• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2018 Fiscal Year Final Research Report

In vivo imaging with FRET mice

Research Project

  • PDF
Project/Area Number 15H02397
Research Category

Grant-in-Aid for Scientific Research (A)

Allocation TypeSingle-year Grants
Section一般
Research Field Cell biology
Research InstitutionKyoto University

Principal Investigator

Matsuda Michiyuki  京都大学, 生命科学研究科, 教授 (10199812)

Co-Investigator(Kenkyū-buntansha) 平塚 拓也  京都大学, 医学(系)研究科(研究院), 助教 (90641639)
Research Collaborator HIRATSUKA Takuya  
AOKI Kazuhiro  
IMAjo Masamichi  
KOMATSU Naoki  
SUMIYAMA Kenta  
TSUKIJI Shinya  
IMAYOSHI Itaru  
TERAI Kenta  
HOTTA Kazuhiro  
MURATA Tomokazu  
SATO Masaya  
Project Period (FY) 2015-04-01 – 2019-03-31
Keywords蛍光プローブ / 組織形態マーカー / FRETバイオセンサー / 機械学習
Outline of Final Research Achievements

Hematoxylin and eosin (H&E) staining has been the de-facto standard for histological studies. We have developed a genetically encoded fluorescent marker, NuCyM, which is designed to recapitulate H&E staining patterns in vivo. We generated a transgenic mouse line ubiquitously expressing NyCyM. NuCyM evenly marked the plasma membrane, cytoplasm and nucleus in most tissues. In the NuCyM-expressing cells, cell division of a single cell was clearly observed as five basic phases during M phase by three-dimensional imaging. We next crossed NuCyM mice with transgenic mice expressing an ERK biosensor. Using NuCyM, ERK activity in each cell could be extracted from the FRET images. To further accelerate the image analysis, we employed machine learning-based segmentation methods, and thereby automatically quantitated ERK activity in each cell. In conclusion, NuCyM is a versatile cell morphological marker that enables us to grasp histological information as with H&E staining.

Free Research Field

細胞生物学

Academic Significance and Societal Importance of the Research Achievements

生物学の研究は、培養皿上のクローン化された細胞から、オルガノイド、さらには生体組織へとその中心を移しつつある。今回開発したNuCyMは蓄積された組織学の叡智を最新の分子プローブへと繋ぐツールである。今後の病態解明あるいは創薬研究に役立つツールとなることが期待される。また、機械学習を用いた細胞分別法はさまざまに開発されつつあるが、機械学習を念頭においた組織染色あるいは細胞染色法が必要であり、本研究はその嚆矢としても重要である。

URL: 

Published: 2020-03-30  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi