BIO
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3D Visualization and Quantification of Bioplastic PHA in a Living Bacterial Cell
3D holographic microscopy leads to in-depth analysis of bacterial cells accumulating the bacterial bioplastic, polyhydroxyalkanoate (PHA)
A research team at KAIST has observed how bioplastic granule is being accumulated in living bacteria cells through 3D holographic microscopy. Their 3D imaging and quantitative analysis of the bioplastic ‘polyhydroxyalkanoate’ (PHA) via optical diffraction tomography provides insights into biosynthesizing sustainable substitutes for petroleum-based plastics.
The bio-degradable polyester polyhydroxyalkanoate (PHA) is being touted as an eco-friendly bioplastic to replace existing synthetic plastics. While carrying similar properties to general-purpose plastics such as polyethylene and polypropylene, PHA can be used in various industrial applications such as container packaging and disposable products.
PHA is synthesized by numerous bacteria as an energy and carbon storage material under unbalanced growth conditions in the presence of excess carbon sources. PHA exists in the form of insoluble granules in the cytoplasm. Previous studies on investigating in vivo PHA granules have been performed by using fluorescence microscopy, transmission electron microscopy (TEM), and electron cryotomography.
These techniques have generally relied on the statistical analysis of multiple 2D snapshots of fixed cells or the short-time monitoring of the cells. For the TEM analysis, cells need to be fixed and sectioned, and thus the investigation of living cells was not possible. Fluorescence-based techniques require fluorescence labeling or dye staining. Thus, indirect imaging with the use of reporter proteins cannot show the native state of PHAs or cells, and invasive exogenous dyes can affect the physiology and viability of the cells. Therefore, it was difficult to fully understand the formation of PHA granules in cells due to the technical limitations, and thus several mechanism models based on the observations have been only proposed.
The team of metabolic engineering researchers led by Distinguished Professor Sang Yup Lee and Physics Professor YongKeun Park, who established the startup Tomocube with his 3D holographic microscopy, reported the results of 3D quantitative label-free analysis of PHA granules in individual live bacterial cells by measuring the refractive index distributions using optical diffraction tomography. The formation and growth of PHA granules in the cells of Cupriavidus necator, the most-studied native PHA (specifically, poly(3-hydroxybutyrate), also known as PHB) producer, and recombinant Escherichia coli harboring C. necator PHB biosynthesis pathway were comparatively examined.
From the reconstructed 3D refractive index distribution of the cells, the team succeeded in the 3D visualization and quantitative analysis of cells and intracellular PHA granules at a single-cell level. In particular, the team newly presented the concept of “in vivo PHA granule density.” Through the statistical analysis of hundreds of single cells accumulating PHA granules, the distinctive differences of density and localization of PHA granules in the two micro-organisms were found. Furthermore, the team identified the key protein that plays a major role in making the difference that enabled the characteristics of PHA granules in the recombinant E. coli to become similar to those of C. necator.
The research team also presented 3D time-lapse movies showing the actual processes of PHA granule formation combined with cell growth and division. Movies showing the living cells synthesizing and accumulating PHA granules in their native state had never been reported before.
Professor Lee said, “This study provides insights into the morphological and physical characteristics of in vivo PHA as well as the unique mechanisms of PHA granule formation that undergo the phase transition from soluble monomers into the insoluble polymer, followed by granule formation. Through this study, a deeper understanding of PHA granule formation within the bacterial cells is now possible, which has great significance in that a convergence study of biology and physics was achieved. This study will help develop various bioplastics production processes in the future.”
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (Grants NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557) and the Bio & Medical Technology Development Program (Grant No. 2021M3A9I4022740) from the Ministry of Science and ICT (MSIT) through the National Research Foundation (NRF) of Korea to S.Y.L. This work was also supported by the KAIST Cross-Generation Collaborative Laboratory project.
