Profiling Chlamydomonas Metabolism under Dark, Anoxic H2

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Profiling Chlamydomonas Metabolism under Dark, Anoxic H2‑Producing Conditions Using a Combined Proteomic, Transcriptomic, and Metabolomic Approach Venkataramanan Subramanian,*,†,‡ Alexandra Dubini,† David P. Astling,†,§ Lieve M. L. Laurens,† William M. Old,∥ Arthur R. Grossman,⊥ Matthew C. Posewitz,‡ and Michael Seibert†,‡ †

National Renewable Energy Laboratory, Golden, Colorado 80401, United States Department of Chemistry and Geochemistry, Colorado School of Mines, Golden, Colorado 80401, United States § Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, Colorado 80045, United States ∥ Department of Chemistry and Biochemistry, University of Colorado, Boulder, Colorado 80309, United States ⊥ Department of Plant Biology, Carnegie Institution for Science, Stanford, California 94305, United States ‡

S Supporting Information *

ABSTRACT: Chlamydomonas reinhardtii is well adapted to survive under different environmental conditions due to the unique flexibility of its metabolism. Here we report metabolic pathways that are active during acclimation to anoxia, but were previously not thoroughly studied under dark, anoxic H2-producing conditions in this model green alga. Proteomic analyses, using 2D-differential in-gel electrophoresis in combination with shotgun mass fingerprinting, revealed increased levels of proteins involved in the glycolytic pathway downstream of 3-phosphoglycerate, the glyoxylate pathway, and steps of the tricarboxylic acid (TCA) reactions. Upregulation of the enzyme, isocitrate lyase (ICL), was observed, which was accompanied by increased intracellular succinate levels, suggesting the functioning of glyoxylate pathway reactions. The ICL-inhibitor study revealed presence of reverse TCA reactions under these conditions. Contributions of the serine-isocitrate lyase pathway, glycine cleavage system, and c1-THF/serine hydroxymethyltransferase pathway in the acclimation to dark anoxia were found. We also observed increased levels of amino acids (AAs) suggesting nitrogen reorganization in the form of de novo AA biosynthesis during anoxia. Overall, novel routes for reductant utilization, in combination with redistribution of carbon and nitrogen, are used by this alga during acclimation to O2 deprivation in the dark. KEYWORDS: Chlamydomonas reinhardtii, hydrogen production, proteomics, TCA reactions, glyoxylate pathway, isocitrate lyase, amino acid synthesis



illuminated cultures that are deprived of sulfur.19,21−23 When purged with inert gas in the dark, C. reinhardtii activates fermentative pathways through the catabolism of starch, which leads to the accumulation of metabolites including formate, acetate, and ethanol, with the simultaneous production of H2 and CO2.5,13,24,25 Synthesis of H2 is believed to serve as an electron valve that allows for the oxidation of metabolic reductant.25 The hydrogenase enzyme obtains electrons from reduced [2Fe2S]ferredoxins, which receive electrons from pyruvate-ferredoxin oxidoreductase (PFR) after the conversion of pyruvate to acetylCoA and CO2. On the other hand, when C. reinhardtii cells are deprived of sulfur in the light, electrons are transferred to

INTRODUCTION Chlamydomonas reinhardtii is a soil and freshwater green alga with versatile metabolic capacities, allowing it to acclimate to different environmental challenges ranging from oxic to hypoxic, to anoxic conditions. This alga is a model system for a variety of molecular studies since it can be probed with a range of sophisticated genetic tools, its genome has been sequenced, and there is significant genomewide information based on several recent “omics” studies.1−16 In addition to being used for understanding biological processes like cell cycle control, photosynthesis, chloroplast biogenesis, and flagellar function, C. reinhardtii is also studied intensively for its ability to produce molecular H2, which is a potentially important renewable source of biofuel.17−20 Hydrogen production is catalyzed by [FeFe]-hydrogenases in this alga and is observed in cultures experiencing dark anoxia, as well as in © XXXX American Chemical Society

Received: April 2, 2014

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15 min, and 15000g for 15 min followed by storage at −80 °C for future use. Total protein content in the soluble extract was measured using a Bradford assay (Bio-Rad Laboratories, Inc.).

hydrogenases from ferredoxins that are reduced by photosystem I activity. Previous omics-based analyses of anoxia in C. reinhardtii have emphasized identification and characterization of genes and proteins participating in fermentative pathways and the subcellular localization of these proteins.5,13,15 These studies showed that several genes encoding proteins that function in fermentation and H2 production are tightly regulated at the transcriptional level.5,13 Furthermore, deletions of individual genes in specific fermentative pathways lead to the activation of new pathways. For example, deletion of hydrogenase genes in the hydEF strain leads to an increase in succinate production.5 Similarly, the pfl1 mutant, which lacks formate production, accumulates lactate as an electron sink.26 On the other hand, the adh1 mutant, which lacks alcohol production, accumulates lactate and glycerol.27 However, the changes in the activities of the tricarboxylic acid (TCA) reactions, glycolysis, and mitochondrial metabolism when cells experience dark, anoxic conditions have been unclear. In this report, anoxic metabolism and carbon flow downstream of glycolysis, in addition to nitrogen redistribution, were investigated. We further examined the functioning of the TCA- and glyoxylate-pathway reactions under dark, anoxic conditions by a combination of proteomic-, metabolite-, and transcript-based analyses.



2D-DIGE Analysis

Protein extracts from five independent biological replicates were concentrated using a Microcon centrifugation device with a molecular weight cutoff of 3000 Da (Millipore Corp.). Proteins were then precipitated using a 2D cleanup kit (GE Healthcare) and resuspended in buffer containing 30 mM Tris-Cl (pH 8.5), 7 M urea, 2 M thiourea, and 4% (w/v) 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate (CHAPS) for compatibility with the DIGE labeling kit. The labeling scheme used for DIGE analysis was as follows: 50 μg of protein each for light, aerobic, and dark, anoxic samples were labeled with Cy5 and Cy3 fluorescent dyes (GE Healthcare), respectively. Twenty-five micrograms of both protein samples were mixed and labeled with a third (Cy2) fluorescent dye to serve as an internal control. The three labeled samples (with Cy5, Cy3, and Cy2) were combined (150 μg protein total) to generate one biological sample, which was then mixed with 450 μL of Destreak rehydration reagent (GE Healthcare), 20 mM DTT, and 2% (v/v) ampholytes (pH 4−7). A pH 4.0−7.0 nonlinear immobilized pH gradient (IPG) strip (GE Healthcare) was passively rehydrated overnight in this sample protein mixture. Proteins were then separated in the first dimension using an Ettan IPGphor II manifold. Conditions used for the separation included an initial hold at 500 V for 1 h, a linear gradient to reach 1000 V in 1 h, a linear gradient to reach 8000 V in 3 h, and a hold period at 8000 V for 9 h. The total voltagehours applied was ∼82,000. The IPG strip was immediately transferred to −80 °C for storage before the second dimension electrophoresis was performed. Prior to separating the proteins in the second dimension, the IPG strip was thawed at room temperature and then incubated twice for 15 min each in two different equilibration buffers, EQ1 and EQ2. EQ1 contained 6 M urea, 30% glycerol, 75 mM Tris-Cl pH 8.8, 2% SDS, 0.02% bromophenol blue, and 2% DTT, while EQ2 contained the same components except that 2% DTT was replaced with 2% iodoacetamide. The IPG strip was then placed on a 12−14% SDS-polyacrylamide gel for separation of proteins in the second dimension. Gels were scanned using a Typhoon Imager at three different wavelengths (460 nm for Cy5, 480 nm for Cy3, and 710 nm for Cy2) and then treated with SYPRO Ruby protein stain (Life Technologies) for spot identification using LC−MS/MS. The three images obtained for each biological replicate were analyzed using DeCyder 7.0 software (GE Healthcare). Briefly, protein spots were detected, they were quantified after normalization of spot volumes to the internal standard, and the ratios of protein abundances between the proteins of the internal standard and those of each sample within the gel were generated using the Differential In-gel Analysis (DIA) module of the DeCyder software. Gel-to-gel comparisons were performed using the Biological Variation (BVA) module of the software. To eliminate the possibility of mistaking background noise for a spot, each spot was manually assessed and selected for further statistical analysis. Only those spots that were present in one or the other labeling condition (Cy3 or Cy5) and also present in the corresponding internal standard were confirmed as valid and used for further statistical analysis. A Student’s t test was performed on the two sets of quantified spot intensity values. Those spots showing a ratio of intensity of greater than or equal

MATERIALS AND METHODS

Culturing C. reinhardtii Cells for Anaerobic Induction

C. reinhardtii CC-425 (cw15, sr-u-60, arg7−8, mt+) cells were grown on Tris-acetate-phosphate (TAP) medium (pH 7.2), containing arginine (200 mg/mL) at 25 °C under continuous irradiance (80 μmol photon m−2 s−1 PAR from cool fluorescent lamps), to a chlorophyll concentration of 15−18 μg/mL (∼107 cells/mL).13 Five hundred milliliters of the culture was centrifuged at 3000g for 1 min, and the pelleted cells were resuspended in 50 mL of anaerobic induction buffer (AIB), containing 50 mM potassium phosphate (pH 7.0) and 3 mM MgCl2. Resuspended cells were then transferred to 100 mL glass bottles, which were crimp-sealed to prevent the entry of air and wrapped with aluminum foil to exclude light. The bottles were flushed with argon for 30 min and incubated in the dark for 4 h (t4) prior to harvesting cells for protein extraction. At the end of 4 h, the rate of H2 photoproduction was determined using a Clark-type electrode. Only those cultures that exhibited production rates of at least 50 μmol H2 mg Chl−1 h−1 were used for proteomic analyses (Supplemental Figure 1 in the Supporting Information). Cells from such anaerobically induced cultures (50 mL) were immediately pelleted by centrifugation at 10000g for 1 min and the pellets quickly frozen in liquid nitrogen. Prior to anaerobic induction, 50 mL of aerobically grown cultures were also centrifuged at 10000g for 1 min and the cell pellets frozen in liquid nitrogen for use as aerobic control samples (time = 0; t0). Protein Extraction for Proteomic Analyses

Frozen cell pellets derived from anaerobically induced cultures (described above) were thawed, resuspended in extraction buffer (10 mM Tris-Cl pH 7.5, 1 mM EDTA, 0.5 mM DTT) containing 0.1 mM phenylmethanesulfonyl fluoride (PMSF) and a 1:1000 dilution of protease inhibitor cocktail (Sigma Inc.), and then subjected to sonication using 10 intervals of 30 s duration each. The cells were kept on ice for 30 s between each 30 s sonication interval. Soluble protein extracts were clarified by sequential centrifugations at 6000g for 10 min, 8000g for 10 min, 10000g for B

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control of 1 × 106. The maximal injection time for the LTQ MS/ MS was 250 ms, with one microscan and automatic gain control of 1 × 104. The normalized collision energy was 35%, with activation Q = 0.25 for 30 ms, and the isolation width was 2.0 Da. MS/MS spectra were searched against JGI’s C. reinhardtii protein database (version 4.0) using MASCOT (Matrix Science), with ion score thresholds set to a false discovery rate (FDR) = 0.01 using inverted database searching. For searches of the LTQOrbitrap spectra, parent ion tolerances were set to 50 ppm on the monoisotopic peak, and the fragment ion tolerance was set to 0.6 Da, allowing 1 missed cleavage.

to ±1.5-fold and a p-value of less than 0.05 were considered to be statistically significant. Spot Analysis of 2D-DIGE Gels

For identification of differentially induced proteins, additional polyacrylamide gel electrophoresis (PAGE) (as described above) was performed with higher concentrations (1 mg) of protein. Spots that showed statistically significant ratios (greater than or equal to ±1.5 fold) were excised with a hand-held spot picker (GEL Company Inc.). The acrylamide containing the individual spots was then sliced into small pieces, washed twice with a 25 mM ammonium bicarbonate/50% acetonitrile (ACN) solution, and dried under vacuum. The dried gel pieces were resuspended in 12.5 ng/μL trypsin solution (containing 25 mM ammonium bicarbonate) and incubated at 37 °C overnight for enzymatic proteolysis. The digestion solution was removed from the sample, and the gel pieces were washed with a 50:50 mixture of ACN and 5% formic acid. The extracts were combined, dried under vacuum, and resuspended in 10 μL of 5% formic acid. The tryptic digests were further purified using ZipTips (Millipore Corp.) before being analyzed by LC−MS/MS. Identification of in-gel digested protein spots was performed on an Agilent LC/ MSD Trap XCT mass spectrometer coupled to an Agilent 1100 nano-HPLC system. Peptides were loaded onto a 15 cm × 75 μm (i.d.) Acclaim PepMap C18 column with 3 μm bead size (Dionex) and eluted with a linear gradient from 100% buffer A (0.1% formic acid) to 70% buffer B (0.1% formic acid, 80% ACN) in 60 min at a flow rate of 300 nL/min. For searches of the 2D gel ion trap spectra, parent ion tolerances were set to 1.2 Da on the monoisotopic peak, and the fragment ion tolerance was set to 0.8 Da, allowing for 1 missed cleavage site by the trypsin.

Statistical Analysis of Shotgun Proteomic Data

All data manipulations and computations were carried out using the R language and environment of statistical computing (http://www.R-project.org). First the data were normalized by dividing the spectral counts of each protein by the total counts for that sample. Proteins were discarded if the maximum spectral count was less than 5 as these values were considered unreliable. A preliminary principal component analysis revealed that there was significant variation between the different biological replicates performed on different days. To remove this day-today specific variation and to identify differentially regulated proteins, we used partial least squares (PLS) analysis with categorical variables for the oxic/anoxic conditions as the response variable.28 Determination of significant proteins was performed with Martens’s uncertainty test (jack-knifing) with the 95% confidence intervals.29 In addition, fold changes were calculated for each of these proteins, using normalized spectral count values. To further confirm differential regulation of proteins, we applied the significance analysis of microarrays (SAM) statistical test.30 To overcome day-to-day variation, we applied a two-class block design, with the day that the experiment was performed as the experimental block. Using a delta value of 0.2, we identified 33 proteins. The differences in many of the proteins that were found to be significant by SAM were also identified by PLS analysis.

Treatment of Protein Extracts for Shotgun Sequencing

Thawed protein extracts were concentrated using a Microcon centrifuge filter device with a molecular weight cutoff of 3000 Da. Fifty micrograms of the concentrated protein extract was diluted to 100 μL with 50 mM Tris-Cl buffer (pH 7.5) and reduced with 4 mM DTT for 10 min at 60 °C. This was followed by alkylation with 14 mM iodoacetamide at room temperature for 30 min. Finally, this reduced and alkylated protein solution was incubated with 1.0 μg of trypsin (Promega Corp.) overnight at 37 °C. The reaction was stopped with formic acid and the final treated sample was used for mass spectrometry.

