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A Study Reveals What Triggers Lung Damage during COVID-19
A longitudinal study of macrophages from SARS-CoV-2 infected lungs offers new insights into dynamic immunological changes A KAIST immunology research team found that a specific subtype of macrophages that originated from blood monocytes plays a key role in the hyper-inflammatory response in SARS-CoV-2 infected lungs, by performing single-cell RNA sequencing of bronchoalveolar lavage fluid cells. This study provides new insights for understanding dynamic changes in immune responses to COVID-19. In the early phase of COVID-19, SARS-CoV-2 infected lung tissue and the immediate defense system is activated. This early and fast response is called ‘innate immunity,’ provided by immune cells residing in lungs. Macrophages are major cell types of the innate immune system of the lungs, and newly differentiated macrophages originating from the bloodstream also contribute to early defenses against viruses. Professor Su-Hyung Park and his collaborators investigated the quantitative and qualitative evaluation of immune responses in the lungs of SARS-CoV-2 infected ferrets. To overcome the limitations of research using patient-originated specimens, the researchers used a ferret infection model to obtain SARS-CoV-2 infected lungs sequentially with a defined time interval. The researchers analyzed the 10 subtypes of macrophages during the five-day course of SARS-CoV-2 infection, and found that infiltrating macrophages originating from activated monocytes in the blood were key players for viral clearance as well as damaged lung tissue. Moreover, they found that the differentiation process of these inflammatory macrophages resembled the immune responses in the lung tissue of severe COVID-19 patients. Currently, the research team is conducting a follow-up study to identify the dynamic changes in immune responses during the use of immunosuppressive agents to control hyper-inflammatory response called ‘cytokine storm’ in patients with COVID-19. Dr. Jeong Seok Lee, the chief medical officer at Genome Insight Inc., explained, “Our analysis will enhance the understanding of the early features of COVID-19 immunity and provide a scientific background for the more precise use of immunosuppressive agents targeting specific macrophage subtypes.” “This study is the first longitudinal study using sequentially obtained immune cells originating from SARS-CoV-2 infected lungs. The research describes the innate immune response to COVID-19 using single cell transcriptome data and enhances our understanding of the two phases of inflammatory responses,” Professor Park said. This work was supported by the Ministry of Health and Welfare and KAIST, and was published in Nature Communications on July 28. -PublicationSu-Hyung Park, Jeong Seok Lee, Su-Hyung Park et al. “Single-cell transcriptome of bronchoalverolar lavage fluid reveals sequential change of macrophages during SARS-CoV-2 infection in ferrets” Nature Communications (https://doi.org/10.1038/s41467-021-24807-0) -ProfileProfessor Su-Hyung ParkLaboratory of Translational Immunology and Vaccinologyhttps://ltiv.kaist.ac.kr/ Graduate School of Medical Science and EngineeringKAIST
2021.08.04
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Professor Heung-Sun Sim the MSIT Scientist of July
Professor Heung-Sun Sim from the Department of Physics was selected as the Scientist of July by the Ministry of Science and ICT. Professor Sim was recognized for his research of the Kondo effect, which opened a novel way to engineer spin screening and entanglement by directly observing a quantum phenomenon known as a Kondo screening cloud. His research revealed that the cloud can mediate interactions between distant spins confined in quantum dots, which is a necessary protocol for semiconductor spin-based quantum information processing. This phenomenon is essentially a cloud that masks magnetic impurities in a material. It was known to exist but its spatial extension had never been observed, creating controversy over whether such an extension actually existed. The research was reported in Nature in March 2020. With this award, Professor Sim received 10 million KRW in prize money.
