Systemic Cold Stress Adaptation of Chlamydomonas reinhardtii
2013; Elsevier BV; Volume: 12; Issue: 8 Linguagem: Inglês
10.1074/mcp.m112.026765
ISSN1535-9484
AutoresLuís Valledor, Takeshi Furuhashi, Anne-Mette Hanak, Wolfram Weckwerth,
Tópico(s)Algal biology and biofuel production
ResumoChlamydomonas reinhardtii is one of the most important model organisms nowadays phylogenetically situated between higher plants and animals (Merchant et al. 2007). Stress adaptation of this unicellular model algae is in the focus because of its relevance to biomass and biofuel production. Here, we have studied cold stress adaptation of C. reinhardtii hitherto not described for this algae whereas intensively studied in higher plants. Toward this goal, high throughput mass spectrometry was employed to integrate proteome, metabolome, physiological and cell-morphological changes during a time-course from 0 to 120 h. These data were complemented with RT-qPCR for target genes involved in central metabolism, signaling, and lipid biosynthesis. Using this approach dynamics in central metabolism were linked to cold-stress dependent sugar and autophagy pathways as well as novel genes in C. reinhardtii such as CKIN1, CKIN2 and a hitherto functionally not annotated protein named CKIN3. Cold stress affected extensively the physiology and the organization of the cell. Gluconeogenesis and starch biosynthesis pathways are activated leading to a pronounced starch and sugar accumulation. Quantitative lipid profiles indicate a sharp decrease in the lipophilic fraction and an increase in polyunsaturated fatty acids suggesting this as a mechanism of maintaining membrane fluidity. The proteome is completely remodeled during cold stress: specific candidates of the ribosome and the spliceosome indicate altered biosynthesis and degradation of proteins important for adaptation to low temperatures. Specific proteasome degradation may be mediated by the observed cold-specific changes in the ubiquitinylation system. Sparse partial least squares regression analysis was applied for protein correlation network analysis using proteins as predictors and Fv/Fm, FW, total lipids, and starch as responses. We applied also Granger causality analysis and revealed correlations between proteins and metabolites otherwise not detectable. Twenty percent of the proteins responsive to cold are uncharacterized proteins. This presents a considerable resource for new discoveries in cold stress biology in alga and plants. Chlamydomonas reinhardtii is one of the most important model organisms nowadays phylogenetically situated between higher plants and animals (Merchant et al. 2007). Stress adaptation of this unicellular model algae is in the focus because of its relevance to biomass and biofuel production. Here, we have studied cold stress adaptation of C. reinhardtii hitherto not described for this algae whereas intensively studied in higher plants. Toward this goal, high throughput mass spectrometry was employed to integrate proteome, metabolome, physiological and cell-morphological changes during a time-course from 0 to 120 h. These data were complemented with RT-qPCR for target genes involved in central metabolism, signaling, and lipid biosynthesis. Using this approach dynamics in central metabolism were linked to cold-stress dependent sugar and autophagy pathways as well as novel genes in C. reinhardtii such as CKIN1, CKIN2 and a hitherto functionally not annotated protein named CKIN3. Cold stress affected extensively the physiology and the organization of the cell. Gluconeogenesis and starch biosynthesis pathways are activated leading to a pronounced starch and sugar accumulation. Quantitative lipid profiles indicate a sharp decrease in the lipophilic fraction and an increase in polyunsaturated fatty acids suggesting this as a mechanism of maintaining membrane fluidity. The proteome is completely remodeled during cold stress: specific candidates of the ribosome and the spliceosome indicate altered biosynthesis and degradation of proteins important for adaptation to low temperatures. Specific proteasome degradation