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Proteomic and Metabolic Profiling of Rice Suspension Culture Cells as a Model to Study Abscisic Acid Signaling Response Pathways inPlantsSushma R.Rao,†Kristina L.Ford,Andrew M.Cassin,Ute Roessner,John H.Patterson,‡andAntony Bacic*Australian Centre for Plant Functional Genomics,School of Botany,University of Melbourne,VIC 3010,AustraliaReceived July 28,2010Rice (Oryza sativa cv Taipei 309)suspension culture cells (SCCs)were used as a simple,single cell model system to gain insights into the complex abscisic acid (ABA)signaling response pathways in plants.Following system establishment involving morphological observations and transcript profiling of genes known to be ABA responsive in planta,a comprehensive proteomic and metabolomic study was performed.A total of 759buffer-soluble proteins that included 3284peptides categorized into 656protein families are ing iTRAQ,only 36of these proteins showed statistically significant changes in abundance in response to ABA.In addition,a GC -MS based metabolite profiling study allowed the identification of 148metabolites that included 25amino acids (AAs),45organic acids (OAs),35sugars,19fatty acids,2polyamines,4sterols,5sugar acids,4sugar alcohols,and 9miscellaneous compounds.Of these,only 11(8.8%)changed in a statistically significant manner in response to ABA treatment.These studies provide important insights into plant responses to ABA at the protein and metabolite level.Keywords:Oryza sativa (rice)suspension culture cells •ABA •proteomics •metabolomicsIntroductionThe plant hormone abscisic acid (ABA)is a mediator of cellular responses during growth and development as well as to environmental stresses,including drought.ABA is produced in the roots in response to a water deficit and this signal moves throughout the plant where it is perceived by ABA receptors.This interaction activates a complex web of signaling pathways that include protein phosphorylation,activation of G-proteins and modulation of RNA metabolism.1,2The pH and redox status of the cell are crucial factors in mediating ABA signal transduction.3These signals lead to appropriate physiological,metabolic,transcriptional and translational modifications.Studying ABA signal transduction at the molecular level is helping to identify new targets and pathways involved in these responses.Part of the rationale for the present study was to evaluate the utility of SCCs,given they are a simple single cell type that can be generated in high yield,as a model system to study plant ABA responses using high throughput ’omics technologies.Advances in proteomic and metabolomic techniques have allowed the large-scale profiling of samples from many species.The ability to analyze and compare dynamic changes quanti-tatively in a plant proteome in response to a stimulus,using the iTRAQ approach is a significant added advantage of modern proteomics.4Proteome profiling has been carried out in various plant species such as Arabidopsis mitochondrion,5Pinus ra-diata ,6Holm oak leaf,7wheat lemma 8and leaf.9Comprehensive comparative studies of protein profiling during either develop-ment or stress responses,and functional analysis and charac-terization of regulatory processes are now needed to under-stand plant complex signaling and response mechanisms.Likewise,with the detection and relative quantification of many of the major metabolites,it should be possible to link them to biochemical pathways and understand their role.It is predicted that there are around 200000metabolites in the plant king-dom.10Metabolite profiling has been used to study tempera-ture,water,salinity,sulfur,phosphorus,oxidative and heavy metal stress responses in a number of plant species 11-13and have resulted in the identification of previously unknown metabolic responses and networks.In this study,GC -MS based metabolite profiling was used,as its utility has been demon-strated in the analysis of metabolites from Solanum tubero-sum ,14Lycopersicon esculentum ,15Hordeum vulgare ,12Lotus japonicus ,16Oryza sativa 17,18and Arabidopsis thaliana.19The integrated metabolomic and quantitative proteomic approach adopted in this study reveals some of the known components of the ABA signaling process and also suggests the possible involvement of other factors.The time-course design enabled*To whom correspondence should be addressed.Antony Bacic.E-mail:abacic@.au.Phone.:+613-83445041.Fax:+913-93471071.Web-site:.au.†Current address:Sushma Rao,Children’s Medical Research Institute,214Hawkesbury Road,Westmead,NSW 2145.‡Current address:John Patterson,Viewbank College,Warren Rd,View-bank VIC 3084.10.1021/pr100788m2010American Chemical SocietyJournal of Proteome Research 2010,9,6623–66346623Published on Web10/20/2010the temporal tracking of changes together with identification of relevant proteins and metabolites in response to ABA. Materials and MethodsPlant Material and ABA Treatment.All chemicals were from Sigma Aldrich unless otherwise specified.Rice(Oryza sativa cv Taipei309)suspension cell cultures(SCCs),a gift from the late Prof.Hans Kende,Michigan State University,East Lansing, MI,were grown in Murashige and Skoog medium lacking IAA, kinetin or sucrose(MP Biomedicals).This was supplemented with6%(w/v)sucrose,60mM2,4-dichlorophenoxyacetic acid (2,4-D)and 2.5mM2-(N-morpholino)ethanesulfonic acid (MES).The pH of the medium was adjusted to5.6with1M KOH.The cultures were maintained in250mLflasks on shakers running at100rpm at a temperature of23°C in the dark.The cells were subcultured every7days by transferring50mL of cells and media into fresh MS medium.Rice SCCs(1L)were grown to their midlog phase(7d after subculture).Cell growth curves were obtained by monitoring the fresh weight of cells for2weeks in the presence or absence of100µM ABA(added from a100mM stock,dissolved in ethanol).At48h intervals, the fresh weight of cells was recorded for control cells and cells from cultures supplemented with either100µL ethanol or100µL MS media(3replicates in separateflasks used for each treatment).In each experiment,the cells were harvested and weighed in triplicate(Supporting Information I).Cells in the exponential phase of their growth(7days)were used for all further experimentation.For proteomic and metabolomic experiments,the parental culture(1L)was divided into4separate cultureflasks(250mL each).Oneflask from each set was used as the untreated control.The3remainingflasks were treated with100µM ABA for0.5,2,and6h,respectively.Three individual biological replicate parentalflasks were grown and divided as described for each time point.The triplicates were harvested byfiltering the SCCs through a vacuumfilter setup with a cellulosefilter disc(Whatman)to remove the media.The cells were then snap frozen in liquid nitrogen.Biological replicates,three for pro-teomics andfive for metabolomics were used.Real Time-Q-PCR.Cells treated with100µM ABA for0 (without ABA),2,4,6,and8h were used for the Q-PCR experiments.Separateflasks were used for each time sampling point.The primer pairs indicated in Supplementary Table4 (Supporting Information)were used for RT-QPCR experiments carried out at the University of Adelaide with the assistance of Dr.Neil Shirley(ACPFG,.au/).The size and the identity of the products were confirmed by sequencing. Q-PCR analysis was carried out as per the method described by Burton et al.20Three replicate PCRs for each of the cDNAs were included in every run.The data obtained were normalized with respect to the control genes,actin(OsActin),ribosomal (10S)RNA(Os10SRNA),tubulin(OsTubulin)and glyceralde-hyde-3-phosphate dehydrogenase(OsGAPDH)and analyzed.Protein Extraction.The frozen samples were ground in liquid nitrogen to afine powder and suspended in an extraction buffer containing Tris.HCl(50mM pH8.5),MgCl2(15mM), NaCl(75mM), -glycerophosphate(15mM),para-nitrophe-nylphosphate(pNPP)(15mM),NaF(1mM),EDTA(0.25M), PMSF(1mM),Na3VO4(0.5mM),DTT(1mM),aprotinin(40 g/L),leupeptin(20g/L)and pepstatin A(20g/L)at4°C. Samples were vortexed and centrifuged at3000×g for30min. The supernatant was collected and further centrifuged at 100000×g for30min.Proteins in the membrane-depleted supernatant were collected and concentrated by mixing with six volumes of-20°C equilibrated acetone,left at-20°C for 2.5h and centrifuged at3000×g for10min.The protein pellet was resuspended in triethylammonium bicarbonate(0.5M,pH 8.5)containing0.1%SDS.Soluble protein concentration was determined by the Bradford assay using bovine serum albumin (BSA)as a standard.21The acetone precipitated proteins(40µg)were reduced with tris-(2-carboxylethyl)phosphine(5mM), at60°C for1h.Cysteine residues were blocked by incubating proteins in methyl methane thiosulphate(MMTS)(90mM)in isopropanol for10min at RT.Proteins were then digested with trypsin(4µg;1:10w/w,sequencing grade,Promega)for16h at37°C.iTRAQ Labeling.iTRAQ tags(Applied Biosystems)were resuspended in ethanol(70µL)and added to the peptide mixtures.One set of iTRAQ tags were used per biological replicate(replicate1:control114;0.5h115;2h116;6h117, replicate2:control115;0.5h116;2h117;6h114,replicate3: control116;0.5h117;2h114;6h115).iTRAQ tagging was carried out by incubation at RT for1h and resulting labeled peptide mixtures were pooled and lyophilized for2D-LC-MS/ MS.Offline Strong Cation Exchange of the iTRAQ-Labeled Peptides.The iTRAQ tagged peptide sample was resuspended in0.1%formic acid and passed over a C18SepPak column (Waters,Milford,MA)and concentrated under vacuum to a final volume of100µL.The concentrated tryptic peptides were separated on a PolySULFOETHYL Aspartamide SCX column (4.6mm×200mm,5µm,300Å,PolyLC Inc.,Columbia,MD) attached to an Agilent1100series HPLC system(Agilent Technologies,Palo Alto,CA)with the following separation gradient:buffer A(25%(v/v)acetonitrile in5mM phosphate buffer,pH3)for10min,then up to100%buffer B(300mM potassium chloride,25%(v/v)acetonitrile in5mM phosphate buffer,pH5)over30min at aflow rate of0.7mL/min with0.5 min fractions being collected in a96-well plate.Inline Reversed-Phase LC-ESI-MS/MS.Fractions obtained from SCX-HPLC were reduced under vacuum and resuspended in0.1%formic acid(60µL),filtered through a minisart membrane(0.2µm;Sartorius Stadim Biotech,Aubagne,France) and one-quarter of each fraction was loaded onto a reversed-phase precolumn(300µm×5mm Zorbax300SB-C18;Agilent Technologies,Palo Alto,CA)attached to a Shimadzu Promi-nence nano LC system(Shimadzu Corporation,Kyoto,Japan). The precolumn was washed with0.1%formic acid in5% acetonitrile for15min before placing in-line with a75µm i.d.