-PublicationSo Young Choi, Jeonghun Oh, JaeHwang Jung, YongKeun Park, and Sang Yup Lee. Three-dimensional label-free visualization and quantification of polyhydroxyalkanoates in individualbacterial cell in its native state. PNAS(https://doi.org./10.1073/pnas.2103956118)
-ProfileDistinguished Professor Sang Yup LeeMetabolic Engineering and Synthetic Biologyhttp://mbel.kaist.ac.kr/
Department of Chemical and Biomolecular Engineering KAIST
Endowed Chair Professor YongKeun ParkBiomedical Optics Laboratoryhttps://bmokaist.wordpress.com/
Department of PhysicsKAIST
2021.07.28 View 10348 -
Biomimetic Resonant Acoustic Sensor Detecting Far-Distant Voices Accurately to Hit the Market
A KAIST research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering has developed a bioinspired flexible piezoelectric acoustic sensor with multi-resonant ultrathin piezoelectric membrane mimicking the basilar membrane of the human cochlea. The flexible acoustic sensor has been miniaturized for embedding into smartphones and the first commercial prototype is ready for accurate and far-distant voice detection.
In 2018, Professor Lee presented the first concept of a flexible piezoelectric acoustic sensor, inspired by the fact that humans can accurately detect far-distant voices using a multi-resonant trapezoidal membrane with 20,000 hair cells. However, previous acoustic sensors could not be integrated into commercial products like smartphones and AI speakers due to their large device size.
In this work, the research team fabricated a mobile-sized acoustic sensor by adopting ultrathin piezoelectric membranes with high sensitivity. Simulation studies proved that the ultrathin polymer underneath inorganic piezoelectric thin film can broaden the resonant bandwidth to cover the entire voice frequency range using seven channels. Based on this theory, the research team successfully demonstrated the miniaturized acoustic sensor mounted in commercial smartphones and AI speakers for machine learning-based biometric authentication and voice processing. (Please refer to the explanatory movie KAIST Flexible Piezoelectric Mobile Acoustic Sensor).
The resonant mobile acoustic sensor has superior sensitivity and multi-channel signals compared to conventional condenser microphones with a single channel, and it has shown highly accurate and far-distant speaker identification with a small amount of voice training data. The error rate of speaker identification was significantly reduced by 56% (with 150 training datasets) and 75% (with 2,800 training datasets) compared to that of a MEMS condenser device.
Professor Lee said, “Recently, Google has been targeting the ‘Wolverine Project’ on far-distant voice separation from multi-users for next-generation AI user interfaces. I expect that our multi-channel resonant acoustic sensor with abundant voice information is the best fit for this application. Currently, the mass production process is on the verge of completion, so we hope that this will be used in our daily lives very soon.”
Professor Lee also established a startup company called Fronics Inc., located both in Korea and U.S. (branch office) to commercialize this flexible acoustic sensor and is seeking collaborations with global AI companies.
These research results entitled “Biomimetic and Flexible Piezoelectric Mobile Acoustic Sensors with Multi-Resonant Ultrathin Structures for Machine Learning Biometrics” were published in Science Advances in 2021 (7, eabe5683).
-Publication
“Biomimetic and flexible piezoelectric mobile acoustic sensors with multiresonant ultrathin structures for machine learning biometrics,” Science Advances (DOI: 10.1126/sciadv.abe5683)
-Profile
Professor Keon Jae Lee
Department of Materials Science and Engineering
Flexible and Nanobio Device Lab
http://fand.kaist.ac.kr/
KAIST
2021.06.14 View 8352 -
Microbial Production of a Natural Red Colorant Carminic Acid
Metabolic engineering and computer-simulated enzyme engineering led to the production of carminic acid, a natural red colorant, from bacteria for the first time
A research group at KAIST has engineered a bacterium capable of producing a natural red colorant, carminic acid, which is widely used for food and cosmetics. The research team reported the complete biosynthesis of carminic acid from glucose in engineered Escherichia coli. The strategies will be useful for the design and construction of biosynthetic pathways involving unknown enzymes and consequently the production of diverse industrially important natural products for the food, pharmaceutical, and cosmetic industries.
Carminic acid is a natural red colorant widely being used for products such as strawberry milk and lipstick. However, carminic acid has been produced by farming cochineals, a scale insect which only grows in the region around Peru and Canary Islands, followed by complicated multi-step purification processes. Moreover, carminic acid often contains protein contaminants that cause allergies so many people are unwilling to consume products made of insect-driven colorants. On that account, manufacturers around the world are using alternative red colorants despite the fact that carminic acid is one of the most stable natural red colorants.
