Journal of Photochemistry and Photobiology B: Biology 130 (2014) 349–356

Contents lists available at ScienceDirect

Journal of Photochemistry and Photobiology B: Biology journal homepage: www.elsevier.com/locate/jphotobiol

Transcriptional response of Enterococcus faecalis to sunlight Lauren M. Sassoubre a, Matthew M. Ramsey b,1, Michael S. Gilmore b, Alexandria B. Boehm a,⇑ a b

Environmental and Water Studies, Department of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford, CA, USA Departments of Ophthalmology, Microbiology and Immunobiology, Harvard Medical School, Massachusetts Eye and Ear Infirmary, Boston, MA, USA

a r t i c l e

i n f o

Article history: Received 27 August 2013 Received in revised form 17 December 2013 Accepted 20 December 2013 Available online 30 December 2013 Keywords: Enterococcus Photoinactivation Gene expression Sunlight Oxidative stress

a b s t r a c t Microarrays were used to investigate the transcriptional response of Enterococcus faecalis to photostress. E. faecalis are Gram-positive bacteria used as indicators of water quality and have been shown to vary diurnally in response to sunlight. E. faecalis in filtered seawater microcosms were exposed to artificial sunlight for 12 h and then placed in the dark for 12 h. Transcript abundance was measured at 0, 2, 6, 12, and 24 h in the sunlit microcosm and a dark control using microarrays. Culturable E. faecalis concentrations decreased 6–7 orders of magnitude within the first 6 h of light exposure. After 12 h in the dark, no evidence of dark-repair was observed. Expression data collected after 12 h of sunlight exposure revealed a difference in transcript abundance in the light relative to dark microcosms for 35 unique ORFs, 33 ORFs showed increased transcript abundance and 2 ORFs showed reduced transcript abundance. A majority (51%) of the ORFs with increased transcript abundance in the sunlit relative to dark microcosms encoded hypothetical proteins; others were associated with protein synthesis, oxidative stress and DNA repair. Results suggest that E. faecalis exposed to sunlight actively transcribe RNA in response to photostress. Ó 2013 Elsevier B.V. All rights reserved.

1. Introduction Contact with microbially contaminated recreational waters can result in gastrointestinal and respiratory illnesses or cutaneous infections [1–4]. Waterborne pathogens include bacteria, viruses, and protozoa. Because monitoring all pathogens is not feasible, enterococci are used as indicators of microbial contamination in recreational waters throughout the world. Culturable enterococcal concentrations vary diurnally in natural waters in response to sunlight, complicating water quality monitoring efforts. Understanding how enterococci respond to sunlight has important implications for their use as water quality indicators, and for assessing public health risks. Enterococci exposed to light in both field and laboratory experiments exhibit a loss of culturability referred to as photoinactivation [5]. Photoinactivation occurs by direct and indirect mechanisms. Direct photoinactivation occurs when cellular components (e.g., nucleic acids) absorb photons resulting in changes to chemical bond structures [6,7]. Indirect photoinactivation occurs when endogenous (intracellular) or exogenous (extracellular) sensitizers absorb photons. Energy or electrons are transferred from the sensitizers to cellular components causing damage to ⇑ Corresponding author. Address: Department of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Mail Code 4020, Stanford, CA 94305, USA. Tel.: +1 650 724 9128; fax: +1 650 723 7058. E-mail address: [email protected] (A.B. Boehm). 1 Present address: The Forsyth Institute, 245 First Street, Cambridge, MA, USA. 1011-1344/$ - see front matter Ó 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jphotobiol.2013.12.013

the cell, or react with molecular oxygen to create reactive oxygen species (ROS) that cause photooxidative damage to membranes, proteins, enzymes or nucleic acids [8–11]. The relative importance of direct and indirect mechanisms is an ongoing field of research. Previous research suggests that oxygen-mediated indirect mechanisms are particularly important for enterococci [12–17]. The exact nature of the enterococcal response to photostress, and the extent to which enterococci have the ability to repair sunlight-induced damage, however, are unknown. The present study uses microarray technology, validated by quantitative polymerase chain reaction (qPCR), to investigate the transcriptional response of Enterococcus faecalis to photostress. Microarrays have been used to investigate the transcriptional responses of bacteria to stresses, including Escherichia coli K-12, Shewanella oneidensis, and Crocosphaera watsonii response to photostress [18–20], E. coli response to magnetic fields [21], Enterococcus faecalis response to the antibiotic erythromycin [22], Salmonella enterica serovar Typhimurium SL1344 response to dehydration [23], Desulfovibrio vulgaris response to heat and oxidative stress [24], Neisseria gonorrhoeae to oxidative stress [25] and Sphingomonas sp. Strain LH128 response to NaCl stress [26]. The observation of differentially expressed genes gave researchers in these studies insight into stress mechanisms. For example, Berney et al. [18] reported that E. coli growing in a chemostat adapted to UVA irradiation, and upregulated genes to address both DNA damage and oxidative stress. The research described above focused on Gram-negative bacteria, with substantially different cell walls and genetic programs than Gram-positive

350

L.M. Sassoubre et al. / Journal of Photochemistry and Photobiology B: Biology 130 (2014) 349–356

