Highly precise quantification of protein molecules per cell during stress and starvation responses...

Highly Precise Quantification of ProteinMolecules per Cell During Stress andStarvation Responses in Bacillus subtilis*□S

Sandra Maa�‡, Gerhild Wachlin‡, Jorg Bernhardt‡, Christine Eymann‡,Vincent Fromion§, Katharina Riedel‡, Dorte Becher‡¶, and Michael Hecker‡

Systems biology based on high quality absolute quanti-fication data, which are mandatory for the simulation ofbiological processes, successively becomes importantfor life sciences. We provide protein concentrations onthe level of molecules per cell for more than 700 cytosolicproteins of the Gram-positive model bacterium Bacillussubtilis during adaptation to changing growth conditions.As glucose starvation and heat stress are typical chal-lenges in B. subtilis’ natural environment and induce both,specific and general stress and starvation proteins, theseconditions were selected as models for starvation andstress responses. Analyzing samples from numerous timepoints along the bacterial growth curve yielded reliableand physiologically relevant data suitable for modeling ofcellular regulation under altered growth conditions. Theanalysis of the adaptational processes based on proteinmolecules per cell revealed stress-specific modulation ofgeneral adaptive responses in terms of protein amountand proteome composition.

Furthermore, analysis of protein repartition during glu-cose starvation showed that biomass seems to be redis-tributed from proteins involved in amino acid biosynthesisto enzymes of the central carbon metabolism. In contrast,during heat stress most resources of the cell, namelythose from amino acid synthetic pathways, are used toincrease the amount of chaperones and proteases. Anal-ysis of dynamical aspects of protein synthesis during heatstress adaptation revealed, that these proteins make upalmost 30% of the protein mass accumulated during earlyphases of this stress. Molecular & Cellular Proteomics13: 10.1074/mcp.M113.035741, 2260–2276, 2014.

Recently technical approaches in systems biology havebecome more and more important for the life science com-munity. Successful modeling of biological pathways as part of

these approaches strongly depends on quantitative, high-quality, and validated data sets (1). Proteins are an importantpart of these attempts to uncover the systemic properties ofbiological systems as they represent the central players in thecomplex cellular metabolic and adaptational network (2).

Although relative protein quantification methods allow forcomparison of protein abundances in samples and to char-acterize the proteome dynamics in cellular systems, thesedata are not sufficient for mathematical modeling in systemsbiology. Furthermore, the availability of protein concentrationsat the proteome level can provide new insights in what isgoing on in the cell upon stress, and thus enable us to betterunderstand how cells adapt to changing conditions. Knowingintracellular protein concentrations is essential in order toobtain a real mass balance leading to evaluation of the costsof running an active metabolic pathway or expressing en-zymes for stress responses. In order to provide suitableproteomic data for systems biology, techniques for globalabsolute quantification of proteins recently emerged. Theseapproaches make use of quantitative Western blotting (3),mass spectrometry (4, 5), or merge traditional two-dimen-sional polyacrylamide gel electrophoresis (two-dimensionalPAGE)1 and mass spectrometry (6) to determine cellular pro-tein concentrations on a global scale. Entirely mass spec-trometry-based strategies have recently convincingly demon-strated the capacity to quantify about half of the predictedproteome of Leptospira interrogans (5) and therefore providemore comprehensive data for systems biology than two-di-mensional PAGE based methods (6, 7). Although these gel-based methods are biased toward high-abundant proteins,usage of MS-calibrated two-dimensional gels allows distin-guishing even between different protein isoforms caused bypost-translational modifications without missing values alonga time course experiment. Moreover, two-dimensional PAGE

From the ‡Institute for Microbiology, Ernst Moritz Arndt UniversityGreifswald, Greifswald, Germany; §INRA, Mathematique Informatiqueet Genome UR1077, 78350 Jouy-en-Josas, France

Received, November 19, 2013 and in revised form, May 2, 2014Published, MCP Papers in Press, May 30, 2014, DOI 10.1074/

mcp.M113.035741Author contributions: S.M., D.B., and M.H. designed research;

S.M., G.W., and C.E. performed research; S.M., J.B., C.E., and V.F.analyzed data; S.M., J.B., K.R., D.B., and M.H. wrote the paper.

1 The abbreviations used are: two-dimensional PAGE, two-dimen-sional polyacrylamide gel electrophoresis; PTS, phosphotransferasesystem; SRM, selected reaction monitoring; S/N, signal to noise;TCC, tricarboxylic acid cycle.

DATA ACCESS: Protein abundance data for heat stress and glucosestarvation are available as Supplementary Information (supplemental Ta-bles S1 and S2).

Research© 2014 by The American Society for Biochemistry and Molecular Biology, Inc.This paper is available on line at http://www.mcponline.org

2260 Molecular & Cellular Proteomics 13.9

http://www.mcponline.org/cgi/content/full/M113.035741/DC1


is a well-established method for easy and convenient visual-ization of main metabolic pathways and the most obviousadaptational responses.

Until now, approaches for large-scale absolute proteinquantification have had a strong technological focus. Only afew predominantly physiological applications have been re-ported (5, 8, 9).

In this study, we provide absolute protein concentrations ofthe bacterial model organism Bacillus subtilis during stressand starvation adaptation. As model for different stress con-ditions, we selected the best-studied responses during heatstress and glucose starvation. A comparative analysis of dif-ferent stress conditions allows to differentiate between gen-eral, nonspecific adaptive responses ensuring survival duringa wide spectrum of conditions and specific stress adaptationby differential expression of particular regulons facilitating adirect interaction with the stimulus (10).

The general adaptive response of B. subtilis is governed byglobal regulators such as the alternative RNA polymerasesigma factor Sigma B or the main stringent factor RelA.

Induction of SigB-dependent genes provides cells with amultiple, nonspecific and preventive stress resistance (11, 12).The SigB-dependent general stress response in B. subtilis isinduced by a different set of stress and starvation stimuli.Thereby, environmental stresses, like heat shock, activate thephosphatase RsbU via a signal transduction pathway thatinvolves additional regulatory proteins to dephosphorylate theanti-anti-sigma-factor RsbV that subsequently releases SigB(13, 14). During starvation for carbon sources, phosphorus oroxygen dephosphorylation of phosphorylated RsbV followedby the release of active SigB is catalyzed by RsbP (15).

The main (p)ppGpp synthetase RelA mediates the stringentresponse, which is a crucial component of the regulatorynetwork in B. subtilis cells. The main feature of the stringentresponse is the down-regulation of genes whose productstypically consume energy and building blocks for cell growth,particularly genes encoding components of the transcriptionand translation apparatus as well as genes coding for proteinsinvolved in nucleotide biosynthesis and DNA replication (16).

During glucose starvation, a substantial reprogramming ofprotein synthesis pattern is caused by the restricted access toenergy and carbon sources. The carbon starvation specificstress response is characterized by repression and degradationof glycolytic enzymes with simultaneous up-regulation of spe-cifically gluconeogenesis and tricarboxylic acid cycle relatedenzymes (10, 17–19). Additionally metabolic pathways for theutilization of overflow metabolites and other secondary carbonsources such as �- or �-glucosides or amino acids are induced(10, 17).

In addition to starvation B. subtilis has to adjust to variousphysical stresses in its natural habitat. In order to investigatethis adaptational response we have chosen the model heatstress. Already described specific heat-shock induced genes

of B. subtilis belong to the HrcA regulon (20), the CtsR regulon(21–23), or the HtpG operon (24).

Moreover, there are heat inducible stress proteins whoseregulation does not follow the already mentioned mecha-nisms. These proteins are for example FtsH (25), ClpX (26),SacB (27), LonA (28), AhpC, AhpF (29), NfrA, YwcH (30), andmembers of the SigI regulon (31).