These challenges inspired the metabolic engineering research group at KAIST to address this issue. Its members include postdoctoral researchers Dongsoo Yang and Woo Dae Jang, and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering. This study entitled “Production of carminic acid by metabolically engineered Escherichia coli” was published online in the Journal of the American Chemical Society (JACS) on April 2.
This research reports for the first time the development of a bacterial strain capable of producing carminic acid from glucose via metabolic engineering and computer simulation-assisted enzyme engineering. The research group optimized the type II polyketide synthase machinery to efficiently produce the precursor of carminic acid, flavokermesic acid.
Since the enzymes responsible for the remaining two reactions were neither discovered nor functional, biochemical reaction analysis was performed to identify enzymes that can convert flavokermesic acid into carminic acid. Then, homology modeling and docking simulations were performed to enhance the activities of the two identified enzymes. The team could confirm that the final engineered strain could produce carminic acid directly from glucose. The C-glucosyltransferase developed in this study was found to be generally applicable for other natural products as showcased by the successful production of an additional product, aloesin, which is found in aloe leaves.
“The most important part of this research is that unknown enzymes for the production of target natural products were identified and improved by biochemical reaction analyses and computer simulation-assisted enzyme engineering,” says Dr. Dongsoo Yang. He explained the development of a generally applicable C-glucosyltransferase is also useful since C-glucosylation is a relatively unexplored reaction in bacteria including Escherichia coli. Using the C-glucosyltransferase developed in this study, both carminic acid and aloesin were successfully produced from glucose.
“A sustainable and insect-free method of producing carminic acid was achieved for the first time in this study. Unknown or inefficient enzymes have always been a major problem in natural product biosynthesis, and here we suggest one effective solution for solving this problem. As maintaining good health in the aging society is becoming increasingly important, we expect that the technology and strategies developed here will play pivotal roles in producing other valuable natural products of medical or nutritional importance,” said Distinguished Professor Sang Yup Lee.
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries of the Ministry of Science and ICT (MSIT) through the National Research Foundation (NRF) of Korea and the KAIST Cross-Generation Collaborative Lab project; Sang Yup Lee and Dongsoo Yang were also supported by Novo Nordisk Foundation in Denmark.
Publication:
Dongsoo Yang, Woo Dae Jang, and Sang Yup Lee. Production of carminic acid by metabolically engineered Escherichia coli. at the Journal of the American Chemical Society. https://doi.org.10.1021/jacs.0c12406
Profile:
Sang Yup Lee, PhD
Distinguished Professor
leesy@kaist.ac.kr
http://mbel.kaist.ac.kr
Metabolic &Biomolecular Engineering National Research Laboratory
Department of Chemical and Biomolecular Engineering
KAIST
2021.04.06 View 10348 -
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.
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2021.03.18 View 8175 -
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 View 10370 -
Attachable Skin Monitors that Wick the Sweat Away
- A silicone membrane for wearable devices is more comfortable and breathable thanks to better-sized pores made with the help of citric acid crystals. -
A new preparation technique fabricates thin, silicone-based patches that rapidly wick water away from the skin. The technique could reduce the redness and itching caused by wearable biosensors that trap sweat beneath them. The technique was developed by bioengineer and professor Young-Ho Cho and his colleagues at KAIST and reported in the journal Scientific Reports last month.
“Wearable bioelectronics are becoming more attractive for the day-to-day monitoring of biological compounds found in sweat, like hormones or glucose, as well as body temperature, heart rate, and energy expenditure,” Professor Cho explained. “But currently available materials can cause skin irritation, so scientists are looking for ways to improve them,” he added.
Attachable biosensors often use a silicone-based compound called polydimethylsiloxane (PDMS), as it has a relatively high water vapour transmission rate compared to other materials. Still, this rate is only two-thirds that of skin’s water evaporation rate, meaning sweat still gets trapped underneath it.
Current fabrication approaches mix PDMS with beads or solutes, such as sugars or salts, and then remove them to leave pores in their place. Another technique uses gas to form pores in the material. Each technique has its disadvantages, from being expensive and complex to leaving pores of different sizes.