bacteria like E. faecalis. The transcriptional response of E. faecalis to photostress has not been investigated and would provide insight into photoinactivation mechanisms of Gram-positive bacteria. The research presented in this paper uses gene expression data to investigate the response of E. faecalis to artificial sunlight. The primary objective was to compare gene expression data from microcosms exposed to artificial sunlight to those kept in the dark, to determine which mRNA transcripts became more abundant or less abundant in response to photostress, and to use this information to gain insight into possible photoinactivation mechanisms. A secondary objective was to determine if E. faecalis exposed to photostress had the ability to repair photo-induced damage, during a 12 h incubation in the dark following 12 h of artificial sunlight exposure. 2. Materials and methods 2.1. Bacterial seed Two containers of 200 ml tryptic soy broth (TSB, BD, Franklin Lakes, NJ) were inoculated with Enterococcus faecalis V583 (ATCC # 700802) from a frozen stock maintained at 80 °C. Cultures were grown to late stationary phase without stirring at 37 °C for 35 h and used to inoculate photoinactivation experiments. We grew cultures to late stationary phase to parallel conditions in the aquatic environment where rapid cell division does not occur. Cells were harvested from growth medium by centrifugation at 4000g for 10 min. Pelleted cells were rinsed twice by resuspending them in phosphate buffered saline (PBS, pH = 7.2, Gibco, Life Technologies, Grand Island, NY) and centrifuging at 4000g for 10 min. 2.2. Experimental design Microcosms consisted of 1200 ml of tangentially filtered seawater collected from Montara State Beach, CA (37°320 41.9700 N 122°300 57.630 0 W) in circular Pyrex glass containers (Corning, Tewksbury MA). The tangential filtration system pumped water through a 30 kDa pore size membrane (Pall Corporation, Port Washington, NY) under pressure. The sides of the Pyrex glass containers were painted flat black to eliminate incidental light filtered through the glass. Microcosms were seeded with 108 CFU/ml rinsed E. faecalis V583, and placed in a dark, 15 °C constant temperature room to acclimate for 1–2 h before beginning experiments. After acclimating, one microcosm, hereafter referred to as the ‘dark microcosm’, was kept in the dark in the 15 °C constant temperature room as a control. The other microcosm, hereafter referred to as the ‘light microcosm’, was placed in a 15 °C water bath and exposed to artificial sunlight in a solar simulator (Altas Suntest CPS+; Linsengericht-Altenhaßlau, Germany) with a 1.1 kW xenon arc lamp with a 560 cm2 exposure area. Light passed through a glass filter that removed UV wavelength transmission below 290 nm [27,28] (Fig. 1). Both light and dark microcosms were slowly, mechanically stirred throughout the experiments. The light microcosm was exposed to 250 W/m2 for 12 h and then placed in the dark in the 15 °C constant temperature room with the dark microcosm for an additional 12 h. The temperature of the light microcosms was measured after 12 h of light exposure and confirmed to be 15 °C ± 5 °C. Three replicate experiments each with one light and one dark microcosm were conducted on three separate days. 2.3. Light spectrum measurements The light spectrum (290–800 nm) was measured using an International Light ILT950 UV/VIS/NIR spectroradiometer (International

Fig. 1. Irradiance (raw data) of artificial sunlight between 250 and 800 nm measured using an International Light ILT950 UV/VIS/NIR spectroradiometer (International Light, Peabody, MA).

Light, Peabody, MA) (Fig. 1). Fluence between 300 nm and 370 nm (a combination of UVB and UVA wavelengths) was also measured using actinometry. The actinometry solution was made of p-nitroanisole with the addition of pyridine (PNA-PYR) following the procedures in Leifer [29]. Briefly, 0.092 g of p-nitroanisole was dissolved in 5 ml of acetonitrile and 120.9 ll of pyridine was added. Milli-Q water was added to a total volume of 1200 ml. 2.4. Sampling procedure During each of the three replicate experiments, we collected samples from both light and dark microcosms at the start of the experiment (t = 0 h), and at 2 h, 6 h, 12 h, and 24 h. At each time point, 100 ll of sample (or a dilution thereof) was spread plated onto tryptic soy agar (TSA, BD, Franklin Lakes, NJ) and incubated at 37 °C for 24 h, to determine culturable E. faecalis counts. Additionally, RNA was isolated from the light and dark microcosms at each time point from 100 ml of water as follows. Cells were immediately pelleted by centrifugation at 4000g for 10 min. Pelleted cells were then resuspended in RNA Bacterial Protect (Qiagen, Valencia, CA) and incubated at room temperature for 5 min. Cells were then pelleted again by centrifugation at 4000g for 10 min, the supernatant discarded and the pellet stored at 20 °C until extraction (completed within a week). 2.5. RNA extraction and microarray preparation Pelleted cells were resuspended in 100 ll of 30 mg/ml lysozyme and 2.5 ll of 5 KU mutanolysin and incubated at 37 °C for 1 h to lyse the cells, further lysis was accomplished with the addition of a bead beating step (Lysing Matrix B tube, MP Biomedicals, Solon, OH) for 4.5 min at 30 s intervals. RNA was extracted using Qiagen RNeasy kit (Qiagen, Valencia, CA), and a total of 40 ll was eluted with RNAse free water warmed to 60 °C. The eluant was DNase treated (Roche) followed by a clean-up using the Qiagen RNeasy kit. PCR for the clpX gene confirmed that there was no DNA contamination relative to a genomic DNA control. The PCR consisted of 25 ll reactions with final concentrations of 1X TaKaRa PCR Buffer, 0.5 lM forward (CGCACACTTTCTGTTGCTG) and reverse (CCATCAAATGCTCCACCAAC) primers, 0.04 U/ll TaKaRa Taq Polymerase, and 200 lM dNTPs (Dr. Kelli Palmer, personal communication). The thermocycling parameters included an initial denaturation step at 95 °C for 5 min followed by 30 cycles of denaturating at 95 °C for 35 s, annealing at 50 °C for 35 s and elongation at 72 °C

L.M. Sassoubre et al. / Journal of Photochemistry and Photobiology B: Biology 130 (2014) 349–356