Western Blot Analysis

Protein extracts (25 μg) were subjected to SDS-PAGE and the resolved proteins transferred to nitrocellulose membranes. Membranes were probed with monospecific rabbit polyclonal antibodies, and proteins were detected using a horseradish peroxidase (HRP) conjugated secondary antibody (GE Healthcare). Pyruvate formate lyase (PFL1) and alcohol/acetaldehyde dehydrogenase (ADH1) antibodies were kindly provided by the laboratory of Dr. A. Atteia (Marseille, France). Primary antibodies to malic enzyme (MME4), fumarate malate reductase (FMR1), and [Fe-Fe]-dependent hydrogenase (HYDA1) were custom-raised by Agrisera Inc. in rabbits. ICL1 (protein ID Cre06.g282800.t1.2) antibodies were custom-raised in rabbits by Proteintech Group, Inc. Antibodies against the Rubisco large subunit (RbcL), light-harvesting complex II binding proteins (LHCBM1 and 4), and ribosomal protein S1 were obtained from Agrisera Inc. Antibodies to human peroxiredoxin (PRX) were obtained from Santa Cruz Biotechnology, Inc.

Shotgun Proteomics

LC−MS/MS was performed on six protein samples (including three biological and two technical replicates each) using a LTQOrbitrap mass spectrometer (Thermo Scientific) interfaced with a nanoAcquity UPLC (Waters). Peptide mixtures were loaded onto a trap column (Waters C18 Symmetry, 20 mm × 180 μm i.d., 5 μm bead), washed, and placed in line with a BEH C18 reversed-phase column (25 cm × 75 μm i.d., 1.7 μm bead, 100 Å pore size; Waters). Peptides were eluted from the second dimension column with a linear gradient from 95% buffer A (0.1% formic acid) to 40% buffer B (0.1% formic acid, 80% acetonitrile [ACN]) in 120 min at a flow rate of 300 nL/min. Fragmentation MS/MS spectra using collision-induced dissociation were collected on the top 10 most intense precursor ions, enabling monoisotopic precursor and charge selection setting that excludes ions with an unassigned charge state. Dynamic exclusion settings were set to a 30 s repeat duration, 180 s exclusion duration, 20 ppm exclusion width, and a repeat count of 1. The maximum injection time for Orbitrap parent scans was 500 ms, allowing one microscan and an automatic gain

RT-qPCR

The reverse transcription reaction was performed using the Superscript III reverse transcriptase enzyme (Life Technologies) followed by a PCR reaction using DyNAmo HS (Finnzymes) as previously described in Mus et al.13 The RACK1 gene (originally CBLP) was used as an internal control for fold change (Ct value) C

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Total Protein, Nitrogen (N), Lipids, and Starch Analyses

calculations. The gene-specific primers used in this study and their sequences are presented in Supplemental Table 1 in the Supporting Information.

Total protein content was estimated by quantifying the total AA levels obtained using a Hitachi L-8800 citrate-based AA analyzer at the Proteomics Core Facility of the University of California, Davis. Cells were hydrolyzed with 6 N hydrochloric acid for 24 h at 110 °C. The individual AA content obtained from the analysis was added and considered as the total protein content of the cell. Cysteine and methionine were quantified separately by oxidation with performic acid prior to acid hydrolysis. Due to the lack of stability of tryptophan to acid hydrolysis, this AA could not be quantified. Hence the total protein content does not take tryptophan into account. Total N content of the cells was measured independently by combustion (Dumas method) of ∼10 mg of lyophilized biomass at Huffman Laboratories in Golden, Colorado. Elemental N data is expressed as weight % of dry biomass. Whole biomass lipid content was measured as fatty acid methyl esters (FAMEs) according to a published protocol.31 Briefly, 7 to 10 mg of lyophilyzed microalgal biomass (dried overnight at 40 °C under vacuum) was homogenized with 0.2 mL of chloroform:methanol (2:1, v/v), and the resulting solubilized lipids were transesterified in situ with 0.3 mL of 5% HCl in methanol (v/v) for 1 h at 85 °C in the presence of tridecanoic acid (C13) methyl ester as an internal standard. FAMEs were extracted with hexane (1 mL) at room temperature for 1 h and analyzed by gas chromatography-flame ionization detection (GC-FID) on an Agilent 6890N; DB-WAX column with dimensions 30 m × 0.25 mm i.d. and 0.25 μm film thickness. Individual fatty acids were quantified based on a 37-FAME calibration mixture after normalizing for the internal standard. The sum of the individual fatty acids was calculated and expressed as weight % of dry biomass. Starch concentration was determined using a Megazyme kit per the manufacturer’s protocol. In brief, 25 mg of lyophilized algal biomass was treated with 50 μL of 190-proof ethanol and 0.5 mL of dimethyl sulfoxide (DMSO) and then vortexed vigorously. This mixture was placed in a boiling water bath for 5 min. To this mixture were added 0.75 mL of 3-(N-morpholino)propanesulfonic acid (MOPS) buffer and 25 μL of thermostable alpha-amylase, and the samples were returned to the boiling water bath for 12 min. Samples were then incubated for 30 min in a 50 °C water bath after addition of 1 mL of sodium acetate buffer and 25 μL of amyloglucosidase. Samples were centrifuged, and the resulting supernatant was collected and analyzed for glucose by high performance liquid chromatography with refractive index detection (HPLC-RID). Glucose concentration was expressed as weight % of dry biomass.

Preparation of Samples for Intracellular Metabolite Analysis

Cultures were anaerobically induced as described earlier; however, in addition to t0 and t4, samples were collected at the time points t1 (1 h) and t2 (2 h) post-anaerobic induction. At each time point, 1 mL of culture was transferred with an Arpurged syringe into 3.0 mL of chilled 70% methanol and centrifuged at 10000g for 1 min, and the cell pellet was immediately frozen in liquid nitrogen. An exception to this was the aerobic sample at t0, where 2.0 mL of culture was quenched with 6.0 mL of chilled 70% methanol. Before extraction of metabolites, the cell pellet (obtained as described above) was thawed on dry ice. One milliliter of chilled (−80 °C) methanol:chloroform:water (M:C:W) solution in the ratio 10:3:1 (v:v:v) was added to the pellet, and the mixture was sonicated (3 cycles of 30 s each with 30 s intervals on dry ice) and centrifuged at 10000g for 1 min to remove the cell debris, and then 2 μL of 1 mg/mL tridecanoic acid (C13) was added to the supernatant as a retention index reference. The supernatant was dried under a nitrogen atmosphere and derivatized prior to gas chromatography−mass spectrometry (GC−MS) analysis as follows. The dried extracts were resuspended in 20 μL of methoxyamine hydrochloride (20 mg/mL in pyridine) for the aerobic samples (t0), and 40 μL for the anaerobic samples (t1, t2, and t4). All samples were incubated at 37 °C for 90 min and then derivatizated at 55 °C for 30 min using a mixture of 30 μL or 60 μL of N-methyl-N-(trimethylsilyl)trifluoroacetamide (MSTFA), containing 1% trimethylchlorosilane (TMCS, Sigma Inc.), for the aerobic and anaerobic samples, respectively. GC−MS Procedure for Quantification of Intracellular Metabolites

One microliter of derivatized sample was injected into the GC− MS instrument using a splitless injection technique. This instrument consisted of a 7683 series autosampler, a 7890A GC system, and a 5975C inert XL MSD (mass spectral detector) with Triple-Axis Detector from Agilent Technologies, Inc. The inlet temperature was set at 225 °C. The compounds were separated using a 30 m HP-5MS column (Agilent) with 0.25 mm i.d. and a 0.25 μm film thickness. Helium was used as the carrier gas at a flow rate of 1 mL/min. The GC parameters included 35 °C isothermal heating for 5 min followed by a 10 °C/min increase to 150 °C, a hold for 1 min at 150 °C, and a second ramping phase at 15 °C/min to 300 °C, followed by a final hold for 2.5 min at 300 °C. The MSD transfer line and the MS quadrupole were maintained at 280 and 150 °C, respectively. The MS source temperature was maintained at 230 °C. Compounds were detected using the scan mode with a mass detection range of 40 to 600 atomic mass units (amu). Chromatograms were analyzed for retention times using MSD Enhanced ChemStation data analysis software (Agilent Technologies), and the individual compounds were identified by comparison to the NIST mass spectral library. Compounds were quantified by generating calibration curves for individual compounds (obtained from Sigma, Inc.) over a defined concentration range. Unique m/z ions were selected for each compound to allow identification and quantification of AAs and other organic acids.

Inhibitor Treatments for Intra- and Extra- Cellular Metabolite Analyses

Cultures were anaerobically induced in the dark (as explained earlier). Immediately after the cells were washed in AIB, 1 mL of 10× concentrated cell suspension in AIB was transferred into chilled 70% methanol, the cells were pelleted by centrifugation at 10000g for 1 min, and the pellet was then frozen in liquid nitrogen for intracellular metabolite extraction (t0). For extracellular organic acid quantification, 1 mL of cell suspension was pelleted by centrifugation, and the supernatant was frozen at −80 °C for subsequent high performance liquid chromatography (HPLC) analysis. Cells were then treated with the isocitrate lyase (ICL) inhibitor, itaconic acid (Sigma, Inc.), at 2 mM, 10 mM, and 50 mM for intracellular metabolite quantification and at 2 mM concentration for extra-cellular metabolite quantification. The D

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Figure 1. Combined 2D profile of C. reinhardtii CC-425 proteins grown under light, oxic and dark, anoxic conditions. Fifty micrograms of protein extracted from light, oxic and dark, anoxic conditions were labeled alternatively with cy3 (green) or cy5 (red) dyes. A third sample containing equal amounts of both of these extracts was labeled with cy2 (yellow) dye. The three labeled samples were mixed together and separated in the first dimension using a pH 4−7 nonlinear IPG strip followed by separation in the second dimension using 12−14% SDS-PAGE gel. After the gel was visualized at 3 different wavelengths (one for each of the cy dyes) for 2D-DIGE analysis, it was stained with the fluorescent dye SYPRO Ruby (Life Technologies). Arrows represent the 19 spots that showed induction under dark, anoxic conditions, which were further analyzed by LC−MS/MS.

Five CC-425 cultures with H2-production rates of ≥50 (μmol H2 mg Chl−1) h−1 (Supplemental Figure 1 in the Supporting Information) were selected for protein extraction and proteomic studies.

inhibitor was dissolved in water and neutralized before addition to the cultures. Cells were harvested at 2 h (t2) and 4 h (t4) after inhibitor treatment under dark, anoxic conditions, followed by methanol quenching and freezing of the sample in liquid nitrogen for intracellular metabolite extraction (as done earlier). For extracellular organic acid analysis, samples were harvested at 1 h (t1), 2 h (t2), and 4 h (t4) as explained earlier in this paragraph. Untreated triplicate cultures were induced in parallel and were used as controls. All inhibitor experiments were performed with three different biological samples (biological triplicates). For the GC−MS analysis, four technical replicate samples were taken at each time point from each of the biological replicates; therefore, 12 samples were analyzed per time point. GC−MS analysis was performed as explained in Catalanotti et al.26 Extracellular organic acid analysis was performed using an Agilent 1200 series HPLC system as described previously.26 Fermentative H2 production was measured in the head space using an Agilent 7890A GC system. 400 μL of head space gas was analyzed using a Supelco column (60/80 mol sieve 5A 6 feet × 1/8 in.) coupled to a thermal conductivity detector (TCD).



Semiquantitative Analysis of Proteins Using 2D-DIGE

2D-DIGE analysis of proteins was performed using total soluble protein extracts from five independent biological replicates obtained from light, oxic- and dark, anoxic-treated cultures. Based on our analysis using the DECYDER 7.0 software, we detected 299 proteins on SDS-PAGE gels (Figure 1). Of these, the levels of 41 proteins increased (≥1.5-fold) and 69 decreased (≥1.5-fold) under dark, anoxic conditions, relative to light, oxic conditions. The remaining 189 proteins were within the cutoff limit of ±1.5-fold change. Of the 41 proteins that increased, we identified 19 by LC−MS/MS analysis. As shown in Table 1, the identified proteins included light-harvesting complex proteins, flagella proteins, ATP-synthase complex proteins, a glyoxylate cycle protein, nitrogen reorganization proteins, and putative redox proteins. The largest increase (5.7-fold) was observed for the flagella-associated protein, FAP278. Among the other most significantly upregulated proteins were ICL1, involved in the glyoxylate shunt pathway (4.0-fold upregulated); glutamine synthetases, GLN1 and GLN2/3, involved in the glutamine oxoglutarate aminotransferase (GOGAT) cycle (2.2- and 1.6fold upregulation, respectively); the redox-associated proteins, disulfide isomerase (PDI3) and peroxiredoxin (PRX2) (2.3- and 1.7-fold upregulation, respectively); and the light-harvesting proteins, LHCBM3, LHCA1, LHCBM2/7, LHCA5, and

RESULTS

Selection of C. reinhardtii Cultures for Proteomic Analysis

To investigate proteome rearrangements in cells acclimated to dark, anoxic conditions, we prepared samples for both 2D-DIGE and shotgun-based proteomic analyses as described in Materials and Methods. After 4 h of anoxic acclimation, cultures were tested for H2 photoproduction using a Clark-type electrode.13,32 E

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Table 1. Identification of Proteins in CC-425 Showing Increased Levels in Response to Dark Anoxiaa spot no.

protein ID (JGI ver 4.0)

1

190547

Cre03.g204550.t1.3

2

130316

g9830.t1

3 4

191668 195162

Cre06.g282800.t1.2 g5059.t1

5 6 7

184471 144935 184067

8 9

136069 82091

g6583.t1 Cre06.g304500.t1.2 Cre12.g548400.t1.2/ Cre12.g548950.t1.2 Cre03.g189950.t1.2 Cre11.g468300.t1.2

10 11 12 13

186299 185378 133971 184490

14

78348

Cre10.g425900.t1.2 g15623.t1 Cre02.g113200.t1.3 g6631.t1/Cre06.g283950.t1.2/ g6609.t1/g5059.t1/ cre06.g284200.t1.2 Cre17.g698000.t1.2

