Microbial community structure was determined as in (25). Briefly, DNA was extracted from soil samples collected from each mesocosm at the end of the conditioning stage, and marker genes [the internal transcribed spacer of the ribosomal RNA (rRNA) operon for fungi, 16S rRNA for bacteria, and 18S rRNA for protists] were polymerase chain reaction amplified and used to characterize the microbial communities. The amplicons were sequenced on an Illumina MiSeq instrument with 2 × 151 base pair kits.

Exact sequence variant (ESV; also known as unique sequence variants and zero-radius operational taxonomic units) counts were determined from raw sequence data using the DADA2 pipeline (42). Only ESVs that were detected in more than one mesocosm in the conditioning stage [based on a larger dataset including 88 mesocosms and 26 plant species (25)] were included in data analysis (i.e., only sequences that were detected in two independent soil samples were analyzed). Microbial data were rarefied to the minimum sequence number per soil sample (13,023, 3833, and 3688 for fungal, bacterial, and protist data, respectively). Fungal sequencing data were split into three functional groups—putative pathogens, AM fungi, and saprotrophs—based on taxonomy [determined using the RDP classifier (43) and data available in FUNGuild (26)]. Sequences that had multiple function assignments in FUNGuild were excluded from the analysis. Seventy-seven ESVs of putative pathogens were recorded (41 were identified to species level comprising 18 species, and 36 were identified to genus level comprising 19 genera; the most common species were Ilyonectria anthuriicola, Neonectria radicicola, Nectria ramulariae, and Olpidium brassicae). AM fungi were represented with 126 ESVs (12, 42, 47, 18, and 7 were identified to species, genus, family, order, and class level, respectively, comprising 5 species, 8 genera, 5 families, 3 orders, and 1 class, respectively; the most abundant families were Paraglomeraceae, Glomeraceae, and Acaulosporaceae). Saprotrophs were represented by 338 ESVs (155 and 183 were identified to species and genus level, respectively; the most abundant genera were Mortierella and Clavaria). Detailed functional data are not currently available for soil bacteria and protists. We therefore only assessed the composition of bacterial and protist communities, and the relative abundance and richness of well-known pathogenic oomycete ESVs (Pythium and Phytophthora genera), as predictors of plant-soil feedbacks. We found that the composition of bacterial and protist communities was strongly correlated with that of saprotrophic fungi (table S2). Only the latter was included in the subsequent path analysis as a representative characteristic of overall microbial community composition.

Sequences were categorized as specialist if a particular sequence was detected in soil samples conditioned by fewer than 5 species and generalist if occurring in soil of more than 10 plant species (of 14 species in total). For each soil sample, the relative abundance, ESV richness, and exponential Shannon diversity (effective species number) were calculated for each fungal functional group and specialist and generalist sequences within each functional group. Asymptotic exponential Shannon diversity was calculated for each fungal group using the package iNEXT in R (44) to ensure that higher diversity values were not due to higher sequence read numbers belonging to a particular fungal group in some of the soil samples. However, very similar results were obtained using raw and asymptotic diversity estimates. In addition, to test whether plant-soil feedback was related to the abundance of a host-specific pathogen, indicator analysis of fungal pathogenic sequences was performed using the package indicspecies in R (45), and the relative abundance of the most host-specific pathogenic sequence was calculated for soil samples conditioned by each plant species. Calculated microbial abundance and diversity estimates were loge transformed if necessary to satisfy the assumption of normal distribution before use in the models described below.

Note: The content above has been extracted from a research article, so it may not display correctly.



Q&A
Please log in to submit your questions online.
Your question will be posted on the Bio-101 website. We will send your questions to the authors of this protocol and Bio-protocol community members who are experienced with this method. you will be informed using the email address associated with your Bio-protocol account.



We use cookies on this site to enhance your user experience. By using our website, you are agreeing to allow the storage of cookies on your computer.