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J. Biol. Chem., Vol. 280, Issue 18, 17758-17768, May 6, 2005

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The Global Transcriptional Response of Escherichia coli to Induced ³² Protein Involves ³² Regulon Activation Followed by Inactivation and Degradation of ³² in Vivo^*

Kai Zhao, Mingzhu Liu¶, and Richard R. Burgess||

From the McArdle Laboratory for Cancer Research, the Department of Genetics, and the ^¶Department of Computer Science, University of Wisconsin, Madison, Wisconsin 53706

Received for publication, January 12, 2005

	ABSTRACT

TOP ABSTRACT INTRODUCTION EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
³² is the first alternative factor discovered in Escherichia coli and can direct transcription of many genes in response to heat shock stress. To define the physiological role of ³², we have used transcription profiling experiments to identify, on a genome-wide basis, genes under the control of ³² in E. coli by moderate induction of a plasmid-borne rpoH gene under defined, steady-state growth conditions. Together with a bioinformatics approach, we successfully confirmed genes known previously to be directly under the control of ³² and also assigned many additional genes to the ³² regulon. In addition, to understand better the functional relevance of the increased amount of ³² to changes in the transcriptional level of ³²-dependent genes, we measured the protein level of ³² both before and after induction by a newly developed quantitative Western blot method. At a normal constant growth temperature (37 °C), we found that the ³² protein level rapidly increased, plateaued, and then gradually decreased after induction, indicating ³² can be regulated by genes in its regulon and that the mechanisms of ³² synthesis, inactivation, and degradation are not strictly temperature-dependent. The decrease in the transcriptional level of ³²-dependent genes occurs earlier than the decrease in full-length ³² in the wild type strain, and the decrease in the transcriptional level of ³²-dependent genes is greatly diminished in a DnaK strain, suggesting that DnaK can act as an anti- factor to functionally inactivate ³² and thus reduce ³²-dependent transcription in vivo.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
Escherichia coli core DNA-dependent RNA polymerase consists of four different subunits and has the composition ₂'. Core RNA polymerase (E) together with a factor constitutes a holoenzyme complex (E) (1, 2). The holoenzyme complex is able to initiate transcription at specific DNA sequences termed promoters. Since the discovery of ⁷⁰ 36 years ago, numerous factors have been described in E. coli and other prokaryotic organisms (3–7). The seven known E. coli factors are ⁷⁰, ⁵⁴, ³², ^S, ^F, ^E, and ^fecI.

The major factor, ⁷⁰, is involved in the transcription of the majority of genes in the cell. The other factors are alternative factors that enable RNA polymerase to transcribe genes required for cellular adaptation to changes in the external environment. Each factor recognizes and directs RNA polymerase to a different set of promoters.

Among the six known alternative factors, ³², which is encoded by rpoH (htpR, hin, and fam), was the first minor factor to be discovered in E. coli. For heat shock and some other general stress responses (such as sublethal concentrations of ethanol, viral infection, etc.), transcription initiation is regulated largely by ³². The first step of the transcription initiation pathway is the binding of ³² to core RNA polymerase to form an E³² holoenzyme complex. This binding results in the expression of many heat shock proteins (HSPs)¹ that play important roles in protein folding, repair, and degradation under normal and stress conditions.

Because ³² plays an important role in heat shock stress, early work on ³²-dependent genes was focused on the induction of a group of genes upon heat shock stress. Most known ³²-dependent genes were identified either by monitoring synthesis rates of individual proteins before and after heat shock on two-dimensional gels (8) or by hybridizing cDNA (generated mRNA from heat-shocked cells) with membrane filters containing an ordered E. coli genomic library (9). However, in response to temperature upshift, the induction of ^S was shown in a Western blot experiment, and the induction of ^S-dependent genes was confirmed by using a ^S-dependent promoter-lacZ fusion approach (10). Also, Taylor and co-workers (11) found ⁵⁴-controlled genes are another group of genes that can be induced by heat shock in addition to ³² and ^E regulons (12). Therefore, although the heat shock response is mainly mediated by ³², there are some other global gene regulators that increase and turn on genes during the heat shock response. This makes the heat shock stimulon a complicated group of different regulons.