2021.07.12
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Quantum Laser Turns Energy Loss into Gain
A new laser that generates quantum particles can recycle lost energy for highly efficient, low threshold laser applications Scientists at KAIST have fabricated a laser system that generates highly interactive quantum particles at room temperature. Their findings, published in the journal Nature Photonics, could lead to a single microcavity laser system that requires lower threshold energy as its energy loss increases. The system, developed by KAIST physicist Yong-Hoon Cho and colleagues, involves shining light through a single hexagonal-shaped microcavity treated with a loss-modulated silicon nitride substrate. The system design leads to the generation of a polariton laser at room temperature, which is exciting because this usually requires cryogenic temperatures. The researchers found another unique and counter-intuitive feature of this design. Normally, energy is lost during laser operation. But in this system, as energy loss increased, the amount of energy needed to induce lasing decreased. Exploiting this phenomenon could lead to the development of high efficiency, low threshold lasers for future quantum optical devices. “This system applies a concept of quantum physics known as parity-time reversal symmetry,” explains Professor Cho. “This is an important platform that allows energy loss to be used as gain. It can be used to reduce laser threshold energy for classical optical devices and sensors, as well as quantum devices and controlling the direction of light.” The key is the design and materials. The hexagonal microcavity divides light particles into two different modes: one that passes through the upward-facing triangle of the hexagon and another that passes through its downward-facing triangle. Both modes of light particles have the same energy and path but don’t interact with each other. However, the light particles do interact with other particles called excitons, provided by the hexagonal microcavity, which is made of semiconductors. This interaction leads to the generation of new quantum particles called polaritons that then interact with each other to generate the polariton laser. By controlling the degree of loss between the microcavity and the semiconductor substrate, an intriguing phenomenon arises, with the threshold energy becoming smaller as energy loss increases. This research was supported by the Samsung Science and Technology Foundation and Korea’s National Research Foundation. -PublicationSong,H.G, Choi, M, Woo, K.Y. Yong-Hoon Cho Room-temperature polaritonic non-Hermitian system with single microcavityNature Photonics (https://doi.org/10.1038/s41566-021-00820-z) -ProfileProfessor Yong-Hoon ChoQuantum & Nanobio Photonics Laboratoryhttp://qnp.kaist.ac.kr/ Department of PhysicsKAIST
2021.07.07
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Study of T Cells from COVID-19 Convalescents Guides Vaccine Strategies
Researchers confirm that most COVID-19 patients in their convalescent stage carry stem cell-like memory T cells for months A KAIST immunology research team found that most convalescent patients of COVID-19 develop and maintain T cell memory for over 10 months regardless of the severity of their symptoms. In addition, memory T cells proliferate rapidly after encountering their cognate antigen and accomplish their multifunctional roles. This study provides new insights for effective vaccine strategies against COVID-19, considering the self-renewal capacity and multipotency of memory T cells. COVID-19 is a disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. When patients recover from COVID-19, SARS-CoV-2-specific adaptive immune memory is developed. The adaptive immune system consists of two principal components: B cells that produce antibodies and T cells that eliminate infected cells. The current results suggest that the protective immune function of memory T cells will be implemented upon re-exposure to SARS-CoV-2. Recently, the role of memory T cells against SARS-CoV-2 has been gaining attention as neutralizing antibodies wane after recovery. Although memory T cells cannot prevent the infection itself, they play a central role in preventing the severe progression of COVID-19. However, the longevity and functional maintenance of SARS-CoV-2-specific memory T cells remain unknown. Professor Eui-Cheol Shin and his collaborators investigated the characteristics and functions of stem cell-like memory T cells, which are expected to play a crucial role in long-term immunity. Researchers analyzed the generation of stem cell-like memory T cells and multi-cytokine producing polyfunctional memory T cells, using cutting-edge immunological techniques. This research is significant in that revealing the long-term immunity of COVID-19 convalescent patients provides an indicator regarding the long-term persistence of T cell immunity, one of the main goals of future vaccine development, as well as evaluating the long-term efficacy of currently available COVID-19 vaccines. The research team is presently conducting a follow-up study to identify the memory T cell formation and functional characteristics of those who received COVID-19 vaccines, and to understand the immunological effect of COVID-19 vaccines by comparing the characteristics of memory T cells from vaccinated individuals with those of COVID-19 convalescent patients. PhD candidate Jae Hyung Jung and Dr. Min-Seok Rha, a clinical fellow at Yonsei Severance Hospital, who led the study together explained, “Our analysis will enhance the understanding of COVID-19 immunity and establish an index for COVID-19 vaccine-induced memory T