Supplemental Information to: Metagenomic and metaproteomic analyses of Accumulibacter phosphatis enriched floccular and granular biofilm Jeremy J. Barr 1,2,3* , Bas E. Dutilh 4,5,6 , Connor T. Skennerton 2,7,10 , Toshikazu Fukushima 2,8 , Marcus L. Hastie 9 , Jeffrey J. Gorman 9 , Gene W. Tyson 2,7 , Philip L. Bond 2,3 1 San Diego State University, Department of Biology, San Diego, CA 92182, USA 2 The University of Queensland, Advanced Water Management Centre (AWMC), QLD 4072, Australia 3 Environmental Biotechnology Cooperative Research Centre (EBCRC), Sydney, Australia 4 Theoretical Biology and Bioinformatics, Utrecht University, Padualaan 8, 3584 CH, Utrecht, The Netherlands 5 Centre for Molecular and Biomedical Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Greet Grooteplein 28, 6525 GA, Nijmegen, The Netherlands 6 Department of Marine Biology, Institute of Biology, Federal University of Rio de Janeiro, Brazil 7 The University of Queensland, Australian Centre for Ecogenomics, School of Chemistry and Molecular Bioscience, QLD 4072, Australia 8 Division of Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan 9 Protein Discovery Centre, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, Herston, QLD 4006, Australia 10 Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA *Corresponding author. Jeremy J. Barr Department of Biology, San Diego State University, San Diego, CA 92182, USA
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Supplemental Information to:
Metagenomic and metaproteomic analyses of Accumulibacter phosphatis enriched floccular and granular biofilm Jeremy J. Barr1,2,3*, Bas E. Dutilh4,5,6, Connor T. Skennerton2,7,10, Toshikazu Fukushima2,8, Marcus L. Hastie9, Jeffrey J. Gorman9, Gene W. Tyson2,7, Philip L. Bond2,3
1 San Diego State University, Department of Biology, San Diego, CA 92182, USA2 The University of Queensland, Advanced Water Management Centre (AWMC), QLD 4072, Australia3 Environmental Biotechnology Cooperative Research Centre (EBCRC), Sydney, Australia4 Theoretical Biology and Bioinformatics, Utrecht University, Padualaan 8, 3584 CH, Utrecht, The Netherlands5 Centre for Molecular and Biomedical Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Greet Grooteplein 28, 6525 GA, Nijmegen, The Netherlands6 Department of Marine Biology, Institute of Biology, Federal University of Rio de Janeiro, Brazil7 The University of Queensland, Australian Centre for Ecogenomics, School of Chemistry and Molecular Bioscience, QLD 4072, Australia8 Division of Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan9 Protein Discovery Centre, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, Herston, QLD 4006, Australia10 Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA
*Corresponding author. Jeremy J. BarrDepartment of Biology,San Diego State University, San Diego, CA 92182, [email protected]
Supplemental Information – Methods.
Metagenome assembly, and genome binningThe raw sequencing data was imported into CLC genomics workbench 5 (www.clcbio.com) and
trimmed using a quality threshold of 0.05 and assembled using the CLC de novo assembler,
using the default settings. Metagenome assembly resulted in 117,544 and 152,528 contigs greater
than 200 bp for the Floc and Gran samples, respectively. Contigs were identified as putatively
originating from Accumulibacter if they contained blast alignment lengths greater than 2 Kbp to
Candidatus Accumulibacter phosphatis (NCBI id: NC_013194). These putative contigs were
further binned based on their coverage in the datasets. Raw metagenomic sequencing reads were
aligned to contigs using BWA 0.6.2 (Li & Durbin, 2009), and average coverage determined by a
identifier; protein annotation; COG category; protein sequence; Floc protein abundance; Gran
protein abundance.
SI Table 4. List of proteins that were continually increasing or decreasing in abundance
throughout the floccular-to-granular sludge transition period within the Gran reactor. Proteins
were using a Spearman’s rank correlation coefficient analysis of normalized spectra counts and
the time points collected during the transitionary period. Table showing increasing or decreasing
Spearman rank correlation; metagenome identifier number; IMG identifier; protein annotation;
COG category; protein sequence.
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Supplemental Information – References
Barr JJ, Cook AE, Bond PL. (2010). Granule formation mechanisms within an aerobic wastewater system for phosphorus removal. Appl Environ Microbiol 76:7588–97.
Dick GJ, Andersson AF, Baker BJ, Simmons SL, Thomas BC, Yelton AP, et al. (2009). Community-wide analysis of microbial genome sequence signatures. Genome Biol 10:85.
Li H, Durbin R. (2009). Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–60.
Wood DE, Salzberg SL. (2014). Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol 15:46.