Supplementary Material and Methods Yergeau et al. “Microbial expression profiles in the rhizosphere of willows depend on soil contamination” Ion Torrent 16S rRNA sequencing Reverse-transcriptase-PCR of the partial 16S rRNA was performed using the universal primers F343 (5’TACGGRAGGCAGCAG-3’) and R533 (5’- ATTACCGCGGCTGCTGGC-3’) containing the 10-bp multiplex identifiers (MID) and adaptor sequences for Ion Torrent sequencing described previously (Yergeau et al., 2012a; Bell et al., 2013). Reactions were performed using a Qiagen OneStep RT-PCR kit (QiaGen, Valencia, CA) in 25-μl volumes containing 2 μl of template RNA (50-100 ng/µl), 5µl of 5X reaction buffer, 0.6 μM of each primer, 0.4 mM of dNTPs and 1 μl of enzyme mix. Cycling conditions involved a reversetranscriptase step at 50°C for 30 min, an initial 15 min denaturing step at 95°C, followed by 15 cycles of 30 s at 94°C, 30 s at 55°C, and 60 s at 72°C, and a final elongation step of 10 min at 72°C. All PCR products were purified on agarose gels using the QIAquick Gel Extraction Kit (Qiagen) and quantified using the PicoGreen dsDNA quantitation assay (Invitrogen, Carlsbad, CA). All amplification reactions from the 24 different samples were pooled in an equimolar ratio and sequenced together. A total of 3.50x107 molecules were used in an emulsion PCR using the Ion OneTouch 200 Template Kit v2 (Life Technologies) and the OneTouch instruments (Life Technologies) according to the manufacturer’s protocol. The sequencing of the pooled library was done using the Ion Torrent Personal Genome Machine (PGM) system and a 316 chip with the Ion Sequencing 200 kit according to the manufacturer’s protocol. Sequences were binned by MID, after which MIDs were trimmed from each sequence. Sequences were trimmed when the average quality over a 5 bp window dropped below a Phred score of 20 or at the first occurrence of an “N” or of a >8bp homopolymer. Sequences shorter than 100 bp, were then filtered out of the dataset. Taxonomic identities were assigned to sequences using the “multiclassifier”, which is the local multi-sample version of the RDP Pipeline Classifier (http://pyro.cme.msu.edu/). Weighted-normalized Unifrac distances between each sample pair were calculated using the FastUnifrac website (Hamady et al., 2010) based on the GreenGene core dataset. For OTU calculations, sequence data were randomly normalized to 10,000 sequences and were then denoised using the procedure of Quince et al. (2011). The raw sequence data have been submitted to the NCBI SRA database under accession No. SRP028579 (NCBI BioProject PRJNA213915). illumina mRNA sequencing rRNA was subtracted following the protocol described by Stewart et al. (2010). After subtraction, a 227 bp control RNA transcribed from the pSPT18 vector (positions 2867-3104 and 1-70) was added in a 1:2000 ratio (on a nanogram basis) to the total rRNA-subtracted RNA. This mixture was then reversetranscribed using the SuperScript III kit (Invitrogen). illumina libraries were prepared following the protocol of Meyer and Kircher (2010), with indices 1 to 24 pooled together and sent for eight lanes of Illumina HiSeq 2000 paired-end 2x101 bp sequencing at McGill University and Génome Québec Innovation Center, Montréal, Canada. Resulting data were split into 384 files (24 samples x 2 reads x 8 lanes). The raw sequence data have been submitted to the NCBI SRA database under accession No. SRP028579 (NCBI BioProject PRJNA213915). Data from the different lanes were pooled together and the resulting 48 files were filtered in pairs using a custom-made Perl script. Sequences were trimmed at the first occurrence of a low quality base (below phred-like score of 20) or when an adapter sequence was found. Sequences shorter than 50 bp were filtered out and if one of the sequences