Here we report the results of using transcription profiling experiments to identify the ³² regulon in E. coli. Our basic strategy is to minimally perturb steady-state growth (E. coli MG1655 growing exponentially in minimum medium at 37 °C) by moderate induction of ³². We then monitor global RNA transcript abundance changes as a function of time using Affymetrix GeneChip^R E. coli antisense genome arrays. This approach allows us to reduce the possibility of induction of genes under the control of other factors that was found in the previous heat shock response studies. Meanwhile, to characterize how the transcriptional level of ³²-dependent genes is regulated by the amount of ³² in vivo, we measure the protein level of ³² both before and at various time points after induction by a quantitative Western blot analysis. On the basis of this first systematic study of the ³² regulon in E. coli including ³² protein level determination, we gain insight into the complex network regulated by ³² and how it contributes physiological adaptation to changes in the external environment.

	EXPERIMENTAL PROCEDURES

TOP ABSTRACT INTRODUCTION EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
Reagents and Media—All reagents were purchased from Sigma unless otherwise indicated. 10x MOPS minimal media was prepared as described in Neidhardt et al. (13). The media were filter-sterilized through a 0.2-µm filter and stored at 4 °C. The defined media for cell log-phase growth contained 1x MOPS minimal media, 0.1% glucose, 0.66 mM K₂HPO₄.

Bacteria Strains and Plasmids—To controllably and quantitatively overexpress ³² in E. coli, we constructed an overexpression vector derived from the pZ vectors developed by Lutz and Bujard (14). The pZ-vector system features a tightly regulated low copy number plasmid with a widely controllable regulatory range. A DNA fragment containing the entire ³² protein-coding region was cloned into the KpnI and AvaII sites of pZA31-luc plasmid, putting the entire rpoH ORF under the control of the P_Ltet promoter to produce the ³² overexpression vector pTet32.

A Tet repressor (TetR) expression plasmid, pIL4, carrying the entire TetR gene served as the PCR template. A 690-bp-long Tet repressor gene was PCR-amplified by using primers TetRUp (5'-AACTGCAGAACCAATGCATTGGTGGTAAAATAACTCTATCAA-3'; PstI site underlined) and TetRDown (5'-TCCCCCGGGGGATTTTAAGACCCACTTTCACATT-3'; SmaI site underlined). A kanamycin resistance (Km) coding sequence was amplified from plasmid pACYC177 by PCR using primer pairs of KmUp (5'-GGAATTCCCGTTCGTAAGCCATTTCC-3'; EcoRI site underlined) and KmDown (5'-GGGGTACCCCGTCCCGTCAAGTCAGCGTAA-3'; KpnI site underlined). Both resulting PCR products were cloned into pMOD-2 transposon construction vector (Epicenter).

Because the E. coli Genechip probe set is based on the sequenced E. coli K-12 strain MG1655 (^– F^– ilvG^– rfb^–50 rph-1, prototroph) (15), we chose this bacterial strain to use in our study. For tight control of the P_Ltet promoter, we constructed a derivative E. coli strain MG1655K1, integrating Tet repressor gene and a selectable marker kanamycin resistance gene into the MG1655 chromosome. Tn5 transposon and transposase were used following the procedure of Goryshin and Reznikoff (16).

Growth Conditions and Preparation of Cell Lysates—All cultures were grown in a New Brunswick gyratory water bath shaker (model G76) with vigorous aeration (225 rpm) unless otherwise indicated. For cultures of cells carrying antibiotic resistance markers, the media were supplemented with ampicillin (100 µg/ml), chloramphenicol (30 µg/ml), or kanamycin (50 µg/ml) where appropriate. For induction of ³² under the control of the anhydrotetracycline-regulated promoter, anhydrotetracycline was added at a final concentration of 100 ng/ml.

E. coli strain MG1655K1 containing a ³² overexpression plasmid (pTet32) was grown overnight in MOPS minimal media at 37 °C in an air shaker. 2 ml of the overnight culture was used to inoculate 100 ml of fresh MOPS minimal medium. When the culture density reached an optical density of 0.2, a 1000-µl portion of culture was harvested into a pre-chilled 1.5-ml Eppendorf tube and then immediately put on ice for 1 min. This sample served as the control for Western blot analysis. To measure changes in the ³² intracellular level, cells were then harvested every 5 min after induction, immediately put on ice for 1 min, and centrifuged at 10,000 x g (12,000 rpm for Beckman Microfuge^R) for 10 min at 4 °C. The supernatant was removed, and the cell pellet was resuspended immediately in 40 µl of lysis buffer (1x SDS) and heated at 75 °C for 5 min to quickly lyse the cells and prevent changes in the intracellular levels of the factors being measured.