×150mm Zorbax300SB-C18(Agilent Technologies,Palo Alto, CA)reversed-phase column.Peptides were eluted using a gradient of5-65%(v/v)acetonitrile in0.1%formic acid over 60min,at aflow rate of0.25µL min-1.Peptides were analyzed via electrospray ionization(ESI)on a QSTAR Elite hybrid quadrupole time-of-flight mass spectrometer(Applied Biosys-tems/MDS Sciex,Foster City,CA).Each SCX-HPLC fraction was chromatographed and analyzed three times.The MS was operated in the positive ion mode,ion source voltage of2200V,using10µm uncoated SilicaTips(New Objective,Woburn,MA).Analyst QS2.0software(Applied Biosystems/MDS Sciex,Foster City,CA)was used to collect data in a data-dependent acquisition mode for the three most intense ions fulfilling the following criteria:m/z between450 and2000;ion intensity40counts;and charge state between +2and+5.After MS/MS analysis,these ions were dynamically excluded for18s,using a mass tolerance of50mDa.MS scansresearch articles Rao et al. 6624Journal of Proteome Research•Vol.9,No.12,2010were accumulated for0.5s,and MS/MS scans were collected in automatic accumulation mode for a maximum of2s.Mass and charge state-dependent rolling collision energy was used and the MS instrument was calibrated daily with[Glu]-fibrinopeptide B(Sigma-Aldrich,St.Louis,MO).Proteomic Data Analysis.Peak lists from the MS/MS spectra were made using ProteinPilot software version2.0.1(Applied Biosystems/MDS Sciex Foster City,CA).The peak list was searched against Oryza sativa proteins downloaded from NCBI in July2009using MASCOT22and the Paragon Algorithm (Applied Biosystems/MDS Sciex).23The rationale for using two separate algorithms was to reduce the false positive rates of the peptides identified.The false positive rate for this study was calculated using randomized version of the rice protein database from NCBI and was found to be0.2%.The MASCOT parameters were:enzyme:trypsin,fixed modifications:iTRAQ4plex(N-term);iTRAQ4plex(K);Meth-ylthiol(C),variable modifications:iTRAQ4plex(Y),MS peptide tolerance:0.25Da,MS/MS tolerance:0.15Da,number of missed cleavages:up to1.The Paragon Algorithm parameters were:sample type:iTRAQ4plex(peptide labeled);Cys Alkyla-tion:MMTS;Digestion:Trypsin;Search effort:Thorough ID. The outputs from both search algorithms were combined and only proteins with2or more peptides with a P<0.05in both search algorithms were reported.The reporter ion peak areas generated in ProteinPilot were used for quantification.Any peptide with a reporter ion peak area of less than20was removed from quantification.When a peptide was detected more than once,the peak area for each reporter ion was summed,each peptide was then normalized by the sum of its channel intensities(114,115,116,and117). Peptides were ignored when the normalized peptide value was more than2standard deviations from the calculated mean of the protein the peptide matched to.The mean was then calculated for proteins with3or more peptides that fulfilled the above criteria.The time points were normalized to the control and again by the average protein ratio for each time point.The results for each replicate were combined and only those proteins seen in all3replicates are reported.This analysis therefore focused primarily on proteins that showed changes in abundance in response to ABA,rather than proteins that may have become differentially post-translationally modified in response to ABA.Proteins were classified into their respective functional categories as specified either in NCBI or Uniprot (Universal protein resource:/).Extraction,Derivatization,Profiling and Statistical Analysis of Metabolites.The harvested rice SCCs were frozen in liquid nitrogen,homogenized to afine powder which was used for metabolite extraction using a modified method of Jacobs et al.18 To account for biological and technical variability,5biological replicates(SCCs grown in separateflasks)were analyzed for each particular time point.15Approximately70-100mg of the sample(accurate weights were recorded)was extracted in100% methanol(500µL)and a polar internal standard(20µL of0.2 mg/mL ribitol/norleucine in water)was added.The mixture was extracted for15min at70°C and water(500µL)was added and vortexed.The mixture was centrifuged at14000rpm for 10min.The dried polar residue was derivatized using both the trimethylsilyl(TMS)and tributyldimethylsilyl(TBS)methods.14,15 as described by Roessner et al.12and the samples(1µL)were injected onto a GC column in the splitless mode and run on a GC-MS system comprising of an AS3000auto sampler,an ultra trace GC and a DSQ quadrupole MS(Thermo Electron Cor-poration,Madison,WI)using the conditions described in Roessner et al.12The analysis of TBS samples was performed as described in Jacobs et al.18and the mass spectra were recorded at two scans per second over a mass range of mass-to-charge(m/z)ratio of70to600atomic mass units(amu). Both total ion chromatograms(TIC)and mass spectra were evaluated using the Xcalibur program(ThermoFinnigan)and the resulting data prepared and normalized as described in Roessner et al.14Mass spectra of eluting compounds were identified using a combination of an in-house constructed mass spectra library of authentic standards,the public domain mass spectra library of the Max-Planck-Institute for Molecular Plant Physiology,and the commercial mass spectra library of the National Institute of Standards and Technology.14,18,24,25Where possible,all matching mass spectra were additionally confirmed by determination of the retention time and mass spectra by analysis of authentic standards.Resultant relative response ratios were normalized per gram extracted fresh weight as previously described.12Metabolite profile data is presented as fold changes with respect to the control which is set at1. Differences between the treated samples were considered as significant when the p-value using student’s t test was<0.05. The Bonferroni correction was applied to reduce the number of false positives and only metabolites significant after this correction were considered as most important.26,27 ResultsTranscriptomic Profiling.To establish the validity of the SCC system as a model to examine ABA responses,the effect of exposure to100µM ABA on transcript abundance(see Figure 1)growth rate and morphology(Supporting Information I)was initially examined.The expression levels of four different genes known to be ABA responsive in planta,myosin heavy chain-like protein(OsMyo1),28chlorophyll a/b-binding protein pre-cursor(OsCab26),28low temperature induced protein19 (OsLIP19)28and putative sphingosine kinase(OsSPHK)28were analyzed by QPCR.Expression was normalized to the control genes,OsActin,Os10SRNA,OsTubulin and OsGAPDH(Figure 1).Three of the four genes showed an ABA-dependent increase in transcript abundance.The increase was transient and either at the2h(OsCab26;Figure1B)or the4h(OsMyo1;Figure1A, OsLIP19;Figure1C)time point after ABA exposure.OsSPHK did not respond to ABA treatment(Figure1D)and surprisingly decreased relative to the no-ABA control.Measurement of the growth of SCCs following ABA exposure also suggested an effect that presented as an initial lag in growth caused by a loss in turgor but following osmotic adjustment the cells entered exponential phase and reached a similar biomass to the controls after18days culture(see Supplementary Figure I, Supporting Information).On the basis of these data,proteomic and metabolomic profiling was conducted at early time points (0.5,2.0,and6.0h)and is described below.Proteomic Profiling.A total of3284peptides(Supplemen-tary Table1,Supporting Information)were detected that corresponded to759proteins(minimal set)identified with two or more peptides and an additional583proteins if relying on only one peptide for identification.Only those proteins with2 or more peptide matches and with a p<0.05(in both Mascot and Paragon)were reported for greater confidence.The list of peptides identified and the set of proteins are presented in Supplementary Table1(Supporting Information).Figure2 illustrates the number of proteins identified based on the number of peptides that matched to that particular protein.AOryza sativa Cell Suspension Culture Proteomics research articlesJournal of Proteome Research•Vol.9,No.12,20106625pie-chart of the functional classifications of these proteins is presented in Figure 3.One of the interesting features of this data set was the identification of proteins that are predicted to have a relatively low abundance (including,for example,Skp1,pathogenesis related protein,14-3-3proteins and the cell division cycle protein 48),alongside proteins with a predicted,relatively high abundance (including,for example,enzymes of primary metabolism,for example,glycolytic and citric acid cycle pathways).The largest functional classification group,representing 38%of the proteins identified,was proteins involved in primary metabolic processes,including glycolysis and the citric acid cycle.The second largest group was proteins with an unknown