Paired-end reads were assigned to samples based on unique barcodes and then trimmed of barcode and primer sequences. Paired-end reads were merged using FLASH (v. 1.2.7)35, and the resultant sequences were used as raw tags. Quality filtering of raw tags to obtain high-quality clean tags was performed according to the QIIME (v. 1.7.0)36 quality control protocol. Fungal tags were compared with the Unite database (v. 20140703), bacterial tags were compared to the SILVA Gold database (v. 20110519) using the UCHIME algorithm (v. 4.1)37 to detect chimaera sequences, and sequences flagged as chimaeras were then removed. The resultant high-quality sequences were used for further analyses. OTU clustering analysis was performed using the Uparse software (v. 7.0.1001)38. Sequences with ≥97% similarity in nucleotide identity were assigned to the same OTUs (Operational Taxonomic Units). Representative sequences for each OTU were then used for taxonomic annotation. For each representative fungal sequence, BLAST analysis was performed against the Unite database (v. 20140703)39 in QIIME (v. 1.7.0) to taxonomically annotate OTUs. For bacterial OTUs, the Greengenes database (http://greengenes.lbl.gov) was used with the RDP classifier (v. 2.2)40 algorithm for taxonomic annotation. Multiple sequence alignments were then conducted using MUSCLE (v. 3.8.31)41 in order to compare OTU distributions among samples. Read numbers were normalized to the sample with the least amount of sequences in order to standardize sequence numbers among samples.