RNA Isolation, cDNA Synthesis, Labeling, and Hybridization—For preparing the total RNA for microarray experiments, 15-ml samples of cells were taken at 5, 10, and 15 min after induction, immediately mixed with a double volume of RNAprotect bacterial reagent (Qiagen), and then incubated at room temperature for 10 min. Cells were centrifuged at 5,800 x g for 20 min, and cell pellets were stored at –80 °C prior to RNA extraction. Total nucleic acid was isolated using Master-Pure kits (Epicenter) as described by the manufacturer. DNase I (Epicenter) was used to remove genomic DNA contamination. The quality and integrity of the isolated RNA were checked by visualizing the 23 S and 16 S rRNA bands on a 2% agarose gel. 10 µg of total RNA was mixed with 500 ng of random hexamers and then was reverse-transcribed for first strand cDNA by using the Superscript II system (Invitrogen). RNA was removed by using RNase H (Invitrogen) and RNase A (Epicenter). cDNA was purified by using the QIAquick PCR purification kit (Qiagen) followed by partial DNase I digestion to fragment cDNA to an average length of 50–100 bp. The fragmented cDNA was 3'-end-labeled by using terminal transferase (New England Biolabs) and biotin-N⁶-ddATP (PerkinElmer Life Sciences) and was added to the hybridization solution to load onto the Affymetrix GeneChip^R E. coli antisense genome arrays. Hybridization was carried out at 45 °C for 16 h. The arrays were then washed and subsequently stained with streptavidin, biotin-bound anti-streptavidin antibody, and streptavidin-phycoerythrin (Molecular Probes) to enhance the signal. Arrays were scanned at 570 nm with a 3-µm resolution using a confocal laser scanner (Hewlett-Packard). For each time point, two independent cultures were prepared, and the RNA was analyzed in microarray experiments.

Data Analysis—Image analysis was carried out by Affymetrix® Microarray Suite 5.0 software. Cell intensity files were first generated from the image data files. An absolute expression analysis then computes the detection call, detection p value, and signal (background-subtracted and adjusted for noise) for each gene. Genes were considered up-regulated relative to the 0-min time point (before induction) sample if they had a 2-fold increase in signal intensity, and the signal intensity in the experiment had a log₂ value of at least 8.0 with a "present" detection call. The higher log₂ intensity values were used to limit the analysis to those genes for which we have a high degree of confidence in their level of expression.

Purification and Fluorescence Labeling of Proteins and mAbs—Purified core RNA polymerase was made from E. coli MG1655 according to the method of Thompson et al. (17). Purified factors and monoclonal antibodies (mAbs) were made as described by Anthony et al. (18). Mouse mAbs used in this experiment were anti- (4RA2), anti-' (NT73), anti-⁷⁰(2G10), and anti-³² (3RH3). Fluorescence dye, IC5-OSu (Dojindo), was used to label the primary antibodies according to methods described previously (19). The IC5-labeled mAbs, stored at a final concentration of 1 mg/ml, were diluted 1:2000 for use in this experiment.

Electrophoresis and Immunoblot Assay—Lysate samples were electrophoresed on a 4–12% NuPAGE gel. The purified core RNA polymerase as well as the purified factor protein was also loaded on the same gel to serve as controls. The gel was run at a constant voltage of 125 V until the bromphenol blue loading dye had almost run off the bottom of the gel. Proteins in the gel were transferred electrophoretically to a 0.45-µm nitrocellulose membrane at 50 V for 2 h at room temperature. The membrane was blocked with 1% (w/v) nonfat dry milk (Blotto) for 30 min at room temperature or overnight at 4 °C. The blot was then probed in Blotto for 1 h at room temperature with fluorescence-labeled mAbs specific to the factor under study and a subunit of core RNA polymerase. The blot was rinsed three times with 25 ml of PBS buffer and scanned with a Typhoon FluoroImager in the red fluorescence-scanning mode. Signal intensities of the bands were quantified using the ImageQuant program.

To measure soluble protein levels in vivo, the cell pellet was harvested and resuspended in buffer A as described by Anthony et al. (18) before lysozyme was added to facilitate cell breakage. Cells were then sonicated for 90 s to completely break cell walls, and the sample was centrifuged at 20,000 x g for 15 min at 4 °C. Any insoluble inclusion bodies plus cell debris would be in the pellet. The supernatant containing soluble protein was then measured in Western blot assay.

