Single-Cell Analysis of the Dps Response to Oxidative Stress

Michela De Martino,a Dmitry Ershov,b Peter J. van den Berg,a Sander J. Tans,b Anne S. Meyera

Department of Bionanoscience, Kavli Institute of Nanoscience, Delft University of Technology, Delft, The Netherlandsa; FOM Institute AMOLF, Amsterdam,The Netherlandsb

ABSTRACT

Microorganisms have developed an elaborate spectrum of mechanisms to respond and adapt to environmental stress conditions.Among these is the expression of dps, coding for the DNA-binding protein from starved cells. Dps becomes the dominant nucle-oid-organizing protein in stationary-phase Escherichia coli cells and is required for robust survival under stress conditions, in-cluding carbon or nitrogen starvation, oxidative stress, metal exposure, and irradiation. To study the complex regulation of Dpsin E. coli, we utilized time-lapse fluorescence microscopy imaging to examine the kinetics, input encoding, and variability of theDps response in single cells. In the presence of an oxidative stressor, we observed a single pulse of activation of Dps production.Increased concentrations of H2O2 led to increased intensity and duration of the pulse. While lower concentrations of H2O2 ro-bustly activated the Dps response with little effect on the growth rate, higher concentrations of H2O2 resulted in dramaticallylower and highly varied growth rates. A comparison of cells exposed to the same concentration of H2O2 revealed that increasedlevels of Dps expression did not confer a growth advantage, indicating that recovery from stress may rely primarily upon varia-tion in the amount of damage caused to individual cells.

IMPORTANCE

We show for the first time the response of the DNA-binding protein from starved cells (Dps) to oxidative stress in single cells ofE. coli. Through time-lapse fluorescence microscopy, a single pulse of Dps production is observed in cells exposed to H2O2, witha duration and intensity of induction proportional to the concentration of the applied stress. More intense Dps expression didnot provide a growth benefit to the bacteria, suggesting that healing from oxidative stress may largely depend upon the amountof damage in each individual cell.

Bacteria encounter many stresses during their development,and they need to be able to adapt quickly to the environment

to survive. Bacterial response mechanisms frequently involve spe-cific sets of genes that are activated to help the cell adapt to stress.Alternative sigma factors, of which Escherichia coli has seven, are afrequently used regulatory mechanism (1). While housekeepinggenes expressed during exponential growth are controlled by thetranscription factor �70 (2, 3), alternative sigma factors act as tran-scription initiation factors to control the activation of specializedregulons under specific growth or stress conditions (4). The gen-eral stress response sigma factor �S activates the transcriptionof �70 genes, conferring resistance to carbon/phosphate/nitro-gen starvation, heat shock, high/low pH, UV radiation, and oxi-dative stress, among others (5, 6).

Microorganisms living in an aerobic environment unavoidablyencounter oxidative stress as a by-product of their aerobic metab-olism (7). The resultant formation of reactive oxygen species(ROS) can lead to damage to cellular components, includingmembranes, DNA, and proteins (8). As an adaptation to this con-dition, bacteria produce enzymes, such as superoxide dismutasesand reductases, to scavenge these toxic components (9). Addition-ally, cells also face external sources of oxidative stress: macro-phages produce superoxide and nitric oxide to kill invading bac-teria (10), following perception of pathogens, plants also inducethe synthesis of organic peroxides (11), certain communities ofmicroorganisms excrete ROS to inhibit the growth of their com-petitors (12), and exposure to environmental redox cycling com-pounds can cause damaging intracellular redox reactions (13).

In this challenging environment, bacteria have developed re-fined molecular mechanisms of defense. The DNA-binding pro-

tein from starved cells (Dps) plays a crucial role during stressexposure. Escherichia coli dps mutants experience a severe reduc-tion in survival when exposed to any of several different stressors,including oxidative stress, heat shock, metal exposure, UV andgamma irradiation, or extreme pH (14–16). Additionally, Dps wasshown to protect cells against DNA strand breakage (17). In E. coli,the protective effect of Dps is attributed to its dual biochemicalfunctions. Dps has the ability to bind DNA and form Dps-DNAcrystals, which may provide mechanical shielding against damag-ing agents (14, 18, 19). The ferroxidase activity of Dps may alsocontribute significantly to its protective ability. Hydroxyl radicalscan be formed intracellularly through a chemical reaction betweenferrous iron and H2O2, either internally generated or derived fromthe environment. Dps catalyzes the oxidation of ferrous iron,preferring H2O2 as a reactant rather than O2, thereby prevent-ing the formation of hydroxyl radicals (20). Dps oligomers arecomposed of 12 identical monomers, each one folded into acompact four-helix bundle (21), surrounding a central cavity

Received 14 March 2016 Accepted 20 March 2016

Accepted manuscript posted online 28 March 2016

Citation De Martino M, Ershov D, van den Berg PJ, Tans SJ, Meyer AS. 2016. Single-cell analysis of the Dps response to oxidative stress. J Bacteriol 198:1662–1674.doi:10.1128/JB.00239-16.

Editor: R. L. Gourse

Address correspondence to Anne S. Meyer, a.s.meyer@tudelft.nl.

Supplemental material for this article may be found at http://dx.doi.org/10.1128/JB.00239-16.

Copyright © 2016, American Society for Microbiology. All Rights Reserved.

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that can store up to 500 iron atoms (22). The DNA-binding andferroxidase activities of Dps are biochemically separable, butthey both contribute to the maintenance of DNA integrity andcellular viability (23).

Intracellular Dps levels are controlled by a complex regulatorynetwork. During the transition from exponential to stationaryphase, the number of Dps molecules within a single E. coli bacte-rium increases from approximately 6,000 to 180,000, whereby itbecomes the most abundant DNA-binding protein (24). dps istranscribed from a single promoter recognized by either the �70

(housekeeping) or �S (stationary-phase) sigma factor in responseto different growth and environmental conditions (25–27). In ex-ponential growth, dps can be activated in an OxyR-dependentmanner by treatment of the cells with H2O2, recruiting �70 toinitiate transcription. During stationary phase or carbon starva-tion, �S controls dps expression (25). When bacteria are growingexponentially and not exposed to stress, the dps promoter isdownregulated by two nucleoid-binding proteins, Fis and his-tone-like nucleoid-structuring (H-NS) protein (24, 26).

Despite the knowledge acquired in recent years, the behavior ofthe Dps response is not understood at the single-cell level. Uponexposure to oxidative stress, each cell that sustains oxidative dam-age will require sufficient upregulation of enzymes that can coun-teract the damage in order to maintain its health. However, thehigh-resolution fluctuations of Dps production levels over timeand the intensity and duration of Dps production during the Dpsresponse are still unknown at the single-cell level, as well as in bulkcultures. Very little is known also about the variability of the Dpsstress response in individual cells and its effect on cellular growthrate, which might play a crucial role in the ability of a bacterialpopulation to maintain a competitive advantage under adverseenvironmental conditions. In addition, it is unknown how thedynamics of Dps production are affected when the concentrationof stressor is varied, a question that is central to the ability of a cellto respond appropriately to changes in its environment. Clearinsights into these biological processes require recently developedsingle-cell technologies to overcome the limitations of bulk exper-iments, allowing for the quantification of the cell-to-cell variabil-ity in a population as well as the characterization of the dynamicsof stress responses (28–34).

In this work, we examined the kinetics and variability of acti-vation of Dps production at the single-cell level upon exposure todifferent levels of oxidative stress. We observed a single pulse ofDps production, with an intensity and duration proportional tothe concentration of H2O2 applied, until the highest concentra-tion of H2O2 resulted in saturation of the intensity but not theduration of Dps production. Cell growth was not linearly corre-lated with the H2O2 concentration, such that low concentrationsresulted in robust Dps production but only a minor decrease inthe initial growth rate. Higher concentrations of H2O2 were asso-ciated with major decreases in the growth rate, accompanied bydramatically increased variation. A comparison of bacteria thatwere exposed to the same concentration of stressor revealed thathigher levels of Dps production were associated with similar orslower growth than that of cells with lower Dps production. Thisbehavior was perhaps due to variation in the amount of damageexperienced by individual cells that drove both reduced growthand increased Dps production.

MATERIALS AND METHODSdps-mCherry strain construction. The E. coli dps-mCherry strain was cre-ated from the E. coli K-12 strain W3110 (CGSC 4474) by replacement ofthe genomic dps gene by a counterselectable cat-sacB cassette (23) andsubsequent replacement with a dps-mCherry cassette.

The dps-mCherry cassette was created using an adapted version of theDNA assembly protocol described by Gibson et al. (35) and introducedinto the pBAD33 plasmid to create the pM1 plasmid. The backbone plas-mid pBAD33 (36) was amplified using PCR to create compatible ends forrecombination with the dps-mCherry cassette. The following primers wereused: forward primer MDM1, 5=-GATCCCCGGGTACCGAGCTC-3=;and reverse primer MDM2, 5=-CAAGCTTGGCTGTTTTGGCG-3=. ThemCherry gene was amplified using PCR from the plasmid pROD22 (37) tointroduce the dps ribosome binding site (RBS) sequence immediately up-stream of the mCherry gene. The following primers were used (the se-quence of the RBS is underlined): forward primer MDM3, 5=-CATCAAGAGGATATGAAATTATGGCTATCATTAAAGAGTTC-3=; and reverseprimer MDM4, 5=-TTACTTGTACAGCTCGTCCATGC-3=. This RBS-mCherry PCR product was further amplified to introduce an upstreamflanking sequence homologous to the dps gene and a 30-bp downstreamflanking sequence homologous to the pBAD33 plasmid. The followingprimers were used (the sequences of the homologous regions are under-lined): forward primer MDM5, 5=-GTTTATCGAGTCTAACATCGAATAACATCAAGAGGATATGAAATTATG-3=; and reverse primer MDM6,5=-TTCTCTCATCCGCCAAAACAGCCAAGCTTGTTACTTGTACAGCTCGTCC-3=. The dps gene was amplified from the pET-17b-dps plas-mid (23) to introduce a 30-bp upstream flanking sequence homologous tothe plasmid pBAD33 and a downstream flanking sequence homologousto the RBS-mCherry gene. The following primers were used (the se-quences of the homologous regions are underlined): forward primerMDM7, 5=-TAGCGAATTCGAGCTCGGTACCCGGGGATCATGAGTACCGCTAAATTAGT-3=; and reverse primer MDM8, 5=-CATAATTTCATATCCTCTTGATGTTATTCGATGTTAGACTCGATAAAC-3=.

The three fragments were digested with DpnI (New England BioLabs[NEB]) at 37°C for 1 h, purified with Wizard SV gel and PCR clean-upsystem (Promega), and then assembled using the DNA assembly de-scribed by Gibson et al. (35). The assembly reaction mixture was preparedby combining 15 �l of Gibson assembly master mix (320 �l of 5� ISObuffer [0.5 M Tris-HCl {Sigma} {pH 7.5}, 50 mM MgCl2, 4 mM dinucleo-side triphosphate {dNTP} {Invitrogen} mix {equal concentration of thefour nucleotides}, 50 mM dithiothreitol {DTT} {Sigma}, 25% {wt/vol}polyethylene glycol 8000 {PEG-8000} {Sigma}, 5 mM NAD {NEB}], 0.64�l of 10 U �l�1 T5 exonuclease [Epicentre], 20 �l of 2 U �l�1 Phusionpolymerase [Finnzymes], 160 �l of 40 U �l�1 Taq ligase [NEB], distilledwater [dH2O] to 1.2 ml), 100 ng of linearized vector backbone, and 100 ngof each assembly fragment, in a total volume of 20 �l. The reaction mix-ture was incubated at 50°C for 60 min. Electrocompetent E. coli W3110cells were transformed with 5 �l of the assembly reaction mixture usingelectroporation. The positive colonies carrying the chloramphenicol re-sistance gene from the pBAD33 plasmid were identified, and the accuracyof the sequence was checked with sequencing analysis.

The dps-mCherry cassette was amplified from the pM1 plasmid usingPCR to introduce 50-bp flanking regions homologous to the chromo-somal dps flanking regions. The following primers were used (the se-quences of the homologous regions are underlined): forward primerMDM9, 5=-TACTTAATCTCGTTAATTACTGGGACATAACATCAAGAGGATATGAAATTATGAGTACCGCTAAATTAG-3=; and reverseprimer MDM10, 5=-AGGAAGCCGCTTTTATCGGGTACTAAAGTTCTGCACCATCAGCGATGGATTTACTTGTACAGCTCGTCCA-3=. Thefragment was DpnI digested, purified, and then introduced with electro-poration into a W3110 dps::cat-sacB strain (23). Homologous recombi-nation was allowed to occur for 3 h in LB medium at 37°C while shaking at250 rpm, and cells were plated on NaCl-free LB 10% sucrose agar (coun-terselective for sacB). The plates were incubated overnight at 30°C.Healthy-looking colonies were restreaked on LB agar containing 25

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�g ml�1 chloramphenicol. Colonies that did not grow on chloramphen-icol were screened using colony PCR, and gene replacement was verifiedby sequence analysis. mCherry expression was confirmed with fluores-cence-activated cell sorting (FACS) (data not shown).

Growth conditions for microscopy. For the single-cell microscopyexperiments, one colony of dps-mCherry was inoculated overnight intoHi-Def azure medium (catalog no. 3H500; Teknova) supplemented with0.2% glucose and grown overnight at 37°C. This preculture was diluted1:100 and grown for around 2 h at 37°C until early exponential phase(optical density at 600 nm [OD600], 0.2 to 0.3). The culture was diluted toan OD600 of 0.005 for seeding onto the agarose pad.

Agarose pad preparation. Agarose pads were prepared using a mod-ified version of the protocol described in Young et al. (38). The pads wereprepared freshly for each experiment. A concentration of 2% (wt/vol)low-melt agarose LE (catalog no. V3125; Promega) was added to 5 ml ofHi-Def azure medium and dissolved by microwaving. After the agarosesolution had cooled, H2O2 was added. Agarose pads were formed imme-diately thereafter. Cover glass slides of 20 mm2 (catalog no. 631-0122;VWR) were placed on Parafilm M (Bemis Company, Inc.), and 900 �l ofagarose was pipetted onto each. Immediately after pipetting, a secondcover glass was placed on top of the agarose. The pads were allowed tosolidify for 45 to 60 min at room temperature while covered with a lid toprevent edge evaporation. When the agarose was solidified, it was cut intopads of 0.5 by 0.5 cm. Two microliters of bacterial culture diluted to anOD600 of 0.005 was seeded onto individual agarose pads. The culture wasallowed to evaporate and absorb into the agarose for about 10 min at roomtemperature. When the surface appeared to be dry, the pad was flippedwith a scalpel onto a 4-well slide-base tissue culture chamber (Starstedt).The chamber was closed with a lid and sealed with Parafilm M to avoidevaporation during the imaging. The cells were able to grow in a mono-layer due to their placement between the glass bottom of the chamber andthe agarose pad on top.

The variability of H2O2 distribution in the pads was determined usingrhodamine as a fluorescent reporter. During the preparation of the aga-rose pads, dihydrorhodamine 123 (catalog no. D1054; Sigma-Aldrich)was added to a final concentration of 20 �M after the agarose solution hadcooled, and the pads were formed immediately thereafter. The pads werescanned using a Typhoon Trio (Amersham Biosciences), and the imageswere analyzed using the ImageJ software (39). The fluorescence intensityvalues of 80 different pixels in 2 different pads were averaged, and thestandard deviation was calculated, showing an upper limit of variability of12.9%. We expected a lower variability for the H2O2 molecule than forrhodamine, since the diffusion coefficient of H2O2 is 1 order of magnitudelarger than that of rhodamine, at 1.305 � 0.83 � 10�5 cm2 s�1 (40) and4 � 10�6 cm2 s�1, respectively (41).

Fluorescence microscopy. Microcolonies on agarose pads were im-aged by time-lapse fluorescence microscopy using an inverted microscope(Olympus IX81), an AMH-200 lamp (Andor), and a Cy3 filter cube(4040C). Images were acquired with a Luca R EMCCD camera (Andor).The Andor iQ software was used to control the microscope and to per-form automatic imaging acquisition. Experiments were performed at37°C using an incubation chamber (H201-T; Okolab) to allow precisetemperature control. Phase-contrast images (500-ms exposure time, 3images �0.2 �m from the focus) and fluorescence images (100-ms expo-sure time) were recorded every 5 min for 3 to 4 h.

Data analysis. Images were analyzed using a custom Matlab program(42) based on the Schnitzcells program (38). Data analysis consisted ofthree steps: segmentation, tracking, and extraction of cell parameters.Each phase-contrast image (average of three) was segmented: the back-ground was separated from the cells, and clumps of cells were cut based onconcavity and phase-contrast maxima. Then, the outline of each individ-ual cell was detected. Cell edges were determined using the Laplacian ofGaussian filter. The segmentation of the cells was checked and correctedmanually when necessary. Next, tracking was performed, in which celllineages were traced by a tracking algorithm that searches for nearby cells

in successive frames. Last, cell length was extracted from segment prop-erties, and growth rate was determined from exponential fits of lengths-in-time. Individual cell fluorescence was extracted from fluorescent im-ages using segmentation obtained from phase-contrast images (for moredetails on analysis, see the supplemental material). For each microcolony,the fluorescence intensity curves were fitted with the best-fitting polyno-mial (degree 5), and the maximum of this function was considered to bethe maximum fluorescence intensity. Dps production activity is defined asthe rate of mCherry protein production (32, 34, 38, 43). The duration ofDps production was calculated as the time from the beginning of theexposure to H2O2. Between 11 and 19 colonies for each stress conditionwere analyzed, for a total of 75 colonies.

RESULTSConstruction of a reporter strain for Dps production. To ex-plore Dps production dynamics, we constructed a reporter strainof E. coli (the dps-mCherry strain), with the mCherry gene intro-duced as a reporter for Dps production. Both genes are locatedbehind the dps promoter, with mCherry immediately downstreamof dps. A ribosome binding site (RBS) sequence identical to that ofthe dps RBS was placed upstream of the mCherry reporter gene(see Fig. S1 in the supplemental material). This construct allowedthe detection and the quantification of Dps production activity insingle cells through monitoring of the collective fluorescenceemitted by the fluorescent proteins. In order to characterize thehealth of the dps-mCherry strain, we compared its growth withthat of the wild-type parental strain in the presence of H2O2 con-centrations between 0 and 10 mM. The two strains showed a sim-ilar growth response (see Fig. S2 in the supplemental material).The growth kinetics were comparable at concentrations of H2O2

up to 1 mM, showing similar robust exponential-phase kineticsand final optical densities. At higher concentrations of H2O2, bothstrains showed growth inhibition. Thus, the engineered dps-mCherrystrain exhibits a growth response to H2O2 similar to that of the wild-type strain.

To verify Dps production, both strains were exposed to 0, 0.5,and 1 mM H2O2, and Dps protein levels were analyzed by Westernblotting. An increase in Dps concentration proportional to thestressor concentration was detected in both strains in the presenceof H2O2 (see Fig. S3 in the supplemental material).

An engineered strain carrying a chimeric version of dps, fusedC terminally to the mCherry gene as translational reporter, wasalso constructed. Cells expressing this protein showed a nonho-mogeneous distribution of fluorescence throughout the cell vol-ume, with visible puncta of more intense fluorescence (data notshown). Previous work has similarly shown that fusion of Dpswith the green fluorescent protein (GFP) resulted in aggregationof this fusion protein in E. coli cells (44). This strain was thereforeexcluded from further experimentation.

Dps production dynamics during oxidative stress. Cells ex-posed to concentrations of H2O2 between 0 and 100 �M wereanalyzed using quantitative time-lapse fluorescence microscopyto detect Dps protein production, defined as the rate of mCherryprotein production (32, 34, 38, 43), in each individual cell overtime. The E. coli cells were grown in rich defined medium to earlyexponential phase and then transferred to an agarose pad in whichH2O2 was incorporated to begin the application of oxidative stres-sors. Individual cells grew and divided over time to give rise to amicrocolony. Differences in growth and fluorescence could beobserved in cells not exposed to any stressor compared to those inthe presence of different concentrations of H2O2. In the colonies

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without applied stress, we observed that the fluorescence of eachcell is indistinguishable from background during the entire dura-tion of the measurement (see Fig. S4A in the supplemental mate-rial). In the presence of H2O2, we detected a fluorescent signal thatwas roughly proportional to the amount of applied stress (see Fig.S4B to E in the supplemental material). We observed a generaltrend in the intensity of the fluorescence signal over time: theintensity increased during the initial period of the measurementand then decreased thereafter. Reduced growth was apparent athigher concentrations of H2O2, and at 100 �M H2O2, there was anear-complete inhibition of cell division (see Fig. S4D and E in thesupplemental material).

The data were analyzed using modified Schnitzcells software(38) to extract the fluorescence intensity within single cells as themean fluorescence per unit of area (42). In the absence of oxida-tive stress, the fluorescence intensity of each individual cell presentwithin a microcolony over time was very low (Fig. 1A). Exposureto hydrogen peroxide induced a single pulse of fluorescence thatstarted shortly after the cell progenitor of the colony first experi-enced the stress in every individual cell analyzed (100%) (Fig. 1Bto E). The pulse was highly synchronized between the individual

cells within each microcolony population throughout the dura-tion of the imaging. The variability of the fluorescence signalamong cells within a colony at each time point was evaluated bycalculating the coefficient of variation (CV) as the ratio of thestandard deviation to the mean. As the single cells divided to forma small microcolony over the course of the experiment, the CVremained low, between 0.0 and 0.25, for colonies exposed to 0, 50,or 100 �M H2O2. For cells exposed to 10 or 30 �M H2O2, the CVincreased steadily over time to reach values around 0.5 (Fig. 1F).This increase in CV over time might be due to an asymmetricdivision of oxidative components or mCherry molecules amongindividual bacteria as the cell population increases through celldivision.

In order to compare fluorescent responses between microcolo-nies, we calculated the average of the fluorescence values of all cellswithin a microcolony at each time point measured (Fig. 2). Everycolony grown in the absence of stressor showed a low averagefluorescence signal that decreased slightly over the duration of theimaging (Fig. 2A). The colonies exposed to 10, 30, or 50 �M H2O2

showed a similar fluorescence profile: a large transient increase influorescence over time that took the form of one major peak.

FIG 1 Exposure to H2O2 induces a single pulse of Dps production activity synchronized over the individual cells within each microcolony. (A to E) Examplesof fluorescence intensity over time in individual cells in a microcolony exposed to different concentrations of H2O2. Each line represents a single cell. (F) Theaverage coefficient of variation (CV) over time of the fluorescence intensity among all the cells exposed to the same stress condition, for various concentrationsof H2O2. a.u., arbitrary units.

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Colonies exposed to the same amount of hydrogen peroxideshowed varied peak amplitudes and durations (Fig. 2B to D). Incontrast, at 100 �M H2O2, no peak of fluorescence was detected.Instead, the average fluorescence signal in each colony rose to aplateau over a variable period of time (Fig. 2E). A calculation ofthe average fluorescence profile over time for all colonies undereach experimental condition revealed that increasing concentra-

tions of H2O2 resulted in an increase in both the intensity andduration of the fluorescence signal. The standard deviations asso-ciated with certain conditions showed a large overlap, especiallybetween 50 �M and 100 �M (Fig. 2F). The variability of the aver-age fluorescence signal among different microcolonies under thesame stress condition was evaluated by calculating the coefficientof variation at each time point. The CV values observed at 0, 30,

FIG 2 The Dps response per microcolony exhibits variation in peak amplitude and duration. (A to E) The average fluorescence signal over time of microcoloniesexposed to different concentrations of H2O2. Each line represents the average fluorescence intensity of all cells within one microcolony. (F) The averagefluorescence signal over time of all the colonies exposed to the same stress condition. The shaded area represents the standard deviation. G) The coefficient ofvariation (CV) over time of the average fluorescence signals of all the microcolonies exposed to the same stress condition for various concentrations of H2O2.

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and 100 �M H2O2 remained around 0.3, while at 10 and 50 �MH2O2, the CV values were higher, reaching a maximum value ofaround 0.6 at 10 �M and 0.9 at 50 �M H2O2 before decreasingagain (Fig. 2G).

