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Metabolite, qPCR, and metadata for relationships between Sphaerulina musiva infection and the Populus microbiome and metabolome

Citation

Dove, Nicholas (2022), Metabolite, qPCR, and metadata for relationships between Sphaerulina musiva infection and the Populus microbiome and metabolome, Dryad, Dataset, https://doi.org/10.6071/M3CM2F

Abstract

Pathogenic fungal infections in plants may, in some cases, lead to downstream systematic impacts on the plant metabolome and microbiome that may either alleviate or exacerbate the effects of the fungal pathogen. While Sphaerulina musiva is a well-characterized fungal pathogen which infects Populus tree species, an important wood fiber and biofuel feedstock, little is known about its systematic effects on the metabolome and microbiome of Populus. Here, we investigate the microbiome and metabolome of P. trichocarpa and P. deltoides leaves and roots and the microbiome of the leaf and root endospheres, phylloplane and rhizosphere to understand the systematic impacts of S. musiva abundance and infection on Populus species in a common garden field setting. We find that S. musiva is indeed present in both P. deltoides and P. trichocarpa, but S. musiva abundance was not statistically related to stem canker onset. We also find that the leaf and root metabolomes significantly differ between the two Populus species and that certain leaf metabolites, particularly the phenolic glycosides, salirepin and salireposide, are diminished in canker-infected P. trichocarpa trees compared to their uninfected counterparts. Furthermore, we found significant associations between the metabolome, S. musiva abundance and microbiome composition and α-diversity, particularly in P. trichocarpa leaves. This suggests that the effects of S. musiva on P. trichocarpa trees are systemic and not confined to the site of canker infection.

Methods

S. musiva abundance

S. musiva abundance was measured by quantitative polymerase chain reaction (qPCR) targeting the beta-tubulin gene following Abraham et al. (35) (NABtF: 50-CGACCTGAACCACCTTGTCT-30 and NABtR: 50-CACGGTAACAGCGCGGAACGA-30). Template DNA concentrations were normalized to 10 ng ul-1, and PCRs were conducted in a 384 well plate containing 1 × SYBR Green (iTaq Universal SYBR® Green Supermix), 500 nmol of each primer, and 2 ul template DNA for a total volume of 20 ul. To generate a standard curve, S. musiva DNA standards were extracted from a cultured representative (S. musiva MN14), and diluted 1:10, 1:100, 1:1000 and 1:10000, quantified using the Qubit dsDNA BR Assay Kit (Invitrogen, Waltham, MA). To detect non-specific amplification, negative controls (no template control and Marsonnina brun 441) were included in the assays. The reactions were carried out using a 7900HT Fast Realtime PCR machine (Applied Biosystems, Waltham, MA, USA) under the following conditions: initial denaturation at 95 °C for 10 min, followed by 40 cycles of amplification at 95 °C for 15 s and 58 °C for 30 s.

Metabolite extraction and processing

Leaf and root tissue metabolites were processed and analyzed by gas chromatography-mass spectrometry (GC-MS). Tissues stored at -80 °C were lyophilized and then powdered using a Spex Geno-Grinder (Metuchen, NJ, USA). Approximately 25 mg of powdered leaf and 45 mg of powdered root material was extracted twice with 80% ethanol. Sorbitol (75 µl; 1 mg ml-1) was added to the first extract and used as an internal standard. After combining the extracts, a 1 ml aliquot of the leaf extract and a 250 µl aliquot of the root extract was dried under a stream of nitrogen. Both types of samples were then derivatized by dissolving aliquots in 500 µl acetonitrile followed by an addition of 500 µl of N-Methyl-N-(trimethylsilyl)trifluoroacetamide with 1% trimethylchlorosilane (MSTFA + 1% TMCS) and heating at 70 °C for 1 h to produce trimethylsilyl (TMS) metabolite derivatives. After 2 days, 1 µl was injected to the GC-MS and analyzed. Metabolites were identified using the Wiley Registry, 10th edition as well as a large, user-created database of TMS-derivatized metabolites. Metabolites were quantified relative to the internal standard and normalized to the mass extracted, extract volume analyzed and injection volume. 

Usage Notes

The sequence data for this dataset is deposited in the Sequence Read Archive under BioProject XXX.

Funding

U.S. Department of Energy, Award: DE-AC05-00OR22725