Real Time PCR—Quantitative reverse transcription (RT)-PCR primers were designed using Primer Express software (Applied Biosystems) and were synthesized by the University of Wisconsin Biotechnology Center. Two steps of real time quantitative RT-PCR were performed. 5 µg of the DNase-treated total RNA was reverse-transcribed for first strand cDNA by using the Superscript II system (Invitrogen) as mentioned above. Reactions were then performed using 1 ng of cDNA and 100 nM of each primer in a 50-µl volume with 1x SYBR Green I mixture. Controls lacking AmpliTaq Gold DNA polymerase or template were used. Reactions were run on an ABI 7700 instrument (Applied Biosystems) using the following cycling parameters: 95 °C for 10 min, 40 cycles of denaturation at 94 °C for 15 s, and extension at 60 °C for 1 min. Relative gene expression data analysis was carried out with the standard curve method (20). Changes in expression will be calculated using the time 0 sample as the reference.

Electrophoretic Mobility Shift Assays (EMSA)—The DNA fragments (300 bp) used for gel mobility shift assays were amplified by PCR from the upstream sequence of five genes (yceP, ldhA, macB, mutM, and ybbN) that were highly up-regulated in our microarray data. The DNA was labeled at the 5'-end using T4 polynucleotide kinase (Invitrogen) and [-³²P]ATP (5,000 Ci/mmol; PerkinElmer Life Sciences) at 37 °C for 45 min. The unincorporated nucleotides were removed by passing the labeling reaction mixture through a G-50 Sephadex microspin column (Amersham Biosciences). Core RNA polymerase and ³² were purified using the procedures described earlier (18). The labeled DNA fragment (1.15 nM) was incubated with different concentrations of core RNA polymerase and ³² in a buffer containing 20 mM Tris acetate (pH 8.0), 0.1 mM EDTA, 1 mM dithiothreitol, 50 mM NaCl, 4 mM magnesium acetate, 5% glycerol (v/v), and 200 ng of poly(dI-dC)·poly(dI-dC) (Amersham Biosciences) in a total volume of 20 µl. The mixtures were left on ice for 30 min before being incubated at 30 °C for 15 min. The samples were loaded directly onto a 4–10% native Tris-glycine NOVEX Gel (Invitrogen) and were run at 4 °C in 25 mM Tris, 190 mM glycine (pH 8.3) at 200 V for 1 h. The gel was fixed in a solution of 10% acetic acid and 10% methanol for 15 min and dried at 80 °C on a Slab Dryer (Bio-Rad). BioMax MS film (Eastman Kodak Co.) was used for autoradiography. The gels were scanned using a PhosphorImager (Amersham Biosciences), and the intensities of the bands were determined by using ImageQuant version 5.2 software.

	RESULTS

TOP ABSTRACT INTRODUCTION EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
The Construction of E. coli Strain MG1655K1—The sequenced E. coli K12 strain MG1655 (^– F^– ilvG^– rfb^–50 rph-1, prototroph) (15), on which the E. coli Affymetrix Genechip probe design is based, was chosen for our studies. For controllable induction of individual factors in vivo, we used the P_Ltet promoter to construct an overexpression vector (14). The P_Ltet promoter is controlled by the repressor TetR. A downstream gene can be induced in the presence of the inducer anhydrotetracycline. The TetR repressor gene as well as the kanamycin resistance gene were cloned into the pMOD-2 transposon construction vector as described under "Experimental Procedures." To ensure stable and defined conditions for the synthesis and maintenance of the regulatory protein TetR, the gene encoding this repressor molecular was integrated into the chromosome of this sequenced E. coli strain by using the Tn5 transposon as described by Goryshin and Reznikoff (16). Analysis of several kanamycin-resistant colonies by PCR and Southern blots showed that the transcription unit encoding TetR as well as the kanamycin resistance marker were stably integrated into the MG1655 genome (data not shown).

Quantitation of ³² after Induction—A newly developed quantitative Western blot method (19) was used to monitor the intracellular level of ³² in vivo before and after induction. The -or '-subunits of core RNA polymerase were also examined to serve as internal controls because their intracellular levels remain constant under various conditions (21, 22). The signal intensities of the proteins were immunodetected by the corresponding IC5-labeled monoclonal antibodies. Our results (Fig. 1A) show that although the signal intensities of -or '-subunits were quite constant at all the time points before and after induction, ³² levels varied at different time points. Generally, the ³² protein level, which is normalized to the '-subunit of RNA polymerase, rapidly increased 5 min after induction with an almost 7.4-fold change and then stayed at a high level for 10 min (8.2-fold) before it gradually decreased (Fig. 1B).