15 16 17

128523 155464 380461

Cre03.g190950.t1.2/g4512.t1 Cre02.g114600.t1.2 Cre12.g547400.t1.1

18

129468

19

344964

g13061.t1/g13061.t2/ Cre12.g530600.t1.3 Cre08.g362700.t1.2

mol wt (Da)

score

av fold change

T-test pvalue

33600

145

5.7

0.000016

30732

619

4.8

0.00052

45948 27437

669 427

4 3.2

0.000044 0.00061

25012 36139 26707

44 502 307

3.1 3.1 2.7

0.00066 0.000016 0.0011

63352 21907

1513 79

2.6 2.6

0.0011 0.0023

28399 15497 42716 27075

42 102 100 52

2.4 2.3 2.2 2.2

0.0016 0.00016 0.001 0.0013

ATP synthase F1F0 beta chain, mitochondrial precursor (ATP2) alpha tubulin 1 (TUA1) 2-cys peroxiredoxin (PRX2) glyoxylase/bleomycin resistance protein/predicted dioxygenase of estradiol dioxygenase family glutamine synthetase (GLN2/3)

61992

1522

2.0

0.00089

50213 21813 15820

426 149 117

1.7 1.7 1.7

0.0097 0.00027 0.0069

41741

83

1.6

0.000016

unknown protein

34614

47

1.5

0.0087

transcript ID (JGI ver 5.3.1)

description flagellar associated coiled-coil protein, adenosine kinase-like protein (FAP278) oxygen-evolving enhancer protein 1, chloroplast precursor (OEE1/PSBO) isocitrate lyase (ICL1) light-harvesting complex II chlorophyll a-b binding protein M3 (LHCBM3) light-harvesting protein of photosystem I (LHCA1) ZYS4, a zygote-specific protein light-harvesting protein of photosystem II (LHCBM 2/7) HSP70-HSP90 organizing protein (HOP1) Sar-type GTPase, involved in COP-II coat formation at the endoplasmic reticulum light-harvesting protein of PSI (LHCA5) thioredoxin/protein disulfide isomerase (PDI3) glutamine synthetase (GLN1) light-harvesting protein chloropyll a-b binding protein 2 (LHCBM4/6/7/9)

a

Protein spots were excised from 2D-PAGE gels followed by identification using LC−MS/MS. Fold changes were calculated after normalization of spot volumes to the internal standard as described in Materials and Methods. Proteins that showed ≥1.5-fold induction are shown. Spot numbers correspond to those in Figure 1.

LHCBM4/6/7/9 (3.2-, 3.1-, 2.7-, 2.4-, and 2.2-fold upregulation, respectively) (Table 1). Semiquantitative Analysis of Proteins Using Shotgun Proteomics

For the shotgun-based proteomic analysis, we used three biological replicates (1, 2, and 3, see Supplemental Figure 1 in the Supporting Information) with two technical replicates for each; thus, 6 samples were tested for each condition. Our LTQOrbitrap analysis detected a total of 1664 proteins under control conditions (light, oxic) and 1485 proteins in samples exposed to dark, anoxic conditions. The spectral counts varied from 1 to 40 counts for light, oxic samples, and from 1 to 28 counts for dark, anoxic samples. For statistical analysis, we only considered proteins with a spectral count greater than a threshold value of 5, resulting in 305 proteins. PLS regression and SAM were used to identify significantly regulated proteins. PLS showed that while the three samples used for the LC−MS/MS analysis exhibited significant differences when exposed to light, oxic and dark, anoxic conditions, captured by the first principal component, there was significant variation between the biological replicates, captured by the second principal component (Figure 2). Martens’s uncertainty test (jack-knifing) was used on the first principal component to identify statistically significant proteins. In parallel, SAM analysis was also used as an independent statistical test, using a block design to remove the unwanted variation among biological replicates. Proteins that showed differential regulation based on either of the statistical tests (SAM and Martens’s p-value) were considered to be highly significant (Table 2). Of the 305 proteins, 90 proteins were differentially

Figure 2. Scores plot from the partial least squares regression test (PLS) that shows differences between the three biological replicate samples. Component 1 captures the variation between the two tested experimental conditions (light, oxic and dark, anoxic), and component 2 captures the variation between biological replicates. Numbers in parentheses explain percent variation in each of the principal components. Filled circles, light, oxic samples; filled triangles, dark, anoxic samples. Color shades represent individual biological replicates with their technical replicates.

expressed in light, oxic and dark, anoxic conditions (data not shown). Of these, 17 proteins were found to be statistically significant based on Martens’s p-value test (Table 2). The F

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G

148487 184047

56005

Cre08.g380250.t1.2 Cre12.g544150.t1.2

Cre04.g223850.t1.2

DEH1*

CP12* CYN20-2

0.121

0.104 0.105

0.025 0.078

135713 136288

Group 6: Other Proteins Cre06.g307500.t1.1 Cre07.g339150.t1.1 LCIC** CPN60B2*

0.058

0.027

Group 5: Redox and Oxidative Stress Related Proteins Cre09.g391900.t1.3 195887 TRXH*

GCSL**/ DLD**

0.033 0.153 0.142 0.019 0.087 0.153 0.079 0.065

57890

Group 4: Ribosome- and Translation-Related Proteins Cre14.g621450.t1.2 183782 RPL5** Cre01.g047750.t1.2 146844 RPL18a* Cre16.g690500.t1.2 193640 NHP2* g877.t1/t2 195602 RPS2** g2858.t1 334749 unassigned* Cre03.g160500.t1.2 138493 unassigned* Cre06.g298650.t1.2 188942 unassigned* g4529.t1 140639 EIF3C*

g18113.t2

0.039

0.091

GLN2/3*Ψ

129468/136895

Cre12.g530600.t1.3/g13061. t1

GCSP**

0.06

DAE1*

150957

g5661.t1

Group 3: Glycine Metabolism Related Proteins Cre12.g534800.t1.1 136984

0.073

Group 2: Nitrogen Reorganization Pathway Related Proteins Cre06.g252650.t1.2 126865 LEU1S*

yes

yes yes

yes yes

yes

yes yes yes yes yes yes yes yes

yes

yes

yes

yes

yes

yes

SAMd

0.101

Martens’s pvaluec yes yes yes yes yes

protein nameb 0.066 0.047 0.056 0.031 0.033

protein ID (JGI ver 4.0)

Group 1: Central Metabolic Pathway Related Proteins Cre05.g234550.t2.1 24459 FBA3* Cre02.g141400.t1.2 196612 PCK1** Cre12.g526800.t1.2 158911 GND1b* Cre04.g214500.t1.3 196567 IDH3** Cre07.g357200.t1.2/g6328.1 185081_jgi|Chlre4| UGD1/2** 205498 Cre02.g120150.t1.2 206640 RBCS2*

transcript name (Phytozome ver 5.3.1)

small protein associating with GAPDH and PRK cyclophilin-type peptidyl-prolyl cis-trans isomerase activity ATP-dependent helicase activity

−1.46 (0.44)

low-CO2 inducible protein protein binding-ATP binding

thioredoxin-disulfide reductase activity

1.78 (0.64) 2 (0.39)

−2.28 (0.95) 1.7 (0.79)

1.32 (0.18)

structural constituent of ribosome structural constituent of ribosome ribonucleoprotein complex structural constituent of ribosome (RPS2) aminoacyl-tRNA ligase activity aminoacyl-tRNA ligase activity ATP-dependent helicase activity translation initiation factor activity

dihydrolipoyl dehydrogenase activity

−3.15 (1.7)

1.68 (0.28) −1.82 (0.67) −1.35 (0.31) −2.56 (2.3) 1.38 (0.17) 1.53 (0.23) −1.5 (0.26) −2.91 (1.8)

glycine dehydrogenase (decarboxylating) activity

1.57 (0.40)

glutamate-ammonia ligase activity

diaminopimelate (DAP) epimerase

−1.65 (0.66) 1.44 (0.21)

isopropylmalate dehydratase

ribulose-bisphosphate carboxylase activity

fructose-bisphosphate aldolase activity phosphoenolpyruvate carboxykinase (ATP) activity phosphogluconate dehydrogenase (decarboxylating) activity isocitrate dehydrogenase (NADP+) activity UDP-glucose dehydrogenase

GO function/description

1.52 (0.15)

1.96 (0.53)

1.26 (0.18) 1.33 (0.24) −1.27 (0.11) −6.36 (5.0) −2.21 (0.85)

fold change (SD)e

CO2 responsive proteins post translational modification/ chaperones general and unknown functions post translational modification/ chaperones transcriptional processing and modification

electron transport

ribosomal proteins ribosomal proteins ribosomal proteins ribosomal proteins translational regulation translational regulation translational regulation translational regulation

amino acid transport and metabolism electron transport

amino acid transport and metabolism amino acid transport and metabolism amino acid transport and metabolism

metabolism/fermentation

metabolism/fermentation metabolism/fermentation metabolism/fermentation metabolism/fermentation metabolism/fermentation

protein class

Table 2. In Depth Identification of Proteins in CC-425 Differentially Regulated in Response to Dark, Anoxic Acclimation Using Shotgun Mass Spectrometrya

Journal of Proteome Research Article

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147682 134171

196311 183027

195431 78205 188357

171374 195437 182408

Group 6: Other Proteins Cre14.g631900.t1.2 Cre06.g269950.t1.2

Cre07.g353450.t1.2 Cre12.g508000.t1.1

Cre05.g245950.t1.1 Cre06.g310750.t1.1 Cre10.g441400.t1.1

Cre07.g352800.t1.2 Cre13.g565850.t1.2 g5603.t1

unassigned** COPA1** METM**

DRP1** COPG1** NOP58**

ACS3** TIC40**

unassigned* CDC48**

protein nameb

0.01 0.027 0.012

0.044 0.044 0.046

0.037 0.024

0.105 0.044

Martens’s pvaluec

yes yes yes

yes yes yes

yes yes

yes yes

SAMd

predicted protein (related to RNA ligase) protein transporter activity methionine adenosyltransferase activity

−2.29 (0.95) −4.37 (3.8) −1.42 (0.21) -Inf −3.45 (2.0) −1.65 (0.08)

dynamin GTPase activity protein binding nucleolar protein, component of C/D snoRNPs

−2.23 (0.93) −2.45 (1.2)

GO function/description endoribonuclease ATP binding, nucleotide binding, nucleoside-triphosphatase activity, hydrolase activity catalytic activity (acetyl-CoA synthetase) not known

−1.55 (0.22) −1.35 (0.05)

fold change (SD)e

general and unknown functions post translational modification/ chaperones lipid transport and metabolism post translational modification/ chaperones general and unknown functions transport and traffic transcriptional processing and modification general and unknown functions transport and traffic metabolism/fermentation

protein class

a

Data has been obtained from three independent biological replicates. Only those proteins that were found to be statistically significant have been shown. b** represents proteins that were found to be statistically significant between the two tested conditions in the two statistical tests. * represents proteins that were found to be statistically significant between the two tested conditions in one statistical test. Ψ represents proteins that showed similar regulation pattern in 2D-DIGE analysis. cMartens’s p-values of ≤0.05 represent statistically significant changes in protein expression. d“Yes” and “no” under SAM analysis represent either statistically significant change in protein expression or not. ePositive fold changes represent proteins upregulated under dark, anoxic conditions, and negative fold changes represent proteins downregulated under dark, anoxic conditions. Numbers in parentheses represent standard deviation (SD). -Inf indicates that the protein was not detected in dark, anoxic condition, but was detected in light, oxic condition.

protein ID (JGI ver 4.0)

transcript name (Phytozome ver 5.3.1)

Table 2. continued

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conversion of isocitrate to α-ketoglutarate; UDP-glucose dehydrogenase (UGD1/2), which is involved in the conversion of UDP-glucose to UDP-glucuronic acid, a precursor for cell wall polysaccharide synthesis; 6-phosphogluconate dehydrogenase (GND1b), involved in the oxidative pentose phosphate pathway; the glycine cleavage system L protein (GCSL), the large subunit in the glycine cleavage system; and acetyl-CoA synthetase (ACS3), which is involved in the ATP-dependent addition of coenzyme A to acetate [Table 2 (groups 1, 3, and 6) and Figure 8].

independent SAM analysis revealed 35 statistically significant proteins. Interestingly, all 17 proteins that were identified by Martens’s p-value test also showed statistical significance by the SAM analysis test (Table 2). These 35 proteins, which showed statistically significant changes in either of the two tests, are shown in Table 2. Of these, 13 proteins were upregulated in response to dark, anoxic conditions, whereas 22 were downregulated under the same conditions in comparison with light, oxic conditions (Table 2). Fold changes for each of these proteins along with standard deviations (in parentheses) are shown (Table 2). Figure 3 shows a heat map representing the 35

Analysis of Intracellular Metabolite Levels in Response to Dark Anoxia

GC−MS analysis was performed to determine the intracellular metabolite levels of the TCA-cycle intermediates along with selected AAs and organic acids (Table 3). Citric acid marginally Table 3. Intracellular Metabolite Analysis Using GC−MSa concns of metabolites (μM)

Figure 3. Relative expression levels of proteins that showed statistically significant regulation under light, oxic and dark, anoxic conditions and their functional classification. Heat map shows expression levels of 35 proteins that were significantly different under the two tested experimental conditions. Each sample was analyzed in biological triplicate (labeled as 1, 2, 3) under each condition. Each colored rectangle (green or red shades) within a column represents an individual protein and its expression level in a particular sample. Red represents upregulation, and green represents downregulation. Lighter shades of red represent lower levels of induction, and lighter shades of green represent lower levels of downregulation. Wherever possible, the annotated gene names have been provided (Table 2). For unannotated proteins, the Phytozome ver 5.3.1 names have been provided (Table 2).

t0

t1

t2

t4

fumaric acid succinic acid malic acid citric acid

0.01 ± 0.00 0.09 ± 0.02 0.14 ± 0.02 0.06 ± 0.02

Organic Acids 0.03 ± 0.00 0.44 ± 0.03 0.10 ± 0.02 0.03 ± 0.00

0.03 ± 0.00 0.50 ± 0.03 0.15 ± 0.00 0.05 ± 0.02

0.04 ± 0.02 0.47 ± 0.18 0.16 ± 0.08 0.04 ± 0.01

glutamic acid serine glycine alanine

0.57 ± 0.13 0.03 ± 0.00 0.03 ± 0.00 0.09 ± 0.01

Amino Acids 1.57 ± 0.73 0.11 ± 0.02 0.15 ± 0.04 0.23 ± 0.23

1.94 ± 0.52 0.14 ± 0.02 0.28 ± 0.05 0.57 ± 0.04

1.88 ± 0.71 0.13 ± 0.01 0.28 ± 0.03 0.69 ± 0.17

lactic acid glycolic acid

1.39 ± 0.44 0.10 ± 0.01

Other Acids 0.50 ± 0.05 0.03 ± 0.00

0.58 ± 0.16 0.03 ± 0.00

0.75 ± 0.18 0.04 ± 0.00

a

Metabolite extracts were prepared by extracting C. reinhardtii cells in methanol:chloroform:water (10:3:1). Samples were derivatized as described in Materials and Methods. Metabolites were identified and quantified using GC−MS. Individual metabolites were quantified using calibration curves of defined standards. Data represents an average of a minimum of 9 replicate samples from a total of 12 tested replicate samples. t0, t1, t2, and t4 represent time 0 h (light, oxic), 1 h, 2 h, and 4 h post dark, anoxic induction, respectively.

decreased over the time course of 4 h, whereas malic acid levels decreased after an hour and regained their original levels after 4 h (Table 3). Fumaric acid and succinic acid showed ∼4- and 5-fold increases, respectively, after 4 h of induction (Table 3). Interestingly, the levels of glycine, serine, glutamic acid, and alanine increased over the course of 4 h of dark, anoxic conditions (Table 3). The intracellular levels of glycine and serine increased from 0.03 μM to 0.28 μM and 0.13 μM, respectively (Table 3). Alanine and glutamic acid were each elevated by nearly 8- and 3fold, respectively (Table 3). In addition to TCA-cycle intermediates and AAs, organic acid levels (lactic and glycolic acids) were also analyzed (Table 3). Levels of lactic acid, which is a fermentative product in the Chlamydomonas adh1 and the pf l1 mutants, and glycolic acid, which is a metabolite involved in photorespiration, were monitored as internal controls as their levels are expected to be lower in CC-425 cells under the tested conditions.26,27,33 As predicted, both of these organic acids showed a decrease during the course of the experiment (Table 3).

statistically significant proteins along with their functional categories, in each of the biological replicates under the two test conditions. Proteins that showed significant increase under dark, anoxic conditions included fructose-1,6-bisphosphate aldolase (FBA3), which is involved in starch/glucose mobilization; the small subunit of RuBisCO (RBCS2), which is involved in carbon fixation; phosphoenolpyruvate carboxykinase (PCK1), which is involved in the reversible conversion of oxaloacetate to phosphoenol pyruvate; GLN2/3 and isopropylmalate dehydratase (LEU1S), which are involved in nitrogen reorganization; and the glycine cleavage system P protein (GCSP), which is involved in glycine metabolism [Table 2 (groups 1, 2, and 3) and Figure 8]. Among the significantly downregulated proteins were isocitrate dehydrogenase (IDH3), which is involved in the I

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Protein, Lipids, and Starch Content of CC-425 Cells

Table 4. Overall Protein, Nitrogen (N), Fatty Acid, and Starch Content of CC-425 Cells under Light, Oxic and Dark, Anoxic Conditionsa

Whole cell analysis was performed to quantify the total protein, lipid, and starch content of CC-425 cells induced under dark, anoxic conditions in comparison to light, aerobically grown cells. All AAs showed an increase under dark, anoxic conditions in comparison to the light, aerobically grown cells (Figure 4A).

growth conditions (wt %)

light, oxic

dark, anoxic (4 h)

protein content N content lipid content starch content

48.56 ± 0.71 10.07 ± 0.17 9.34 ± 0.41 9.7 ± 0.26

52.54 ± 1.17 10.47 ± 0.13 10.04 ± 0.01 6.1 ± 0.98

a

Protein content was calculated by combining individual AA levels that were measured via whole cell amino acid analysis. The total N content was estimated using the Dumas method at the Huffman Laboratories, Golden, CO. Whole cell lipid content was measured as fatty acid methyl esters (FAME) after whole biomass transesterification and analysis by GC-FID. Starch content was measured after enzymatic hydrolysis and analysis of constituent glucose by HPLC. Data were obtained from three biological replicates.

Western Blot Analysis

In order to determine the levels of several proteins involved either directly or indirectly in acclimation, survival, and metabolism by C. reinhardtii under dark anoxia as well as to confirm the 2D-DIGE and the shotgun proteomic data, Western blot analysis was performed on total protein extracts. An independent SDS-PAGE gel stained with Coomassie Blue dye that contained equal amounts of protein was used as the loading control (Figure 5A). Further, we also separated increasing amounts of protein (25% to 150%) and ensured linearity of the Western blot signals using the RbcL antibody (Figure 5B). We observed that alcohol dehydrogenase (ADH1), malic enzyme (MME4), and fumarate-malate reductase (FMR), which are known to be regulated under fermentative conditions in C. reinhardtii,5 were upregulated under dark anoxic conditions (Figure 5C). Although ADH1 peptides were detected by LC− MS/MS, their spectral counts were below the cutoff limits, and hence they were not used for statistical analysis. On the contrary, MME4 and FMR1 peptides were not detected by either of the proteomic techniques. This also highlights the fact that mass spectrometry technique is less sensitive than the traditional Western blotting technique. We also observed that the PRX2 protein, which is involved in maintaining redox balance in the cell, was upregulated under dark, anoxic conditions (Figure 5C), although the primary antibody used was not able to differentiate between PRX1 and PRX2. Peroxiredoxins are involved in catalyzing peroxide decomposition, using electrons from thioredoxins, as observed in cyanobacteria.35 PRX2 levels were also found to be upregulated in the 2D-DIGE analysis (Figure 1, Table 1). On the other hand, PFL1 protein levels were not significantly affected, which is in accord with previous observations (Figure 5C).15,36 Furthermore, the large subunit of RuBisCO, RbcL, was also found to be upregulated under dark, anoxic conditions, based on interactions with anti-RbcL antibody (Agrisera) (Figure 5C). This is in contrast to what was observed under light, anoxic conditions with an 8 h induction in sulfurreplete TAP medium, where there was no significant change in RuBisCO protein levels.15 Interestingly, the RbcL protein level was shown to be severely affected by sulfur deprivation in the light, with extremely low levels observed within 24 h of sulfur deprivation.3,37 Hydrogenase protein (HYDA1) accumulation was found, as expected, to be elevated under dark, anoxic conditions (Figure 5C). This protein remained undetected in our global proteomic analysis techniques. We further examined the

Figure 4. Amino acid and fatty acid composition of CC-425 cells when transitioned from light, oxic (0 h) to dark, anoxic (4 h) conditions. C. reinhardtii cells were induced for 4 h under dark, anoxic conditions in AIB buffer. Cells were harvested postinduction and were dried under vacuum. (A) Amino acid composition was measured by acid hydrolysis of whole cells using a Hitachi L-8800 citrate-based AA analyzer. Absolute concentration was calculated after normalization using the internal control, norleucine. (B) Fatty acid composition was measured using GC-FID and is expressed on a dry weight basis after normalizing for the internal standard, tridecanoic acid methyl ester.

Consistent with this analysis was an independent N analysis that revealed a ∼4.0% increase in N content under dark, anoxic conditions (Table 4). This data was further extrapolated to calculate the total protein content using a nitrogen-to-protein conversion factor (% protein = % N × 4.78), which highlighted an increase of ∼8% under dark, anoxic conditions in comparison to the light, oxic cells (Table 4).34 There was a small increase (∼7%) in the total lipid content, measured as total fatty acid methyl esters of CC-425 cells grown under dark, anoxic conditions (Table 4). The lipid content increase is accompanied by a small increase in the primary fatty acid products of the biomass, namely, C16:0 (palmitic acid), C18:3n3 (linolenic acid), C18:1n9 (oleic acid), and C18:2n6 (linoleic acid), which indicates that core fatty acid biosynthesis pathways may be activated under these conditions (Figure 4B). On the other hand, total starch content of the cells decreased ∼37% under dark, anoxic conditions (Table 4), suggesting that the primary source of energy for anoxic metabolism is obtained from the breakdown of starch. Starch degradation could also provide the carbon skeletons for new AA and lipid biosynthesis. J

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Figure 5. Effect of dark anaerobiosis on proteins involved in fermentation, light-harvesting complexes, and other pathways. (A) Twenty-five micrograms of protein was separated on 10% SDS-PAGE gel and stained with Coomassie Blue dye. Lanes 1−3, independent biological replicates from light, oxic samples. Lanes 4−6, independent biological replicates from dark, anoxic samples. (B) Serial dilutions of total protein (25% to 150%) from light, oxic and 4 h induced dark, anoxic samples were separated on 10% SDS-PAGE gels and transferred to nitrocellulose membrane. Western blotting was performed using anti-RbcL antibody in order to determine the linearity of the signals. (C) Detection and quantification of the selected proteins was performed using Western blot analysis technique. Relative band intensities with standard deviations are shown on the right and represent dark, anoxic samples over light, oxic samples. Lanes 1−3, independent biological replicate samples under light, oxic conditions. Lanes 4−6, independent biological replicate samples under dark, anoxic conditions. ADH1, alcohol/acetaldehyde dehydrogenase; PFL1, pyruvate formate lyase; MME4, malic enzyme; FMR, fumarate malate reductase; ICL1, isocitrate lyase isoform 1; HYDA1, hydrogenase A1; LHCBM1 and LHCBM4, light-harvesting antenna complex II proteins; RPS1, ribosomal protein small subunit 1; RbcL, RuBisCO large subunit; PRX1/2, peroxiredoxin 1/2.

OGD1 (α-ketoglutarate dehydrogenase) as well as for PRK1 (phosphoribulokinase), GGAT (glutamate:glyoxylate aminotransferase), and SGA (serine:glyoxylate aminotransferase) are shown in Figure 6. The ICL1 transcript levels showed an increase under anoxic conditions, in comparison to light, oxic conditions (t0), which was consistent with 2D-DIGE analysis (Figure 6, Table 1). The transcripts from the IDH1 gene showed a slight increase (∼2-fold), as opposed to IDH2 and IDH3, which showed between 2- and 7-fold increases under dark, anoxic conditions over the 4 h induction period (Figure 6). The level of IDH3 protein declined [Table 2 (group 1)], while there was no significant change in the levels of IDH2 in the shotgun analysis (data not shown); the IDH1 protein was barely detectable under either condition (data not shown). Transcript levels of SDH, GGAT, and SGA decreased under dark, anoxic conditions, where as those of MDH1 and MDH5 showed an increase (from 2- up to 12-fold) during the dark, anoxic induction period (Figure 6). MDH1 protein levels showed a consistent increasing trend, while MDH5 was not detected in the shotgun analysis (data not shown). ACH1 and OGD1 transcript levels peaked at 2 h after induction (Figure 6). On the other hand, protein levels of ACH1 remained unchanged in the shotgun analysis (data not shown) whereas that of OGD1 had a decreasing trend at 4 h postinduction (data not shown).

levels of the ribosomal protein, RPS1. This protein was upregulated under dark, anoxic conditions in comparison to light, oxic conditions (Figure 5C). Among the other proteins examined, ICL1 was shown to be upregulated under dark, anoxic conditions, consistent with our 2D-DIGE (Figure 5C, Table 1). ICL1 protein was also found to have higher abundance in the shotgun analysis (data not shown). We also examined the levels of the light-harvesting complex proteins, LHCBM1 and LHCBM4. Both of these proteins were found to be upregulated under dark, anoxic conditions. Whereas LHCBM1 was not detected in 2D-DIGE analysis, LHCBM4 showed upregulation similar to what was observed in 2D-DIGE analysis (Figure 5C, Table 1). Transcriptional Levels of Differentially Regulated Proteins

In order to examine the correlation between transcript and protein levels, we performed reverse transcriptase quantitative PCR (RT-qPCR) analysis on selected genes (Figure 6). Specifically, those genes that coded for proteins showing differential regulation in response to dark, anoxic conditions in our proteomic analyses were tested. In addition we also determined the transcript levels of genes that were required to understand functioning of other metabolic pathways for which proteomic data were not available (Figure 6). Levels of transcript accumulation for the TCA and/or glyoxylate pathway genes ICL1, IDH1, IDH2, IDH3, MDH1, MDH5 (malate dehydrogenase), SDH (succinate dehydrogenase), ACH1 (aconitase), and K

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Figure 6. Altered level of transcripts observed during dark anoxic acclimation. RT-qPCR was performed using Brilliant II SYBR Green QRT-PCR Master Mix Kit (Stratagene Inc.). 100 ng of RNA that was extracted from CC-425 cells, induced under dark anoxia for 1, 2, and 4 h, was used for the RTqPCR reaction. Data was normalized to that of the internal control gene RACK1 (protein ID g6364.t1) and represents average of 3 independent biological replicates and two technical replicates each. Changes in transcript levels are presented as fold change relative to time t0 (i.e., light, oxic conditions). ICL1, isocitrate lyase isoform 1 (protein ID Cre06.g282800.t1.2); IDH1, isocitrate dehydrogenase isoform 1 (protein ID Cre17.g728800.t1.2); IDH2, isocitrate dehydrogenase isoform 2 (protein ID Cre02.g143250.t1.2); IDH3, isocitrate dehydrogenase isoform 3 (protein ID Cre04.g214500.t1.3); MDH1, malate dehydrogenase (protein ID Cre03.g194850.t1.2); MDH5, malate dehydrogenase (protein ID Cre09.g410700.t1.2); SDH, succinate dehydrogenase (protein ID g14920.t1), ACH1, aconitase dehydratase (protein ID Cre01.g042750.t1.2); OGD1, α-ketoglutarate dehydrogenase (protein ID Cre12.g537200.t1.3); PRK1, phosphoribulokinase (protein ID Cre12.g554800.t1.2); GGAT, annotated as alanine:glyoxylate aminotransferases (protein IDs Cre10.g451950.t1.2 and Cre06.g284700.t1.2); SGA, serine:glyoxylate aminotransferase (protein ID Cre01.g005150.t1.1).

Analysis of Intra- and Extra- Cellular Metabolite Changes in Response to an ICL Inhibitor, under Dark, Anaerobic Conditions

succinic acid levels relative to untreated cultures over a period of 4 h, suggesting the functioning of reverse TCA reactions under these conditions (Figure 7A). Additionally, glutamic acid and alanine levels also increased during the 4 h incubation period in the presence of the inhibitor (Figure 7A); glycine levels decreased when treated with 2 mM itaconic acid, whereas at higher concentrations, the change was minimal when compared with the untreated controls (Figure 7A). We also tested the effect of the ICL inhibitor on the levels of fermentative metabolites, namely, formate, acetate, and ethanol along with H2. Whereas there was hardly any effect of the inhibitor on the levels of extra-cellular acetate, ethanol, and H2, the levels of formate was found to be lower by ∼50% after 2 h treatment in comparison to that of the untreated control (Figure

In order to study the role of ICL in the glyoxylate cycle and the ability of C. reinhardtii to use TCA reactions under dark, anoxic conditions, cells were treated with the ICL inhibitor, itaconic acid, at three different concentrations. Treatment with this inhibitor was expected to block or lower the synthesis of glyoxylate and succinate, if the glyoxylate shunt is the only glyoxylate- and succinate-synthesizing pathway functioning under the tested conditions (Figure 8). Alternatively, if reverse TCA reactions are active, succinate production would still be observed. This treatment resulted in a 4-fold rise in intracellular L

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Figure 7. Effect of the ICL inhibitor itaconic acid on intra- and extra- cellular metabolite levels of CC-425. Cells were induced under dark, anoxic conditions and were then treated with the inhibitor at final concentrations of 2 mM, 10 mM, and 50 mM for 2 h (t2) and 4 h (t4) post addition of the inhibitor for intracellular metabolite quantification and with 2 mM inhibitor for extra-cellular metabolite quantification. (A) Internal metabolite analysis was performed on 12 replicate samples (3 biological with 4 technical replicates each) using GC−MS analyses of cell extracts obtained at those time points. An untreated culture (t0) was used as a control. Four metabolites were measured, namely, succinic acid, glycine, alanine, and glutamic acid. Values on the Y axis are arbitrary units, which represent relative abundances of individual compounds against the internal control, ribitol. (B) Extracellular metabolites were quantified by HPLC using standard curves generated with known concentrations of metabolites. Fermentative H2 of the head space was measured by gas chromatography.

7B). At 4 h post treatment, the levels of formate were 20% lower than those of the untreated controls (Figure 7B).

Here, our primary goal was to identify metabolic pathways that had not been detected or predicted in this organism under dark, anoxic, H2-producing conditions.

DISCUSSION In an effort to define pathways that are unique to anaerobic metabolism, we performed integrated proteomic and metabolomic analyses combined with the use of conventional molecular techniques. We used a combination of 2D-DIGE and semiquantitative shotgun-based techniques in our proteomic approach to identify global changes in the proteome. We hypothesized that the largest changes occurring at the level of protein accumulation should be detectable using 2D-DIGE, with confirmation derived from a shotgun proteomic approach, which can identify a much larger number of proteins than 2D-DIGE.

Upregulation of ICL1 in Dark, Anoxic Conditions



Of the upregulated proteins detected by 2D-DIGE analysis, we were able to identify 16 by LC−MS/MS analysis. The most highly upregulated of the metabolic pathway-related proteins was ICL1 with a 4.0-fold elevation in protein accumulation (Figure 1, Table 1), and a 1.34-fold increase based on shotgun analysis (data not shown). These results were also confirmed by Western blot analysis (Figure 5C). This predicted mitochondrial ICL1 protein is a redox-regulated protein whose activity is affected by glutathionylation.15,36−38 It has been observed in plants that glyoxysomes, which contain the fatty acid β-oxidation and M

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Figure 8. Metabolic pathways functioning under dark, anaerobic conditions in C. reinhardti CC-425. Glycolytic pathway, TCA-cycle, nitrogen reorganization/amino acid synthesis pathways, serine-isocitrate lyase pathway, glycine cleavage system, and C1-THFsynthase/SHMT pathway are shown. Proteins that showed differential induction in response to dark anoxia were identified by 2D-DIGE and shotgun mass spectrometry. Proteins in red indicate upregulation, and those in green indicate downregulation. Proteins in blue were not detected in our proteomic analysis but are predicted to be functioning based on transcript and metabolite analyses. Pathways in green indicate central metabolite pathways. Blue boxes represent amino acids. 1: Glycine is synthesized from glyoxylate by the action of the enzymes GGAT, AGT, or SGA. 2: Glycine is converted to glyceraldehyde-3-phosphate (gly-3P) via the serine-isocitrate lyase pathway and feeds into glycolysis. 3a: Glyoxylate can also be converted to formate, which could then recycle back into the serine-isocitrate lyase pathway via the c1-THF/SHMT pathway. 3b: Alternatively, formate that is generated from the breakdown of pyruvate (via PFL1) can be converted to serine in the presence of met THF and glycine. 4: Glycine cleavage system. 5: Regeneration of glutamate by transamination reactions. Glutamate is then converted to glutamine by the action of GLN1 and GLN2, or is used for the synthesis of proline (not shown). 6: Alanine synthesis pathway from pyruvate by alanine aminotransferase. *, proteins that were found to be statistically significant by one statistical test (Table 2). **, proteins that were found to be statistically significant by two statistical tests (Table 2). @, proteins that were found to show similar regulatory patterns in both 2D-DIGE and shotgun proteomic analyses (Tables 1 and 2).

glyoxylate-cycle enzymes, play a role in mobilizing the fat reserve in oil-rich tissue of seeds.39 It is also known that ICL-gene expression is repressed as the photosynthetic capacity of the plant increases and glyoxysomes are replaced by peroxisomes.40−42 Furthermore, ICL-gene expression is also known to play a role in senescence as shown by its transcriptional induction in plants in the absence of light, which was attributed to the transition of leaf peroxisomes into a glyoxysome-like type of microbody.39,40,43−45 It has been suggested that, under starvation conditions, the increase in glyoxylate enzymes converts the

acetyl-CoA (arising from the breakdown of lipids) to organic acids, which can subsequently be converted into sugars, as observed in fat-storing seeds following germination.44,46 This gluconeogenic reaction would require the presence of PCK or the malic enzyme. Interestingly, PCK1 and ICL1 were both found to be upregulated in our study [Tables 1 and 2 (group 1)]. We observed that both ICL1 and PCK1 are upregulated simultaneously as opposed to both enzymes being downregulated in the icl mutant.47 Malate synthase (MS), which is involved in the conversion of glyoxylate to malate, via N

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condensation with a molecule of acetyl-CoA, was detected in the shotgun analysis, although its expression levels remained the same under light, oxic and dark, anoxic conditions (data not shown). This parallel expression pattern of glyoxylate cycle and gluconeogenesis pathway proteins has also been observed in plants like cucumber.48,49 We tested activities of the enzymes ICL1 and MS using biochemical assays. Both the ICL and MS activities remained the same (within the margin of error) under light, oxic and dark, anoxic conditions (Supplemental Figure 2 in the Supporting Information). However, in contrast there was no decrease in the fatty acid content (Table 4), suggesting that breakdown of fatty acids is not a major source of acetyl-CoA, which results in the increase in ICL-mediated glyoxylate pathway reactions. It thus seems likely that the glyoxylate pathway reaction is primarily initiated by acetyl-CoA, via the breakdown of starch (Figure 8). This is used to bypass the CO2-generating steps of the TCA, thereby retaining the carbon, which can then be channeled into AA synthesis (Figure 8). A certain amount of increase in ICL could also be attributed to the metabolism of the residual acetate (via the glyoxylate pathway) that is left behind during the processing of cells for dark, anoxic induction (cells grown in TAP medium, containing acetate, were pelleted and resuspended in AIB buffer). We observed an increase in ICL1 transcript levels under dark, anoxic conditions in comparison to light, oxic conditions (Figure 6). A similar observation has been reported by Petridou et al., where wild-type cells accumulated higher levels of ICL mRNA in the dark.50 Whereas we exposed log-phase cells to anoxia (with argon purging for the first 30 min) in the dark, anoxic conditions were generated by argon purging for 8 h in the light, in Terashima et al.’s study.15 Hence, partial oxic conditions prevailed due to the activity of PSII in their study.15 Thus, microoxic condition along with the presence of light and nutrients most likely provided a different cellular redox status, compared to the current study, for expression and function of proteins like ICL, which probably had more complex (light, O2, and nutrient) regulatory features.

1)]. On the contrary the total lipid content of the cells remains unchanged/marginally increased under dark, anoxic conditions, suggesting that breakdown of lipids is not the source of acetylCoA in this organism (Table 4). If gluconeogenesis were still happening, it is likely not for the generation of starch. In this context the UGD1/2 proteins (Cre07.g357200.t1.2/g6328.1) showed upregulation, suggesting a possible diversion in the gluconeogenesis pathway upstream of glucose, leading to the generation of cell wall polysaccharides [Table 2 (group 1)]. Our data further suggests that AA synthesis is initiated under dark, anoxic conditions (Table 4, Figure 4A). The carbon skeleton is expected to be provided by intermediates of glycolysis and the TCA reactions. Despite the negligible activity of the TCA-cycle as evidenced by the lower levels of the NADP+dependent IDH3 protein (Table 2), as well as the lack of oxidative phosphorylation because of the dark, anoxic conditions, selected reverse TCA reactions are still functional based on the observation that, in the presence of the ICL inhibitor, itaconic acid, the intracellular levels of the TCA intermediate, succinic acid, remain high (Figure 7A). Glutamate levels also increased (Figure 7A) in the presence of the inhibitor, which is a transamination product generated from the TCA-cycle intermediate, α-ketoglutarate. It is apparent that metabolite flux is altered in the presence of the inhibitor, based on the fact that alanine levels (possibly generated from pyruvate) also increased (Figure 7A). This was also consistent with the reduced levels of formate, which is generated from pyruvate by PFL1, in the presence of the inhibitor (Figure 7B). H2 production remained unaffected at the tested inhibitor concentration (Figure 7B). Glycine levels were similar in the inhibitor-treated and untreated controls at higher inhibitor concentrations (10 mM and 50 mM), strongly indicating that the glyoxylate pathway was one of the multiple glycine-generating pathways in this organism (Figure 7A). The observed increase of AAs and succinic acid in the itaconic acid treated cells under dark, anoxic conditions parallels their increase in the icl mutant of C. reinhardtii, under mixotrophic conditions.47 Acetyl-CoA, which is generated from starch breakdown via glycolysis, is thus primarily a coproduct of the fermentative pathway arising from pyruvate by the action of PFL1, and pyruvate ferredoxin oxidoreductase, PFR1,13 which could further lead to the production and secretion of acetate and ethanol (Figure 7B).13 This fermentative pathway is used to generate ATP and balance the reducing equivalents generated in glycolysis.13 A small portion of acetyl-CoA is, however, utilized for the generation of new AAs, via the TCA reactions/glyoxylate pathway (Figure 8). Utilization of acetate as the sole carbon source that feeds into the glyoxylate pathway is not considered a potential source of acetyl-CoA since the cells are maintained in induction buffer, which does not contain acetate. Furthermore, the levels of acetyl-CoA synthetase (ACS3), which convert acetate to acetyl-CoA, were also found to decrease [Table 2 (group 6)]. It is interesting to note that the induction of ICL1 occurs in the light under anoxic, sulfur-replete conditions,15 as well as under dark, nutrient-depleted, anoxic conditions (this study, Table 1, Figure 5C); the latter is a H2-producing condition. Under the former condition, despite an accumulation of hydrogenase transcripts, there can be little H2 production, because O2, generated by the light-induced, water-splitting activity of PSII, would suppress the hydrogenase activity in vivo. On the other hand, under light, sulfur-deprived, anoxic conditions, the expression of ICL is downregulated at the transcript level and upregulated at the protein level (up to 32 h of sulfur

Generation of Acetyl-CoA and Implications of ICL in the Glyoxylate Pathway

Based on our data, ICL1 appears to function primarily in channeling acetyl-CoA through the glyoxylate shunt pathway for synthesis of AA precursors. This pathway bypasses a part of the TCA-cycle and produces glyoxylate and succinate (Figure 8). Intracellular levels of succinate were found to be higher following the initiation of induction under dark, anoxic conditions (Table 3). Succinate accumulation has also been observed in plants exposed to anoxic conditions.51 Glyoxylate in turn combines with another molecule of acetyl-CoA and generates malate, which then is converted to oxaloacetate by the enzyme malate dehydrogenase. Alternatively, glyoxylate can undergo a transamination reaction to form glycine [Figure 8 (pathway 1)], a discussion of which is presented in the following sections. Oxaloacetate could then be used either for the generation of aspartate and the suite of AAs derived from aspartate, fed into the reverse glycolysis pathway via the generation of phosphoenolpyruvate (PEP) by the reversible enzyme PCK1, or could enter another round of TCA-cycle/glyoxylate cycle to replenish TCAcycle intermediates. The reverse glycolysis pathway seems unlikely due to the fact that starch content decreased ∼37% during the course of the dark induction period (Table 4). Nevertheless, the gluconeogenesis protein, PCK1, was upregulated, suggesting a certain level of reverse glycolysis occurring in this organism under dark, anoxic conditions [(Table 2 (group O

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deprivation).3 This suggests a particularly different metabolic rerouting that C. reinhardtii uses in terms of starch breakdown to sustain ATP production and to maintain redox balance under the varying nutrient and O2 conditions.

A common RT-qPCR primer was designed to determine the level of overall expression of the GGAT homologues. Whereas transcript abundance for the GGAT homologues decreased under dark, anaerobic conditions, the level of SGA transcript was elevated (∼3-fold at 1 h postinduction) (Figure 6). Induction of SGA at the transcript level suggests the involvement of an aminotransferase (AT)-type enzyme (possibly by SGA) with a predictable glyoxylate transamination activity. Additional biochemical analyses are needed to determine whether the activity of ATs is regulated at the level of transcription or translation. Glycine, which can be converted to serine, could then enter glycolysis at the level of 3-phosphoglycerate via hydroxypyruvate, as observed in Shewanella putrefaciens [Figure 8 (pathway 2)].53,54

Functioning of Reverse TCA Reactions under Dark, Anoxic Conditions

The levels of citric acid, which appear early in the TCA-cycle, were lower throughout the induction period (Table 3). The intracellular fumarate levels increased during the induction period, an observation similar to that observed in rice under anoxic conditions (Table 3).52 The finding that malate levels remained the same (Table 3) suggests that the rate of conversion of glyoxylate and fumarate to malate is much lower than the rate of its utilization in the synthesis of succinate and/or oxaloacetate. The level of the SDH transcript (SDH converts succinate to fumarate) was low under dark, anoxic conditions (Figure 6), while based on Western blot analysis, levels of fumarate reductase (FMR1, Cre17.g696600.t1.3) (catalyzes the reverse reaction; fumarate conversion to succinate) was higher under the same conditions (Figure 5C). However, FMR1 peptides were not detected in either of the proteomics techniques. These findings could explain the accumulation of succinate under anoxic conditions, which was also confirmed by the inhibitor study (Figure 7A). This is also the case with the hydEF mutant of C. reinhardtii under dark, anoxic conditions, where FMR1 transcript levels were induced along with the concomitant increase in succinate levels.5 Although the intracellular succinate levels are high under dark, anoxic conditions in this study (Table 3), their levels are only a quarter of that secreted by the hydEF mutant under similar conditions.5 It thus could be inferred that fumarate is another pathway observed for the synthesis of succinate under dark, anoxic conditions as opposed to being used primarily as an electron sink, as is the case of the hydEF mutant.