may be mediated by the observed cold-specific changes in the ubiquitinylation system. Sparse partial least squares regression analysis was applied for protein correlation network analysis using proteins as predictors and Fv/Fm, FW, total lipids, and starch as responses. We applied also Granger causality analysis and revealed correlations between proteins and metabolites otherwise not detectable. Twenty percent of the proteins responsive to cold are uncharacterized proteins. This presents a considerable resource for new discoveries in cold stress biology in alga and plants. Microalgae have a plastic metabolism allowing them to cope with many biotic and abiotic factors that may occur in its environment. Not so much is known about cold stress for algal metabolism, including chilling (below 15 °C) and freezing (below 0 °C). In Chlamydomonas, a moderate chilling stress lead to a decreased growth rate, chlorosis, progressive membrane and oxidative damage (1Hema R. Senthil-Kumar M. Shivakumar S. Chandrasekhara Reddy P. Udayakumar M. Chlamydomonas reinhardtii, a model system for functional validation of abiotic stress responsive genes.Planta. 2007; 226: 655-670Crossref PubMed Scopus (0) Google Scholar) whereas severe stress, with temperatures below 3 °C, lead to cell death after a short period. These injuries are similar to those observed in higher plants (2Janská A. Marsík P. Zelenková S. Ovesná J. Cold stress and acclimation – what is important for metabolic adjustment?.Plant Biol. 2010; 12: 395-405Crossref PubMed Scopus (0) Google Scholar), in which growth and development are also reduced by a direct inhibition of metabolic reactions and, indirectly, through cold-induced osmotic, oxidative, energetic, and other stresses (3Chinnusamy V. Zhu J. Zhu J.K. Cold stress regulation of gene expression in plants.Trends Plant Sci. 2007; 12: 444-451Abstract Full Text Full Text PDF PubMed Scopus (1032) Google Scholar). The chilling syndrome and its related injuries, in which no mechanical damage is produced as a consequence of ice crystals, can be explained both by structural membrane damage (alterations of membranes fluidity, breakage of cell structures) (4Upchurch R.G. Fatty acid unsaturation, mobilization, and regulation in the response of plants to stress.Biotechnol. Lett. 2008; 30: 967-977Crossref PubMed Scopus (457) Google Scholar, 5Vaultier M.-N. Cantrel C. Vergnolle C. Justin A.-M. Demandre C. Benhassaine-Kesri G. √ái√βek D. Zachowski A. Ruelland E. Desaturase mutants reveal that membrane rigidification acts as a cold perception mechanism upstream of the diacylglycerol kinase pathway in Arabidopsis cells.FEBS Lett. 2006; 580: 4218-4223Crossref PubMed Scopus (0) Google Scholar) and decreased enzymatic kinetics as a consequence of protein denaturation resulting in a reduced or total loss of enzymatic activity. It was described that cold partially denatures the enzyme Thioredoxin h in Chlamydomonas, leading to a reduced activity (6Richardson J.M. Lemaire S.p.D. Jacquot J.-P. Makhatadze G.I. Difference in the Mechanisms of the Cold and Heat Induced Unfolding of Thioredoxin h from Chlamydomonas reinhardtii: Spectroscopic and Calorimetric Studies.Biochemistry. 2000; 39: 11154-11162Crossref PubMed Scopus (0) Google Scholar). To avoid these effects that may affect all of the metabolic pathways and withstand low temperatures, the cells should accomplish numerous physiological, biochemical and molecular changes. This process, called acclimation, is not described in Chlamydomonas whereas extensively studied in higher plants (7Xin Z. Browse J. Cold comfort farm: the acclimation of plants to freezing temperatures.Plant Cell Environment. 2000; 23: 893-902Crossref Scopus (0) Google Scholar, 8Mahajan S. Tuteja N. Cold, salinity and drought stresses: An overview.Arch. Biochem. Biophys. 2005; 444: 139-158Crossref PubMed Scopus (1725) Google Scholar): Stress-related genes are induced (9Shinozaki K. Yamaguchi-Shinozaki K. Seki M. Regulatory network of gene expression in the drought and cold stress responses.Curr. Opinion Plant Biol. 2003; 6: 410-417Crossref PubMed Scopus (0) Google Scholar, 10Thomashow M.F. So what's new in the field of plant cold acclimation?.Lots! Plant Physiol. 