for 35 s and then a final elongation step at 72 °C for 10 min. We confirmed RNA integrity by visualization on a 1% agarose gel in NorthernMax-Gly running buffer (Ambion, Life Technologies, Grand Island, NY). After DNA removal and RNA integrity were confirmed, cDNA was synthesized, fragmented and labeled. First, 6–12 lg of RNA was mixed with random hexamers (250 ng/ll) (Qiagen, Valencia, CA) and water to a final volume of 30 ll, then incubated at 70 °C for 10 min followed by 25 °C for 10 min. cDNA was synthesized using Superscript II Reverse Transcriptase (Invitrogen), dNTP mix (Invitrogen, Life Sciences, Grand Island, NY), and RNase inhibitor (Ambion, Life Sciences, Grand Island, NY) in a reaction volume of 60 ll. The mixture was incubated at 25 °C for 10 min, followed by 37 °C for 60 min, 42 °C for 60 min and 70 °C for 10 min. RNA was then removed by the addition of 20 ll 1 N sodium hydroxide (NaOH), followed by incubation at 65 °C for 30 min, and then the addition of 20 ll 1 N hydrochloric acid (HCl). The QIAquick PCR purification kit (Qiagen, Valencia, CA) was used to purify cDNA following manufacturer’s directions, except that Buffer PBI was not used. Three micrograms of cDNA were fragmented in DNase I Buffer using Roche DNase I (10,000 U) (Roche Applied Science, Indianapolis, IN), and incubation at 37 °C for 10 min immediately followed by denaturation for 10 min at 98–100 °C. We confirmed fragmentation by visually comparing the fragmented and unfragmented cDNA in a 2% agarose gel with GelStar Nucleic Acid Stain (Lonza, VWR, Radnor, PA). Fragmented cDNA was terminally labeled with the Enzo Bioarray Terminal Labeling Kit (Axxora, Farmingdale, NY) according to the manufacturer’s instructions. Stanford University’s Protein and Nucleic Acid (PAN) Facility hybridized the labeled samples to the custom Affymetrix GeneChip microarrays overnight at 45 °C. PAN used a Affymetrix GeneChip Scanner 3000 7G to read the microarrays. The custom Affymetrix GeneChip microarray was based on St. Louis Antibiotic Resistant Enterococcus-1 (SLARE 1) and has been described previously [30]. It contained a total of 3582 probe sets to 3182 predicted ORFs from the strain V583 chromosome (GenBank AE016830) as well as additional plasmids and antibiotic resistance genes or clusters from other E. faecalis strains and pathogenicity island genes of strain MMH594 not represented inV583 [30]. Most ORFs had unique probe sets, however, approximately 264 ORFs had two or more probe sets. 2.6. Microarray analysis Raw intensity data (CEL files) were processed using the Robust Multichip Average method in RMAExpress [31,32], which included a background adjustment, quantile normalization and summarization by the PLM method [31–34]. The calculated residuals were then plotted using the RMAExpress software to visually check for outliers. The RMAExpress software outputs log2-transformed expression values. Microarray data were submitted to ArrayExpress public repository at http://www.ebi.ac.uk/arrayexpress under accession number E-MTAB-1797. Expression values were used to calculate differential expression and the fold changes for each ORF at 0 h, 2 h, 6 h, and 12 h. Differential expression is defined as the ratio of the expression value of the light microcosm and the expression value of the dark microcosm for a given time point, or, in log2 space, the difference between the light and dark expression values. The fold change (fc) for each ORF was calculated using the average differential expression for P3 1 the three replicate experiments: fcðtÞ ¼ 2½ð3Þ i¼1 ðlighti ðtÞdarki ðtÞÞ , where lighti(t) and darki(t) are the expression values for the light and dark microcosms of the ith replicate experiment at time t. A fold change greater than 1 indicates an increase in expression in the

351

light relative to the dark microcosm while a fold change less than 1 indicates a decrease in expression. Microarray data was further analyzed using the LIMMA (linear models for microarray data) package in R Bioconductor [35]. First, we tested whether there was a difference in transcript abundance between the light and dark microcosms at each experimental time point during light exposure (0 h, 2 h, 6 h, and 12 h). To account for type I errors from multiple hypothesis testing, we used the Benjamini–Hochberg adjustment in LIMMA to determine a False Discovery Rate (FDR) [36]. The FDR represents the expected proportion of false positives out of all the genes deemed significant. We considered transcript abundance to be statistically different in the light and dark microcosms at the tested time points if both the FDR was less than 20% and the fold change in abundance was P2 (increased expression) or 60.5 (decreased expression). Using both a threshold for the FDR and the fold change to determine differentially expressed genes is a conservative approach that has been used previously [18,19,23,26]. The second hypothesis we tested was that the change in transcript abundance for an individual ORF between 12 h and 24 h in the light microcosms was different than the change in abundance for that ORF between 12 h and 24 h in the dark microcosms. The second hypothesis investigated whether dark incubation after 12 h of sunlight exposure resulted in transcriptional activity that suggested an ability to repair light-induced cellular damage. We considered the change in expression values between 12 h and 24 h in the light microcosms to be statistically different from the change in expression values between 12 and 24 h in the dark microcosms if the FDR was less than 20%. Differentially expressed ORFs are identified in this paper by either the gene name or the Open Reading Frame (ORF) probe set that begins with EF followed by a number. The Broad Institute’s EnteroCyc [37], Kyoto Encyclopedia of Genes and Genomes [38], Gene Ontology [39], and Joint Craig Venture Institute Comprehensive Microbial Resource [40] were used to gain insight into specific genes as well as hypothetical proteins. 2.7. Confirmation by qPCR Differential expression was confirmed using qPCR with Taqman chemistry. We selected three genes to confirm the microarray results at 12 h, superoxide dismutase (sodA), thioredoxin (trx), and ribosomal protein (rpsF). One ORF sequence was chosen to be an internal control, EF1920 (a C4 anaerobic carrier protein), because RNA corresponding to this sequence did not exhibit any change in the microarray analysis, suggesting it was not affected by photostress. This approach of choosing an internal control gene has been used previously [23,41]. Primers and probes were designed using Primer Express version 3 (Applied Biosystems) and are listed in Table 1. qPCR included 20 ll reactions with 2 ll of template cDNA, 1X Universal Mastermix (Applied Biosystems), and final primer and probe concentrations of 0.6 lM and 0.08 lM, respectively. Unfragmented cDNA from all the experiments was diluted to 10 ng/ll before being added to the qPCR as template. Dark quencher probes were used (ZEN/Iowa Black FQ, Integrated DNA Technologies). A fluorescence intensity threshold of 0.02 was used for all targets. The amplification efficiency of each primer/probe set was determined using the average slope of duplicate 5 point standard curves based on a 10-fold dilution series of genomic E. faecalis  1  DNA. The efficiency was calculated as 10slope  1  100, where the slope is based on a linear regression of the log10 transformed gDNA concentration (x) and the average quantification cycle (y). We used the average quantification cycle values (Cq) of duplicate reactions for the light and dark microcosms to calculate a fold change based on the previously described relative quantification

352

L.M. Sassoubre et al. / Journal of Photochemistry and Photobiology B: Biology 130 (2014) 349–356

Table 1 Primer and probes used for qPCR confirmation. ORF

Primer

Sequence

Product size (bp)

EF1920

EF1920-F EF1920-R EF1920-P

GATTGCAATGACGGCAACTATC GGTATTTGCGGCGATTACGT TGCCAACACCTTTAGGCGCGGA

67

EF0463

EF0463-F EF0463-R EF0463-P

CCGCACAGCTGTTCGTAACA CCAGCATTTGGTGCCATAATT TGGCGGTCACGCAAACCATACATTC

78

EF1405

EF1405-F EF1405-R EF1405-P

CGACTTTTGGGCAACTTGGT CACTTCGTCTTCATCATATTCTTCAGA TTGCCGTATGCAAGCACCCATCTTAGA

88

EF0007

EF0007-F EF0007-R EF0007-P

CCGTGAAGGCATCTATCATATCG TCGTCATTGATTTTTGCTAAACGA TAATGTTACTTCTCCATCAACAGCTGGCGC

93

Table 2 Differentially expressed ORFs after 12 h of artificial sunlight exposure. Fold changes greater than or equal to 2 represent an increase in transcript abundance in the light relative to the dark microcosms while fold changes less than 1 indicate a decrease in transcript abundance. ORF probe Set

