How Do Ethanolamine Plasmalogens Contribute to Order and Structure of Neurological Membranes?

Ana West, Valeria Zoni, Walter E. Teague, Alison N. Leonard, Stefano Vanni, Klaus Gawrisch, Stephanie Tristram-Nagle, Jonathan N. Sachs, Jeffery B. Klauda

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Ethanolamine plasmalogen (EtnPLA) is a conical-shaped ether lipid and an essential component of neurological membranes. Low stability against oxidation limits its study in experiments. The concentration of EtnPLA in the bilayer varies depending on cell type and disease progression. Here we report on mixed bilayers of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and 1-(1Z-octadecenyl)-2-oleoyl-sn-glycero-3-phosphoethanolamine (C18(Plasm)-18:1PE, PLAPE), an EtnPLA lipid subtype, at mole ratios of 2:1, 1:1, and 1:2. We present X-ray diffuse scattering (XDS) form factors F(qz) from oriented stacks of bilayers, related electron-density profiles, and hydrocarbon chain NMR order parameters. To aid future research on EtnPLA lipids and associated proteins, we have also extended the CHARMM36 all-atom force field to include the PLAPE lipid. The ability of the new force-field parameters to reproduce both X-ray and NMR structural properties of the mixed bilayer is remarkable. Our results indicate a thickening of the bilayer upon incorporation of increasing amounts of PLAPE into mixed bilayers, a reduction of lateral area per molecule, and an increase in lipid tail-ordering. The lateral compressibility modulus (KA) calculated from simulations yielded values for PLAPE similar to POPC.

Original languageEnglish (US)
Pages (from-to)828-839
Number of pages12
JournalJournal of Physical Chemistry B
Volume124
Issue number5
DOIs
StatePublished - Feb 6 2020

Bibliographical note

Funding Information:
The research presented in this article from Dr. Klauda’s lab has been supported by the NSF grant MCB-1149187. Computational support for simulations performed in Dr. Klauda’s lab comes from the University of Maryland’s High Performance Computational Cluster Deepthought2 and time using the Extreme Science and Engineering Discovery Environment (XSEDE) allocations by grant number MCB-100139, which are supported by National Science Foundation grant number ACI-1053575. A.W. and J.N.S. gratefully acknowledge funding from the National Institutes of Health (R01 NS084998 to J.N.S.). W.E.T. and K.G. are supported by the Intramural Program of the National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health. V.Z. and S.V. work was supported by a grant from the Swiss National Supercomputing Centre (CSCS) under project ID s726 and s842. V.Z. and S.V. also acknowledge support from the Swiss National Science Foundation (#PP00P3_163966). S.T.N. acknowledges support from the Winters Foundation.

Publisher Copyright:
Copyright © 2020 American Chemical Society.

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

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