2001; 125: 89-93Crossref PubMed Scopus (0) Google Scholar), antioxidative mechanisms (11Fiorani F. Umbach A.L. Siedow J.N. The Alternative Oxidase of Plant Mitochondria Is Involved in the Acclimation of Shoot Growth at Low Temperature. A Study of Arabidopsis AOX1a Transgenic Plants.Plant Physiol. 2005; 139: 1795-1805Crossref PubMed Scopus (158) Google Scholar), cryoprotectant osmolytes and proteins are increased (12Livingston D.P. Henson C.A. Apoplastic Sugars, Fructans, Fructan Exohydrolase, and Invertase in Winter Oat: Responses to Second-Phase Cold Hardening.Plant Physiol. 1998; 116: 403-408Crossref Google Scholar, 13Hare P.D. Cress W.A. Van Staden J. Dissecting the roles of osmolyte accumulation during stress.Plant Cell Environment. 1998; 21: 535-553Crossref Scopus (0) Google Scholar), lipid composition is altered and membranes are stabilized (14Wang X. Li W. Li M. Welti R. Profiling lipid changes in plant response to low temperatures.Physiol. Plant. 2006; 126: 90-96Crossref Scopus (93) Google Scholar, 15Uemura M. Steponkus P.L. Modification of the intracellular sugar content alters the incidence of freeze-induced membrane lesions of protoplasts isolated from Arabidopsis thaliana leaves.Plant Cell Environment. 2003; 26: 1083-1096Crossref Scopus (78) Google Scholar) whereas photosynthesis (16Ivanov A.G. Sane P. Hurry V. Król M. Sveshnikov D. Huner N.P.A. Öquist G. Low-temperature modulation of the redox properties of the acceptor side of photosystem II: photoprotection through reaction centre quenching of excess energy.Physiol. Plant. 2003; 119: 376-383Crossref Scopus (48) Google Scholar), nutrient absorption, and growth are decreased (17Kozlowski T.T. Pallardy S.G. Acclimation and Adaptive Responses of Woody Plants to Environmental Stresses.Botanical Rev. 2002; 68: 270-334Crossref Scopus (0) Google Scholar). The physiological changes listed above are the consequence of a major remodelling of the proteome, a complex process that involve not only stress sensing, signaling, and gene regulation, but also transcript and protein processing and degradation. In higher plants part of the sensing process starts with the change in the membrane fluidity, which at the end activates the cold responsive and ICE-CBF elements which regulate gene expression, also sharing some elements with drought response via drought responsive elements and MAPK cascades (for a review see (3Chinnusamy V. Zhu J. Zhu J.K. Cold stress regulation of gene expression in plants.Trends Plant Sci. 2007; 12: 444-451Abstract Full Text Full Text PDF PubMed Scopus (1032) Google Scholar, 18Yamaguchi-Shinozaki K. Shinozaki K. Organization of cis-acting regulatory elements in osmotic- and cold-stress-responsive promoters.Trends Plant Sci. 2005; 10: 88-94Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar, 19Krasensky J. Jonak C. Drought, salt, and temperature stress-induced metabolic rearrangements and regulatory networks.J. Exp. Bot. 2012; 63: 1593-1608Crossref PubMed Scopus (1048) Google Scholar)). A second signaling mechanism is the monitoring of the changes in the central metabolism. It has been proposed that energy-deficiency signals, specific sugars, triggers specific responses. This mechanism is based on the enzymes hexokinase (HXK) and SnRK1 1The abbreviations used are:SnRK1SNF related kinase 1sPLSsparse partial least squaresFAfatty acid. 1The abbreviations used are:SnRK1SNF related kinase 1sPLSsparse partial least squaresFAfatty acid. (SNF related kinase 1) (for a review on sugar signaling see (20Rolland F. Baena-Gonzalez E. Sheen J. SUGAR SENSING AND SIGNALING IN PLANTS: Conserved and Novel Mechanisms.Ann. Rev. Plant Biol. 2006; 57: 675-709Crossref PubMed Scopus (0) Google Scholar, 21Baena-González E. Sheen J. Convergent energy and stress signaling.Trends Plant Sci. 2008; 13: 474-482Abstract Full Text Full Text PDF PubMed Scopus (378) Google Scholar, 22Halford N.G. Hey S.J. Snf1-related protein kinases (SnRKs) act within an intricate network that links metabolic and stress signalling in plants.Biochem. J. 2009; 419: 247-259Crossref PubMed Scopus (226) Google Scholar). SnRK1 is inhibited by phosphate sugars, and under energy deficit it activates transcription factors, including bZIPs (23Baena-González E. Rolland F. Thevelein J.M. Sheen J. A central integrator of transcription networks in plant stress and energy signalling.Nature. 