Alterations in Transcript, Proteomic, and Metabolite Levels and Their Implications in the Glycine-Cleavage System

We observed an induction of glycine decarboxylase (GCSP), which is one of the components of the mitochondrial glycine cleavage system [Table 2 (group 3)]. The glycine cleavage system is responsible for the generation of a C1 (one carbon metabolite) pool. This system also generates CO2, ammonia, and NADH. The ammonia generated could be used for the synthesis of glutamine from glutamate by glutamine synthetases (GLN), which was supported by the higher levels of glutamine synthetases GLN1 and GLN2 observed under dark, anoxic conditions [Tables 1, 2 (group 2)]. The α-ketoglutarate (generated during the synthesis of glycine from glyoxylate and catalyzed by an AT enzyme) could be converted by GOGAT to glutamate in a ferredoxin dependent manner [Figure 8 (pathway 5)]. Consistent with this pathway, α-ketoglutarate levels were found to be below detectable levels by GC−MS analysis. Our inability to detect α-ketoglutarate is also consistent with the observed downregulation of the NADP+-IDH3 protein (also ∼3fold increase in the transcript levels as shown in Figure 6) in the shotgun analysis [Table 2 (group 1)]. The other two NAD+dependent isoforms, IDH1 and IDH2, were not detected in our shotgun analysis, although a small increase in IDH2 mRNA was observed based on RT-qPCR analysis (Figure 6). Glutamate can also be used for the generation of alanine [Figure 8 (pathway 6)], a storage form of pyruvate. The intracellular alanine levels were found to increase over 4 h (Table 3), which was also accompanied by a decrease in formate levels (which is a product of pyruvate), in the presence of the ICL inhibitor (Figure 7B), which suggests a role for AAT activity. A similar response is observed in plants exposed to anaerobic conditions.57,58 Induction of AAT1 in response to low CO2 conditions has also been observed in C. reinhardtii.3 The alanine synthesis pathway, using AAT1 (protein ID Cre10.g451950.t1.2), involves glutamate and pyruvate; α-ketoglutarate is a byproduct of this pathway that could be used for the regeneration of glutamate. It is important to note that AAT1 could have a dual role, first in transferring an amino group to glyoxylate for the generation of glycine (see the earlier section on serine-isocitrate lyase pathway) and second for transferring an amino group to pyruvate to generate alanine. Although AAT1 was detected in the shotgun analysis, its level was not significantly different between light, oxic and dark, anoxic conditions (data not shown). An interesting observation that was made was that an increase in carbon fixation enzymes, RBCS2 and RbcL proteins, was also observed by shotgun sequencing and by Western blotting, respectively (Table 2 and Figure 5C) under dark, anoxic conditions. The small subunit of RuBisCO has been shown to be induced under dark,

Metabolite- and Transcript-Level Changes and Their Implications in the Serine-Isocitrate Lyase Pathway

Internal metabolite analysis revealed an increased accumulation of glycine and serine under dark, anoxic conditions (Table 3, Figure 4A). The simultaneous induction of ICL at the translational level, the observed increase in succinate, and an increase in both glycine and serine suggest the presence of a serine-isocitrate lyase pathway in this alga. Organisms like Shewanella oneidensis, which can tolerate anaerobic conditions like yeast (Saccharomyces cerevisiae) and methylotrophs, can utilize glyoxylate.53−55 Glyoxylate is converted to glycine by the activity of the enzyme GGAT [Figure 8 (pathway 1)]. However, the JGI C. reinhardtii genome version 5.3.1 did not show any predicted gene models for GGATs. Therefore, we searched for GGAT in the Arabidopsis thaliana genome and used those sequences to identify homologous proteins in C. reinhardtii. Interestingly, we found two protein models (Cre10.g451950.t1.2 and Cre06.g284700.t1.2) in the alga that showed high similarity (E-values of 0.0 and 4.8 × 10−171, respectively) to GGATs from A. thaliana. They are annotated as alanine aminotransferases, AAT1 and AAT2. In addition to the GGAT homologues, there are one predicted protein model for alanine:glyoxylate aminotransferases (AGT, protein ID Cre16.g650650.t1.3) and one protein model for SGA (protein ID Cre01.g005150.t1.1) in C. reinhardtii. Furthermore, it has been shown in A. thaliana that glyoxylate aminotransferase reactions can be catalyzed by two different types of aminotransferase (AT) enzymes, one with SGA activity and the other with AGT activity.56 A similar redundancy in activities between the ATs in C. reinhardtii cannot be excluded. P

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conditions.59 Additionally, an increase in PRK1 mRNA levels (Figure 6) was also observed, with marginal increase in protein levels in the shotgun analysis (data not shown). These observations collectively suggest a small amount of C being assimilated in the form of CO2, the glycine cleavage system being a possible C source [Figure 8 (pathway 4)].

cell.69,70 A similar increase in total AAs has also been observed in this study, suggesting that Chlamydomonas possibly undergoes a similar physiological process to adapt to anoxic conditions. Possible Alternate Glyoxylate Utilization Pathways

Glyoxylate generated from isocitrate via the glyoxylate shunt pathway is converted to glycine by the action of ATs (GGAT/ SGA/AGT). The glycine can be converted to serine and finally to phosphoglycerate, which can then re-enter the glycolysis pathway [Figure 8 (pathway 2)]. This pathway has been considered as a mechanism of carbon fixation in the methylotrophic S. oniedensis.53−55 Furthermore, glyoxylate could be converted to formate spontaneously in the presence of H2O2, which could in turn be routed into the C1 pool via the C1-tetrahydrofolate (THF) synthase/serine hydroxymethyltransferase (SHMT) pathway [Figure 8 (pathway 3a)], as observed in the glycine-accumulating mutants of Hordeum vulgare and Amaranthus edulis plants.71 Notably, the C. reinhardtii genome contains the gene for the enzyme formylmethylTHF synthetase (protein ID g10042.t1) to convert formate to formylTHF (C1 pool), although the enzyme was not detected in our shotgun analysis. The C1 pool can enter the serine-isocitrate lyase pathway at the level of serine [Figure 8 (pathway 3a)]. Under dark, anoxic conditions, oxidative stress-related proteins, including catalase (enzyme that catalyzes the breakdown of H2O2) and superoxide dismutase (enzyme that can generate H2O2), are upregulated,5,13,15 suggesting the presence of H2O2 in the intracellular environment. This could be explained by the presence of residual oxygen within the cell during transitioning from oxic to hypoxic to anoxic phases. In support of this information, we also observed that antioxidant protein, peroxiredoxin PRX2 (Cre02.g114600.t1.2) (Table 1, Figures 1 and 5C), probably serving as a means to eliminate the toxic effects of the reactive oxygen species. These observations are consistent with previously published results.13,15 Recently it was also shown that PRX2 is specifically induced only during the night in C. reinhardtii and interacts with protein disulfide isomerase CrPDI2, a protein involved in folding of nascent proteins. The authors suggested a close coupling of redox processes and the circadian clock in this alga.72 Interestingly, in our study we found another member of the PDI family, PDI3 upregulated under dark, anoxic conditions (Table 1). A similar role of PRX2−PDI3 interaction under these conditions cannot be ruled out. A very recent study has shown a link between reactive oxygen species (ROS) and the synthesis of fatty acids in algae.73 The authors showed that fatty acid content increased in response to H2O2 treatment.73 Although the levels of fatty acids only marginally increased in our study (Figure 4B, Table 4), it is still consistent with the observed increase in oxidative stress related proteins, indicating the presence of H2O2 or related ROS within the cell. Finally, the formate that is generated by the action of PFL1 could be converted to formaldehyde by the action of formaldehyde dehydrogenase (protein IDs Cre12.g543400.t1.2 and Cre12.g543350.t1.3), which could then feed into the serineisocitrate lyase pathway [Figure 8 (pathway 3b)].

Metabolite- and Protein-Based Alterations and Their Implications in Nitrogen Reorganization

There are several lines of evidence that suggest initiation of nitrogen recycling in the form of AAs. First, the intracellular levels of glutamate/glutamine were higher (Figure 4A, Table 3), in addition to the higher protein levels of the GLN enzymes, GLN1 and GLN2/3 [Tables 1 and 2 (group 2)]. Second, the intracellular levels of alanine increased (Figure 4A, Table 3), possibly by the action of AATs in this organism. Alanine accumulation not only serves as a source of nitrogen but also serves as a source of carbon; under favorable conditions they could be converted back into pyruvate.60,61 Furthermore, alanine levels are suggested to regulate the level of pyruvate in plants,62 which is an activator of the alternative oxidase enzyme and is known to interfere with the hypoxia-induced inhibition of respiration.63−65 PEP, which originates during glycolysis (i.e., via starch breakdown), can also be used directly for the synthesis of aromatic AAs, namely, phenylalanine, tyrosine, and tryptophan, via the shikimate pathway. Incidentally, tyrosine and phenylalanine levels were found to be marginally higher in this study (after a 4 h induction) as well as in previous studies under dark, anoxic conditions (Figure 4A).26,27 Furthermore, leucine levels showed a significant increase (Figure 4A), which was consistent with the increase in the levels of one of the leucine pathway synthesis proteins, LEU1S [Table 2 (group 2)]. The increased glycolytic activity, as observed by the increase in glycolytic enzyme(s) [Table 2 (group 1) and data not shown] under nutrient starvation conditions (both C and N) along with the activity of specific TCA reactions (that could provide the carbon skeleton), explains the increases in AAs under these conditions. Specifically, increases in glutamate/glutamine (arising from αketoglutarate), serine/glycine (arising from 3-PGA and/or from glyoxylate), and leucine (arising from pyruvate via acetyl-CoA) levels further confirm this hypothesis (Figures 4A and 8, Table 3). It should be noted that anoxic induction was carried out in a closed system where no additional source of N was provided. Hence the increase in N in the form of AAs does not arise from an external N source. Finally, the ratio of AAs in the samples remained constant (data not shown), suggesting no recycling of AAs. Thus, the increase in AA content can only be attributed to the synthesis of new AAs under the induction conditions, which is consistent with our observations (Figure 4A, Table 3). A similar increase in AAs, particularly alanine, glycine, and serine, has been observed in seedlings of rice under anoxic conditions.52 The authors showed that addition of this AA combination (alanine, glycine, and serine) increased cell viability in wheat, which does not accumulate the three AAs under anoxic conditions. A similar function has also been suggested in mammalian cells exposed to hypoxic conditions.66−68 It can be concluded that the increase in these three AAs probably has a similar protective effect on the viability of C. reinhardtii under dark, anoxic conditions. Further, it has also been shown that the adaptation from oxic to anoxic conditions in rice involves an increase of total free AAs along with the ∼80% restoration of energy charge levels (i.e., the energy status of a biological cell), suggesting functioning of most cellular processes within the

Alterations in the Abundance of Proteins Involved in the Light Harvesting and Translational Machineries

Three proteins associated with light-harvesting complex II were identified as upregulated by 2D-DIGE analysis, under dark, anoxic conditions, which were also confirmed by Western blot analysis (Figure 5C). These include LHCBM2, LHCBM3, and LHCBM4/6/7/9 with 2.7-, 3.2-, and 2.2-fold increases in protein content, respectively (Figure 1). Two photosystem I lightQ

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harvesting proteins, LHCA1 and LHCA5, were also found to be upregulated by 2D-DIGE analysis (3.1- and 2.4-fold, respectively; Figure 1, Table 1). In addition, coproporphyrinogen oxidase (CPX1), which is involved in chlorophyll synthesis, also showed an increase, although not statistically significant (data not shown). These induction data could suggest that the organism is preparing its photosynthetic apparatus to function efficiently once the cells are exposed to light. Our data showed that there was a good correlation observed between the increase in transcript levels13 and protein accumulation in selective glycolysis/glyoxylate and nitrogen reorganization pathway genes, as well as oxidative stressresponse and chlorophyll synthesis genes (Tables 1 and 2, Figure 6),13 suggesting control of these proteins at the transcriptional level. On the other hand, proteins like IDH3, which showed higher transcript levels13 (Figure 6), showed significantly lower protein levels (Table 2), thereby suggesting selective translation of mRNAs under dark, anoxic stress conditions. A similar selective translation mechanism has been attributed to cytosolic ribosome modification in plants.74−78 It is therefore not surprising that ribosomal protein subunit levels are differentially regulated in C. reinhardtii as well (Figure 5C), a mechanism that might selectively control translation of some RNAs as opposed to the others under dark, anoxic conditions.



Article

ASSOCIATED CONTENT

S Supporting Information *

Supplemental Figure 1, photobiological hydrogen production rate of different CC-425 cultures. Supplemental Figure 2, activity assays for isocitrate lyase and malate synthase enzymes. Supplementary Table 1, list of primers used in this study. This material is available free of charge via the Internet at http://pubs. acs.org.



AUTHOR INFORMATION

Corresponding Author

*Tel: 303-384-7719. Fax: 303-384-7836. E-mail: venkat. [email protected]. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS This work was supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (M.S., A.D., M.C.P., and A.R.G.). We would also like to thank Ambarish Nag, Peter Lunacek, Monte Lunacek, and Christopher Chang for assistance with critical analysis of the proteomics data.



