holotomography
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KAIST Succeeds in the Real-time Observation of Organoids using Holotomography
Organoids, which are 3D miniature organs that mimic the structure and function of human organs, play an essential role in disease research and drug development. A Korean research team has overcome the limitations of existing imaging technologies, succeeding in the real-time, high-resolution observation of living organoids.
KAIST (represented by President Kwang Hyung Lee) announced on the 14th of October that Professor YongKeun Park’s research team from the Department of Physics, in collaboration with the Genome Editing Research Center (Director Bon-Kyoung Koo) of the Institute for Basic Science (IBS President Do-Young Noh) and Tomocube Inc., has developed an imaging technology using holotomography to observe live, small intestinal organoids in real time at a high resolution.
Existing imaging techniques have struggled to observe living organoids in high resolution over extended periods and often required additional treatments like fluorescent staining.
< Figure 1. Overview of the low-coherence HT workflow. Using holotomography, 3D morphological restoration and quantitative analysis of organoids can be performed. In order to improve the limited field of view, which is a limitation of the microscope, our research team utilized a large-area field of view combination algorithm and made a 3D restoration by acquiring multi-focus holographic images for 3D measurements. After that, the organoids were compartmentalized to divide the parts necessary for analysis and quantitatively evaluated the protein concentration measurable from the refractive index and the survival rate of the organoids. >
The research team introduced holotomography technology to address these issues, which provides high-resolution images without the need for fluorescent staining and allows for the long-term observation of dynamic changes in real time without causing cell damage.
The team validated this technology using small intestinal organoids from experimental mice and were able to observe various cell structures inside the organoids in detail. They also captured dynamic changes such as growth processes, cell division, and cell death in real time using holotomography.
Additionally, the technology allowed for the precise analysis of the organoids' responses to drug treatments, verifying the survival of the cells.
The researchers believe that this breakthrough will open new horizons in organoid research, enabling the greater utilization of organoids in drug development, personalized medicine, and regenerative medicine.
Future research is expected to more accurately replicate the in vivo environment of organoids, contributing significantly to a more detailed understanding of various life phenomena at the cellular level through more precise 3D imaging.
< Figure 2. Real-time organoid morphology analysis. Using holotomography, it is possible to observe the lumen and villus development process of intestinal organoids in real time, which was difficult to observe with a conventional microscope. In addition, various information about intestinal organoids can be obtained by quantifying the size and protein amount of intestinal organoids through image analysis. >
Dr. Mahn Jae Lee, a graduate of KAIST's Graduate School of Medical Science and Engineering, currently at Chungnam National University Hospital and the first author of the paper, commented, "This research represents a new imaging technology that surpasses previous limitations and is expected to make a major contribution to disease modeling, personalized treatments, and drug development research using organoids."
The research results were published online in the international journal Experimental & Molecular Medicine on October 1, 2024, and the technology has been recognized for its applicability in various fields of life sciences. (Paper title: “Long-term three-dimensional high-resolution imaging of live unlabeled small intestinal organoids via low-coherence holotomography”)
This research was supported by the National Research Foundation of Korea, KAIST Institutes, and the Institute for Basic Science.
2024.10.14 View 868 -
KAIST presents strategies for Holotomography in advanced bio research
Measuring and analyzing three-dimensional (3D) images of live cells and tissues is considered crucial in advanced fields of biology and medicine. Organoids, which are 3D structures that mimic organs, are particular examples that significantly benefits 3D live imaging. Organoids provide effective alternatives to animal testing in the drug development processes, and can rapidly determine personalized medicine. On the other hand, active researches are ongoing to utilize organoids for organ replacement.
< Figure 1. Schematic illustration of holotomography compared to X-ray CT. Similar to CT, they share the commonality of measuring the optical properties of an unlabeled specimen in three dimensions. Instead of X-rays, holotomography irradiates light in the visible range, and provides refractive index measurements of transparent specimens rather than absorptivity. While CT obtains three-dimensional information only through mechanical rotation of the irradiating light, holotomography can replace this by applying wavefront control technology in the visible range. >
Organelle-level observation of 3D biological specimens such as organoids and stem cell colonies without staining or preprocessing holds significant implications for both innovating basic research and bioindustrial applications related to regenerative medicine and bioindustrial applications.
