An overview of the impact of HL on gene regulation for various functional categories is provided in Supplemental Table S1. In total, 762 genes showed differential regulation in response to HL that differed by at least 1.3-fold (P < 0.01). The fold change of 1.3× was experimentally verified using real-time PCR and, combined with the P-value determinants, can be confidently used as criteria to identify differential regulation of a gene (Supplemental Table S2). We attribute the confidence in a 1.3-fold cutoff to the significant improvement in data generation by using the custom-designed Agilent chips. A comparative analysis of differentially regulated genes obtained in this work with those identified by Hihara et al. (2001; Table I) showed that 638 regulated genes, including 277 genes designated as hypothetical or unknown in Cyanobase, were uniquely identified in this work; 124 regulated genes were identified in both studies, although some genes showed opposite regulation, whereas only 36 regulated genes, including 23 genes designated as hypothetical or unknown in Cyanobase (http://bacteria.kazusa.or.jp/cyano), were uniquely identified by Hihara et al. (2001). In addition, several genes present on various plasmids were strongly transcribed (Supplemental Fig. S2) and differentially regulated in response to HL (Fig. 2; Supplemental Table S3). The large number of uniquely identified genes, as well as the identification of transcripts from plasmids in this work, can be attributed directly to improvements in chip design and data generation. A number of differentially regulated genes showed statistically significant differences in the fold change depending on the probe's location on an individual open reading frame (ORF; Supplemental Fig. S3), suggesting that mRNA turnover plays a role in gene regulation during HL treatment. A large number of genes showed differential regulation immediately in response to HL that increased over 4 h and eventually decreased by 6 h (Supplemental Table S1). Thus, differential regulation of genes corresponded to the physiological response of Synechocystis observed by the F_v/F_m ratio in response to HL.

A single-copy gene (sll0220) encoding Gln:Fru-6-P amidotransferase (GFAT) was consistently up-regulated throughout HL treatment (cluster 8). GFAT catalyzes the formation of glucosamine-6-P from Fru-6-P (Fig. 4). It is the rate-limiting enzyme of the HS pathway, which is required for O-glycosylation of soluble proteins in eukaryotes and in some bacteria (Love and Hanover, 2005). A branch-point metabolite, UDP-N-acetyl-d-glucosamine (UDP-GlcNAc), produced in this pathway can either be utilized for the biosynthesis of peptidoglycan or can act as a substrate for O-linked GlcNAc transferase (OGT; Fig. 4). However, our data show that several genes involved in the biosynthesis of peptidoglycan were down-regulated in response to HL (Fig. 4). These results suggest that increased synthesis of UDP-GlcNAc as inferred by up-regulation of the GFAT gene is utilized by OGT for the addition of GlcNAc to substrate proteins. It is known that OGT glycosylates its substrates by responding to concentrations of UDP-GlcNAc (Love and Hanover, 2005). We further confirmed differential regulation of the GFAT gene during HL treatment by reverse transcription (RT)-PCR (Fig. 5A). Interestingly, steady-state transcript levels of the GFAT gene in control samples decreased with time, whereas cells transitioned to HL maintained steady-state transcript levels of the GFAT gene for the entire duration of HL treatment. We also found that Synechocystis contains at least two OGT proteins. An OGT encoded by the slr0626 gene shows similarity to GmaR, a recently identified OGT in Listeria monocytogenes (Shen et al., 2006). A second OGT encoded by the slr1816 gene shows similarity with SPINDLY, an OGT present in Arabidopsis thaliana, which is involved in GA-dependent signal transduction (Jacobsen et al., 1996). Additional evidence on the presence of HS pathway in Synechocystis comes from an identification of glycosylated proteins with monoclonal antibody CTD110.6 (Fig. 5C). The CTD110.6 antibody specifically recognizes O-linked GlcNAc residues (Comer et al., 2001). Four major proteins of apparent molecular mass 21, 25, 28, and 34 kD were detected by the CTD110.6 antibody on a western blot (Fig. 5C). In addition, several minor proteins of higher molecular mass could also be detected. It is clear from the comparison between the western blot and a Coomassie-stained SDS-polyacrylamide gel (Fig. 5B) that proteins identified by CTD110.6 are due to specific interactions because they do not belong to bands representing abundant proteins. These results together suggest that the HS pathway is present and active in Synechocystis. Furthermore, regulation of the gene for the rate-limiting enzyme GFAT by HL treatment suggests that the HS pathway may act as a regulatory pathway in Synechocystis as shown in eukaryotes (Love and Hanover, 2005).

Fluorescence induction kinetics at room temperature were performed on a dual modulation kinetic fluorometer (model FL-100; Photon Systems Instruments) interfaced with a computer.

