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general may be a relatively more important metabolic activity in the night. Prochlorococcus marinus has recently been shown to exhibit diel patterns of amino acid uptake, with acquisition occurring predominantly at dusk (Mary et al., 2008). Our data agree with this and further suggest that heterotrophic taxa also devote a greater percentage of their transcriptome to transporting and synthesizing amino acids at night. Night-time accumulation of amino acids might be a mechanism for nitrogen storage by many organisms, particularly for P. marinus, which undergoes cell division at night. Histidine, the amino acid with the most consistent signal for synthesis at night by both autotrophs and heterotrophs (Fig. 7A and Fig. S1), is one of the most nitrogen-rich amino acids (only arginine has more amino groups). Overall, bacterial community investment in this oligotrophic ocean system was skewed towards energy acquisition and metabolism during the day, while biosynthesis (specifically of membranes, amino acids and vitamins) received relatively greater investments at night. Many microbial processes expected to be differentially expressed over a day/night cycle, such as photosynthesis, oxidative phosphorylation and proteorhodopsin activity, were indeed captured in the sequence data. Less anticipated processes that emerged included the utilization of C1 compounds, the uptake of polyamines and the degradation of aromatic compounds (Table 3). Other metabolic processes ongoing in this microbial community, although without statistical evidence for day/night patterns, included: use of nitrate and urea as nitrogen sources; use of phosphate, phosphonate and carbonoxygen-phosphorus (C-O-P) compounds as phosphorus sources; oxidation of reduced sulphur compounds; oxidation of carbon monoxide; and uptake of multiple trace metals (Table 3). This comparative analysis of microbial community transcripts has provided an inventory of ongoing metabolic processes, offered insights into their temporal patterns and supplied a new type of data for predictive modelling of environmental controls on ecosystem properties. Experimental procedures Sample collection Samples were collected at the Hawaiian Ocean Time-series (HOT) Station ALOHA, defined by the 6-nautical-mile radius circle centred at 22°45′N, 158°W in November, 2005 (HOT- 175). For RNA extraction, sea water was collected from a depth of 25 m using Niskin bottles on a conductivitytemperature-depth rosette sampler. A night sample was collected at 03:00 on 11 November 2005, and a daytime sample was collected at 13:00 on 13 November 2005. During HOT-175, the peak PAR level was at 12:00, with sunrise occurring around 07:00 and sunset just before 18:00. Sea water (80 l for the night sample and 40 l for the Comparative Metatranscriptomic Analysis 1371 day sample) was prefiltered through a 5 mm, 142 mm polycarbonate filter (GE Osmonics, Minnetonka, MN) followed by a 0.2 mm, 142 mm Durapore (Millipore) filter using positive air pressure. The 0.2 mm filters were placed in a 15 ml tube containing 2 ml Buffer RLT (containing b-mercaptoethanol) from the RNeasy kit (Qiagen, Valencia, CA) and flash-frozen in liquid nitrogen for RNA extraction. For DNA extraction, an additional 20 l of sea water were simultaneously filtered using the protocol outlined above at both time points. The 0.2 mm filters were placed in Whirlpack bags and flash-frozen. The total sampling time from initiation of collection until freezing in liquid nitrogen was approximately 1.5 h. We obtained ~1 mg of total RNA from 40 to 80 l of sea water. Following mRNA enrichment and amplification, 30–100 mg of mRNA was available for conversion to cDNA for sequencing. Typically, only 3–5 mg of DNA was required for pyrosequencing. RNA and DNA preparation DNA was extracted using a phenol : chloroform-based protocol (Fuhrman et al., 1988). Briefly, frozen filters inside Whirlpak bags were transferred to 50 ml Falcon centrifuge tubes. Ten millilitre extraction buffer [SDS (10% Sodium Doecyl Sulphate) : STE (100 mM NaCl, 10 mM Tris, 1 mM EDTA), 9:1] was added to the tubes and boiled in a water bath for 5 min. The extraction buffer was then removed from the tubes, placed into Oak Ridge round-bottom centrifuge tubes, to which 3 ml NaOAc and 28 ml 100% EtOH were added. Organic macromolecules were precipitated overnight at -20°C, before the tubes were centrifuged for 1 h at 15 000 g. The supernatant was decanted, and pellets dried for 30 min in the air. The pellets were resuspended in 600 ml deionized water, and sequentially extracted with 500 ml phenol, 500 ml phenol : chloroform : isoamyl alcohol (24:1:0.1), and 500 ml chloroform:isoamyl alcohol (9:1); after each extraction the organic phase was removed and discarded. The supernatant was removed into a fresh tube at the end of last extraction, amended with 150 ml NaOAc and 1.2 ml 100% EtOH, and precipitated overnight. The tube contents were then centrifuged at 15 000 g for 1 h, the supernatant decanted, and pellets dried in a speed vacuum dryer for 10 min. The DNA pellets were resuspended in 100 ml DNAse and RNAse-free deionized water (Ambion). RNA was extracted using a modified version of the RNeasy kit (Qiagen) that results in high RNA yields from material on polycarbonate filters (Poretsky et al., 2008). Frozen samples were first thawed slightly for 2 min in a 40–50°C water bath and then vortexed for 10 min with RNase-free beads from the Mo-Bio RNA PowerSoil kit (Carlsbad, CA). Following centrifugation for 5 min at 3000–5000 g, the supernatant was transferred to a new tube. Beginning with the RNeasy Midi kit, 1 vol. of 70% ethanol was added to the lysate and, in order to shear large-molecular-weight nucleic acids, the lysate was drawn through a 22-gauge needle several (~5) times. RNA extraction then continued with the RNeasy Mini kit according to the manufacturer’s instructions. Following extraction, RNA was treated with DNase using the TURBO DNA-free kit (Ambion, Austin, TX). Two methods were employed to rid the RNA samples of rRNA. The RNA was first treated enzymatically with the mRNA-ONLY © 2009 The Authors Journal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1358–1375
