###Supplemental Data 1: Pipelines for QIIME2, PICRUSt2, and generation of the SILVA 16S rRNA gene taxonomy database #QIIME2 is run on a Linux-based virtual machine on the command line ##Main QIIME2 pipeline ##import using manifest qiime tools import \ --type 'SampleData[SequencesWithQuality]' \ --input-path manifest.tsv \ --output-path demux-single-end.qza \ --input-format SingleEndFastqManifestPhred33V2 #summarize qiime demux summarize \ --i-data demux-single-end.qza \ --o-visualization demux.qzv ##dada2 cleanup qiime dada2 denoise-single \ --i-demultiplexed-seqs demux-single-end.qza \ --p-n-threads 16 \ --p-trim-left 13 \ --p-trunc-len 181 \ --o-representative-sequences unfiltered-rep-seqs.qza \ --o-table unfiltered-table.qza \ --o-denoising-stats unfilter-denoise-stats.qza #tabulate results of dada2 qiime metadata tabulate \ --m-input-file unfilter-denoise-stats.qza \ --o-visualization unfilter-denoise-stats.qzv ##filter low-depth seqs qiime feature-table filter-samples \ --i-table unfiltered-table.qza \ --p-min-frequency 1500 \ --o-filtered-table filtered-table.qza qiime feature-table filter-seqs \ --i-data unfiltered-rep-seqs.qza \ --i-table filtered-table.qza \ --o-filtered-data filtered-rep-seqs.qza #summarize results qiime feature-table summarize \ --i-table filtered-table.qza \ --m-sample-metadata-file metadata.tsv \ --o-visualization filtered-table.qzv qiime feature-table tabulate-seqs \ --i-data filtered-rep-seqs.qza \ --o-visualization filtered-rep-seqs.qzv ##creation of SILVA database #Downloaded Silva release 138.1 - fasta files of database and taxonomy file #138.1-SSURef-trunc.fasta - seqs #pre-aligned and truncated version (unaligned regions cut out) #importing SILVA sequences qiime tools import \ --type 'FeatureData[AlignedSequence]' \ --input-path SILVA138.fasta \ --input-format AlignedRNAFASTAFormat \ --output-path silva_138.qza #importing Silva taxonomy qiime tools import \ --type 'FeatureTable[Taxonomy]' \ --input-format HeaderlessTSVTaxonomyFormat \ --input-path tax_silva_138.txt \ --output-path silva-138-taxonomy.qza #trimmed the database reads by 515F/806R primers qiime feature-classifier extract-reads \ --i-sequences silva_138.qza \ --p-f-primer GTGCCAGCMGCCGCGGTAA \ --p-r-primer GGACTACHVGGGTWTCTAAT \ --p-trunc-len 120 \ --p-min-length 100 \ --p-max-length 400 \ --o-reads silva-138-ref-seqs.qza #then trained the Qiime classifier on this database qiime feature-classifier fit-classifier-naive-bayes \ --i-reference-reads silva-138-ref-seqs.qza \ --i-reference-taxonomy silva-138-taxonomy.qza \ --o-classifier silva-classifier-qza ##QIIME2 taxonomy classification qiime feature-classifier classify-sklearn \ --i-classifier silva-classifier.qza \ --i-reads filtered-rep-seqs.qza \ --o-classification taxonomy.qza #view results qiime metadata tabulate \ --m-input-file taxonomy.qza \ --o-visualization taxonomy.qzv ##taxa barplots qiime taxa barplot \ --i-table filtered-table.qza \ --i-taxonomy taxonomy.qza \ --m-metadata-file metadata.tsv \ --o-visualization taxa-bar-plots.qzv ##PICRUSt2 pipeline qiime picrust2 full-pipeline \ --i-table filtered-table.qza \ --i-seq filtered-rep-seqs.qza \ --output-dir picrust2_out \ --p-threads 1 \ --p-hsp-method mp \ --p-max-nsti 2 \ --verbose #export qiime tools export \ --input-path ko_metagenome.qza \ --output-path ko_metagenome #convert BIOM to TSV biom convert -i feature-table.biom -o feature-table.tsv --to-tsv