A team of researchers led by Professor Cho from the KAIST Department of Bio and Brain Engineering was able to form small, uniform pores by crystallizing citric acid in PDMS and then removing the crystals using ethanol. The approach is significantly cheaper than using beads, and leads to 93.2% smaller and 425% more uniformly-sized pores compared to using sugar. Importantly, the membrane transmits water vapour 2.2 times faster than human skin.
The team tested their membrane on human skin for seven days and found that it caused only minor redness and no itching, whereas a non-porous PDMS membrane did.
Professor Cho said, “Our method could be used to fabricate porous PDMS membranes for skin-attachable devices used for daily monitoring of physiological signals.”
“We next plan to modify our membrane so it can be more readily attached to and removed from skin,” he added.
This work was supported by the Ministry of Trade, Industry and Energy (MOTIE) of Korea under the Alchemist Project.
Image description:
Smaller, more uniformly-sized pores are made in the PDMS membrane by mixing PDMS, toluene, citric acid, and ethanol. Toluene dilutes PDMS so it can easily mix with the other two constituents. Toluene and ethanol are then evaporated, which causes the citric acid to crystallize within the PDMS material. The mixture is placed in a mould where it solidifies into a thin film. The crystals are then removed using ethanol, leaving pores in their place.
Image credit:
Professor Young-Ho Cho, 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:
Yoon, S, et al. (2021) Wearable porous PDMS layer of high moisture permeability for skin trouble reduction. Scientific Reports 11, Article No. 938. Available online at https://doi.org/10.1038/s41598-020-78580-z
Profile:
Young-Ho Cho, Ph.D
Professor
mems@kaist.ac.kr
https://mems.kaist.ac.kr
NanoSentuating Systems Laboratory
Department of Bio and Brain Engineering
https://kaist.ac.kr
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, Republic of Korea
(END)
2021.02.22 View 10978 -
Wirelessly Rechargeable Soft Brain Implant Controls Brain Cells
Researchers have invented a smartphone-controlled soft brain implant that can be recharged wirelessly from outside the body. It enables long-term neural circuit manipulation without the need for periodic disruptive surgeries to replace the battery of the implant. Scientists believe this technology can help uncover and treat psychiatric disorders and neurodegenerative diseases such as addiction, depression, and Parkinson’s.
A group of KAIST researchers and collaborators have engineered a tiny brain implant that can be wirelessly recharged from outside the body to control brain circuits for long periods of time without battery replacement. The device is constructed of ultra-soft and bio-compliant polymers to help provide long-term compatibility with tissue. Geared with micrometer-sized LEDs (equivalent to the size of a grain of salt) mounted on ultrathin probes (the thickness of a human hair), it can wirelessly manipulate target neurons in the deep brain using light.
This study, led by Professor Jae-Woong Jeong, is a step forward from the wireless head-mounted implant neural device he developed in 2019. That previous version could indefinitely deliver multiple drugs and light stimulation treatment wirelessly by using a smartphone. For more, Manipulating Brain Cells by Smartphone.
For the new upgraded version, the research team came up with a fully implantable, soft optoelectronic system that can be remotely and selectively controlled by a smartphone. This research was published on January 22, 2021 in Nature Communications.
The new wireless charging technology addresses the limitations of current brain implants. Wireless implantable device technologies have recently become popular as alternatives to conventional tethered implants, because they help minimize stress and inflammation in freely-moving animals during brain studies, which in turn enhance the lifetime of the devices. However, such devices require either intermittent surgeries to replace discharged batteries, or special and bulky wireless power setups, which limit experimental options as well as the scalability of animal experiments.
“This powerful device eliminates the need for additional painful surgeries to replace an exhausted battery in the implant, allowing seamless chronic neuromodulation,” said Professor Jeong. “We believe that the same basic technology can be applied to various types of implants, including deep brain stimulators, and cardiac and gastric pacemakers, to reduce the burden on patients for long-term use within the body.”
To enable wireless battery charging and controls, researchers developed a tiny circuit that integrates a wireless energy harvester with a coil antenna and a Bluetooth low-energy chip. An alternating magnetic field can harmlessly penetrate through tissue, and generate electricity inside the device to charge the battery. Then the battery-powered Bluetooth implant delivers programmable patterns of light to brain cells using an “easy-to-use” smartphone app for real-time brain control.