2007; 448: 938-942Crossref PubMed Scopus (847) Google Scholar), general stress response elements, and histone modification leading to epigenetic changes. The activation of this enzyme leads to limiting cell growth and division, autophagy, protein, lipid, cell wall, and starch degradation, while promoting photosynthesis, gluconeogenesis, and sucrose metabolism. On the other hand HXK is associated to increased biosynthetic processes (24Moore B. Zhou L. Rolland F. Hall Q. Cheng W.-H. Liu Y.-X. Hwang I. Jones T. Sheen J. Role of the Arabidopsis Glucose Sensor HXK1 in Nutrient, Light, and Hormonal Signaling.Science. 2003; 300: 332-336Crossref PubMed Scopus (760) Google Scholar), also down-regulating SnRK1 by the production of hexoses-phosphate. Other sugars like trehalose and trehalose-phosphate, proposed to act downstream of SnRK1, are related to inhibitory processes and growth control (25Schluepmann H. van Dijken A. Aghdasi M. Wobbes B. Paul M. Smeekens S. Trehalose Mediated growth inhibition of arabidopsis seedlings is due to trehalose-6-phosphate accumulation.Plant Physiol. 2004; 135: 879-890Crossref PubMed Scopus (215) Google Scholar) and might also be involved in the cold stress signaling (26Iordachescu M. Imai R. Trehalose Biosynthesis in Response to Abiotic Stresses.J. Integrative Plant Biol. 2008; 50: 1223-1229Crossref PubMed Scopus (0) Google Scholar). SNF related kinase 1 sparse partial least squares fatty acid. SNF related kinase 1 sparse partial least squares fatty acid. Despite a number of genetic and physiological studies of cold acclimation in higher plants, deeper understanding of how algae are adapting to low temperatures is missing. In recent years, integrative studies of transcript, metabolite and protein data revealed complex biochemical networks and systemic regulation at an organismal level (27Lee do Y. Park J.J. Barupal D.K. Fiehn O. System response of metabolic networks in Chlamydomonas reinhardtii to total available ammonium.Mol. Cell. Proteomics. 2012; 11: 973-988Abstract Full Text Full Text PDF PubMed Scopus (78) Google Scholar, 28Morgenthal K. Wienkoop S. Scholz M. Selbig J. Weckwerth W. Correlative GC-TOF-MS based metabolite profiling and LC-MS based protein profiling reveal time-related systemic regulation of metabolite-protein networks and improve pattern recognition for multiple biomarker selection.Metabolomics. 2005; 1: 109-121Crossref Scopus (0) Google Scholar, 29Hirai M.Y. Yano M. Goodenowe D.B. Kanaya S. Kimura T. Awazuhara M. Arita M. Fujiwara T. Saito K. Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana.Proc. Natl. Acad. Sci. U.S.A. 2004; 101: 10205-10210Crossref PubMed Scopus (577) Google Scholar, 30Wienkoop S. Morgenthal K. Wolschin F. Scholz M. Selbig J. Weckwerth W. Integration of metabolomic and proteomic phenotypes: analysis of data covariance dissects starch and RFO metabolism from low and high temperature compensation response in Arabidopsis thaliana.Mol. Cell. Proteomics. 2008; 7: 1725-1736Abstract Full Text Full Text PDF PubMed Scopus (103) Google Scholar, 31Wienkoop S. Weiss J. May P. Kempa S. Irgang S. Recuenco-Munoz L. Pietzke M. Schwemmer T. Rupprecht J. Egelhofer V. Weckwerth W. Targeted proteomics for Chlamydomonas reinhardtii combined with rapid subcellular protein fractionation, metabolomics and metabolic flux analyses.Mol. Biosyst. 