ChargeSwitch PCR Clean-Up Kit

Protocol tips

Upstream tips	Protocol tips	Downstream tips
The amount of agarose excised from the gel should be as small as possible.	Remove the flow-through by aspiration. Avoid contamination of the collection tube rim.

Upstream tips
The amount of agarose excised from the gel should be as small as possible.
Protocol tips
Remove the flow-through by aspiration. Avoid contamination of the collection tube rim.

Publication protocol

To provide a taxonomic baseline for the OTUs identified by ARISA, we further analysed a subset of samples from each species (electronic supplementary material, table S1). Because the same DNA extracts were simultaneously used for Bd quantification and community fingerprinting, we did not have enough material to sequence every sample from the ARISA dataset. We performed paired-end 16S microbial community sequencing [52] on the Illumina MiSeq platform (2×250 bp) at the Genomics facility at Cornell University. We only used forward sequence reads for phylotype assignment. We PCR-amplified the V4 region of the 16S ribosomal RNA using universal bacterial/archaeal primers 515F/806R [53]. Briefly, triplicate PCR-amplifications and negative (no template) controls contained 10 μl 5-Prime Hot Master Mix (5-Prime Inc.), 13 μl water, 0.5 μl of 10 μM solution of each primer and 2 μl undiluted DNA template or water. Thermocycler conditions included the following steps: denaturation for 3 min at 94°C; followed by 35 cycles of 45 s at 94°C, 60 s at 50°C and 90 s at 72°C; and a final extension for 10 min at 72°C. PCR products were visualized on a 1.5% agarose gel and quantified using a Qubit® double strand DNA high-sensitivity assay (Life Technologies, Inc.). We pooled 50 ng of all PCR products into a single vial and cleaned it using ChargeSwitch PCR clean-up kit (Invitrogen, Inc.) before sequencing. To ensure that our estimates of microbial diversity from field-collected swabs were not biased by Bd load, we blasted all the universal bacterial primer sets used in this study to the Bd genome and found no matches.

We analysed sequences and assigned phylotypes de novo using the quantitative insights into microbial ecology (QIIME) default pipeline v. 1.7.0 [54]. Briefly, sequences were filtered for quality, clustered into OTUs based on 97% sequence similarity with uclust using greengenes database (May 2013), aligned using PyNAST and used to infer a phylogenetic tree [54]. We filtered out phylotypes containing 0.001% of the total sequences [38], as well as samples with low coverage (less than 5000 sequences). We rarefied all samples to 5000 reads for alpha diversity analyses using 20 iterations.

We obtained a total of 1 179 178 16S rRNA tag sequence reads from 25 skin swab samples. This subset of samples achieved an average sequencing depth of 60 843 reads (min: 2823; max: 285 403) for adult E. coqui (N=15) versus 30 436 reads (min: 3048; max: 27 485) for juvenile frogs (N=6). Unfortunately, due to insufficient template material, we were only able to sequence four winter-collected L. yavapaiensis with an average of 20 976 reads (min: 7330; max: 43 217) per sample, precluding phylotype analyses between seasons. After applying the 0.001% abundance filter, we annotated 5206 unique phylotypes based on 97% sequence similarity with QIIME [54] from a total of 954 212 reads (electronic supplementary material, figure S1). We deposited sequences, phylotype table and mapping file in Dryad (http://dx.doi.org/10.5061/dryad.7v81b). Three individuals (one L. yavapaiensis, and an E. coqui adult and juvenile) were removed from analyses due to low coverage (more than 5000 reads).

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