Gene

Gene description

Fold change (fc)

False Discovery Rate (FDR) (%)

EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF EF

rpsF infA rpmJ rpmJ fabZ-1 EF0409 EF0443 sodA EF0478 ptsI EF0723 EF1017 EF1022 rpmF-3 rpmF-3 fba EF1251 trx EF1693 EF1751 EF1905 EF2084 EF2283 EF2305 EF2415 rpsD EF3087 EF3087 EF3088 EF3088 recA EF3247 EF3247 rpmH

Ribosomal protein S6 Translation initiation factor IF-1 Ribosomal protein L36 Ribosomal protein L36 (3R)-hydroxymyristoyl-(acyl-carrier-protein) dehydratase Hypothetical protein LysM domain protein Superoxide dismutase, Mn Hypothetical protein Phosphoenolpyruvate-protein phosphotransferase enzyme I Hypothetical protein PTS system, IIB component Hypothetical protein Ribosomal protein L32 Ribosomal protein L32 Fructose-bisphosphate aldolase class-II Hypothetical protein Thioredoxin KH domain protein Membrane protein, putative Hypothetical protein Hypothetical protein Site-specific recombinase, resolvase family, putative Toprim domain protein Conserved hypothetical protein Ribosomal protein S4 Hypothetical protein Hypothetical protein Hypothetical protein Hypothetical protein recA protein Hypothetical protein Hypothetical protein Ribosomal protein L34 Hypothetical protein Hypothetical protein repE protein Hypothetical protein Hypothetical protein Hypothetical protein Hypothetical protein

2.29 2.11 2.24 2.30 2.04 3.42 2.38 2.04 2.15 2.16 2.18 2.00 2.77 2.84 2.59 2.33 2.25 2.37 2.32 2.03 2.83 2.12 0.48 0.48 2.39 2.20 3.36 3.14 3.32 2.62 2.22 2.43 2.34 2.03 2.09 2.03 2.01 3.62 2.48 2.01 2.35

7 5 15 18 3 0 7 19 14 5 1 8 8 2 6 0 4 14 0 1 1 7 14 3 3 0 0 3 0 0 8 3 7 7 7 0 4% 8 5 5 3

0007 0229 0230a 0230a 0284 0409 0443 0463 0478 0710 0723 1017 1022 1048a 1048a 1167 1251 1405 1693 1751 1905 2084 2283 2305 2415 3070 3087a 3087a 3088a 3088a 3171a 3247a 3247a 3333a A0015a A0017a A0058a B00051a B00051a B0056 C0016

EF A0015, A0058, B00051, B0056, C0016 are from one of three E. faecalis plasmids. a Duplicate probe sets targeting the same ORF.

ðDarktg Lighttg Þ

method, fc ¼

Etg

ðDarkcg Lightcg Þ Ecg

, where ‘‘E’’ refers to log10 of the

efficiency of the assay, ‘‘tg’’ refers to the target gene that showed differential expression in the microarray results, and ‘‘cg’’ refers to the control gene that did not show differential expression in

the microarray results [23,41–43]. We compared the fold changes calculated from the microarray data to the qPCR data. All statistical analyses were conducted using the software R (v3.0.1) [44], Microsoft Excel 2008 (Redmond, WA), and IGOR Pro (Wavemetrics, Lake Oswego, OR).

L.M. Sassoubre et al. / Journal of Photochemistry and Photobiology B: Biology 130 (2014) 349–356

3. Results and discussion 3.1. E. faecalis responses to photostress measured by culture-based and molecular methods Exposure to artificial sunlight photoinactivated E. faecalis. Concentrations measured by culturing on tryptic soy agar in the light microcosms for all three replicate experiments showed first-order decay kinetics between 0 and 6 h (Fig. 2), decreasing approximately 6–7 orders of magnitude at an average light inactivation rate, k = 2.5 ± 0.16 per h (±indicates the standard deviation). E. faecalis concentrations in the light microcosms did not significantly increase or decrease between 6 h and 12 h (paired t-test, p = 0.24). There was no evidence of dark repair in the light microcosms between 12 h and 24 h during which time they were placed into the dark (paired t-test, p = 0.67). In the dark microcosms, E. faecalis concentrations stayed constant throughout the experiment (Fig. 2), confirming the decrease in culturable E. faecalis observed in the light microcosms was due to artificial sunlight exposure. Expression data revealed no ORF was significantly differentially expressed in the light relative to dark microcosms at 0, 2, and 6 h. At 12 h, a total of 41 probe sets showed differences in expression in the light relative to the dark microcosms. Thirty-five unique ORFs were represented, 33 showed increases in transcript abundance and 2 showed decreases in abundance in light relative to dark microcosms (Table 2). Thirty-four of the 41 probe sets targeted 30 unique ORFs on the chromosome while 7 targeted 6 unique ORFs on three plasmids contained in E. faecalis V583, pTEF1, pTEF2 and pTEF3. Taken together, the bacterial concentration and gene expression data suggest that transcriptional activity continued after a large portion of E. faecalis had lost culturability. A small subpopulation in the light microcosms did not lose culturability throughout the experiments. It is not clear if the transcriptional activity observed at 12 h can be attributed to this culturable subpopulation or to non-culturable cells. Previous research observed that nonculturable E. faecalis can be metabolically active [45] and

Fig. 2. Culturable E. faecalis concentrations in triplicate experiments. Each unique symbol represents a different experiment. E. faecalis in the light microcosms were exposed to 12 h of sunlight, after which they were incubated in the dark between the 12 h and 24 h sampling time points. The bottom axis denotes time (hours). The top axes denote cumulative fluence (kJ/m2) between 290 and 800 nm (measured by a spectroradiometer) and 300–370 nm (measured by an actinometer).