function (18%)that were unable to be matched to any other proteins of known function,after BLAST searching against the NCBInr database.Proteins involved in stress responses con-stituted 7%of the data set.Translation factors,elongation factors and translation initiation factors were categorized into a single group “protein biosynthesis”,which included 6%of the proteins identified.Five percent of the proteins were involved in amino acid metabolism and another 4%included proteins that were involved in DNA or RNA binding categorized as “nucleic acid binding”proteins.Proteins involved in protein folding and transport made up to 3%each of identified proteins.Proteins responsible for maintaining the cell homeo-stasis by regulating the redox status constituted 3%and those involved in nucleotide biosynthesis included another 2%of the proteins.Other groups included proteins involved in the production of ATP -energy proteins (1%),proteins involved in nucleotide binding (1%),protein modification (1%),transcrip-tion (1%),cell cycle (<1%),cellular organization (1%),nucleo-some assembly (1%),protein degradation (<1%)and storage proteins contributed toward 1%of the data set.Relative Protein Abundance.Of the 759proteins identified,92proteins were able to be quantified after collating the data from the three biological replicates over a time period of ABAFigure 1.Normalized expression levels of OsMyo1,OsCab26,OsLIP19and OsSPHK gene transcripts.Q-PCR was used to examine the transcript abundance of the above genes following exposure to ABA over 0,2,4,6,and 8h.Light gray bars indicate expression levels of genes after 100µM ABA treatment and the dark gray bars are the levels of expression of control samples (treated with 100µL ethanol).Error bars represent (SD,n )3replicates.research articlesRao et al.6626Journal of Proteome Research •Vol.9,No.12,2010treatment at 0.5,2,and 6h relative to an untreated control,using the stringent criteria indicated in the methods section.The 92quantified proteins are listed in Supplementary Table 2(Supporting Information).The distribution of protein abundances is depicted in Figure 4.Eleven proteins (11.9%),which included phosphoenolpyru-vate carboxylase,sucrose synthase 2and OsGDI1(the three with the greatest changes)and aminopeptidase C and aconitate hydratase,show increased abundances of >1.25fold at at least one time-point and just 1protein (OSIGBa0148P16.5;1%)shows a decrease of <0.8fold at the 0.5h time point.A BLAST search of this protein revealed it to be similar to an unchar-Figure 2.Proteins assigned based upon the number of peptides identified.The graph shows the number of proteins assigned based on the number of peptides identified.The x -axis represents the number of peptides assigned to a single protein.The y -axis represents the number of proteins identified.Figure 3.Functional classification of proteins identified.The pie chart includes the 759proteins identified (see Supplementary Tables 1and II,Supporting Information)on the basis of two or more peptides and classified based on known and predicted functions as specified either in NCBI or Uniprot.Figure 4.Relative protein abundances.Box plots showing distribution of iTRAQ protein ratios on a log scale across the time-course of ABA treatment.All 92proteins are represented in this figure.Boxes define the 25th and 75th percentiles of the popula-tion.Asterisks indicate extreme outlying values (*)phosphe-nolpyruvate carboxylase,**)sucrose synthase 2,***)OsG-DI1).Oryza sativa Cell Suspension Culture Proteomicsresearch articlesJournal of Proteome Research •Vol.9,No.12,20106627acterized protein,Os04g0386600.It is however important to note that the above-mentioned proteins showed consistent increases considering the average values of the three biological replicates at the three different time points.However,25other proteins after a student t test showed a p value of <0.02with consistent changes across all three biological replicates were also of interest.Most of these proteins included primary metabolic enzymes and proteins involved in oxidative stress responses described in the Discussion (see ABA-responsive metabolites,proteins and pathways).Metabolite Profiling.The metabolite responses of rice SCCs to ABA (100µM)was examined over a time period of 0.5h,2and 6h relative to an untreated control.Metabolite levels were determined using GC-MS and a total of 148metabolites were identified which included 25amino acids (AAs),45organic acids (OAs),35sugars,19fatty acids,2polyamines,4sterols,5sugar acids,4sugar alcohols and 9miscellaneous compounds (Supplementary Table 3,Supporting Information).This is comparable to the 129compounds identified in the analysis of rice leaves.18In part,this may reflect the metabolic com-plexity of the SCC system under examination,but also,the increased maturity of GC-MS based system and compound libraries that were used for searching the data to identify metabolites.The identified metabolites and their fold-changes relative to the control samples are presented in Supplementary Table 3(Supporting Information)with a standard error to the mean ((SE).Although many metabolites showed a p-value <0.05after a Student’s t test,the Bonferroni correction was used as the threshold to reduce false discovery rate.The values that were found to be statistically significant after Bonferroni correction 26,27are presented in bold font in Supplementary Table 3.A surprisingly small number of metabolites (13;8.78%)showed statistically significant changes in response to ABA at one or more time points,indicating that the response was quite specific.Of the 13significantly altered metabolites,8displayed significant decreases at 0.5h,2at 2h,while 10were signifi-cantly changed after 6h (includes metabolites that showed significant changes at more than one time point).The distribution of metabolite abundances are depicted in Figure 5.Unlike the protein abundance distribution,no single metabolites displayed consistently altered abundance at more than one time-point.Some of the outlier metabolites (most significantly changed)include glucuronate,erythritol,2-oxo-glutarate,galactose,aspartate and fructose-6-phosphate (Figure 5).The abundance of fumarate decreased significantly at both the 2h (0.7fold)and 6h (0.2fold)time points.This compound is one of the core metabolites of the citric acid cycle.Notably,three of the four other metabolites identified that are part of the citric acid cycle,citrate,isocitrate,malate and succinate also displayed decreased abundance following exposure to ABA,although none of these decreases were statistically significant.Tyrosine (Tyr)showed a decrease in abundance at the 0.5h (0.7fold)and 6h (0.6fold)time points.This metabolite can be decarboxylated to form tyramine through the action of a tyrosine decarboxylase (EC 4.1.1.28).29Three other organic acids displayed significant decreases in abundance during ABA treatment,4-hydroxybenzoate,itaconate and propanoic acid.4-Hydroxybenzoate,involved in the degradation of benzoate,displays a similar pattern of decreased abundance as Tyr.Benzoate also displayed a decrease in abundance following exposure to ABA,although it was not statistically significant.The abundance of itaconate significantly decreased at the 0.5h (0.5fold)and 6h (0.3fold)time points.cis -Aconitate is converted to itaconate releasing CO 2by the action of the enzyme cis -aconitate carboxylyase.29cis -Aconitate also dis-played a large decrease at the 6h time points,however,it increased at the 0.5h time point.Mannitol,a sugar alcohol,involved in fructose (Fru)and mannose metabolism 29was slightly reduced in abundance at the 0.5and 2h time point but displayed a significant (<0.6fold)reduction in abundance at the 6h time point.Fru-6-phosphate (Fru-6-P)increases rapidly in the first 0.5h (6-fold)and then gradually decreases over the 2and 6h time points.DiscussionRice SCCs were established as a model system to study ABA responses by studying known ABA responsive genes.Three of the four in planta ABA responsive genes examined,OsMyo1,OsCab26and OsLIP19,responded to ABA treatment within 4h of application.As reported by Lin et al,28our results are consistent in showing that the OsMyo1transcript responded to ABA in a manner similar to whole plants by increasing within 4h.28Cab26is both negatively regulated by ABA in soybean cotyledons during embryogenesis 30and induced by ABA in rice shoots.28In rice SCCS the OsCab26transcript levels increased at 2h of ABA treatment.These reports suggest that the Cab genes are differentially expressed during different stages of plant development and are under different mechanisms of regulation.We also observed the induction of OsLIP19at 2h further illustrating that SCCS can mimic whole plants.In cDNA macroarray and RT-PCR experiments OsSPHK transcript did increase after 2h of ABA treatment.28From the Q-PCR data obtained (Figure 1D),there was no increase in the transcript abundance of OsSPHK over the time-course of ABA treatment.This could be because the transcript was activated within 2h of treatment (first time-point analyzed in the Q-PCR)with ABA similar to that previously observed for rice shoots.28These results indicate that the SCCs respond to ABA treatment in a similar,but not always identical manner to that reported in planta .We therefore concluded it was a useful model to apply an ’omics technology approach to studying the proteome and metobolome responses to ABA.Figure 5.Relative metabolite abundances.Box plots showing distribution of relative metabolite fold change values on a log scale across the time-course of ABA treatment.All 148metabo-lites are represented in this figure.Boxes define the 25th and 75th percentiles of the population.research articlesRao et al.6628Journal of Proteome Research •Vol.9,No.12,2010。