of the pair was rejected, then the second one was also automatically rejected. The resulting high-quality sequences were submitted to MG-RAST 3.0 (Meyer et al., 2008) for automated annotation. Paired-end files were combined and overlapping reads were assembled within MG-RAST. Filtered and annotated sequence data are available through MG-RAST accessions 4512569-4512592. The number of sequences related to the pSPT18 vector in the filtered datasets was obtained by Blast using an e-value cutoff of 10-25 and this number was used to normalize the number of transcripts using the method of Moran et al. (2013). Quantitative reverse-transcriptase real-time PCR (RT-qPCR) RT-qPCR was performed in 20 µl volumes using the iScript One-Step RT-PCR kit with Sybr green (Bio-Rad Laboratories, Hercules, CA) on a Rotor-Gene 3000 apparatus (Corbett Life Science, Sydney, Australia), as previously described (Yergeau et al., 2009; 2010; 2012b). Reactions were set-up as per the manufacturer’s instructions, with 0.01 ng of total soil RNA and primers Eub338/Eub518 (Fierer et al., 2005). The amplification procedure was as follows: cDNA synthesis for 10 min at 50°C, reverse transcriptase inactivation for 5 min at 95°C, PCR cycling and detection (40 cycles) for 10 s at 95°C, 15 s at 53°C and 15 s at 72°C (acquiring signal at the end of this step). Standards were made from 10-fold dilutions of linearized plasmids containing a full length 16S rRNA gene that was cloned from an isolated bacterial strain. Several no-reverse-transcriptase and no-template controls were carried out and yielded no detectable signals. References Bell TH, Yergeau E, Maynard C, Juck D, Whyte LG, Greer CW (2013). Predictable bacterial composition and hydrocarbon degradation in Arctic soils following diesel and nutrient disturbance. ISME J 7: 1200-1210. Fierer N, Jackson JA, Vilgalys R, Jackson RB (2005). Assessment of soil microbial community structure by use of taxon-specific quantitative PCR assays. Appl Environ Microbiol 71: 4117–4120. Hamady M, Lozupone C, Knight R (2010). Fast UniFrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data. ISME J 4: 17-27. Meyer F, Paarmann D, D'Souza M, Olson R, Glass EM, Kubal M et al. (2008). The metagenomics RAST server - a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 9: 386. Meyer M, Kircher M (2010). Illumina Sequencing Library Preparation for Highly Multiplexed Target Capture and Sequencing. Cold Spring Harb Protoc doi:10.1101/pdb.prot5448. Moran MA, Satinsky B, Gifford SM, Luo H, Rivers A, Chan LK et al. (2013). Sizing up metatranscriptomics. ISME J 7: 237-43. Quince C, Lanzen A, Davenport RJ, Turnbaugh PJ (2011). Removing noise from pyrosequenced amplicons. BMC Bioinformatics 12: 38. Stewart FJ, Ottesen EA, DeLong EF (2010). Development and quantitative analyses of a universal rRNAsubtraction protocol for microbial metatranscriptomics. ISME J 4: 896-907. Yergeau E, Arbour M, Brousseau R, Juck D, Lawrence JR, Masson L et al. (2009). Microarray and real-time PCR analyses of the responses of high Arctic soil bacteria to hydrocarbon pollution and bioremediation treatments. Appl Environ Microbiol 75: 6258–6267. Yergeau E, Lawrence JR, Korber DR, Waiser MJ, Greer CW (2010). Meta-transcriptomic analysis of the response of river biofilms to pharmaceutical products using anonymous DNA microarrays. Appl Environ Microbiol 76: 5432-5439. Yergeau E, Lawrence JR, Sanschagrin S, Waiser MJ, Korber DR, Greer CW (2012a). Next-generation sequencing of microbial communities in the Athabasca River and its tributaries in relation to oil sands mining activities. Appl Environ Microbiol 78: 7626-7637. Yergeau E, Sanschagrin S, Beaumier D, Greer CW (2012b). Metagenomic analysis of the bioremediation of diesel-contaminated Canadian high Arctic soils. PLoS One 7: e30058.