2010; 6: 1018-1031Crossref PubMed Scopus (71) Google Scholar). Here, we looked at global changes at the metabolome, proteome, and complementary transcript levels under cold acclimation of Chlamydomonas reinhardtii. This species is an ideal model system because it shares most of the metabolic and stress responsive pathways with the higher plants, but at the same time its genome is less complex and most of the gene families have a reduced number of members compared, i.e. to Arabidopsis. Phylogenetically C. reinhardtii is placed between higher plants and animals (32Merchant 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. Gonzalez-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. Mueller-Roeber 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: 245-250Crossref PubMed Scopus (1706) Google Scholar). In this work we aim to present an integrative study of the cold stress acclimation process in C. reinhardtii during a 5-day time course experiment. We have employed methods of high sensitivity quantitative proteomics (GeLC-LTQ-Orbitrap MS; (33Valledor L. Weckwerth W. An Improved Detergent-Compatible Gel-Fractionation LC-LTQ-Orbitrap workflow for plant and microbial proteomics.Method Mol. Biol. 2013; (in press)Google Scholar)), metabolomics (GC-MS), targeted transcriptomics (RT-qPCR), physiology, and cell-morphology to describe a complete picture of metabolic, physiological and morphological acclimation, providing insights into cold-stress response in Chlamydomonas. We have found a broad set of responses, from classical stress evidences such us reduced growth and photosynthesis reduction, accumulation of sugars, and membrane composition, to more complex responses involving the identification of specific changes in ribosomes, spliceosomes, and proteasomes, and in sugar signaling pathways. Chlamydomonas reinhardtii CC-503 cw92 mt+ (available at the Chlamydomonas Culture Collection, Duke University) cultures were grown in HEPES-acetate-phosphate medium (standard TAP medium in which TRIS was replaced by 5 mm HEPES) supplemented with 8 mm NH4Cl, at 25 °C or 5 °C with shaking (120 rpm) under continuous light (85 μmol m−2 s−1; Sylvania GroLux lamps). CC-503 is a cell wall mutant, derived from CC-125 (agg1+, nit1, nit2), which cannot grow on nitrate as a sole N source because of the lack of nitrate reductase (nit1), showing a blocked nitrate-dependent signaling because of the mutation in the regulatory gene nit2. Cultures were prepared 48 h before starting the experiment diluting sixfold a stock culture originated from a single colony. Cells were collected at density 1–6 × 106 cell ml−1 (0–120 h of culture; in exponential phase). At each harvesting time the cell density was measured employing a Thoma counting chamber and the fresh weight was estimated gravimetrically. Photosynthetic rates were measured with an imaging and pulse-amplitude modulation fluorimeter (OS1-FL, Opti-Sciences) after filtering 2 ml of culture onto a 20 mm2 surface (Munktell Glass Microfibre Discs). Total lipids were extracted from frozen pellets with 200 μl of a mixture of chloroform/isopropanol (1:1) and vigorous vortexing for 3 min. Samples were centrifuged (14,000 × g, 5 min, room temperature) and supernatant were transferred to a new tube. The pellet was re-extracted with 500 μl of hexane and vigorous vortexing for 3 min. Samples were centrifuged and the combined supernatants were dried in a speedvac. The amount of lipids was determined gravimetrically. For the starch determination the pellets were disaggregated and washed with 2 ml of 80% ethanol and incubated in boiling water for 3 min. The samples were then centrifuged (10,000 × g, 5 min, room temperature) to precipitate solids and the supernatant was carefully discarded and the pellet was air dried. The pellet was homogenized into 400 μl of water, and the starch was gelatinized by heating at 100 °C for 10 min. Starch content was quantified using a iodine-based assay using commercial starch as a reference. Chlamydomonas cultures were fixed in 3% (v/v) formaldehyde and stained with a lugol solution. Stained cultures were observed under an LSM 780 confocal microscope (Zeiss, Germany) and Z series covering all of the cell height were captured. From these stacks the three images closer to the middle section were selected and used for obtaining a maximum projection using the software Fiji (34Schindelin J. Arganda-Carreras I. Frise E. Kaynig V. Longair M. Pietzsch T. Preibisch S. Rueden C. Saalfeld S. Schmid B. Tinevez J.