353

may still have intact membranes (as measured by a dye based LIVE/DEAD assay) [12]. Additional research is needed to determine whether the small subpopulation of culturable cells or non-culturable yet viable cells are actively involved in cellular processes. 3.2. Differentially expressed ORFs and cellular processes The genes differentially expressed in the light relative to dark microcosms at 12 h were associated with a range of cellular processes (Table 2). Two ORFs showing increased transcript abundance in the light relative to dark microcosms were related to membrane transport and the phosphotransferase system (PTS) (EF0710, phosphoenolpyruvate-protein phosphotransferase enzyme I, ptsI, and EF1017, PTS system IIB component). Two ORFs also showing increased transcript abundance in the light relative to dark were related to fatty acid metabolism and carbohydrate metabolism, specifically glycolysis, (EF0284, fabZ-1, (3R)-hydroxymyristoyl-acyl-carrier-protein dehydratase and EF1167, fba, fructose-bisphosphate aldolase class II, respectively). Additional ORFs for which RNA abundance was greater in the light relative to dark microcosms included those related to oxidative stress (EF0463, sodA), DNA repair (EF3171, recA), DNA replication initiation (EFA0058, repE on plasmid pTEF1), translation initiation (EF0229, infA), cell redox homeostatis (EF1405, trx), RNA binding (KH domain protein), membrane proteins (EF1751), and peptidoglycan binding/cell wall degradation (EF0443, LysM domain protein). Only two ORFs showed decreases in RNA transcript abundance in the light relative to dark microcosms at 12 h, ORF EF2305 encoding the toprim domain protein and EF2283, a putative site-specific recombinase. Both the toprim domain protein and EF2283 are associated with DNA metabolism [40], EF2283 specifically with DNA binding [39]. Fifteen percent (5/33) of the ORFs showing increased transcript abundance in the light relative to dark microcosms were associated with ribosomal proteins. Of the 5 unique ORFs associated with ribosomal proteins, 2 were related to the small subunit (30S) and 3 were related to the large subunit (50S) ribosome. Increased transcript abundance of ORFs encoding ribosomal proteins suggests that E. faecalis cells were actively involved in protein biosynthesis after 12 h of artificial sunlight exposure. Previous research has shown differential expression of genes related to ribosomal structure in bacteria after exposure to stressors. Gruzdev et al. [23] report that the largest group of upregulated genes in Salmonella after being dehydrated belonged to the ribosome structure and biogenesis group. Similarly, 47 out of 55 ribosomal protein-encoding genes were induced in Desulfovibrio exposed to heat stress [24]. Genes encoding ribosomal proteins were also upregulated in Neisseria gonorrhoeae in response to oxidative stress (specifically peroxides) [25]. Hypothetical proteins represented 40% of the probe sets on the entire microarray (1391 out of 3454 probe sets) and 46% (16 of 35) of the unique, differentially expressed ORFs at 12 h. All the differentially expressed ORFs encoding hypothetical proteins showed increased transcript abundance in light relative to dark microcosms. Only one of the hypothetical proteins, EF2415, had an annotated cellular function as a GatB/Yqey family protein [40] reportedly involved in carbon–nitrogen ligase activity [39]. An important portion of the genes whose abundance significantly changed during our experiments were hypothetical proteins with no annotated function. Therefore, we considered their location on the genome to gain insight into their potential function [23] and determine which hypothetical proteins warrant further investigation. Two of the 15 unique hypothetical proteins differentially expressed and without annotations were located next to genes with annotated functions. EF0723, which showed increased

354

L.M. Sassoubre et al. / Journal of Photochemistry and Photobiology B: Biology 130 (2014) 349–356

transcript abundance in the light relative to dark microcosms, is adjacent to EF0724 (gatC) which is involved in translation and EF0722 (DNA ligase) which is involved in DNA replication and repair. Increased transcript abundance of a gene related to DNA repair would be consistent with our finding that recA transcript abundance increased in the light relative to dark microcosms. Another hypothetical protein, EF0409, showed increased transcript abundance and is located between EF0408 and EF0411 both of which are involved in the phototransferase system (PTS). As described earlier, two of the annotated ORFs that showed statistically significant increases in abundance were also involved in the PTS (EF1017 and EF0710, ptsI) suggesting the PTS could be a part of E. faecalis stress response. 3.3. Differential expression of genes involved in bacterial stress response Several of the ORFs with increased transcript abundance after 12 h of sunlight exposure are associated with bacterial stress response. Previous research has demonstrated that environmental stressors induce transcription of multiple genes, and these genes are often similar across different stressors and different species of bacteria [11]. We compared genes found to be differentially expressed in this study to genes associated with stress response more generally in E. faecalis [22,48–53] as well as other bacteria [11,23,24,54–56]. The recombinase A gene, recA, is involved in homologous recombination, DNA repair, and known to be an important part of bacterial stress response. Increased expression of recA specifically in response to photostress has been previously observed in the marine bacterium Vibrio natriegens [57] and E. coli [18]. We observed an increase in recA transcript abundance at 12 h (fc = 2.22 and FDR = 8%) suggesting photostress resulted in DNA damage that E. faecalis cells were actively addressing. The gene, fba, encoding fructose-bisphosphate aldolase which is involved in carbohydrate metabolism, specifically glycolysis, is considered to be a part of E. faecalis stress response. E. faecalis induced into the viable but nonculturable state by incubation in oligotrophic water at 4 °C show increased expression of the fba gene [58]. We observed an increase in fba transcripts at 12 h in the light microcosms (fc = 2.33 and FDR = 0.4%). Desulfovibrio exposed to heat shock induced transcription of 3-oxoacyl-(acyl-carrier-protein) synthase II (fabF) which is associated with fatty acid and phospholipid metabolism. In E. faecalis exposed to 12 h of sunlight, we observed an increase in transcript abundance of (3R)-hydroxymyristoyl-(acylcarrier-protein) dehydratase (EF0284, fabZ-1) (fc = 2.04 and FDR = 3%). E. faecalis exposed to 12 h of photostress appear to be actively repairing DNA damage and engaging in multiple metabolic processes. Based on previous research emphasizing the importance of photooxidative stress for E. faecalis, we did a focused comparison between genes found to be differentially expressed in this study with genes known to be associated with oxidative stress in E. faecalis and other bacteria. Previous research demonstrates the importance of superoxide dismutase in Salmonella and E. coli exposed to reactive oxygen species such as hydrogen peroxide [47], N. gonorrhoeae exposed to peroxides [25], and Staphlococcus aureus in seawater [59]. In the present study, superoxide dismutase in E. faecalis exposed to sunlight for 12 h increased in abundance (fc = 2.04 and FDR = 19%). Thioredoxin encoding genes are thought to play a role in protecting bacteria (specifically Desulfovibrio, S. aureus, N. gonorrhoeae) against oxygen species toxic to cells by helping reduce oxidized disulfide bonds [24,25,54,55]. Thioredoxin gene (trx) transcripts increased in abundance (fc = 2.37 and FDR = 14%) in the light microcosms. NAD(P)H is also an important reducing agent that, along with compounds such as glutathione and thioredoxin, helps maintain a reducing environment in cells

Fig. 3. Comparison between average fold changes calculated from microarray results and qPCR confirmations at 12 h. Error bars on the microarray and qPCR results represent the standard deviation obtained from the triplicate experiments. The standard deviations for the fold changes calculated from the qPCR data were estimated by assuming the efficiencies were 100%.