cells.” “This study is the world’s longest longitudinal study on differentiation and functions of memory T cells among COVID-19 convalescent patients. The research on the temporal dynamics of immune responses has laid the groundwork for building a strategy for next-generation vaccine development,” Professor Shin added. This work was supported by the Samsung Science and Technology Foundation and KAIST, and was published in Nature Communications on June 30. -Publication: Jung, J.H., Rha, MS., Sa, M. et al. SARS-CoV-2-specific T cell memory is sustained in COVID-19 convalescent patients for 10 months with successful development of stem cell-like memory T cells. Nat Communications 12, 4043 (2021). https://doi.org/10.1038/s41467-021-24377-1 -Profile: Professor Eui-Cheol Shin Laboratory of Immunology & Infectious Diseases (http://liid.kaist.ac.kr/) Graduate School of Medical Science and Engineering KAIST
2021.07.05
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Defining the Hund Physics Landscape of Two-Orbital Systems
Researchers identify exotic metals in unexpected quantum systems Electrons are ubiquitous among atoms, subatomic tokens of energy that can independently change how a system behaves—but they also can change each other. An international research collaboration found that collectively measuring electrons revealed unique and unanticipated findings. The researchers published their results on May 17 in Physical Review Letters. “It is not feasible to obtain the solution just by tracing the behavior of each individual electron,” said paper author Myung Joon Han, professor of physics at KAIST. “Instead, one should describe or track all the entangled electrons at once. This requires a clever way of treating this entanglement.” Professor Han and the researchers used a recently developed “many-particle” theory to account for the entangled nature of electrons in solids, which approximates how electrons locally interact with one another to predict their global activity. Through this approach, the researchers examined systems with two orbitals — the space in which electrons can inhabit. They found that the electrons locked into parallel arrangements within atom sites in solids. This phenomenon, known as Hund’s coupling, results in a Hund’s metal. This metallic phase, which can give rise to such properties as superconductivity, was thought only to exist in three-orbital systems. “Our finding overturns a conventional viewpoint that at least three orbitals are needed for Hund’s metallicity to emerge,” Professor Han said, noting that two-orbital systems have not been a focus of attention for many physicists. “In addition to this finding of a Hund’s metal, we identified various metallic regimes that can naturally occur in generic, correlated electron materials.” The researchers found four different correlated metals. One stems from the proximity to a Mott insulator, a state of a solid material that should be conductive but actually prevents conduction due to how the electrons interact. The other three metals form as electrons align their magnetic moments — or phases of producing a magnetic field — at various distances from the Mott insulator. Beyond identifying the metal phases, the researchers also suggested classification criteria to define each metal phase in other systems. “This research will help scientists better characterize and understand the deeper nature of so-called ‘strongly correlated materials,’ in which the standard theory of solids breaks down due to the presence of strong Coulomb interactions between electrons,” Professor Han said, referring to the force with which the electrons attract or repel each other. These interactions are not typically present in solid materials but appear in materials with metallic phases. The revelation of metals in two-orbital systems and the ability to determine whole system electron behavior could lead to even more discoveries, according to Professor Han. “This will ultimately enable us to manipulate and control a variety of electron correlation phenomena,” Professor Han said. Co-authors include Siheon Ryee from KAIST and Sangkook Choi from the Condensed Matter Physics and Materials Science Department, Brookhaven National Laboratory in the United States. Korea’s National Research Foundation and the U.S. Department of Energy’s (DOE) Office of Science, Basic Energy Sciences, supported this work. -PublicationSiheon Ryee, Myung Joon Han, and SangKook Choi, 2021.Hund Physics Landscape of Two-Orbital Systems, Physical Review Letters, DOI: 10.1103/PhysRevLett.126.206401 -ProfileProfessor Myung Joon HanDepartment of PhysicsCollege of Natural ScienceKAIST
2021.06.17
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Gut Hormone Triggers Craving for More Proteins
- Revelations from a fly study could improve our understanding of protein malnutrition in humans. - A new study led by KAIST researchers using fruit flies reveals how protein deficiency in the diet triggers cross talk between the gut and brain to induce a desire to eat foods rich in proteins or essential amino acids. This finding reported in the May 5 issue of Nature can lead to a better understanding of malnutrition in humans. “All organisms require a balanced intake of carbohydrates, proteins, and fats for their well being,” explained KAIST neuroscientist and professor Greg Seong-Bae Suh. “Taking in sufficient calories alone won’t do the job, as it can still lead to severe forms of malnutrition including kwashiorkor, if the diet does not include enough proteins,” he added. Scientists already knew that inadequate protein intake in organisms causes a preferential choice of foods rich in proteins or essential amino acids but they