In this study, we quantitatively characterize the adapta-tion of B. subtilis to glucose starvation and heat stress andpresent concentrations on the level of molecules per cell formore than 700 cytosolic proteins. Furthermore, we analyzeddynamical protein repartition between main processes ofthe cell during exponential growth and stress providingvaluable insights in adaptation to changing conditions.Thus, this comprehensive data set may be suitable for mod-eling of metabolic pathways.

EXPERIMENTAL PROCEDURES

Pulse-labeling with L-[35S]-methionine—Radioactive pulse-labelingexperiments with 35S-methionine were carried out to investigate pro-tein synthesis of B. subtilis during glucose starvation. Therefore threeindependent biological replicates of B. subtilis 168 trp� (32) weregrown in M9 minimal medium at 37 °C under vigorous agitation. Thecomposition of M9 was: 0.1% (w/v) glucose, 0.1% (w/v) L-malate,CaCl2 * 2H2O (0.015 g L�1), MgSO4 * 7H2O (0.246 g L�1), Na2HPO4 *2H2O (8.5 g L�1), and KH2PO4 (3 g L�1), NaCl (0.5 g L�1), NH4Cl (1 gL�1) and trace elements (10 ml stock solution for 1 L medium). Thetrace element stock solution consisted of (per liter): ZnCl2 (0.170 g),CuCl2 * 2H2O (0.043 g), MnCl2 * 4H2O (0.100 g), CoCl2 * 6H2O (0.060g), and Na2MoO4 * 2H2O (0.060 g). Cultures were pulse-labeled for5 min each with 10 �Ci of L-[35S]-methionine per ml at an OD600 nm of0.4 - 0.5 (for control), at maximal OD and at several time points (15,30, 60, and 120 min) after the transition to glucose starvation asdescribed previously (10). In combination with protein amounts de-rived from fluorescence stained two-dimensional gels (see below) itcan be investigated which proteins are actually synthesized at aspecific time point and which protein amounts have already beenaccumulated.

Cell Culture and Protein Preparation—For starvation experimentsB. subtilis 168 trp� (32) was cultivated as mentioned above. Sampleswere harvested in exponential phase (OD600 nm 0.5), in transientphase, at maximal OD and 60, 120, 180, and 240 min after enteringthe stationary phase triggered by glucose exhaustion (Fig. 1). For heatstress experiments, cells were cultivated in minimal medium (33) andstressed by a sudden temperature shift to 52 °C. Cells were har-vested shortly before (control) and at 10, 30, and 60 min after con-tinuous heat shock (Fig. 1). For every experiment, three independentbiological replicates were analyzed.

After harvesting and centrifuging cells were resuspended in TE-Buffer (10 mM Tris, 1 mM EDTA, pH 7.5) and mechanically disruptedusing the Precellys 24 homogenizator (PeqLab, Germany; 3 � 30 s at6.5 m s�1). Protein concentration of extracts was determined using aninhydrin-based assay (6, 34).

Preparation of Two-dimensional Gels—Two-dimensional PAGEwas performed as previously described (35) in five technical repli-cates. 100 �g protein was loaded onto 18 cm IPG strips (pH 4–7,GE-Healthcare). After two-dimensional PAGE gels were fixed with40% (v/v) ethanol and 10% (v/v) acetic acid for 1 to 2 h and subse-quently stained with FlamingoTM. Stained gels were scanned (Ty-phoon 9400, GE-Healthcare) and their images analyzed employingDelta2D 4.2 software (Decodon GmbH, Germany). For all spots de-

Molecular Protein Quantification of Stress Responses

Molecular & Cellular Proteomics 13.9 2261

tected on the gel the spot volume was assigned to proteins, exportedfrom the software and subsequently used for calibration of two-dimensional gels as described earlier (6).

Sample Preparation for MS Analysis—Protein samples were re-duced, alkylated and digested as previously described (6). Sampleswere spiked with heavy peptides of anchor proteins used for cali-bration of two-dimensional gels to a final concentration of 5–25fmol �l�1. A detailed list of used peptides and their optimizedtransition parameters has been published elsewhere (6).

Targeted MS Analysis and Global Absolute Protein Quantification—LC-MS analyses was performed as described previously (6). All rawfiles were processed using MultiQuantTM 1.1 software (AppliedBiosystems, Foster City, CA). A peptide ratio of native and heavyspecies was based on three transitions that were weighted accord-ing to their signal to noise (S/N) ratios before being averaged.Accordingly, S/N weighted peptide ratios were combined to thefinal protein ratio. Based on the added amount of heavy peptides,the absolute quantity of target anchor proteins could be calculated.

Absolute amounts of targeted anchor proteins obtained by SRMwere used to calibrate two-dimensional gels of the same sample inorder to obtain absolute abundance of all proteins visible on this gel.Amounts of multiple spots of the same protein were added up.Standard deviations for proteins represented by multiple spots werecalculated using error propagation. Final standard deviation was cal-culated using a random effect model (36).

Efficiency of Cell Disruption and Determination of Cell Size—Bac-terial cell size and cell disruption efficiency were determined as pre-viously published (6). Volumes of the rod-shaped cells were calcu-lated assuming a cylinder and two hemispheres without subtractingany values for the cell envelope. At least 100 cells were dimensionedfor every sample. Therefore, a standard deviation could be calculatedfor each analyzed population (supplemental Table S6).

RESULTS

Determination of absolute protein abundances by combiningaccurate targeted mass spectrometry with the resolvingpower of two-dimensional PAGE provides a global view onthe concentrations of a large number of proteins. Althoughthe derived quantification data across biological replicatescan be at most a highly accurate determination of molecularcounts we will use in the following the common term “ab-solute quantification.”

In this study we present a comprehensive proteomic dataset applicable for bioinformatic modeling of B. subtilis’ stressand starvation responses. As models of starvation and stressresponses we chose glucose starvation and heat stress.

Therefore we determined protein concentration at seven dif-ferent time points along the bacterial growth curve for cellsunder glucose starvation and at four time points during heatstress (Fig. 1). Whereas glucose starvation causes a completestop of cell growth, 52 °C heat stress leads to a drop ofgrowth rate from 1.2/h during exponential growth to 0.5/hduring heat stress.

Absolute Quantification of Proteins—After preparation of acell count calibrated protein sample by determination of celltiter, cell disruption efficiency and protein content accordingto previously published protocols (6, 34), isotopically la-beled peptides of anchor proteins were spiked in the samplein known concentrations. Digestion and targeted SRM acqui-sition led to determination of protein concentration for all anchorproteins in the total protein sample. Hence, the absolute amountof anchor protein on fluorescently stained two-dimensional gelsprepared from the same sample could be calculated and wasused for calibration of these two-dimensional images by relatingspot intensities to the ones of anchor proteins (6). This enableddetermination of protein concentration for all proteins detecta-ble on the two-dimensional gels. Detectable soluble cytosolicproteins have an isoelectric point between 4 and 7 and a mo-lecular weight of 10–150 kDa. In order to provide reliable data,only anchor proteins with less than 15% CV among four tech-nical replicates of MS analysis and less than 35% CV betweenfive technical two-dimensional gel replicates were used for cal-ibration of two-dimensional gels.

Noncovalently binding fluorescent dyes (e.g. Flamingo,Krypton) bind proteins in an amount proportional to the pro-tein size (6) so that the same molecular count of a smallprotein correlates with a lower signal compared with that of alarger protein molecule during detection. Taking this into ac-count the detection of the same count of large protein mole-cules should be more sensitive compared with smaller ones,which is supported by experimental data (Fig. 2). Accordingly,the molecular weight of every protein has to be considered inthe calculation of the number of molecules per cell on thebasis of protein concentrations.