“This device can be operated anywhere and anytime to manipulate neural circuits, which makes it a highly versatile tool for investigating brain functions,” said lead author Choong Yeon Kim, a researcher at KAIST.
Neuroscientists successfully tested these implants in rats and demonstrated their ability to suppress cocaine-induced behaviour after the rats were injected with cocaine. This was achieved by precise light stimulation of relevant target neurons in their brains using the smartphone-controlled LEDs. Furthermore, the battery in the implants could be repeatedly recharged while the rats were behaving freely, thus minimizing any physical interruption to the experiments.
“Wireless battery re-charging makes experimental procedures much less complicated,” said the co-lead author Min Jeong Ku, a researcher at Yonsei University’s College of Medicine.
“The fact that we can control a specific behaviour of animals, by delivering light stimulation into the brain just with a simple manipulation of smartphone app, watching freely moving animals nearby, is very interesting and stimulates a lot of imagination,” said Jeong-Hoon Kim, a professor of physiology at Yonsei University’s College of Medicine. “This technology will facilitate various avenues of brain research.”
The researchers believe this brain implant technology may lead to new opportunities for brain research and therapeutic intervention to treat diseases in the brain and other organs.
This work was supported by grants from the National Research Foundation of Korea and the KAIST Global Singularity Research Program.
-Profile
Professor Jae-Woong Jeong
https://www.jeongresearch.org/
School of Electrical Engineering
KAIST
2021.01.26 View 23320 -
Expanding the Biosynthetic Pathway via Retrobiosynthesis
- Researchers reports a new strategy for the microbial production of multiple short-chain primary amines via retrobiosynthesis. -
KAIST metabolic engineers presented the bio-based production of multiple short-chain primary amines that have a wide range of applications in chemical industries for the first time. The research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering designed the novel biosynthetic pathways for short-chain primary amines by combining retrobiosynthesis and a precursor selection step.
The research team verified the newly designed pathways by confirming the in vivo production of 10 short-chain primary amines by supplying the precursors. Furthermore, the platform Escherichia coli strains were metabolically engineered to produce three proof-of-concept short-chain primary amines from glucose, demonstrating the possibility of the bio-based production of diverse short-chain primary amines from renewable resources. The research team said this study expands the strategy of systematically designing biosynthetic pathways for the production of a group of related chemicals as demonstrated by multiple short-chain primary amines as examples.
Currently, most of the industrial chemicals used in our daily lives are produced with petroleum-based products. However, there are several serious issues with the petroleum industry such as the depletion of fossil fuel reserves and environmental problems including global warming. To solve these problems, the sustainable production of industrial chemicals and materials is being explored with microorganisms as cell factories and renewable non-food biomass as raw materials for alternative to petroleum-based products. The engineering of these microorganisms has increasingly become more efficient and effective with the help of systems metabolic engineering – a practice of engineering the metabolism of a living organism toward the production of a desired metabolite. In this regard, the number of chemicals produced using biomass as a raw material has substantially increased.
Although the scope of chemicals that are producible using microorganisms continues to expand through advances in systems metabolic engineering, the biological production of short-chain primary amines has not yet been reported despite their industrial importance. Short-chain primary amines are the chemicals that have an alkyl or aryl group in the place of a hydrogen atom in ammonia with carbon chain lengths ranging from C1 to C7. Short-chain primary amines have a wide range of applications in chemical industries, for example, as a precursor for pharmaceuticals (e.g., antidiabetic and antihypertensive drugs), agrochemicals (e.g., herbicides, fungicides and insecticides), solvents, and vulcanization accelerators for rubber and plasticizers. The market size of short-chain primary amines was estimated to be more than 4 billion US dollars in 2014.
The main reason why the bio-based production of short-chain primary amines was not yet possible was due to their unknown biosynthetic pathways. Therefore, the team designed synthetic biosynthetic pathways for short-chain primary amines by combining retrobiosynthesis and a precursor selection step. The retrobiosynthesis allowed the systematic design of a biosynthetic pathway for short-chain primary amines by using a set of biochemical reaction rules that describe chemical transformation patterns between a substrate and product molecules at an atomic level.