didn’t know precisely how this happens. A group of researchers led by Professor Suh at KAIST and Professor Won-Jae Lee at Seoul National University (SNU) investigated this process in flies by examining the effects of different genes on food preference following protein deprivation. The group found that protein deprivation triggered the release of a gut hormone called neuropeptide CNMamide (CNMa) from a specific population of enterocytes - the intestine lining cells. Until now, scientists have known that enterocytes release digestive enzymes into the intestine to help digest and absorb nutrients in the gut. “Our study showed that enterocytes have a more complex role than we previously thought,” said Professor Suh. Enterocytes respond to protein deprivation by releasing CNMa that conveys the nutrient status in the gut to the CNMa receptors on nerve cells in the brain. This then triggers a desire to eat foods containing essential amino acids. Interestingly, the KAIST-SNU team also found that the microbiome - Acetobacter bacteria - present in the gut produces amino acids that can compensate for mild protein deficit in the diet. This basal level of amino acids provided by the microbiome modifies CNMa release and tempers the flies’ compensatory desire to ingest more proteins. The research team was able to further clarify two signalling pathways that respond to protein loss from the diet and ultimately produce the CNMa hormone in these specific enterocytes. The team said that further studies are still needed to understand how CNMa communicates with its receptors in the brain, and whether this happens by directly activating nerve cells that link the gut to the brain or by indirectly activating the brain through blood circulation. Their research could provide insights into the understanding of similar process in mammals including humans. “We chose to investigate a simple organism, the fly, which would make it easier for us to identify and characterize key nutrient sensors. Because all organisms have cravings for needed nutrients, the nutrient sensors and their pathways we identified in flies would also be relevant to those in mammals. We believe that this research will greatly advance our understanding of the causes of metabolic disease and eating-related disorders,” Professor Suh added. This work was supported by the Samsung Science and Technology Foundation (SSTF) and the National Research Foundation (NRF) of Korea. Publication: Kim, B., et al. (2021) Response of the Drosophila microbiome– gut–brain axis to amino acid deficit. Nature. Available online at https://doi.org/10.1038/s41586-021-03522-2 Profile: Greg Seong-Bae Suh, Ph.D Associate Professor seongbaesuh@kaist.ac.krLab of Neural Interoception https://www.suhlab-neuralinteroception.kaist.ac.kr/Department of Biological Sciences https://bio.kaist.ac.kr/ Korea Advanced Institute of Science and Technology (KAIST) https:/kaist.ac.kr/en/ Daejeon 34141, Korea (END)
2021.05.17
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Observing Individual Atoms in 3D Nanomaterials and Their Surfaces
Atoms are the basic building blocks for all materials. To tailor functional properties, it is essential to accurately determine their atomic structures. KAIST researchers observed the 3D atomic structure of a nanoparticle at the atom level via neural network-assisted atomic electron tomography. Using a platinum nanoparticle as a model system, a research team led by Professor Yongsoo Yang demonstrated that an atomicity-based deep learning approach can reliably identify the 3D surface atomic structure with a precision of 15 picometers (only about 1/3 of a hydrogen atom’s radius). The atomic displacement, strain, and facet analysis revealed that the surface atomic structure and strain are related to both the shape of the nanoparticle and the particle-substrate interface. Combined with quantum mechanical calculations such as density functional theory, the ability to precisely identify surface atomic structure will serve as a powerful key for understanding catalytic performance and oxidation effect. “We solved the problem of determining the 3D surface atomic structure of nanomaterials in a reliable manner. It has been difficult to accurately measure the surface atomic structures due to the ‘missing wedge problem’ in electron tomography, which arises from geometrical limitations, allowing only part of a full tomographic angular range to be measured. We resolved the problem using a deep learning-based approach,” explained Professor Yang. The missing wedge problem results in elongation and ringing artifacts, negatively affecting the accuracy of the atomic structure determined from the tomogram, especially for identifying the surface structures. The missing wedge problem has been the main roadblock for the precise determination of the 3D surface atomic structures of nanomaterials. The team used atomic electron tomography (AET), which is basically a very high-resolution CT scan for nanomaterials using transmission electron microscopes. AET allows individual atom level 3D atomic structural determination. “The main idea behind this deep learning-based approach is atomicity—the fact that all matter is composed of atoms. This means that true atomic resolution electron tomogram should only contain sharp 3D atomic potentials convolved with the electron beam profile,” said Professor Yang. “A deep neural network can be trained using simulated tomograms that suffer from missing wedges as inputs, and the ground truth 3D atomic volumes as targets. The trained deep learning network effectively augments the imperfect tomograms and removes the artifacts resulting from the missing wedge problem.” The precision