To assess whether the observed dynamics of Dps inductionwere an artifact of the experimental procedure, several controlexperiments were performed. To determine the consequences oflight exposure on the mCherry protein during the time-lapsefluorescence microscopy process, a photobleaching test was per-formed on a strain of E. coli with constitutive mCherry expression(see the supplemental material). We observed an average of abouta 20% decrease in the fluorescence signal due to the cumulativephotobleaching effect of our image acquisition process on a singlecell (see Fig. S5 in the supplemental material). To test the effect ofimaging on the cellular fluorescence, images of the dps-mCherrystrain in the presence of 30, 50, or 100 �M H2O2 were acquiredevery 30 min. These fluorescence curves showed a shape similar tothat obtained from image acquisition every 5 min (Fig. 2; see alsoFig. S6 in the supplemental material), demonstrating that that theimaging process does not significantly affect the measured cellularbehavior. Similarly shaped peaks of fluorescence were observed inboth the agarose pad system and in a microfluidics device (45) inwhich H2O2 was constantly applied to the cells over the durationof the imaging (see Fig. S7 in the supplemental material), indicat-ing that the shape of the fluorescence curve is not due to the deg-radation of H2O2 over time. The stability of mCherry signal in thepresence of the oxidating effect of 50 and 100 �M H2O2 was alsoinvestigated, showing no statistically significant difference inmCherry degradation or loss of fluorescence intensity due to ox-idation (see Fig. S8 in the supplemental material).

Correlations between oxidative stressor concentration andthe intensity and duration of Dps production. For a quantitativeanalysis of Dps induction in the presence of oxidative stress, weanalyzed the intensity and length of the fluorescence peak. Foreach microcolony, the curve representing the average fluorescenceintensity among its constituent cells was fitted with a polynomialfunction in order to extract both the maximum value of the fluo-rescence and the time point at which it was reached. These valueswere calculated from averaged microcolony fluorescence values,since individual cells within each microcolony showed low vari-ability in fluorescence at time points before the peak of fluores-cence was reached (Fig. 1F). A calculation of the average maxi-mum fluorescence values of colonies exposed to the same amountof H2O2 revealed that higher concentrations of stressor werecorrelated with higher peak amplitude for H2O2 concentrationsbetween 0 �M and 50 �M (Fig. 3A). No increase in average max-imum fluorescence value was observed when the H2O2 concentra-tion was increased from 50 �M to 100 �M (Fig. 3A). The variabil-ity in the maximum fluorescence intensity among differentcolonies in the presence of the same concentration of stressor wasevaluated by calculating the coefficient of variation. These CVvalues ranged between 0.23 and 0.47, with the maximum variabil-ity observed at 10 �M H2O2 (Fig. 3B). No overall trend was seenbetween the coefficient of variation and the maximum fluores-cence values over the various concentrations of H2O2 (Fig. 3C).No significant differences were observed in the distribution ofmaximum fluorescence values when microcolonies were grownon the same agarose pad versus different agarose pads.

The average time at which the maximum fluorescence signalwas observed for microcolonies under each experimental condi-

tion increased steadily with the amount of H2O2 applied to theculture (Fig. 4A). The coefficient of variation for the time of max-imum fluorescence intensity was calculated between different mi-crocolonies under the same stress condition and ranged between0.10 and 0.29, lower than the variability observed for the strengthof the induction (Fig. 4B). No relationship was observed betweenthe coefficient of variation values and the time to maximum fluo-rescence over the concentrations of H2O2 (Fig. 4C). Taken to-

FIG 3 Dps induction intensity increases with exposure to higher concentra-tions of H2O2. (A) The average maximum values of the fluorescence signal foreach microcolony for each concentration of H2O2. The error bars represent thestandard deviations. The letters represent the statistical significance; sampleslabeled with different letters are statistically different (analysis of variance[ANOVA] test, P � 0.05). (B) The maximum values of the fluorescence signalfor each microcolony and the coefficient of variation (CV) of the maximumfluorescence intensity among microcolonies for each H2O2 concentration. (C)Scatter plot of the coefficient of variation versus the average maximum fluo-rescence value for each concentration of H2O2. R represents the Pearson cor-relation coefficient.

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gether, our data indicate that an increase in hydrogen peroxideconcentration led to an increase in Dps production activity. Inaddition, the duration of protein synthesis increased with the con-centration of the stressor.

Correlation analyses were performed on the extracted valuesfor the maximum fluorescence intensity and the duration of theincrease in fluorescence for individual microcolonies. In a simul-taneous comparison of all the stress conditions, the Pearson cor-relation coefficient (R) between the time to reach the fluorescencepeak and its intensity was 0.80, with a P value of �0.0001 (Fig. 5A).

Fluorescence peaks that were higher in amplitude were thereforestrongly correlated with a longer period of Dps production. Whilethis strongly positive correlation was observed through analysis ofthe pooled data, the data for each individual H2O2 concentration

FIG 4 The duration of Dps induction increases with exposure to higher con-centrations of H2O2. (A) The average time at which the maximum value of thefluorescence signal was observed for each microcolony for each concentrationof H2O2. The error bars represent the standard deviations. The letters repre-sent the statistical significance; samples labeled with different letters are statis-tically different (ANOVA test, P � 0.05). (B) The time to the maximum valueof the fluorescence signal for each microcolony and the coefficient of variation(CV) of the time to the maximum fluorescence intensity among microcoloniesfor each H2O2 concentration. (C) Scatter plot of the coefficient of variationversus the time to the average maximum fluorescence value for each concen-tration of H2O2. R represents the Pearson correlation coefficient.

FIG 5 Correlations between growth rate, intensity, and duration of Dps in-duction. (A) Scatter plot of the average maximum fluorescence intensity ver-sus the average time to the maximum fluorescence for individual microcolo-nies. (B) Scatter plot of the average growth rate per colony versus the averagemaximum fluorescence intensity for individual microcolonies. (C) Scatter plotof the average growth rate per colony versus the average time to the maximumfluorescence intensity for individual microcolonies. Each dot represents a sin-gle microcolony. Microcolonies exposed to the same H2O2 concentration arerepresented in the same color. The R value in the top right corner of each graphrepresents the Pearson correlation coefficient over all the data. The R below thelabel for each concentration of H2O2 represents the R value calculated over allmicrocolonies under each stress condition. *, P � 0.05.

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when considered separately showed a weaker positive correlation,ranging from 0.23 to 0.82, with an average of 0.49 (Fig. 5A).

Effects of oxidative stress on cellular growth. To analyze theeffect of oxidative stress on cellular morphology, the parameter ofcell length was calculated as the length of the axis between the twopoles of a cell (42). We compared the average lengths of all cellswithin each microcolony over time for all the microcolonies ana-lyzed (see Fig. S9 in the supplemental material). If 0 �M or 10 �MH2O2 was applied, we observed the trend that cell length slightlydecreased over time, declining from an average of 5.5 �m to 3.5�m (Fig. 6; see also Fig. S9 and B). The application of higher H2O2

concentrations of 30 �M or 50 �M resulted in a small increase inthe average cell length but a higher proportion of elongated cells,reaching a length of up to 12.5 �m (Fig. 6; see also Fig. S9C and Din the supplemental material). The highest concentration of H2O2

applied, 100 �M, caused a complete halt of cell growth and divi-sion; each cell remained the same length throughout the course ofthe experiment (Fig. 6; see also Fig. S9E in the supplemental ma-terial). The standard deviation for the average cell length per mi-crocolony overlapped greatly between conditions, such that theamount of stressor applied was a poor predictor of cell length (Fig.6). We observed that the variability in cell length increased overtime for colonies exposed to 0 to 50 �M H2O2, rising from near-zero at the start of imaging to 0.6, but it remained close to zero for100 �M H2O2 (see Fig. S9 in the supplemental material).

We also evaluated the cellular growth rate over time upon ex-posure to oxidative stress. The instantaneous growth rate, �, wascalculated by fitting the cell length over time to an exponentialfunction (42). Cell width was not seen to vary significantly duringthe experiments. We calculated the average instantaneous growthrate of all the cells within a microcolony at each point in time (Fig.7). The cells exposed to either 0 �M or 10 �M hydrogen peroxideshowed a similar and slightly increasing growth rate over time,ranging between 1.1 and 1.8 � h�1 (Fig. 7A and B). Each furtherincrease in the stressor concentration led to a reduction in cellgrowth. We observed that at 30 �M H2O2, the colonies grew onlymoderately during the initial part of the experiment, with an av-erage starting growth rate of approximately 0.6 � h�1, but showed

a complete recovery of growth over several hours (Fig. 7C). At a 50�M concentration of hydrogen peroxide, growth was severely af-fected. Initial growth rates of 0.2 to 0.3 � h�1 increased slowly overtime but only partially recovered over the course of imaging (Fig.7D). When hydrogen peroxide was increased to 100 �M, cellulargrowth was completely stalled during the entire duration of theimaging (Fig. 7E). Overall, increasing concentrations of H2O2 re-sulted in a greater initial decrease in cell growth and increasinglyimpaired recovery of cell growth over time (Fig. 7F).

Analysis of the average growth rate per microcolony over theduration of the experiment revealed that concentrations of H2O2

up to 30 �M had moderate effects on the average growth rate,producing a decrease from 1.9 � h�1 at 0 �M to 1.4 � h�1 at 30�M. A strong reduction in growth was observed at exposure to 50�M H2O2, with an average rate of 0.6 � h�1, and at 100 �M, cellgrowth was negligible, with an average growth rate of 0.01 � h�1

(Fig. 8A). The coefficients of variation for the average growth rateswere low under conditions of 0 to 30 �M H2O2, ranging from 0.09to 0.24, while the variation for 50 �M H2O2 was extremely high, at0.75 (Fig. 8B). For 100 �M H2O2, the coefficient of variation couldnot be accurately calculated because the mean value of the growthrate was close to zero for most microcolonies. Higher H2O2 con-centrations were correlated with higher coefficient of variationvalues (Fig. 8C). Thus, an increase in H2O2 concentration wasstrongly correlated with both a decrease in growth rate and anincrease in growth rate variability, primarily for the higher con-centrations of stressor.

To analyze the relationship between Dps induction parametersand cellular growth, we determined Pearson correlation coeffi-cients between the average growth rate within microcolonies andthe intensity and the duration of induction peaks. Between theaverage growth rate and amplitude of Dps induction for all stressconditions compared simultaneously, we observed a strong nega-tive correlation (R �0.71), with a P value of �0.0001 (Fig. 5B).Interestingly, the correlation coefficients calculated within eachstress condition were dramatically weaker, with an average of 0.03,and not significantly correlated. Similarly, the correlation coeffi-cient comparing the growth rate and the time to reach the maxi-

FIG 6 Effects of oxidative stress on cellular length. (A) Distribution of the length of all cells in a microcolony, averaged over all time points within eachexperiment, for different concentrations of H2O2. The tops and bottoms of the vertical bars represent the maximum and minimum length values, respectively;the top and bottom of the box represent the 75th and the 25th percentiles, respectively; the line within the box is the median; and the small square in the box isthe mean value. The letters represent the statistical significance; samples with different letters are statistically different (ANOVA test, P � 0.05). (B) The averagelength of all cells within the microcolonies over time for various concentrations of H2O2. The shaded areas represent the standard deviations.

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mum fluorescence was strongly negative when calculated over allconditions (R �0.85), with a P value of �0.0001, but muchweaker within each individual condition (average R �0.18)(Fig. 5C). Lower average growth rate was therefore seen to bestrongly associated with both higher Dps production and a longerinduction time over a range of H2O2 concentrations.

We further analyzed the relationship between the mean fluo-rescence signal per colony and the mean growth rate per colonyover time, identifying three response categories. The first categoryconsisted of colonies that showed a constant high growth rate witha small-amplitude pulse or decrease over time of the fluorescencesignal (Fig. 9A). In the second category, the colonies exhibited asteady increase in growth rate over time, starting around 0.5 � h�1

and reaching values of around 1.8 to 2 � h�1. The fluorescencesignal initially increased, reached its peak value, and then de-creased again (Fig. 9B). The third category contained colonies in

which the growth rate remained constantly low while the fluores-cence signal increased robustly over time (Fig. 9C).

Increasing concentrations of H2O2 resulted in microcolonygrowth that was increasingly likely to exhibit a higher-numberedcategory of response, associated with increasingly impairedgrowth rate. All (100%) of the colonies grown without H2O2

showed a category I-type response (Fig. 9D). Of the coloniesgrown in 10 �M H2O2, an intermediate behavior was seen inwhich 37% showed a category I response and 63% showed a cat-egory II response (Fig. 9D). All (100%) of the colonies exposed to30 �M H2O2 exhibited a category II response (Fig. 9D). Of thecolonies grown in 50 �M H2O2, an intermediate behavior wasagain seen in which 79% showed category II behavior and 21%showed a category III response (Fig. 9D). Finally, all (100%) of thecolonies at 100 �M H2O2 showed a category III response (Fig.9D). The presence of these three distinct patterns may suggest a

FIG 7 Oxidative stress suppresses initial rates of cellular growth. (A to E) The average instantaneous growth rate of all the cells within a colony over time fordifferent concentrations of H2O2. Each line represents the average growth rate of all cells within one microcolony. (F) The average growth rate over time of all thecolonies in the presence of the same concentration of H2O2. The shaded areas represent the standard deviations.

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threshold model in which increasing stressor levels cause a recov-erable reduction in growth rate at a lower threshold concentrationor a long-term halt in growth rate at a higher threshold concen-tration, due to still-uncharacterized internal regulatory processes.

DISCUSSION

In this study, we have investigated for the first time the Dps stressresponse at the single-cell level. When exposed to H2O2, E. colicells exhibit a single pulse of activation of Dps production. Higherconcentrations of H2O2 induce an increase in both the intensityand duration of the activation pulse. The correlation between cel-lular growth and stressor intensity is quite nonlinear. Low H2O2

concentrations initiate a robust Dps response but have little effecton cellular growth, while higher concentrations of H2O2 lower thegrowth rate dramatically and cause high variability. Cells exposedto the same H2O2 concentration do not receive a growth advan-tage in the case of higher Dps induction. The recovery from stressmay thus rely more upon the degree of damage generated in indi-vidual cells than on the strong induction of specific stress responseproteins.

Stressor intensity predicts pulse amplitude and duration butnot growth rate variability. The single pulse of induction of Dpsproduction likely arises from more general features of the oxida-tive stress-induced response in E. coli. In the presence of H2O2, dpsactivation is regulated by the OxyR protein (25), a key regulator ofthe adaptive response to oxidative stress (46, 47). During expo-nential growth, H2O2 converts the OxyR protein to an oxidizedactive form that recruits 70-RNA polymerase to initiate dps tran-scription (25). In E. coli cells treated with 200 �M H2O2, OxyR wasfully converted to its oxidized form within 30 s of exposure to thestressor. Thereafter, OxyR reverted back to its reduced form witha half-life of �5 min, and no oxidized OxyR was detected after 10min (48). This transient activation response provides a potentialwindow for dps transcription lasting on the order of only minutes.Specific analysis of dps transcription kinetics in cells exposed to 10�M H2O2 revealed dps induction to be active for a limited periodof time as well. Maximum levels of dps transcript were detected at1 min after exposure, followed by a steady decrease until returningto background levels by 20 min postexposure (49). Following thedecrease in OxyR activity, transcriptional repression of dps occursvia the formation of an unproductive complex between the nucle-oid-associated protein Fis and 70 on the dps promoter (26), whichmay provide stringent downregulation of dps transcription at theend of its pulse of activation. The initial increase in observed Dpsreporter signal intensity is thus likely due to the transient burst ofdps transcriptional activity. Thereafter, the decrease in signal in-tensity likely derives from a combination of transcriptional re-pression of the dps promoter and an increase in cellular growthrate that dilutes the reporter protein (Fig. 7), with a minor contri-bution from photobleaching of the reporter protein (see Fig. S5 inthe supplemental material). The absence of a decrease in signalintensity at the highest concentration of H2O2 (Fig. 2E and F) canbe explained by the near-zero cellular growth rate under this con-dition (Fig. 7E and F) that results in a lack of dilution of thereporter protein.

We observe a correlation between the amount of stress appliedto the cells and the peak intensity of the Dps response, whichsaturates at the highest concentrations of stressor (Fig. 3). A cor-relation between the magnitude of the stress and the duration ofthe Dps response is also indicated by our observations (Fig. 4), sothat stronger stresses are associated with both longer and strongerDps production. The lack of increase in the peak intensity of theDps response between our highest two concentrations of H2O2

(Fig. 3A) seems to indicate a saturation of the Dps production

FIG 8 Variation in microcolony growth rate increases at lower growth rates.(A) The average growth rate per microcolony averaged over all cells over alltime points for each microcolony for each concentration of H2O2. The errorbars represent the standard deviations. The letters represent the statistical sig-nificance; samples labeled with different letters are statistically different(ANOVA test, P � 0.05). (B) The average growth rate for each microcolonyand the coefficient of variation (CV) of growth rate among microcolonies foreach H2O2 concentration. Two of the microcolonies exposed to 50 �M H2O2

and 10 of the microcolonies exposed to 100 �M H2O2 are not visible in the plotbecause their average growth rate is 0. (C) Scatter plot of the coefficient ofvariation versus the average growth rate for each concentration of H2O2. Rrepresents the Pearson correlation coefficient. *, P � 0.05.

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mechanism, perhaps due to the limited number of OxyR regula-tory molecules present in the cells. The speed of the initial increasein protein production was seen to be similar under all conditions,such that stronger Dps responses are achieved by modulation ofthe duration of production. However, not all bacterial stress re-sponse genes show a similar pattern of expression. In Bacillus sub-tilis, the addition of increasing concentrations of stressors resultsin production of the general stress response factor �B with eitheran increase in peak amplitude but no alteration in the duration ofthe response (34) or an increase in the frequency of pulses ofinduction, accompanied by only weak changes in pulse amplitudeand duration (32). In contrast, the highly modulated duration ofthe Dps response under various intensities of oxidative stress maybe a strategy to allow for an extended period of repair under con-ditions of more extensive damage.

Over a range of H2O2 concentrations, lower average growthrate is strongly correlated with both stronger Dps production anda longer induction time (Fig. 5). Interestingly, cells exposed to thesame concentration of H2O2 do not receive a growth advantagefrom increased levels of Dps production but instead exhibit sim-ilar or slower growth, even under the 50 �M H2O2 condition, inwhich Dps production levels varied by up to 4-fold. This observa-tion indicates that the kinetics of recovery from stress are notdictated by the magnitude of induction of specific stress responseenzymes. Rather, we propose that individual cells may vary signif-

icantly in their amount of oxidative damage, such that cells sus-taining more damage both have slower growth and induce a largerstress response. The development of real-time in vivo markers ofoxidative damage will be quite interesting for study of the relation-ship between damage and stress response induction.

Separate analysis of the stress conditions reveals that a low doseof H2O2 does not result in a major reduction in cell growth rate,although the Dps enzyme is already produced (Fig. 1 and 7).When the H2O2 concentration reaches a critical level, the bacteriaexhibit extremely high variability in growth rate. This variabilitydoes not correlate with either the intensity or variability of Dpsproduction (Fig. 3 and 8). Noise in metabolic gene expression hasbeen shown to affect the growth stability of a cell under conditionsof active metabolism (31). While metabolic reactions are crucialfor the synthesis of enzymes and molecules necessary for cell de-velopment, stress response processes are responsible for main-taining the stability of cellular equilibrium under disruptive con-ditions. The observed variation in cell growth during exposure tohigh levels of oxidative stress might be linked to increased stochas-tic noise of one or more essential metabolic pathways under theseconditions.

Cell-to-cell variability in Dps production is greater betweenmicrocolonies. The Dps response to oxidative stress shows somefeatures of excitable dynamics, a class of transient cellular differ-entiation in which cells probabilistically enter into an “on” state

FIG 9 Microcolonies exhibited three categories of Dps response. (A to C) Scatter plots of the mean fluorescence signal and the mean growth rate permicrocolony, over time, for example microcolonies in each category. Each dot represents the average fluorescence and the average growth rate of a singlemicrocolony at a specific time point, colored to indicate the time point. (A) Category I, a constant high growth rate associated with a slightly decreasing lowfluorescence signal. (B) Category II, a steady increase in growth rate over time associated with a pulse of fluorescence signal. (C) Category III, a robust increasein fluorescence signal over time associated with a constant low growth rate. (D) The percentage of microcolonies in each response category for each concentrationof H2O2. The letters represent the statistical significance; samples in each group labeled with different letters are statistically different (two-sample t test; P � 0.05).

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and return to the initial “off” state after a certain stereotypicalperiod of time (50). Within the resolution of our experiments, wedetect a single burst of protein production that rapidly activates atemporary stress response state (Fig. 1 and 2). Unlike a true excit-able noise-triggered system, the return to an off state is not stereo-typical in the case of Dps production. Instead, the return to theinitial state occurs after a variable period of time that partiallydepends on growth kinetics. Additionally, we do not observeprobabilistic entry into the on state. Instead, every cell that wasexposed to hydrogen peroxide was seen to initiate Dps produc-tion, and the kinetics and amplitude of the stress response weresynchronized over each microcolony throughout the duration ofimaging.

Cells lacking the dps gene are more sensitive to oxidative stress,showing dramatically reduced viability and elevated DNA damage(16, 18, 23). Because the Dps protein is a key protector in stresssurvival, especially during the initial stage of the exposure, thenonprobabilistic initiation of Dps production allows all affectedcells to respond to the oxidative damage. The similar kinetics ofthe Dps response among individual cells within microcolonies islikely a consequence of the majority of the active Dps productiontaking place in the single-cell stage, before the founding cell hasundergone cell division. Once an oxidatively damaged cell re-sumes growth, the profile of the response is primarily reflective ofdilution only, which seems to exhibit low variation (Fig. 1).

The profile of the Dps response showed greater variability be-tween different microcolonies exposed to the same amount ofstress than among different cells within microcolonies (Fig. 1 and2). While some of this variability may originate from the nonho-mogeneous distribution of hydrogen peroxide in the environ-ment, a relatively moderate amount of site-to-site variability wasobserved on the agarose pads. The variability between microcolo-nies was seen to be dramatically higher for stressor concentrationsin which the microcolonies were seen to fall into either of twodifferent patterns of growth and expression behavior rather thanonly one (Fig. 2 and 9). Most of the variability observed in the Dpsresponses is likely due to differences between the progenitor cellsof each individual colony. Nongenetic cell-to-cell heterogeneitywithin a clonal population is common to many biological pro-cesses (33) and can arise from a broad range of phenomena, in-cluding noise in gene expression or intracellular protein concen-tration, stochastic biochemical interactions, or nonsynchronicityin cell cycle stage (29, 51–53). A genome-wide survey of pheno-typic noise over approximately 75% of E. coli promoters foundthat stress response genes, such as dps, exhibit particularly variedexpression during nonstressful growth (53). On top of this base-line variability, we find that the variability in Dps production ac-tivity can increase �3-fold between nonstress and high-stressconditions (Fig. 2). Whether this dramatic increase in variabilityunder stress or upregulation is a common feature of all bacterialgenes or is limited to certain functional classes will require furtherinvestigation.

ACKNOWLEDGMENTS

We are grateful to Ilja Westerlaken, Mathia Arens, Sriram Tiruvadi Krish-nan, Charl Moolman, and Daniel Lam for fruitful discussions. We thankNynke Dekker for her kind gift of the pROD22 plasmid and ChristopheDanelon for the pRESET-mCherry strain.

We declare no conflicts of interest.This work was supported by the Netherlands Organization for Scien-

tific Research (NWO/OCW) as part of the Frontiers of Nanoscience pro-gram under grant no. NF13BNS10 and the Department of Bionanosci-ence of the Delft University of Technology.

FUNDING INFORMATIONThis work, including the efforts of Michela De Martino and Anne S.Meyer, was funded by Nederlandse Organisatie voor WetenschappelijkOnderzoek (NWO) (NF13BNS10).

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