View larger version (51K): [in this window] [in a new window]   FIG. 1. 32 and 70 protein level changes before and after 32 induction as measured by quantitative Western blot analysis. The - and '-subunits of core RNA polymerase served as internal controls. A, the - and '-subunits of core RNA polymerase are relatively constant across the time points. 70 keeps increasing after induction and gradually reaches a maximum expression level after 30 min, whereas the maximum detected 32 protein level appears around 15 min after induction and gradually decreases. B shows the fold changes of two factors after being normalized to signal values of the core RNA polymerase subunits. Signal intensities are determined using ImageQuant version 5.2 software. Error bars represent standard deviation in three different experiments.

The more significant increase (fold change) of ³² at the 5-min time point, compared with ⁷⁰ induction level, was due to the fact that the experiment was performed at log-phase (A₆₀₀ = 0.2) in minimum medium, in which ⁷⁰ is the dominant factor and has a much higher protein level than ³² before induction. Thus, although the two factors are under the same P_Ltet promoter control, the fold change of ³² was much higher because of its lower initial protein level.

Known ³²-dependent Genes Are Induced after ³² Overexpression—To characterize the effect of the increasing ³² protein level in vivo on gene expression, global RNA transcript abundance was monitored at 5, 10, and 15 min after ³² induction with cells grown in log-phase (A₆₀₀ = 0.2) in MOPS minimal medium at 37 °C. Transcriptional profiles were obtained as described under "Experimental Procedures." The sample at time 0 was used as the reference to identify genes whose transcript abundance had significantly changed after ³² overexpression.

DNA microarray results showed most of the well characterized genes belonging to the ³² regulon were induced following ³² overexpression. Several known ³²-dependent genes (such as rpoD, a ³²-dependent gene, whose transcriptional level increased 1.9-fold after 5 min of induction) were not included in our data set because of our cut-off level (2-fold increase). In Table I, we show some known ³²-dependent genes that were up-regulated at least 2-fold in 5 min, and we also list the transcriptional levels of these genes at 10 and 15 min. Most of those genes were initially identified in heat shock stress and can be divided into three functional groups as shown in Table I as follows: 1) adaptation (heat shock-related, atypical); 2) proteases (degradation of proteins/peptides); 3) chaperones.

View this table: [in this window] [in a new window]   TABLE I Transcriptional levels of most known 32-dependent genes are upregulated

A number of heat shock protein chaperones were also involved in degrading abnormal proteins (27, 28). Among the induced chaperone proteins, the DnaK/DnaJ/GrpE chaperone team was involved in the folding of nascent chains and played a significant role in cellular folding reactions (31–35). A similar function can be found in the GroEL and GroES chaperone team (31, 36). The transcriptional level of these five genes (dnaK, dnaJ, grpE, groEL, and groES) increased 4.8-, 2.3-, 10.5-, 7.6-, and 4.8-fold, respectively, 5 min after induction. The potential role of chaperones to promote ³² degradation is that chaperones can compete with RNAP to bind ³² and then make ³² unstable and more easily degraded by the protease machinery (27, 28).

New Candidate Genes for ³² Regulon—Expression profiling of transcripts corresponding to the complete set of ORFs in E. coli genome revealed that the response to induced ³² levels in vivo was quite broad. As a result of simple mass action, an increase in the level of ³² relative to the other factors should lead to an increase in the expression of genes in the ³² regulon due to the increase of the corresponding ³² holoenzyme. In addition to identifying known ³²-dependent genes, our microarray data also allowed us to assign many additional new candidate genes to the ³² regulon. There are 129 (3.0% of genome), 116 (2.7% of genome), and 51 (1.2% of genome) genes up-regulated 2-fold or more at 5, 10, and 15 min after induction, respectively. In this paper, we show in Table II a group of genes whose transcriptional level increases more than 4-fold at 5 min and keeps at a high level (more than 2-fold) at 10 min.

View this table: [in this window] [in a new window]   TABLE II New candidate genes for the 32 regulon

View larger version (27K): [in this window] [in a new window]   FIG. 2. Evidence indicating potential new transcriptional start sites in three previously predicted operons. Transcription profiling in both 32 overexpression and heat shock assays shows that the transcription level of second genes (macB, yceP, and ybbN) in the respective operons has been highly induced, whereas the transcription level of first genes (macA, dinl, and ybbO, respectively) in the same operons exhibits no change or a slight decrease. This indicates that new transcription start sites maybe exist just upstream of macB, yceP, and ybbN. The x axis indicated different experiments. Solid arrows represent previously predicted transcription start sites, and dashed arrows represent potential new transcription start sites.

