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Curated Papers > Recent high-impact research on "organoids" (IF≥30, last 5 years)

Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification. ​

Literature Information ​

DOI10.1038/s41592-022-01508-0
PMID35697835
JournalNature methods
Impact Factor32.1
JCR QuartileQ1
Publication Year2022
Times Cited50
KeywordsAutomation, 3D Imaging, Organoids, Multi-scale Characterization, Deep Learning
Literature TypeJournal Article, Research Support, Non-U.S. Gov't
ISSN1548-7091
Pages881-892
Issue19(7)
AuthorsAnne Beghin, Gianluca Grenci, Geetika Sahni, Su Guo, Harini Rajendiran, Tom Delaire, Saburnisha Binte Mohamad Raffi, Damien Blanc, Richard de Mets, Hui Ting Ong, Xareni Galindo, Anais Monet, Vidhyalakshmi Acharya, Victor Racine, Florian Levet, Remi Galland, Jean-Baptiste Sibarita, Virgile Viasnoff

TL;DR ​

This study introduces an automated multi-scale 3D imaging platform that enhances the characterization of high-density organoid cultures using live 3D light-sheet imaging, achieving a throughput of 300 organoids per hour. The platform's ability to generate extensive 3D data enables the training of deep learning algorithms to analyze morphogenetic features across various organoid types, advancing our understanding of organoid biology and their potential applications in research and medicine.

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Automation · 3D Imaging · Organoids · Multi-scale Characterization · Deep Learning

Abstract ​

Current imaging approaches limit the ability to perform multi-scale characterization of three-dimensional (3D) organotypic cultures (organoids) in large numbers. Here, we present an automated multi-scale 3D imaging platform synergizing high-density organoid cultures with rapid and live 3D single-objective light-sheet imaging. It is composed of disposable microfabricated organoid culture chips, termed JeWells, with embedded optical components and a laser beam-steering unit coupled to a commercial inverted microscope. It permits streamlining organoid culture and high-content 3D imaging on a single user-friendly instrument with minimal manipulations and a throughput of 300 organoids per hour. We demonstrate that the large number of 3D stacks that can be collected via our platform allows training deep learning-based algorithms to quantify morphogenetic organizations of organoids at multi-scales, ranging from the subcellular scale to the whole organoid level. We validated the versatility and robustness of our approach on intestine, hepatic, neuroectoderm organoids and oncospheres.

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Primary Questions Addressed ​

  1. How does the integration of deep learning algorithms enhance the analysis of multi-scale phenotypic data from organoid cultures?
  2. What are the potential applications of high-speed 3D imaging in drug discovery and disease modeling using organoid cultures?
  3. How do the JeWells microfabricated culture chips improve the efficiency and accuracy of organoid imaging compared to traditional methods?
  4. What challenges are associated with scaling up the automated imaging platform for use in larger biological studies or clinical applications?
  5. In what ways can the quantification of morphogenetic organizations at different scales contribute to our understanding of organoid development and function?

Key Findings ​

Key Insights ​

  1. Research Background and Objectives: The study addresses the limitations of current imaging techniques that hinder the comprehensive multi-scale characterization of three-dimensional (3D) organotypic cultures, known as organoids. Traditional methods struggle with high-throughput imaging, thereby restricting the ability to analyze large numbers of organoids effectively. The objective of this research is to develop an automated, high-speed 3D imaging platform that facilitates the in-depth analysis of organoid cultures, enabling researchers to quantify phenotypic variations across different scales, from subcellular structures to entire organoids.

