterns over time showed real-time motion of the protein during the folding process. The team found cytochrome c proteins initially exist in a wide variety of unfolded states. Once the folding process is triggered, they stop by a group of intermediates within 31.6 microseconds, and then those intermediates follow different pathways with different folding times to reach an energetically stable folded state. “We don’t know if this diversity in folding paths can be generalized to other proteins,” Ihee confessed. He continued, “However, we believe that our approach can be used to study other protein folding systems.” Ihee hopes this approach can improve the accuracy of models that simulate protein interactions by including information on their unstructured states. These simulations are important as they can help identify barriers to proper folding and predict a protein’s folded state given its amino acid sequence. Ultimately, the models could help clarify how some diseases develop and how drugs interact with various protein structures. Ihee’s group collaborated with Professor Young Min Rhee at the KAIST Department of Chemistry, and this work was supported by the National Research Foundation of Korea (NRF) and the Institute for Basic Science (IBS). Figure. The scientists found that non-functional unfolded forms of the protein cytochrome c follow different pathways and timelines to reach a stable functional folded state. Publications: Kim, T. W., et al. (2020) ‘Protein folding from heterogeneous unfolded state revealed by time-resolved X-ray solution scattering’. PNAS. Volume 117. Issue 26. Page 14996-15005. Available online at https://doi.org/10.1073/pnas.1913442117 Profile: Hyotcherl Ihee, Ph.D. Professor email@example.com http://time.kaist.ac.kr/ Ihee Laboratory Department of Chemistry KAIST https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Young Min Rhee, Ph.D. Professor firstname.lastname@example.org http://singlet.kaist.ac.kr Rhee Research Group Department of Chemistry KAIST https://www.kaist.ac.kr Daejeon 34141, Korea (END)
A Theoretical Boost to Nano-Scale Devices
- Researchers calculate the quasi-Fermi levels in molecular junctions applying an initio approach. - Semiconductor companies are struggling to develop devices that are mere nanometers in size, and much of the challenge lies in being able to more accurately describe the underlying physics at that nano-scale. But a new computational approach that has been in the works for a decade could break down these barriers. Devices using semiconductors, from computers to solar cells, have enjoyed tremendous efficiency improvements in the last few decades. Famously, one of the co-founders of Intel, Gordon Moore, observed that the number of transistors in an integrated circuit doubles about every two years—and this ‘Moore’s law’ held true for some time. In recent years, however, such gains have slowed as firms that attempt to engineer nano-scale transistors hit the limits of miniaturization at the atomic level. Researchers with the School of Electrical Engineering at KAIST have developed a new approach to the underlying physics of semiconductors. “With open quantum systems as the main research target of our lab, we were revisiting concepts that had been taken for granted and even appear in standard semiconductor physics textbooks such as the voltage drop in operating semiconductor devices,” said the lead researcher Professor Yong-Hoon Kim. “Questioning how all these concepts could be understood and possibly revised at the nano-scale, it was clear that there was something incomplete about our current understanding.” “And as the semiconductor chips are being scaled down to the atomic level, coming up with a better theory to describe semiconductor devices has become an urgent task.” The current understanding states that semiconductors are materials that act like half-way houses between conductors, like copper or steel, and insulators, like rubber or Styrofoam. They sometimes conduct electricity, but not always. This makes them a great material for intentionally controlling the flow of current, which in turn is useful for constructing the simple on/off switches—transistors—that are the foundation of memory and logic devices in computers. In order to ‘switch on’ a semiconductor, a current or light source is applied, exciting an electron in an atom to jump from what is called a ‘valence band,’ which is filled with electrons, up to the ‘conduction band,’ which is originally unfilled or only partially filled with electrons. Electrons that have jumped up to the conduction band thanks to external stimuli and the remaining ‘holes’ are now able to move about and act as charge carriers to flow electric current. The physical concept that describes the populations of the electrons in the conduction band and the holes in the valence band and the energy required to make this jump is formulated in terms of the so-called ‘Fermi level.’ For example, you need to know the Fermi levels of the electrons and holes in order to know what amount of energy you are going to get out of a solar cell, including losses. But the Fermi level concept is only straightforwardly defined so long as a semiconductor device is at equilibrium—sitting on a shelf doing nothing—and the whole point of semiconductor devices is not to leave them on the shelf. Some 70 years ago, William Shockley, the Nobel Prize-winning co-inventor of the transistor at the Bell Labs, came up with a bit of a theoretical fudge, the ‘quasi-Fermi level,’ or QFL, enabling rough prediction and measurement of the interaction between valence band holes and conduction band electrons, and this has worked pretty well until now. “But when you are working at the scale of just a few nanometers, the methods to theoretically calculate or experimentally measure the splitting of QFLs were just not available,” said Professor Kim. This means that at this scale, issues such as errors relating to voltage drop take on much greater significance. Kim’s team worked for nearly ten years on developing a novel theoretical description of nano-scale quantum electron transport that can replace the standard method—and the software that allows them to put it to use. This involved the further development of a bit of math known as the Density Functional Theory that simplifies the equations describing the interactions of electrons, and which has been very useful in other fields such as high-throughput computational materials discovery. For the first time, they were able to calculate the QFL splitting, offering a new understanding of the relationship between voltage drop and quantum electron transport in atomic scale devices. In addition to looking into various interesting non-equilibrium quantum phenomena with their novel methodology, the team is now further developing their software into a computer-aided design tool to be used by semiconductor companies for developing and fabricating advanced semiconductor devices. The study, featured at the Proceedings of the National Academy of Sciences of the USA on May 12, was supported by the National Research Foundation and the Korea Institute of Science and Technology Information Supercomputing Center. Image caption: The newly developed formalism and QFL splitting analysis led to new ways of characterizing extremely scaled-down semiconductor devices and the technology computer-aided design (TCAD) of next- generation nano-electronic/energy/bio devices. Image credit: Yong-Hoon Kim, KAIST Image usage restrictions: News organizations may use or redistribute this image, with proper attribution, as part of news coverage of this paper only. Publication: Juho Lee, Hyeonwoo Yeo, and Yong-Hoon Kim. (2020) ‘Quasi-Fermi level splitting in nanoscale junctions from ab initio.’ Proceedings of the National Academy of Sciences of the United States of America (PNAS), Volume 117, Issue 19, pp.10142-101488. Available online at https://doi.org/10.1073/pnas.1921273117 Profile: Yong-Hoon Kim Professor email@example.com http://nanocore.kaist.ac.kr/ 1st-Principles Nano-Device Computing Lab School of Electrical Engineering KAIST (END)
3D Hierarchically Porous Nanostructured Catalyst Helps Efficiently Reduce CO2
- This new catalyst will bring CO2 one step closer to serving as a sustainable energy source. - KAIST researchers developed a three-dimensional (3D) hierarchically porous nanostructured catalyst with carbon dioxide (CO2) to carbon monoxide (CO) conversion rate up to 3.96 times higher than that of conventional nanoporous gold catalysts. This new catalyst helps overcome the existing limitations of the mass transport that has been a major cause of decreases in the CO2 conversion rate, holding a strong promise for the large-scale and cost-effective electrochemical conversion of CO2 into useful chemicals. As CO2 emissions increase and fossil fuels deplete globally, reducing and converting CO2 to clean energy electrochemically has attracted a great deal of attention as a promising technology. Especially due to the fact that the CO2 reduction reaction occurs competitively with hydrogen evolution reactions (HER) at similar redox potentials, the development of an efficient electrocatalyst for selective and robust CO2 reduction reactions has remained a key technological issue. Gold (Au) is one of the most commonly used catalysts in CO2 reduction reactions, but the high cost and scarcity of Au pose obstacles for mass commercial applications. The development of nanostructures has been extensively studied as a potential approach to improving the selectivity for target products and maximizing the number of active stable sites, thus enhancing the energy efficiency. However, the nanopores of the previously reported complex nanostructures were easily blocked by gaseous CO bubbles during aqueous reactions. The CO bubbles hindered mass transport of the reactants through the electrolyte, resulting in low CO2 conversion rates. In the study published in the Proceedings of the National Academy of Sciences of the USA (PNAS) on March 4, a research group at KAIST led by Professor Seokwoo Jeon and Professor Jihun Oh from the Department of Materials Science and Engineering designed a 3D hierarchically porous Au nanostructure with two different sizes of macropores and nanopores. The team used proximity-field nanopatterning (PnP) and electroplating techniques that are effective for fabricating the 3D well-ordered nanostructures. The proposed nanostructure, comprised of interconnected macroporous channels 200 to 300 nanometers (nm) wide and 10 nm nanopores, induces efficient mass transport through the interconnected macroporous channels as well as high selectivity by producing highly active stable sites from numerous nanopores. As a result, its electrodes show a high CO selectivity of 85.8% at a low overpotential of 0.264 V and efficient mass activity that is up to 3.96 times higher than that of de-alloyed nanoporous Au electrodes. “These results are expected to solve the problem of mass transfer in the field of similar electrochemical reactions and can be applied to a wide range of green energy applications for the efficient utilization of electrocatalysts,” said the researchers. This work was supported by the National Research Foundation (NRF) of Korea. Image credit: Professor Seokwoo Jeon and Professor Jihun Oh, KAIST Image usage restrictions: News organizations may use or redistribute this image, with proper attribution, as part of news coverage of this paper only. Publication: Hyun et al. (2020) Hierarchically porous Au nanostructures with interconnected channels for efficient mass transport in electrocatalytic CO2 reduction. Proceedings of the National Academy of Sciences of the USA (PNAS). Available online at https://doi.org/10.1073/pnas.1918837117 Profile: Seokwoo Jeon, PhD Professor firstname.lastname@example.org http://fdml.kaist.ac.kr Department of Materials Science and Engineering (MSE) https://www.kaist.ac.kr Korea Advanced Institute of Science and Technology (KAIST)Daejeon, Republic of Korea Profile: Jihun Oh, PhD Associate Professor email@example.com http://les.kaist.ac.kr Department of Materials Science and Engineering (MSE) Department of Energy, Environment, Water and Sustainability (EEWS) KAIST Profile: Gayea Hyun PhD Candidate firstname.lastname@example.org http://fdml.kaist.ac.kr Flexible Devices and Metamaterials Laboratory (FDML) Department of Materials Science and Engineering (MSE) KAIST Profile: Jun Tae Song, PhD Assistant Professor email@example.com http://www.cstf.kyushu-u.ac.jp/~ishihara-lab/ Department of Applied Chemistry https://www.kyushu-u.ac.jp Kyushu UniversityFukuoka, Japan (END)
Coordination Chemistry and Alzheimer’s Disease
It has become evident recently that the interactions between copper and amyloid-b neurotoxically impact the brain of patients with Alzheimer’s disease. KAIST researchers have reported a new strategy to alter the neurotoxicity in Alzheimer’s disease by using a rationally designed chemical reagent. This strategy, developed by Professor Mi Hee Lim from the Department of Chemistry, can modify the coordination sphere of copper bound to amyloid-b, effectively inhibiting copper’s binding to amyloid-b and altering its aggregation and toxicity. Their study was featured in PNAS last month. The researchers developed a small molecule that is able to directly interact with the coordination sphere of copper–amyloid-b complexes followed by modifications via either covalent conjugation, oxidation, or both under aerobic conditions. The research team simply utilized copper–dioxygen chemistry to design a chemical reagent. Answering how peptide modifications by a small molecule occur remains very challenging. The system includes transition metals and amyloidogenic proteins and is quite heterogeneous, since they are continuously being changed. It is critical to carefully check the multiple variables such as the presence of dioxygen and the type of transition metal ions and amyloidogenic proteins in order to identify the underlying mechanisms and target specificity of the chemical reagent. The research team employed various biophysical and biochemical methods to determine the mechanisms for modifications on the coordination sphere of copper–Aꞵ complexes. Among them, peptide modifications were mainly analyzed using electrospray ionization-mass spectrometry. Mass spectrometry (MS) has been applied to verify such peptide modifications by calculating the shift in exact mass. The research team also performed collision-induced dissociation (CID) of the target ion detected by MS to pinpoint which amino acid residue is specifically modified. The CID fragmentizes the amide bond located between the amino acid residues. This fragmental analysis allows us to identify the specific sites of peptide modifications. The copper and amyloid-b complexes represent a pathological connection between metal ions and amyloid-b in Alzheimer’s disease. Recent findings indicate that copper and amyloid-b can directly contribute toward neurodegeneration by producing toxic amyloid-b oligomers and reactive oxygen species. Professor Lim said, “This study illustrates the first experimental evidence that the 14th histidine residue in copper–amyloid-b complexes can be specifically modified through either covalent conjugation, oxidation, or both. Considering the neurotoxic implications of the interactions between copper and amyloid-b, such modifications at the coordination sphere of copper in amyloid-b could effectively alter its properties and toxicity.” “This multidisciplinary study with an emphasis on approaches, reactivities, and mechanisms looks forward to opening a new way to develop candidates of anti-neurodegenerative diseases,” she added. The National Research Foundation of Korea funded this research.