Native gel shift experiments were performed to test the binding of purified ³² holoenzyme to the promoter regions of these genes. The upstream sequence of the fliL gene that contributed to flagella biosynthesis function was chosen as a negative control for the gel shift assay because transcription of this gene was regulated by ⁷⁰ and ^F and was not ³²-dependent (39). In our ³² overexpression microarray data, the transcriptional level of this gene (fliL) was down-regulated 2.6-fold at 5 min after induction.

Binding of each promoter region by ³²-associated holoenzyme was examined at three different molar ratios (1:0, 1:2.5, and 1:5) of core RNA polymerase to ³² protein. EMSA results (Fig. 3C) showed that the DNA fragment generated from the upstream DNA sequences of these five up-regulated genes can be shifted by ³² holoenzyme. Although yecP is the most up-regulated among the five genes as indicated by the microarray data, its transcript abundance was lower than ldhA and almost the same as that of other genes. Therefore, we were not surprised that its relative promoter binding preferences were not the most efficiently bound by holoenzyme as determined by EMSA. The fliL promoter region showed no binding, suggesting that its down-regulation, as mentioned above, was not due to negative control by E³² binding but was more likely to competition of s for core binding in vivo. We have observed that many of ^F-dependent genes were down-regulated upon ³² induction (data not shown).

View larger version (72K): [in this window] [in a new window]   FIG. 3. Electrophoretic mobility shift assays to test the binding of 32 holoenzyme to DNA fragments carrying putative promoter elements. A, SDS-polyacrylamide gel show purified core RNA polymerase and 32 as well as MultiMark molecular weight standard. B, potential 32 consensus binding sites of each gene are predicted and aligned. C, native gel shift assays are performed at three different molar ratios (1:0, 1:2.5, and 1:5) of core enzyme to 32 protein with each DNA sample. The upstream sequence of fliL served as a negative control.

Gene Expression Patterns as a Function of Time after ³² Induction—One of the interesting observations in this time course microarray analysis was that the global changes in gene expression upon ³² increase in vivo were quite transient. The consistent pattern is as follows: the ³² regulon was rapidly induced in response to the ³² protein level increase with RNA levels increasing by 5 min and generally declining 10 min after induction (Fig. 4). The maximum number of up-regulated genes was found 5 min after induction, and signal intensities of the genes that represent their transcriptional level were highest at this same time point. A slight decrease in both the number and the transcriptional level of the up-regulated genes occurred by 10 min. By 15 min after induction, a significant decrease of the number of up-regulated genes occurred (Fig. 4A), and the transcriptional levels of those genes up-regulated at 5 min became low or almost returned to preinduction levels (Fig. 4B).

View larger version (35K): [in this window] [in a new window]   FIG. 4. Temporal changes of the number of up-regulated genes and their transcript abundance across time points. A, the table shows the numbers of up-regulated genes (at least 2-fold) in different function groups. B, transcriptional abundance changes of the genes in relevant function groups. The y axis is log2 intensity that represents the transcriptional level, and the x axis is different time points (0, 5, 10, and 15 min) after induction. C, dynamic changes of total 32 protein level, soluble 32 protein level, and the number of up-regulated genes after induction. Comparative analysis showed that transcription of 32-dependent genes does not strictly parallel 32 level.

One possible reason is that more of the ³² was present in inclusion bodies at 10 and 15 min than at 5 min after induction. Therefore, although we might have detected the total ³² increase in whole cell lysates at the 10- and 15-min time points by using the specific mAb, the ³² in inclusion bodies would not functionally bind to core RNA polymerase to form holoenzyme and then transcribe ³²-dependent genes. To test this possibility, instead of measuring the total ³² in whole cell lysates, we performed experiments to measure soluble ³² protein levels before and after induction. Results showed the soluble ³² still remained at a high level 10 and 15 min after induction, and the overall trend of increased soluble ³² was similar to that of the increased total ³² we measured before (Fig. 4C). This result suggested that although inclusion body production was common in protein overexpression (usually the induction time is 3 or 4 h), most overexpressed ³² observed here was soluble and did not reach the threshold of ³² aggregation in that short time period (0–20 min). Therefore, transcription of ³²-dependent genes rapidly decreased as a result of the decrease in ³² activity rather than in ³² level or solubility.