of 3D atomic structure can be enhanced by nearly 70% by applying the deep learning-based augmentation. The accuracy of surface atom identification was also significantly improved. Structure-property relationships of functional nanomaterials, especially the ones that strongly depend on the surface structures, such as catalytic properties for fuel-cell applications, can now be revealed at one of the most fundamental scales: the atomic scale. Professor Yang concluded, “We would like to fully map out the 3D atomic structure with higher precision and better elemental specificity. And not being limited to atomic structures, we aim to measure the physical, chemical, and functional properties of nanomaterials at the 3D atomic scale by further advancing electron tomography techniques.” This research, reported at Nature Communications, was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research M3I3 Project. -Publication Juhyeok Lee, Chaehwa Jeong & Yongsoo Yang “Single-atom level determination of 3-dimensional surface atomic structure via neural network-assisted atomic electron tomography” Nature Communications -Profile Professor Yongsoo Yang Department of Physics Multi-Dimensional Atomic Imaging Lab (MDAIL) http://mdail.kaist.ac.kr KAIST
2021.05.12
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Professor Jae Kyoung Kim to Lead a New Mathematical Biology Research Group at IBS
Professor Jae Kyoung Kim from the KAIST Department of Mathematical Sciences was appointed as the third Chief Investigator (CI) of the Pioneer Research Center (PRC) for Mathematical and Computational Sciences at the Institute for Basic Science (IBS). Professor Kim will launch and lead a new research group that will be devoted to resolving various biological conundrums from a mathematical perspective. His appointment began on March 1, 2021. Professor Kim, a rising researcher in the field of mathematical biology, has received attention from both the mathematical and biological communities at the international level. Professor Kim puts novel and unremitting efforts into understanding biological systems such as cell-to-cell interactions mathematically and designing mathematical models for identifying causes of diseases and developing therapeutic medicines. Through active joint research with biologists, mathematician Kim has addressed many challenges that have remained unsolved in biology and published papers in a number of leading international journals in related fields. His notable works based on mathematical modelling include having designed a biological circuit that can maintain a stable circadian rhythm (Science, 2015) and unveiling the principles of how the biological clock in the body maintains a steady speed for the first time in over 60 years (Molecular Cell, 2015). Recently, through a joint research project with Pfizer, Professor Kim identified what causes the differences between animal and clinical test results during drug development explaining why drugs have different efficacies in different people (Molecular Systems Biology, 2019). The new IBS biomedical mathematics research group led by Professor Kim will further investigate the causes of unstable circadian rhythms and sleeping patterns. The team will aim to present a new paradigm in treatments for sleep disorders. Professor Kim said, “We are all so familiar with sleep behaviors, but the exact mechanisms behind how such behaviors occur are still unknown. Through cooperation with biomedical scientists, our group will do its best to discover the complicated, fundamental mechanisms of sleep, and investigate the causes and cures of sleep disorders.” Every year, the IBS selects young and promising researchers and appoints them as CIs. A maximum of five selected CIs can form each independent research group within the IBS PRC, and receive research funds of 1 billion to 1.5 billion KRW over five years. (END)
2021.03.18
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Professor Mu-Hyun Baik Honored with the POSCO TJ Park Prize
Professor Mu-Hyun Baik at the Department of Chemistry was honored to be the recipient of the 2021 POSCO TJ Park Prize in Science. The POSCO TJ Park Foundation awards every year the individual or organization which made significant contribution in science, education, community development, philanthropy, and technology. Professor Baik, a renowned computational chemist in analyzing complicated chemical reactions to understand how molecules behave and how they change. Professor Baik was awarded in recognition of his pioneering research in designing numerous organometallic catalysts with using computational molecular modelling. In 2016, he published in Science on the catalytic borylation of methane that showed how chemical reactions can be carried out using the natural gas methane as a substrate. In 2020, he reported in Science that electrodes can be used as functional groups with adjustable inductive effects to change the chemical reactivity of molecules that are attached to them, closely mimicking the inductive effect of conventional functional groups. This constitutes a potentially powerful new way of controlling chemical reactions, offering an alternative to preparing derivatives to install electron-withdrawing functional groups. Joined at KAIST in 2015, Professor Baik also serves as associate director at the Center for Catalytic Hydrocarbon Functionalization at the Institute for Basic Science (IBS) since 2015. Among the many recognitions and awards that he received include the Kavli Fellowship by the Kavli Foundation and the National Academy of Science in the US in 2019 and the 2018 Friedrich Wilhelm Bessel Award by the Alexander von Humboldt Foundation in Germany.