1372 R. S. Poretsky et al. Prokaryotic mRNA Isolation Kit (Epicentre Biotechnologies, Madison, WI) that uses a 5′-phosphate-dependent exonuclease to degrade rRNAs. The MICROBExpress kit (Ambion) subtractive hybridization with capture oligonucleotides hybridized to magnetic beads was subsequently used as an additional mRNA enrichment step. In order to obtain mg quantities of mRNA, approximately 500 ng of RNA was linearly amplified using the MessageAmp II-Bacteria Kit (Ambion) according to the manufacturer’s instructions. Finally, the amplified, antisense RNA (aRNA) was converted to double-stranded cDNA with random hexamers using the Universal RiboClone cDNA Synthesis System (Promega, Madison, WI). The cDNA was purified with the Wizard DNA Clean-up System (Promega). The quality and quantity of the total RNA, mRNA, aRNA and cDNA were assessed by measurement on the NanoDrop-1000 Spectrophotometer (NanoDrop Technologies, Wilmington, DE) and the Experion Automated Electrophoresis System (Bio-Rad, Hercules, CA). cDNA sequencing and quality control cDNAs from each sample (night and day) were sequenced using the GS 20 sequencing system by 454 Life Sciences (Branford, CT) (Margulies et al., 2005), resulting in 10 682 120 bp from 106 907 reads for the night sample and 13 255 704 bp from 133 515 reads for the day sample. The average sequence length was 99 bp. The sequences have been deposited in the NCBI Short Read Archive with the Genome Project ID #33463. rRNA identification and removal For rRNA sequence identification, the sequences were clustered at an identity threshold of 98% based on a local alignment (number of identical residues divided by length of alignment) using the program Cd-hit (Li and Godzik, 2006). Ribosomal RNA sequences were identified by BLASTN queries of the reference sequence of each cluster against the noncurated, GenBank nucleotide database (nt) (Benson et al., 2007) using cut-off criteria of E-value � 10 -3 , nucleic acid length � 69 and per cent identity � 40% previously established with in silico tests for rRNA sequence predictions of short pyrosequences (Frias-Lopez et al., 2008; Mou et al., 2008). We conservatively identified a sequence as rRNAderived and removed it from the analysis pipeline if any of the top three BLASTN hits were to an rRNA gene. cDNA sequence annotation The criteria for protein predictions generated using BLASTX against the NCBI curated, non-redundant reference sequence database (RefSeq) (Pruitt et al., 2005) were established with in silico tests to determine suitable cut-off limits for reliable functional prediction. For these tests, 100 arbitrarily selected, known functional gene sequences were fragmented into 20–500 bp fragments and analysed using BLASTX against RefSeq to determine if the best BLAST hit was to the correct gene function, excluding self-hits. Based on these analyses, the cut-off criteria for protein prediction were set as E-value < 0.01, identity > 40% and overlapping length > 23 aa to the corresponding best hit. Sequences with hits to RefSeq were assigned functional protein or pathway predictions based on the COG database (Tatusov et al., 2000) or KEGG database (Kanehisa and Goto, 2000). The cut-off criteria for functional protein prediction based on orthologous groups using BLASTX analysis against the COG database were established using the same in silico approach with 100 bp fragments of known functional genes as E-value < 0.1, identity > 40% and overlapping length > 23 aa to the corresponding best hit. The COG cut-off criteria were also applied to the KEGG database for pathway prediction because of the similarity in database size. Taxonomic binning of the sequences was carried out using MEGAN with the default settings for all parameters (Huson et al., 2007); this program assigns likely taxonomic origin to sequences based on the NCBI taxonomy of closest BLAST hits. The taxonomic affiliations of the putative mRNA sequences were predicted using MEGAN to the family level, and the top BLAST hit for any higher-resolution taxonomic assignments. All non-rRNA sequences that had no RefSeq hits were BLASTX-queried against the nr database as well as against CAMERA un-assembled ORFs predicted from the Global Ocean Survey reads (http://camera.calit2.net/ index.php) (Seshadri et al., 2007). Eukaryotic sequence annotation Eukaryotic transcripts were binned by MEGAN. Sequences were queried (BLASTX) against a curated database of protein sequences derived from all available complete eukaryotic organelle and nuclear genomes (currently, 46 eukaryotic genomes). Transcripts that matched a reference protein sequence with > 60% identity and an E-value < e -10 were retained and the reference protein for the cluster was used for functional annotation. Functional annotation was performed using Java-based Blast2go (Conesa et al., 2005) that annotates genes based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. 16S rRNA gene libraries PCR amplification of ribosomal DNA was carried out using primers 27F and 1522R (Johnson, 1994). The PCR conditions were as follows: 3 min at 96°C, followed by 30 cycles of denaturation at 95°C for 50 s, annealing at 58°C for 50 s, primer extension at 72°C for 1 min and a final extension at 72°C for 10 min. PCR products were cleaned using the QIAquick PCR Purification Kit (Qiagen) and multiple PCR reactions were pooled and cloned into pCR2.1 vector using the TOPO TA cloning kit (Invitrogen, Carlsbad, CA). PCR amplifications included standard no-template controls. Clones from each sample (192) were sequenced at the University of Georgia Sequencing Facility on an ABI 3100 (Applied Biosystems, Foster City, CA). Predicted highly expressed genes The PHX genes were determined for cultured representatives of three prokaryotic taxa that were well represented in the transcript libraries (Prochlorococcus, Roseobacter and © 2009 The Authors Journal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1358–1375
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