論文

査読有り
2019年1月

A Molecular Target for an Alcohol Chain-Length Cutoff

JOURNAL OF MOLECULAR BIOLOGY
  • Hae-Won Chung
  • ,
  • E. Nicholas Petersen
  • ,
  • Cerrone Cabanos
  • ,
  • Keith R. Murphy
  • ,
  • Mahmud Arif Pavel
  • ,
  • Andrew S. Hansen
  • ,
  • William W. Ja
  • ,
  • Scott B. Hansen

431
2
開始ページ
196
終了ページ
209
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.jmb.2018.11.028
出版者・発行元
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD

Despite the widespread consumption of ethanol, mechanisms underlying its anesthetic effects remain uncertain. n-Alcohols induce anesthesia up to a specific chain length and then lose potency-an observation known as the "chain-length cutoff effect." This cutoff effect is thought to be mediated by alcohol binding sites on proteins such as ion channels, but where these sites are for long-chain alcohols and how they mediate a cutoff remain poorly defined. In animals, the enzyme phospholipase D (PLD) has been shown to generate alcohol metabolites (e.g., phosphatidylethanol) with a cutoff, but no phenotype has been shown connecting PLD to an anesthetic effect. Here we show loss of PLD blocks ethanol-mediated hyperactivity in Drosophila melanogaster (fruit fly), demonstrating that PLD mediates behavioral responses to alcohol in vivo. Furthermore, the metabolite phosphatidylethanol directly competes for the endogenous PLD product phosphatidic acid at lipid-binding sites within potassium channels [e.g., TWIK-related K+ channel type 1 (K2P2.1, TREK-1)]. This gives rise to a PLD-dependent cutoff in TREK-1. We propose an alcohol pathway where PLD produces lipid-alcohol metabolites that bind to and regulate downstream effector molecules including lipid-regulated potassium channels. (C) 2018 Elsevier Ltd.

リンク情報
DOI
https://doi.org/10.1016/j.jmb.2018.11.028
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000456750800006&DestApp=WOS_CPL
ID情報
  • DOI : 10.1016/j.jmb.2018.11.028
  • ISSN : 0022-2836
  • eISSN : 1089-8638
  • Web of Science ID : WOS:000456750800006

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