[54]. RNA transcripts encoding for NAD(P)H reductase were found to increase in Salmonella exposed to hydrogen peroxide [47]. We observed an increased abundance of NADPH-dependent FMN reductase domain-containing protein (EF1698) transcripts in E. faecalis at 12 h but the increase only met one of the two statistical criteria we set (fc = 2.11 and FDR = 23%). One gene identified by Paulsen et al. [53] as having a role in E. faecalis oxidative stress response was also differentially expressed in the present study, EF2739 alkyl hydroperoxidase reductase (ahpC), but the increase only met one of the two statistical criteria we set (fc = 1.75 and FDR = 8%). Alkyl hydroperoxidase reductase is also a part of the OxyR regulon which is the main transcription factor in E. coli response to oxidative stress [18,46,60]. The research presented here suggests that E. faecalis use superoxide dismutase, thioredoxin, NAD(P)H reductase, and alkyl hydroperoxide reductase as part of their defense system against oxidative stress. The observed increase in transcripts associated with oxidative stress response suggests that indirect endogenous photodamage is occurring within the sunlit cells. The importance of oxidative stress in photoinactivating enterococci could be explored in future experiments using mutants for specific genes, such as a sodA mutant. The fold changes we observed in the present study are smaller than many previously published microarray studies that investigated bacterial stress response [23], a finding confirmed by qPCR. In addition, several previously reported E. faecalis stress related genes [53] showed little or no differential expression. One possible explanation is that stress related genes increased in abundance in both the light and dark microcosms in response to photostress and oligotrophy, respectively, so they did not appear differentially expressed at any given time point. Zhang et al. [24] observed this with several stress related genes in Desulfovibrio. Another explanation is that noise inherent in microarray data [61] overshadowed small, but meaningful changes in gene expression. This possibility underscores the importance of careful data analysis when working with microarrays. Finally, additional samples collected more frequently during the experiment might have provided beneficial information about expression changes occurring on shorter timescales. 3.4. Differential expression after dark incubation following exposure to photostress The change in transcript abundance for an individual ORF between 12 h and 24 h in the light microcosms was not different

L.M. Sassoubre et al. / Journal of Photochemistry and Photobiology B: Biology 130 (2014) 349–356

from the change in abundance for that ORF between 12 h and 24 h in the dark microcosms (all ORFs had FDR > 20%). This result suggests that either E. faecalis were not actively repairing photo-induced damage during the 12 h dark incubation following light exposure or any change in transcript abundance was not large enough to be detected by our methods. Previous studies that have observed E. faecalis repair [45,62] incubated the bacteria in a nutrient-rich broth to induce repair mechanisms. The filtered seawater used in this study was oligotrophic, so little to no nutrients were available for cellular repair. 3.5. qPCR confirmation of expression data The expression of genes measured by qPCR confirmed the microarray results (Fig. 3). The fold changes calculated based on the qPCR results agree with the fold changes calculated based on the microarray results. The amplification efficiencies for the qPCR confirmation assays were as follows: 95% for EF1920, 92% for EF0463 (sodA), 86% for EF1405 (trx), and 101% for EF0007 (rspF). 3.6. Concluding remarks The research presented in this paper provides insight into the effect of artificial sunlight exposure on a Gram-positive bacterium in oligotrophic seawater. In response to photostress, E. faecalis concentrations decreased while transcriptional activity increased in the light relative to dark microcosms for multiple cellular processes including protein synthesis, metabolism, and stress response. Both DNA damage and oxidative stress appear to be important consequences of sunlight exposure for E. faecalis. With limited nutrients available in the filtered seawater, E. faecalis showed limited ability to repair damage from photostress. Future research is warranted as many of the ORFs with an increased abundance of transcripts in the light relative to dark microcosms had no annotated function. E. faecalis response to photostress is complex, with multiple cellular processes activated. Acknowledgements This project was funded by NSF OCE-1129270 as well as NIH/ NIAID Grants AI083214 (Harvard-wide Program on Antibiotic Resistance) and AI072360. We thank two anonymous reviewers that provided helpful comments that improved the manuscript. References [1] T.J. Wade, R.L. Calderon, E. Sams, M. Beach, K.P. Brenner, A.H. Williams, A.P. Dufour, Rapidly measured indicators of recreational water quality are predictive of swimming-associated gastrointestinal illness, Environ. Health Perspect. 114 (2006) 24–28. [2] J.M. Colford Jr, T.J. Wade, K.C. Schiff, C.C. Wright, J.G. Griffith, S.K. Sandhu, S. Burns, J. Hayes, M. Sobsey, G. Lovelace, S.B. Weisberg, Water quality indicators and the risk of illness at non-point source beaches in Mission Bay, California, Epidemiology 18 (2007) 27–35. [3] J.M. Fleisher, L.E. Fleming, H.M. Solo-Gabriele, J.K. Kish, C.D. Sinigalliano, L. Plano, S.M. Elmir, J.D. Wang, K. Withum, T. Shibata, M.L. Gidley, A. Abdelzaher, G. He, C. Ortega, X. Zhu, M. Wright, J. Hollenbeck, L.C. Backer, The BEACHES Study: health effects and exposures from non-point source microbial contaminants in subtropical recreational marine waters, Int. J. Epidemiol. 39 (2010) 1291–1298. [4] N. Charoenca, R.S. Fujioka, Association of staphylococcal skin infections and swimming, Water Sci. Technol. 31 (1995) 11–17. [5] R.S. Fujioka, H.H. Hashimoto, E.B. Siwak, R.H.F. Young, Effect of sunlight on survival of indicator bacteria in seawater, Appl. Environ. Microbiol. 41 (1981) 690–696. [6] R.P. Sinha, D.P. Hader, UV-induced DNA damage and repair: a review, Photochem. Photobiol. Sci. 1 (2002) 225–236. [7] J.L. Ravanat, T. Douki, J. Cadet, U.G. Paolo, UV damage to nucleic acid components, Comprehensive Series in Photosciences, Elsevier, 2001 (Chapter 10).

