1
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Polak R, Zhang ET, Kuo CJ. Cancer organoids 2.0: modelling the complexity of the tumour immune microenvironment. Nat Rev Cancer 2024; 24:523-539. [PMID: 38977835 DOI: 10.1038/s41568-024-00706-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/09/2024] [Indexed: 07/10/2024]
Abstract
The development of neoplasia involves a complex and continuous interplay between malignantly transformed cells and the tumour microenvironment (TME). Cancer immunotherapies targeting the immune TME have been increasingly validated in clinical trials but response rates vary substantially between tumour histologies and are often transient, idiosyncratic and confounded by resistance. Faithful experimental models of the patient-specific tumour immune microenvironment, capable of recapitulating tumour biology and immunotherapy effects, would greatly improve patient selection, target identification and definition of resistance mechanisms for immuno-oncology therapeutics. In this Review, we discuss currently available and rapidly evolving 3D tumour organoid models that capture important immune features of the TME. We highlight diverse opportunities for organoid-based investigations of tumour immunity, drug development and precision medicine.
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Affiliation(s)
- Roel Polak
- Department of Medicine, Division of Hematology, Stanford University School of Medicine, Stanford, CA, USA
- Princess Máxima Center for Pediatric Oncology, Utrecht, Netherlands
| | - Elisa T Zhang
- Department of Medicine, Division of Hematology, Stanford University School of Medicine, Stanford, CA, USA
| | - Calvin J Kuo
- Department of Medicine, Division of Hematology, Stanford University School of Medicine, Stanford, CA, USA.
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2
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Huang Y, Liu T, Huang Q, Wang Y. From Organ-on-a-Chip to Human-on-a-Chip: A Review of Research Progress and Latest Applications. ACS Sens 2024; 9:3466-3488. [PMID: 38991227 DOI: 10.1021/acssensors.4c00004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
Abstract
Organ-on-a-Chip (OOC) technology, which emulates the physiological environment and functionality of human organs on a microfluidic chip, is undergoing significant technological advancements. Despite its rapid evolution, this technology is also facing notable challenges, such as the lack of vascularization, the development of multiorgan-on-a-chip systems, and the replication of the human body on a single chip. The progress of microfluidic technology has played a crucial role in steering OOC toward mimicking the human microenvironment, including vascularization, microenvironment replication, and the development of multiorgan microphysiological systems. Additionally, advancements in detection, analysis, and organoid imaging technologies have enhanced the functionality and efficiency of Organs-on-Chips (OOCs). In particular, the integration of artificial intelligence has revolutionized organoid imaging, significantly enhancing high-throughput drug screening. Consequently, this review covers the research progress of OOC toward Human-on-a-chip, the integration of sensors in OOCs, and the latest applications of organoid imaging technologies in the biomedical field.
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Affiliation(s)
- Yisha Huang
- Frontiers Medical Center, Tianfu Jincheng Laboratory, Chengdu, Sichuan 610212, China
| | - Tong Liu
- Department of Respiratory and Critical Care Medicine, Targeted Tracer Research and Development Laboratory, Institute of Respiratory Health, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Qi Huang
- School of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
| | - Yuxi Wang
- Department of Respiratory and Critical Care Medicine, Targeted Tracer Research and Development Laboratory, Institute of Respiratory Health, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
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3
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Mao Y, Hu H. Establishment of Advanced Tumor Organoids with Emerging Innovative Technologies. Cancer Lett 2024:217122. [PMID: 39029781 DOI: 10.1016/j.canlet.2024.217122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 06/21/2024] [Accepted: 07/12/2024] [Indexed: 07/21/2024]
Abstract
Tumor organoids have emerged as a crucial preclinical model for multiple cancer research. Their high establishment rates, stability, and ability to replicate key biological features of original tumor cells in vivo render them invaluable for exploring tumor molecular mechanisms, discovering potential anti-tumor drugs, and predicting clinical drug efficacy. Here, we review the establishment of tumor organoid models and provide an extensive overview of organoid culturing strategies. We also emphasize the significance of integrating cellular components of the tumor microenvironment and physicochemical factors in the organoid culturing system, highlighting the importance of artificial intelligence technology in advancing organoid construction. Moreover, we summarize recent advancements in utilizing organoid systems for novel anti-cancer drug screening and discuss promising trends for enhancing advanced organoids in next-generation disease modeling.
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Affiliation(s)
- Yunuo Mao
- The Key Laboratory of Experimental Teratology, Ministry of Education, Department of Systems Biomedicine, School of Basic Medical Sciences, Shandong University, Jinan, 250012, P. R. China
| | - Huili Hu
- The Key Laboratory of Experimental Teratology, Ministry of Education, Department of Systems Biomedicine, School of Basic Medical Sciences, Shandong University, Jinan, 250012, P. R. China.
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4
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Katoh TA, Fukai YT, Ishibashi T. Optical microscopic imaging, manipulation, and analysis methods for morphogenesis research. Microscopy (Oxf) 2024; 73:226-242. [PMID: 38102756 PMCID: PMC11154147 DOI: 10.1093/jmicro/dfad059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 11/20/2023] [Accepted: 03/22/2024] [Indexed: 12/17/2023] Open
Abstract
Morphogenesis is a developmental process of organisms being shaped through complex and cooperative cellular movements. To understand the interplay between genetic programs and the resulting multicellular morphogenesis, it is essential to characterize the morphologies and dynamics at the single-cell level and to understand how physical forces serve as both signaling components and driving forces of tissue deformations. In recent years, advances in microscopy techniques have led to improvements in imaging speed, resolution and depth. Concurrently, the development of various software packages has supported large-scale, analyses of challenging images at the single-cell resolution. While these tools have enhanced our ability to examine dynamics of cells and mechanical processes during morphogenesis, their effective integration requires specialized expertise. With this background, this review provides a practical overview of those techniques. First, we introduce microscopic techniques for multicellular imaging and image analysis software tools with a focus on cell segmentation and tracking. Second, we provide an overview of cutting-edge techniques for mechanical manipulation of cells and tissues. Finally, we introduce recent findings on morphogenetic mechanisms and mechanosensations that have been achieved by effectively combining microscopy, image analysis tools and mechanical manipulation techniques.
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Affiliation(s)
- Takanobu A Katoh
- Department of Cell Biology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yohsuke T Fukai
- Nonequilibrium Physics of Living Matter RIKEN Hakubi Research Team, RIKEN Center for Biosystems Dynamics Research, 2-2-3 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Tomoki Ishibashi
- Laboratory for Physical Biology, RIKEN Center for Biosystems Dynamics Research, 2-2-3 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
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5
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Brückner DB, Tkačik G. Information content and optimization of self-organized developmental systems. Proc Natl Acad Sci U S A 2024; 121:e2322326121. [PMID: 38819997 PMCID: PMC11161761 DOI: 10.1073/pnas.2322326121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 04/27/2024] [Indexed: 06/02/2024] Open
Abstract
A key feature of many developmental systems is their ability to self-organize spatial patterns of functionally distinct cell fates. To ensure proper biological function, such patterns must be established reproducibly, by controlling and even harnessing intrinsic and extrinsic fluctuations. While the relevant molecular processes are increasingly well understood, we lack a principled framework to quantify the performance of such stochastic self-organizing systems. To that end, we introduce an information-theoretic measure for self-organized fate specification during embryonic development. We show that the proposed measure assesses the total information content of fate patterns and decomposes it into interpretable contributions corresponding to the positional and correlational information. By optimizing the proposed measure, our framework provides a normative theory for developmental circuits, which we demonstrate on lateral inhibition, cell type proportioning, and reaction-diffusion models of self-organization. This paves a way toward a classification of developmental systems based on a common information-theoretic language, thereby organizing the zoo of implicated chemical and mechanical signaling processes.