DnaK Is Responsible for Inactivating ³² in Vivo—Inactivation and degradation of ³² under conditions of excess ³² regulon expression as shown in our assay suggest that ³² can be feedback-regulated by genes in its regulon. The possible ³²-dependent gene expression that was involved in inactivation of ³² might be chaperones, particularly the DnaK-DnaJ chaperones. Physical interaction (binding) between ³² and DnaK is well documented, both in crude lysates and in a purified system (43, 44). To test the function of DnaK in our ³² overexpression system, we made a dnaK in-frame deletion strain, where the chromosomal position from 12,93 to 14,049 in the DnaK coding region has been deleted, following the description of Datsenko and Wanner (45 and see Ref. 46). A ³² overexpression experiment like that performed earlier in this paper was performed in this DnaK strain. Instead of using a microarray approach, we used a real time RT-PCR assay to measure the transcriptional level changes of two well known ³²-dependent genes (lon and grpE) as described below. Results showed that the decrease of the transcriptional level of these two ³²-dependent genes was diminished and more parallel to the decrease of ³² protein level in the DnaK strain (Fig. 5), indicating DnaK contributed to inactivation of ³² and caused a decrease of ³²-dependent gene transcription in our assay.

View larger version (25K): [in this window] [in a new window]   FIG. 5. Temporal changes of the 32 protein and transcript abundance of two 32-dependent genes in wild type and DnaK strain across time points. The induced 32 protein level is slightly higher in the DnaK strain than in the wild type, and the temporal decrease of the transcriptional level of lon and grpE is reduced in the DnaK strain.

View larger version (16K): [in this window] [in a new window]   FIG. 6. Comparison of gene expression levels measured by microarray and RT-PCR approaches. Gene expression level measured by RT-PCR from 32 overexpression samples at different time points is plotted against corresponding microarray data value.

Computer Prediction of ³²-related Promoter Elements—A computer program was used to examine the upstream DNA sequence of up-regulated genes in our microarray data to look for regulatory sequence motifs. As prokaryotic promoter motifs often occur in two blocks with a gap of variable length, BioProspector (41), a C program that is capable of modeling motifs with two blocks and uses a Gibbs sampling strategy, was used to find the –10 and –35 consensus regions for ³² binding. Upstream sequences (300 bases from the first genes in transcription units that contained 2-fold up-regulated genes in our microarray data) were extracted as input sequences. A number of the overall highest scoring motifs as position-specific probability matrices were reported. According to the reported highest scoring motif and its site locations on the input sequence, a graphical display of the results was generated using SEQUENCE LOGO (47) (Fig. 7). The resulting consensus was represented as a ggcTTGa (N)_12–20cCCCAT, where lowercase letters indicate a less highly conserved site. Higher sequence conservation was observed in the –10 region. This consensus agreed well with the previously reported E³² consensus that was aligned to maximize alignment (CTTGAA(N)_13–¹⁷CCCCATNT) in the –35 and –10 regions of several published E³² promoters (3, 27, 28, 48).

View larger version (17K): [in this window] [in a new window]   FIG. 7. Determination of the 32 consensus binding site. 32-related two-block promoter element is aligned using Bioprospector (41) from the upstream sequence of up-regulated genes in 32 overexpression data and displayed using SEQUENCE LOGO (47). The height of each column reflects the nonrandom bias of particular residues at that position, and the size of each residue letter reflects its frequency at that position.

View larger version (18K): [in this window] [in a new window]   FIG. 8. Comparison of the number of up-regulated genes in heat shock experiment and in 32 overexpression experiment. The Venn diagram shows the 32 regulon is overlapping but not identical to the heat shock stimulon. Boxed values represent fold increase of the four s at 5 or 10 min after 32 induction or 10 min after heat shock. The total number of regulated genes in each experiment is in parentheses.

	DISCUSSION

TOP ABSTRACT INTRODUCTION EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

Through studies on E. coli and many other organisms, it has become clear that a major means of gene regulation occurs at the level of transcription initiation. Transcription initiation is regulated by factors, and the first step of the transcription initiation pathway is the binding of a factor to core RNA polymerase to form a holoenzyme complex that then binds to a specific set of promoters and initiates transcription. The binding of the different factors to core RNA polymerase ultimately results in the expression of a set of genes or a regulon. As a result of simple mass action, an increase in the level of ³² relative to the other factors would result in an increase in the level of the corresponding ³² holoenzyme. This would lead to an increase in the expression of the ³² regulon.

Compared with heat shock experiments in which several other factors are also induced in vivo, our system has the advantage of reducing the up-regulation of genes controlled by other factors and allowing specific study the ³² regulon. By using our specific monoclonal antibodies for different factors, we tested ⁷⁰, ^S, ^E, and ⁵⁴ protein level changes as a function of time in our ³² overexpression experiments, and we found there are no significant changes of these factors in our assays (data not shown). We also examined the expression of several well known genes that are under the direct control of six other factors. The transcriptional level of these genes showed either no change or decreased in our ³² overexpression microarray data. Taken together, these results make us confident that the group of up-regulated genes in our experiment is predominantly due to the increased ³² in vivo.

Another advantage of our approach for studying the ³² regulon is its relatively higher induced ³² protein level. Under the control of strong P_Ltet promoter, the induced ³² protein level in our assay is higher than the ³² level caused by the temperature upshift in previous heat shock experiments. The higher level of ³² in our assay will turn on a group of genes that have a weak ³²-dependent promoter to detectable levels. When compared with the sample at time 0 as reference, the significant changes of genes in this group will be detected in our data but missed in previous heat shock studies due to no or a low transcriptional level of those genes. Therefore, we think our approach provides a "purer" and more complete set (if not all) of genes in the ³² regulon.

We have also utilized a new method of quantitative Western blotting (19) to measure the intracellular protein levels of factors. Measuring both the protein level of ³² and the transcriptional levels of ³²-controlled genes as a function of time provides valuable information for exploring the complex network regulated by ³² and gives us an insight into how the ³² protein level regulates the transcriptional level of ³²-controlled genes in vivo. Our results showed that although the ³² protein level remained at a high level 10 and 15 min after induction, the numbers of induced genes and the transcriptional level of ³²-controlled genes were significantly down-regulated at these same time points (Fig. 4), i.e. the decrease in the transcriptional level of ³²-dependent genes occurs earlier than the decrease in full-length ³².

In heat shock response, the induced synthesis of ³² usually takes place in 5 min and then declines to a new steady-state level, 2–3-fold higher than the pre-shift level (57). Meanwhile, a group of heat shock proteins decreases as well after their initial increase (57). The decrease of the ³² protein and the heat shock proteins virtually takes place at the same time. Therefore, the amount of ³² in the cell was believed to be one of the key regulatory elements in the heat shock response (57).

The activity control of ³² that is involved in regulation of a limited number of HSPs was found in cold shock experiments (58) and in mutants lacking FstH function (59). Instead of measuring the synthesis of several heat shock proteins at the translational level as carried out in these early studies, we measured the global transcriptional level change that better represents the level of active ³² in vivo by microarray assays. The transcriptional levels of several genes have been confirmed by real time PCR. Results clearly showed that, whereas the increased amount of ³² largely accounts for initial induction of ³² regulon, the constitutive production of ³² from our overexpression system does not maintain the activation of ³² regulon in later time points. This indicates that the decrease in ³² activity rather than in the ³² level or solubility is responsible for the rapid shutoff of the transcription of ³²-dependent genes in our assays. In addition, we measured the soluble ³² level to eliminate the explanation that the decrease in ³² activity was due to insolubilities.

The DnaK-DnaJ-GrpE chaperone team is involved in ³² degradation in vivo (60, 61), as mutations in each of the corresponding genes decrease the rate of ³² degradation (58). Tomoyasu and co-workers (59, 62) found a small increase (1.5-fold) in the DnaK-DnaJ level reduced the level and activity of ³² and caused faster shutoff of heat shock response, whereas a small decrease in the chaperone level caused inverse effects. The loss of the DnaK function leads to markedly impaired down-regulation of the transcriptional level ³²-dependent genes in our assay. This indicates that DnaK is a factor (or at least one of multiple factors) that is involved in inactivating ³² in vivo. However, the particular role played by DnaK or other factor(s) in promoting inactivation is not clear. A possible mechanism is that DnaK and core RNAP appear to compete with each other in binding to ³² at specific region(s) (28, 63, 64). The DnaK binding leads to ³² inactivation, whereas the RNAP binding stabilizes ³². From our in vitro studies that compare all seven purified E. coli -subunits binding affinities to the core RNA polymerase, we found ³² has highest binding affinity to core RNA polymerase among seven known factors in E. coli.⁴ Although the present study clearly reveals that the increased level of the ³² regulon expression exerts a negative feedback regulation on the intracellular protein level and activity of ³² and that DnaK is a factor involved in this process, more work needs to be done. We will explore whether DnaK or other factor(s) can only associate with free ³² and then prevent its formation of functional holoenzyme with core or whether they can bind to and remove ³² from a tightly bound RNAP-³² complex by using a luminescence resonance energy transfer-based homogeneous binding assay (65).

	FOOTNOTES