  2. Main Methods and Findings: The research introduces a novel automated multi-scale 3D imaging platform, which integrates high-density organoid cultures with rapid live 3D imaging using a single-objective light-sheet technique. The platform utilizes microfabricated organoid culture chips, referred to as JeWells, which are equipped with optical components and a laser beam-steering unit, all integrated into a commercial inverted microscope. This setup streamlines the process of culturing organoids and conducting high-content imaging with minimal manual intervention. The system boasts a throughput capacity of 300 organoids per hour, significantly enhancing the efficiency of data collection. The study successfully applied this platform to capture vast amounts of 3D imaging data, which facilitated the training of deep learning algorithms for quantifying the morphogenetic organization of organoids across multiple scales. The versatility of the platform was validated across various organoid types, including intestinal, hepatic, neuroectodermal organoids, and oncospheres.

  3. Core Conclusion: The automated multi-scale 3D imaging platform presents a significant advancement in the field of organoid research by enabling high-throughput, detailed analysis of organoid morphology. The integration of deep learning for phenotypic quantification allows for a more comprehensive understanding of organoid development and organization, offering insights that can drive further research in regenerative medicine, disease modeling, and drug testing.

  4. Research Significance and Impact: This research has profound implications for biomedical research, particularly in enhancing the study of organoid cultures, which are pivotal in simulating human tissues for various applications. The ability to conduct high-speed, detailed imaging and quantification could accelerate discoveries in developmental biology and disease pathology. Furthermore, by providing a user-friendly platform that requires minimal manual manipulation, this technology could democratize access to advanced imaging techniques, allowing a broader range of laboratories to engage in cutting-edge organoid research. The approach could also pave the way for more personalized medicine strategies by facilitating the analysis of patient-derived organoids in drug response studies and disease modeling.

References ​

  1. Human organoids: model systems for human biology and medicine. - Jihoon Kim;Bon-Kyoung Koo;Juergen A Knoblich - Nature reviews. Molecular cell biology (2020)
  2. The challenge of developing human 3D organoids into medicines. - Joaquim Vives;Laura Batlle-Morera - Stem cell research & therapy (2020)
  3. The potential and challenges of patient-derived organoids in guiding the multimodality treatment of upper gastrointestinal malignancies. - Georg A Busslinger;Fianne Lissendorp;Ingrid A Franken;Richard van Hillegersberg;Jelle P Ruurda;Hans Clevers;Michiel F G de Maat - Open biology (2020)
  4. Phenotypic landscape of intestinal organoid regeneration. - Ilya Lukonin;Denise Serra;Ludivine Challet Meylan;Katrin Volkmann;Janine Baaten;Rui Zhao;Shelly Meeusen;Karyn Colman;Francisca Maurer;Michael B Stadler;Jeremy Jenkins;Prisca Liberali - Nature (2020)
  5. A fully automated high-throughput workflow for 3D-based chemical screening in human midbrain organoids. - Henrik Renner;Martha Grabos;Katharina J Becker;Theresa E Kagermeier;Jie Wu;Mandy Otto;Stefan Peischard;Dagmar Zeuschner;Yaroslav TsyTsyura;Paul Disse;Jürgen Klingauf;Sebastian A Leidel;Guiscard Seebohm;Hans R Schöler;Jan M Bruder - eLife (2020)
  6. The Organoid Cell Atlas. - Christoph Bock;Michael Boutros;J Gray Camp;Laura Clarke;Hans Clevers;Juergen A Knoblich;Prisca Liberali;Aviv Regev;Anne C Rios;Oliver Stegle;Hendrik G Stunnenberg;Sarah A Teichmann;Barbara Treutlein;Robert G J Vries; - Nature biotechnology (2021)
  7. Imaging organoids: a bright future ahead. - Anne C Rios;Hans Clevers - Nature methods (2018)
  8. Organoids in image-based phenotypic chemical screens. - Ilya Lukonin;Marietta Zinner;Prisca Liberali - Experimental & molecular medicine (2021)
  9. Light-Sheet Microscopy and Its Potential for Understanding Developmental Processes. - Yinan Wan;Katie McDole;Philipp J Keller - Annual review of cell and developmental biology (2019)
  10. A single-cell transcriptomic landscape of the lungs of patients with COVID-19. - Si Wang;Xiaohong Yao;Shuai Ma;Yifang Ping;Yanling Fan;Shuhui Sun;Zhicheng He;Yu Shi;Liang Sun;Shiqi Xiao;Moshi Song;Jun Cai;Jiaming Li;Rui Tang;Liyun Zhao;Chaofu Wang;Qiaoran Wang;Lei Zhao;Huifang Hu;Xindong Liu;Guoqiang Sun;Lu Chen;Guoqing Pan;Huaiyong Chen;Qingrui Li;Peipei Zhang;Yuanyuan Xu;Huyi Feng;Guo-Guang Zhao;Tianzi Wen;Yungui Yang;Xuequan Huang;Wei Li;Zhenhua Liu;Hongmei Wang;Haibo Wu;Baoyang Hu;Yong Ren;Qi Zhou;Jing Qu;Weiqi Zhang;Guang-Hui Liu;Xiu-Wu Bian - Nature cell biology (2021)

