Nature publication: Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification

Calipso Nature tweet

Classification of the organoid morphologies. Credits Calipso/CNRS@CREATE/Nature Methods. 

Congratulations to Anne 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  for this new publication in Nature Methods: Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification!

An excellent publication illustrating the power of teamwork, in a multicultural environment. “Highly interdisciplinary”, this work gathers “worldclass
expertise of all the members of the French and Singaporean teams in optics, microfabrication, biology and image analysis”. A “great example of how international collaborations can bring the best of several academic systems together”, said Virgile Viasnoff from Calipso CNRS@CREATE project and Director of BMC2 CNRS IRL.

Jan Bruder, expert from The Max Planck Institute for Molecular Biomedicine, Münster, Germany, highlights that the “3D imaging strategy is impressive in its speed and complexity.”

The editor, Madhura Mukhopadhyay, Associate Editor, Nature Methods, describes this paper as “an elegant approach that enables rapid, high content screening of organoids in a 3D format.”

 

Read more about Calipso project here. 

Learn more about the BMC² CNRS International Research Laboratory here.   

 

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.

Nature Methods: Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification