Journal Article

FZJ-2018-07847

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Nutrient exchange in arbuscular mycorrhizal symbiosis from a thermodynamic point of view

Dreyer, I. (Corresponding author) ; Spitz, O. ; Kanonenberg, K. ; Montag, K. ; Handrich, M. ; Ahmad, S. ; Schott-Verdugo, S. ; Navarro-Retamal, C. ; Rubio-Meléndez, M. E. ; Gomez-Porras, J. L. ; Riedelsberger, J. ; Molina-Montenegro, M. A. ; Succurro, A. ; Zuccaro, A. ; Gould, S. B. ; Bauer, P. ; Schmitt, L. ; Gohlke, H.FZJ*

2019
Wiley-Blackwell Oxford [u.a.]

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Please use a persistent id in citations: http://hdl.handle.net/2128/31317  doi:10.1111/nph.15646

Abstract: To obtain insights into the dynamics of nutrient exchange in arbuscular mycorrhizal (AM) symbiosis, we modelled mathematically the two‐membrane system at the plant–fungus interface and simulated its dynamics. In computational cell biology experiments, the full range of nutrient transport pathways was tested for their ability to exchange phosphorus (P)/carbon (C)/nitrogen (N) sources. As a result, we obtained a thermodynamically justified, independent and comprehensive model of the dynamics of the nutrient exchange at the plant–fungus contact zone. The predicted optimal transporter network coincides with the transporter set independently confirmed in wet‐laboratory experiments previously, indicating that all essential transporter types have been discovered. The thermodynamic analyses suggest that phosphate is released from the fungus via proton‐coupled phosphate transporters rather than anion channels. Optimal transport pathways, such as cation channels or proton‐coupled symporters, shuttle nutrients together with a positive charge across the membranes. Only in exceptional cases does electroneutral transport via diffusion facilitators appear to be plausible. The thermodynamic models presented here can be generalized and adapted to other forms of mycorrhiza and open the door for future studies combining wet‐laboratory experiments with computational simulations to obtain a deeper understanding of the investigated phenomena.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)
2. Strukturbiochemie (ICS-6)
3. John von Neumann - Institut für Computing (NIC)

Research Program(s):

1. 511 - Computational Science and Mathematical Methods (POF3-511) (POF3-511)
2. Forschergruppe Gohlke (hkf7_20170501) (hkf7_20170501)

Appears in the scientific report 2019

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Database coverage:
; ; ; BIOSIS Previews ; Clarivate Analytics Master Journal List ; Current Contents - Agriculture, Biology and Environmental Sciences ; Ebsco Academic Search ; IF >= 5 ; JCR ; NCBI Molecular Biology Database ; National-Konsortium ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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