2021.03.11
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Rare Mutations May Have Big Impact on Schizophrenia Pathology
- Somatic mutations found only in brain cells disrupt synaptic function. - Schizophrenia is a neurodevelopmental disorder that disrupts brain activity, producing hallucinations, delusions, and other cognitive disturbances. Researchers have long searched for genetic influences in the disease, but genetic mutations have been identified in only a small fraction—fewer than a quarter—of sequenced patients. Now a study shows that “somatic” gene mutations in brain cells could account for some of the disease’s neuropathology. The results of the study, led by Professor Jeong Ho Lee at the Graduate School of Medical Science and Engineering in collaboration with the Stanley Medical Research Institute in the US, appeared in Biological Psychiatry. Traditional genetic mutations, called germline mutations, occur in sperm or egg cells and are passed on to offspring by their parents. Somatic mutations, in contrast, occur in an embryo after fertilization, and they can show up throughout the body or in isolated pockets of tissues, making them much harder to detect from blood or saliva samples, which are typically used for such sequencing studies. Recently, more-advanced genetic sequencing techniques have allowed researchers to detect somatic mutations and studies have shown that even mutations present at very low levels can have functional consequences. A previous study hinted that brain somatic mutations were associated with schizophrenia, but it was not powerful enough to cement an association between brain somatic mutations and schizophrenia. In the current study, the researchers used deep whole-exome sequencing to determine the genetic code of all exomes, the parts of genes that encode proteins. The scientists sequenced postmortem samples from brain, liver, spleen, or heart tissue of 27 people with schizophrenia and 31 control participants allowing them to compare the sequences in the two tissues. Using a powerful analytic technique, the team identified an average of 4.9 somatic single-nucleotide variants, or mutations, in brain samples from people with schizophrenia, and 5.6 somatic single-nucleotide variants in brain samples from control subjects. Although there were no significant quantitative differences in somatic single-nucleotide variants between schizophrenia and control tissue samples, the researchers found that the mutations in schizophrenia patients were found in genes already associated with schizophrenia. Of the germline mutations that had previously been associated with schizophrenia, the genes affected encode proteins associated with synaptic neural communication, particularly in a brain region called the dorsolateral prefrontal cortex. In the new analysis, the researchers determined which proteins might be affected by the newly identified somatic mutations. Remarkably, a protein called GRIN2B emerged as highly affected and two patients with schizophrenia carried somatic mutations on the GRIN2B gene itself. GRIN2B is a protein component of NMDA-type glutamate receptors, which are critical for neural signaling. Faulty glutamate receptors have long been suspected of contributing to schizophrenia pathology; GRIN2B ranks among the most-studied genes in schizophrenia. The somatic mutations identified in the study had a variant allele frequency of only ~1%, indicating that the mutations were rare among brain cells as a whole. Nevertheless, they have the potential to create widespread cortical dysfunction. Professor Lee said, “Besides the comprehensive genetic analysis of brain-only mutations in postmortem tissues from schizophrenia patients, this study experimentally showed the biological consequence of identified somatic mutations, which led to neuronal abnormalities associated with schizophrenia. Thus, this study suggests that brain somatic mutations can be a hidden major contributor to schizophrenia and provides new insights into the molecular genetic architecture of schizophrenia. John Krystal, MD, editor of Biological Psychiatry, said of the work, "The genetics of schizophrenia has received intensive study for several decades. Now a new possibility emerges, that in some cases, mutations in the DNA of brain cells contributes to the biology of schizophrenia. Remarkably this new biology points to an old schizophrenia story: NMDA glutamate receptor dysfunction. Perhaps the path through which somatic mutations contribute to schizophrenia converges with other sources of abnormalities in glutamate signaling in this disorder." Professor Lee and the team next want to assess the functional consequences of the somatic mutations. Because of the location of the GRIN2B mutations found in schizophrenia patients, the researchers hypothesized that they might interfere with the receptors’ localization on neurons. Experiments on the cortical neurons of mice showed that the mutations indeed disrupted the receptors’ usual localization to dendrites, the “listening” ends of neurons, which in turn prevented the formation of normal synapses in the neurons. This finding suggests that the somatic mutations could disrupt neural communication, contributing to schizophrenia pathology. - Profile: Professor Jeong Ho Lee Translational Neurogenetics Laboratory ( https://tnl.kaist.ac.kr/) The Graduate School of Medical Science and Engineering KAIST (END)
2021.03.11