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Affiliation(s)
- David B. Brückner
- Institute of Science and Technology Austria, AT-3400Klosterneuburg, Austria
| | - Gašper Tkačik
- Institute of Science and Technology Austria, AT-3400Klosterneuburg, Austria
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6
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Tang Q, Ratnayake R, Seabra G, Jiang Z, Fang R, Cui L, Ding Y, Kahveci T, Bian J, Li C, Luesch H, Li Y. Morphological profiling for drug discovery in the era of deep learning. Brief Bioinform 2024; 25:bbae284. [PMID: 38886164 PMCID: PMC11182685 DOI: 10.1093/bib/bbae284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Revised: 05/13/2024] [Accepted: 06/03/2024] [Indexed: 06/20/2024] Open
Abstract
Morphological profiling is a valuable tool in phenotypic drug discovery. The advent of high-throughput automated imaging has enabled the capturing of a wide range of morphological features of cells or organisms in response to perturbations at the single-cell resolution. Concurrently, significant advances in machine learning and deep learning, especially in computer vision, have led to substantial improvements in analyzing large-scale high-content images at high throughput. These efforts have facilitated understanding of compound mechanism of action, drug repurposing, characterization of cell morphodynamics under perturbation, and ultimately contributing to the development of novel therapeutics. In this review, we provide a comprehensive overview of the recent advances in the field of morphological profiling. We summarize the image profiling analysis workflow, survey a broad spectrum of analysis strategies encompassing feature engineering- and deep learning-based approaches, and introduce publicly available benchmark datasets. We place a particular emphasis on the application of deep learning in this pipeline, covering cell segmentation, image representation learning, and multimodal learning. Additionally, we illuminate the application of morphological profiling in phenotypic drug discovery and highlight potential challenges and opportunities in this field.
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Affiliation(s)
- Qiaosi Tang
- Calico Life Sciences, South San Francisco, CA 94080, United States
| | - Ranjala Ratnayake
- Department of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, United States
| | - Gustavo Seabra
- Department of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, United States
| | - Zhe Jiang
- Department of Computer & Information Science & Engineering, University of Florida, Gainesville, FL 32611, United States
| | - Ruogu Fang
- Department of Computer & Information Science & Engineering, University of Florida, Gainesville, FL 32611, United States
- J. Crayton Pruitt Family Department of Biomedical Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL 32611, United States
| | - Lina Cui
- Department of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, United States
| | - Yousong Ding
- Department of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, United States
| | - Tamer Kahveci
- Department of Computer & Information Science & Engineering, University of Florida, Gainesville, FL 32611, United States
| | - Jiang Bian
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32611, United States
| | - Chenglong Li
- Department of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, United States
| | - Hendrik Luesch
- Department of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, United States
| | - Yanjun Li
- Department of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, United States
- Department of Computer & Information Science & Engineering, University of Florida, Gainesville, FL 32611, United States
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7
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Maharjan S, Ma C, Singh B, Kang H, Orive G, Yao J, Shrike Zhang Y. Advanced 3D imaging and organoid bioprinting for biomedical research and therapeutic applications. Adv Drug Deliv Rev 2024; 208:115237. [PMID: 38447931 PMCID: PMC11031334 DOI: 10.1016/j.addr.2024.115237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 01/15/2024] [Accepted: 02/27/2024] [Indexed: 03/08/2024]
Abstract
Organoid cultures offer a valuable platform for studying organ-level biology, allowing for a closer mimicry of human physiology compared to traditional two-dimensional cell culture systems or non-primate animal models. While many organoid cultures use cell aggregates or decellularized extracellular matrices as scaffolds, they often lack precise biochemical and biophysical microenvironments. In contrast, three-dimensional (3D) bioprinting allows precise placement of organoids or spheroids, providing enhanced spatial control and facilitating the direct fusion for the formation of large-scale functional tissues in vitro. In addition, 3D bioprinting enables fine tuning of biochemical and biophysical cues to support organoid development and maturation. With advances in the organoid technology and its potential applications across diverse research fields such as cell biology, developmental biology, disease pathology, precision medicine, drug toxicology, and tissue engineering, organoid imaging has become a crucial aspect of physiological and pathological studies. This review highlights the recent advancements in imaging technologies that have significantly contributed to organoid research. Additionally, we discuss various bioprinting techniques, emphasizing their applications in organoid bioprinting. Integrating 3D imaging tools into a bioprinting platform allows real-time visualization while facilitating quality control, optimization, and comprehensive bioprinting assessment. Similarly, combining imaging technologies with organoid bioprinting can provide valuable insights into tissue formation, maturation, functions, and therapeutic responses. This approach not only improves the reproducibility of physiologically relevant tissues but also enhances understanding of complex biological processes. Thus, careful selection of bioprinting modalities, coupled with appropriate imaging techniques, holds the potential to create a versatile platform capable of addressing existing challenges and harnessing opportunities in these rapidly evolving fields.
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Affiliation(s)
- Sushila Maharjan
- Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA 02139, USA
| | - Chenshuo Ma
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Bibhor Singh
- Winthrop L. Chenery Upper Elementary School, Belmont, MA 02478, USA
| | - Heemin Kang
- Department of Materials Science and Engineering, Korea University, Seoul 02841, Republic of Korea; College of Medicine, Korea University, Seoul 02841, Republic of Korea
| | - Gorka Orive
- NanoBioCel Research Group, School of Pharmacy, University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain; Bioaraba, NanoBioCel Research Group, Vitoria-Gasteiz, Spain; Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN). Vitoria-Gasteiz, Spain; University Institute for Regenerative Medicine and Oral Implantology - UIRMI (UPV/EHU-Fundación Eduardo Anitua), Vitoria, 01007, Spain; Singapore Eye Research Institute, The Academia, 20 College Road, Discovery Tower, Singapore 169856, Singapore
| | - Junjie Yao
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.
| | - Yu Shrike Zhang
- Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA 02139, USA.
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8
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Moos F, Suppinger S, de Medeiros G, Oost KC, Boni A, Rémy C, Weevers SL, Tsiairis C, Strnad P, Liberali P. Open-top multisample dual-view light-sheet microscope for live imaging of large multicellular systems. Nat Methods 2024; 21:798-803. [PMID: 38509326 PMCID: PMC11093739 DOI: 10.1038/s41592-024-02213-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 02/15/2024] [Indexed: 03/22/2024]
Abstract
Multicellular systems grow over the course of weeks from single cells to tissues or even full organisms, making live imaging challenging. To bridge spatiotemporal scales, we present an open-top dual-view and dual-illumination light-sheet microscope dedicated to live imaging of large specimens at single-cell resolution. The configuration of objectives together with a customizable multiwell mounting system combines dual view with high-throughput multiposition imaging. We use this microscope to image a wide variety of samples and highlight its capabilities to gain quantitative single-cell information in large specimens such as mature intestinal organoids and gastruloids.
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Affiliation(s)
- Franziska Moos
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Simon Suppinger
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Gustavo de Medeiros
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- Viventis Microscopy Sàrl, Lausanne, Switzerland
| | | | - Andrea Boni
- Viventis Microscopy Sàrl, Lausanne, Switzerland
| | | | - Sera Lotte Weevers
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Charisios Tsiairis
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Petr Strnad
- Viventis Microscopy Sàrl, Lausanne, Switzerland.
| | - Prisca Liberali
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
- University of Basel, Basel, Switzerland.