In this study we were able to identify 783 proteins (465proteins in starvation and 701 proteins in heat stress experi-

FIG. 1. Representative growth curvesof B. subtilis during glucose starvationand heat stress. Growth of bacterialcells was followed by measuring opticaldensity (OD) at 600 nm. Sampling pointsare indicated by dots. Sampling oc-curred as following: glucose starvation:exponential growth, transient, maximalOD, 60, 120, 180, and 240 min stationaryphase, heat stress: control (OD600 nm �0.5), 10, 30, and 60 min 52 °C heat.Phases of starvation or heat stress areindicated by the gray area.




ments), of which 773 proteins (465 proteins in starvation and691 in heat stress experiments) could be reliably quantified forat least one time point (supplemental Table S1, S2). Theamount of 219 and 287 proteins changed significantly(p � 0.05, one-way ANOVA) during glucose starvation andheat stress, respectively (Fig. 3, supplemental Figs. S1, S2).Supplemental Fig. S3 shows the distribution of these proteinsaccording to different regulation thresholds.

During exponential growth cellular concentrations of pro-teins spans from very few molecules per cell (11 moleculesper cell for the DNA mismatch repair protein MutL) to about250,000 molecules per cell (major cold-shock protein CspB).Considering protein abundances during stress adaptation theproteins determined to have the lowest cellular concentrationare the unknown protein YobO under starvation conditions(87 kDa, 13 molecules per cell after 120 min stationary phase)and the DNA exonuclease SbcC under heat stress (128 kDa,7 molecules per cell after 60 min heat stress). The chaperoninGroES was found to be the most abundant protein underheat stress condition (500,000 molecules per cell after30 min heat stress), whereas IlvC, an enzyme involved inbiosynthesis of branched-chain amino acids, and the elon-gation factor Tu (TufA) represent the most abundant pro-teins during glucose starvation (about 20,000 molecules percell after 60 min stationary phase). Hence, as reportedearlier with the method used here a range of cellular proteinabundances of 3 to 4 orders of magnitude can be covered(6) (Fig. 3, supplemental Fig. S4).

The availability of absolute quantification data for proteinsat a large scale allows calculation of stoichiometries ofknown oligomeric protein complexes. The already reportedratio of 1:2 for the components of the 2-oxoglutarate dehy-drogenase OdhA and OdhB, was verified (6, 37). The stoi-chiometric ratio for the core complex of the tricarboxylic

acid cycle consisting of isocitrate dehydrogenase Icd,malate dehydrogenase Mdh, and citrate synthase CitZ (38)has been determined to 4 molecules Icd : 4 moleculesMdh : 1 molecules CitZ. However, because of Mdh and Icdperforming multiple interactions with other proteins of theTCC and coupled pathways, calculated stoichiometriesderived from total cytoplasmic protein extracts may notnecessarily reflect stoichiometries in the core complexalone.

Sustainment of Basal Metabolic Functions and Cellular Pro-cesses during Stress Adaptation—During exponential growthin defined medium the metabolic situation in a bacterial cell iscomparatively simple. The bacterium uses its main resourcesto degrade carbohydrates in order to produce energy andbuilding blocks necessary to build up biomass. Although innature this situation is a rare exception there are metabolicand regulatory pathways that need to stay active even underchanging conditions. Absolute quantification results obtainedin this study indicate that bacterial cells sustain basal func-tions of metabolism and cellular processes needed duringexponential growth even after exposure to stress and starva-tion. About 60% of the top 100 abundant proteins (2.5 �

106 molecules/cell) are present in all conditions examined(Fig. 4, dark blue). Although proteins functioning in the acqui-sition of iron and the carbon core metabolism are regulated inresponse to glucose starvation and heat stress, these pathwaysalways stay active. Only few quantified proteins of these respec-tive pathways (less than 2.5%) were found in decreasedamounts. Therefore we suggest that these enzymes are stronglyneeded to ensure the cell’s supply with carbon intermediatesand iron during all phases of growth. Additionally, the proteinamounts of enzymes involved in biosynthesis of serine, glycine,and alanine do not change. Notably, also no enzyme needed forthe utilization of branched amino acids was found in lowered

FIG. 2. Limit of detection is a func-tion of molecular weight. Because ofsequence-unspecific noncovalent bind-ing of fluorescent dyes the same molec-ular count of a small protein generates asmaller signal compared with that of alarger protein. Molecules per cell for ev-ery protein quantified in this study wereplotted against their molecular weight tocalculate the limit of detection. Theequation as well as the coefficient of de-termination are indicated.







amounts in this study, indicating that this pathway, using themost abundant amino acid in proteins, needs to stay activeduring all conditions tested.

Moreover, no protein with functions in DNA condensation,segregation, repair, or combination was found in loweredamounts indicating that these functions are strongly neededto keep the genetic integrity and enable the cell to respondto stress. Dealing with stress is also ensured by keepingtranslation and transcription mechanisms active. Hence,more than 80% of the involved proteins quantified in thisstudy were found with stable or even increased amounts.

When cells get stressed the situation described abovechanges rapidly. Now the focus of the cell is no longer

growth, integrity, and supply with resources but survival.Analysis of protein quantification data set presented hererevealed that the most pronounced regulons involved ingeneral adaptive responses are the negative stringent re-sponse under starvation and the SigB response for cellsunder heat stress, indicating that quality and intensity of thegeneral stress response differs for stress and starvationconditions. During glucose starvation the cells down-regu-lated glycolysis and up-regulated gluconeogenesis which isin good agreement with previously published data (10). Thespecific response to heat stress is mostly characterized byaccumulation of cytosolic chaperones and proteases whosegenes are controlled by HrcA and CtsR.

FIG. 3. Voronoi-treemaps of B. subtilis during glucose starvation and heat stress. Protein abundances (copies/cell * molecular weight)during control (left) and stress conditions (right). Each cell in the graph displays a protein that belongs to other functionally related elementsin parent convex-shaped categories. These are again summarized in higher-level categories (see legend on the right side). Functionally relatedelements are depicted in close neighborhood to each other and colored similarly. Gene functional data are based on KEGG-orthology. Areasize in the graph encodes protein abundance.



However, the impact of the stress stimulus on the proteinamount is surprisingly small, only 10.0% and 9.4% of the 100most abundant proteins (6.1 � 105 molecules/cell and 2.6 �

105 molecules/cell) accumulated in response to heat stressand glucose starvation, respectively (Fig. 4, red, yellow, or-ange), suggesting an exceptionally high functional efficiencyduring stress adaptation. The impact of the general stressproteins on the total protein amount is even lower. Only 1% ofthe 100 most abundant proteins accumulated under bothstress conditions (Fig. 4, orange).

General Adaptive Response under Glucose Starvation—When exponential growing cells begin to starve, the needs ofthe cells change dramatically within a very short time. Al-though producing biomass has been the main purpose duringgrowth, it is now the demand for energy and metabolic inter-mediates. In this study, we select glucose starvation as modelfor starvation conditions. Hierarchical clustering of proteinexpression patterns during glucose starvation revealed thatthe cell handles the changed situation by decreasing theamounts of almost 50% of all proteins exerting functions inprotein biosynthesis or in biosynthesis and acquisition ofamino acids, cofactors, or nucleotides emphasizing the im-portant role of the negative stringent response and relatedresponses under glucose starvation (supplemental Fig. S5).The main feature of the stringent response is the down-regulation of genes typically expressed in growing cells (16).Those genes are involved in transcription and translation,nucleotide biosynthesis, and DNA replication that was alsoreflected by reduced molecular counts in stationary phase forthe ribosomal protein RpsB, the elongation factor FusA,adenylate kinase Adk, phosphoribosylpyrophosphate synthe-tase Prs, and the single-strand DNA-binding protein SsbA.

Additionally, a decreasing protein concentration was ob-served for cell-shape determining proteins like Mbl or proteinsinvolved in ATP synthesis and respiration, like AtpA and AtpD(Table I). The lower level of proteins necessary in starved cellsis caused not only by repression of the corresponding genes,but also by degradation of vegetative proteins no longer ac-tive in nongrowing cells (10, 18, 19).

Besides the negative stringent response the alternativesigma factor SigB is expected to be a key player of the generalstress response, but only 19 proteins whose regulation iscontrolled by SigB could be quantified during glucose starva-tion. Quantitative results for 10 of these were statisticallysignificant (p � 0.05, one-way ANOVA). Seven of thesechanged more than twofold in at least one of seven timepoints examined. Thereby, the general stress proteins YdbD,YdaD, YdaG, and YfkM showed highest fold changes (TableI). With 14,400 to 81,500 molecules per cell the protease ClpPand the general stress proteins YvgN, YvaA were the mostabundant SigB-dependent proteins. Five out of seven signif-icantly changed proteins accumulated not until late stationaryphase, namely the general stress proteins YdbD, YdaD,YdaG, YfkM, and the catalase KatE. In contrast, the generalstress protein Ctc and the SigB- and CtsR-dependently ex-pressed protein arginine kinase McsB accumulated only tran-siently. Although Ctc was present in highest amounts duringtransient phase, McsB accumulated most after 120 min sta-tionary phase caused by glucose exhaustion.

Supporting analysis by 35S-pulse-labeling during glucosestarvation allowed relative quantification of the protein syn-thesis of 37 SigB-dependent proteins. 27 of these changedsignificantly (p � 0.05, one-way ANOVA) more than threefoldin at least one time point examined (supplemental Table S3,supplemental Fig. S6). The induction of general stress pro-teins peaked 30 min after entry into starvation-triggered sta-tionary phase and reached almost control levels after 120 minof glucose exhaustion. Despite this transient induction only aslight accumulation of a few stress proteins could be ob-served (Fig. 5).

This raises the question how long it takes until changes inprotein synthesis become detectable on the level of proteinamounts. Therefore, we compared absolute protein quantitiesduring glucose starvation of this study with previously pub-lished data on protein synthesis (10). As only proteins withchanged expression pattern are of interest for this kind ofanalysis only common proteins of both studies that showsignificant changes in protein synthesis (�twofold) were com-pared leading to 41 induced and 100 repressed proteins. Forabout half of the induced proteins an increase in proteinamount could be detected in the same time point indicatingan immediate protein translation and accumulation (Fig. 6).These proteins are involved in genetic information processinglike the ribosomal protein paralog Ctc, transcriptional elonga-tion factor GreA and the sigma factor SigB, or are required forthe utilization of alternative carbon sources (AcsA, LicH, and

FIG. 4. 100 most abundant proteins at exponential growth, heatstress, and glucose starvation. Protein amounts (molecules/cell) ofthe 100 most abundant proteins during exponential growth (first bar),after 60 min heat stress (second bar), and after 120 min glucosestarvation (third bar) are used to calculate the relative amount ofstable and newly accumulated proteins within the 100 most abundantproteins in the cell.






AcoB). For other induced proteins accumulation takes at least60 min (Fig. 6). Functions of proteins that accumulate muchlater (after at least 240 min) are very diverse and do not followan obvious direction. 80% of the repressed proteins are sta-ble for more than 240 min after repression of protein synthesis(Fig. 6). Most of these proteins (62.5%) function in carboncore metabolism or biosynthesis of nucleotides, amino acids,and cofactors. Only three proteins were found to be very

unstable as their amount decreases at the same time pointwhere the repression was detected. These proteins are Tgt,functioning in translation, CarB, involved in biosynthesis ofarginine, and Sat, an enzyme of the sulfur metabolism.

Specific Response to Glucose Starvation—Growth ofB. subtilis in its natural environment, the upper layers of soil,is characterized by alternating phases of glucose supply andlimitation. Adaptation to starvation for glucose and other car-

TABLE IDetermined protein amounts (in molecules per cell) of selected proteins after 240 min stationary phase due to glucose starvation. Absolute

amounts for all quantified proteins can be found in supplementary Table S2. *Provided data at time point of maximal induction

Molecules/cell

Protein Function Exponential growth Stress

Stringent responseRpsB Ribosomal protein 16,000 8600FusA Elongation factor 67,000 37,000Adk Adenylate kinase 11,000 4700Prs Biosynthesis of histidine 3500 1300SsbA DNA replication 9000 4200Mbl Cell shape determination 3100 960AtpA ATP synthase subunit 31,000 16,000AtpD ATP synthase subunit 30,000 14,000

�B-regulon*YdbD General stress protein 190 4000YdaD General stress protein 150 1200YdaG General stress protein 7600 37,600YfkM General stress protein 1600 4400ClpP Clp protease proteolytic subunit 24,200 24,500YvgN General stress protein 81,500 67,400YvaA General stress protein 15,900 14,400KatE General stress protein 1300 2700Ctc General stress protein 9200 20,000McsB Modulator of CtsR-dependent repression 4300 12,300

GlycolysisPgi Glucose 6-P isomerase 35,600 14,400PfkA Phosphofructokinase 8100 4300FbaA Fructose 1,6-P aldolase 120,000 69,900GapA Glyceraldehyde 3-P dehydrogenase 19,300 13,600Pgk Phosphoglycerate kinase 28,900 21,100Pgm Phosphoglycerate mutase 12,300 7800Eno Enolase 140,000 71,000

Gluconeogenesis and acquisition ofsecondary carbon sources

GapB Glyceraldehyde 3-P dehydrogenase 1700 4400PckA Phosphoenolpyruvate carboxykinase 3700 5200AcoA Acetoin dehydrogenase subunit 6300 24,000AcoB Acetoin dehydrogenase subunit 5900 13,800AcoC Acetoin dehydrogenase subunit 850 2100AcsA Acetyl-CoA synthetase 4100 8400MalA 6-P-alpha-glucosidase 1200 3100IolD Myo-inositol catabolism 160 410

TCCCitZ Citrate synthase 21,300 34,300OdhA 2-oxoglutarate dehydrogenase subunit 4000 7900SucC Succinyl-CoA synthetase subunit 17,300 28,700SucD Succinyl-CoA synthetase subunit 4900 11,500SdhA Succinate dehydrogenase subunit 4500 7600

Amino acid synthesisMetC Cystathionine beta-lyase 4900 1600MetE Methionine synthase 67,400 21,700ArgC N-acetyl-g-glutamyl-P reductase 2800 800ArgD Acetylornithine transaminase 4300 1400IlvA Threonine dehydratase 2400 180YwaA Branched-chain amino acid aminotransferase 15,300 5800LeuA 2-isopropylmalate synthase 7500 3000




bon sources is the key for survival of the cells. Hence, afterexhaustion of glucose the glycolytic pathway is repressedbecause of the need of a high glucose concentration for gapAoperon expression (39–41). As repression in nongrowing cellswould mean nonchanging protein amounts, an additional pro-teolytic degradation of unemployed glycolytic enzymes prob-ably occurs. This is supported by halved protein concentra-tions after 180 min of starvation triggered stationary phase innongrowing cells (Table I, Fig. 3, supplemental Fig. S5). Ingeneral, numbers of protein copies per cell differ in metabolicpathways, which is most probably caused by differentenzyme efficiencies as a result of varying binding coefficientsand metabolic rates (42) (supplemental Fig. S7). This is alsotrue for glycolytic enzymes for which molecules per cell differwith an average factor of 15 (Table I). However, averagestoichiometries of constitutively expressed glycolytic en-zymes catalyzing reversible reactions seem to remain stableduring all time points examined (5 molecules Pgi : 19 mole-cules FbaA : 5 molecules Pgk : 2 molecules Pgm : 20 mole-cules Eno, Table I). In contrast, measured stoichiometriesbetween key players of glycolysis (phosphofructokinase PfkA,glyceraldehyde 3-phosphate dehydrogenases GapA andGapB) change during transition into stationary phase causedby starvation (exponential growth: 20 molecules Pgi : 4 mol-ecules PfkA: 10 molecules GapA : 1 molecule GapB; station-ary phase: 20 molecules Pgi: 4 molecules PfkA : 4 moleculesGapA : 2 molecules GapB, Table I, supplemental Fig. S7).

Dealing with glucose starvation also requires new accumu-lation of proteins specifically needed to react to the changedsupply of carbon sources. Hence, after glucose exhaustiongluconeogenesis becomes necessary because cells start touse secondary carbon sources like for example overflow me-

tabolites produced during excess of the preferred carbonsource. Hence, the protein amount of the gluconeogenic glyc-eraldehyde-3-phosphate dehydrogenase GapB increasedmore than twofold in late stationary phase. Moreover, forphosphoenolpyruvate carboxykinase PckA, feeding into glu-coneogenesis by converting oxalacetate to phosphoenolpy-ruvate, an increased amount could be detected (Table I).Additionally, amounts of enzymes for the utilization of sec-ondary carbon sources like the subunits of acetoin dehydro-genase AcoABC increased significantly. This also applies toacetyl-CoA synthetase AcsA, 6-phospho-alpha-glucosidaseMalA, and IolD, necessary for the catabolism of acetate, malt-ose and myo-inositol, respectively, indicating that someCcpA-dependent catabolic genes also seem to be dere-pressed in glucose-starved cells without any obvious externalinducer (Table I, Fig. 3, supplemental Table S4). For AcsA thiscan be explained by a possible internal inducer as lipid deg-radation during stationary phase could provide an additionalsource of acetyl-CoA (17).

During glucose starvation down-regulation of glycolysisand induction of gluconeogenesis occur simultaneously withinduction of TCC enzymes (10, 17, 18). Induction of thismetabolic pathway allows for utilization of organic acids andfree amino acids as energy sources, which might becomeavailable because of protein degradation. As expected proteinamounts for these enzymes revealed an increased need forcitrate cycle intermediates. Hence, molecules per cell for cit-rate synthase CitZ, 2-oxoglutarate dehydrogenase subunitOdhA, both subunits of the succinyl-CoA synthetase (SucC,SucD), and succinate dehydrogenase subunit SdhA increasedat least 1.7-fold when cells starve for glucose (Table I, Fig. 3,supplemental Fig. S5).

FIG. 5. Changes in protein abundance for selected SigB-dependent proteins in growing and stressed cells. Protein patterns ofexponential growing (green) and stressed cells (red) of selected SigB-dependent proteins during different growth stages (columns correspondto sampling points mentioned in Experimental Procedures). On the bottom of spot tiles the protein amount is given (molecules per cell). Barcharts show log2 ratios of protein amounts compared with control sample (exponential growth) for starvation (blue) and heat stress (orange).For the starvation experiment ratios for accumulated proteins (light blue) and synthesized proteins (dark blue) are given.








Accumulation of new proteins needed for the specific re-action to starvation conditions requires a lot of energy. How-ever, the availability of energy is restricted in a starved cell.Therefore the decreased growth rate and the reorientation of

protein synthesis is necessary when energy becomes limited.Investigation of the repartition of protein amounts among themain processes in B. subtilis during adaptation to glucosestarvation detected significantly lowered protein amounts in

FIG. 6. Distribution of duration of protein accumulation and depletion after induction and repression of synthesis after glucosestarvation. Common proteins of this study and a work on protein synthesis (10), which show significant regulation in protein synthesis (at leasttwofold) in one of the time points (maximal OD, 30 min, 60 min, and 240 min glucose starvation normalized to exponential growth) werecompared. The time point of first regulation on the level of synthesis and the first detection of changes in protein amount were compared andthe period of time needed was calculated. Calculated durations were color-encoded in a Voronoi-Treemap. Induced/accumulated proteins areshown in orange, repressed/depleted proteins are colored blue. The faster the change in protein abundance occurred, the darker the colorappears.



amino acid biosynthetic pathways already at entry into sta-tionary phase. After 180 min stationary phase caused byglucose exhaustion this becomes only more pronounced(supplemental Fig. S5). Most drastic changes in proteinamount could be detected for synthetic pathways of methio-nine, arginine, and branched amino acids. Hence, the amountof cystathionine beta-lyase MetC and methionine synthaseMetE lowered more than threefold during glucose starvation.This was also the case for proteins involved in biosynthesis ofarginine like N-acetyl-g-glutamyl-phosphate reductase ArgCand acetylornithine transaminase ArgD. Similar results couldbe obtained for enzymes that function in synthesis ofbranched amino acids like threonine dehydratase IlvA, ami-notransferase YwaA, and 2-isopropylmalate synthase LeuA(Table I). This supports the assumption that under starvationconditions the degradation of unemployed enzymes not pro-tected in functional metabolic complexes can help to providethe amino acids necessary for de novo protein synthesis.However, the arrest of biomass production is most probablythe major actor of this repression. An integrated view ofprotein repartition is provided in Fig. 7. A considerable portionof protein mass dedicated to amino acid biosynthesis path-ways seems to be allocated to the central carbon metabolism.The increased need of protein mass is most probably causedby induction of the TCC, gluconeogenesis, and pathways foracquisition of secondary carbon sources and cannot be cov-ered by lowered protein amounts of glycolytic enzymes alone(supplemental Fig. S5).

General Adaptive Response under Heat Stress—In thiswork, heat stress was selected as well described model forphysical stresses. In contrast to glucose starvation here theavailability of carbon sources is not limited and protein dam-age is the main challenge the cell has to face. For the growth-restricting heat stress (�exp � 1.2/h, �heat � 0.5/h) analyzed inthis work hierarchical clustering revealed that 40% of allproteins with increasing amounts are SigB-dependent stressproteins or mediate stress resistance. Altogether 44 membersof the SigB regulon could be absolutely quantified from which

33 were found to be accumulated more than twofold. Indeed,heat stress seems to elicit the induction of the SigB regulon,but it could be a substantial burden for the cell, as it canoccupy up to 20% of the translation capacity (43). Accord-ingly, only a transient transcription of genes of the SigB regu-lon is reported for both conditions (17, 44). As cells starvingfor glucose and heat stressed cells exhibit considerably dif-ferent cell volumes (differences around factor 2, supplementalTable S6), absolute protein abundances in heat stressed cellshave been corrected for the differences in cell size by normal-izing to cell volumes of glucose starved cells in order to allowcomparison of protein concentration per cell under both con-ditions. For comparison of the SigB response in both condi-tions tested, corrected protein abundances will be given inmolecules per size-corrected cell in the following. In contrastto glucose starvation, a clear accumulation of induced SigB-dependent proteins can be measured only during heat stress(Fig. 5). Thereby, the general stress proteins YhdN, YvyD, andGsiB showed highest increase in protein amount (more than19-fold in size-corrected cells, Table II). With 97,800–151,000molecules per cell (49,400–110,000 molecules per size-cor-rected cell) most abundant SigB-dependent proteins duringheat stress were the relatively small general stress proteinGsiB, the anti-anti-SigmaB-protein RsbV, and the proteaseClpP. These increases indicate an important functional role ofthe SigB-dependent proteins during heat stress, which legit-imates the high translation capacity needed for them.

Further analysis of the distribution of protein amounts todifferent regulons in the cell additionally revealed that proteinswhose expression is controlled by PerR (response to perox-ide) and Spx (response to thiol specific oxidative stress) arealso enriched (supplemental Table S5), emphasizing the over-lap between heat shock response and reaction to oxidativestress. As secondary oxidative stress is described to occurafter different environmental stresses (45, 46) quantitativedata of proteins with function in adaptation to oxidative andelectrophile stress derived from this study were checked.Indeed, the amount of 25 out of 35 quantified oxidative stress

FIG. 7. Integrated view of functional class assigned protein abundances of B. subtilis during glucose starvation. The relativedistribution of protein amounts among the main processes of B. subtilis during adaptation to glucose starvation are shown in different bars(from left to right) for exponentially growing cells (exp), cells during transient phase (trans) and at maximal optical density (max. OD) as well asfor cells after 60 min D, 180 min E, and 240 min F, stationary phase caused by glucose depletion.








proteins increased at least twofold (Table III). The moleculesper cell of the general stress proteins YvyD, OhrB, SigB, andDps increased more than 10-fold after 60 min of heat stress(supplemental Table S1, supplemental Fig. S8). Protein con-centrations of the nitro/flavinreductase NfrA, the probablethiol peroxidase Tpx, the alkyl hydroperoxide reductaseAhpC/AhpF, and superoxide dismutase SodA were amplifiedat least fourfold.

Specific Response to Heat Stress—Adaptation to growth-restricting heat stress was mainly realized by a strong accu-mulation of proteins belonging to the HrcA and CtsR regulons.Under this condition for six out of nine proteins of the HrcAregulon, which mainly function in protein folding, increasedamounts could be determined. The molecular chaperon DnaKand its activator GrpE accumulated four-fivefold (Table II, Fig.3, supplemental Fig. S8). Amounts of chaperonins GroEL andGroES even increased more than 10-fold (Table II, Fig. 3,supplemental Fig. S8). With that GroES was the most abun-dant protein under stress conditions constituting more than7% of the total molecule amount detected.

Besides proteins of the HrcA regulon, products of genescontrolled by CtsR were clearly enriched. On protein level 7of 12 members of the regulon could be absolutely quantifiedand were found to be accumulated. A significant (p � 0.05,one-way ANOVA) increase in protein concentration of theATPases ClpE, ClpC, and protease ClpP was detected. Theamount of ClpE increased about sevenfold after 10 min of

heat stress. However, after 30 min of stress ClpE concen-tration had already reached basal level of about 800 mole-cules per cell again indicating low protein stability. Similarobservations have been made by Gerth and co-workers(47). In contrast, enrichment of ClpC and ClpP (Table II) wasdetermined to be four-eightfold already after 10 min of heatstress, but remained stable during all time points of stressexamined.

Although the already described induction of the HrcA andCtsR regulons represent the main response to heat stress,various other heat inducible proteins could be absolutelyquantified in this study. HtpG was found to be induced14-fold during heat stress. LonA accumulated about three-fold, but failed to reach significance level (p � 0.05, one-way ANOVA). NfrA was found to be accumulated fivefoldwhereas protein amounts of AhpC and AhpF increasedabout fourfold (Table II).

Under heat stress most altered protein amounts were pos-itively influenced, but there were also enzymes whose amountdecreased. The majority of these proteins is involved in bio-synthesis and acquisition of amino acids and cofactors (sup-plemental Fig. S8). Examples for negatively controlled en-zymes are tyrosine transaminase HisH, methionine synthaseMetE, and ThiF, involved in thiamine biosynthesis (Table II).The protein amount of these proteins was lowered constantlyduring heat stress (supplemental Table S1). In contrast, theconcentrations of cyclase-like protein HisF, N-acetylgluta-

TABLE IIDetermined protein amounts (in molecules per cell) of selected proteins after 60 min heat stress. Absolute amounts for all quantified proteins

can be found in supplementary Table S1

Molecules/cell

Protein Function Exponential growth Stress

�B-regulonYhdN General stress protein 100 5800YvyD General stress protein 200 9500GsiB General stress protein 3900 151,000RsbV Control of SigB activity 47,400 135,000

Chaperones and proteasesDnaK Molecular chaperone 11,000 51,000GrpE Activation of DnaK 2000 8400GroEL Chaperonin 20,000 190,000GroES Chaperonin 37,000 500,000HtpG Molecular chaperone 1200 17,000LonA Protease 250 680ClpC ATPase subunit of the ClpC-ClpP protease 1100 11,200ClpE ATP-dependent Clp protease-like 850 900ClpP ATP-dependent Clp protease proteolytic subunit 12,500 97,800

Heat inducible proteinsNfrA Stress protein 400 2000AhpC Alkyl hydroperoxide reductase subunit 56,000 250,000AhpF Alkyl hydroperoxide reductase subunit 7800 33,000

Negatively altered proteinsHisH Tyrosine transaminase 1000 600MetE Methionine synthase 70,800 42,600ThiF Biosynthesis of thiamine 370 200HisF Biosynthesis of histidine 4200 2700ArgB N-acetylglutamate 5-phosphotransferase 470 150PatB Cystathione-beta-lyase 3800 2600MoeA Molybdopterin biosynthesis protein 730 290











mate 5-phosphotransferase ArgB, cystathione-beta-lyasePatB, and the molybdopterin biosynthesis protein MoeA weredecreased until 30 min of heat stress to reach control levels at60 min of stress again (Table II, supplemental Table S1),emphasizing the global coordination of various regulation inresponse to the growth rate adaptation during heat stress.

The results of this study show that B. subtilis needs toreorientate protein synthesis during heat stress adaptation inorder to accumulate general and stress-specific proteins al-though the main metabolic processes seem to be compro-mised because of the stress. The graphical representation ofthe repartition of protein amounts among main pathways ofB. subtilis during heat stress depicts the very pronounced

accumulation of chaperones and proteases during heat stress(Fig. 8, left). These proteins constitute 4% of the total proteinmass during exponential growth at 37 °C, but their fraction isalready increased to 13% after 30 min heat stress at 52 °C.Furthermore, the left part of Fig. 8 indicates that proteinamounts dedicated to chaperones and proteases are mostprobably derived from resources won by turnover of enzymesresponsible for amino acid synthesis (22% of total proteinamount under control conditions, 13% after 30 min heatstress).

Dynamical Aspects of Heat Stress Adaptation—The avail-ability of large-scale absolute protein concentrations allowsanalysis of dynamical aspects of protein synthesis during

TABLE IIIProteins with function in adaptation to oxidative and electrophile stress and their amounts after heat stress. For all proteins listed SigB-de-pendent regulation or already known induction by heat and oxidative stress (45) are indicated by x. For each protein molecules per cell and the

relative quantitative change is given. Protein names in boldface are subject to quantitative changes of a factor of 4 or higher

Molecules per cell Relative foldchange

Protein BSUnumber SigB-dependent

Induced after heatand oxidative

stress (45)Control 10 min 30 min 60 min 10 min 30 min 60 min

YvyD BSU35310 x x 207 681 3262 9540 3.29 15.76 46.09OhrB BSU13160 x x 1457 12,252 26,988 20,433 8.41 18.52 14.02SigB BSU04730 x x 53 227 459 676 4.28 8.66 12.75YsnF BSU28340 x x 115 986 509 256 8.57 4.43 2.23Dps BSU30650 x – 1657 11,213 14,860 17,867 6.77 8.97 10.78SodA BSU25020 x – 50,924 110,342 179,084 224,860 2.17 3.52 4.42TrxA BSU28500 x – 9490 23,432 36,874 36,691 2.47 3.89 3.87YraA BSU27020 x – 1373 4051 5061 4852 2.95 3.69 3.53KatE BSU39050 x – 570 1028 1269 1855 1.80 2.23 3.25YvgN BSU33400 x – 22,012 38,419 44,612 54,906 1.75 2.03 2.49YdbD BSU04430 x – 2088 3282 3989 3890 1.57 1.91 1.86KatX BSU38630 x – 414 577 361 242 1.39 0.87 0.58NfrA BSU38110 – – 394 1102 1623 2015 2.80 4.12 5.11Tpx BSU29490 – – 7703 16,365 26,057 35,678 2.12 3.38 4.63AhpC BSU40090 – – 56,404 122,829 179,490 253,482 2.18 3.18 4.49AhpF BSU40100 – – 7753 14,286 21,777 33,379 1.84 2.81 4.31OhrA BSU13140 – – 502 877 1239 1958 1.75 2.47 3.90

ProteinBSU

numberSigB-dependent

Induced after heatand oxidative

stressControl 10 min 30 min 60 min 10 min 30 min 60 min

AzoR1 BSU19230 – – 3013 5211 11,391 11,585 1.73 3.78 3.85AzoR2 BSU33540 – – 4564 7377 8379 15,738 1.62 1.84 3.45MsrA BSU21690 – – 164 249 481 562 1.52 2.93 3.43MhqA BSU12870 – – 519 986 1398 1658 1.90 2.69 3.19YgaF BSU08720 – – 1278 2110 2346 4000 1.65 1.84 3.13HypO BSU07830 – – 979 1402 1631 3062 1.43 1.67 3.13YwbC BSU38370 – – 3854 6778 8080 11,618 1.76 2.10 3.01MrgA BSU32990 – – 808 1210 1279 2321 1.50 1.58 2.87CatR BSU33680 – – 105 287 316 300 2.73 3.01 2.86YodC BSU19550 – – 3942 5772 6104 10,996 1.46 1.55 2.79YqjM BSU23820 – – 957 1532 1805 2209 1.60 1.89 2.31MhqD BSU19560 – – 2156 2889 2322 4354 1.34 1.08 2.02BshA BSU22460 – – 312 444 678 612 1.42 2.17 1.96MsrB BSU21680 – – 775 1264 1520 1154 1.63 1.96 1.49BshB1 BSU22470 – – 406 416 349 557 1.02 0.86 1.37BshC BSU15120 – – 894 1093 973 1193 1.22 1.09 1.33KatA BSU08820 – – 2359 2485 1720 2330 1.05 0.73 0.99HxlA BSU03460 – – 180 267 87 36 1.48 0.48 0.20




stress adaptation. In order to calculate protein productionrates during heat stress we assume that proteins synthesizedduring exponential growth under control conditions and stillincreasing during heat stress are stable. Studies on glucosestarvation revealed that this is quite reasonable at least forvegetative enzymes (19). Regulatory proteins may have amuch higher turnover rate because they are required for tem-porary reaction of the living cell to changing surroundings.However, in our representative data set regulatory proteinsmake up less than 1.5% of the total protein amount in a celland their mass will therefore not essentially influence calcu-lation on protein production.

The optical density of a bacterial culture reflects cell growthand therewith the “dilution” of protein amounts by cell divi-sion. In this study, the optical density increases 1.62-foldbetween the control sample of exponentially growing cellsand the sample after 60 min of heat stress at 52 °C (Fig. 1).Hence, we would estimate that 62% of the total protein massin heat stressed cells was already present in the controlsample. In reverse this could mean that 38% of the totalprotein amount present in the stressed cells was newly pro-duced during the 60 min heat stress phase (Fig. 8, circles). Inorder to illustrate this point the distribution of protein massaccumulated between the sample points to functional groupswas analyzed. This led to a figure that shows the repartition of

protein production in a given phase (Fig. 8 [left, bars], supple-mental Fig. S9). In the first phase, between 0 and 10 min heatstress, 22% of newly accumulated proteins are chaperones.In contrast, the portion of protein amount dedicated to aminoacid synthesis is strongly reduced. During the second phase,between 10 and 30 min of stress, the main portion of allprotein amount accumulated is devoted only to chaperones,the portion of accumulated proteins with functions in aminoacid synthesis is now smaller than 1%. In the third phase,between 30 and 60 min of heat stress, the heat adaptationalresponse seems to be finished. A significant amount of accu-mulated proteins is now again dedicated to amino acidsynthesis.

DISCUSSION

In the study presented here we compared for the first timethe differential adaptation of B. subtilis to heat stress andglucose starvation on the basis of absolute protein concen-trations at a large scale. Using two-dimensional PAGE with apH range of 4–7 we were able to determine protein amountson the single cell level for 773 cytosolic proteins at seven timepoints of glucose starvation and four time points in a heatstress experiment including controls. Hence, only 26.7% of allcytosolic proteins (locateP (48)) could be identified by thisgel-based approach. However, assuming that only 80% of all

FIG. 8. Integrated view of protein abundance and protein production assigned to functional processes of B. subtilis during heatstress. In the left part of the Fig. the relative distribution of protein amounts among the main processes of B. subtilis during adaptation to heatstress are shown in different bars for (from left to right): exponentially growing cells (control) and cells after 10 min, 30 min, and 60 min (D) heatstress. The right part of the Fig. illustrates dynamical aspects of protein repartition (protein production) in B. subtilis during heat stress. Therelative distribution of accumulated protein amounts among the main processes during adaptation to heat stress is shown in different bars for(from left to right): exponentially growing cells (exp.) and accumulated proteins between 0 and 10 min, 10 min and 30 min, 30 min and 60 minheat stress. The size of the circles represents the relative amount of proteins accumulated between single sample points (values are given inthe respective circles).





proteins are expressed at the same time (49), the proteincoverage of the presented approach increases to 33.4%,covering most main metabolic pathways and processes in B.subtilis (supplemental Fig. S7, supplemental Fig. S10).

427 proteins quantified during glucose starvation in thisstudy have been relatively quantified elsewhere (18). Whereasthe study presented here is limited to cytosolic proteins thatcan be detected by two-dimensional PAGE Otto and cowork-ers (18) could provide quantitative data for additional 890cytosolic proteins using mass spectrometry-based tech-niques. However, they were only able to provide relativequantification data whereas the study presented here for thefirst time reports physiologically relevant absolute proteinconcentrations on B. subtilis under glucose starvation. For theproteomic analysis of the heat stress adaptation this is evenmore pronounced. Until now relative protein quantificationdata for 246 cytosolic proteins have been available (50). Thiscould be extended by additional 455 proteins. For all 701proteins identified during heat stress in this study absolutequantification data are available.

The quantification of protein molecules per cell renders thepossibility to compute the redeployment of resources in thebacterium during stress and to accurately estimate the asso-ciated energy costs. However, such applications will requirethe accurate estimation of the costs associated to the mRNAsredeployment. This could be achieved if access to the abso-lute quantification of mRNAs during the stress period andtheir half-life during the same stress period was provided.Additionally the integration of nonprotein parameters, such asknown polysaccharides or lipids would be of great interest inorder to gain new insight on, for example, the membranecomposition during different stress conditions. Unfortunately,until now the absolute quantification of membrane proteins isstill a challenge because of the need for a complex samplepreparation (51). Furthermore, absolute quantification of non-proteinogenic components would be inevitable in this context.

Adaptation of B. subtilis cells to various stresses is the keyto survival in the natural habitat. Thereby it is crucial to bal-ance saving of energy and resources and accumulating ofinevitably needed stress proteins. This study illustrates differ-ent characteristics of general and specific stress responses todistinct stresses as exemplarily shown for glucose starvationand heat stress. Although general, nonspecific adaptive re-sponses ensure survival during various conditions, the spe-cific stress adaptation allows a direct interaction with thestimulus (10).

The general response to starvation is mainly marked by thenegative stringent response whereas nonspecific response toheat stress is dominated by activation of promoters controlledby the alternative sigma-factor SigB. Although the SigB regu-lon is activated under stress and starvation, proteins of SigB-dependent genes accumulate only after heat stress. Duringglucose starvation these proteins are transiently synthesized,but only five accumulated significantly more than twofold. On

average SigB-dependent proteins accumulated 1.8-fold after240 min of glucose starvation, but 2.6-fold after 60 min of heatstress. Concurrently, gelfree relative quantification data onsalt stress in B. subtilis (52) revealed an average accumulationof 3.2-fold. Maximal accumulation ratios were 5.4 for saltstress, 8.0 for glucose starvation, and 26.5 for heat stressindicating pronounced differences in the SigB-dependentregulation in response to various stresses.

