Characterization of the Staphylococcus aureus Heat Shock, Cold Shock, Stringent, and SOS Responses and Their Effects on Log-Phase mRNA Turnover

Kelsi L Anderson; Corbette Roberts; Terrence Disz; Veronika Vonstein; Kaitlyn Hwang; Ross Overbeek; Patrick D Olson; Steven J Projan; Paul M Dunman

doi:10.1128/JB.00609-06

. 2006 Oct;188(19):6739–6756. doi: 10.1128/JB.00609-06

Characterization of the Staphylococcus aureus Heat Shock, Cold Shock, Stringent, and SOS Responses and Their Effects on Log-Phase mRNA Turnover^†

Kelsi L Anderson ¹, Corbette Roberts ¹, Terrence Disz ², Veronika Vonstein ³, Kaitlyn Hwang ^2,4, Ross Overbeek ³, Patrick D Olson ¹, Steven J Projan ⁵, Paul M Dunman ^1,^*

PMCID: PMC1595530 PMID: 16980476

Abstract

Despite its being a leading cause of nosocomal and community-acquired infections, surprisingly little is known about Staphylococcus aureus stress responses. In the current study, Affymetrix S. aureus GeneChips were used to define transcriptome changes in response to cold shock, heat shock, stringent, and SOS response-inducing conditions. Additionally, the RNA turnover properties of each response were measured. Each stress response induced distinct biological processes, subsets of virulence factors, and antibiotic determinants. The results were validated by real-time PCR and stress-mediated changes in antimicrobial agent susceptibility. Collectively, many S. aureus stress-responsive functions are conserved across bacteria, whereas others are unique to the organism. Sets of small stable RNA molecules with no open reading frames were also components of each response. Induction of the stringent, cold shock, and heat shock responses dramatically stabilized most mRNA species. Correlations between mRNA turnover properties and transcript titers suggest that S. aureus stress response-dependent alterations in transcript abundances can, in part, be attributed to alterations in RNA stability. This phenomenon was not observed within SOS-responsive cells.

Staphylococcus aureus is a leading cause of nosocomial and community-acquired infections. The organism owes its ability to cause disease, in part, to the production of a repertoire of virulence factors that modulate its ability to colonize host/inert surfaces, thwart host defenses, and disseminate to satellite sites (6, 39). Another facet of S. aureus pathogenesis is the organism's ability to maintain cellular homeostasis while enduring environmental challenges, such as changes in host cell core temperature or exposure to phagocyte-mediated reactive oxygen species (58). Although considerable progress has been made in defining S. aureus virulence factors and their regulatory networks, surprisingly little is known about the organism's ability to cope with environmental stresses.

Studies from Escherichia coli and, to a lesser extent, Bacillus subtilis indicate that bacteria have developed highly orchestrated responses to environmental stresses, which when elicited alter the organism's cellular physiology in a manner that enhances survival. For instance, DNA-damaging agents trigger induction (derepression) of the SOS response (reviewed in reference 16). Components of the SOS response increase the cell's capacity to inhibit cell division, repair DNA damage, and replicate noninstructive DNA lesions in an error-prone manner. Bacteria cope with conditions of nutrient limitation by eliciting the stringent response, which both reduces the cellular protein synthesis capacity and increases amino acid biosynthesis when substrates for protein synthesis are lacking (42, 52). Products of the cold shock response restore translation apparatus function, which is compromised at low temperatures, and resolve low temperature-mediated mRNA secondary structures that would otherwise impede the translation machinery (25, 26). At elevated temperatures, cells express heat shock factors that degrade/restructure heat-denatured proteins as well as factors that restore temperature-mediated alterations in chromosome topology (33, 61). It is currently unclear if S. aureus elicits similar responses and/or has developed novel strategies to cope with DNA damage, starvation, and temperature changes.

Recent studies indicate that bacterial stress responses are not merely controlled at the level of transcript synthesis. Rather, some responses modulate target mRNA stability to influence protein production (reviewed in reference 53). Perhaps the best example of this involves production of the major E. coli cold shock protein, CspA, an RNA structure-resolving protein that accounts for 13% of the total cellular protein at low temperatures (18). Under cold shock conditions, increased cspA mRNA stability, as opposed to changes in transcript synthesis, primarily accounts for the amount of CspA produced (14). Similarly, Klebsiella pneumoniae nitrogen fixation protein production corresponds to regulated mRNA turnover (10, 28, 29). Moreover, in Vibrio angustum, the cellular response to nutrient depravation is regulated by altering mRNA stability (53).

The focus of the current work is to define the members of S. aureus stress responses and their mechanisms of regulation. Doing so may provide a better understanding of the organism's ability to adapt to environmental challenges and provide novel strategies for the therapeutic intervention of bacterial infections. Accordingly, Affymetrix GeneChips were used to define the S. aureus SOS, stringent, cold shock, and heat shock responses and to measure the mRNA turnover properties of each response. The results indicate that each stress response influences the expression of distinct cellular processes, subsets of virulence factors, and antimicrobial resistance determinants. Many stress-responsive biological processes appear to be conserved across bacteria, whereas others are unique to S. aureus. Induction of the S. aureus cold shock, heat shock, and stringent responses caused dramatic global changes in mRNA turnover. This suggests that stress-mediated changes in mRNA abundances can, in part, be attributed to alterations in RNA stability as opposed to or in addition to changes in transcript synthesis. This phenomenon was not observed under SOS response-inducing conditions. Sets of S. aureus small stable RNA (SSR) molecules with no obvious open reading frames were also components of each stress response. Given the importance of SSR-like molecules in other organisms, it is likely that these stable RNA species influence stress-responsive functions (1, 51, 60).

MATERIALS AND METHODS

Bacterial strains.

S. aureus strain UAMS-1 is a well-characterized methicillin-susceptible clinical osteomyelitis isolate (2, 3, 5, 7, 46).

Growth conditions.

Overnight cultures of UAMS-1 cells were diluted 1:100 in 200 ml fresh brain heart infusion (BHI) medium and were incubated at 37°C at 225 rpm with a flask-to-medium-volume ratio of 5:1. Once cultures reached mid-log phase (optical density at 600 nm, 0.25), they were challenged with either mupirocin (60 μg ml⁻¹; AppliChem, Cheshire, CT) or mitomycin C (1 μg ml⁻¹; Sigma-Aldrich, St. Louis, MO) and were subsequently incubated at 37°C for 30 min with aeration for induction of the stringent or SOS response, respectively. For induction of the cold shock and heat shock responses, cultures of UAMS-1 were grown to mid-log phase (as described above) and were subsequently incubated for an additional 30 min with aeration at 10°C and 42°C, respectively. Following induction of each response, rifampin (200 μg ml⁻¹; Sigma-Aldrich) was added to arrest transcription, and 21 ml of cells was removed at 0, 2.5, 5, 15, and 30 min post-rifampin treatment. Twenty milliliters of each aliquot was added to 20 ml ice-cold acetone-ethanol (1:1) and stored at −80°C overnight; 10⁻¹ and 10⁻⁵ dilutions of the remaining 1 ml were plated on BHI-rifampin (200 μg ml⁻¹) agar and BHI agar, respectively. Plates were incubated overnight at 37°C, and viable CFU ml⁻¹ were calculated to ensure that cell proliferation was halted by the addition of rifampin. If rifampin-resistant colonies were detected, the experimental samples were discarded, and the experiment was repeated.

Antibiotic susceptibility assays.

Fifty milliliters of mid-log-phase UAMS-1 cells was either mock treated or challenged with mupirocin (60 μg ml⁻¹) to induce the stringent response (as described above). Next, mock- and mupirocin-treated cultures at time zero (T0) were incubated in the absence or presence of either rifampin (200 μg ml⁻¹) or ciprofloxacin (1.3 μg ml⁻¹, which is the MIC) for an additional 4 h. Cell viability was monitored by determining the total CFU ml⁻¹ at T0 and every hour thereafter. All susceptibility assays were repeated at least twice.

Microarray studies.

Total bacterial RNA was isolated from each sample, labeled, and hybridized to Affymetrix S. aureus GeneChips (Santa Clara, CA) as previously described (46). The S. aureus GeneChips used in this study are the most comprehensive commercially available Affymetrix arrays, representing genomic sequences from S. aureus strains NCTC 8325, COL, N315, and Mu50 as well as intergenic regions. The experiment for each response was repeated twice (biological replicates), and posttranscriptional arrest samples were prepared from each biological replicate. GeneChip signal intensity values for each qualifier at each time point (both pre- and posttranscriptional arrest) were then averaged and normalized to Affymetrix spike-in signals, using GeneSpring 6.2 software (Silicon Genetics, Redwood City, CA). The half-life of each transcript was calculated as the time point at which the T0 signal decreased by a factor of 2, as previously described (46, 49).

Real-time PCR.

Quantitative real-time PCR primers are shown in Table 1. Real time-PCRs were performed as previously described (46). Briefly, 25 ng of total bacterial RNA was reverse transcribed, amplified, and measured using a LightCycler RNA Master SYBR green I kit (Roche Applied Science, Indianapolis, IN) following the manufacturer's recommendations. As an internal control, 25 pg of RNA was used to quantitate rRNA. Transcript concentrations were calculated using LightCycler software, with a LightCycler control cytokine RNA (Roche Applied Science) titration kit as a standard, and were then normalized to the 16S rRNA abundance.

TABLE 1.

Sequences of oligonucleotides used for real-time PCR in this study

Primer	Oligonucleotide sequence (5′→3′)
ilvB-F	ATCGAATATATCGGCAAAATTACAA
ilvB-R	AGCATACGACTGTTTTATCAGGATT
rpsL-F	ACCACAAAAACGTGGTGTATGTACT
rpsL-R	ACACCTGGTAAGTCTTTTACACGTC
recA-F	ATATGGAGAAATCTTTCGGTAAAGG
recA-R	CAGGACCATAAATTTCAATAATTCG
uvrB-F	AATATTCCCAGCCTCTAAAGAAGAA
uvrB-R	CTCATCTCGTAATTCTTTCAATCGT
16SrRNA-F	TAACCTACCTATAAGACTGGGATAA
16SrRNA-R	GCTTTCACATCAGACTTAAAAA
sarR-F	TTAGTCAACGCAACATTTCAAGTTA
sarR-R	GAACTCTGAGCACTTAGCAATCTCT
norA-F	AGTGATTTAGGGTTACTTGTTGCTG
norA-R	CAACTGCAAACATAAATTCTGACAC
clpC-F	AGTAGACGTACGAAAAACAATCCTG
clpC-R	GTTGGATTTCTTCCATAACCTTTTT
ctsR-F	ATTTGAAGAGTCGAATGAAGATGTC
ctsR-R	AATTTTAGTGATTCGGATGTAACCA
srtA-F	CTTATCCTAGTGGCAGCATATTTGT
srtA-R	GATTTATCTTTCGGAATTTGAGGTT
COLSA2731-F	AACGGTACAGTAAAATGGTTTAACG
COLSA2731-F	AGTTTGTACGTTAACTGCTTGGTCT

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RESULTS

Cold shock response.

To characterize the ability of S. aureus to adapt to changes in temperature, we first identified members of the organism's cold shock response. Accordingly, S. aureus strain UAMS-1 was grown at 37°C to the mid-log phase of growth, at which point cell cultures were incubated at 10°C for an additional 30 min to induce the cold shock response. Affymetrix S. aureus GeneChips were used to compare the transcript titers of cold-shocked and unshocked cells (grown at 37°C).

The cold shock condition studied did not appreciably affect cell viability (data not shown) but did increase the mRNA titers of 46 genes (Table 2). Transcription of the cold shock gene cspB was induced 9.3-fold at the lower temperature, confirming that the conditions used were appropriate for studying the S. aureus cold shock response. Transcription of the cold shock gene cspA was also upregulated 2.0-fold, but this was not considered significant by the t test (P ≤ 0.05). This correlates with E. coli cspA expression; cspA is strongly induced at 25°C but is marginally upregulated (at the transcriptional level) at a lower temperature (15°C) (57). The majority of cold shock-induced transcripts (36%) included hypothetical or conserved hypothetical genes; the latter are conserved within all publicly available sequenced S. aureus genomes. Two members of the cid regulon, lrgA and lrgB, which are believed to counteract the cell's programmed cell death machinery, were induced (23), as were four competence orthologs (SACOL0813, SACOL0814, SACOL1601, and SACOL1644). Several virulence determinants were induced during cold shock conditions, including two pathogenicity island genes (SACOL0901 and SACOL0902), an enterotoxin gene (seo), a lipase gene (lip), and a sortase gene (srtA). Two putative antimicrobial resistance determinants, mepA (27) and a beta-lactamase-like gene (yycJ), were induced by cold shock. The SOS repressor LexA (59) and a general stress-inducible protein (SACOL0958) that is predicted to bind mRNA were also upregulated at the low temperature. Real-time PCR confirmed that srtA and cspB transcripts were induced 2.2- and >1,000-fold, respectively, by cold shock conditions (data not shown). A total of 416 transcript titers decreased in response to low temperature (see Table S6 in the supplemental material).

TABLE 2.

S. aureus cold shock-induced transcripts

Category and qualifier^a	Fold induction^b	Common name	Locus^c	Description
Amino acid metabolism
sa_c4601s3932_a_at	2.4*	rocF	SA2154	Arginase
Carbohydrates
sa_c8477s7437_at	2.8		SA0869	Phosphoglycerate mutase
Cell division and cell cycle
sa_c1078s861_at	3.3		SA1191	Conserved hypothetical protein
Fatty acids and lipids
sa_c6688s5833_a_at	2.3*	lip	N315-SA2463	Triacylglycerol lipase precursor
sa_c7744s6747_at	2.5		SA0621	Substrate-CoA ligase, putative
Hypothetical
sa_c4550s9974_x_at	2.2		MSSA476-SAS070	Conserved hypothetical protein
sa_c7348s6387_a_at	2.2*		N315-SA0413	Conserved hypothetical protein
sa_c8469s7429_a_at	4.1		N315-SA0751	Conserved hypothetical protein
sa_c9785s10434_at	3.3*		N315-SA1186	Conserved hypothetical protein
sa_c6821s5955_a_at	15.9*		N315-SA2496	Conserved hypothetical protein
sa_c3224s2774_a_at	2.9		SA0161	Conserved hypothetical protein
sa_c6917s6037_a_at	3.4*		SA0299	Hypothetical protein
sa_c7132s6241_a_at	2.9*		SA0436	Conserved hypothetical protein
sa_c7215s6283_a_at	2.4*		SA0448	Conserved hypothetical protein
sa_c7352s6391_a_at	2.8*		SA0497	Conserved hypothetical protein
sa_c7491s6511_at	2.2		SA0537	Conserved hypothetical protein
sa_c8897s7814_a_at	2.1*		SA0692	Conserved hypothetical protein
sa_c485s314_at	28.0*		SA1033	Hypothetical protein
sa_c10045s10498_at	2.8*		SA1372	Hypothetical protein
sa_c1705s1441_a_at	3.6		SA1375	Conserved hypothetical protein
sa_c1960s1685_a_at	2.4		SA1438	Conserved hypothetical protein
sa_c2254s1952_a_at	2.2		SA1524	Conserved hypothetical protein
sa_c2266s1966_a_at	2.1		SA1526	Conserved hypothetical protein
sa_c2807s2375_a_at	2.4*		SA1664	Conserved hypothetical protein
sa_c10133s10545_a_at	2.3*		SA1777	Conserved hypothetical
sa_c4628s3951_a_at	9.2		SA2162	Conserved hypothetical protein
sa_c10213s10636_at	2.1*		SA2218	Conserved hypothetical protein
sa_c6732s5872_a_at	3.5		SA2705	Hypothetical protein
Miscellaneous
sa_c10345s9018_a_at	3.0*		SA0162	NAD-dependent formate dehydrogenase
sa_c6230s5410_at	10.4*	lrgA	SA0247	Holin-like protein
sa_c6266s5446_a_at	4.7*	lrgB	SA0248	Holin-like protein
Regulation
sa_c7020s6143_a_at	4.4		SA0404	Transcriptional regulator, MarR family
sa_c9575s8335_a_at	5.0	lexA	SA1374	LexA repressor
Resistance
sa_c9464s8272_a_at	2.2	yycJ	SA0023	Metallo-beta-lactamase family
sa_c7024s6147_a_at	2.7	mepA	SA0405	MATE efflux family protein
Stress response
sa_c1956s1681_a_at	9.3	cspB	SA2731	Cold shock protein
Transport
sa_c5431s4700_a_at	2.8		SA0882	ABC transporter
sa_c8327s7303_a_at	2.8*		SA0813	Putative ComF protein 1
sa_c8331s7308_a_at	3.9*		SA0814	Competence protein F
sa_c9678s8436_a_at	3.5*		SA1601	Putative competence protein ComGA
sa_c2731s2305_a_at	2.1*		SA1644	Putative competence protein
Virulence
sa_c10522s10973_s_at	2.6	srtA	N315-SA2539	Sortase
sa_c7169s10140_a_at	7.6		SA0901	Pathogenicity island protein
sa_c10151s10571_a_at	2.4		SA0902	Pathogenicity island protein
sa_c3571s9834_a_at	2.2*	seo	SA1648	Enterotoxin SeO

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Affymetrix S. aureus GeneChip descriptive representing indicated predicted open reading frame (ORF).

*, transcript was below the lower limits of sensitivity in unstressed cells and thus the amount of change represents an estimate.

S. aureus strain COL locus, unless otherwise indicated (strain preceeds locus identifier).

Heat shock response.

Next, we identified transcripts that are induced in heat-shocked UAMS-1 cells. To do so, mid-log-phase cells (grown at 37°C) were incubated for 30 min at 42°C to induce the S. aureus heat shock response. The transcript profile of heat-shocked cells was then compared to that of unstressed cells. Induction of the heat shock response did not affect cell viability (data not shown) but did induce the transcription of 98 genes.

As shown in Table 3, three well-characterized heat shock response genes, ctsR, clpB, and clpC, were upregulated 3.1-, 5.0-, and 2.3-fold, respectively, during growth at the elevated temperature, suggesting that the conditions tested are appropriate for studying aspects of the S. aureus heat shock response (12). Among the genes induced by heat shock were a number of putative S. aureus virulence factors, including (i) the alpha-hemolysin gene (hla), (ii) pathogenicity island genes (SACOL0900 and SACOL0901), (iii) an LPXTG motif-containing gene (SACOL2668), and (iv) members of the urease system (ureA-ureG), which are strongly upregulated in S. aureus biofilms (3). Thirty-six hypothetical or conserved hypothetical proteins were induced by heat shock conditions. Eleven cold shock genes were also induced within heat-shocked cells, indicating that they may constitute members of a general temperature-mediated stress response. Included among these were six conserved hypothetical genes, a pathogenicity island gene (SACOL0901), the MarR family regulator gene, and two competence orthologs (SACOL0813 and SACOL0814). Real-time PCR confirmed that clpC and ctsR were upregulated 65- and 95-fold, respectively, under heat shock conditions (data not shown). Forty-two transcripts decreased in response to heat shock conditions (see Table S6 in the supplemental material).

TABLE 3.

S. aureus heat shock-induced transcripts

Category and qualifier^a	Fold induction^b	Common name	Locus^c	Description
Amino acids and derivatives
sa_c7410s6434_a_at	2.0*	gltB	SA0514	Glutamate synthase large subunit
sa_c8813s7749_a_at	2.2		SA0569	Guanido phosphotransferase family protein
sa_c1659s1395_a_at	2.4	hom	SA1362	Homoserine dehydrogenase
sa_c1922s1644_a_at	2.4*	dapA	SA1430	Dihydrodipicolinate synthase
sa_c1928s1652_a_at	2.3*	dapD	SA1432	2,3,4,5-Tetrahydropyridine-2,6-dicarboxylate N-Succinyltransferase
sa_c5019s4319_a_at	2.1*		SA2279	Putative transporter
sa_c5023s4322_at	6.0	ureA	SA2280	Urease, gamma subunit
sa_c5029s4326_a_at	5.2	ureB	SA2281	Urease, beta subunit
sa_c5031s4330_a_at	3.8	ureC	SA2282	Urease, alpha subunit
sa_c5035s4334_at	3.3	ureE	SA2283	Urease accessory protein
sa_c5039s4340_a_at	3.2	ureF	SA2284	Urease accessory protein
sa_c5043s4344_a_at	3.0	ureG	SA2285	Urease accessory protein
sa_c9293s8136_a_at	3.4	ureD	SA2286	Urease accessory protein
sa_c9420s8234_a_at	6.3	betA	SA2627	Choline dehydrogenase
Carbohydrates
sa_c6411s5581_a_at	3.8	bglA	SA0251	6-Phospho-beta-glucosidase
sa_c2458s2040_a_at	2.2*	malA	SA1551	Alpha-glucosidase
sa_c4699s4019_a_at	2.7*	lacG	SA2180	6-Phospho-beta-galactosidase
sa_c4703s4023_a_at	7.0*	lacD	SA2183	Tagatose 1,6-diphosphate aldolase
sa_c4709s4027_a_at	3.6*	lacC	SA2184	Tagatose-6-phosphate kinase
sa_c4711s4031_a_at	4.5*	lacB	SA2185	Galactose-6-phosphate isomerase
sa_c4715s4037_at	5.9*	lacA	SA2186	Galactose-6-phosphate isomerase
sa_c6417s5584_a_at	6.4	betB	SA2628	Betaine aldehyde dehydrogenase
Cell wall and capsule
sa_c6381s5549_a_at	4.6		SA0250	PTS system, IIA component
sa_c1330s1105_a_at	3.5*	lytN	SA1264	Cell wall hydrolase
sa_c9866s8605_at	2.7		SA1932	Transglycosylase domain protein
Cofactors
sa_c3380s9339_a_at	2.4	ribH	SA1817	Riboflavin synthase, beta subunit
sa_c3391s2919_a_at	2.9	ribE	SA1819	Riboflavin synthase, alpha subunit
sa_c3395s2925_a_at	2.4	ribD	SA1820	Riboflavin biosynthesis protein
DNA metabolism
sa_c963s754_a_at	2.3	uvrC	SA1157	Excinuclease C subunit
Hypothetical
sa_c2938s2500_at	5.0		MW2-MW1600	Conserved hypothetical protein
sa_c4558s9982_x_at	3.0		MW2-MW2077	Conserved hypothetical protein
sa_c10133s10545_a_at	2.0*		N315-SA1777	Conserved hypothetical
sa_c7157s10125_a_at	9.8*		N315-SA1832	Conserved hypothetical protein
sa_c6011s10068_at	2.3*		N315-SA2299	Conserved hypothetical protein
sa_c7036s9080_a_at	2.8		N315-SA0326	Conserved hypothetical protein
sa_c7819s6819_a_at	4.5		N315-SA0551	Conserved mercuric reductase homologus
sa_c7161s10131_at	2.8*		N315-SA1829	Conserved hypothetical protein
sa_c3224s2774_a_at	5.6		SA0161	Conserved hypothetical protein
sa_c4120s3473_a_at	3.7*		SA0191	M23/M37 peptidase domain protein
sa_c4917s4223_a_at	4.3*		SA0215	Putative propionate CoA-transferase
sa_c6449s5616_a_at	3.2		SA0252	Conserved hypothetical protein
sa_c9259s8103_a_at	2.2		SA0255	Putative membrane protein
sa_c6700s5841_a_at	2.8		SA0259	Hypothetical protein
sa_c6967s6091_a_at	2.5		SA0314	Conserved hypothetical protein
sa_c7132s6241_a_at	3.3*		SA0436	Conserved hypothetical protein
sa_c7571s6589_a_at	2.6		SA0568	Conserved hypothetical protein
sa_c7760s6763_at	15.1		SA0625	Conserved hypothetical protein
sa_c7821s6823_a_at	6.3*		SA0641	Conserved hypothetical protein
sa_c8331s7308_a_at	4.6*		SA0814	Competence protein F
sa_c485s314_at	16.7*		SA1033	Hypothetical protein
sa_c582s408_a_at	2.6		SA1059	Conserved hypothetical protein
sa_c1071s9138_a_at	4.2		SA1189	Putative acetyltransferase
sa_c1618s1361_a_at	3.7*		SA1349	Conserved hypothetical protein
sa_c1705s1441_a_at	3.7		SA1375	Conserved hypothetical protein
sa_c1960s1685_a_at	5.0		SA1438	Conserved hypothetical protein
sa_c2432s2017_a_at	2.4		SA1539	Conserved hypothetical protein
sa_c2942s2505_a_at	8.7		SA1705	Hypothetical protein
sa_c3692s3173_at	2.5		SA1927	Conserved hypothetical protein
sa_c9309s8152_at	3.2		SA2315	Conserved hypothetical protein
sa_c6395s5566_a_at	3.2		SA2401	Conserved hypothetical protein
sa_c5614s4868_a_at	2.5*		SA2404	Conserved hypothetical protein
sa_c5616s4872_a_at	3.1*		SA2405	Conserved hypothetical protein
sa_c9344s8176_a_at	3.3		SA2436	Conserved hypothetical protein
sa_c6112s5297_a_at	2.0		SA2551	Conserved hypothetical protein
sa_c6206s5387_a_at	28.2*		SA2571	Conserved hypothetical protein
Miscellaneous
sa_c4301s3654_a_at	3.3	kdpD	SA2070	Sensor histidine kinase
sa_c6058s5252_a_at	2.1		SA2533	Glyoxalase family protein
sa_c9434s8247_a_at	2.2		SA2667	Isochorismatase family protein
Nucleosides and nucleotides
sa_c1898s1619_a_at	4.5*	deoD	SA0121	Purine nucleoside phosphorylase
sa_c1167s950_a_at	2.3	pyrF	SA1216	Orotidine 5-phosphate decarboxylase
Protein metabolism
sa_c3341s2876_a_at	2.0		SA0164	Gramicidin S synthetase 2-related protein
sa_c256s9573_s_at	2.3	clpC	SA0570	ATP-dependent protease
sa_c8966s7880_a_at	2.6		SA0815	Ribosomal subunit interface protein
sa_c278s123_a_at	5.0	clpB	SA0979	ATP-dependent protease
Regulation
sa_c9074s7960_a_at	14.5*		N315-SA0882	Similar to competence transcription factor
sa_c6190s5368_a_at	2.4		N315-SA2340	Putative transcriptional regulator, TetR family
sa_c7020s6143_a_at	2.6		SA0404	Transcriptional regulator, MarR family
sa_c7405s6429_a_at	3.2*	gltC	SA0513	Transcriptional regulator
sa_c8807s7748_a_at	3.1	ctsR	SA0567	Transcriptional regulator
sa_c4305s3658_at	2.4*	kdpE	SA2071	DNA-binding response regulator
sa_c9305s8148_a_at	2.9		SA2304	Conserved regulatory domain protein
sa_c5496s4759_a_at	2.6		SA2374	Putative transcriptional regulator, TetR family
Resistance
sa_c1968s1693_a_at	2.2	tetR	SA0122	Tetracycline resistance
Transport
sa_c5355s4632_a_at	2.8	opuCA	N315-SA2237	Glycine betaine/carnitine/choline ABC transporter
sa_c3997s3420_a_at	2.4		SA0184	Peptide ABC transporter
sa_c8327s7303_a_at	3.6*		SA0813	Putative ComF protein 1
sa_c3603s3083_a_at	2.4		SA1897	Putative protein export protein
sa_c9938s8633_a_at	3.3*	lacE	SA2181	PTS system, lactose-specific IIB components
sa_c9939s8637_a_at	3.4*	lacF	SA2182	PTS system, lactose-specific IIA component transporter CorA family
sa_c5500s4763_a_at	2.2		SA2375
sa_c5773s5016_at	2.0		SA2450	ABC transporter
Virulence
sa_c10620s11074_a_at	4.5*		N315-SA0895	Pathogenicity island protein
sa_c10156s10581_at	20.8*		N315-SA1833	SaPI pathogenicity island protein
sa_c7165s10136_a_at	3.1*		SA0900	Pathogenicity island protein
sa_c7169s10140_a_at	4.2		SA0901	Pathogenicity island protein
sa_c1023s810_a_at	3.4*	hla	SA1173	Alpha-hemolysin precursor
sa_c1334s1109_a_at	2.6*	eprH	SA1265	Endopeptidase resistance
sa_c6575s5743_a_at	2.8		SA2668	LPXTG cell wall surface anchor family protein

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Affymetrix S. aureus GeneChip descriptive representing indicated predicted ORF.

*, transcript was below the lower limits of sensitivity in unstressed cells, and thus the amount of change represents an estimate.

S. aureus strain COL locus, unless otherwise indicated (strain preceeds locus identifier).

Stringent response.

Mupirocin is an antimicrobial agent that induces the staphylococcal stringent response by inhibiting isoleucyl tRNA synthetase, thereby increasing the cellular concentration of uncharged tRNA^Ile molecules (8, 11). Using real-time PCR, we determined that 30 min of mupirocin treatment (60 μg ml⁻¹) increased the transcript titers of the stringent response control factor relA and the ilv operon (3- and >1,000-fold, respectively), whereas rpsL transcript levels were decreased (5-fold); cell viability was marginally affected (data not shown). These results mimic the transcription profile for mupirocin-mediated E. coli stringent response induction and were the same conditions used by Crosse and colleagues to induce the stringent response in S. aureus strain 8325-4 (11, 47). Lower mupirocin concentrations did not appreciably alter the transcript titers of relA, ilvA, and rpsL, whereas higher concentrations increased toxicity.

Mupirocin treatment induced 248 open reading frame transcripts (Table 4). As expected, the stringent response element relA was upregulated (2.4-fold). Likewise, members of the ilv (ilvA-ilvD and ilvN), leu (leuA-leuD), and thr (thrB and thrC) operons were strongly upregulated by mupirocin challenge (30- to 157.1-fold); all have been shown to be responsive to isoleucyl tRNA limitation (47). Collectively, these results suggest that the conditions used were appropriate for studying components of the S. aureus stringent response. Eliciting the stringent response induced several classes of gene products, including (i) 37 transport proteins, (ii) 10 previously characterized virulence factors, (iii) 18 regulatory molecules, and (iv) 10 peptidases. The last class is a hallmark of the stringent response (22). Among the elevated transport proteins were three putative drug efflux pumps, i.e., NorA (10.1-fold), MepA (5-fold), and an EmrB/QacA-like protein encoded by the SACOL2413 gene (36, 64). Two loci, encoding a set of putative ABC transporter proteins (SACOL0504 to SACOL0506; average induction, 124-fold) and a set of oligopeptide transporter proteins (SACOL0991 to SACOL0995; average induction, 73-fold), were among the most dramatically upregulated transcripts in mupirocin-challenged cells. The virulence determinants of the stringent response included autolysin (alt), fibrinogen binding protein (fbp), sortase A (srtA), components of the intracellular adhesion locus (icaA and icaB), and extracellular proteases (sspA-sspC). Among the transcription factors that were upregulated were three well-characterized virulence factor regulators, i.e., sarR (3.2-fold), sarZ (8.7-fold), and a component of the agr locus (agrA; 3.1-fold). Real-time PCR demonstrated that the norA mRNA titer was induced 36.2-fold following induction of the stringent response (data not shown). A total of 814 transcripts decreased in abundance under stringent conditions (see Table S6 in the supplemental material).

TABLE 4.

S. aureus stringent response-induced transcripts

Category and qualifier^a	Fold induction^b	Common name	Locus^c	Description
Amino acid metabolism
sa_c2576s2153_a_at	2.4	aroK	SA1596	Shikimate kinase
sa_c1918s1640_a_at	75.1*	asd	SA1429	Aspartate-semialdehyde dehydrogenase
sa_c1922s1644_a_at	87.1*	dapA	SA1430	Dihydrodipicolinate synthase
sa_c1924s1648_a_at	57.6*	dapB	SA1431	Dihydrodipicolinate reductase
sa_c1928s1652_a_at	32.7*	dapD	SA1432	2,3,4,5-Tetrahydropyridine-2,6-dicarboxylate N-succinyltransferase
sa_c2572s2149_a_at	2.5	gcvT	SA1595	Glycine cleavage system T protein
sa_c7410s6434_a_at	29.6*	gltB	SA0514	Glutamate synthase large subunit
sa_c7412s6438_a_at	15.6	gltD	SA0515	Glutamate synthase small subunit
sa_c8240s7220_a_at	7.1	hisC	SA0784	Histidinol-phosphate aminotransferase
sa_c6724s5865_a_at	4.1*	hisG	SA2703	ATP phosphoribosyltransferase
sa_c1659s1395_a_at	28.9	hom	SA1362	Homoserine dehydrogenase
sa_c4243s3594_a_at	48.2*	ilvA	SA2050	Threonine dehydratase
sa_c4213s3565_a_at	142.1*	ilvB	SA2043	Acetolactate synthase large subunit
sa_c9931s8627_a_at	156.7*	ilvC	SA2045	Ketol-acid reductoisomerase
sa_c4209s3561_a_at	131.9*	ilvD	SA2042	Dihydroxy-acid dehydratase
sa_c4217s3569_at	153.6*	ilvN	SA2044	Acetolactate synthase small subunit
sa_c4223s3575_a_at	157.1*	leuA	SA2046	2-Isopropylmalate synthase
sa_c4225s3576_a_at	100.8*	leuB	SA2047	3-Isopropylmalate dehydrogenase
sa_c4229s3580_a_at	80.0*	leuC	SA2048	3-Isopropylmalate dehydratase large subunit
sa_c4239s3588_a_at	71.1*	leuD	SA2049	3-Isopropylmalate dehydratase small subunit
sa_c1940s1663_at	3.5	lysA	SA1435	Diaminopimelate decarboxylase
sa_c1912s1635_a_at	67.6*	lysC	SA1428	Aspartokinase alpha and beta subunits
sa_c10721s11169cv_s_at	2.8	metB	N315-SA0419	Cystathionine gamma-synthase
sa_c9702s8459_a_at	3.6	proC	SA1546	Pyrroline-5-carboxylate reductase
sa_c3376s2908_a_at	3.9*	putA	SA1816	Proline dehydrogenase
sa_c3548s3054_a_at	3.9*	rocD	SA0170	Ornithine aminotransferase
sa_c3204s2753_a_at	19.4*	serA	SA1773	d-3-Phosphoglycerate dehydrogenase
sa_c1994s9145_a_at	2.4	sucA	SA1449	2-Oxoglutarate dehydrogenase E1 component
sa_c1669s1406_a_at	36.4	thrB	SA1364	Homoserine kinase
sa_c1665s1401_a_at	30.0	thrC	SA1363	Threonine synthase
sa_c1810s1538_a_at	8.5*	tyrA	SA1401	Prephenate dehydrogenase
sa_c47s43_a_at	7.4*		SA0012	Putative homoserine O-acetyltransferase
sa_c7106s6219_a_at	6.7*		SA0430	trans-Sulfuration enzyme family protein
sa_c7112s6224_a_at	5.8*		SA0431	trans-Sulfuration enzyme family protein
sa_c7368s9209_a_at	2.1		SA0502	Cysteine synthase/cystathionine beta-synthase family protein
sa_c7372s10188cs_s_at	3.0		SA0503	trans-Sulfuration enzyme family protein
sa_c7649s6662_a_at	4.4		SA0595	Peptidase, M20/M25/M40 family
sa_c574s400_a_at	9.5		SA1058	Aminotransferase class I
sa_c9581s8342_a_at	20.6*		SA1360	Aspartate kinase
sa_c1934s1655_a_at	8.0		SA1433	Peptidase, M20/M25/M40 family
sa_c1936s1659_a_at	8.3		SA1434	Alanine racemase family protein
sa_c2570s2145_a_at	2.6		SA1594	Glycine cleavage system P protein
sa_c3262s2810_a_at	6.4		SA1787	Chorismate mutase/phospho-2-dehydro-3-Deoxyheptonate aldolase
sa_c3945s3412_a_at	2.4		SA2000	Putative aminotransferase
sa_c6224s5400_a_at	7.4		SA2575	Aminotransferase
sa_c6718s5857_a_at	2.3*		SA2701	Putative histidinol-phosphate aminotransferase
Carbohydrates
sa_c9528s8308_a_at	2.4		SA0111	Oxidoreductase, short-chain-dehydrogenase/reductase family
sa_c8477s7437_at	11.1		SA0869	Phosphoglycerate mutase family protein
sa_c629s448_at	3.5		SA1071	Chitinase-related protein
sa_c2791s2362_a_at	3.3		SA1661	Putative acetyl-CoA carboxylase
sa_c5142s4440_at	4.0		SA2313	Hydrolase haloacid dehalogenase-like family
sa_c6220s5396_a_at	3.7		SA2574	2-Hydroxyacid dehydrogenase family protein
Cell wall and capsule
sa_c6371s5542_a_at	2.3	budA	SA2617	Alpha-acetolactate decarboxylase
sa_c1124s904_a_at	2.2		SA1205	Putative cell division initiation protein
sa_c4589s3921_a_at	4.8*	fmtB	N315-SA1964	FmtB protein
sa_c3228s2778_a_at	3.6		SA1779	Transglycosylase domain protein
sa_c9866s8605_at	5.7		SA1932	Transglycosylase domain protein
sa_c4494s3841_a_at	3.6		SA2125	Peptidase, M20/M25/M40 family
sa_c5176s4476_a_at	26.3*		SA2322	Peptidase, M20/M25/M40 family
DNA metabolism
sa_c8705s9226_a_at	2.0	rexB	SA0970	Exonuclease
sa_c2436s2020_a_at	2.9	xerD	SA1540	Site-specific recombinase
sa_c1804s1534_a_at	3.6*		SA1400	ImpB/MucB/SamB family protein
sa_c2977s2534_a_at	6.4		SA1711	DNA-3-methyladenine glycosylase
Hypothetical
sa_c2287s9677_a_at	2.4*		N315-SA0141	Conserved hypothetical protein
sa_c7819s6819_a_at	3.5		N315-SA0551	Mercuric reductase homologue
sa_c8469s7429_a_at	16.1		N315-SA0751	Conserved hypothetical protein
sa_c4084s9951_at	2.6*		N315-SA1802	Conserved hypothetical protein
sa_c7157s10125_a_at	6.9*		N315-SA1832	Conserved hypothetical protein
sa_c6385s5555_a_at	127.9*		N315-SA2397	Conserved hypothetical protein
sa_c8467s10245_s_at	4.6		N315-SAS018	Conserved hypothetical protein
sa_c41s39_a_at	31.0*		SA0011	Conserved hypothetical protein
sa_c648s458_a_at	2.2		SA0076	Hypothetical protein
sa_c2222s1923_a_at	3.3*		SA0129	Conserved hypothetical protein
sa_c3008s2564_a_at	12.5		SA0157	Conserved hypothetical protein
sa_c3158s2704_a_at	16.5		SA0160	Conserved hypothetical protein
sa_c3224s2774_a_at	9.2		SA0161	Conserved hypothetical protein
sa_c3976s9867_at	2.9*		SA0181	Conserved domain protein
sa_c4729s4046_at	6.2*		SA0208	Hypothetical protein
sa_c6917s6037_a_at	5.1*		SA0299	Hypothetical protein
sa_c6967s6091_a_at	4.7		SA0314	Conserved hypothetical protein
sa_c7055s6165_a_at	9.0*		SA0414	Putative lipoprotein
sa_c7061s6172_a_at	2.8*		SA0415	Hypothetical protein
sa_c7088s6200_a_at	3.7		SA0425	Hypothetical protein
sa_c7094s6206_a_at	3.6		SA0427	Conserved hypothetical protein
sa_c7132s6241_a_at	4.9*		SA0436	Conserved hypothetical protein
sa_c7203s6269_a_at	5.3*		SA0445	Conserved hypothetical protein
sa_c7313s9398_a_at	16.5		SA0480	Hypothetical protein
sa_c7760s6763_at	2.7		SA0625	Conserved hypothetical protein
sa_c7813s6815_at	4.1		SA0639	Conserved hypothetical protein
sa_c7821s6823_a_at	3.7*		SA0641	Conserved hypothetical protein
sa_c8897s7814_a_at	5.0*		SA0692	Conserved hypothetical protein
sa_c7985s6972_at	2.2		SA0703	Conserved hypothetical protein
sa_c8069s7049_a_at	2.6		SA0730	Conserved hypothetical protein
sa_c8928s7841_a_at	3.1		SA0755	Conserved hypothetical protein
sa_c8196s7173_a_at	3.5		SA0768	Conserved hypothetical protein
sa_c8244s7224_a_at	2.7		SA0785	Conserved hypothetical protein
sa_c8348s7321_a_at	5.3		SA0821	HD domain protein
sa_c10288s8968_a_at	3.3*		SA0822	Conserved hypothetical protein
sa_c6027s5223_a_at	7.5*		SA0870	LysE/YggA family protein
sa_c10616s11070_s_at	15.1		SA0871	Putative acetyltransferase
sa_c8548s7508_a_at	4.5*		SA0920	Hypothetical protein
sa_c485s314_at	103.2*		SA1033	Hypothetical protein
sa_c525s350_at	2.3		SA1044	Conserved hypothetical protein
sa_c750s552_a_at	2.4		SA1101	Conserved hypothetical protein
sa_c827s629_a_at	2.9		SA1117	Conserved hypothetical protein
sa_c1078s861_at	3.1		SA1191	Conserved hypothetical protein
sa_c1112s893_a_at	2.1		SA1200	Conserved hypothetical protein
sa_c1705s1441_a_at	33.0		SA1375	Conserved hypothetical protein
sa_c9771s8515_a_at	2.5		SA1418	Conserved hypothetical protein
sa_c2481s2059_at	4.3		SA1556	Hypothetical protein
sa_c2779s2349_a_at	18.1		SA1658	Hypothetical protein
sa_c2783s2353_a_at	4.9*		SA1659	Conserved hypothetical protein
sa_c2807s2375_a_at	5.8*		SA1664	Conserved hypothetical protein
sa_c2819s2389_at	2.8		SA1670	Conserved hypothetical protein
sa_c3298s2841_at	2.7		SA1796	Conserved hypothetical protein
sa_c3306s2847_a_at	2.5		SA1798	Conserved hypothetical protein
sa_c3357s2894_a_at	2.3		SA1810	Conserved hypothetical protein
sa_c9141s8010_at	3.4*		SA1896	Conserved hypothetical protein
sa_c3786s3258_a_at	2.8		SA1956	Conserved hypothetical protein
sa_c3842s3311_at	2.3		SA1972	Conserved hypothetical protein
sa_c3900s3368_at	5.8		SA1986	Conserved hypothetical protein
sa_c4134s3487_a_at	12.3		SA2019	Putative SdrH protein
sa_c4171s3522_a_at	7.3		SA2033	Conserved hypothetical protein
sa_c4173s3526_a_at	4.1		SA2034	Conserved hypothetical protein
sa_c9799s8540_a_at	2.3		SA2123	Conserved hypothetical protein
sa_c4492s3837_a_at	4.3		SA2124	Conserved hypothetical protein
sa_c4628s3951_a_at	2.8		SA2162	Conserved hypothetical protein
sa_c5081s4376_a_at	2.4		SA2294	Conserved hypothetical protein
sa_c9305s8148_a_at	5.7		SA2304	Conserved domain protein
sa_c5156s4454_a_at	2.3		SA2318	Conserved hypothetical protein
sa_c5174s4471_a_at	4.8		SA2321	Oxidoreductase, short-chain-dehydrogenase/reductase family
sa_c10593s9072_a_at	2.9		SA2338	Hypothetical protein
sa_c5299s4579_a_at	4.9		SA2354	Putative membrane protein
sa_c5458s4723_a_at	3.8		SA2365	Conserved hypothetical protein
sa_c5516s4772_a_at	2.0		SA2379	Conserved hypothetical protein
sa_c5614s4868_a_at	11.9*		SA2404	Conserved hypothetical protein
sa_c5616s4872_a_at	19.1*		SA2405	Conserved hypothetical protein
sa_c5624s4878_a_at	3.2		SA2408	Conserved hypothetical protein
sa_c9344s8176_a_at	3.4		SA2436	Conserved hypothetical protein
sa_c5788s5026_a_at	2.2		SA2456	Conserved hypothetical protein
sa_c5815s5055_a_at	6.3		SA2467	Putative lipoprotein
sa_c10598s11052_s_at	2.6		SA2526	Putative membrane protein
sa_c6270s5451_a_at	2.2		SA2587	Conserved hypothetical protein
sa_c6274s5452_at	4.4*		SA2588	Hypothetical protein
sa_c6278s5456_a_at	13.6*		SA2589	Conserved hypothetical protein
sa_c6728s5871_a_at	8.8*		SA2704	Conserved hypothetical protein
sa_c6750s5891_a_at	16.1*		SA2709	Conserved hypothetical protein
sa_c6752s5895_a_at	26.3*		SA2710	Conserved hypothetical protein
Miscellaneous
sa_c6461s5629_a_at	2.2	cysJ	SA2639	Sulfite reductase
sa_c1739s1473_a_at	3.2	mscL	SA1383	Mechanosensitive channel protein
sa_c10345s9018_a_at	4.6*		SA0162	NAD-dependent formate dehydrogenase
sa_c8485s7447_a_at	2.3		SA0872	OsmC/Ohr family protein
sa_c10627s11083cv_s_at	2.6		SA0941	Putative NADH dehydrogenase
sa_c594s417_at	5.2		SA1063	Acetyltransferase GNAT family
sa_c1671s1408_a_at	4.1		SA1365	Hydrolase, haloacid dehalogenase-like family
sa_c2466s2048_a_at	2.1		SA1553	Glyoxalase family protein
sa_c8677s7626_a_at	3.6*		SA0962	Putative glycerophosphoryl diester phosphodiesterase
sa_c3202s2750_a_at	25.5*		SA1772	Aminotransferase class V
sa_c3210s2757_a_at	15.3		SA1774	Hydrolase, haloacid dehalogenase-like family
sa_c6764s5905_a_at	6.2		SA2713	Rhodanese-like domain protein
sa_c5009s4311_a_at	4.7		SA2276	Inosine-uridine-preferring nucleoside hydrolase
Protein metabolism
sa_c1128s910_a_at	2.5	ileS	SA1206	Isoleucyl-tRNA synthetase
sa_c1800s1530_a_at	2.2	msrA	SA1397	Peptide methionine sulfoxide reductase
sa_c6770s5910_a_at	3.3*	pcp	SA2714	Pyrrolidone-carboxylate peptidase
sa_c7051s6163_a_at	15.1*		SA0413	Putative ribosomal protein-serine acetyltransferase
sa_c8966s7880_a_at	10.7		SA0815	Ribosomal subunit interface protein
sa_c2024s1734_a_at	2.8		SA1455	Carboxyl-terminal protease
sa_c5620s4877_a_at	5.7		SA2407	Putative lipoprotein
Regulation
sa_c4149s3503_a_at	3.1	agrA	SA2026	Accessory gene regulator protein A
sa_c4530s3875_a_at	11.7	czrA	SA2137	Transcriptional regulator
sa_c9575s8335_a_at	4.7	lexA	SA1374	LexA repressor
sa_c2879s2445_a_at	2.4	relA	SA1689	GTP pyrophosphokinase
sa_c5047s4347_at	3.2	sarR	SA2287	Staphylococcal accessory regulator R
sa_c5529s4783_a_at	8.7	sarZ	SA2384	Staphylococcal accessory protein Z
sa_c10319s10704cv_s_at	3.4		N315-SA0142	Putative transcription factor
sa_c9074s7960_a_at	7.2*		N315-SA0882	Putative competence transcription factor
sa_c7020s6143_a_at	14.0		SA0404	Transcriptional regulator, MarR family
sa_c9104s7978_a_at	2.5		SA1003	Negative regulator of competence
sa_c9058s7951_a_at	10.8		SA1060	Transcriptional regulator, MarR family
sa_c9706s8463_a_at	3.2		SA1541	Transcriptional regulator, Fur family
sa_c9202s8059_a_at	3.1		SA1906	Putative sensor histidine kinase
sa_c3661s3140_a_at	2.8		SA1917	PTS system IIC component
sa_c3663s3145_a_at	4.2		SA1919	Transcriptional regulator, Fur family
sa_c9297s8140_at	2.2		SA2302	Putative transcriptional regulator
sa_c6050s5246_a_at	2.7		SA2531	Transcriptional regulator, MarR family
sa_c6262s5443_a_at	78.4*		SA2585	Putative regulatory protein
Resistance
sa_c7024s6147_a_at	5.5	mepA	SA0405	MATE efflux family protein
sa_c8155s7139_a_at	10.1	norA	SA0754	Multidrug resistance protein
sa_c346s186_a_at	2.0		SA2413	Drug resistance transporter, EmrB/QacA subfamily
sa_c5721s4964_a_at	6.7	bcr	SA2437	Bicyclomycin resistance protein
Stress response
sa_c1956s1681_a_at	2.4	cspB	SA2731	Cold shock protein
sa_c3134s2687_a_at	3.6		SA1753	Universal stress protein family
sa_c8744s7687_a_at	13.0		SA1759	Universal stress protein family
sa_c9791s8532_a_at	4.6		SA2131	Dps family protein
sa_c5530s4787_a_at	6.0*		SA2385	Heat shock protein, Hsp20 family
Transport
sa_c3567s9159_a_at	10.0	brnQ	SA0171	Branched-chain amino acid transport
sa_c324s166_a_at	100.8*	oppC	SA0992	Oligopeptide ABC transporter
sa_c328s170_a_at	64.2*	oppD	SA0993	Oligopeptide ABC transporter
sa_c332s172_a_at	12.3*	oppF	SA0994	Oligopeptide ABC transporter
sa_c37s34_a_at	17.4*		SA0010	AzlC family protein
sa_c9538s8314_a_at	2.9*		SA0128	Phosphonate ABC transporter
sa_c3043s2596_a_at	35.4		SA0158	ABC transporter
sa_c3118s2672_a_at	24.0		SA0159	ABC transporter
sa_c3997s3420_a_at	29.2		SA0184	Peptide ABC transporter
sa_c7236s6302_a_at	5.3		SA0454	Sodium:dicarboxylate symporter family protein
sa_c5418s4689_a_at	133.0*		SA0504	ABC transporter
sa_c7374s6406_a_at	124.9*		SA0505	ABC transporter
sa_c7378s6412_a_at	114.6*		SA0506	ABC transporter
sa_c8252s7229_a_at	2.1		SA0788	Oligopeptide transporter family protein
sa_c5431s4700_a_at	27.7		SA0882	ABC transporter
sa_c8512s7471_a_at	25.9		SA0883	ABC transporter
sa_c8518s7475_a_at	28.5		SA0884	ABC transporter
sa_c10571s9056_a_at	124.5*		SA0991	Oligopeptide ABC transporter
sa_c350s191_a_at	63.5*		SA0995	Oligopeptide ABC transporter
sa_c1675s1413_a_at	2.5		SA1367	Amino acid permease
sa_c3810s3279_a_at	4.9		SA1963	Proline permease
sa_c4110s3463_a_at	3.5*		SA2011	Sodium transport family protein
sa_c4536s3879_a_at	17.0		SA2138	Cation efflux family protein
sa_c5416s4682_a_at	2.4		SA2211	ABC transporter
sa_c5126s4423_a_at	2.4		SA2309	Amino acid permease
sa_c5148s4444_a_at	17.0		SA2314	Sodium/bile acid symporter family protein
sa_c5160s4458_a_at	3.1		SA2319	Na⁺/H⁺ antiporter family protein
sa_c5632s4887_a_at	3.0*		SA2411	Amino acid ABC transporter
sa_c9340s8173_a_at	2.5*		SA2416	Cation efflux family protein
sa_c5769s5011_a_at	3.0		SA2449	Putative drug transporter
sa_c5795s5035_a_at	4.1		SA2458	Amino acid permease
sa_c5875s5111_a_at	31.9		SA2483	Putative transporter
sa_c6017s5213_a_at	3.2		SA2521	Putative transporter
sa_c5345s4618_a_at	2.2		SA2525	ABC transporter
sa_c6186s5364_a_at	3.5		SA2566	Putative MmpL efflux pump
sa_c6378s5547_a_at	17.2		SA2619	Amino acid permease
Virulence
sa_c592s9345_a_at	2.4	atl	SA1062	Bifunctional autolysin
sa_c1007s793_a_at	7.9	fbp	SA1168	Fibrinogen-binding protein
sa_c5630s4882_a_at	4.4	fmhA	SA2409	FmhA protein
sa_c6975s6099_a_at	3.1	geh	N315-SA0309	Glycerol ester hydrolase
sa_c3951s9849_a_at	12.5*	hlb	SA2003	Phospholipase C
sa_c9442s8255_a_at	9.2*	icaA	SA2689	Intercellular adhesion protein A
sa_c6681s9106_a_at	3.1*	icaB	SA2691	Intercellular adhesion protein B
sa_c6688s5833_a_at	17.5*	lip	N315-SA2463	Triacylglycerol lipase precursor
sa_c9390s8214_a_at	7.4	srtA	SA2539	Sortase
sa_c570s397_a_at	4.0*	sspA	N315-SA0901	Serine protease
sa_c568s393_a_at	5.1	sspB	SA1056	Cysteine protease
sa_c564s391_a_at	5.2*	sspC	SA1055	Protease
sa_c10149s10564_at	2.2*		N315-SA1819	Toxic shock syndrome toxin 1
sa_c10156s10581_at	11.9*		N315-SA1833	SaPI pathogenicity island
sa_c6859s5993_a_at	3.8		SA0270	Putative staphyloxanthin biosynthesis protein
sa_c7169s10140_a_at	2.5		SA0901	Pathogenicity island protein
sa_c1181s961_a_at	3.8		SA1220	Fibronectin/fibrinogen binding-related protein

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Affymetrix S. aureus GeneChip descriptive representing indicated predicted ORF.

*, transcript was below the lower limits of sensitivity in unstressed cells, and thus the amount of change represents an estimate.

S. aureus strain COL locus, unless otherwise indicated (strain preceeds locus identifier).

SOS response.

Mitomycin C is an antimicrobial and anticancer agent that causes DNA intra- and interstrand cross-linking as well as monofunctional alkyl lesions and is a potent inducer of the bacterial SOS regulon (41). To define the optimal conditions for induction of the SOS regulon, log-phase UAMS-1 cells were treated with 0.5, 1.0, 2.5, or 5 μg ml⁻¹ mitomycin C for 30 min. Real-time PCR was used to compare recA and uvrB transcript titers at each drug concentration to those in mock-treated cells; recA and uvrB are well-characterized components of the SOS response (24, 32, 48). The cell viability of each mitomycin C-challenged sample was also compared to that of mock-treated cells. It was determined that 1 μg ml⁻¹ mitomycin C induced both recA (2.0-fold) and uvrB (15-fold) transcription and simultaneously produced the least amount of toxicity (data not shown), suggesting that these conditions were appropriate for studying mitomycin C-mediated induction of the SOS response. Accordingly, log-phase UAMS-1 cells were treated with 1 μg ml⁻¹ mitomycin C for 30 min, and transcript titers were compared to those for untreated cells.

A total of 73 genes were induced by mitomycin C challenge (Table 5). Among these were the genes for the SOS repressor protein LexA (4.6-fold), components of the nucleotide excision repair machinery, namely, UvrA (2.4-fold) and UvrB (4.1-fold), the single-stranded binding protein (ssb; 44.5-fold), and the recombination repair proteins SbcC (4.9-fold) and SbcD (4.3-fold), all of which are known members of the bacterial SOS response (13). Additionally, a umuC-like gene (SACOL1400) was dramatically upregulated (36.2-fold) by mitomycin C challenge; UmuC is a component of the E. coli SOS response that promotes replicative lesion bypass of noninstructive DNA lesions (44). Collectively, these results suggest that the conditions used were appropriate for studying the SOS system.

TABLE 5.

S. aureus SOS response-induced transcripts

Category and qualifier^a	Fold induction^b	Common name	Locus^c	Description
DNA metabolism
sa_c10340s10724_s_at	4.9*	sbcC	SA1382	Exonuclease SbcC
sa_c1727s1464_a_at	4.3	sbcD	SA1381	Exonuclease SbcD
sa_c4052s9933_a_at	44.5	ssb	N315-SA1792	Single-stranded DNA-binding protein
sa_c8354s7326_a_at	2.4	uvrA	SA0824	Excinuclease ABC, A subunit
sa_c10546s11006_s_at	4.1	uvrB	SA0823	Excinuclease ABC, B subunit
sa_c10309s10698_a_at	14.5*		N315-SA1196	ImpB/MucB/SamB family protein
sa_i875ur_x_at	36.2*		SA1400	ImpB/MucB/SamB family protein
Hypothetical
sa_c2404s9766cs_s_at	46.8		MSSA476-SAS064	Conserved hypothetical protein
sa_c4550s9974_at	2.2		MSSA476-SAS070	Conserved hypothetical protein
sa_c4556s9980_x_at	2.1		MSSA476-SAS072	Conserved hypothetical protein
sa_c4049s9931_a_at	42.1*		MSSA476-SAS1903	Putative phage regulatory protein
sa_c4031s9915_at	8.0*		Mu50-SAV0881	Conserved hypothetical protein
sa_c10677s11128_at	2.3		Mu50-SAV2001	Putative lipoprotein
sa_c4046s9927_at	17.4*		MW2-MW1918	Conserved hypothetical protein
sa_c4075s9947_at	86.9*		MW2-MW1930	Conserved hypothetical protein
sa_c8469s7429_a_at	2.2		N315-SA0751	Conserved hypothetical protein
sa_c4058s9936_a_at	40.9		N315-SA1795	Conserved hypothetical protein
sa_c4070s9942_a_at	83.0		N315-SA1799	Conserved hypothetical protein
sa_c10141s10553_s_at	35.1		N315-SA1803	Conserved hypothetical protein
sa_c7177s10148_a_at	7.6*		N315-SA1821	Conserved hypothetical protein
sa_c6248s5424_a_at	2.7*		N315-SA2352	Conserved hypothetical protein
sa_c7132s6241_a_at	15.5*		SA0436	Conserved hypothetical protein
sa_c1071s9138_a_at	2.0		SA1189	Acetyltransferase
sa_c1705s1441_a_at	30.8		SA1375	Conserved hypothetical protein
sa_c1960s1685_a_at	2.8		SA1438	Conserved hypothetical protein
sa_c3900s3368_at	33.3		SA1986	Conserved hypothetical protein
sa_c3910s3377_a_at	8.0		SA1988	Conserved hypothetical protein
sa_c10125s8848_a_at	20.6		SA1999	Conserved hypothetical protein
sa_c4628s3951_a_at	6.1		SA2162	Conserved hypothetical protein
Miscellaneous
sa_c8264s7244_at	2.3	nrdI	SA0791	NrdI protein
sa_c1810s1538_a_at	6.9*	tyrA	SA1401	Prephenate dehydrogenase
sa_c6244s5421_a_at	2.1		SA2579	Phytoene dehydrogenase
Prophage
sa_c10417s10840_s_at	32.2	dut	SA0357	Deoxyuridine 5-triphosphate nucleotidohydrolase
sa_c9918s10462_a_at	3.2	int	N315-SA1810	Integrase
sa_c10465s10903_s_at	33.5		BA000017///BA000018	Phage antirepressor protein
sa_c10466s10905_a_at	42.5		BA000017///BA000018	Phage antirepressor protein
sa_c4046s9927_a_at	67.8*		BA000017///BA000018	Endodeoxyribonuclease RusA
sa_i10903u_x_at	34.9		BA000017///BA000018	Phage antirepressor protein
sa_c4040s9922cs_s_at	26.2		BA000017///BA000018	Conserved hypothetical protein
sa_c10668s11120_a_at	7.4		MRSA252-SAR2051	Hypothetical protein
sa_c2375s1984_a_at	2.7*		Mu50-SAV0874	phi PVL ORF 51 homolog
sa_c3991s9882_a_at	4.3		Mu50-SAV1954	phi PVL ORF 18-19-like protein
sa_c3992s9884_a_at	5.8		Mu50-SAV1955	phi PVL ORF 15 and 16 homolog
sa_c4039s9920_at	6.9*		Mu50-SAV1979	phi PVL ORF 50 homolog
sa_c3994s9885_s_at	4.6		MW2-MW1895	Conserved hypothetical protein
sa_c4057s9934_a_at	38.7		MW2-MW1923	Conserved hypothetical protein
sa_c3995s9886_a_at	6.8		N315-SA1767	Conserved hypothetical protein
sa_c4005s9893_a_at	4.0		N315-SA1769	Conserved hypothetical protein
sa_c4009s9897_a_at	4.0		N315-SA1770	Conserved hypothetical protein
sa_c4010s9899_at	4.9		N315-SA1771	Conserved hypothetical protein
sa_c4014s9903_a_at	4.2		N315-SA1773	Conserved hypothetical protein
sa_c10670s11122_a_at	5.2		N315-SA1774	Conserved hypothetical protein
sa_c10672s11124_a_at	6.0		N315-SA1775	Conserved putative Clp protease
sa_c4020s9905_at	11.5		N315-SA1776	Conserved hypothetical protein
sa_c10134s10547_a_at	15.6		N315-SA1777	Conserved hypothetical protein
sa_c4022s9907_a_at	23.9		N315-SA1778	Conserved hypothetical protein
sa_c4024s9909_a_at	42.7		N315-SA1779	Conserved hypothetical protein
sa_c4026s9911_at	41.9		N315-SA1780	Conserved hypothetical protein
sa_c4048s9929_a_at	43.3		N315-SA1790	Conserved hypothetical protein
sa_c9913s10456_a_at	75.3*		N315-SA1793	Conserved hypothetical protein
sa_c4060s9937_a_at	41.0*		N315-SA1797	Conserved hypothetical protein
sa_c7182s10152cs_s_at	8.6		SA2014	Phage terminase family protein
Protein metabolism
sa_c1812s1540_a_at	9.0		SA1402	Putative glutamyl aminopeptidase
Regulation
sa_c9575s8335_a_at	4.6	lexA	SA1374	LexA repressor
sa_c10143s10555cv_s_at	28.4		N315-SA1804	Putative transcriptional regulator
sa_c1737s1469_a_at	4.8*	mscL	N315-SA1182	Large-conductance mechanosensitive channel
Virulence
sa_c4094s3450_a_at	3.4	hlb	SA2003	Phospholipase C
sa_c10522s10973_s_at	2.3	srtA	SA2539	Sortase
sa_c7169s10140_a_at	24.9		SA0901	Pathogenicity island protein
sa_c10151s10571_a_at	9.9		SA0902	Pathogenicity island protein
sa_c10150s10567_a_at	7.4		SA0903	Pathogenicity island protein
sa_c7173s10144_at	8.1		SA0904	Pathogenicity island protein

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Affymetrix S. aureus GeneChip descriptive representing indicated predicted ORF.

*, transcript was below the lower limits of sensitivity in unstressed cells, and thus the amount of change represents an estimate.

S. aureus strain COL locus, unless otherwise indicated (strain preceeds locus identifier).

Among the SOS-induced transcripts were several bacteriophage replication/packaging genes, including those for N315 SA1791 (42.1-fold), which has homology to the replication initiation protein DnaB, a dUTPase (COLSA0357; 34.3-fold), putative phage tail components (SAV1954 [4.3-fold] and SAV1955 [5.8-fold]), and a small terminase protein (SACOL0906; 8.6-fold). Induction of these phage transcripts correlated with the dramatic SOS-mediated upregulation of a putative phage antirepressor gene, SAV1994 (42.5-fold). Two loci, each harboring a set of genes, were among the highest SOS-induced transcripts. They included members of a bovine pathogenicity island (SACOL0901 to SACOL0904; average induction, 12.5-fold) and a set of genes encoding conserved hypothetical proteins (N315 SA1767 to SA1780; average induction, 12.9-fold). A putative Holliday junction resolvase gene (rusA) was also dramatically upregulated (67.8-fold). These results were validated, in part, by real-time PCR, which demonstrated that uvrB was upregulated in SOS-induced cells (41.5-fold) (data not shown). RecA transcript titers saturated the microarray, and thus we could not accurately determine what, if any, effect mitomycin C challenge had on recA expression. Nonetheless, real-time PCR did indeed indicate that recA was upregulated (2.4-fold) in mitomycin C-challenged cells, as opposed to the case in untreated cells. As shown in Table S6 in the supplemental material, 453 transcripts decreased in response to SOS-inducing conditions.

Global effects of stress responses on RNA half-lives.

As stated above, studies have linked stress response-mediated changes in protein production to alterations in target transcript mRNA stability, suggesting that modulating mRNA turnover plays a role in bacterial adaptability to environmental challenges. Admittedly, most of those studies have been limited to a few transcripts. Nonetheless, we set out to determine whether induction of the S. aureus cold shock, heat shock, stringent, or SOS response globally influences mRNA turnover. To do so, either log-phase UAMS-1 cells were mock treated or the corresponding stress response was induced (conditions described above). Rifampin was then added to inhibit de novo transcript synthesis, as previously described (46). Aliquots were removed at 0, 2.5, 5.0, 15, and 30 min post-transcriptional arrest, and cell viability and rifampin resistance were measured (see Materials and Methods). Total bacterial RNA was isolated, and the mRNA half-lives of transcripts produced in mock-treated, cold-shocked, heat-shocked, stringent response-induced, and SOS response-induced cells were determined using Affymetrix S. aureus GeneChips as previously described (46, 49).

The results (Fig. 1) indicate that log-phase transcripts are degraded rapidly within mock-treated cells; 89.7% of all transcripts had half-lives of ≤5 min, 206 transcripts (9.2%) had intermediate half-lives (>5 min but ≤30 min), and 25 (1.1%) RNA species were stable (half-lives of >30 min). These results are in agreement with previous studies using custom-made S. aureus GeneChips (Saur2a), which found that the half-lives of 89.6% of all UAMS-1 log-phase transcripts were <5 min, those of 9.5% of transcripts were intermediate, and those of 0.7% of transcripts were stable (>60 min) (46). Induction of the SOS response did not appreciably affect global RNA turnover properties, whereas induction of the heat shock, cold shock, and stringent responses appeared to dramatically stabilize RNA species (Fig. 1). Within heat-shocked cells, 38.5% of log-phase transcripts had half-lives of ≤5 min, 54.5% demonstrated intermediate rates of mRNA turnover, and 7.1% were stable. Similarly, the half-lives of transcripts in stringent response-induced cells were as follows: 42.9% were ≤5 min, 45.7% were intermediate, and 11.4% were stable. Cold-shocked cells had a unique RNA turnover profile, as only 0.7% of transcripts had half-lives of ≤5 min, while the majority (64.1%) had half-lives of between 5 and 30 min or were stable (35.1%).

One possible explanation for the observed stress-mediated increases in mRNA stability could be that rifampin is not active within heat-shocked, cold-shocked, and stringent response-induced cells. Indeed, most of these stress conditions induce transport functions and/or drug efflux pumps (stringent response; NorA and MepA). However, several lines of evidence suggest that the efflux of rifampin does not contribute to this phenomenon and that the antibiotic arrests de novo transcript synthesis under each stress condition. First, Williams and Piddock have shown that efflux inhibitors do not influence rifampin accumulation within S. aureus cells (63). Second, a large portion of the transcriptome is rapidly degraded (half-lives of ≤5 min) under both heat shock and stringent response conditions, suggesting that de novo transcript synthesis is arrested. Third, rifampin challenge has similar effects on unstressed and stressed cell proliferation at 2.5, 5.0, 15, and 30 min post-rifampin treatment (data not shown). Moreover, the results in Fig. 2 demonstrate that induction of the stringent response confers resistance to the fluoroquinolone ciprofloxacin, presumably via norA and/or mepA upregulation, but does not reduce rifampin susceptibility. More specifically, UAMS-1 viability was decreased 2,600-fold during prolonged exposure (3 h) to ciprofloxacin (Fig. 2A). In contrast, induction of the stringent response decreased UAMS-1 susceptibility to ciprofloxacin, resulting in a threefold reduction in cell viability (Fig. 2B). In contrast, induction of the stringent response had no measurable effect on S. aureus rifampin susceptibility; cells challenged with rifampin demonstrated dramatic reductions in cell viability, in both stringent response-induced and noninduced cells (compare Fig. 2A and B). Finally, these results fit directly with studies of other organisms (53). Collectively, these results suggest that the stringent, cold shock, and heat shock responses influence molecular components that influence mRNA turnover in S. aureus cells.

FIG. 2. — Stringent response-inducing conditions decrease *S. aureus* susceptibility to ciprofloxacin but not rifampin. The graphs show cell viabilities of unstressed (A) and mupirocin-treated (B) log-phase *S. aureus* UAMS-1 cells (0 h) in the absence (diamonds) or presence of either rifampin (triangles) or ciprofloxacin (squares). Cell viability was monitored for 4 h and then plotted.

The global increases in mRNA stability in stringent response-induced, cold-shocked, and heat-shocked cells could be explained by two other scenarios, as follows: (i) these stress conditions induce/activate cellular RNA-stabilizing capacities or (ii) the conditions repress RNase production/function. Interestingly, we found that homologues of putative B. subtilis RNase genes (15 genes) are positively regulated by the alternative sigma factor σ^B (P. M. Dunman, P. D. Olson, and K. L. Anderson, unpublished data). However, as shown in Fig. 1, no global differences in mRNA turnover were observed between UAMS-1 sigB⁺ and UAMS-1 sigB mutant cells. Thus, it is likely that stress-induced σ^B-dependent alterations in RNase expression do not account for differences in mRNA stability.

Correlation between stress responses and target transcript stability.

Table S6 in the supplemental material lists all loci represented on the S. aureus GeneChip that were up- or downregulated by each stress response and the RNA half-lives of these transcripts under each stress condition as well as in mock-treated cells. A comparison of stress-mediated changes in transcript titers and their corresponding RNA turnover properties indicated that stress response-dependent alterations in transcript abundances can be attributed, in part, to alterations in RNA stability. In other words, induction of a stress response appears to alter both transcript synthesis and stability, suggesting that modulating RNA turnover may be an important component of the ability of S. aureus to cope with environmental challenges.

More specifically, as shown in Table S6 in the supplemental material, 164 of the 277 stringent response-induced transcripts are also expressed in mock-treated cells. A comparison of their RNA half-lives indicated that 147 (89.6%) of these transcripts are more stable when the stringent response is elicited than in mock-treated cells. Similarly, 65 heat shock-induced transcripts were also detected within mock-treated cells. Sixty-three (96.9%) of these transcripts were more stable in heat-shocked cells than in mock-treated cells. Most (56%) cold shock-induced transcripts were not detected in mock-treated cells, and thus their RNA half-lives could not be compared. The remaining 28 transcripts were more stable under cold shock conditions than in mock-treated cells. Sixty-two SOS-induced transcripts were detected within mock-treated cells. A comparison of their half-lives found that five (8%) SOS-induced transcripts were more stable in mitomycin C-stressed cells than in mock-treated cells. Real-time PCR was used to validate these results in part. As shown in Table 6, GeneChip-based RNA turnover measurements correlated with real-time PCR-determined RNA half-lives for each mRNA species analyzed.

TABLE 6.

Comparison of real-time PCR- and GeneChip-based mRNA half-life determinations

Assay	mRNA half-life (min)
	Cold shock		Heat shock		Stringent response		SOS response
	srtA	cspB	clpC	ctsR	sarR	norA	recA	uvrB
GeneChip microarray	15-30	≥30	≥30	≥30	15-30	≥30	≤2.5	≤2.5
Real-time PCR	30	30	15	15-30	15	15-30	2.5	2.5

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We also investigated whether stress response-mediated decreases in transcript titers correlated with increased rates of mRNA turnover. Although induction of the stringent response globally increased RNA stability (Fig. 1), 20% of the stringent response-downregulated transcripts were degraded by the first posttranscriptional arrest sampling time (half-lives of ≤2.5 min) or were more rapidly degraded under stringent response conditions than under mock treatment conditions (see Table S6 in the supplemental material). Forty-three genes were downregulated within heat-shocked cells. Of these, 8 transcripts were not detected under heat shock conditions, and a comparison of mRNA half-lives of the remaining 35 transcripts indicated that 3 (8%) were less stable within heat-shocked cells or had half-lives of ≤2.5 min. No cold shock-repressed transcript demonstrated more rapid turnover under cold shock conditions. RNA turnover was more rapid under SOS-induced conditions than in mock-treated cells for 15% of the SOS-repressed transcripts.

Stable RNA species.

We have previously shown that log-phase UAMS-1 cells produce a set of SSR (half-lives of >60 min) molecules that are not expected to code for protein products (46). Given the importance of the S. aureus agr-encoded RNAIII molecule and small noncoding RNAs within other pathogens, it is likely that many of these molecules play an important role(s) in S. aureus biological processes. As shown in Table S8 in the supplemental material, 126 stable transcripts (half-lives of >30 min) that map to short S. aureus intergenic regions but have no defined function were identified to be produced under mock and/or stressed conditions.

Most SSRs were found to be stress-responsive; 12 small stable RNAs were produced in untreated cells, whereas 90% of SSRs were produced in response to stress. More specifically, two RNA species were stable under all conditions examined. Six transcripts were stable under four of the five conditions. Five transcripts were stable under three conditions, with the majority of these (4) being stable under stringent response, cold shock, and heat shock conditions but having half-lives of between 2.5 and 15 min under mock treatment and SOS-induced conditions. Eleven RNA species were stable under two conditions studied, and 102 transcripts were stable under one condition. Based on the surrounding genomic content and directionality of each SSR, it is likely that some stable RNA molecules are cotranscribed as part of an operon, whereas others are more likely to behave as antisense RNA molecules.

DISCUSSION

Infection is a dynamic process, during which the invading organism is subjected to an array of environmental challenges. Bacteria have developed highly orchestrated processes to respond to environmental stresses, which when elicited alter the cellular physiology in a manner that enhances the organism's survival and its ability to cause disease. Much effort has been devoted toward defining the members of bacterial stress responses by identifying genes whose transcript synthesis is controlled in a stress-specific manner. Only recently has it become recognized that modulation of mRNA degradation is a highly regulated process that also plays an essential role in many stress responses.

Despite S. aureus being a leading cause of nosocomial and community-acquired infections, surprisingly little is known about S. aureus stress responses. Here we have used Affymetrix S. aureus GeneChips to define transcript species that are altered under cold shock, heat shock, stringent, and SOS response-inducing conditions. In addition, we have defined the mRNA turnover characteristics of each response and identified a set of small stable RNA molecules with no obvious open reading frames that are produced as a component of each stress response.

Collectively, our results suggest that S. aureus stress response-dependent alterations in transcript abundances can be attributed, in part, to alterations in RNA stability. This was especially true for conditions of heat shock, cold shock, and stringent response induction, where most (89 to 100%) stress-induced transcripts had increased stability compared to those in untreated cells. Admittedly, it is not yet clear what, if any, effect the observed alterations in transcript stability have on protein production. However, studies of other organisms suggested that modulation of RNA turnover directly influences protein abundance. Thus, it seems likely that the ability of S. aureus to modulate mRNA turnover in a stress-responsive manner correlates with changes at the protein level. Nonetheless, currently it would be premature to interpret the effects of stress-mediated mRNA stabilization on the cellular physiology of S. aureus cells, simply because we do not know whether increases in transcript stability increase or decrease protein production (of all or subsets of mRNA species). However, our expression data do provide many insights about how S. aureus copes with various types of stress.

In general, our results suggest that, like the case for other bacteria, S. aureus stress responses are distinct, but response members do overlap. Moreover, there is a high degree of similarity between the ways that different bacteria cope with environmental stresses. For instance, induction of the S. aureus cold shock response profoundly stabilized most RNA species, increased the transcript titer of the SOS repressor LexA, and decreased expression of the stringent response control factor relA. This suggests that cold shock conditions repress both SOS and stringent responses. Studies have demonstrated that cold-shocked E. coli cells behave similarly, as low temperatures increase RNA stability and reduce RelA activity (61). Although low temperature appears to repress the stringent response, 27 S. aureus cold shock response genes were also components of the stringent response (see Table S6 in the supplemental material), indicating that they may represent members of a generalized stress response. Included among these 27 genes was the cold shock factor cspB. In E. coli, CspB and the major cold shock protein, CspA, are believed to act as RNA chaperones, although their RNA binding specificities differ (25, 43). Transcription of CspA was only marginally induced in cold-shocked cells, yet cspA mRNA was profoundly stabilized during low-temperature growth (half-life of <2.5 min at 37°C versus >30 min at 10°C), which based on E. coli cspA studies, suggests that CspA production was increased. Indeed, preliminary proteomics studies indicated that CspA levels are dramatically increased within cold-shocked UAMS-1 cells (S. Slater and P. M. Dunman, unpublished). Interestingly, cspA mRNA was also significantly stabilized in stringent response-induced cells (see Table S6 in the supplemental material), with an intermediate half-life. Given that cspB expression and cspA mRNA stability correlate with decreased mRNA turnover within both cold-shocked and stringent response-induced cells, it is conceivable that CspB and/or CspA may directly modulate transcript stability.

Induction of the cold shock response primarily increased the transcription of genes with no previously determined function. These gene products may play a role in rescuing stalled ribosomes, which is a requirement for cellular survival at low temperatures. Cold shock conditions also induced the expression of a protein with an S1 RNA binding domain, which is thought to mediate single-stranded RNA and RNA-pseudoknot binding (45) and may contribute to RNA stability at low temperatures. As shown in Fig. 3A, the predominant effect of cold shock conditions was the general decrease in mRNA titers involved in most cellular functions, despite globally increasing mRNA stability. This suggests that low temperatures promote basal S. aureus gene expression, but because RNA species are stable, templates for translation are available for the cell to efficiently respond to changes in growth conditions without having to expend energy for de novo gene expression.

FIG. 3. — Biological processes that are regulated in response to cold shock (A), heat shock (B), stringent response-inducing (C), and SOS response-inducing (D) conditions.