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Yu T, Yang Q, Peng B, Gu Z, Zhu D. Vascularized organoid-on-a-chip: design, imaging, and analysis. Angiogenesis 2024; 27:147-172. [PMID: 38409567 DOI: 10.1007/s10456-024-09905-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 01/11/2024] [Indexed: 02/28/2024]
Abstract
Vascularized organoid-on-a-chip (VOoC) models achieve substance exchange in deep layers of organoids and provide a more physiologically relevant system in vitro. Common designs for VOoC primarily involve two categories: self-assembly of endothelial cells (ECs) to form microvessels and pre-patterned vessel lumens, both of which include the hydrogel region for EC growth and allow for controlled fluid perfusion on the chip. Characterizing the vasculature of VOoC often relies on high-resolution microscopic imaging. However, the high scattering of turbid tissues can limit optical imaging depth. To overcome this limitation, tissue optical clearing (TOC) techniques have emerged, allowing for 3D visualization of VOoC in conjunction with optical imaging techniques. The acquisition of large-scale imaging data, coupled with high-resolution imaging in whole-mount preparations, necessitates the development of highly efficient analysis methods. In this review, we provide an overview of the chip designs and culturing strategies employed for VOoC, as well as the applicable optical imaging and TOC methods. Furthermore, we summarize the vascular analysis techniques employed in VOoC, including deep learning. Finally, we discuss the existing challenges in VOoC and vascular analysis methods and provide an outlook for future development.
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Affiliation(s)
- Tingting Yu
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
- Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Qihang Yang
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
- Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Bo Peng
- Frontiers Science Center for Flexible Electronics, Xi'an Institute of Flexible Electronics (IFE) and Xi'an Institute of Biomedical Materials & Engineering, Northwestern Polytechnical University, Xi'an, Shanxi, 710072, China
| | - Zhongze Gu
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu, 210096, China
- Institute of Biomaterials and Medical Devices, Southeast University, Suzhou, Jiangsu, 215163, China
| | - Dan Zhu
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
- Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
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Park S, Cho SW. Bioengineering toolkits for potentiating organoid therapeutics. Adv Drug Deliv Rev 2024; 208:115238. [PMID: 38447933 DOI: 10.1016/j.addr.2024.115238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 01/28/2024] [Accepted: 02/27/2024] [Indexed: 03/08/2024]
Abstract
Organoids are three-dimensional, multicellular constructs that recapitulate the structural and functional features of specific organs. Because of these characteristics, organoids have been widely applied in biomedical research in recent decades. Remarkable advancements in organoid technology have positioned them as promising candidates for regenerative medicine. However, current organoids still have limitations, such as the absence of internal vasculature, limited functionality, and a small size that is not commensurate with that of actual organs. These limitations hinder their survival and regenerative effects after transplantation. Another significant concern is the reliance on mouse tumor-derived matrix in organoid culture, which is unsuitable for clinical translation due to its tumor origin and safety issues. Therefore, our aim is to describe engineering strategies and alternative biocompatible materials that can facilitate the practical applications of organoids in regenerative medicine. Furthermore, we highlight meaningful progress in organoid transplantation, with a particular emphasis on the functional restoration of various organs.
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Affiliation(s)
- Sewon Park
- Department of Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
| | - Seung-Woo Cho
- Department of Biotechnology, Yonsei University, Seoul 03722, Republic of Korea; Center for Nanomedicine, Institute for Basic Science (IBS), Seoul 03722, Republic of Korea; Graduate Program of Nano Biomedical Engineering (NanoBME), Advanced Science Institute, Yonsei University, Seoul 03722, Republic of Korea.
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11
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Xie S, Zhang S, de Medeiros G, Liberali P, Skotheim JM. The G1/S transition in mammalian stem cells in vivo is autonomously regulated by cell size. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.09.588781. [PMID: 38645246 PMCID: PMC11030448 DOI: 10.1101/2024.04.09.588781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Cell growth and division must be coordinated to maintain a stable cell size, but how this coordination is implemented in multicellular tissues remains unclear. In unicellular eukaryotes, autonomous cell size control mechanisms couple cell growth and division with little extracellular input. However, in multicellular tissues we do not know if autonomous cell size control mechanisms operate the same way or whether cell growth and cell cycle progression are separately controlled by cell-extrinsic signals. Here, we address this question by tracking single epidermal stem cells growing in adult mice. We find that a cell-autonomous size control mechanism, dependent on the RB pathway, sets the timing of S phase entry based on the cell's current size. Cell-extrinsic variations in the cellular microenvironment affect cell growth rates but not this autonomous coupling. Our work reassesses long-standing models of cell cycle regulation within complex metazoan tissues and identifies cell-autonomous size control as a critical mechanism regulating cell divisions in vivo and thereby a major contributor to stem cell heterogeneity.
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12
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Wang J, Xu X, Ye H, Zhang X, Shi G. Interferometric modulation for generating extended light sheet: improving field of view. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:046501. [PMID: 38629030 PMCID: PMC11020319 DOI: 10.1117/1.jbo.29.4.046501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/20/2024] [Accepted: 03/27/2024] [Indexed: 04/19/2024]
Abstract
Significance Light-sheet fluorescence microscopy (LSFM) has emerged as a powerful and versatile imaging technique renowned for its remarkable features, including high-speed 3D tomography, minimal photobleaching, and low phototoxicity. The interference light-sheet fluorescence microscope, with its larger field of view (FOV) and more uniform axial resolution, possesses significant potential for a wide range of applications in biology and medicine. Aim The aim of this study is to investigate the interference behavior among multiple light sheets (LSs) in LSFM and optimize the FOV and resolution of the light-sheet fluorescence microscope. Approach We conducted a detailed investigation of the interference effects among LSs through theoretical derivation and numerical simulations, aiming to find optimal parameters. Subsequently, we constructed a customized system of multi-LSFM that incorporates both interference light sheets (ILS) and noninterference light-sheet configurations. We performed beam imaging and microsphere imaging tests to evaluate the FOV and axial resolution of these systems. Results Using our custom-designed light-sheet fluorescence microscope, we captured the intensity distribution profiles of both interference and noninterference light sheets (NILS). Additionally, we conducted imaging tests on microspheres to assess their imaging outcomes. The ILS not only exhibits a larger FOV compared to the NILS but also demonstrates a more uniform axial resolution. Conclusions By effectively modulating the interference among multiple LSs, it is possible to optimize the intensity distribution of the LSs, expand the FOV, and achieve a more uniform axial resolution.
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Affiliation(s)
- Jixiang Wang
- University of Science and Technology of China, School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, Hefei, China
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Xin Xu
- University of Science and Technology of China, School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, Hefei, China
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Hong Ye
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Xin Zhang
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Guohua Shi
- University of Science and Technology of China, School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, Hefei, China
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
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13
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Ko J, Hyung S, Cheong S, Chung Y, Li Jeon N. Revealing the clinical potential of high-resolution organoids. Adv Drug Deliv Rev 2024; 207:115202. [PMID: 38336091 DOI: 10.1016/j.addr.2024.115202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 01/01/2024] [Accepted: 02/02/2024] [Indexed: 02/12/2024]
Abstract
The symbiotic interplay of organoid technology and advanced imaging strategies yields innovative breakthroughs in research and clinical applications. Organoids, intricate three-dimensional cell cultures derived from pluripotent or adult stem/progenitor cells, have emerged as potent tools for in vitro modeling, reflecting in vivo organs and advancing our grasp of tissue physiology and disease. Concurrently, advanced imaging technologies such as confocal, light-sheet, and two-photon microscopy ignite fresh explorations, uncovering rich organoid information. Combined with advanced imaging technologies and the power of artificial intelligence, organoids provide new insights that bridge experimental models and real-world clinical scenarios. This review explores exemplary research that embodies this technological synergy and how organoids reshape personalized medicine and therapeutics.
