Revisiting soil fungal biomarkers and conversion factors: Interspecific variability in phospholipid fatty acids, ergosterol and rDNA copy numbers

Abstract

The abundances of fungi and bacteria in soil are used as simple predictors for carbon dynamics, and represent widely available microbial traits. Soil biomarkers serve as quantitative estimates of these microbial groups, though not quantifying microbial biomass per se. The accurate conversion to microbial carbon pools, and an understanding of its comparability among soils is therefore needed. We refined conversion factors for classical fungal biomarkers, and evaluated the application of quantitative PCR (qPCR, rDNA copies) as a biomarker for soil fungi. Based on biomarker contents in pure fungal cultures of 30 isolates, combined with available references, we propose average conversion factors of 95.3 g fungal C g-1 ergosterol, 32.0 mg fungal C ymol-1 PLFA 18:2w6,9 and 0.264 pg fungal C ITS1 DNA copy-1. As expected, interspecific variability was most pronounced in rDNA copies, though qPCR results showed the least phylogenetic bias. A modeling approach based on exemplary agricultural soils further supported the hypothesis that high diversity in soil buffers against biomarker variability, whereas also phylogenetic biases impact the accuracy of comparisons in biomarker estimates. Our analyses suggest that qPCR results cover the fungal community in soil best, though with a variability only partly offset in highly diverse soils. PLFA 18:2ω6,9 and ergosterol represent accurate biomarkers to quantify Ascomycota and Basidiomycota. To conclude, the ecological interpretation and coverage of biomarker data prior to their application in global models is important, where the combination of different biomarkers may be most insightful.

A comparison among EL-FAME, PLFA, and quantitative PCR methods to detect changes in the abundance of soil bacteria and fungi

“…Attempts to transform data of abundance provided by EL-FAME, PLFA, or qPCR analyses into absolute amounts of soil microbial biomass (i.e., µg microbial biomass C g -1 soil) have been made (Baldrian et al, 2013; Willers et al, 2015). However, the reliability of these conversion factors has been questioned (Willers et al, 2015) and further research is needed for verification (Camenzind et al, 2024). Therefore, the three methods used here quantify soil microbial abundance and are a proxy of soil microbial biomass.…”