Data for: Environments and hosts structure the bacterial microbiomes of fungus-gardening ants and their symbiotic fungus gardens

We collected up to five ants from each colony of T. septentrionalis and M. turrifex; these ants were pooled into a single DNA extract. Ants were collected directly from inside fungus gardens with ethanol and flame-sterilized forceps. Roughly an equal number of colonies of both species from our samples of the East Texas and Central Texas populations were utilized (N = 13 for T. septentrionalis and N = 11 for M. turrifex). A small sample of fungus garden material was collected similarly with flame and ethanol sterilized forceps from the same garden chambers where the ants were collected. Seven soil samples were taken from within the nest fungal chambers (N = 4 from East Texas and N = 3 from Central Texas) to act as a negative control, and make sure the microbe communities observed with the ant or fungal samples were not a relic of soil contamination. All samples were preserved immediately upon collection in 100% ethanol. DNA sequences were amplified from ants, fungus, and soil using primers Gray28F 5’GAGTTTGATCNTGGCTCAG and Gray519R 5’GTNTTACNGGGCKGCTG that span the V1-V3 hypervariable regions of the 16S rRNA gene. They were processed using the HotStarTaq Plus Master Mix Kit (Qiagen, USA) under the following conditions: 94°C for 3 minutes, followed by 28 cycles of 94°C for 30 seconds, 53°C for 40 seconds and 72°C for 1 minute, after which a final elongation step at 72°C for 5 minutes was performed. After the samples were amplified and checked for adequate genetic yields, the sub-samples were pooled back together and purified using calibrated Ampure XP beads. The purified and pooled PCR product was used to create a DNA library and sequenced using the Illumina MiSeq platform in PEx300 mode. Initial sequence cleanup was performed by removing short sequences with <150 bp, sequences with ambiguous base calls, chimeras, sequences with runs exceeding 6 bp, and singleton sequences (Dowd et al., 2008). The resulting sequences were then inputted into Qiime2-2020.6, after having their barcodes and linker and reverse primers removed (Bolyen et al., 2019). Sequences were demultiplexed using the demux plugin (https://github.com/qiime2/q2-demux). The dada2 plugin was then used to merge the forward and reverse sequences, as well as perform basic quality control (Callahan et al., 2016). When using the dada2 plugin, sequences were truncated down to 260 base pairs as the average quality score dipped below 20 beyond this point. Taxonomy classification with 99% similarity was performed utilizing the SILVA 132_QIIME database (Quast et al., 2013; Yilmaz et al., 2014). To do this, we created our own taxonomic classifier using the “feature-classifier fit-classifier-naive-bayes” command and the SILVA database. This classifier was used to assign sequences a taxonomic classification using the feature-classifier plugin (Bokulich et al., 2018) with the “classify-sklearn” command. Sequences associated with mitochondria and chloroplasts were removed using the “qiime taxa filter-table “ and “qiime taxa filter-seqs” commands. To ensure an equal diversity comparison across all samples, the sequences of each sample had to be rarified to reduce the effects of samples with more sequences having more potentially unique sequences (McMurdie and Holmes, 2014). For this, a sampling depth of 1700 sequences per sample was utilized using the “qiime feature-table rarefy” command. An OTU table of the rarified samples was created by inputting a tabulated taxonomic bar plot, created using the “taxa barplot” command, of our sequences into Qiime2 View (https://view.qiime2.org).