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Affiliation(s)
- Jihoon Ko
- Department of BioNano Technology, Gachon University, Gyeonggi 13120, Republic of Korea
| | - Sujin Hyung
- Precision Medicine Research Institute, Samsung Medical Center, Seoul 08826, Republic of Korea; Division of Hematology-Oncology, Department of Medicine, Sungkyunkwan University, Samsung Medical Center, Seoul 08826, Republic of Korea
| | - Sunghun Cheong
- Interdisciplinary Program in Bioengineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Yoojin Chung
- Division of Computer Engineering, Hankuk University of Foreign Studies, Yongin 17035, Republic of Korea
| | - Noo Li Jeon
- Interdisciplinary Program in Bioengineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea; Department of Mechanical Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea; Institute of Advanced Machines and Design, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea; Qureator, Inc., San Diego, CA, USA.
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14
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Reynolds DE, Sun Y, Wang X, Vallapureddy P, Lim J, Pan M, Fernandez Del Castillo A, Carlson JCT, Sellmyer MA, Nasrallah M, Binder Z, O'Rourke DM, Ming G, Song H, Ko J. Live Organoid Cyclic Imaging. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2309289. [PMID: 38326078 PMCID: PMC11005682 DOI: 10.1002/advs.202309289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/07/2024] [Indexed: 02/09/2024]
Abstract
Organoids are becoming increasingly relevant in biology and medicine for their physiological complexity and accuracy in modeling human disease. To fully assess their biological profile while preserving their spatial information, spatiotemporal imaging tools are warranted. While previously developed imaging techniques, such as four-dimensional (4D) live imaging and light-sheet imaging have yielded important clinical insights, these technologies lack the combination of cyclic and multiplexed analysis. To address these challenges, bioorthogonal click chemistry is applied to display the first demonstration of multiplexed cyclic imaging of live and fixed patient-derived glioblastoma tumor organoids. This technology exploits bioorthogonal click chemistry to quench fluorescent signals from the surface and intracellular of labeled cells across multiple cycles, allowing for more accurate and efficient molecular profiling of their complex phenotypes. Herein, the versatility of this technology is demonstrated for the screening of glioblastoma markers in patient-derived human glioblastoma organoids while conserving their viability. It is anticipated that the findings and applications of this work can be broadly translated into investigating physiological developments in other organoid systems.
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Affiliation(s)
- David E. Reynolds
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Yusha Sun
- Department of NeuroscienceMahoney Institute for NeurosciencesPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Xin Wang
- Department of NeuroscienceMahoney Institute for NeurosciencesPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Phoebe Vallapureddy
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Jianhua Lim
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Menghan Pan
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Andres Fernandez Del Castillo
- Department of Biochemistry & Molecular BiophysicsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Jonathan C. T. Carlson
- Center for Systems BiologyMassachusetts General HospitalBostonMA02114USA
- Department of MedicineMassachusetts General HospitalHarvard Medical SchoolBostonMA02114USA
| | - Mark A. Sellmyer
- Department of RadiologyPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - MacLean Nasrallah
- GBM Translational Center of ExcellenceAbramson Cancer CenterUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Department of Pathology and Laboratory MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Zev Binder
- GBM Translational Center of ExcellenceAbramson Cancer CenterUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Center for Cellular ImmunotherapiesUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Department of NeurosurgeryPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Donald M. O'Rourke
- GBM Translational Center of ExcellenceAbramson Cancer CenterUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Center for Cellular ImmunotherapiesUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Department of NeurosurgeryPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Guo‐li Ming
- Department of NeuroscienceMahoney Institute for NeurosciencesPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Department of Cell and Developmental BiologyPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Department of PsychiatryPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Institute for Regenerative MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Hongjun Song
- Department of NeuroscienceMahoney Institute for NeurosciencesPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
- GBM Translational Center of ExcellenceAbramson Cancer CenterUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Department of Cell and Developmental BiologyPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Department of PsychiatryPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
- The Epigenetics InstitutePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Jina Ko
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Department of Pathology and Laboratory MedicineUniversity of PennsylvaniaPhiladelphiaPA19104USA
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15
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Soumier A, Lio G, Demily C. Current and future applications of light-sheet imaging for identifying molecular and developmental processes in autism spectrum disorders. Mol Psychiatry 2024:10.1038/s41380-024-02487-8. [PMID: 38443634 DOI: 10.1038/s41380-024-02487-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 02/09/2024] [Accepted: 02/13/2024] [Indexed: 03/07/2024]
Abstract
Autism spectrum disorder (ASD) is identified by a set of neurodevelopmental divergences that typically affect the social communication domain. ASD is also characterized by heterogeneous cognitive impairments and is associated with cooccurring physical and medical conditions. As behaviors emerge as the brain matures, it is particularly essential to identify any gaps in neurodevelopmental trajectories during early perinatal life. Here, we introduce the potential of light-sheet imaging for studying developmental biology and cross-scale interactions among genetic, cellular, molecular and macroscale levels of circuitry and connectivity. We first report the core principles of light-sheet imaging and the recent progress in studying brain development in preclinical animal models and human organoids. We also present studies using light-sheet imaging to understand the development and function of other organs, such as the skin and gastrointestinal tract. We also provide information on the potential of light-sheet imaging in preclinical drug development. Finally, we speculate on the translational benefits of light-sheet imaging for studying individual brain-body interactions in advancing ASD research and creating personalized interventions.
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Affiliation(s)
- Amelie Soumier
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France.
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France.
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France.
- University Claude Bernard Lyon 1, 43 boulevard du 11 Novembre 1918, 69622, Villeurbanne cedex, France.
| | - Guillaume Lio
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France
| | - Caroline Demily
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France
- University Claude Bernard Lyon 1, 43 boulevard du 11 Novembre 1918, 69622, Villeurbanne cedex, France
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16
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Cameron O, Neves JF, Gentleman E. Listen to Your Gut: Key Concepts for Bioengineering Advanced Models of the Intestine. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2302165. [PMID: 38009508 PMCID: PMC10837392 DOI: 10.1002/advs.202302165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 10/12/2023] [Indexed: 11/29/2023]
Abstract
The intestine performs functions central to human health by breaking down food and absorbing nutrients while maintaining a selective barrier against the intestinal microbiome. Key to this barrier function are the combined efforts of lumen-lining specialized intestinal epithelial cells, and the supportive underlying immune cell-rich stromal tissue. The discovery that the intestinal epithelium can be reproduced in vitro as intestinal organoids introduced a new way to understand intestinal development, homeostasis, and disease. However, organoids reflect the intestinal epithelium in isolation whereas the underlying tissue also contains myriad cell types and impressive chemical and structural complexity. This review dissects the cellular and matrix components of the intestine and discusses strategies to replicate them in vitro using principles drawing from bottom-up biological self-organization and top-down bioengineering. It also covers the cellular, biochemical and biophysical features of the intestinal microenvironment and how these can be replicated in vitro by combining strategies from organoid biology with materials science. Particularly accessible chemistries that mimic the native extracellular matrix are discussed, and bioengineering approaches that aim to overcome limitations in modelling the intestine are critically evaluated. Finally, the review considers how further advances may extend the applications of intestinal models and their suitability for clinical therapies.
