論文

査読有り 国際誌
2020年9月1日

Single-Cell Information Analysis Reveals That Skeletal Muscles Incorporate Cell-to-Cell Variability as Information Not Noise

CELL REPORTS
  • Takumi Wada
  • Ken-ichi Hironaka
  • Mitsutaka Wataya
  • Masashi Fujii
  • Miki Eto
  • Shinsuke Uda
  • Daisuke Hoshino
  • Katsuyuki Kunida
  • Haruki Inoue
  • Hiroyuki Kubota
  • Tsuguto Takizawa
  • Yasuaki Karasawa
  • Hirofumi Nakatomi
  • Nobuhito Saito
  • Hiroki Hamaguchi
  • Yasuro Furuichi
  • Yasuko Manabe
  • Nobuharu L. Fujii
  • Shinya Kuroda
  • 全て表示

32
9
開始ページ
108051
終了ページ
108051
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.celrep.2020.108051
出版者・発行元
CELL PRESS

Cell-to-cell variability in signal transduction in biological systems is often considered noise. However, intercellular variation (i.e., cell-to-cell variability) has the potential to enable individual cells to encode different information. Here, we show that intercellular variation increases information transmission of skeletal muscle. We analyze the responses of multiple cultured myotubes or isolated skeletal muscle fibers as a multiple-cell channel composed of single-cell channels. We find that the multiple-cell channel, which incorporates intercellular variation as information, not noise, transmitted more information in the presence of intercellular variation than in the absence according to the "response diversity effect," increasing in the gradualness of dose response by summing the cell-to-cell variable dose responses. We quantify the information transmission of human facial muscle contraction during intraoperative neurophysiological monitoring and find that information transmission of muscle contraction is comparable to that of a multiple-cell channel. Thus, our data indicate that intercellular variation can increase the information capacity of tissues.

リンク情報
DOI
https://doi.org/10.1016/j.celrep.2020.108051
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/32877665
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000565154100001&DestApp=WOS_CPL
ID情報
  • DOI : 10.1016/j.celrep.2020.108051
  • ISSN : 2211-1247
  • PubMed ID : 32877665
  • Web of Science ID : WOS:000565154100001

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