355

[8] F. Bosshard, K. Riedel, T. Schneider, C. Geiser, M. Bucheli, T. Egli, Protein oxidation and aggregation in UVA-irradiated Escherichia coli cells as signs of accelerated cellular senescence, Environ. Microbiol. 12 (2010) 2931–2945. [9] J.A. Imlay, Pathways of oxidative damage, Annu. Rev. Microbiol. 57 (2003) 395–418. [10] T. Maisch, J. Baier, B. Franz, M. Maier, M. Landthaler, R.M. Szeimies, W. Baumler, The role of singlet oxygen and oxygen concentration in photodynamic inactivation of bacteria, Proc. Natl. Acad. Sci. USA 104 (2007) 7223–7228. [11] E.C. Ziegelhoffer, T.J. Donohue, Bacterial responses to photo-oxidative stress, Nat. Rev. Microbiol. 7 (2009) 856–863. [12] L.M. Sassoubre, K.L. Nelson, A.B. Boehm, Mechanisms for photoinactivation of Enterococcus faecalis in seawater, Appl. Environ. Microbiol. 78 (2012) 7776– 7785. [13] F. Bosshard, F. Armand, R. Hamelin, T. Kohn, Human adenovirus sunlight and UVC inactivation mechanisms as examined by qPCR and quantitative proteomics, Appl. Environ. Microbiol. 79 (2013) 1325–1332. [14] T.P. Curtis, D.D. Mara, S.A. Silva, Influence of pH, oxygen, and humic substances on ability of sunlight to damage fecal coliforms in waste stabilization pond water, Appl. Environ. Microbiol. 58 (1992) 1335–1343. [15] R.J. Davies-Colley, A.M. Donnison, D.J. Speed, C.M. Ross, J.W. Nagels, Inactivation of feacal indicator microorganisms in waste stabilization ponds: interactions of environmental factors with sunlight, Water Res. 33 (1999) 1220–1230. [16] R.H. Reed, Solar inactivation of faecal bacteria in water: the critical role of oxygen, Lett. Appl. Microbiol. 24 (1997) 276–280. [17] K. Kadir, K.L. Nelson, Sunlight mediated inactivation mechanisms of Enterococcus faecalis and Escherichia coli in clear water versus waste stabilization pond water, Water Res (2013), http://dx.doi.org/10.1016/ j.watres.2013.10.046. [18] M. Berney, H.U. Weilenmann, T. Egli, Gene expression of Escherichia coli in continuous culture during adaptation to artificial sunlight, Environ. Microbiol. 8 (2006) 1635–1647. [19] X. Qui, G.W. Sundin, L. Wu, J. Zhou, J.M. Tiedje, Comparative analysis of differentially expressed genes in Shewanella oneidensis MR-1 following exposure to UVC, UVB, and UVA radiation, J. Bacteriol. 187 (2005) 3556–3564. [20] T. Shi, I. Ilikchyan, S. Rabouille, J.P. Zehr, Genome-wide analysis of diel gene expression in the unicellular N2-fixing cyanobacterium Crocosphaera watsonii WH 8501, ISME J. 4 (2010) 621–632. [21] S.G. Huwiler, C. Beyer, J. Frohlich, H. Hennecke, T. Egli, D. Schurmann, H. Rehrauer, H.M. Fischer, Genome-wide transcription analysis of Escherichia coli in response to extremely low-frequency magnetic fields, Bioelectromagnetics 33 (2012) 488–496. [22] A. Aakra, H. Vebo, L. Script, H. Hirt, A. Aastveit, V. Kapur, G. Dunny, B. Murray, I.F. Nes, Transcriptional response of Enterococcus faecalis V583 to Erythromycin, Antimicrob. Agents Chemother. (2005) 2246–2259. [23] N. Gruzdev, M. McClelland, S. Porwollik, S. Ofaim, R. Pinto, S. Saldinger-Sela, Global transcriptional analysis of dehydrated Salmonella enterica serovar Typhimurium, Appl. Environ. Microbiol. 78 (2012) 7866–7875. [24] W. Zhang, D.E. Culley, M. Hogan, L. Vitiritti, F.J. Brockman, Oxidative stress and heat-shock responses in Desulfovibrio vulgaris by genome-wide transcriptomic analysis, Antonie Van Leeuwenhoek 90 (2006) 41–55. [25] K.L. Seib, H.J. Wu, S.P. Kidd, M.A. Apicella, M.P. Jennings, A.G. McEwan, Defenses against oxidative stress in Neisseria gonorrhoeae: a system tailored for a challenging environment, Microbiol. Mol. Biol. Rev. : MMBR 70 (2006) 344–361. [26] T.T. Fida, P. Breugelmans, R. Lavigne, E. Coronado, D.R. Johnson, J.R. van der Meer, A.P. Mayer, H.J. Heipieper, J. Hofkens, D. Springael, Exposure to solute stress affects genome-wide expression but not the polycyclic aromatic hydrocarbon-degrading activity of Sphingomonas sp. strain LH128 in biofilms, Appl. Environ. Microbiol. 78 (2012) 8311–8320. [27] M.H. Plumlee, M. Reinhard, Photochemical attenuation of Nnitrosodimethylamine (NDMA) and other nitrosamines in surface water, Environ. Sci. Technol. 41 (2007) 6170–6176. [28] A.Y. Lin, M. Reinhard, Photodegradation of common environmental pharmaceuticals and estrogens in river water, Environ. Toxicol. Chem. SETAC 24 (2005) 1303–1309. [29] A. Leifer, The Kinetics of Environmental Aquatic Photochemistry : Theory and Practice, American Chemical Society, Washington, DC, 1988. [30] S.M. McBride, V.A. Fischetti, D.J. Leblanc, R.C. Moellering Jr., M.S. Gilmore, Genetic diversity among Enterococcus faecalis, PLoS ONE 2 (2007) e582. [31] B.M. Bolstad, R.A. Irizarry, M. Astrand, T.P. Speed, A comparison of normalization methods for high density oligonucleotide array data based on variance and bias, Bioinformatics 19 (2003) 185–193. [32] R.A. Irizarry, B.M. Bolstad, F. Collin, L.M. Cope, B. Hobbs, T.P. Speed, Summaries of Affymetrix GeneChip probe level data, Nucl. Acids Res. 31 (2003) e15. [33] R.A. Irizarry, B. Hobbs, F. Collin, Y.D. Beazer-Barclay, K.J. Antonellis, U. Scherf, T.P. Speed, Exploration, normalization, and summaries of high density oligonucleotide array probe level data, Biostatistics 4 (2003) 249–264. [34] C.F. Bolstad BM, J. Brettschneider, K. Simpson, L. Cope, R.A. Irizarry, T.P. Speed, Quality Assessment of Affymetrix GeneChip Data, Springer, 2005. [35] G.K. Smyth, Linear models and empirical bayes methods for assessing differential expression in microarray experiments, Stat. Appl. Gen. Mol. Biol. 3 (2004). Article3. [36] Y. Benjamini, Y. Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, J. R. Stat. Soc. B 57 (1995) 289–300.