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Affiliation(s)
- Oliver Cameron
- Centre for Craniofacial and Regenerative BiologyKing's College LondonLondonSE1 9RTUK
| | - Joana F. Neves
- Centre for Host‐Microbiome InteractionsKing's College LondonLondonSE1 9RTUK
| | - Eileen Gentleman
- Centre for Craniofacial and Regenerative BiologyKing's College LondonLondonSE1 9RTUK
- Department of Biomedical SciencesUniversity of LausanneLausanne1005Switzerland
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17
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Leng B, Jiang H, Wang B, Wang J, Luo G. Deep-Orga: An improved deep learning-based lightweight model for intestinal organoid detection. Comput Biol Med 2024; 169:107847. [PMID: 38141452 DOI: 10.1016/j.compbiomed.2023.107847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 12/03/2023] [Accepted: 12/11/2023] [Indexed: 12/25/2023]
Abstract
PROBLEM Organoids are 3D cultures that are commonly used for biological and medical research in vitro due to their functional and structural similarity to source organs. The development of organoids can be assessed by morphological tests. However, manual analysis of organoid morphology requires intensive labor from professionals and is prone to observer discrepancies. AIM Computer-assisted methods alleviate the pressure of manual labor, especially with the development of deep learning, the performance of morphological detection has been further improved. The aim of this paper is to automate the assessment of organoid morphology using deep learning techniques to reduce the labor pressure of professionals. METHODS Based on the lightweight model YOLOX, a lightweight intestinal organoid detection model named Deep-Orga is proposed. First, the performance of the Deep-Orga model is compared with other classical models on the intestinal organoids dataset. Then, ablation experiments are used to validate the improvement of the model detection performance by the improved module. Finally, Deep-Orga is compared with other methods. RESULTS Deep-Orga achieves optimal organoid detection with a partial increase in computational effort. Using Deep-Orga to replace the manual analysis process provides a new automated method for organoid morphology evaluation. CONCLUSION Deep-Orga proposed in this paper is able to accurately assess organoid development, effectively relieving the labor pressure of professionals and avoiding the subjectivity of assessment. This paper demonstrates the potential application of deep learning in the field of organoid morphology analysis.
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Affiliation(s)
- Bing Leng
- School of Biomedical Engineering (Suzhou), Division of Life Science and Medicine, University of Science and Technology of China, Hefei, 230026, People's Republic of China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, People's Republic of China
| | - Hao Jiang
- School of Biomedical Engineering (Suzhou), Division of Life Science and Medicine, University of Science and Technology of China, Hefei, 230026, People's Republic of China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, People's Republic of China
| | - Bidou Wang
- School of Biomedical Engineering (Suzhou), Division of Life Science and Medicine, University of Science and Technology of China, Hefei, 230026, People's Republic of China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, People's Republic of China
| | - Jinxian Wang
- School of Biomedical Engineering (Suzhou), Division of Life Science and Medicine, University of Science and Technology of China, Hefei, 230026, People's Republic of China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, People's Republic of China.
| | - Gangyin Luo
- School of Biomedical Engineering (Suzhou), Division of Life Science and Medicine, University of Science and Technology of China, Hefei, 230026, People's Republic of China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, People's Republic of China.
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18
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Schwayer C, Brückner DB. Connecting theory and experiment in cell and tissue mechanics. J Cell Sci 2023; 136:jcs261515. [PMID: 38149871 DOI: 10.1242/jcs.261515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2023] Open
Abstract
Understanding complex living systems, which are fundamentally constrained by physical phenomena, requires combining experimental data with theoretical physical and mathematical models. To develop such models, collaborations between experimental cell biologists and theoreticians are increasingly important but these two groups often face challenges achieving mutual understanding. To help navigate these challenges, this Perspective discusses different modelling approaches, including bottom-up hypothesis-driven and top-down data-driven models, and highlights their strengths and applications. Using cell mechanics as an example, we explore the integration of specific physical models with experimental data from the molecular, cellular and tissue level up to multiscale input. We also emphasize the importance of constraining model complexity and outline strategies for crosstalk between experimental design and model development. Furthermore, we highlight how physical models can provide conceptual insights and produce unifying and generalizable frameworks for biological phenomena. Overall, this Perspective aims to promote fruitful collaborations that advance our understanding of complex biological systems.
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Affiliation(s)
- Cornelia Schwayer
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland
| | - David B Brückner
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
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19
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Gall L, Duckworth C, Jardi F, Lammens L, Parker A, Bianco A, Kimko H, Pritchard DM, Pin C. Homeostasis, injury, and recovery dynamics at multiple scales in a self-organizing mouse intestinal crypt. eLife 2023; 12:e85478. [PMID: 38063302 PMCID: PMC10789491 DOI: 10.7554/elife.85478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 12/07/2023] [Indexed: 01/16/2024] Open
Abstract
The maintenance of the functional integrity of the intestinal epithelium requires a tight coordination between cell production, migration, and shedding along the crypt-villus axis. Dysregulation of these processes may result in loss of the intestinal barrier and disease. With the aim of generating a more complete and integrated understanding of how the epithelium maintains homeostasis and recovers after injury, we have built a multi-scale agent-based model (ABM) of the mouse intestinal epithelium. We demonstrate that stable, self-organizing behaviour in the crypt emerges from the dynamic interaction of multiple signalling pathways, such as Wnt, Notch, BMP, ZNRF3/RNF43, and YAP-Hippo pathways, which regulate proliferation and differentiation, respond to environmental mechanical cues, form feedback mechanisms, and modulate the dynamics of the cell cycle protein network. The model recapitulates the crypt phenotype reported after persistent stem cell ablation and after the inhibition of the CDK1 cycle protein. Moreover, we simulated 5-fluorouracil (5-FU)-induced toxicity at multiple scales starting from DNA and RNA damage, which disrupts the cell cycle, cell signalling, proliferation, differentiation, and migration and leads to loss of barrier integrity. During recovery, our in silico crypt regenerates its structure in a self-organizing, dynamic fashion driven by dedifferentiation and enhanced by negative feedback loops. Thus, the model enables the simulation of xenobiotic-, in particular chemotherapy-, induced mechanisms of intestinal toxicity and epithelial recovery. Overall, we present a systems model able to simulate the disruption of molecular events and its impact across multiple levels of epithelial organization and demonstrate its application to epithelial research and drug development.
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Affiliation(s)
- Louis Gall
- Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&D, AstraZenecaCambridgeUnited Kingdom
| | - Carrie Duckworth
- Institute of Systems, Molecular and Integrative Biology, University of LiverpoolLiverpoolUnited Kingdom
| | - Ferran Jardi
- Preclinical Sciences and Translational Safety, JanssenBeerseBelgium
| | - Lieve Lammens
- Preclinical Sciences and Translational Safety, JanssenBeerseBelgium
| | - Aimee Parker
- Gut Microbes and Health Programme, Quadram InstituteNorwichUnited Kingdom
| | - Ambra Bianco
- Clinical Pharmacology and Safety Sciences, AstraZenecaCambridgeUnited Kingdom
| | - Holly Kimko
- Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&D, AstraZenecaCambridgeUnited Kingdom
| | - David Mark Pritchard
- Institute of Systems, Molecular and Integrative Biology, University of LiverpoolLiverpoolUnited Kingdom
| | - Carmen Pin
- Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&D, AstraZenecaCambridgeUnited Kingdom
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20
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Affiliation(s)
- Bushra Raj
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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21
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Alieva M, Wezenaar AKL, Wehrens EJ, Rios AC. Bridging live-cell imaging and next-generation cancer treatment. Nat Rev Cancer 2023; 23:731-745. [PMID: 37704740 DOI: 10.1038/s41568-023-00610-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/25/2023] [Indexed: 09/15/2023]
Abstract
By providing spatial, molecular and morphological data over time, live-cell imaging can provide a deeper understanding of the cellular and signalling events that determine cancer response to treatment. Understanding this dynamic response has the potential to enhance clinical outcome by identifying biomarkers or actionable targets to improve therapeutic efficacy. Here, we review recent applications of live-cell imaging for uncovering both tumour heterogeneity in treatment response and the mode of action of cancer-targeting drugs. Given the increasing uses of T cell therapies, we discuss the unique opportunity of time-lapse imaging for capturing the interactivity and motility of immunotherapies. Although traditionally limited in the number of molecular features captured, novel developments in multidimensional imaging and multi-omics data integration offer strategies to connect single-cell dynamics to molecular phenotypes. We review the effect of these recent technological advances on our understanding of the cellular dynamics of tumour targeting and discuss their implication for next-generation precision medicine.
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Affiliation(s)
- Maria Alieva
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Instituto de Investigaciones Biomedicas Sols-Morreale (IIBM), CSIC-UAM, Madrid, Spain
| | - Amber K L Wezenaar
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | - Ellen J Wehrens
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
- Oncode Institute, Utrecht, The Netherlands.
| | - Anne C Rios
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
- Oncode Institute, Utrecht, The Netherlands.
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22
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Andrés-San Román JA, Gordillo-Vázquez C, Franco-Barranco D, Morato L, Fernández-Espartero CH, Baonza G, Tagua A, Vicente-Munuera P, Palacios AM, Gavilán MP, Martín-Belmonte F, Annese V, Gómez-Gálvez P, Arganda-Carreras I, Escudero LM. CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia. CELL REPORTS METHODS 2023; 3:100597. [PMID: 37751739 PMCID: PMC10626192 DOI: 10.1016/j.crmeth.2023.100597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 07/19/2023] [Accepted: 08/31/2023] [Indexed: 09/28/2023]
Abstract
Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues.
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Affiliation(s)
- Jesús A Andrés-San Román
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - Carmen Gordillo-Vázquez
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - Daniel Franco-Barranco
- Department of Computer Science and Artificial Intelligence, University of the Basque Country (UPV/EHU), 20018 San Sebastian, Spain; Donostia International Physics Center (DIPC), 20018 San Sebastian, Spain
| | - Laura Morato
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - Cecilia H Fernández-Espartero
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - Gabriel Baonza
- Program of Tissue and Organ Homeostasis, Centro de Biología Molecular Severo Ochoa, CSIC-UAM and Ramón & Cajal Health Research Institute (IRYCIS), Hospital Universitario Ramón y Cajal, 28034 Madrid, Spain
| | - Antonio Tagua
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | | | - Ana M Palacios
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - María P Gavilán
- Centro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), JA/CSIC/Universidad de Sevilla/Universidad Pablo de Olavide and Departamento de Citología e Histología Normal y Patológica, Facultad de Medicina, Universidad de Sevilla, 41009 Seville, Spain
| | - Fernando Martín-Belmonte
- Program of Tissue and Organ Homeostasis, Centro de Biología Molecular Severo Ochoa, CSIC-UAM and Ramón & Cajal Health Research Institute (IRYCIS), Hospital Universitario Ramón y Cajal, 28034 Madrid, Spain
| | - Valentina Annese
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - Pedro Gómez-Gálvez
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain; MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Avenue, Trumpington, Cambridge CB2 0QH, UK; Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EG, UK.
| | - Ignacio Arganda-Carreras
- Department of Computer Science and Artificial Intelligence, University of the Basque Country (UPV/EHU), 20018 San Sebastian, Spain; Donostia International Physics Center (DIPC), 20018 San Sebastian, Spain; Ikerbasque, Basque Foundation for Science, 48009 Bilbao, Spain; Biofisika Institute, 48940 Leioa, Spain.
| | - Luis M Escudero
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain; Biomedical Network Research Centre on Neurodegenerative Diseases (CIBERNED), 28029 Madrid, Spain.
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23
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Monfort T, Azzollini S, Brogard J, Clémençon M, Slembrouck-Brec A, Forster V, Picaud S, Goureau O, Reichman S, Thouvenin O, Grieve K. Dynamic full-field optical coherence tomography module adapted to commercial microscopes allows longitudinal in vitro cell culture study. Commun Biol 2023; 6:992. [PMID: 37770552 PMCID: PMC10539404 DOI: 10.1038/s42003-023-05378-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 09/20/2023] [Indexed: 09/30/2023] Open
Abstract
Dynamic full-field optical coherence tomography (D-FFOCT) has recently emerged as a label-free imaging tool, capable of resolving cell types and organelles within 3D live samples, whilst monitoring their activity at tens of milliseconds resolution. Here, a D-FFOCT module design is presented which can be coupled to a commercial microscope with a stage top incubator, allowing non-invasive label-free longitudinal imaging over periods of minutes to weeks on the same sample. Long term volumetric imaging on human induced pluripotent stem cell-derived retinal organoids is demonstrated, highlighting tissue and cell organization processes such as rosette formation and mitosis as well as cell shape and motility. Imaging on retinal explants highlights single 3D cone and rod structures. An optimal workflow for data acquisition, postprocessing and saving is demonstrated, resulting in a time gain factor of 10 compared to prior state of the art. Finally, a method to increase D-FFOCT signal-to-noise ratio is demonstrated, allowing rapid organoid screening.
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Affiliation(s)
- Tual Monfort
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
- CHNO des Quinze-Vingts, INSERM-DGOS CIC 1423, 28 rue de Charenton, F-75012, Paris, France
- Paris Eye Imaging Group, Quinze-Vingts National Eye Hospital, INSERM-DGOS, CIC 1423, 28 rue de Charenton, Paris, 75012, France
| | - Salvatore Azzollini
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
| | - Jérémy Brogard
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
| | - Marilou Clémençon
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
| | - Amélie Slembrouck-Brec
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
| | - Valerie Forster
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
| | - Serge Picaud
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
| | - Olivier Goureau
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
| | - Sacha Reichman
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
| | - Olivier Thouvenin
- Institut Langevin, ESPCI Paris, Université PSL, CNRS, 75005, Paris, France
| | - Kate Grieve
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France.
- CHNO des Quinze-Vingts, INSERM-DGOS CIC 1423, 28 rue de Charenton, F-75012, Paris, France.
- Paris Eye Imaging Group, Quinze-Vingts National Eye Hospital, INSERM-DGOS, CIC 1423, 28 rue de Charenton, Paris, 75012, France.
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24
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Yu X, Yuan H, Yang Y, Zheng W, Zheng X, Lu SH, Jiang W, Yu X. Mammalian esophageal stratified tissue homeostasis is maintained distinctively by the epithelial pluripotent p63 +Sox2 + and p63 -Sox2 + cell populations. Cell Mol Life Sci 2023; 80:305. [PMID: 37752383 PMCID: PMC11072776 DOI: 10.1007/s00018-023-04952-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 07/30/2023] [Accepted: 09/05/2023] [Indexed: 09/28/2023]
Abstract
Self-renewing, damage-repair and differentiation of mammalian stratified squamous epithelia are subject to tissue homeostasis, but the regulation mechanisms remain elusive. Here, we investigate the esophageal squamous epithelial tissue homeostasis in vitro and in vivo. We establish a rat esophageal organoid (rEO) in vitro system and show that the landscapes of rEO formation, development and maturation trajectories can mimic those of rat esophageal epithelia in vivo. Single-cell RNA sequencing (scRNA-seq), snapshot immunostaining and functional analyses of stratified "matured" rEOs define that the epithelial pluripotent stem cell determinants, p63 and Sox2, play crucial but distinctive roles for regulating mammalian esophageal tissue homeostasis. We identify two cell populations, p63+Sox2+ and p63-Sox2+, of which the p63+Sox2+ population presented at the basal layer is the cells of origin required for esophageal epithelial stemness maintenance and proliferation, whereas the p63-Sox2+ population presented at the suprabasal layers is the cells of origin having a dual role for esophageal epithelial differentiation (differentiation-prone fate) and rapid tissue damage-repair responses (proliferation-prone fate). Given the fact that p63 and Sox2 are developmental lineage oncogenes and commonly overexpressed in ESCC tissues, p63-Sox2+ population could not be detected in organoids formed by esophageal squamous cell carcinoma (ESCC) cell lines. Taken together, these findings reveal that the tissue homeostasis is maintained distinctively by p63 and/or Sox2-dependent cell lineage populations required for the tissue renewing, damage-repair and protection of carcinogenesis in mammalian esophagi.
