Versatile whole-organ/body staining and imaging based on electrolyte-gel properties of biological tissues

Autor: Hiroki Kitaura, Tadashi Isa, Yoshihiro Shimizu, Yuki Saeki, Kazushige Touhara, Ken Morishima, Etsuo A. Susaki, Xiang Li, Kaoru Isa, Kazuki Tainaka, Masashi Fukayama, Takaomi C. Saido, Hiroki R. Ueda, Akihiro Kuno, Takashi Saito, Tetsuo Ushiku, Chika Shimizu, Mitsuhiro Shibayama, Hiroaki Ono, Akiyoshi Kakita, Chihiro Yokoyama, Kengo Nishi, Masako Ikemura, Hirotaka Onoe, Kazunari Miyamichi, Koji L. Ode
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Nature Communications, Vol 11, Iss 1, Pp 1-22 (2020)
Nature Communications
ISSN: 2041-1723
Popis: Whole-organ/body three-dimensional (3D) staining and imaging have been enduring challenges in histology. By dissecting the complex physicochemical environment of the staining system, we developed a highly optimized 3D staining imaging pipeline based on CUBIC. Based on our precise characterization of biological tissues as an electrolyte gel, we experimentally evaluated broad 3D staining conditions by using an artificial tissue-mimicking material. The combination of optimized conditions allows a bottom-up design of a superior 3D staining protocol that can uniformly label whole adult mouse brains, an adult marmoset brain hemisphere, an ~1 cm3 tissue block of a postmortem adult human cerebellum, and an entire infant marmoset body with dozens of antibodies and cell-impermeant nuclear stains. The whole-organ 3D images collected by light-sheet microscopy are used for computational analyses and whole-organ comparison analysis between species. This pipeline, named CUBIC-HistoVIsion, thus offers advanced opportunities for organ- and organism-scale histological analysis of multicellular systems.
Tissue clearing has revolutionised histology, but limited penetration of antibodies and stains into thick tissue segments is still a bottleneck. Here, the authors characterise optically cleared tissue as an electrolyte gel and apply this knowledge to stain the entirety of thick tissue samples.
Databáze: OpenAIRE