-Y. White D.J. Hartenstein V. Eliceiri K. Tomancak P. Cardona A. Fiji: an open-source platform for biological-image analysis.Nat. Meth. 2012; 9: 676-682Crossref PubMed Scopus (19428) Google Scholar). Characteristic projections obtained from cultures at 0, 24, 72, and 120 h are shown in Fig. 1 and supplemental Fig. S1. Proteins were extracted from frozen pellets (50–70 mg fresh weight). Pellets were disaggregated into 400 μl of extraction buffer [62.5 mm Tris-HCl pH 6.5, 5% SDS (w/v), 10% Glycerol (v/v), 10 mm DTT, 1.2% (v/v) Plant protease inhibitor mixture (Sigma P9599)] and incubated 5 min at room temperature. After this time the samples were mixed again by pipeting, incubated 3 min at 90 °C, and then centrifuged at 21,000 × g for 5 min at room temperature. The supernatant was carefully transferred to a new tube and proteins were precipitated by adding four volumes of cold acetone 0.1% β-mercaptoethanol. After 2 h of incubation at −20 °C samples were centrifuged 5 min at 5000 × g at 5 °C. Supernatant was discarded and 2 ml of cold acetone were used to wash the pellet using a pipet for disaggregating the pellet, and then centrifuging 5 min at 5000 × g at 5 °C for pelleting the proteins. This wash step was repeated twice, and then pellets were air dried. Pellets were re-dissolved in 125 mm Tris-HCl pH 6.8, 4% SDS (w/v), 40% Glycerol, 0.5% (v/v) Protease Inhibitor Mixture, 3% (v/v) β-mercaptoethanol and protein concentrations were estimated employing Bicinchoninic acid assay (35Smith P.K. Krohn R.I. Hermanson G.T. Mallia A.K. Gartner F.H. Provenzano M.D. Fujimoto E.K. Goeke N.M. Olson B.J. Klenk D.C. Measurement of Protein Using Bicinchoninic Acid.Anal. Biochem. 1985; 150: 76-85Crossref PubMed Scopus (17672) Google Scholar). Proteins were prefractionated by SDS-PAGE. Fifty μg of total protein were loaded into a miniprotean cell and run for 1.5 cm. Gels were fixed and stained with a Methanol:Acetic Acid:Water: Coomassie Brilliant Blue R-250 (40:10:50:0.001). Gels were distained in methanol/water (40:60) and then each lane was divided into two fractions following a molecular weight criteria (Rubisco Large subunit band was used as reference). Gel pieces were distained, equilibrated, and digested with trypsin as previously described (36Shevchenko A. Tomas H. Havlis J. Olsen J.V. Mann M. In-gel digestion for mass spectrometric characterization of proteins and proteomes.Nat. Protocols. 2007; 1: 2856-2860Crossref Scopus (0) Google Scholar). Peptides were then desalted employing Bond-Elute C-18 SPEC plate (Agilent) and concentrated into speedvac. Before the mass spectrometric measurement, protein digest pellets were dissolved in 4% (v/v) acetonitrile, 0.1% (v/v) formic acid. Ten micrograms of digested peptides were injected into an one-dimensional (1D) nano-flow LC-MS/MS system equipped with a pre-column (Eksigent, Germany). Peptides were eluted using a monolithic C18 column Chromolith RP-18r (Merck, Darmstadt, Germany) of 15 cm length and 0.1 mm internal diameter during a 80 min gradient from 5% to 50% (v/v) acetonitrile/0.1% (v/v) formic acid. MS analysis was performed on an Orbitrap LTQ XL mass spectrometer (Thermo, Germany) with a controlled flow rate of 500 nL per minute. Specific tune settings for the MS were as follows: spray voltage was set to 1.8 kV; temperature of the heated transfer capillary was set to 180 °C. Each full MS scan was followed by ten MS/MS scans, in which the ten most abundant peptide molecular ions were dynamically selected, with a dynamic exclusion window set to 90 s. Raw data were searched with SEQUEST algorithm present in Proteome Discoverer version 1.3 (Thermo, Germany) as previously described (37Valledor L. Recuenco-Munoz L. Egelhofer V. Wienkoop S. Weckwerth W. The different proteomes of Chlamydomonas reinhardtii.J. Proteomics. 