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Affiliation(s)
- Xiaohong Yu
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Hui Yuan
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Yanan Yang
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Wei Zheng
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xuejing Zheng
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
- Departments of Orthopedics, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Shih-Hsin Lu
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
- Beijing Key Laboratory for Carcinogenesis and Cancer Prevention, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Wei Jiang
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
- Beijing Key Laboratory for Carcinogenesis and Cancer Prevention, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Xiying Yu
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
- Beijing Key Laboratory for Carcinogenesis and Cancer Prevention, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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25
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Sockell A, Wong W, Longwell S, Vu T, Karlsson K, Mokhtari D, Schaepe J, Lo YH, Cornelius V, Kuo C, Van Valen D, Curtis C, Fordyce PM. A microwell platform for high-throughput longitudinal phenotyping and selective retrieval of organoids. Cell Syst 2023; 14:764-776.e6. [PMID: 37734323 DOI: 10.1016/j.cels.2023.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 02/24/2023] [Accepted: 08/22/2023] [Indexed: 09/23/2023]
Abstract
Organoids are powerful experimental models for studying the ontogeny and progression of various diseases including cancer. Organoids are conventionally cultured in bulk using an extracellular matrix mimic. However, bulk-cultured organoids physically overlap, making it impossible to track the growth of individual organoids over time in high throughput. Moreover, local spatial variations in bulk matrix properties make it difficult to assess whether observed phenotypic heterogeneity between organoids results from intrinsic cell differences or differences in the microenvironment. Here, we developed a microwell-based method that enables high-throughput quantification of image-based parameters for organoids grown from single cells, which can further be retrieved from their microwells for molecular profiling. Coupled with a deep learning image-processing pipeline, we characterized phenotypic traits including growth rates, cellular movement, and apical-basal polarity in two CRISPR-engineered human gastric organoid models, identifying genomic changes associated with increased growth rate and changes in accessibility and expression correlated with apical-basal polarity. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Alexandra Sockell
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Wing Wong
- Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Scott Longwell
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Thy Vu
- Department of Biochemistry, UT Austin, Austin, TX 78712, USA
| | - Kasper Karlsson
- Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Daniel Mokhtari
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | - Julia Schaepe
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Yuan-Hung Lo
- Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Vincent Cornelius
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Calvin Kuo
- Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - David Van Valen
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Christina Curtis
- Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94110, USA.
| | - Polly M Fordyce
- Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94110, USA; ChEM-H Institute, Stanford University, Stanford, CA 94305, USA.
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26
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Lin X, Sun L, Lu M, Zhao Y. Biomimetic Gland Models with Engineered Stratagems. RESEARCH (WASHINGTON, D.C.) 2023; 6:0232. [PMID: 37719047 PMCID: PMC10503994 DOI: 10.34133/research.0232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 08/29/2023] [Indexed: 09/19/2023]
Abstract
As extensively distributed tissues throughout the human body, glands play a critical role in various physiological processes. Therefore, the construction of biomimetic gland models in vitro has aroused great interest in multiple disciplines. In the biological field, the researchers focus on optimizing the cell sources and culture techniques to reconstruct the specific structures and functions of glands, such as the emergence of organoid technology. From the perspective of biomedical engineering, the generation of biomimetic gland models depends on the combination of engineered scaffolds and microfluidics, to mimic the in vivo environment of glandular tissues. These engineered stratagems endowed gland models with more biomimetic features, as well as a wide range of application prospects. In this review, we first describe the biomimetic strategies for constructing different in vitro gland models, focusing on the role of microfluidics in promoting the structure and function development of biomimetic glands. After summarizing several common in vitro models of endocrine and exocrine glands, the applications of gland models in disease modelling, drug screening, regenerative medicine, and personalized medicine are enumerated. Finally, we conclude the current challenges and our perspective of these biomimetic gland models.
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Affiliation(s)
- Xiang Lin
- Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, School of Biological Science and Medical Engineering,
Southeast University, Nanjing 210096, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health),
Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325001, China
| | - Lingyu Sun
- Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, School of Biological Science and Medical Engineering,
Southeast University, Nanjing 210096, China
| | - Minhui Lu
- Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, School of Biological Science and Medical Engineering,
Southeast University, Nanjing 210096, China
| | - Yuanjin Zhao
- Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, School of Biological Science and Medical Engineering,
Southeast University, Nanjing 210096, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health),
Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325001, China
- Southeast University Shenzhen Research Institute, Shenzhen 518071, China
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27
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Devany J, Falk MJ, Holt LJ, Murugan A, Gardel ML. Epithelial tissue confinement inhibits cell growth and leads to volume-reducing divisions. Dev Cell 2023; 58:1462-1476.e8. [PMID: 37339629 PMCID: PMC10528006 DOI: 10.1016/j.devcel.2023.05.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 05/12/2023] [Accepted: 05/26/2023] [Indexed: 06/22/2023]
Abstract
Cell proliferation is a central process in tissue development, homeostasis, and disease, yet how proliferation is regulated in the tissue context remains poorly understood. Here, we introduce a quantitative framework to elucidate how tissue growth dynamics regulate cell proliferation. Using MDCK epithelial monolayers, we show that a limiting rate of tissue expansion creates confinement that suppresses cell growth; however, this confinement does not directly affect the cell cycle. This leads to uncoupling between rates of cell growth and division in epithelia and, thereby, reduces cell volume. Division becomes arrested at a minimal cell volume, which is consistent across diverse epithelia in vivo. Here, the nucleus approaches the minimum volume capable of packaging the genome. Loss of cyclin D1-dependent cell-volume regulation results in an abnormally high nuclear-to-cytoplasmic volume ratio and DNA damage. Overall, we demonstrate how epithelial proliferation is regulated by the interplay between tissue confinement and cell-volume regulation.
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Affiliation(s)
- John Devany
- Department of Physics, The University of Chicago, Chicago, IL 60637, USA; James Franck Institute, The University of Chicago, Chicago, IL 60637, USA; Institute for Biophysical Dynamics, The University of Chicago, Chicago, IL 60637, USA
| | - Martin J Falk
- Department of Physics, The University of Chicago, Chicago, IL 60637, USA; James Franck Institute, The University of Chicago, Chicago, IL 60637, USA
| | - Liam J Holt
- Institute for Systems Genetics, New York University, Grossman School of Medicine, New York, NY 10016, USA
| | - Arvind Murugan
- Department of Physics, The University of Chicago, Chicago, IL 60637, USA; James Franck Institute, The University of Chicago, Chicago, IL 60637, USA
| | - Margaret L Gardel
- Department of Physics, The University of Chicago, Chicago, IL 60637, USA; James Franck Institute, The University of Chicago, Chicago, IL 60637, USA; Institute for Biophysical Dynamics, The University of Chicago, Chicago, IL 60637, USA; Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL 60637, USA.
