Scavenging organic nitrogen and remodelling lipid metabolism are key survival strategies adopted by the endophytic fungi, Serendipita vermifera and Serendipita bescii to alleviate nitrogen and phosphorous starvation in vitro

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Abstract

Serendipitaceae represents a diverse fungal group in the Basidiomycota that includes endophytes and lineages that repeatedly evolved ericoid, orchid and ectomycorrhizal lifestyle. Plants rely upon both nitrogen and phosphorous, for essential growth processes, and are often provided by mycorrhizal fungi. In this study, we investigated the cellular proteome of Serendipita vermifera MAFF305830 and closely related Serendipita vermifera subsp. bescii NFPB0129 grown in vitro under (N) ammonium and (P) phosphate starvation conditions. Mycelial growth pattern was documented under these conditions to correlate growth-specific responses to nutrient starvation. We found that N-starvation accelerated hyphal radial growth, whereas P-starvation accelerated hyphal branching. Additionally, P-starvation triggers an integrated starvation response leading to remodelling of lipid metabolism. Higher abundance of an ammonium transporter known to serve as both an ammonium sensor and stimulator of hyphal growth was detected under N-starvation. Additionally, N-starvation led to strong up-regulation of nitrate, amino acid, peptide, and urea transporters, along with several proteins predicted to have peptidase activity. Taken together, our finding suggests S. bescii and S. vermifera have the metabolic capacity for nitrogen assimilation from organic forms of N compounds. We hypothesize that the nitrogen metabolite repression is a key regulator of such organic N assimilation.

Original languageEnglish
Pages (from-to)548-557
Number of pages10
JournalEnvironmental Microbiology Reports
Volume11
Issue number4
DOIs
StatePublished - Aug 2019

Funding

Serendipita vermifera (MAFF-305830) used in this study was obtained from the National Institute of Agro-biological Sciences, Tsukuba, Ibaraki, Japan. The authors thank Josh Meo and Fuqi Liao from Noble Research Institute for graphic design and image quantitative analysis and statistics. This work was supported by the United States Department of Energy (DOE), Office of Biological and Environmental Research (OBER) and conducted within the DOE BioEnergy Science Center (BESC) and Center for Bioenergy Innovation (CBI) projects. BESC and CBI are U.S. DOE Bioenergy Research Centers supported by OBER in the DOE Office of Science. This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory. This manuscript has been co-authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy.

FundersFunder number
BESC
Compute and Data Environment for Science
DOE BioEnergy Science Center
DOE Bioenergy Research
DOE Office of Science
LLCDE-AC05-00OR22725
National Institute of Agro-biological Sciences
OBER
Office of Biological and Environmental Research
UT-Battelle
United States Department of Energy
U.S. Department of Energy
Oak Ridge National Laboratory
Center for Bioenergy Innovation

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