Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika; Desai, Shalaka D.; Dai, Yang; Cseke, Leland; Collart, Frank R.

doi:10.3389/fpls.2015.01061

Title: Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

Journal Article · Tue Jan 19 00:00:00 EST 2016 · Frontiers in Plant Science

DOI:https://doi.org/10.3389/fpls.2015.01061· OSTI ID:1248919

Larsen, Peter E. ^[1]; Sreedasyam, Avinash ^[2]; Trivedi, Geetika ^[2]; Desai, Shalaka D. ^[3]; Dai, Yang ^[4]; Cseke, Leland ^[2]; Collart, Frank R. ^[3]

Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Illinois, Chicago, IL (United States)
Univ. of Alabama in Huntsville, Huntsville, AL (United States)
Argonne National Lab. (ANL), Argonne, IL (United States)
Univ. of Illinois, Chicago, IL (United States)

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensor systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.

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Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1248919

Journal Information:: Frontiers in Plant Science, Vol. 6; ISSN 1664-462X

Publisher:: Frontiers Research FoundationCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 26 works

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59 BASIC BIOLOGICAL SCIENCES
Laccaria bicolor
Populus tremuloides
metabolomics
mycorrhizae
proteomics
system modeling
transcriptomics

Title: Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

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