Recombinant E. Coli As a Biofactory for the Biosynthesis of Diverse Nanomaterials
(Distinguished Professor Lee and PhD candidate Choi) A metabolic research group at KAIST and Chung-Ang University in Korea has developed a recombinant E. coli strain that biosynthesizes 60 different nanomaterials covering 35 elements on the periodic table. Among the elements, the team could biosynthesize 33 novel nanomaterials for the first time, advancing the forward design of nanomaterials through the biosynthesis of various single and multi-elements. The study analyzed the nanomaterial biosynthesis conditions using a Pourbaix diagram to predict the producibility and crystallinity. Researchers studied a Pourbaix diagram to predict the stable chemical species of each element for nanomaterial biosynthesis at varying levels of reduction potential (Eh) and pH. Based on the Pourbaix diagram analyses, the initial pH of the reaction was changed from 6.5 to 7.5, resulting in the biosynthesis of various crystalline nanomaterials that were previously amorphous or not synthesized. This strategy was extended to biosynthesize multi-element nanomaterials. Various single and multi-element nanomaterials biosynthesized in this research can potentially serve as new and novel nanomaterials for industrial applications such as catalysts, chemical sensors, biosensors, bioimaging, drug delivery, and cancer therapy. A research group consisting of PhD candidate Yoojin Choi, Associate Professor Doh Chang Lee, and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST and Associate Professor Tae Jung Park of the Department of Chemistry at Chung-Ang University reported the synthesis. This study, entitled “Recombinant Escherichia coli as a biofactory for various single- and multi-element nanomaterials,” was published online in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on May 21. A recent successful biosynthesis of nanomaterials under mild conditions without requiring physical and chemical treatments has triggered the exploration of the full biosynthesis capacity of a biological system for producing a diverse range of nanomaterials as well as for understanding biosynthesis mechanisms for crystalline versus amorphous nanomaterials. There has been increased interest in synthesizing various nanomaterials that have not yet been synthesized for various applications including semiconducting materials, enhanced solar cells, biomedical materials, and many others. This research reports the construction of a recombinant E. coli strain that co-expresses metallothionein, a metal binding protein, and phytochelatin synthase that synthesizes the metal-binding peptide phytochelatin for the biosynthesis of various nanomaterials. Subsequently, an E. coli strain was engineered to produce a diverse range of nanomaterials, including those never biosynthesized before, by using 35 individual elements from the periodic table and also by combining multi-elements. Distinguished Professor Lee said, “An environmentally-friendly and sustainable process is of much interest for producing nanomaterials by not only chemical and physical methods but biological synthesis. Moreover, there has been much attention paid to producing diverse and novel nanomaterials for new industrial applications. This is the first report to predict the biosynthesis of various nanomaterials, by far the largest number of various single- and multi-elements nanomaterials. The strategies used for nanomaterial biosynthesis in this research will be useful for further diversifying the portfolio of nanomaterials that can be manufactured.” Figure: The biosynthesis of diverse nanomaterials using recombinant E. coli. This schematic diagram shows the overall conceptualization of the biosynthesis of various single and multi-element nanomaterials using recombinant E. coli under incubation with corresponding elemental precursors. The 35 elements that were tested to biosynthesize nanomaterials are shown in black circles on the periodic table.