356

L.M. Sassoubre et al. / Journal of Photochemistry and Photobiology B: Biology 130 (2014) 349–356

[37] EnteroCyc, The Broad Institute, http://enterocyc.broadinstitute.org/. [38] KEGG, Kyoto Encyclopedia of Genes and Genomes, http://www.genome.jp/ kegg/. [39] GO, The Gene Ontology, http://www.geneontology.org/. [40] JCVI, Joint Craig Venter Institute Comprehensive Microbial Resource, http:// www.jcvi.org/cms/home/ [41] K.J. Livak, T.D. Schmittgen, Analysis of relative gene expression data using realtime quantitative PCR and the 2(-Delta Delta C(T)) Method, Methods 25 (2001) 402–408. [42] N. Desroche, C. Beltramo, J. Guzzo, Determination of an internal control to apply reverse transcription quantitative PCR to study stress response in the lactic acid bacterium Oenococcus oeni, J. Microbiol. Methods 60 (2005) 325– 333. [43] S. Calvez, H. Prevost, D. Drider, Relative expression of genes involved in the resistance/sensitivity of Enterococcus faecalis JH2-2 to recombinant divercin RV41, Biotechnol. Lett. 30 (2008) 1795–1800. [44] R Core Team, R: A Language and Environment for Statistical Computing, 2013. [45] M.M. Lleo, M.C. Tafi, P. Canepari, Nonculturable Enterococcus faecalis cells are metabolically active and capable of resuming active growth, Syst. Appl. Microbiol. 21 (1998) 333–339. [46] G. Storz, J.A. Imlay, Oxidative stress, Curr. Opin. Microbiol. 2 (1999) 188–194. [47] M.F. Christman, R.W. Morgan, F.S. Jacobson, B.N. Ames, Positive control of a regulon for defenses against oxidative stress and some heat-shock proteins in Salmonella typhimurium, Cell 41 (1985) 753–762. [48] L.A. Bohle, E.M. Faergestad, E. Veiseth-Kent, H. Steinmoen, I.F. Nes, V.G. Eijsink, G. Mathiesen, Identification of proteins related to the stress response in Enterococcus faecalis V583 caused by bovine bile, Proteome Sci. 8 (2010) 37. [49] S. Flahaut, J.M. Laplace, J. Frere, Y. Auffray, The oxidative stress response in Enterococcus faecalis: relationship between H2O2 tolerance and H2O2 stress proteins, Lett. Appl. Microbiol. 26 (1998) 259–264. [50] J.C. Giard, J.M. Laplace, A. Rince, V. Pichereau, A. Benachour, C. Leboeuf, S. Flahaut, Y. Auffray, A. Hartke, The stress proteome of Enterococcus faecalis, Electrophoresis 22 (2001) 2947–2954. [51] A. Rince, M. Uguen, Y. Le Breton, J.C. Giard, S. Flahaut, A. Dufour, Y. Auffray, The Enterococcus faecalis gene encoding the novel general stress protein Gsp62, Microbiology 148 (2002) 703–711. [52] N. Verneuil, M. Sanguinetti, Y. Le Breton, B. Posteraro, G. Fadda, Y. Auffray, A. Hartke, J.C. Giard, Effects of the Enterococcus faecalis hypR gene encoding a new

[53]

[54] [55]

[56]

[57] [58]

[59]

[60]

[61] [62]

transcriptional regulator on oxidative stress response and intracellular survival within macrophages, Infect Immun. 72 (2004) 4424–4431. I.T. Paulsen, L. Banerjei, G.S. Myers, K.E. Nelson, R. Seshadri, T.D. Read, D.E. Fouts, J.A. Eisen, S.R. Gill, J.F. Heidelberg, H. Tettelin, R.J. Dodson, L. Umayam, L. Brinkac, M. Beanan, S. Daugherty, R.T. DeBoy, S. Durkin, J. Kolonay, R. Madupu, W. Nelson, J. Vamathevan, B. Tran, J. Upton, T. Hansen, J. Shetty, H. Khouri, T. Utterback, D. Radune, K.A. Ketchum, B.A. Dougherty, C.M. Fraser, Role of mobile DNA in the evolution of vancomycin-resistant Enterococcus faecalis, Science 299 (2003) 2071–2074. E. Cabiscol, J. Tamarit, J. Ros, Oxidative stress in bacteria and protein damage by reactive oxygen species, Int. Microbiol. 3 (2000) 3–8. O. Uziel, I. Borovok, R. Schreiber, G. Cohen, Y. Aharonowitz, Transcriptional regulation of the Staphylococcus aureus thioredoxin and thioredoxin reductase genes in response to oxygen and disulfide stress, J. Bacteriol. 186 (2004) 326– 334. M. Berney, H.U. Weilenmann, J. Ihssen, C. Bassin, T. Egli, Specific growth rate determines the sensitivity of Escherichia coli to thermal, UVA, and solar disinfection, Appl. Environ. Microbiol. 72 (2006) 2586–2593. M.G. Booth, W.H. Jeffrey, R.V. Miller, RecA Expression in Response to Solar UVR in the Marine Bacterium Vibrio natriegens, Microbiol. Ecol. 42 (2001) 531–539. S. Heim, M. Del Mar Lleo, B. Bonato, C.A. Guzman, P. Canepari, The viable but nonculturable state and starvation are different stress responses of Enterococcus faecalis, as determined by proteome analysis, J. Bacteriol. 184 (2002) 6739–6745. S. Masmoudi, M. Denis, S. Maalej, Inactivation of the gene katA or sodA affects the transient entry into the viable but non-culturable response of Staphylococcus aureus in natural seawater at low temperature, Mar. Pollut. Bull. 60 (2010) 2209–2214. M.F. Christman, G. Storz, B.N. Ames, OxyR, a positive regulator of hydrogen peroxide-inducible genes in Escherichia coli and Salmonella typhimurium, is homologous to a family of bacterial regulatory proteins, Proc. Natl. Acad. Sci. USA 86 (1989) 3484–3488. Y. Tu, G. Stolovitzky, U. Klein, Quantitative noise analysis for gene expression microarray experiments, Proc. Natl. Acad. Sci. USA 99 (2002) 14031–14036. M.M. Lleo, B. Bonato, M.C. Tafi, C. Signoretto, M. Boaretti, P. Canepari, Resuscitation rate in different enterococcal species in the viable but nonculturable state, J. Appl. Microbiol. 91 (2001) 1095–1102.