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单酰甘油脂肪酶调节促进癌症发病的一


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Tumor cells display progressive changes in metabolism that correlate with malignancy, including development of a lipogenic phenotype. How stored fats are liberated and remodeled to support cancer pathogenesis, however, remains unknown. Here, we show that the enzyme monoacylglycerol lipase (MAGL) is highly expressed in aggressive human cancer cells and primary tumors, where it regulates a fatty acid network enriched in oncogenic signaling lipids that promotes migration, invasion, survival, and in vivo tumor growth. Overexpression of MAGL in nonaggressive cancer cells recapitulates this fatty acid network and increases their pathogenicityphenotypes that are reversed by an MAGL inhibitor. Impairments in MAGL-dependent tumor growth are rescued by a high-fat diet, indicating that exogenous sources of fatty acids can contribute to malignancy in cancers lacking MAGL activity. Together, these findings reveal how cancer cells can co-opt a lipolytic enzyme to translate their lipogenic state into an array of protumorigenic signals
蛋白组学和代谢组学

蛋白组学和代谢组学

百泰派克生物科技
蛋白组学和代谢组学
蛋白组学和代谢组学分别是研究蛋白质组和代谢组的学科。

联合分析蛋白组和代谢组有助于更深入地研究生物体的生命活动等。

百泰派克生物科技提供基于质谱的代谢组学分析服务。

蛋白质组学和代谢组学
组学，是对生物体生命活动规律的一种全局研究，即从整体上研究一个生物体、一个细胞或一个组织。

组学研究最早开始于基因组学，蛋白质组学和代谢组学都是后基因组学时代兴起的学科。

蛋白质组学指从整体水平上大规模的研究蛋白质大分子的特征，包括蛋白质的表达水平、翻译后修饰情况和蛋白质与蛋白质的相互作用等。

代谢组学指从整体水平上大规模的研究生物体、细胞或组织中的小分子物质，包括代谢物的鉴定、表达水平分析及其相互作用分析等。

蛋白组学和代谢组学均可应用于多种领域，比如疾病诊断、医药研制开发、营养食品科学、毒理学、环境学和植物学等领域。

蛋白质组和代谢组均可以用液相和质谱技术来进行分析检测。

蛋白质组学和代谢组学联合分析
相比单一组学的研究，多组学联合分析能更全面、更深入的探索生命活动的机制和原理等。

例如将蛋白质组学分析与代谢组学分析相结合，其中代谢组学可以为蛋白质组学数据的功能解释提供信息，而蛋白质组学分析则通过突出显示参与的酶或酶促途径可以帮助更好地理解代谢组学的数据。

