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Morphomics via next-generation electron microscopy
Raku Son1,2 , Kenji Yamazawa3 , Akiko Oguchi1,2 , Mitsuo Suga4 , Masaru Tamura5 , Motoko Yanagita2,6 , Yasuhiro Murakawa1,6,7 , Satoshi Kume8,9,10,*
1RIKEN-IFOM Joint Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
2Department of Nephrology, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan
3Advanced Manufacturing Support Team, RIKEN Center for Advanced Photonics, Wako 351-0198, Japan
4Multimodal Microstructure Analysis Unit, RIKEN–JEOL Collaboration Center, Kobe 650-0047, Japan
5Technology and Development Team for Mouse Phenotype Analysis, RIKEN BioResource Research Center, Tsukuba 305-0074, Japan
6Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto 606-8501, Japan
7IFOM—The FIRC Institute of Molecular Oncology, Milan 20139, Italy
8Laboratory for Pathophysiological and Health Science, RIKEN Center for Biosystems Dynamics Research, Kobe 650-0047, Japan
9Center for Health Science Innovation, Osaka City University, Osaka 530-0011, Japan
10Osaka Electro-Communication University, Neyagawa 572-8530, Japan
*Correspondence to:Satoshi Kume , Email:satoshi.kume@a.riken.jp
J Mol Cell Biol, Volume 15, Issue 12, December 2023, mjad081,  https://doi.org/10.1093/jmcb/mjad081
Keyword: comprehensive morphological analysis, next-generation electron microscopy, 3D bioimaging, imaging database, deep learning

The living body is composed of innumerable fine and complex structures. Although these structures have been studied in the past, a vast amount of information pertaining to them still remains unknown. When attempting to observe these ultra-structures, the use of electron microscopy (EM) has become indispensable. However, conventional EM settings are limited to a narrow tissue area, which can bias observations. Recently, new trends in EM research have emerged, enabling coverage of far broader, nano-scale fields of view for two-dimensional wide areas and three-dimensional large volumes. Moreover, cutting-edge bioimage informatics conducted via deep learning has accelerated the quantification of complex morphological bioimages. Taken together, these technological and analytical advances have led to the comprehensive acquisition and quantification of cellular morphology, which now arises as a new omics science termed ‘morphomics’.