ABBREVIATIONS 2D-DIGE, two-dimensional differential in-gel electrophoresis; AA, amino acid; AAT(1/2), alanine aminotransferase; ACH1, aconitase; ACN, acetonitrile; ACS3, acetyl-CoA synthetase; ADH1, alcohol/acetaldehyde dehydrogenase; AGT, alanine:glyoxylate aminotransferase; AIB, anaerobic induction buffer; AP, alkaline phosphatase; APR, phosphoadenosine phosphosulfate reductase; ATP, adenosine triphosphate; BVA, biological variation; C, carbon; CBLP/RACK1, receptor of activate protein kinase C; CHAPS, 3-[(3-cholamidopropyl)dimethylammonio]1-propanesulfonate; CO2, carbon dioxide; CPX1, coproporphyrinogen oxidase; DIA, differential in-gel analysis; DMSO, dimethyl sulfoxide; DTT, dithiothreitol; EDTA, ethylenediaminetetraacetic acid; EQ(1/2), equilibration buffer; FAME, fatty acid methyl esters; FAP278, flagellar associated protein; FBA(1/ 2), fructose-1,6-bisphosphate aldolase; FBP2, fructose-1,6-bisphosphatase; FMR1, fumarate malate reductase; GC-FID, gas chromatography-flame ionization detector; GC−MS, gas chromatography−mass spectrometry; GCSL, glycine cleavage system L protein; GCSP, glycine cleavage system P protein; GGAT, glutamate:glyoxylate aminotransferase; GLN(1/2/3), glutamine synthetase; GND1b, 6-phosphogluconate dehydrogenase; GOGAT, glutamine oxoglutarate aminotransferase; H2, hydrogen; H2O2, hydrogen peroxide; HPLC-RID, high performance liquid chromatography-refractive index detector; HRP, horseradish peroxidase; HYDA1, hydrogenase; hydEF, hydrogenase assembly protein; ICL1, isocitrate lyase; IDH(1/2/3), isocitrate dehydrogenase; IPG, immobilized pH gradient; LC− MS, liquid chromatography−mass spectrometry; LEU1S, isopropylmalate dehydratase; LHCA, photosystem I lightharvesting protein A; LHCBM, light-harvesting complexes of photosystem II encoding genes; MDH(1/5), malate dehydrogenase; MME4, malic enzyme; MOPS, 3-(N-morpholino)propanesulfonic acid; MSD, mass spectral detector; MSTFA, N-methyl-N-(trimethylsilyl)trifluoroacetamide; N, nitrogen; NAD, nicotinamide dinucleotide; NIST, National Institute of Standards and Technology; O2, oxygen; OGD1, α-ketoglutarate

CONCLUSIONS

The unique adaptability of C. reinhardtii to survive and maintain its cellular activity under dark, anoxic H2-producing conditions is well-known, and fermentative pathways become active under these conditions.5,13,15 In the current study, we highlighted pathways stemming from glycolysis, particularly the metabolism downstream of acetyl-CoA synthesis, since acetyl-CoA is a key intermediate at which carbon flux is diverted to biofuels or biofuel precursors, including fatty acids, triacylgycerides, isoprenoids, and alkanes.79 Understanding the metabolic flux through this key intermediate is crucial for engineering better biofuel-producing algal strains. Interpreted in the light of proteomic, metabolomic, and transcript level data, we have now demonstrated the presence of nitrogen recycling and alternate carbon utilization pathways under dark, anoxic conditions. These pathways can act as additional electron sinks as well as in energy generation to ensure the survival of the alga under dark anoxia. In particular, strong evidence that shows the functioning of the glyoxylate pathway as well as reverse TCA reactions under dark, anoxic conditions has been identified, which helps in conserving carbon within the cell, while simultaneously reoxidizing NADH. Additionally, the presence of the serine-isocitrate lyase pathway has been reported to be active in this study. Finally, C. reinhardtii appears to cope with the reduced cellular energy levels under dark, anoxic conditions, by relying on glycolysis and fermentation in order to generate more ATP and regenerate NAD+, respectively, for continuity of catabolic processes. Future work would require measurement of energy carrier levels and their allocation to different processes within the cell over longer periods of anoxia, in order to understand the alteration of the alga’s metabolism in response to oxygen-deprived conditions. It would also be worthwhile to determine their levels under other H2-producing nutrient stress conditions. R

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Ballester, D.; Gonzalez-Halphen, D.; Hallmann, A.; Hanikenne, M.; Hippler, M.; Inwood, W.; Jabbari, K.; Kalanon, M.; Kuras, R.; Lefebvre, P. A.; Lemaire, S. D.; Lobanov, A. V.; Lohr, M.; Manuell, A.; Meier, I.; Mets, L.; Mittag, M.; Mittelmeier, T.; Moroney, J. V.; Moseley, J.; Napoli, C.; Nedelcu, A. M.; Niyogi, K.; Novoselov, S. V.; Paulsen, I. T.; Pazour, G.; Purton, S.; Ral, J. P.; Riano-Pachon, D. M.; Riekhof, W.; Rymarquis, L.; Schroda, M.; Stern, D.; Umen, J.; Willows, R.; Wilson, N.; Zimmer, S. L.; Allmer, J.; Balk, J.; Bisova, K.; Chen, C. J.; Elias, M.; Gendler, K.; Hauser, C.; Lamb, M. R.; Ledford, H.; Long, J. C.; Minagawa, J.; Page, M. D.; Pan, J.; Pootakham, W.; Roje, S.; Rose, A.; Stahlberg, E.; Terauchi, A. M.; Yang, P.; Ball, S.; Bowler, C.; Dieckmann, C. L.; Gladyshev, V. N.; Green, P.; Jorgensen, R.; Mayfield, S.; MuellerRoeber, B.; Rajamani, S.; Sayre, R. T.; Brokstein, P.; Dubchak, I.; Goodstein, D.; Hornick, L.; Huang, Y. W.; Jhaveri, J.; Luo, Y.; Martinez, D.; Ngau, W. C.; Otillar, B.; Poliakov, A.; Porter, A.; Szajkowski, L.; Werner, G.; Zhou, K.; Grigoriev, I. V.; Rokhsar, D. S.; Grossman, A. R. The Chlamydomonas genome reveals the evolution of key animal and plant functions. Science 2007, 318 (5848), 245−50. (12) Miura, K.; Yamano, T.; Yoshioka, S.; Kohinata, T.; Inoue, Y.; Taniguchi, F.; Asamizu, E.; Nakamura, Y.; Tabata, S.; Yamato, K. T.; Ohyama, K.; Fukuzawa, H. Expression profiling-based identification of CO2-responsive genes regulated by CCM1 controlling a carbonconcentrating mechanism in Chlamydomonas reinhardtii. Plant Physiol. 2004, 135 (3), 1595−607. (13) Mus, F.; Dubini, A.; Seibert, M.; Posewitz, M. C.; Grossman, A. R. Anaerobic acclimation in Chlamydomonas reinhardtii: anoxic gene expression, hydrogenase induction, and metabolic pathways. J. Biol. Chem. 2007, 282 (35), 25475−86. (14) Nguyen, A. V.; Thomas-Hall, S. R.; Malnoe, A.; Timmins, M.; Mussgnug, J. H.; Rupprecht, J.; Kruse, O.; Hankamer, B.; Schenk, P. M. Transcriptome for photobiological hydrogen production induced by sulfur deprivation in the green alga Chlamydomonas reinhardtii. Eukaryotic Cell 2008, 7 (11), 1965−79. (15) Terashima, M.; Specht, M.; Naumann, B.; Hippler, M. Characterizing the anaerobic response of Chlamydomonas reinhardtii by quantitative proteomics. Mol. Cell. Proteomics 2010, 9 (7), 1514−32. (16) Zhang, Z.; Shrager, J.; Jain, M.; Chang, C. W.; Vallon, O.; Grossman, A. R. Insights into the survival of Chlamydomonas reinhardtii during sulfur starvation based on microarray analysis of gene expression. Eukaryotic Cell 2004, 3 (5), 1331−48. (17) Ghirardi, M. L.; Posewitz, M. C.; Maness, P. C.; Dubini, A.; Yu, J.; Seibert, M. Hydrogenases and hydrogen photoproduction in oxygenic photosynthetic organisms. Annu. Rev. Plant Biol. 2007, 58, 71−91. (18) Melis, A.; Happe, T. Hydrogen production. Green algae as a source of energy. Plant Physiol. 2001, 127 (3), 740−8. (19) Melis, A.; Zhang, L.; Forestier, M.; Ghirardi, M. L.; Seibert, M. Sustained photobiological hydrogen gas production upon reversible inactivation of oxygen evolution in the green alga Chlamydomonas reinhardtii. Plant Physiol. 2000, 122 (1), 127−36. (20) Seibert, M.; King, P.; Posewitz, M. C.; Melis, A.; Ghirardi, M. L. Photosynthetic water splitting for hydrogen production. In Bioenergy; Wall, J., Harwood, C., Demain, A., Ed.; ASM Press: Washington, DC, 2008; pp 273−91. (21) Ghirardi, M. L.; Zhang, L.; Lee, J. W.; Flynn, T.; Seibert, M.; Greenbaum, E.; Melis, A. Microalgae: a green source of renewable H(2). Trends Biotechnol. 2000, 18 (12), 506−11. (22) Happe, T.; Kaminski, A. Differential regulation of the Fehydrogenase during anaerobic adaptation in the green alga Chlamydomonas reinhardtii. Eur. J. Biochem. 2002, 269 (3), 1022−32. (23) Kosourov, S.; Tsygankov, A.; Seibert, M.; Ghirardi, M. L. Sustained hydrogen photoproduction by Chlamydomonas reinhardtii: Effects of culture parameters. Biotechnol. Bioeng. 2002, 78 (7), 731−40. (24) Gfeller, R. P.; Gibbs, M. Fermentative metabolism of Chlamydomonas reinhardtii. Plant Physiol. 1984, 75, 212−218. (25) Ohta, S.; Miyamoto, K.; Miura, Y. Hydrogen evolution as a consumption mode of reducing equivalents in green algal fermentation. Plant Physiol. 1987, 83 (4), 1022−6. (26) Catalanotti, C.; Dubini, A.; Subramanian, V.; Yang, W.; Magneschi, L.; Mus, F.; Seibert, M.; Posewitz, M. C.; Grossman, A. R.

dehydrogenase; PAGE, polyacrylamide gel electrophoresis; PAR, photosynthetically active radiation; PCA, principal component analysis; PCK1, phosphoenolpyruvate carboxykinase; PDI3, protein disulfide isomerase; PEP, phosphoenolpyruvate; PFL1, pyruvate formate lyase; PFR, pyruvate-ferredoxin oxidoreductase; PGH1, enolase; RBCS2, RuBisCO small subunit; PGI, phosphoglucoisomerase; PLS, partial least squares; PRK1, phosphoribulokinase; PRX, peroxiredoxin; PSII, photosystem II; PTS, peroxisomal targeting signal; RbcL, RuBisCO large subunit; ROS, reactive oxygen species; RPL, ribosomal protein large subunit; RPS, ribosomal protein small subunit; RT-qPCR, reverse transcription-quantitative polymerase chain reaction; SAM, significance analysis of microarrays; SGA, serine:glyoxylate aminotransferase; SHMT, serine hydroxymethyltransferase; TAP, Tris-acetate-phosphate; TCA, tricarboxylic acid; THF, tetrahydrofolate; TRXH, thioredoxin H1; UGD1/2, UDPglucose dehydrogenase



REFERENCES

(1) Bolling, C.; Fiehn, O. Metabolite profiling of Chlamydomonas reinhardtii under nutrient deprivation. Plant Physiol. 2005, 139 (4), 1995−2005. (2) Castruita, M.; Casero, D.; Karpowicz, S. J.; Kropat, J.; Vieler, A.; Hsieh, S. I.; Yan, W.; Cokus, S.; Loo, J. A.; Benning, C.; Pellegrini, M.; Merchant, S. S. Systems biology approach in Chlamydomonas reveals connections between copper nutrition and multiple metabolic steps. Plant Cell 2011, 23 (4), 1273−92. (3) Chen, M.; Zhao, L.; Sun, Y. L.; Cui, S. X.; Zhang, L. F.; Yang, B.; Wang, J.; Kuang, T. Y.; Huang, F. Proteomic analysis of hydrogen photoproduction in sulfur-deprived Chlamydomonas cells. J. Proteome Res. 2010, 9 (8), 3854−66. (4) Doebbe, A.; Keck, M.; La Russa, M.; Mussgnug, J. H.; Hankamer, B.; Tekce, E.; Niehaus, K.; Kruse, O. The interplay of proton, electron, and metabolite supply for photosynthetic H 2 production in Chlamydomonas reinhardtii. J. Biol. Chem. 2010, 285 (39), 30247−60. (5) Dubini, A.; Mus, F.; Seibert, M.; Grossman, A. R.; Posewitz, M. C. Flexibility in anaerobic metabolism as revealed in a mutant of Chlamydomonas reinhardtii lacking hydrogenase activity. J. Biol. Chem. 2009, 284 (11), 7201−13. (6) Eberhard, S.; Jain, M.; Im, C. S.; Pollock, S.; Shrager, J.; Lin, Y.; Peek, A. S.; Grossman, A. R. Generation of an oligonucleotide array for analysis of gene expression in Chlamydomonas reinhardtii. Curr. Genet. 2006, 49 (2), 106−24. (7) Gonzalez-Ballester, D.; Casero, D.; Cokus, S.; Pellegrini, M.; Merchant, S. S.; Grossman, A. R. RNA-seq analysis of sulfur-deprived Chlamydomonas cells reveals aspects of acclimation critical for cell survival. Plant Cell 2010, 22 (6), 2058−84. (8) Im, C. S.; Grossman, A. R. Identification and regulation of high light-induced genes in Chlamydomonas reinhardtii. Plant J. 2002, 30 (3), 301−13. (9) Matthew, T.; Zhou, W.; Rupprecht, J.; Lim, L.; Thomas-Hall, S. R.; Doebbe, A.; Kruse, O.; Hankamer, B.; Marx, U. C.; Smith, S. M.; Schenk, P. M. The metabolome of Chlamydomonas reinhardtii following induction of anaerobic H2 production by sulfur depletion. J. Biol. Chem. 2009, 284 (35), 23415−25. (10) May, P.; Wienkoop, S.; Kempa, S.; Usadel, B.; Christian, N.; Rupprecht, J.; Weiss, J.; Recuenco-Munoz, L.; Ebenhoh, O.; Weckwerth, W.; Walther, D. Metabolomics- and proteomics-assisted genome annotation and analysis of the draft metabolic network of Chlamydomonas reinhardtii. Genetics 2008, 179 (1), 157−66. (11) Merchant, S. S.; Prochnik, S. E.; Vallon, O.; Harris, E. H.; Karpowicz, S. J.; Witman, G. B.; Terry, A.; Salamov, A.; Fritz-Laylin, L. K.; Marechal-Drouard, L.; Marshall, W. F.; Qu, L. H.; Nelson, D. R.; Sanderfoot, A. A.; Spalding, M. H.; Kapitonov, V. V.; Ren, Q.; Ferris, P.; Lindquist, E.; Shapiro, H.; Lucas, S. M.; Grimwood, J.; Schmutz, J.; Cardol, P.; Cerutti, H.; Chanfreau, G.; Chen, C. L.; Cognat, V.; Croft, M. T.; Dent, R.; Dutcher, S.; Fernandez, E.; Fukuzawa, H.; GonzalezS

