Microsatellite-Based Quantification Method to Estimate Biomass of Endophytic Phialocephala Species in Strain Mixtures
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Fungi of the Phialocephala fortinii sensu lato–Acephala applanata species complex (PAC) are ubiquitous endophytic colonizers of tree roots in which they form genotypically diverse communities. Measurement of the colonization density of each of the fungal colonizers is a prerequisite to study the ecology of these communities. Up to now, there is no method readily available for the quantification of PAC strains co-colonizing the same root. The new DNA quantification method presented here is based on the amplification of microsatellites by competitive polymerase chain reaction (PCR). The method proved to be suitable to detect and quantify at least two strains within one single sample by the addition of a known amount of mycelium of a reference strain before DNA extraction. The method exploits the correlation between the reference/target ratio of light emitted during microsatellite detection (peak ratio) and the reference/target ratio of mycelial weights to determine the biomass of the target strain. Hence, calibration curves were obtained by linear regression of the peak ratios on the weight ratios for different mixtures of reference and target strains. The slopes of the calibration curves and the coefficients of determination were close to 1, indicating that peak ratios are good predictors of weight ratios. Estimates of fungal biomass in mycelial test mixtures of known composition laid within the 95% prediction interval and deviated on average by 16% (maximally 50%) from the true biomass. On average, 3–6% of the root biomass of Norway spruce seedlings consisted of mycelial biomass of either one of two inoculated PAC strains. Biomass estimates obtained by real-time quantitative PCR were correlated with the estimates obtained by the microsatellite-based method, but variation between the two estimates from the same root was high in some samples. The microsatellite-based DNA quantification method described here is currently the best method for strainwise estimation of endophytic biomass of PAC fungi in small root samples.
KeywordsFungal Biomass Prediction Interval Biomass Estimate Dark Septate Endophyte Mycelial Biomass
We would like to thank the Genetic Diversity Centre (GDC) of ETH Zurich for providing the necessary laboratory facilities to perform real-time quantitative PCR and microsatellite analyses. We also thank Manuel Koller of the Seminar for Statistics (SfS), ETH Zurich, for his support. The study represents part of the research project GEDIHAP funded by the Competence Center Environment and Sustainability (CCES) of the ETH Domain.
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