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Deep-Learning and 3D Holographic Microscopy Beats Scientists at Analyzing Cancer Immunotherapy
Live tracking and analyzing of the dynamics of chimeric antigen receptor (CAR) T-cells targeting cancer cells can open new avenues for the development of cancer immunotherapy. However, imaging via conventional microscopy approaches can result in cellular damage, and assessments of cell-to-cell interactions are extremely difficult and labor-intensive. When researchers applied deep learning and 3D holographic microscopy to the task, however, they not only avoided these difficultues but found that AI was better at it than humans were. Artificial intelligence (AI) is helping researchers decipher images from a new holographic microscopy technique needed to investigate a key process in cancer immunotherapy “live” as it takes place. The AI transformed work that, if performed manually by scientists, would otherwise be incredibly labor-intensive and time-consuming into one that is not only effortless but done better than they could have done it themselves. The research, conducted by the team of Professor YongKeun Park from the Department of Physics, appeared in the journal eLife last December. A critical stage in the development of the human immune system’s ability to respond not just generally to any invader (such as pathogens or cancer cells) but specifically to that particular type of invader and remember it should it attempt to invade again is the formation of a junction between an immune cell called a T-cell and a cell that presents the antigen, or part of the invader that is causing the problem, to it. This process is like when a picture of a suspect is sent to a police car so that the officers can recognize the criminal they are trying to track down. The junction between the two cells, called the immunological synapse, or IS, is the key process in teaching the immune system how to recognize a specific type of invader. Since the formation of the IS junction is such a critical step for the initiation of an antigen-specific immune response, various techniques allowing researchers to observe the process as it happens have been used to study its dynamics. Most of these live imaging techniques rely on fluorescence microscopy, where genetic tweaking causes part of a protein from a cell to fluoresce, in turn allowing the subject to be tracked via fluorescence rather than via the reflected light used in many conventional microscopy techniques. However, fluorescence-based imaging can suffer from effects such as photo-bleaching and photo-toxicity, preventing the assessment of dynamic changes in the IS junction process over the long term. Fluorescence-based imaging still involves illumination, whereupon the fluorophores (chemical compounds that cause the fluorescence) emit light of a different color. Photo-bleaching or photo-toxicity occur when the subject is exposed to too much illumination, resulting in chemical alteration or cellular damage. One recent option that does away with fluorescent labelling and thereby avoids such problems is 3D holographic microscopy or holotomography (HT). In this technique, the refractive index (the way that light changes direction when encountering a substance with a different density—why a straw looks like it bends in a glass of water) is recorded in 3D as a hologram. Until now, HT has been used to study single cells, but never cell-cell interactions involved in immune responses. One of the main reasons is the difficulty of “segmentation,” or distinguishing the different parts of a cell and thus distinguishing between the interacting cells; in other words, deciphering which part belongs to which cell. Manual segmentation, or marking out the different parts manually, is one option, but it is difficult and time-consuming, especially in three dimensions. To overcome this problem, automatic segmentation has been developed in which simple computer algorithms perform the identification. “But these basic algorithms often make mistakes,” explained Professor YongKeun Park, “particularly with respect to adjoining segmentation, which of course is exactly what is occurring here in the immune response we’re most interested in.” So, the researchers applied a deep learning framework to the HT segmentation problem. Deep learning is a type of machine learning in which artificial neural networks based on the human brain recognize patterns in a way that is similar to how humans do this. Regular machine learning requires data as an input that has already been labelled. The AI “learns” by understanding the labeled data and then recognizes the concept that has been labelled when it is fed novel data. For example, AI trained on a thousand images of cats labelled “cat” should be able to recognize a cat the next time it encounters an image with a cat in it. Deep learning involves multiple layers of artificial neural networks attacking much larger, but unlabeled datasets, in which the AI develops its own ‘labels’ for concepts it encounters. In essence, the deep learning framework that KAIST researchers developed, called DeepIS, came up with its own concepts by which it distinguishes the different parts of the IS junction process. To validate this method, the research team applied it to the dynamics of a particular IS junction formed between chimeric antigen receptor (CAR) T-cells and target cancer cells. They then compared the results to what they would normally have done: the laborious process of performing the segmentation manually. They found not only that DeepIS was able to define areas within the IS with high accuracy, but that the technique was even able to capture information about the total distribution of proteins within the IS that may not have been easily measured using conventional techniques. “In addition to allowing us to avoid the drudgery of manual segmentation and the problems of photo-bleaching and photo-toxicity, we found that the AI actually did a better job,” Professor Park added. The next step will be to combine the technique with methods of measuring how much physical force is applied by different parts of the IS junction, such as holographic optical tweezers or traction force microscopy. -Profile Professor YongKeun Park Department of Physics Biomedical Optics Laboratory http://bmol.kaist.ac.kr KAIST