例如，蛋白质组学和代谢组学的结合有助于阐明各种疾病的分子机制，包括癌症、精神疾病和心血管疾病等。

脉红螺幼虫变态过程多组学解析及关键基因的调控作用

脉红螺幼虫变态过程多组学解析及关键基因的调控作用

博士学位论文脉红螺幼虫变态过程多组学解析及关键基因的调控作用作者姓名：宋浩指导教师: 张涛研究员（博士）中国科学院海洋研究所学位类别: 理学博士学科专业: 海洋生态学研究所: 中国科学院海洋研究所2018年6 月Understanding the Metamorphosis in Veined Rapa Whelk Rapana venosa from omics insight and the regulation role of key genes on itsmetamorphosisA Dissertation Submitted toUniversity of Chinese Academy of SciencesIn partial fulfillment of the requirementFor the degree ofDoctor of philosophyByHao SongDissertation Supervisor : Professor Tao ZhangInstitute of Oceanology, Chinese Academy of SciencesJune, 2018摘要摘要脉红螺（Rapana venosa），自然分布于我国的渤海、黄海和东海以及日本海等海域，是我国重要的经济贝类，但在欧洲黑海、爱琴海、美国切萨皮克湾、阿根廷拉普拉塔河等海域为生物入侵种，对当地的双壳贝类资源造成破坏。

变态过程是贝类生活史中重要的发育阶段，变态的成功与否直接关系到贝类种群资源变动。

因此，研究脉红螺幼虫变态机理，对于促进其苗种繁育、资源恢复、生物入侵防控等工作的开展具有重要的现实和理论意义。

本研究利用RNA-seq、iTRAQ、GC-MS、Real time PCR等技术对脉红螺幼虫变态过程分子机理展开研究，从转录组水平、蛋白质组水平和代谢组水平揭示了幼虫变态过程调控特征，筛选了脉红螺变态过程中的差异表达的关键转录本/蛋白组/代谢物，并对它们在变态中发挥的潜在生物学功能进行了探讨；开展了脉红螺幼虫变态过程microRNA的响应特征研究，筛选了变态中的差异表达的microRNA并对它们潜在调控的靶基因进行预测，揭示其在变态过程中所发挥的功能；筛选了在脉红螺变态发育过程中和在不同组织中稳定表达的内参基因，为将来进一步研究关键基因在变态过程中的表达水平提供基础；获得关键基因5-HT receptor和NOS的cDNA序列，探讨了其在脉红螺变态过程中表达特点及调控机理。