These multiple precursors predicted for the possible biosynthesis of each short-chain primary amine were sequentially narrowed down by using the precursor selection step for efficient metabolic engineering experiments.
“Our research demonstrates the possibility of the renewable production of short-chain primary amines for the first time. We are planning to increase production efficiencies of short-chain primary amines. We believe that our study will play an important role in the development of sustainable and eco-friendly bio-based industries and the reorganization of the chemical industry, which is mandatory for solving the environmental problems threating the survival of mankind,” said Professor Lee.
This paper titled “Microbial production of multiple short-chain primary amines via retrobiosynthesis” was published in Nature Communications. This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT through the National Research Foundation (NRF) of Korea.
-Publication
Dong In Kim, Tong Un Chae, Hyun Uk Kim, Woo Dae Jang, and Sang Yup Lee. Microbial production of multiple short-chain primary amines via retrobiosynthesis. Nature Communications ( https://www.nature.com/articles/s41467-020-20423-6)
-Profile
Distinguished Professor Sang Yup Lee
leesy@kaist.ac.kr
Metabolic &Biomolecular Engineering National Research Laboratory
http://mbel.kaist.ac.kr
Department of Chemical and Biomolecular Engineering
KAIST
2021.01.14 View 10277 -
A Comprehensive Review of Biosynthesis of Inorganic Nanomaterials Using Microorganisms and Bacteriophages
There are diverse methods for producing numerous inorganic nanomaterials involving many experimental variables. Among the numerous possible matches, finding the best pair for synthesizing in an environmentally friendly way has been a longstanding challenge for researchers and industries.
A KAIST bioprocess engineering research team led by Distinguished Professor Sang Yup Lee conducted a summary of 146 biosynthesized single and multi-element inorganic nanomaterials covering 55 elements in the periodic table synthesized using wild-type and genetically engineered microorganisms. Their research highlights the diverse applications of biogenic nanomaterials and gives strategies for improving the biosynthesis of nanomaterials in terms of their producibility, crystallinity, size, and shape.
The research team described a 10-step flow chart for developing the biosynthesis of inorganic nanomaterials using microorganisms and bacteriophages. The research was published at Nature Review Chemistry as a cover and hero paper on December 3.
“We suggest general strategies for microbial nanomaterial biosynthesis via a step-by-step flow chart and give our perspectives on the future of nanomaterial biosynthesis and applications. This flow chart will serve as a general guide for those wishing to prepare biosynthetic inorganic nanomaterials using microbial cells,” explained Dr.Yoojin Choi, a co-author of this research.
Most inorganic nanomaterials are produced using physical and chemical methods and biological synthesis has been gaining more and more attention. However, conventional synthesis processes have drawbacks in terms of high energy consumption and non-environmentally friendly processes. Meanwhile, microorganisms such as microalgae, yeasts, fungi, bacteria, and even viruses can be utilized as biofactories to produce single and multi-element inorganic nanomaterials under mild conditions.
After conducting a massive survey, the research team summed up that the development of genetically engineered microorganisms with increased inorganic-ion-binding affinity, inorganic-ion-reduction ability, and nanomaterial biosynthetic efficiency has enabled the synthesis of many inorganic nanomaterials.
Among the strategies, the team introduced their analysis of a Pourbaix diagram for controlling the size and morphology of a product. The research team said this Pourbaix diagram analysis can be widely employed for biosynthesizing new nanomaterials with industrial applications.Professor Sang Yup Lee added, “This research provides extensive information and perspectives on the biosynthesis of diverse inorganic nanomaterials using microorganisms and bacteriophages and their applications. We expect that biosynthetic inorganic nanomaterials will find more diverse and innovative applications across diverse fields of science and technology.”
Dr. Choi started this research in 2018 and her interview about completing this extensive research was featured in an article at Nature Career article on December 4.
-ProfileDistinguished Professor Sang Yup Lee leesy@kaist.ac.krMetabolic &Biomolecular Engineering National Research Laboratoryhttp://mbel.kaist.ac.krDepartment of Chemical and Biomolecular EngineeringKAIST
2020.12.07 View 8928 -
Three Professors Named to Highly Cited Researchers 2020 List
Distinguished Professor Sukbok Chang from the Department of Chemistry, Distinguished Professor Sang-Yup Lee from the Department of Chemical & Biomolecular Engineering, and Professor Jiyong Eom from the College of Business were named to Clarivate’s Highly Cited Researchers 2020 list.