Professor Seyun Kim Identifies a Neuron Signal Controlling Molecule
A research team led by Professor Seyun Kim of the Department of Biological Sciences at KAIST has identified inositol pyrophosphates as the molecule that strongly controls neuron signaling via synaptotagmin. Professors Tae-Young Yoon of Yonsei University’s Y-IBS and Sung-Hyun Kim of Kyung Hee University’s Department of Biomedical Science also joined the team. The results were published in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on June 30, 2016. This interdisciplinary research project was conducted by six research teams from four different countries and covered a wide scope of academic fields, from neurobiology to super resolution optic imaging. Inositol pyrophosphates such as 5-diphosphoinositol pentakisphos-phate (5-IP7), which naturally occur in corns and beans, are essential metabolites in the body. In particular, inositol hexakisphosphate (IP6) has anti-cancer properties and is thought to have an important role in cell signaling. Inositol pentakisphosphate (IP7) differs from IP6 by having an additional phosphate group, which was first discovered 20 years ago. IP7 has recently been identified as playing a key role in diabetes and obesity. Psychopathy and neurodegenerative diseases are known to result from the disrupted balance of inositol pyrophosphates. However, the role and the mechanism of action of IP7 in brain neurons and nerve transmission remained unknown. Professor Kim’s team has worked on inositol pyrophosphates for several years and discovered that very small quantities of IP7 control cell-signaling transduction. Professor Yoon of Yonsei University identified IP7 as a much stronger inhibitor of neuron signaling compared to IP6. In particular, IP7 directly suppresses synaptotagmin, one of the key proteins in neuron signaling. Moreover, Professor Kim of Kyung Hee University observed IP7 inhibition in sea horse neurons. Together, the joint research team identified inositol pyrophosphates as the key switch metabolite of brain-signaling transduction. The researchers hope that future research on synaptotagmin and IP7 will reveal the mechanism of neuron-signal transduction and thus enable the treatment of neurological disorders. These research findings were the result of cooperation of various science and technology institutes: KAIST, Yonsei-IBS (Institute for Basic Science), Kyung Hee University, Sungkyunkwan University, KIST, University of Zurich in Switzerland, and Albert-Ludwigs-University Freiburg in Germany. Schematic Image of Controlling the Synaptic Exocytotic Pathway by 5-IP7 , Helping the Understanding of the Signaling Mechanisms of Inositol Pyrophosphates
Artificial Antibody-based Therapeutic Candidate for Lung Cancer Developed
Professor Hak-Sung Kim of Biological Sciences at KAIST publishes a cover article on artificial antibody in "Molecular Therapy". Repebody-based lung cancer therapeutic drug candidate developed Repebody-based protein demonstrates the possibility of the development of a new drug KAIST Biological Sciences Department’s Professor Hak-Sung Kim, in collaboration with Professor Eun-Kyung Cho from the College of Medicine at Chungnam National University, has successfully developed an artificial antibody-based, or repebody, cancer therapeutic candidate. These research results were published as a cover paper of the July edition of Molecular Therapy. The repebody developed by Professor Kim and his team strongly binds to interleukin-6, a cancer-causing factor. It has also been confirmed that the repebody can significantly inhibit the proliferation of cancer cells in non-small-cell lung cancer animal model. Numerous multinational pharmaceutical and biotechnology companies have invested astronomical amounts of money in research for the development of protein therapeutics with low side effects and high efficacy. More than 20 kinds of such therapeutics are currently under clinical trials, and over 100 drugs are under clinical demonstration. Among these, the majority is antibody-based therapeutics, and most of the investments are heavily concentrated in this field. However, antibody production cost is very high because it has large molecular weights and complex structural properties, and this makes it difficult to engineer. Consequently, the development costs a great deal of time and money. In order to overcome the existing limitations of antibody-based therapeutics, Professor Kim and his team have developed a new artificial antibody, or repebody, which was published in Proceedings of the National Academy of Sciences (PNAS) in 2012. Based on this research, they have succeeded in developing a therapeutic candidate for treating non-small-cell lung cancer with a specifically strong cohesion