柠檬提取物相关SCI文献

柠檬提取物相关SCI文献

Process Biochemistry 51(2016)213–219Contents lists available at ScienceDirectProcessBiochemistryj o u r n a l h o m e p a g e :w w w.e l s e v i e r.c o m /l o c a t e /p r o c b ioAcid tolerance response of Tetragenococcus halophilus :A combined physiological and proteomic analysisGuiqiang He a ,Chongde Wu a ,b ,∗,Jun Huang a ,Rongqing Zhou aaCollege of Light Industry,Textile &Food Engineering,Key Laboratory of Leather Chemistry and Engineering,Ministry of Education,Sichuan University,Chengdu 610065,China bLiquor Making Biological Technology and Application of Key Laboratory of Sichuan Province,Sichuan University of Science &Engineering,Zigong 643000,Chinaa r t i c l ei n f oArticle history:Received 31August 2015Received in revised form 17November 2015Accepted 23November 2015Available online 11December 2015Keywords:Tetragenococcus halophilus Acid stressStress response Proteomic analysisa b s t r a c tTetragenococcus halophilus is known to flourish in extreme salt environments,and frequently existed during the manufacture of fermented foods,where various environmental stresses are encountered.In this study,acid tolerance response of T.halophilus was investigated based on physiological and proteomic analysis.The optimal acid-adaptation condition was optimized to stimulate acid tolerance response effec-tively.After acid adaptation at pH 4.0for 1h,the highest survival rate at lethal pH 2.5was observed.Analysis of the physiological data showed that higher intracellular pH and NH 4+pool were detected in cells adapted at pH 4.0compared with cells without acid adaptation.In addition,the activities of hexok-inase,pyruvate kinase,and lactate dehydrogenase were determined,and significantly higher activities were monitored in cells after acid parison of the intracellular amino acid pools indicated that six amino acids (glutamate,aspartate,isoleucine,leucine,citrulline,ornithine)exhibited notable alternations during acid treatments,and acid pre-adaption led to higher pools of amino acid compared to that without acid pre-treatment.Proteomic analysis demonstrated that eight proteins (Glk,Pfk,Fba,Gap,Gpm,Eno,Pyk,and Ldh)involved in carbohydrate metabolism and three classic stress response proteins (Ssb,UspA,and GroL)were up-regulated after acid adaptation.Results presented in this study may help to further understand the acid tolerance response in T.halophilus and improve the industrial performance of this species.©2015Elsevier Ltd.All rights reserved.1.IntroductionTetragenococcus halophilus is one of the halophilic lactic acid bacteria found in extreme salt environments,and it is one of the most osmotolerant of all the prokaryotes [1].This halophilic bac-terium plays an important role in the production of soy sauce,soy paste,fish paste,and Chinese horsebean-chili-paste [2–4].Previous research revealed that T.halophilus contributed to the formation of aroma in fermented foods as they produced numerous volatile compounds,including 2-methylpropanal,3-methylbutanal,and 4-ethyl guaiacol [2,5].Therefore,the addition of T.halophilus as starter culture for flavor improvement has been proposed in many fermented foods [3–5].Such volatiles also act as antimicrobials that can confer a competitive advantage,via their chaotropic∗Corresponding author at:College of Light Industry,Textile &Food Engineering,Sichuan University,Chengdu 610065,China.Fax:+862885405237.E-mail address:cdwu@ (C.Wu).activities [6–8].However,T.halophilus ,similar to other lactic acid bacteria,encounters various environmental challenges including chaptropicity-induced,osmotic,acidic and oxidative stresses dur-ing the manufacture of fermented foods,which lead to the decrease of metabolic capacity and production efficiency.Thus,to engineer the robustness of lactic acid bacteria may contribute to enhance the industrial application and industrial functionality of this species.To cope with the harsh conditions,lactic acid bacteria employed a variety of strategies,including the up-regulation of stress response proteins,maintaining the cell membrane functionality,and metabolic shifts [9–12].Based on these results,many feasi-ble strategies have been proposed to increase the stress resistance,and increased robustness of lactic acid bacteria was also acquired.For example,acid stress led to the up-regulation of DNA repair protein RecO in Lactobacillus casei ,and the acid-resistant mutant exhibited higher expression level compared to the corresponding control strain [9].To further validate the protective role of RecO,a RecO-overproducing mutant was constructed by using Lactococcus lactis ,and the mutant exhibited higher tolerance to acid,salt and/10.1016/j.procbio.2015.11.0351359-5113/©2015Elsevier Ltd.All rights reserved.214G.He et al./Process Biochemistry51(2016)213–219oxygen stresses[13].Wu et al.[9]reported that acid stress induced the accumulation of aspartate in L.casei.Validation of the data was performed by the exogenous addition of aspartate to the medium, and at least65.8%higher biomass was observed during growth at pH4.3[14].Acid tolerance response is a widely existed phenomenon in LAB, which made these organisms less susceptible to lethal acid stress by prior exposure of the cells to acidic conditions[12,15–17].More-over,acid tolerance response appears to confer protection against other stresses in addition to severe acid stress[18].However,infor-mation is still lacking on mechanisms used by lactic acid bacteria to modulate acid tolerance response.In this study,we optimized the conditions for acid tolerance response induction in T.halophilus,and then analyzed its effects on physiological characters including intracellular pH,intracellu-lar pools of amino acids and key enzymatic activities.In addition, a comparative proteomic analysis was performed between cells with or without acid adaptation.This result may gain insights into, and contribute knowledge to,the mechanisms underlying the acid tolerance response.2.Materials and methods2.1.Strains and growth conditionsThe strain used in this study was T.halophilus CGMCC3792, which was originally isolated from soy sauce moromi and then identified via physiological,biochemical,and16S rDNA sequence analysis[3].Cultures were grown statically in GM17(M17broth (Oxide)supplemented with0.5%(w/v)glucose)at30◦C for20h.2.2.Acid stress experimentTo investigate the acid tolerance response,cells grown to mid-exponential growth phase in GM17were harvested,centrifugated at10000×g for5min,washed and resuspended in GM17adjusted to different pHs with1mol/l hydrochloric acid for pre-adaptation. After pre-adaptation for1h,cells were harvested and washed as noted and suspended in GM17adjusted to acid stress at pH2.5.Cells challenged at pH2.5were serially diluted at spotted in triplicate onto GM17agar plates to determine the viability.2.3.Measurement of intracellular pH(pH i)pHi was measured by thefluorescence method developed by Breeuwer et al.[19]using5(and6-)-carboxyfluorescein succimidyl ester as thefluorescent probe.Calibration curves establishing the relationship between extracellular pH and intracellular pH were established to exclude artifacts caused by environmental conditions.Loading of cells with5(and6-)-carboxyfluorescein succimidyl ester,determination of pH i,and calibration of pH i all followed the procedure described previously[19].2.4.Determination of intracellular ammoniaCells subjected to different treatments were harvested by cen-trifugation at12000×g for10min,washed twice with200mM phosphate-buffer saline(PBS,pH7.5),and then resuspended in the same buffer.The solution was sonicated on ice for10min and followed by centrifugation at12000×g for10min.The amount of ammonia in the supernatant was analyzed with the ammonia assay kit(Sigma,USA)according to manufacturer’s instructions.2.5.Determination of enzymes activitiesCells subjected to different treatments were harvested by cen-trifugation at12000×g for10min,washed twice with ice-cold saline(0.85%NaCl,w/v),and resuspended in an equal volume of phosphate-buffer saline(PBS,0.2M potassium phosphate,2mM EDTA,pH7.0).The cell-free extract was prepared according to method described by Zhang et al.[20],and the cell-free extract was used for determination of enzyme activity.The activities of hexok-inase,pyruvate kinase,and lactate dehydrogenase activities were analyzed with the assay kits(Nanjing Jiancheng,China)according to the manufacturer’s instructions.2.6.Determination of intracellular amino acidFor the extraction of amino acids,cells subjected to differ-ent treatments were harvested by centrifugation at12000×g for 10min,washed twice,resuspended in1ml of200mM phosphate buffer solution(pH7.0),and then boiled for15min.Cell debris was discarded by centrifugation(12000×g,10min,4◦C).The super-natants were treated at room temperature by addition of1ml of 10%tricarboxylic acid for10min.The mixture was then centrifu-gated(12000×g,4◦C)again for10min,and the supernatants were analyzed with HPLC according to the method of Fountoulakis and Lahm[21].2.7.2D gel electrophoresis,gel image analysis and proteinidentificationCells treated with different pHs(7.0and4.0)for1h were cen-trifugated at10000×g for5min,washed for three times with distilled water to remove the residual acidified medium.The whole-cell extracts were prepared using the BioRad kit and the con-centration of each protein sample was determined using the BioRad Protein Assay Kit(BioRad)with bovine serum albumin as a stan-dard.Each sample was applied to immobilized pH gradient(IPG) strips(18cm,pH4–7,BioRad)with afinal concentration of600␮g protein in350␮l rehydration buffer.Isoelectric focusing(IEF)and SDS-PAGE were performed according to the method described by Wu et al.