Clarivate announced the researchers who rank in the top 1% of citations by field and publication year in the Web of Science citation index. A total of 6,167 researchers from more than 60 countries were listed this year and 37 Korean scholars made the list.
The methodology that determines the “Who’s Who” of influential researchers draws on data and analyses performed by bibliometric experts and data scientists at the Institute for Scientific Information at Clarivate. It also uses the tallies to identify the countries and research institutions where these scientific elite are based. More than 6,000 researchers from 21 fields in the sciences, social sciences, and cross field categories were selected based on the number of highly cited papers they produced over an 11-year period from January 2009 to December 2019.
Professor Chang made the list six years in a row, while Professor Lee made it for four consecutive years, and Professor Eom for the last two years. Professor Chang’s group (http://sbchang.kaist.ac.kr) investigates catalytic hydrocarbon functionalization. Professor Lee (http://mbel.kaist.ac.kr) is a pioneering scholar in the field of metabolic engineering, systems, and synthetic biology. Professor Eom’s (https://kaistceps.quv.kr) research extends to energy and environmental economics and management, energy big data, and green information systems.
2020.11.30 View 7772 -
E. coli Engineered to Grow on CO₂ and Formic Acid as Sole Carbon Sources
- An E. coli strain that can grow to a relatively high cell density solely on CO₂ and formic acid was developed by employing metabolic engineering. -
Most biorefinery processes have relied on the use of biomass as a raw material for the production of chemicals and materials. Even though the use of CO₂ as a carbon source in biorefineries is desirable, it has not been possible to make common microbial strains such as E. coli grow on CO₂.
Now, a metabolic engineering research group at KAIST has developed a strategy to grow an E. coli strain to higher cell density solely on CO₂ and formic acid. Formic acid is a one carbon carboxylic acid, and can be easily produced from CO₂ using a variety of methods. Since it is easier to store and transport than CO₂, formic acid can be considered a good liquid-form alternative of CO₂.
With support from the C1 Gas Refinery R&D Center and the Ministry of Science and ICT, a research team led by Distinguished Professor Sang Yup Lee stepped up their work to develop an engineered E. coli strain capable of growing up to 11-fold higher cell density than those previously reported, using CO₂ and formic acid as sole carbon sources. This work was published in Nature Microbiology on September 28.
Despite the recent reports by several research groups on the development of E. coli strains capable of growing on CO₂ and formic acid, the maximum cell growth remained too low (optical density of around 1) and thus the production of chemicals from CO₂ and formic acid has been far from realized.
The team previously reported the reconstruction of the tetrahydrofolate cycle and reverse glycine cleavage pathway to construct an engineered E. coli strain that can sustain growth on CO₂ and formic acid. To further enhance the growth, the research team introduced the previously designed synthetic CO₂ and formic acid assimilation pathway, and two formate dehydrogenases.
Metabolic fluxes were also fine-tuned, the gluconeogenic flux enhanced, and the levels of cytochrome bo3 and bd-I ubiquinol oxidase for ATP generation were optimized. This engineered E. coli strain was able to grow to a relatively high OD600 of 7~11, showing promise as a platform strain growing solely on CO₂ and formic acid.
Professor Lee said, “We engineered E. coli that can grow to a higher cell density only using CO₂ and formic acid. We think that this is an important step forward, but this is not the end. The engineered strain we developed still needs further engineering so that it can grow faster to a much higher density.”
Professor Lee’s team is continuing to develop such a strain. “In the future, we would be delighted to see the production of chemicals from an engineered E. coli strain using CO₂ and formic acid as sole carbon sources,” he added.