2021.02.24
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Astrocytes Eat Connections to Maintain Plasticity in Adult Brains
Developing brains constantly sprout new neuronal connections called synapses as they learn and remember. Important connections — the ones that are repeatedly introduced, such as how to avoid danger — are nurtured and reinforced, while connections deemed unnecessary are pruned away. Adult brains undergo similar pruning, but it was unclear how or why synapses in the adult brain get eliminated. Now, a team of KAIST researchers has found the mechanism underlying plasticity and, potentially, neurological disorders in adult brains. They published their findings on December 23 in Nature. “Our findings have profound implications for our understanding of how neural circuits change during learning and memory, as well as in diseases,” said paper author Won-Suk Chung, an assistant professor in the Department of Biological Sciences at KAIST. “Changes in synapse number have strong association with the prevalence of various neurological disorders, such as autism spectrum disorder, schizophrenia, frontotemporal dementia, and several forms of seizures.” Gray matter in the brain contains microglia and astrocytes, two complementary cells that, among other things, support neurons and synapses. Microglial are a frontline immunity defense, responsible for eating pathogens and dead cells, and astrocytes are star-shaped cells that help structure the brain and maintain homeostasis by helping to control signaling between neurons. According to Professor Chung, it is generally thought that microglial eat synapses as part of its clean-up effort in a process known as phagocytosis. “Using novel tools, we show that, for the first time, it is astrocytes and not microglia that constantly eliminate excessive and unnecessary adult excitatory synaptic connections in response to neuronal activity,” Professor Chung said. “Our paper challenges the general consensus in this field that microglia are the primary synapse phagocytes that control synapse numbers in the brain.” Professor Chung and his team developed a molecular sensor to detect synapse elimination by glial cells and quantified how often and by which type of cell synapses were eliminated. They also deployed it in a mouse model without MEGF10, the gene that allows astrocytes to eliminate synapses. Adult animals with this defective astrocytic phagocytosis had unusually increased excitatory synapse numbers in the hippocampus. Through a collaboration with Dr. Hyungju Park at KBRI, they showed that these increased excitatory synapses are functionally impaired, which cause defective learning and memory formation in MEGF10 deleted animals. “Through this process, we show that, at least in the adult hippocampal CA1 region, astrocytes are the major player in eliminating synapses, and this astrocytic function is essential for controlling synapse number and plasticity,” Chung said. Professor Chung noted that researchers are only beginning to understand how synapse elimination affects maturation and homeostasis in the brain. In his group’s preliminary data in other brain regions, it appears that each region has different rates of synaptic elimination by astrocytes. They suspect a variety of internal and external factors are influencing how astrocytes modulate each regional circuit, and plan to elucidate these variables. “Our long-term goal is understanding how astrocyte-mediated synapse turnover affects the initiation and progression of various neurological disorders,” Professor Chung said. “It is intriguing to postulate that modulating astrocytic phagocytosis to restore synaptic connectivity may be a novel strategy in treating various brain disorders.” This work was supported by the Samsung Science & Technology Foundation, the National Research Foundation of Korea, and the Korea Brain Research Institute basic research program. Other contributors include Joon-Hyuk Lee and Se Young Lee, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST); Ji-young Kim, Hyoeun Lee and Hyungju Park; Research Group for Neurovascular Unit, Korea Brain Research Institute (KBRI); Seulgi Noh, and Ji Young Mun, Research Group for Neural Circuit, KBRI. Kim, Noh and Park are also affiliated with the Department of Brain and Cognitive Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST). -Profile Professor Won-Suk Chung Department of Biological Sciences Gliabiology Lab (https://www.kaistglia.org/) KAIST -Publication "Astrocytes phagocytose adult hippocampal synapses for circuit homeostasis" https://doi.org/10.1038/s41586-020-03060-3
2020.12.24
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