[12].After SDS-PAGE,the2D gels were stained with0.1% Coomassie blue R-250.The stained gels were scanned using Imagescanner(GE Health-care).Comparative analysis of the protein spots was performed using Image Master6.02D platinum software(GE Healthcare). Proteins that displayed at least2-fold variations were taken into account for further analysis.The proteins spots with significant change were excised using gel plugs,transferred to Eppendorf tubes,then digested with20␮l of10ng/␮l proteomics sequencing grade trypsin at37◦C for16h and rehydrated in500␮l of50mM NH4HCO3(pH8.0).Supernatants of0.5␮l were spotted directly onto the MALDI plate for proteins identified by mass spectrometry as described previously[22].2.8.Statistical analysisAnalysis of variance(one-way ANOVA)with Duncan’s test was performed to evaluate statistical differences.Differences between samples with p-values p≤0.05were considered to be statistically significant.3.Results and discussion3.1.Acid tolerance response of T.halophilus CGMCC3792Acid tolerance response is widely reported in many microbes such as L.casei[12],Lactobacillus sanfranciscensisG.He et al./Process Biochemistry51(2016)213–219215Fig.1.Effect of different acid pre-treatment pHs on the survival of T.halophilus during acid challenge at pH2.5for1h.Cells grown to mid-exponential growth phase were pre-exposed at different pHs(3.5,4.0,4.5,5.0,5.5,6.0),and then were acid challenge at pH2.5for1h.Error bars indicate standard deviations(n=3).Significant differences among the groups are marked with different letters(p<0.05). [17],Lactobacillus delbrueckii[18],Bifidobacterium longum[23], Salmonella Typhimurium[24],and Vibrio vulnificus[25].However, no information is available concerning the acid tolerance response of T.halophilus.In this study,the optimal condition for acid toler-ance response induction in T.halophilus was investigated(Fig.1). Cells pre-adaptation at different pHs for1h were challenged at pH2.5,and the survival rates were determined.Data presented in Fig.1showed that the survival of cells gradually declined with the increment of pre-adaptation pH from4.0to6.0,and the highest survival was observed by pre-exposure of cells at pH4.0 for1h.Thus,this was chosen as the condition for acid tolerance response induction in T.halophilus.Wu et al.[12]optimized the condition for acid tolerance response induction in L.casei,and the results showed that the cells pre-adaptation at pH4.5for1h exhibited significantly higher survival during acid stress at pH 3.5.In addition,similar result was also illustrated in B.longum [23].These results suggest that acid tolerance response may be triggered by exposure to a specific sub-lethal pH.3.2.Changes in pH i and intracellular NH4+during acidadaptationFig.2showed the changes in intracellular pH(pH i)and intra-cellular NH4+during acid treatments.After acid stress at pH2.5 for1h,pH i sharply decreased from7.05to4.65.However,signifi-cantly higher pH i was observed in cells pre-adapted at pH4.0for 1h prior to acid stress at pH2.5(Fig.2A).To further validate this data,intracellular NH4+content was determined(Fig.2B).As is shown,acid treatment led to the increase in intracellular NH4+ content from0.35nmol/(mg protein)to0.52nmol/(mg protein), and the cells pre-adapted at pH4.0exhibited higher NH4+content compared with those without pre-adaptation.These results sug-gest that induction of acid tolerance response at a mildly acidic pH may protect T.halophilus against acid stress by maintaining higher pH i and NH4+content.Generally,pH i plays important roles in the growth and metabolism of lactic acid bacteria,and it affects the uptake of nutrients,and the synthesis of protein and nucleic acid [26].Lactic acid bacteria employ a variety of strategies to maintain the homeostasis of pH i,including formation of NH4+,regulation of the activities of proton-translocating ATPase and amino acid metabolism[9,14,23,27].Jin et al.[23]analyzed the acid tolerance response of B.longum by using RNA-sequencing,and many genes involved in regulating pH i were up-regulated.To cope with acid stress,B.longum initiated the F0F1-ATPase system to discharge H+, and neutralize excess H+by producing NH3[23].3.3.Changes in key enzyme activities during acid stressEffects of acid shock on the activities of key enzymes in mainstream metabolic pathway was investigated(Fig.3).Hexoki-nase catalyzes the formation of sugar-6-phosphates from glucose or other hexoses,and it is important for the regulation of Embden–Meyerhof–Parnas(EMP)pathway.The activity of HK was measured after acid treatments,and differences in enzyme activ-ities were observed(Fig.3A).Significantly higher activity was measured after acid adaptation at pH4.0,compared with that in the control cells(without acid treatment).As expected,acid stress at pH2.5led to decreased activity of HK.However,the cells pre-adapted at pH4.0exhibited higher HK activity after acid stress at pH2.5than those without acid pre-adaptation.Pyruvate kinase is alsoa key enzyme in glycolysis,and lactate dehydrogenase catalyzed the conversion of lactate to pyruvate is responsible for the produc-tion of ATP.It is worth noting that same tendency was observed in the activities of pyruvate kinase and lactate dehydrogenase during different acid treatments.After acid adaptation,higher activities of pyruvate kinase and lactate dehydrogenase were monitored,and the cells subjected to acid stress prior to pre-exposure at pH4.0 exhibited higher enzyme activities.These results suggest that acid pre-adaptation may confer cells with higher metabolic activities and the key enzymes involved in the mainstream metabolic path-way may be a key factor for acid tolerance.3.4.Changes in intracellular amino acid pools during acid stressFig.4showed the changes in intracellular amino acid pools during acid stress,and6amino acids which exhibited significant alterations were presented.As for glutamate and aspartate,no obvi-ous change was observed after acid pre-treatment at pH4.0.While the contents of citrulline,ornithine,and isoleucine increased dur-ing acid pre-treatment.Only the content of leucine was sharply decreased when shocked at pH4.0for1h.However,it was worth noting that the cells challenged at pH4.0and then subjected to acid stress at pH2.5exhibited higher pools of amino acid(except Orn)compared to that without acid pre-treatment at pH4.0prior to acid stress.No obvious difference in content of ornithine was observed in cells at pH2.5with or without acid pre-adaptation, and this may be ascribed to the significant increment in accumu-lation of citrulline during acid stress.Amino acid metabolism in LAB serves a number of physiological roles such as intracellular pH hemostasis,production of ATP or redox power,and resistance to stresses[28].In addition,many amino acids can act as com-patible solutes which protect macromolecular structures against various forms of stresses[29].This is due to their kosmotropicity, which enables them to stabilize membranes and proteins that are otherwise disordered by environmental stresses[30,31].Previous research reported that glutamate contributed to acid resistance of LAB through glutamate decarboxylase by converting a molecule of extracellular glutamate to␥-amino butyrate(GABA)at the expense of consuming an intracellular proton[32,33].The net effect is to reduce the proton concentration in the cell and GABA is less acidic than glutamate,which helps to alkalinize the environment[34].Wu et al.