-Profile:Distinguished Professor Sang Yup Leehttp://mbel.kaist.ac.krDepartment of Chemical and Biomolecular EngineeringKAIST
2020.09.29 View 9561 -
Biomarker Predicts Who Will Have Severe COVID-19
- Airway cell analyses showing an activated immune axis could pinpoint the COVID-19 patients who will most benefit from targeted therapies.-
KAIST researchers have identified key markers that could help pinpoint patients who are bound to get a severe reaction to COVID-19 infection. This would help doctors provide the right treatments at the right time, potentially saving lives. The findings were published in the journal Frontiers in Immunology on August 28.
People’s immune systems react differently to infection with SARS-CoV-2, the virus that causes COVID-19, ranging from mild to severe, life-threatening responses.
To understand the differences in responses, Professor Heung Kyu Lee and PhD candidate Jang Hyun Park from the Graduate School of Medical Science and Engineering at KAIST analysed ribonucleic acid (RNA) sequencing data extracted from individual airway cells of healthy controls and of mildly and severely ill patients with COVID-19. The data was available in a public database previously published by a group of Chinese researchers.
“Our analyses identified an association between immune cells called neutrophils and special cell receptors that bind to the steroid hormone glucocorticoid,” Professor Lee explained. “This finding could be used as a biomarker for predicting disease severity in patients and thus selecting a targeted therapy that can help treat them at an appropriate time,” he added.
Severe illness in COVID-19 is associated with an exaggerated immune response that leads to excessive airway-damaging inflammation. This condition, known as acute respiratory distress syndrome (ARDS), accounts for 70% of deaths in fatal COVID-19 infections.
Scientists already know that this excessive inflammation involves heightened neutrophil recruitment to the airways, but the detailed mechanisms of this reaction are still unclear.
Lee and Park’s analyses found that a group of immune cells called myeloid cells produced excess amounts of neutrophil-recruiting chemicals in severely ill patients, including a cytokine called tumour necrosis factor (TNF) and a chemokine called CXCL8.
Further RNA analyses of neutrophils in severely ill patients showed they were less able to recruit very important T cells needed for attacking the virus. At the same time, the neutrophils produced too many extracellular molecules that normally trap pathogens, but damage airway cells when produced in excess.
The researchers additionally found that the airway cells in severely ill patients were not expressing enough glucocorticoid receptors. This was correlated with increased CXCL8 expression and neutrophil recruitment.
Glucocorticoids, like the well-known drug dexamethasone, are anti-inflammatory agents that could play a role in treating COVID-19. However, using them in early or mild forms of the infection could suppress the necessary immune reactions to combat the virus. But if airway damage has already happened in more severe cases, glucocorticoid treatment would be ineffective.
Knowing who to give this treatment to and when is really important. COVID-19 patients showing reduced glucocorticoid receptor expression, increased CXCL8 expression, and excess neutrophil recruitment to the airways could benefit from treatment with glucocorticoids to prevent airway damage. Further research is needed, however, to confirm the relationship between glucocorticoids and neutrophil inflammation at the protein level.
“Our study could serve as a springboard towards more accurate and reliable COVID-19 treatments,” Professor Lee said.
This work was supported by the National Research Foundation of Korea, and Mobile Clinic Module Project funded by KAIST.
Figure. Low glucocorticoid receptor (GR) expression led to excessive inflammation and lung damage by neutrophils through enhancing the expression of CXCL8 and other cytokines.
Image credit: Professor Heung Kyu Lee, KAIST. Created with Biorender.com.
Image usage restrictions: News organizations may use or redistribute these figures and image, with proper attribution, as part of news coverage of this paper only.
-Publication:
Jang Hyun Park, and Heung Kyu Lee. (2020). Re-analysis of Single Cell Transcriptome Reveals That the NR3C1-CXCL8-Neutrophil Axis Determines the Severity of COVID-19. Frontiers in Immunology, Available online at https://doi.org/10.3389/fimmu.2020.02145
-Profile: Heung Kyu Lee
Associate Professor
heungkyu.lee@kaist.ac.kr
https://www.heungkyulee.kaist.ac.kr/
Laboratory of Host Defenses
Graduate School of Medical Science and Engineering (GSMSE)
The Center for Epidemic Preparedness at KAIST Institute
http://kaist.ac.kr
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, Republic of Korea
Profile: Jang Hyun Park
PhD Candidate
janghyun.park@kaist.ac.kr
GSMSE, KAIST
2020.09.17 View 13382