Total RNA from Synechocystis cells was isolated using RNAwiz kit (Ambion) as described by the manufacturer, with some modifications. Briefly, 1 mL of prewarmed RNAwiz at 70°C was pipetted directly into the frozen cells and mixed quickly by vortexing. Following 10-min incubation at 70°C, 0.2 mL of chloroform was added, vigorously mixed, and incubated at room temperature for 10 min. The phase separation was achieved by centrifugation (15 min, 23,000g, 4°C). The aqueous phase containing RNA was transferred in a new Eppendorf tube and an equal volume of diethyl pyrocarbonate (DEPC)-treated water was added, extracted with water-saturated phenol, and finally precipitated by the addition of equal volume of isopropanol. Subsequently, total RNA were pelleted by centrifugation (20 min, 23,000g, 4°C), washed with 75% ethanol, and resuspended in 50 μL of DEPC-treated water. The quantity and quality of extracted RNA were determined spectrophotometrically (Nanodrop) at 260 and 280 nm and by Bio-Analyzer (Agilent).

Total RNA isolated from LL- and HL-treated cells was fluorescently labeled either with Cy3 or Cy5 using the MICROMAX ASAP RNA-labeling kit (Perkin-Elmer Life Sciences) according to the manufacturer's instructions. Two micrograms of total RNA, diluted in the ASAP labeling buffer on ice to a final volume of 19 μL and 1 μL of either Cy3 or Cy5 chemical-labeling reagent, respectively, was added to the reaction mixture. The reaction mixture was incubated at 85°C for 15 min in a thermal cycler (Eppendorf). The reaction mixture was transferred to ice and 5 μL of ASAP stop solution was added to the reaction mixture. The labeled RNA was individually purified using a PCR purification spin column (Zymo Research) and eluted with 20 μL of DEPC-treated water. The specific activity of the labeled RNA was determined in a Nanodrop.

The Synechocystis 11K oligo DNA microarray used in these studies was custom designed and constructed using Agilent noncontact inkjet technology (Agilent). This technology avoids the defects caused by the surface tension interaction with the microarray surface and results in the construction of microarray with more uniform and consistent features. The probes printed on these arrays are 60-mer oligomers that are known to yield excellent sensitivity and specificity compared to cDNA-based DNA microarray and 20-mer oligomer. Candidate oligonucleotides representing 3,459 genes in Synechocystis were selected from the 3′ end of genes. The selected probes were filtered according to optimal base-composition profiles and screened on the basis of predicted hybridization properties and potential cross-hybridization with other sequences. For genes >0.9 kb, an additional probe corresponding to the 5′ region of gene was selected. In the case of genes present on plasmids, target sequences were selected based on self-annotation (Kazusa annotation for plasmids was not available at the time of microarray design). The predicted ORFs from plasmids matched for >95% of currently annotated ORFs; some were represented by multiple oligos and some selected probes did not correspond to any ORF currently annotated in Cyanobase. We also randomly duplicated some probes to provide experimental evidence on intra-array variance. Each microarray slide consisted of two identical arrays consisting of 8,091 probes.

Fluorescently labeled probes were hybridized to Synechocystis 11K custom oligo DNA microarrays. For each array, we mixed 700 ng of Cy3- and Cy5-labeled RNA to a final specific activity of 50 pmol/μg of RNA. Cold RNA was added to adjust the total amount of RNA to 700 ng in the case of higher specific activity of labeled probe. Hybridization, scanning, and data extraction were performed by MOgene (www.mogene.com). Hybridization and wash processes were performed according to the manufacturer's instructions (Agilent). The hybridized microarrays were scanned using an Agilent Microarray Scanner (Agilent). Feature extraction software (Agilent) was used for the image analysis and data extraction processes using parameters optimized for prokaryotic arrays. The transcriptome data generated in this work has been submitted to the ArrayExpress database at the European Bioinformatics Institute (accession no. E-TABM-333).

The main behavioral patterns within the gene expression data were identified by cluster analysis using discretized expressions. This approach offers several advantages compared to other available methods for clustering. First, it does not require specifying the number of clusters beforehand because different patterns in the data are readily observed; second, it is less sensitive to the inherent noise in the data and, finally, it can group genes with some nonlinear relations. Gene expressions at any given time points were discretized to three levels, namely, 1 if log ratio value >0.3785 (up-regulated genes), −1 if log ratio value <−0.3785 (down-regulated genes), and 0 for genes not differentially regulated, to get a discretized vector for each gene. Genes with similar vectors were grouped together and put in a cluster. After an initial phase of clustering, we combined clusters that did not show significant differences among each other. Using this approach, the differentially regulated genes were grouped in 11 clusters that showed distinct behavioral patterns of genes. Those genes which did not fall into any of these categories were combined in cluster 12 (Fig. 2).

Total cell extracts from Synechocystis were isolated as described previously (Kashino et al., 2002). Proteins were electrophoresed on 16% SDS-PAGE containing 6 m urea as described previously (Kashino et al., 2002), transferred on a nitrocellulose membrane, and probed with monoclonal antibody CTD110.6 against O-linked GlcNAc (Covance). Proteins were visualized using a chemiluminescent detection system (Millipore).

Total RNA extracted from Synechocystis cells exposed to different light conditions were treated with RNase-free DNase I (Invitrogen) and used for RT reaction. The cDNA was synthesized using SuperScript II (Invitrogen) and random hexamer primers. The cDNA products were amplified by PCR using gene-specific primers (Supplemental Table S2) and analyzed by electrophoresis on 2% agarose gel. The RNase P gene was used as a control template.