Heat shock conditions induced clpB and clpC transcription. ClpC is proposed to play a role in targeting heat-denatured proteins for degradation by ClpP (15). ClpB is believed to interact with DnaK and other heat shock proteins to mediate solubilization of protein aggregates (19, 37, 38). Although neither clpP nor dnaK transcripts were induced by the heat shock conditions studied, their transcripts were stabilized at the higher temperature (data not shown). The upregulation of clpB and clpC suggests that, like the case for other bacteria, coping with aberrant proteins is a vital component of S. aureus's ability to endure elevated temperatures. The urease operon (ureA-ureG), whose gene products convert urea to ammonia and CO₂, was also upregulated at the high temperature. The thermodependent protein denaturation properties of urea have been well documented. Thus, it is conceivable that heat-shocked cells may guard against urea-based protein denaturation by metabolizing endogenous urea. As shown in Fig. 3B, amino acid biosynthetic genes are in the largest class of genes that are upregulated at elevated temperatures, suggesting that replenishing substrates for protein synthesis is also a priority under heat shock conditions. Paradoxically, the heat shock repressor protein CtsR was also upregulated under heat shock conditions. Frees and colleagues observed this same phenomenon and suggested that CtsR may need a cofactor for repressor function (15). No obvious contributor to the observed increase in heat shock-mediated mRNA stability was found. It is possible that elevated temperatures cause the denaturation of mRNA secondary structures that are recognized by the S. aureus RNA degradation machinery.

Induction of the SOS response increased the expression of nucleotide excision repair pathway and recombinational repair components, suggesting that, like the case for other organisms, repairing DNA damage is an important aspect of S. aureus SOS-induced cells. In a related study, the S. aureus transcriptional response to the oxidizing agent hydrogen peroxide, which also induces the bacterial SOS response, was determined for strain NCTC 8325 (9). The current work differs significantly from that study in several respects. First, H₂O₂ damages DNA, lipids, and proteins (50). Thus, in addition to inducing the SOS response, H₂O₂ also induces other bacterial oxidative stress responses (50), whereas the SOS-inducing agent used here, mitomycin C, primarily causes DNA damage (54, 56). Second, the former study was based on S. aureus strain NCTC 8325, which is functionally deficient for production of the primary stress response sigma factor, SigB (17). SigB has been shown to modulate the expression of a number of genes, including many that contribute to S. aureus pathogenesis (4). Moreover, Giachino and colleagues have shown that by virtue of their SigB deficiency, NCTC 8325 cells are less tolerant to DNA-damaging agents, suggesting that the strain may also be deficient in SOS functions (17). Comparison of our results to the transcriptional changes within H₂O₂-challenged NCTC 8325 cells suggested that SigB does not play a major role in DNA damage-mediated repair functions or the replication of DNA lesions; both studies found that repair components and a homologue to the replication protein UmuC (incorrectly annotated as UvrA in the preceding study) are induced (30). The current work also suggests that SOS induction activates the expression of numerous bacteriophage (Fig. 3D) and pathogenicity island genes. The concerted functions of these factors may account, in part, for the observation that SOS induction results in phage-mediated pathogenicity island dissemination among staphylococci (34, 55).

Striking features were observed within S. aureus stringent response-induced cells. As shown in Fig. 3C, amino acid biosynthetic processes were dramatically upregulated, and members of the translation machinery were downregulated (25 genes), mimicking the effects in mupirocin-treated E. coli cells (47). This implies that S. aureus copes with nutrient-limiting conditions by slowing bulk protein synthesis while increasing the cellular concentration of free amino acids. It was also observed that secreted proteases (i.e., SspA, SspB, and SspC) and transport processes are upregulated (Table 4). These functions may constitute another mechanism by which S. aureus increases its cellular amino acid concentration; the organism may increase digestion of extracellular proteins within its milieu and transport degradation products into the cell to bolster the abundance of amino acids. Another aspect of induction of the stringent response was the profound increase in mRNA stability of most transcripts, but as stated above, we do not yet know the consequences of this phenotype. Interestingly, we found that 60 μg ml⁻¹ mupirocin is optimal for stringent response induction within UAMS-1 cells, which produce high levels of SigB. Crosse and colleagues independently found that the same experimental conditions effectively induce the stringent response within 8325-4 cells, which are SigB deficient (11). This suggests that SigB is not likely to play a major role in stringent response induction.

Each stress condition studied caused alterations in virulence factor expression. In general, S. aureus virulence determinants are expressed in a cell density-dependent manner. Cell surface components that are involved in attachment to host tissue are expressed within exponential-phase cultures, whereas extracellular virulence enzymes/toxins are preferentially produced during the postexponential growth phase (40). Within cold-shocked log-phase cells, extracellular virulence factor regulators (mgrA, sarA, and saeRS) were significantly downregulated in comparison to those in cells grown at 37°C, presumably ensuring low-level production of extracellular virulence determinants. The expression of cell surface virulence factors, including clfA, clfB, and fnbA, did not change at the low temperature. The best-characterized upregulated virulence determinant was sortase (srtA), which is an enzyme that tethers cell surface components (such as host attachment components) to the cell wall (35). Taken together, these results suggest that cold-shocked cells are poised to express cell surface factors on their exterior. Within heat-shocked cells, clpC and the urease operon were upregulated, and as stated above, it is possible that these factors influence the protein turnover properties of the cell. A number of uncharacterized pathogenicity island genes and the alpha-hemolysin gene (hla) were also upregulated at elevated temperature. No known virulence determinants were downregulated under heat shock conditions. Further characterization of the heat-dependent increase in overall mRNA stability may provide a better understanding of pathogenic features of heat-shocked cells. Induction of the S. aureus stringent response upregulated the production of various extracellular virulence determinants, including several proteases. This suggests that stringent response cells are poised to degrade host tissues.

The importance of short noncoding RNAs (microRNAs) in regulating eukaryotic cell development, cell death, and chromosome silencing is well documented. Recent studies have demonstrated that microRNAs also play essential roles in prokaryotic processes, including the regulation of bacterial stress responses and pathogenesis (reviewed in reference 20). For instance, noncoding RNAs are required for Vibrio sp. quorum sensing and Pseudomonas aeruginosa iron homeostasis (31, 62). Within E. coli, over 60 microRNAs have been identified, most of which are thought to act by binding to a protein and modifying its activity or by base pairing with mRNAs and affecting target transcript stability and translation (reviewed in reference 21). We recently identified eight putative S. aureus noncoding small stable RNA molecules (46), which taken together with the results of the current study, suggests that S. aureus produces an array of SSRs both during log-phase growth and in a stress-responsive manner. Based on the genomic context of SSRs, it is likely that many behave as antisense molecules, whereas others are components of operons (see Table S8 in the supplemental material). Studies are currently under way to better characterize these molecules and determine what influence, if any, they have on S. aureus biological processes and stress responses.

Supplementary Material

[Supplemental material]

jbacter_188_19_6739__index.html^{(1.2KB, html)}

Acknowledgments

We thank Gail Crowell for technical assistance.

This work was partially supported by a University of Nebraska Medical Center Assistantship to K.L.A.

Footnotes

^†

Supplemental material for this article may be found at http://jb.asm.org/.

REFERENCES

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[r1] 1.Altuvia, S., D. Weinstein-Fischer, A. Zhang, L. Postow, and G. Storz. 1997. A small, stable RNA induced by oxidative stress: role as a pleiotropic regulator and antimutator. Cell 90:43-53. [DOI] [PubMed] [Google Scholar]

[r2] 2.Beenken, K. E., J. S. Blevins, and M. S. Smeltzer. 2003. Mutation of sarA in Staphylococcus aureus limits biofilm formation. Infect. Immun. 71:4206-4211. [DOI] [PMC free article] [PubMed] [Google Scholar]

[r3] 3.Beenken, K. E., P. M. Dunman, F. McAleese, D. Macapagal, E. Murphy, S. J. Projan, J. S. Blevins, and M. S. Smeltzer. 2004. Global gene expression in Staphylococcus aureus biofilms. J. Bacteriol. 186:4665-4684. [DOI] [PMC free article] [PubMed] [Google Scholar]

[r4] 4.Bischoff, M., P. Dunman, J. Kormanec, D. Macapagal, E. Murphy, W. Mounts, B. Berger-Bachi, and S. Projan. 2004. Microarray-based analysis of the Staphylococcus aureus sigmaB regulon. J. Bacteriol. 186:4085-4099. [DOI] [PMC free article] [PubMed] [Google Scholar]

[r5] 5.Blevins, J. S., M. O. Elasri, S. D. Allmendinger, K. E. Beenken, R. A. Skinner, J. R. Thomas, and M. S. Smeltzer. 2003. Role of sarA in the pathogenesis of Staphylococcus aureus musculoskeletal infection. Infect. Immun. 71:516-523. [DOI] [PMC free article] [PubMed] [Google Scholar]

[r6] 6.Bronner, S., H. Monteil, and G. Prevost. 2004. Regulation of virulence determinants in Staphylococcus aureus: complexity and applications. FEMS Microbiol. Rev. 28:183-200. [DOI] [PubMed] [Google Scholar]

[r7] 7.Cassat, J. E., P. M. Dunman, F. McAleese, E. Murphy, S. J. Projan, and M. S. Smeltzer. 2004. Comparative genomics of Staphylococcus aureus musculoskeletal isolates. J. Bacteriol. 187:576-592. [DOI] [PMC free article] [PubMed] [Google Scholar]

[r8] 8.Cassels, R., B. Oliva, and D. Knowles. 1995. Occurrence of the regulatory nucleotides ppGpp and pppGpp following induction of the stringent response in staphylococci. J. Bacteriol. 177:5161-5165. [DOI] [PMC free article] [PubMed] [Google Scholar]

[r9] 9.Chang, W., D. A. Small, F. Toghrol, and W. E. Bentley. 2006. Global transcriptome analysis of Staphylococcus aureus response to hydrogen peroxide. J. Bacteriol. 188:1648-1659. [DOI] [PMC free article] [PubMed] [Google Scholar]

[r10] 10.Collins, J. J., G. P. Roberts, and W. J. Brill. 1986. Posttranscriptional control of Klebsiella pneumoniae nif mRNA stability by the nifL product. J. Bacteriol. 168:173-178. [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

Characterization of the Staphylococcus aureus Heat Shock, Cold Shock, Stringent, and SOS Responses and Their Effects on Log-Phase mRNA Turnover†

Kelsi L Anderson

Corbette Roberts

Terrence Disz

Veronika Vonstein

Kaitlyn Hwang

Ross Overbeek

Patrick D Olson

Steven J Projan

Paul M Dunman

Abstract

MATERIALS AND METHODS

Bacterial strains.

Growth conditions.

Antibiotic susceptibility assays.

Microarray studies.

Real-time PCR.

TABLE 1.

RESULTS

Cold shock response.

TABLE 2.

Heat shock response.

TABLE 3.

Stringent response.

TABLE 4.

SOS response.

TABLE 5.

Global effects of stress responses on RNA half-lives.

FIG. 1.

FIG. 2.

Correlation between stress responses and target transcript stability.

TABLE 6.

Stable RNA species.

DISCUSSION

FIG. 3.

Supplementary Material

Acknowledgments

Footnotes

REFERENCES

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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Characterization of the Staphylococcus aureus Heat Shock, Cold Shock, Stringent, and SOS Responses and Their Effects on Log-Phase mRNA Turnover^†