Secondary oxidative stress is a phenomenon recently de-scribed to occur after ethanol treatment, hyperosmotic andcold stress (45, 46). For four proteins recently described to beinduced after heat and oxidative stress (45), namely SigB,OhrB, YsnF, and YvyD, a significantly increased amount afterheat stress could be detected in this study. Furthermore, 21additional proteins with functions in the resistance againstoxidative and electrophile stress were found to be accumu-lated (Table III). The molecules per cell for four proteins (YvyD,OhrB, SigB, and Dps) increased more than 10-fold. As theseproteins are controlled by SigmaB this high accumulation ismost probably caused by additive effects of the general stressresponse and the response to oxidative stress. This is sup-ported by the observation that concentrations for proteinswithout additional regulation by the general stress responseincreased not more than fivefold. It has been shown thatoxidative stress also induces genes otherwise repressed byMgsR controlling a subregulon within the general stress re-sponse (53). In this study, 23 target genes of MgsR could beabsolutely quantified after heat stress. Thirteen of these pro-teins show an expression pattern similar to that after ethanoltreatment suggesting a regulatory function of MgsR after heatstress.

In contrast, secondary oxidative stress does not seem toplay an important role in adaptation to glucose starvation. Inthis study the amount of only two proteins with functions inthe resistance against oxidative and electrophile stress wereincreased more than twofold (KatE, YbdD). Both proteins arealso under control of SigB and their accumulation might ratherbe an effect of this regulatory mechanism. Additionally, 16proteins with functions in adaptation to oxidative stress werequantified, but not found in higher copy numbers during sta-tionary phase. This is also supported by recent data from Ottoet al. (18). They quantified 24 SigB-independent cytosolicproteins involved in oxidative stress resistance. Only three ofthese proteins were found to be significantly accumulated.However, this observation might have been caused rather byother direct or indirect regulatory effects than by secondaryoxidative stress.

In addition to the general responses the specific stressresponse to various conditions ensures a direct interactionwith the stimulus. After exhaustion of the preferred carbonsource, the substantial reprogramming of cellular metabolismis characterized by down-regulation of glycolysis and simul-taneous mostly CcpA-dependent induction of metabolicpathways for the utilization of overflow metabolites and other





secondary carbon sources (10, 17–19). However, accumula-tion of TCC enzymes, proteins catalyzing gluconeogeneticreactions as well as of enzymes for the metabolism of sec-ondary carbon sources was less significant in this study whencompared with recently published relative quantification dataof Otto et al. (18). Relative quantification data from Otto et al.(18) compare protein abundances to calculate changes inprotein accumulation without considering protein concentra-tion in the cell. In contrast, absolute quantification data de-rived from this study consider the cell size and cell count of asample in order to calculate copy numbers per cell. Hence, ifcell size is reduced, like it is the case during starvation (sup-plemental Table S6), a stable protein concentration in a sam-ple may result in negative changes of copy numbers per cellcompared with the control sample leading to enhanced quan-titative effects of negative regulations and reduced quantita-tive effects of positive regulations (Fig. 2). This fact mayexplain the lowered protein accumulation of TCC enzymes,gluconeogenetic proteins and proteins for the utilization ofsecondary carbon sources when considering copy numbersper cell.

Specific heat stress response is marked by induction ofclass I and class III heat stress genes controlled by HrcA andCtsR, respectively.

On transcriptional level it is described that after moderateheat stress dnaK, grpE, and hrcA are strongly inducedwhereas downstream genes (dnaJ, yqeT, yqeU, and yqeV),groEL, and groES are not induced more than twofold (44).Under growth-restricting heat stress condition, as describedhere, amounts of all detectable proteins of the regulon in-crease at least fivefold.

In 1997 Schulz et al. found htpG to be induced 10-fold aftertransition from 37 °C to 48 °C both at the level of transcriptionand translation (54). The even higher accumulation rates ofHtpG in this study are therefore most probably caused by thehigher temperature of 52 °C.

Although it is described to be heat inducible, no member ofthe CssRS regulon could be detected in this study. This ismost probably because these proteins are, with exception ofCssR, membrane-anchored and therefore not accessible withtwo-dimensional PAGE.

Comparisons of our data with recent relative protein quan-tification (50) revealed a good overlap of results. Of 46 heat-induced proteins 23 were also found to be induced by Wolffand coworkers (50). A broad overlap also applies to proteinswith reduced amounts that function in biosynthesis and ac-quisition of amino acids and cofactors or in transcription andtranslation. Of 38 proteins negatively influenced in either ofthe studies 27 show a similar regulation pattern in bothstudies.

The availability of a comprehensive data set of absoluteprotein concentrations allows calculation of accumulated pro-teins during a given phase of stress adaptation without “clas-sical” quantitative synthesis data at hand. However this cal-

culation makes use of the assumption that examined proteinsremain stable during the stress phase analyzed. As this maybe a reasonable assumption for the comparable short heatstress study presented here (up to 60 min stress) this may notbe transferred to the glucose starvation data, which becameavailable within this work (up to 240 min starvation). Theamount of a protein is a balance between production anddegradation. In exponential phase, almost all reduced proteinamounts are a direct consequence of the so-called dilutioneffect caused by cell growth. That means that the proteinproduction in balanced systems can be easily estimated be-cause it represents the protein amount needed to compen-sate the dilution effect. Consequently, protein production foreach protein is equal to its steady-state amount times thegrowth rate. In a nonbalanced system, e.g. in transient phaseduring a stress, it is also possible to deduce the proteinproduction program during a given period, but only under theassumption that the protein degradation is restricted to thedilution. In this case possible proteolysis of some proteins willlead to underestimation of their production. Hence, the pre-sented results can only be an estimation of the distribution ofproduced and accumulated proteins to functional categories.However, our data can give valuable insights in regulatoryaspects during adaptation of B. subtilis to changing growthconditions.

The high amount of proteins with decreased amount in thisstudy (especially after glucose starvation) leads to the ques-tion how the proteins are selected to be degraded. The as-signment of proteins with lowered amounts to functional cat-egories (supplemental Table S7) revealed that most detectedenzymes involved in biosynthesis of cofactors are degradedand not newly accumulated under both, glucose starvationand heat stress. Notably, the enzymes catalyzing the firstcommitted steps in biosynthesis of branched amino acids,pyrimidines, and purines, namely IlvB, CarA, CarB, and Prs,have been found in decreased amounts only during responseto glucose starvation pointing to an energy saving mechanismbehind this regulatory effect. Hence, we suggest that starvingcells need to save energy because of the limited availability ofresources and therefore restrict metabolism to minimal activ-ity to guarantee survival. Consequently, in a first instance,cells degrade biosynthetic enzymes, in many cases after reg-ulation of their expression by the stringent response. Althoughproteins that are active and integrated into functional com-plexes are protected against a proteolytic attack, these en-zymes may be damaged or structurally pertubated in theabsence of their (co-) substrates leading to the recognition ofthese proteins by the degradation machinery.

After the introduction of quantitative Western blotting (3),flow cytometry (55), and MS-based or MS-coupled strategies(4–6, 56) for a global determination of absolute protein abun-dance, we herewith present first physiologically relevant datafor stress adaptation in the model bacterium B. subtilis. Be-cause of a large number of examined time points with high






coverage of reliably quantified proteins we are confident toprovide suitable data for modeling of cellular regulation underaltered growth conditions not only for the systems biologycommunity.

Acknowledgments—We thank E. Klotz, R. Jahnke, D. Ulbrich andS. Grund for excellent technical assistance. Furthermore, we aregrateful to V. Liebscher for help with mathematical and statistical dataanalysis. We also thank Decodon GmbH for providing Delta2D soft-ware. D. Zuhlke and D. Albrecht are acknowledged for support inprotein digestion and identification.

* This work was supported by grants from the Bundesministeriumfur Bildung und Forschung (0315784A, 0315592B) and the EU (LSHG-CT-2006-037469, FP7-244093).

□S This article contains supplemental Figs. S1 to S10 and TablesS1 to S7.

¶ To whom correspondence should be addressed: Tel.: �49-3834-864230; Fax: �49-3834-864202; E-mail: [email protected].

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Highly precise quantification of protein molecules per cell during stress and starvation responses...

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