to the cancer-causing factor, interleukin-6. Interleukin-6 is a crucial substance within the body that is involved in immune and inflammatory-related signals. When abnormally expressed, it activates various carcinogenic pathways and promotes tumor growth and metastasis. Because of its importance, multinational pharmaceutical companies are heavily investing in developing therapeutics that can inhibit the signaling of interleukin-6. In this study, Professor Kim and his team observed that a repebody consists of repeated modules, and they conceived a module-based affinity amplification technology that can effectively increase the binding affinity with the disease target. The developed therapeutic candidate has been confirmed in cell and animal experiments to show low immunogenicity, as well as to strongly inhibit the proliferation of non-small-cell lung cancer. Furthermore, by investigating the complex structure of the repebody with interleukin-6, Professor Kim has identified its mechanism, which demonstrated the potential for therapeutic development. The researchers are currently carrying out pre-clinical trials for acquiring permission to perform clinical trials on animals with non-small-cell lung cancer. The repebody can be developed into a new protein drug after demonstrating its safety and efficacy. Professor Hak-Sung Kim and his team have confirmed that the repebody can be utilized as a new protein drug, and this will be a significant contribution to Korea’s protein drugs and biotechnology industry development. The research was supported by the Future Pioneer Industry project and sponsored by the Ministry of Science, ICT and Future Planning. Figure 1. Professor Kim’s article published as the cover article of July edition of Molecular Therapy Figure 2. Clinical proof of the repebody’s inhibition of cancer growth using animal models
Materials Developed for Sodium Rechargeable Battery by EEWS
The research group of Professor William Goddard III, You-Sung Jung, and Jang-Wook Choi from the Graduate School of Energy, Environment, Water, and Sustainability (EEWS) at KAIST has developed a new sodium-ion rechargeable battery which operates at a high voltage, can be charged, and stably discharges over 10,000 cycles. The research results were published in the online version of the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on December 30, 2013. Since the material costs of sodium rechargeable batteries is 30 to 40 times lower than lithium batteries, it has received attention as an energy saving tool for smart grids and as the next generation of lithium rechargeable batteries. Until now, sodium-ion rechargeable batteries have had issues with stability when charging and discharging. The research group developed a vanadium-based electrode to solve these problems. The group said follow-up research will be continued to develop advanced technology on sodium rechargeable batteries as it is still currently in the beginning stages. The research team: From left to right is Professors William Goddard, You-Sung Jung, and Jang-Wook Choi
Secondary, High Capacity Battery developed from Rice Husks
Rice husks, a waste product from rice polishing, has been successfully utilized as the silicon anode for use in high capacity lithium ion secondary batteries. The new silicon anode derived from rice husks exhibit superior output and lifespan. Professor Choi Jang Wook (The Graduate School of Energy, Environment, Water and Sustainability (EEWS)) and Professor Park Seung Min (Department of Biochemistry) and their respective research teams separated naturally occurring, highly porous silica material within the rice husks and developed a 3-dimensional, highly porous silicon anode material. The result of the research effort was published in the online edition of the Proceedings of the National Academy of Sciences (PNAS) journal, a world renowned journal in the field of natural sciences. Silicon has attracted much attention as anode material for next generation lithium ion secondary batteries because it exhibits 3~5 times higher capacity than conventional graphene. The high capacity will pave the way to lithium secondary batteries with higher energy densities than conventional batteries. It is anticipated that the application of silicon batteries will yield electronic devices with a longer duration for use in addition to electronic vehicles boasting longer mileage. The silicon anode is based on the 3-dimensional, highly porous structure of rice husks which remedies the problematic extreme volume expansion of conventional silicon anodes. Utilization of inexpensive rice husks to create high value silicon anodes will cause a ripple effect on the industry and academia.
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