2012; 75: 5883-5887Crossref PubMed Scopus (14) Google Scholar). In brief identification confidence was set to a 5% FDR and the variable modifications were set to: acetylation of N terminus, oxidation of methionine and carbamidomethyl cysteine formation, with a mass tolerance of 10 ppm for the parent ion and 0.8 Da for the fragment ion, and a maximum of one missed cleavage. Nonspecific cleavages were not allowed. Four different databases were employed (Chlamydomonas 3.0 protein, 15256 accessions; and Chlamydomonas Augustus 5, 10.1 and 10.2 protein annotations of the Chlamydomonas 4.0 genome release defined by 16888, 16036, and 17114 accessions respectively). Peptides were matched against these databases plus decoys, considering a significant hit when its XCorr score was greater than peptide-charge state+0.5. Protein functions were identified. The proteins were functionally annotated by homology employing BioMart tool available at Phytozome (www.phytozome.org) and the Algal Functional Annotation Tool (http://pathways.mcdb.ucla.edu/algal/index.html; (38Lopez D. Casero D. Cokus S. Merchant S.S. Pellegrini M. Algal Functional Annotation Tool: a web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data.BMC Bioinformatics. 2011; 12: 282Crossref PubMed Scopus (61) Google Scholar)). The final functional annotation was manually supervised because of the discrepancies found between databases for some accessions and sequences were matched to other plant genomes. Reference spectra for all identified proteins are stored in the publicly available proteomics library PROMEX (39Valledor L. Recuenco-Munoz L. Egelhofer V. Wienkoop S. Weckwerth W. The different proteomes of Chlamydomonas reinhardtii.J. Proteomics. 2012; 75: 5883-5887Crossref PubMed Scopus (14) Google Scholar, 40Wienkoop S. Staudinger C. Hoehenwarter W. Weckwerth W. Egelhofer V. ProMEX - a mass spectral reference database for plant proteomics.Front. Plant Sci. 2012; 3: 125Crossref PubMed Scopus (0) Google Scholar). The identified proteins were quantitated by a label-free approach based on total ion count (41Wienkoop S. Larrainzar E. Niemann M. Gonzalez E.M. Lehmann U. Weckwerth W. Stable isotope-free quantitative shotgun proteomics combined with sample pattern recognition for rapid diagnostics - a case study in Medicago truncatula nodules.J. Sep. Sci. 2006; 29: 2793-2801Crossref PubMed Scopus (0) Google Scholar) followed by a NSAF normalization strategy (42Paoletti A.C. Parmely T.J. Tomomori-Sato C. Sato S. Zhu D. Conaway R.C. Conaway J.W. Florens L. Washburn M.P. Quantitative proteomic analysis of distinct mammalian Mediator complexes using normalized spectral abundance factors.Proc. Natl. Acad. Sci. U.S.A. 2006; 103: 18928-18933Crossref PubMed Scopus (367) Google Scholar): (NSAF)k=(PSM/L)k/∑i=1N(PSM/L)i in which the total number of spectra counts for the matching peptides from protein k (PSM) were divided by the protein's length (L), then divided by the sum of SpC/L for all N proteins. Statistical analyses were conducted according to (43Valledor L. Jorrin J. Back to the basics: Maximizing the information obtained by quantitative two dimensional gel electrophoresis analyses by an appropriate experimental design and statistical analyses.J. Proteomics. 2011; 74: 1-18Crossref PubMed Scopus (129) Google Scholar, 44Valledor L. Romero C. Jorrín-Novo J. Standarization of data processing and statistical analysis in a 2-DE-based comparative plant proteomics experiment.Meth. Mol. Biol. 2013; (in press)Google Scholar). Proteins were accounted for quantification only if they were present in all of the biological replicates (n = 3) at least of one sampling time, or in five samples corresponding to different times. Missing values were estimated from the dataset employing a sequential K-Nearest Neighbor algorithm. This procedure was only performed if the peptide was consistent (appeared in at least 15 out the 18 replicates, and no more than one value was imputed per sampling time). Protein abundance values were scaled and subjected to Principal Component and Heatmap-Clustering analyses. Classical univariate approaches, Kruskal-Wallis and Pearson's correlation coefficient, were conducted after a log transformation for normalizing the samples. Differences within treatments were set for a 10% false discovery rate for an alpha = 0.01. The extraction protocol was adapted from (45Weckwerth W. Wenzel K. Fiehn O. Process for the integrated
Referência(s)