Transcriptional responses of surface water marine microbial assemblages to deep-sea water amendment
Article first published online: 9 OCT 2011
© 2011 Society for Applied Microbiology and Blackwell Publishing Ltd
Special Issue: OMICS Driven Microbial Ecology
Volume 14, Issue 1, pages 191–206, January 2012
How to Cite
Shi, Y., McCarren, J. and DeLong, E. F. (2012), Transcriptional responses of surface water marine microbial assemblages to deep-sea water amendment. Environmental Microbiology, 14: 191–206. doi: 10.1111/j.1462-2920.2011.02598.x
- Issue published online: 2 JAN 2012
- Article first published online: 9 OCT 2011
- Received 1 April, 2011; accepted 27 August, 2011.
Fig. S1. Deep-sea water (DSW) amendment experimental set-up and sampling regime. The experiment was performed in parallel with the dissolved organic matter (DOM)-amendment experiment previously reported (McCarren et al., 2010).
Fig. S2. Phylogenetic tree (weighted neighbour-joining) of selected SSU rRNA gene sequences from proteobacterial type strains, and the near full-length SSU rRNA amplicon sequences obtained from flow cytometric sorting of the larger, higher-DNA-content population of cells present after DSW and DOM amendments.
Fig. S3. Putative taxonomic distribution of differentially represented NCBI-nr reference genes, in the cDNA data sets at each time point. cDNA reads were assigned to NCBI-nr reference genes using BLASTx, and hit counts were used to identify differentially represented nr reference genes using DEGseq (see Experimental procedures). Identified nr reference genes were then assigned to a putative taxon based on NCBI taxonomy. Upper panel shows the taxa distribution of DSW-enriched nr reference genes, and lower panel DSW-depleted nr reference genes. Both y-axes represent the fraction of differentially represented nr reference genes assigned to a specific taxon out of the total identified. Only taxon with more than 20 differentially represented nr reference genes were plotted, including: Prochlorococcus strains MIT9202, MED4, MIT9312, AS9601, MIT9515, MIT9301, MIT9215; Pelagibacter strains HTCC1062, HTCC7211 and HTCC1002; Alteromonas macleodii strains ‘Deep ecotype’, and ATCC27126.
Fig. S4. DNA sequence similarity of DSW-responsive, DOM-responsive and Control Alteromonas populations, to the reference A. macleodii genomes. The plots indicate the fraction of total aligned base pairs to the reference genome by Alteromonas DNA reads (y-axes) per unit of nt identity (x-axes).
Fig. S5. Gene content differences in the DSW- and DOM-responsive Alteromonas populations. ORFs of the two A. macleodii genomes were divided into shared, AltDE-specific and AltATCC-specific (see Experimental procedures). ORFs with significantly difference abundance in Alteromonas T5 DNA data sets were highlighted: red for DSW sample and blue for DOM sample.
Fig. S6. Relative representation of Prochlorococcus ORFs in DSW and Control cDNA samples. The Prochlorococcus strain AS9601 was used as a reference in this analysis. ORFs with significantly different representation in the treatment and control were marked in solid red circles. ORFs detected in the data sets but not considered as differentially represented were marked in open black circles. DEGseq was used for evaluating statistical significance (see Experimental procedures). Data for all time points were pooled in the figure.
Fig. S7. Prochlorococcus ORFs enriched in the DSW-amended sample, at least at one of the time points. ORFs were extracted from the Prochlorococcus AS9601 genome. For each time point, differentially represented ORFs were identified using DEGseq at q-value ≤ 0.01 (see Experimental procedures). Colour on the plot indicates the level of enrichment in the treatment, blue to red being from lower to higher.
Fig. S8. Flowgram showing criteria used for phage sequence identification. A more stringent set of criteria was used, because phage and host version of some protein-coding genes are indistinguishable at the amino acid level (Sullivan et al., 2006).
Fig. S9. Representation of cyanophage like sequences in the Control T5 and DSW T5 DNA samples. Also presented (separated by the dashed vertical line) is the relative abundance of cyanobacteria like sequences. Note differences in the scales of the two y-axes.
Fig. S10. Proposed model of microbial responses in simulated deep mixing events. Model modified from Karl and Letelier (2008). This conceptual model is intended to incorporate the patterns of viral DNA and RNA abundances we observed, into previous models of microbial nutrient response.
Table S1. Nutrient concentration in the microcosm. Data were obtained from the BLOOMER website at: ftp://ftp.soest.hawaii.edu/dkarl/cmore/water/bloomer1/bloomer1.gof. Due to data limitation, nutrient concentrations at 700 m depth were sometimes extrapolated from data available for nearby depths.
Table S2. Flow cytometric analysis of the Control and DSW amendment samples over time. Pro: Prochlorococcus. Total: total cell counts based on SYBR Green staining. Flow cytometry data were provided by Rex Malmstrom.
Table S3. Number of reads that were assigned as Alteromonas, which were defined as reads with a top BLASTx hit against the NCBI-nr database to Alteromonas, with a bits score cut-off of 50.
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