For each site and litter pair we collected a subset of 2-3 g wet mass of litter, a grab sample of soil, and a grab sample of periphyton for each site. All subsamples were preserved at -20°C until extraction, which took place up to a year after initial collection. Samples were sent to Novogene (Novogene Co. Ltd., Beijing, China) for the total RNA extraction followed by metatranscriptome sequencing. Briefly, the total RNA was extracted using TRIzol reagent (Rio et al. 2010) and the quality and quantity of the RNA were assessed using the Agilent 2100 bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) and Nanodrop ND-1000 (ThermoScientific, Waltham, MA, USA), respectively. After the total RNA samples passed the quality check, cDNA libraries were prepared from total RNA using poly(A) enrichment of the mRNA to remove rRNA resulting in the construction of 250-300 bp insert cDNA libraries and sequenced by paired-end (PE) sequencing (PE 2 × 150 bp) using an Illumina NovaSeq 6000 platform (NovaSeq Reagent Kits, Illumina, Inc., San Diego, CA, USA).
Raw reads were processed using the Simple Annotation of Metatranscriptomes by Sequence Analysis 2.0 (SAMSA2) pipeline (Westreich et al. 2018) with slight modification. Briefly, low quality bases were trimmed using Trimmomatic v0.39 (Bolger et al. 2014) and overlapping paired-end reads were merged into single sequences using PEAR v0.9.11 (Zhang et al. 2014). Ribosomal RNA reads were removed with SortMeRNA v2.1 (Kopylova et al. 2012) and the cleaned transcripts were annotated by DIAMOND v0.9.36 (Buchfink et al. 2021) against the National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database (O'leary et al. 2016) for taxonomic and functional characterization. The resulting annotation files were aggregated and merged with custom Python and R scripts included in the SAMSA2 pipeline (Westreich et al. 2018).
We selected n = 12 genes/gene families encoding for focal enzymes to investigate which are important to the breakdown of organic matter: Dioxygenases (associated with aerobic respiration), Sulfatases (associated with the release of sulfates from complex molecules), sulfite reductases (associated with sulfite reduction), methyl coenzyme M reductase and formylmethanofuran (associated with methanogenesis), nitrite reductases (associated with nitrite reduction), cellobiosidase, glucosidase, and xylosidase (associated with cellulose breakdown), phenol oxidase (associated with lignin breakdown), acid phosphatase (associated with phosphate acquisition in acidic environments), and alkaline phosphatase (associated with phosphate acquisition in basic environments; Table 1). For each gene/family of interest, we searched all annotated transcripts for all entries corresponding to that gene/family and combined all values for a total expression.
We selected n = 6 monophyletic microbial functional groups, representing sulfate reducers, sulfate oxidizers, methane oxidizers, methanogens, nitrite oxidizers, and ammonia oxidizers associated with sulfate and methane cycling. We filtered all annotated transcripts for all species with the following in the name: in the name: ‘desulfo’ for sulfate reducers, ‘sulfito’ for sulfite oxidizers, ‘methylo’ for methyl/methane oxidizers, ‘methano’ for methanogens, ‘nitro’ for nitrite oxidizers, and ‘nitroso’ for aerobic ammonia oxidizers.
References:
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Buchfink, B., K. Reuter, and H.-G. Drost. 2021. Sensitive protein alignments at tree-of-life scale using DIAMOND. Nature Methods 18: 366-368.
Kopylova, E., L. Noé, and H. Touzet. 2012. SortMeRNA: Fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics 28: 3211-3217.
O'leary, N. A. and others 2016. Reference sequence (RefSeq) database at NCBI: Current status, taxonomic expansion, and functional annotation. Nucleic Acids Research 44: D733-D745.
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