Literatures Citing This Work ​

  1. Digital Technologies: Advancing Individualized Treatments through Gene and Cell Therapies, Pharmacogenetics, and Disease Detection and Diagnostics. - Peter R Corridon;Xinyu Wang;Adeeba Shakeel;Vincent Chan - Biomedicines (2022)
  2. Applications and Advances of Multicellular Tumor Spheroids: Challenges in Their Development and Analysis. - Achilleas G Mitrakas;Avgi Tsolou;Stylianos Didaskalou;Lito Karkaletsou;Christos Efstathiou;Evgenios Eftalitsidis;Konstantinos Marmanis;Maria Koffa - International journal of molecular sciences (2023)
  3. Middle-out methods for spatiotemporal tissue engineering of organoids. - Michael R Blatchley;Kristi S Anseth - Nature reviews bioengineering (2023)
  4. In-silico and in-vitro morphometric analysis of intestinal organoids. - Sandra Montes-Olivas;Danny Legge;Abbie Lund;Alexander G Fletcher;Ann C Williams;Lucia Marucci;Martin Homer - PLoS computational biology (2023)
  5. A Strainer-Based Platform for the Collection and Immunolabeling of Mouse Intestinal Organoids. - Jinlong Tan;Yinju Liu;Weike Li;Guohua Chen;Yongxiang Fang;Xiaobing He;Baoquan Fu;Zhizhong Jing - International journal of molecular sciences (2023)
  6. A microwell platform for high-throughput longitudinal phenotyping and selective retrieval of organoids. - Alexandra Sockell;Wing Wong;Scott Longwell;Thy Vu;Kasper Karlsson;Daniel Mokhtari;Julia Schaepe;Yuan-Hung Lo;Vincent Cornelius;Calvin Kuo;David Van Valen;Christina Curtis;Polly M Fordyce - Cell systems (2023)
  7. Cerebral Organoid Arrays for Batch Phenotypic Analysis in Sections and Three Dimensions. - Juan Chen;Haihua Ma;Zhiyu Deng;Qingming Luo;Hui Gong;Ben Long;Xiangning Li - International journal of molecular sciences (2023)
  8. Whole-cell multi-target single-molecule super-resolution imaging in 3D with microfluidics and a single-objective tilted light sheet. - Nahima Saliba;Gabriella Gagliano;Anna-Karin Gustavsson - bioRxiv : the preprint server for biology (2024)
  9. Lung cancer organoids: models for preclinical research and precision medicine. - Yajing Liu;Yanbing Zhou;Pu Chen - Frontiers in oncology (2023)
  10. Automated, High-Throughput Phenotypic Screening and Analysis Platform to Study Pre- and Post-Implantation Morphogenesis in Stem Cell-Derived Embryo-Like Structures. - Vinidhra Shankar;Clemens van Blitterswijk;Erik Vrij;Stefan Giselbrecht - Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2024)

... (40 more literatures)

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