Holotomography (HT) is a 3D optical microscopy that implements 3D reconstruction analogous to that of X-ray computed tomography (CT). Although HT and CT share a similar theoretical background, HT facilitates high-resolution examination inside cells and tissues, instead of the human body. HT obtains 3D images of cells and tissues at the organelle level without chemical or genetic labeling, thus overcomes various challenges of existing methods in bio research and industry. Its potential is highlighted in research fields where sample physiology must not be disrupted, such as regenerative medicine, personalized medicine, and infertility treatment.
< Figure 2. Label-free 3D imaging of diverse live cells. Time-lapse image of Hep3B cells illustrating subcellular morphology changes upon H2O2 treatment, followed by cellular recovery after returning to the regular cell culture medium. >
This paper introduces the advantages and broad applicability of HT to biomedical researchers, while presenting an overview of principles and future technical challenges to optical researchers. It showcases various cases of applying HT in studies such as 3D biology, regenerative medicine, and cancer research, as well as suggesting future optical development. Also, it categorizes HT based on the light source, to describe the principles, limitations, and improvements of each category in detail. Particularly, the paper addresses strategies for deepening cell and organoid studies by introducing artificial intelligence (AI) to HT.
Due to its potential to drive advanced bioindustry, HT is attracting interest and investment from universities and corporates worldwide. The KAIST research team has been leading this international field by developing core technologies and carrying out key application researches throughout the last decade.
< Figure 3. Various types of cells and organelles that make up the imaging barrier of a living intestinal organoid can be observed using holotomography. >
This paper, co-authored by Dr. Geon Kim from KAIST Research Center for Natural Sciences, Professor Ki-Jun Yoon's team from the Department of Biological Sciences, Director Bon-Kyoung Koo's team from the Institute for Basic Science (IBS) Center for Genome Engineering, and Dr. Seongsoo Lee's team from the Korea Basic Science Institute (KBSI), was published in 'Nature Reviews Methods Primers' on the 25th of July. This research was supported by the Leader Grant and Basic Science Research Program of the National Research Foundation, the Hologram Core Technology Development Grant of the Ministry of Science and ICT, the Nano and Material Technology Development Project, and the Health and Medical R&D Project of the Ministry of Health and Welfare.
2024.07.30 View 1521 -
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 10306 -
Professor YongKeun Park Elected as a Fellow of the Optical Society
Professor YongKeun Park, from the Department of Physics at KAIST, was elected as a fellow member of the Optical Society (OSA) in Washington, D.C. on September 12. Fellow membership is given to members who have made a significant contribution to the advancement of optics and photonics.
Professor Park was recognized for his research on digital holography and wavefront control technology.
Professor Park has been producing outstanding research outcomes in the field of holographic technology and light scattering control since joining KAIST in 2010. In particular, he developed and commercialized technology for a holographic telescope. He applied it to various medical and biological research projects, leading the field worldwide.
In the past, cells needed to be dyed with fluorescent materials to capture a 3-D image. However, Professor Park’s holotomography (HT) technology can capture 3-D images of living cells and tissues in real time without color dyeing. This technology allows diversified research in the biological and medical field.
Professor Park established a company, Tomocube, Inc. in 2015 to commercialize the technology. In 2016, he received funding from SoftBank Ventures and Hanmi Pharmaceutical. Currently, major institutes, including MIT, the University of Pittsburgh, the German Cancer Research Center, and Seoul National University Hospital are using his equipment.
Recently, Professor Park and his team developed technology based on light scattering measurements. With this technology, they established a company called The Wave Talk and received funding from various organizations, such as NAVER. Its first product is about to be released.
Professor Park said, “I am glad to become a fellow member based on the research outcomes I produced since I was appointed as a professor at KAIST. I would like to thank the excellent researchers as well as the school for its support. I will devote myself to continuously producing novel outcomes in both basic and applied fields.”
Professor Park has published nearly 100 papers in renowned journals including Nature Photonics, Nature Communications, Science Advances, and Physical Review Letters.
2017.10.18 View 10138