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28
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Smith MB, Sparks H, Almagro J, Chaigne A, Behrens A, Dunsby C, Salbreux G. Active mesh and neural network pipeline for cell aggregate segmentation. Biophys J 2023; 122:1586-1599. [PMID: 37002604 PMCID: PMC10183373 DOI: 10.1016/j.bpj.2023.03.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 02/16/2023] [Accepted: 03/24/2023] [Indexed: 04/03/2023] Open
Abstract
Segmenting cells within cellular aggregates in 3D is a growing challenge in cell biology due to improvements in capacity and accuracy of microscopy techniques. Here, we describe a pipeline to segment images of cell aggregates in 3D. The pipeline combines neural network segmentations with active meshes. We apply our segmentation method to cultured mouse mammary gland organoids imaged over 24 h with oblique plane microscopy, a high-throughput light-sheet fluorescence microscopy technique. We show that our method can also be applied to images of mouse embryonic stem cells imaged with a spinning disc microscope. We segment individual cells based on nuclei and cell membrane fluorescent markers, and track cells over time. We describe metrics to quantify the quality of the automated segmentation. Our segmentation pipeline involves a Fiji plugin that implements active mesh deformation and allows a user to create training data, automatically obtain segmentation meshes from original image data or neural network prediction, and manually curate segmentation data to identify and correct mistakes. Our active meshes-based approach facilitates segmentation postprocessing, correction, and integration with neural network prediction.
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Affiliation(s)
| | - Hugh Sparks
- Photonics Group, Department of Physics, Imperial College London, London, United Kingdom
| | | | - Agathe Chaigne
- Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University, Utrecht, the Netherlands
| | - Axel Behrens
- Cancer Stem Cell Team, The Institute of Cancer Research, London, United Kingdom
| | - Chris Dunsby
- Photonics Group, Department of Physics, Imperial College London, London, United Kingdom
| | - Guillaume Salbreux
- The Francis Crick Institute, London, United Kingdom; Department of Genetics and Evolution, Geneva, Switzerland.
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29
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Blatchley MR, Anseth KS. Middle-out methods for spatiotemporal tissue engineering of organoids. NATURE REVIEWS BIOENGINEERING 2023; 1:329-345. [PMID: 37168734 PMCID: PMC10010248 DOI: 10.1038/s44222-023-00039-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 02/03/2023] [Indexed: 05/13/2023]
Abstract
Organoids recapitulate many aspects of the complex three-dimensional (3D) organization found within native tissues and even display tissue and organ-level functionality. Traditional approaches to organoid culture have largely employed a top-down tissue engineering strategy, whereby cells are encapsulated in a 3D matrix, such as Matrigel, alongside well-defined biochemical cues that direct morphogenesis. However, the lack of spatiotemporal control over niche properties renders cellular processes largely stochastic. Therefore, bottom-up tissue engineering approaches have evolved to address some of these limitations and focus on strategies to assemble tissue building blocks with defined multi-scale spatial organization. However, bottom-up design reduces the capacity for self-organization that underpins organoid morphogenesis. Here, we introduce an emerging framework, which we term middle-out strategies, that relies on existing design principles and combines top-down design of defined synthetic matrices that support proliferation and self-organization with bottom-up modular engineered intervention to limit the degrees of freedom in the dynamic process of organoid morphogenesis. We posit that this strategy will provide key advances to guide the growth of organoids with precise geometries, structures and function, thereby facilitating an unprecedented level of biomimicry to accelerate the utility of organoids to more translationally relevant applications.
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Affiliation(s)
- Michael R. Blatchley
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO USA
- The BioFrontiers Institute, University of Colorado Boulder, Boulder, CO USA
| | - Kristi S. Anseth
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO USA
- The BioFrontiers Institute, University of Colorado Boulder, Boulder, CO USA
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30
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Schuhmacher M, Hoogendoorn S. Out With a Bang: Celebrating Global Chemical Biology. ACS Chem Biol 2023; 18:218-222. [PMID: 36648442 DOI: 10.1021/acschembio.2c00905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
On November 8-10, 2022, 163 participants from all over the world gathered at the Campus Biotech in Geneva, Switzerland to share in the latest research in chemical biology. The fourth international symposium of the Swiss National Centres of Competence in Research (NCCR) Chemical Biology coincided with the end of this successful research consortium, and as such this event marked a celebration of the past 12 years of chemical biology research in Switzerland. The inspiring talks delivered by the 15 well-known scientists, balanced in gender, expertise, and geographic location, as well as the numerous poster presentations by junior scientists showcased the breadth of global chemical biology and the bright future ahead.
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Affiliation(s)
- Milena Schuhmacher
- Swiss Federal Institute of Technology Lausanne (EPFL), CH-1015, Lausanne, Switzerland
| | - Sascha Hoogendoorn
- Department of Organic Chemistry, Faculty of Sciences, University of Geneva, 1205 Geneva, Switzerland
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31
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Bao D, Wang L, Zhou X, Yang S, He K, Xu M. Automated detection and growth tracking of 3D bio-printed organoid clusters using optical coherence tomography with deep convolutional neural networks. Front Bioeng Biotechnol 2023; 11:1133090. [PMID: 37122853 PMCID: PMC10130530 DOI: 10.3389/fbioe.2023.1133090] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 03/31/2023] [Indexed: 05/02/2023] Open
Abstract
Organoids are advancing the development of accurate prediction of drug efficacy and toxicity in vitro. These advancements are attributed to the ability of organoids to recapitulate key structural and functional features of organs and parent tumor. Specifically, organoids are self-organized assembly with a multi-scale structure of 30-800 μm, which exacerbates the difficulty of non-destructive three-dimensional (3D) imaging, tracking and classification analysis for organoid clusters by traditional microscopy techniques. Here, we devise a 3D imaging, segmentation and analysis method based on Optical coherence tomography (OCT) technology and deep convolutional neural networks (CNNs) for printed organoid clusters (Organoid Printing and optical coherence tomography-based analysis, OPO). The results demonstrate that the organoid scale influences the segmentation effect of the neural network. The multi-scale information-guided optimized EGO-Net we designed achieves the best results, especially showing better recognition workout for the biologically significant organoid with diameter ≥50 μm than other neural networks. Moreover, OPO achieves to reconstruct the multiscale structure of organoid clusters within printed microbeads and calibrate the printing errors by segmenting the printed microbeads edges. Overall, the classification, tracking and quantitative analysis based on image reveal that the growth process of organoid undergoes morphological changes such as volume growth, cavity creation and fusion, and quantitative calculation of the volume demonstrates that the growth rate of organoid is associated with the initial scale. The new method we proposed enable the study of growth, structural evolution and heterogeneity for the organoid cluster, which is valuable for drug screening and tumor drug sensitivity detection based on organoids.
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Affiliation(s)
- Di Bao
- School of Automation, Hangzhou Dianzi University, Hangzhou, China
| | - Ling Wang
- School of Automation, Hangzhou Dianzi University, Hangzhou, China
- Key Laboratory of Medical Information and 3D Bioprinting of Zhejiang Province, Hangzhou, China
- *Correspondence: Ling Wang, ; Mingen Xu,
| | - Xiaofei Zhou
- School of Automation, Hangzhou Dianzi University, Hangzhou, China
- Key Laboratory of Medical Information and 3D Bioprinting of Zhejiang Province, Hangzhou, China
| | - Shanshan Yang
- School of Automation, Hangzhou Dianzi University, Hangzhou, China
- Key Laboratory of Medical Information and 3D Bioprinting of Zhejiang Province, Hangzhou, China
| | - Kangxin He
- Key Laboratory of Medical Information and 3D Bioprinting of Zhejiang Province, Hangzhou, China
| | - Mingen Xu
- School of Automation, Hangzhou Dianzi University, Hangzhou, China
- Key Laboratory of Medical Information and 3D Bioprinting of Zhejiang Province, Hangzhou, China
- *Correspondence: Ling Wang, ; Mingen Xu,
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