dx.doi.org/10.1021/pr500342j | J. Proteome Res. XXXX, XXX, XXX−XXX

Journal of Proteome Research

Article

Altered fermentative metabolism in Chlamydomonas reinhardtii mutants lacking pyruvate formate lyase and both pyruvate formate lyase and alcohol dehydrogenase. Plant Cell 2012, 24 (2), 692−707. (27) Magneschi, L.; Catalanotti, C.; Subramanian, V.; Dubini, A.; Yang, W.; Mus, F.; Posewitz, M. C.; Seibert, M.; Perata, P.; Grossman, A. R. A mutant in the ADH1 gene of Chlamydomonas reinhardtii elicits metabolic restructuring during anaerobiosis. Plant Physiol. 2012, 158 (3), 1293−305. (28) Mevik, B.-H.; Wehrens, R. The pls Package: Principal Component and Partial Least Squares Regression in R. J. Stat. Software 2007, 18 (2), 1−24. (29) Martens, H.; Martens, M. Modified jack-knife estimation of parameter uncertainty in bilinear modelling (PLSR). Food Qual. Preference 2000, 11 (1−2), 5−16. (30) Tusher, V. G.; Tibshirani, R.; Chu, G. Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. U.S.A. 2001, 98 (9), 5116−21. (31) Laurens, L. M.; Quinn, M.; Van Wychen, S.; Templeton, D. W.; Wolfrum, E. J. Accurate and reliable quantification of total microalgal fuel potential as fatty acid methyl esters by in situ transesterification. Anal. Bioanal. Chem. 2012, 403 (1), 167−78. (32) Posewitz, M. C.; Smolinski, S. L.; Kanakagiri, S.; Melis, A.; Seibert, M.; Ghirardi, M. L. Hydrogen photoproduction is attenuated by disruption of an isoamylase gene in Chlamydomonas reinhardtii. Plant Cell 2004, 16 (8), 2151−63. (33) Moroney, J. V.; Wilson, B. J.; Tolbert, N. E. Glycolate Metabolism and Excretion by Chlamydomonas reinhardtii. Plant Physiol. 1986, 82 (3), 821−6. (34) Lourenco, S. O.; Barbarino, E.; Lavin, P. L.; Lanfer Marquez, U. M.; Aidar, E. Distribution of intracellular nitrogen in marine microalgae: Calculation of new nitrogen-to-protein conversion factors. Eur. J. Phycol. 2004, 39, 17−32. (35) Perez-Perez, M. E.; Mata-Cabana, A.; Sanchez-Riego, A. M.; Lindahl, M.; Florencio, F. J. A comprehensive analysis of the peroxiredoxin reduction system in the Cyanobacterium Synechocystis sp. strain PCC 6803 reveals that all five peroxiredoxins are thioredoxin dependent. J. Bacteriol. 2009, 191 (24), 7477−89. (36) Atteia, A.; van Lis, R.; Gelius-Dietrich, G.; Adrait, A.; Garin, J.; Joyard, J.; Rolland, N.; Martin, W. Pyruvate formate-lyase and a novel route of eukaryotic ATP synthesis in Chlamydomonas mitochondria. J. Biol. Chem. 2006, 281 (15), 9909−18. (37) Zhang, L.; Happe, T.; Melis, A. Biochemical and morphological characterization of sulfur-deprived and H2-producing Chlamydomonas reinhardtii (green alga). Planta 2002, 214 (4), 552−61. (38) Bedhomme, M.; Zaffagnini, M.; Marchand, C. H.; Gao, X. H.; Moslonka-Lefebvre, M.; Michelet, L.; Decottignies, P.; Lemaire, S. D. Regulation by glutathionylation of isocitrate lyase from Chlamydomonas reinhardtii. J. Biol. Chem. 2009, 284 (52), 36282−91. (39) De Bellis, L.; Picciarelli, P.; Pistelli, L.; Alpi, A. Localization of glyoxylate-cycle marker enzymes in peroxisomes of senescent leaves and green cotyledones. Planta (Berlin) 1990, 180, 435−439. (40) Birkhan, R.; Kindl, H. Re-activation of the expression of glyoxysomal genes in green plant tissue. Z. Naturforsch. C 1990, 45, 107−111. (41) Comai, L.; Dietrich, R. A.; Maslyar, D. J.; Baden, C. S.; Harada, J. J. Coordinate expression of transcriptionally regulated isocitrate lyase and malate synthase genes in Brassica napus L. Plant Cell 1989, 1 (3), 293− 300. (42) Zhang, J. Z.; Gomez-Pedrozo, M.; Baden, C. S.; Harada, J. J. Two classes of isocitrate lyase genes are expressed during late embryogeny and postgermination in Brassica napus L. Mol. Gen. Genet. 1993, 238 (1− 2), 177−84. (43) DeBellis, L.; Tsugeki, R.; Nishimura, M. Glyoxylate cycle enzymes in peroxisomes isolated from petals of pumpkin cucurbita-sp during senescence. Plant Cell Physiol 1991, 32, 1227−1236. (44) Gut, H.; Matile, P. Apparent induction of key enzymes of the glyoxylic acid cycle in senescent barley leaves. Planta (Berlin) 1988, 176, 548−550.

(45) Landolt, R.; Matile, P. Glyoxysome-like microbodies in senescent spinach leaves. Plant Sci. 1990, 72, 159−164. (46) Chen, Z. H.; Walker, R. P.; Acheson, R. M.; Tecsi, L. I.; Wingler, A.; Lea, P. J.; Leegood, R. C. Are isocitrate lyase and phosphoenolpyruvate carboxykinase involved in gluconeogenesis during senescence of barley leaves and cucumber cotyledons? Plant Cell Physiol. 2000, 41 (8), 960−7. (47) Plancke, C.; Vigeolas, H.; Hohner, R.; Roberty, S.; Emonds-Alt, B.; Larosa, V.; Willamme, R.; Duby, F.; Onga Dhali, D.; Thonart, P.; Hiligsmann, S.; Franck, F.; Eppe, G.; Cardol, P.; Hippler, M.; Remacle, C. Lack of isocitrate lyase in Chlamydomonas leads to changes in carbon metabolism and in the response to oxidative stress under mixotrophic growth. Plant J. 2014, 77 (3), 404−17. (48) Kim, D. J.; Smith, S. M. Molecular cloning of cucumber phosphoenolpyruvate carboxykinase and developmental regulation of gene expression. Plant Mol. Biol. 1994, 26 (1), 423−34. (49) Rylott, E. L.; Hooks, M. A.; Graham, I. A. Co-ordinate regulation of genes involved in storage lipid mobilization in Arabidopsis thaliana. Biochem. Soc. Trans. 2001, 29 (Part 2), 283−7. (50) Petridou, S.; Foster, K.; Kindle, K. Light induces accumulation of isocitrate lyase mRNA in a carotenoid-deficient mutant of Chlamydomonas reinhardtii. Plant Mol. Biol. 1997, 33 (3), 381−92. (51) Bailey-Serres, J.; Voesenek, L. A. Flooding stress: acclimations and genetic diversity. Annu. Rev. Plant Biol. 2008, 59, 313−39. (52) Shingaki-Wells, R. N.; Huang, S.; Taylor, N. L.; Carroll, A. J.; Zhou, W.; Millar, A. H. Differential molecular responses of rice and wheat coleoptiles to anoxia reveal novel metabolic adaptations in amino acid metabolism for tissue tolerance. Plant Physiol. 2011, 156 (4), 1706− 24. (53) Scott, J. H.; Nealson, K. H. A biochemical study of the intermediary carbon metabolism of Shewanella putrefaciens. J. Bacteriol. 1994, 176 (11), 3408−11. (54) Tang, Y. J.; Hwang, J. S.; Wemmer, D. E.; Keasling, J. D. Shewanella oneidensis MR-1 fluxome under various oxygen conditions. Appl. Environ. Microbiol. 2007, 73 (3), 718−29. (55) Tang, Y. J.; Meadows, A. L.; Kirby, J.; Keasling, J. D. Anaerobic central metabolic pathways in Shewanella oneidensis MR-1 reinterpreted in the light of isotopic metabolite labeling. J. Bacteriol. 2007, 189 (3), 894−901. (56) Liepman, A. H.; Olsen, L. J. Alanine aminotransferase homologs catalyze the glutamate:glyoxylate aminotransferase reaction in peroxisomes of Arabidopsis. Plant Physiol. 2003, 131 (1), 215−27. (57) Stewart, G. R.; Larher, F., Accumulation of amino acids and related compounds in relation to environmental stress. In The Biochemistry of Plants; Miflin, B. J., Ed.; Academic Press: New York, 1980; Vol. 5, pp 609−35. (58) Streeter, J. G.; Thompson, J. F. Anaerobic accumulation of gamma-aminobutyric acid and alanine in radish leaves (Raphanus sativus, L.). Plant Physiol. 1972, 49 (4), 572−8. (59) Goldschmidt-Clermont, M.; Rahire, M. Sequence, evolution and differential expression of the two genes encoding variant small subunits of ribulose bisphosphate carboxylase/oxygenase in Chlamydomonas reinhardtii. J. Mol. Biol. 1986, 191 (3), 421−32. (60) Good, A. G.; Crosby, W. L. Anaerobic induction of alanine aminotransferase in barley root tissue. Plant Physiol. 1989, 90 (4), 1305−9. (61) Miyashita, Y.; Dolferus, R.; Ismond, K. P.; Good, A. G. Alanine aminotransferase catalyses the breakdown of alanine after hypoxia in Arabidopsis thaliana. Plant J. 2007, 49 (6), 1108−21. (62) Rocha, M.; Licausi, F.; Araujo, W. L.; Nunes-Nesi, A.; Sodek, L.; Fernie, A. R.; van Dongen, J. T. Glycolysis and the tricarboxylic acid cycle are linked by alanine aminotransferase during hypoxia induced by waterlogging of Lotus japonicus. Plant Physiol. 2010, 152 (3), 1501−13. (63) Vanlerberghe, G. C.; Yip, J. Y.; Parsons, H. L. In organello and in vivo evidence of the importance of the regulatory sulfhydryl/disulfide system and pyruvate for alternative oxidase activity in tobacco. Plant Physiol. 1999, 121 (3), 793−803. T

dx.doi.org/10.1021/pr500342j | J. Proteome Res. XXXX, XXX, XXX−XXX

Journal of Proteome Research

Article

(64) Gupta, K. J.; Zabalza, A.; van Dongen, J. T. Regulation of respiration when the oxygen availability changes. Physiol. Plant. 2009, 137 (4), 383−91. (65) Zabalza, A.; van Dongen, J. T.; Froehlich, A.; Oliver, S. N.; Faix, B.; Gupta, K. J.; Schmalzlin, E.; Igal, M.; Orcaray, L.; Royuela, M.; Geigenberger, P. Regulation of respiration and fermentation to control the plant internal oxygen concentration. Plant Physiol. 2009, 149 (2), 1087−98. (66) Brecht, M.; de Groot, H. Protection from hypoxic injury in cultured hepatocytes by glycine, alanine, and serine. Amino Acids 1994, 6 (1), 25−35. (67) Tijsen, M. J.; Peters, S. M.; Bindels, R. J.; van Os, C. H.; Wetzels, J. F. Glycine protection against hypoxic injury in isolated rat proximal tubules: the role of proteases. Nephrol., Dialyl., Transplant. 1997, 12 (12), 2549−56. (68) Wang, G. H.; Jiang, Z. L.; Chen, Z. Q.; Li, X.; Peng, L. L. Neuroprotective effect of L-serine against temporary cerebral ischemia in rats. J. Neurosci. Res. 2010, 88 (9), 2035−45. (69) Edwards, J. M.; Roberts, T. H.; Atwell, B. J. Quantifying ATP turnover in anoxic coleoptiles of rice (Oryza sativa) demonstrates preferential allocation of energy to protein synthesis. J. Exp. Bot. 2012, 63 (12), 4389−402. (70) Mocquot, B.; Prat, C.; Mouches, C.; Pradet, A. Effect of anoxia on energy charge and protein synthesis in rice embryo. Plant Physiol. 1981, 68 (3), 636−40. (71) Wingler, A.; Lea, P. J.; Leegood, R. C. Photorespiratory metabolism of glyoxylate and formate in glycine-accumulating mutants of barley and Amaranthus edulis. Planta 1999, 207, 518−26. (72) Filonova, A.; Haemsch, P.; Gebauer, C.; Weisheit, W.; Wagner, V. Protein disulfide isomerase 2 of Chlamydomonas reinhardtii is involved in circadian rhythm regulation. Mol. Plant 2013, 6 (5), 1503−17. (73) Yilancioglu, K.; Cokol, M.; Pastirmaci, I.; Erman, B.; Cetiner, S. Oxidative Stress Is a Mediator for Increased Lipid Accumulation in a Newly Isolated Dunaliella salina Strain. PloS One 2014, 9 (3), e91957. (74) Shingaki-Wells, R. N.; Huang, S.; Taylor, N. L.; Millar, A. H. Pursuing the identification of O(2) deprivation survival mechanisms in plants related to selective mRNA translation, hormone-independent cellular elongation and preparation for the arrival of oxygen. Plant Signaling Behav. 2011, 6 (10), 1612−5. (75) Bailey-Serres, J. Selective translation of cytoplasmic mRNAs in plants. Trends Plant Sci. 1999, 4 (4), 142−148. (76) Bailey-Serres, J.; Freeling, M. Hypoxic stress-induced changes in ribosomes of maize seedling roots. Plant Physiol. 1990, 94 (3), 1237−43. (77) Branco-Price, C.; Kaiser, K. A.; Jang, C. J.; Larive, C. K.; BaileySerres, J. Selective mRNA translation coordinates energetic and metabolic adjustments to cellular oxygen deprivation and reoxygenation in Arabidopsis thaliana. Plant J. 2008, 56 (5), 743−55. (78) Sachs, M. M.; Freeling, M.; Okimoto, R. The anaerobic proteins of maize. Cell 1980, 20 (3), 761−7. (79) Subramanian, V.; Dubini, A.; Seibert, M., Metabolic pathways in green algae with potential value for biofuel production. In The science of algal fuels; Gordon, R., Seckback, J., Eds.; Springer: Dordrecht, 2012; pp 401−22.

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dx.doi.org/10.1021/pr500342j | J. Proteome Res. XXXX, XXX, XXX−XXX