[9]demonstrated that aspartate protected L.casei against acid stress,and the addition of aspartate to the medium significantly enhanced the acid tolerance.Upon acid stress,L.casei shifted the metabolic pathway by increasing theflux from aspartate to arginine (arginine deiminase system,ADI system)and decreasing theflux from aspartate to asparagine[9].The ADI system has been identified in many bacteria,including Escherichia coli,Streptococcus mutans,L. lactis,and L.casei[9,35–37].This pathway converted the arginine216G.He et al./Process Biochemistry51(2016)213–219Fig.2.Changes in intracellular pH(A)and intracellular NH4+content(B)during acid treatment.Cells grown to mid-exponential growth phase were acid challenge at pH2.5 for1h.Dotted lines represent cells challenged at pH2.5without pre-adaptation,while solid lines represent cells pre-adapted at pH4.0for1h prior to acid challenge at pH 2.5.Before adaptation represents cells were not subjected to acid treatment,Acid adaptation represents cells were pre-adapted at pH4.0for1h,while Acid stress represents cells were shocked at pH2.5for1h.Error bars indicate standard deviations(n=3).Significant differences among the groups are marked with different letters(p<0.05).Fig.3.Effects of acid treatments on the activities of hexokinase(A),pyruvate kinase(B),and lactate dehydrogenase(C).BA:before acid adaptation;AA:acid adaptation at pH4.0for1h;AS:acid stress at pH2.5for1h;A-AS:acid stress at pH2.5for1h prior to acid adaptation at pH4.0for1h.Error bars indicate standard deviations(n=3). Significant differences among the groups are marked with different letters(p<0.05).Fig.4.Effect of acid treatments on amino acid metabolism of lactic acid bacteria.A:changes in intracellular amino acid pools during acid treatments.B:amino acid metabolism of lactic acid bacteria.Error bars indicate standard deviations(n=3).Significant differences among the groups are marked with different letters(p<0.05).G.He et al./Process Biochemistry51(2016)213–219217to citrulline and ornithine,and concomitant NH3and ATP produc-tion,which may contribute to the intracellular pH hemostasis[33]. This result is agreement with the data of intracellular pH and NH3 content.In addition,in this study,higher contents of isoleucine and leucine were detected in cells after acid pre-adaptation.Pre-vious report suggested that branched amino acids(BCAA)were associated with acid tolerance of LAB,and genes involved in BCAA biosynthesis were upregulated during acid stress[38].This may be ascribed to the fact that the formation of BCAA involves the forma-tion of NH3by glutamine synthetase,and maintains the internal pH[39].3.5.Proteomic analysis of acid tolerance response bytwo-dimensional electrophoresisTo further elucidate the acid tolerance mechanism utilized by T. halophilus,proteins extracted from acid-adapted and control sam-ples were compared by two-dimensional electrophoresis(2-DE). The representative2-DE gels are shown in Fig.5.The gels maps were analyzed and the proteins which exhibited more than1.5-fold higher expression were labeled with numbers and subjected to identification.A total of32proteins were identified and are sum-marized in Table1.As shown in Table1,after acid adaptation at pH 4.0for1h,the expressions of28proteins up-regulated and4pro-teins(Spots2,7,13,and26)down-regulated compared with the control.Fig.6shows the changes of the proteins involved in the cen-tral metabolism,and dramatic alterations took place in the protein expression during acid adaptation.Hpr(spot18)is a heat-stable phosphocarrier protein involved in sugar phosphotransferase sys-tem(PTS),and the increased expression of Hpr may lead to higher activity in glucose utilization and ATP generation through glycoly-sis,resulting in enhanced ability of cells to maintain pH i[9].Eight proteins(Spots5,6,8,9,10,12,14,15)related to glycolysis were detected during acid adaptation,and all of the proteins were sig-nificantly up-regulated in the acid adapted cells compared to the control at pH7.0.The higher expression of proteins involved in glycolysis in acid-adapted cells suggested that higher metabolic activities were obtained in cells after acid pre-adaptation.Gen-erally,the ability of cells to transport and metabolize sugar is a feature that allows these bacteria to grow and survive during acid stress.The enhanced activity in sugar metabolism may lead to an increase in ATP production to support the H+extrusion under acidic conditions.Thus,higher survival was observed in cells after pre-adaptation in sublethal condition,and similar results were also reported previously[12,15].d-alanine-d-alanine ligase(Ddl), which is involved in the synthesis of peptidoglycan was detected in both cells.After acid adaptation,the cells exhibited higher expres-sion compared to the control at pH7.0(Table1).The enhanced expression of Ddl may contribute to the synthesis of peptidoglycan that subsequently maintained the cellular structure integrity,and it might help survival at low pH.In addition,some expression factors and stress response pro-teins were also identified in T.halophilus after acid treatment. Single-stranded DNA-binding protein Ssb(spots3and30)is essential for replication of the chromosome and is involved in DNA recombination and repair[40],and enhanced synthesis was observed in cells after acid treatment.Similarly,this need for chro-mosome repair is also seen in chaotrope stress[30].Consequently, the higher expression of this protein after acid adaptation is con-sidered as a mechanism of the acid survival of the cells.This is consistent with the results obtained by Streit et al.[18].Universal stress protein UspA(Spot25)related to nucleotide-binding protein over-expressed after acid treatment(Table1).UspA was induced by different stress conditions and were identified in acid stress of many microbes such as Lactobacillus casei[41],Lactobacillus Fig.5.Two-dimensional electrophoresis gels of whole cytoplasm proteins of T. halophilus exposed at pH7.0(A)and pH4.0(B)for1h.The identified proteins are indicated by an arrow and number and listed in Table1.plantarum423[42],and Listeria monocytogenes[43].It appears, in some cases,to be linked to resistance to DNA-damaging agents and to respiratory uncouplers[29,30,44].The increased expression may protect the cells against the damage exerted by acid stress, but the exact physiological role of UspA protein in T.halophilus needs more research.GroL(spot29)is a well-characterized classical stress shock protein(60-kDa chaperonin),which play a role in pro-tein folding[45].In this study,it was identified in cells both before and after acid adaptation.As expected,after acid treatment,higher expression of GroL was observed in cells,suggesting potential roles of GroL in acid survival.Previous research also demonstrated that more abundant expression of GroL was detected under acid stress [9,42,46].In this study,acid tolerance response of T.halophilus was investi-gated by employing physiological and proteomic methods.During218G.He et al./Process Biochemistry51(2016)213–219Table1Identification of T.halophilus affected by acid adadptation.Spot no.NCBI accession no.Putative function Gene locus Gene Mass(Da)pI Fold change in intensityrelative to pH7.01gi|352517828Glycerol kinase TEH16450glpK56131.6 4.57 1.61±0.132gi|352518139Ribosome recycling factor TEH19650frr20910.8 4.81−1.82±0.093gi|352516181Single-stranded DNA-binding protein TEH00080ssb18864.3 4.76 1.90±0.144gi|352516351d-Alanine–d-alanine ligase TEH01770ddl40276.3 4.87 1.88±0.165gi|352518161Glucokinase TEH19870glk34602.4 4.76 2.42±0.176gi|352518632l-Lactate dehydrogenase TEH24580ldh35041.8 4.72 2.90±0.187gi|352517519Transketolase TEH13450tkt72335.6 4.77−1.62±0.198gi|352517161Fructose-bisphosphate aldolase TEH09870fba31482.7 4.84 1.70±0.249gi|3525170716-Phosphofructokinase TEH08970pfk34427.6 5.51 1.74±0.1610gi|352517949Glyceraldehyde-3-phosphate dehydrogenase TEH17750gap35758.1 4.79 2.20±0.3411gi|352516972Citrate lyase beta subunit TEH07980citE32347.7 4.71 1.9±0.2112gi|352517072Pyruvate kinase TEH08980pyk63307.3 4.81 1.50±0.1213gi|352516187Adenylosuccinate synthetase TEH00140purA48127.5 5.52−1.7±0.0814gi|352517946Enolase TEH17720eno46628.6 4.58 2.21±0.2415gi|352518465Phosphoglycerate mutase TEH22910gpm25427.0 5.15 1.80±0.8216gi|352518127Hypothetical protein TEH19530TEH1953011891.2 4.77 1.83±0.2517gi|352517890Catabolite control protein A TEH17160ccpA36384.0 5.17 1.92±0.3518gi|352516729Putative6-phosphogluconolactonase TEH05550pgl37728.5 5.14 1.75±0.1319gi|352517920Putative ribosome-associated protein TEH1746021275.9 5.21 1.52±0.0720gi|352518048Alanine dehydrogenase TEH18740ald39665.6 5.02 2.13±0.1821gi|352518051Putative phosphopantothenoylcysteine synthetase TEH18770coaB27529.3 5.7 1.64±0.9222gi|352518514Hypothetical protein TEH23400TEH2340064126.7 5.4 1.85±0.1923gi|352518640Putative NADH dehydrogenase TEH2466044569.5 5.31 2.42±0.1524gi|352517589Putative oxidoreductase TEH1415044542.3 4.54 1.63±0.1325gi|352518338UspA family protein TEH2164017457.9 4.65 1.92±0.2326gi|352517161Fructose-bisphosphate aldolase TEH09870fba31482.7 4.84−1.73±0.0627gi|352518605Hypothetical protein TEH24310TEH2431019537.9 4.73 2.31±0.1928gi|352518124Phosphocarrier protein HPr TEH19500ptsH9301.7 4.88 1.72±0.1229gi|35251644760kDa chaperonin TEH11250groL57740.7 4.47 1.82±0.2530gi|352516181Single-stranded DNA-binding protein TEH00080ssb18864.3 4.76 1.90±0.2431gi|352516877Hypothetical protein TEH07030TEH0703022900.3 4.9 2.21±0.4332gi|352516447Dihydroxyacetone kinase nucleotide-binding subunit DhaL TEH02730dhaL21888.1 5.36 1.77±0.26parative expression of the proteins involved in glycolysis pathway during acid adaptation.Expression profiles shown are based on standardized log2ratio values by using the TIGR MeV software.The color bar indicates the fold change in intensity.acid adaptation,a global regulation was induced and a number of changes took place in T.halophilus tofight against acid injury.Thus, results presented in this study may further facilitate the under-standing the acid tolerance response in T.halophilus,and help to enhance the industrial applications of this species.Moreover,based on this,many feasible strategies could be proposed to enhance the acid tolerance of T.halophilus including engineering the expression of key proteins/enzymes or adding potential protective agent.。