Nucleic Acids Res 2007,35(2):W58-W62.PubMedCrossRef 26. Hume ME, Barbosa NA, Dowd SE, Sakomura NK, Nalian AG, Martynova-Van Kley A, Oviedo-Rondon EO: Use of pyrosequencing and denaturing gradient gel electrophoresis to examine the effects of probiotics and essential oil blends on digestive microflora in broilers under mixed eimeria infection. Foodborne Pathog Dis 2011,8(11):1159–1167.PubMedCrossRef 27. Jakobsson HE, Jernberg C, Andersson AF, Sjolund-Karlsson M, Jansson JK, Engstrand L: Short-term antibiotic selleck chemicals treatment has differing long-term impacts on the human throat and gut microbiome. PLoS One 2010,5(3):e9836.PubMedCrossRef 28. Mushegian AA, Peterson CN, Baker CCM, Pringle

A: Bacterial diversity across individual lichens. Appl Environ Microbiol 2011,77(12):4249–4252.PubMedCrossRef 29. Marsh TL, Saxman P, Cole J, Tiedje J: Terminal restriction fragment length polymorphism analysis program, a web-based research tool for microbial community analysis. Appl Environ Microbiol 2000,66(8):3616–3620.PubMedCrossRef 30. Junier P, Junier T, Witzel KP: TRiFLe, a program for in silico terminal restriction fragment length polymorphism analysis with user-defined sequence sets. Appl Environ Microbiol 2008,74(20):6452–6456.PubMedCrossRef 31. Fernandez-Guerra A, Buchan A, Mou X, Casamayor EO, Gonzalez JM: T-RFPred: a nucleotide sequence size prediction tool for microbial community description based

on terminal-restriction fragment length polymorphism chromatograms. BMC Microbiol 2010, 10:262.PubMedCrossRef https://www.selleckchem.com/products/GDC-0941.html 32. Aeppli C, Hofstetter TB, Amaral

HIF, Kipfer R, Schwarzenbach RP, Berg M: Quantifying in situ transformation rates of chlorinated ethenes by combining compound-specific stable isotope analysis, groundwater dating, and carbon isotope mass balances. Environ Sci Technol 2010,44(10):3705–3711.PubMedCrossRef 33. Shani N: Assessing the Bacterial Ecology of Organohalide Respiration for the Design of Bioremediation Strategies. Ecole selleck products Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; 2012. [PhD thesis #5379] http://​biblion.​epfl.​ch/​EPFL/​theses/​2012/​5379/​EPFL_​TH5379.​pdf 34. Weissbrodt DG, Lochmatter S, Ebrahimi S, Rossi P, Maillard J, Holliger C: Bacterial selection during the formation of early-stage aerobic granules in wastewater treatment systems operated under wash-out dynamics. Front Microbiol 2012, 3:332.PubMed 35. Ebrahimi S, Gabus S, Rohrbach-Brandt E, Hosseini M, Rossi P, Maillard J, Holliger C: Performance and microbial community composition dynamics of aerobic granular sludge from sequencing batch bubble column reactors operated at 20°C, 30°C, and 35°C. Appl Microbiol Biotechnol 2010, 87:1555–1568.PubMedCrossRef 36. Rees G, Baldwin D, Watson G, Perryman S, Nielsen D: Ordination and significance testing of microbial community composition derived from terminal restriction fragment length polymorphisms: application of multivariate statistics.

SplitTree analysis. The concatenated sequences from the SBT loci for all STs were used as input for the SplitTree program (version 4.12.3) and the Neighbor-net algorithm used to draw a tree. The phi test for recombination as implemented in this program was performed.   Recombination within genes (intragenic) Two approaches were taken a. Running the recombination tests within the RDP3 suite [43]. A locus was considered to have

undergone significant recombination if two or more of the tests in the RDP3 suite were positive.   b. Applying the Sawyer’s AMN-107 run test (Implemented in Start 2).   Clustering algorithms eBURST eBURST was used to cluster strains using the default settings: grouping strains sharing

alleles at ≥ 6 of the 7 loci with at least one other ST in each group. The number of re-samplings for bootstrapping was 1000 [26]. Bayesian Analysis of Population Structure (BAPS) This methodology is described in detail in the references [27-29]. Clustering of individuals was performed on allelic data from STs formatted in GENEPOP format. Ten runs were performed setting an upper limit of 20 clusters. Admixture analysis was performed using the following parameters: minimum population size considered 5, iterations 50, number of reference individuals simulated from each population 50, number of iterations for each reference individual 10. BAPS analysis was also carried out using the clustering of linked molecular data functionality. The sequence data were saved in Excel (Microsoft) format. https://www.selleckchem.com/products/c646.html The same parameters for clustering and admixture were oxyclozanide used as for the allelic data. Whole genome sequencing Strains Strains used in the study were either sequenced by Next Generation Sequencing (NGS) technologies or available through GenBank

(Table  3). At the time of the study the EWGLI SBT database contained data from 4272 strains from 43 countries (date 09/06/2010). The authors’ strain collection of strains in the database comprises 1110 clinical and environmental isolates, representing 222 ST obtained from 33 countries around the world. Although 77% of these were obtained from UK many of these STs are found worldwide and thus selecting strains only from the authors’ collection is unlikely to introduce a significant geographical bias. Strains were selected from the authors’ collection to represent all 15 BAPS clusters derived from SBT sequence data (Figure  4). The ST that was nearest to a notional centroid of each cluster was calculated as described below. Where possible this ‘nearest to centroid’ ST was used as a representative of the cluster for sequencing purposes. In all but one case, at least one other strain with a different ST from the ‘centroid ST’ was sequenced for each cluster. Where possible these strains were selected because the ST is of public health significance. Details are given in Table  3.

Emerg Infect Dis 2002, 8:843–849.PubMed 9. Lan NTN, Lien HTK, Tung LB, Borgdorff MW, Kremer K, van Soolingen

D:Mycobaterium tuberculosis Beijing genotype and risk for treatment failure and relapse, Vietnam. Emerg Infect Selleck EPZ004777 Dis 2003,9(12):1633–1635.PubMed 10. Vree M, Bui DD, Dinh NS, Nguyen VC, Borgdorff MVV, Cobelens FG: Tuberculosis trends. Vietnam. Emerg Infect Dis 2007,13(5):796–797.PubMed 11. European Concerted Action on New Generation Genetic Markers and Techniques for the Epidemiology and Control of Tuberculosis: Beijing/W genotype Mycobacterium tuberculosis and drug resistance. Emerg Infect Dis 2006, 12:736–743. 12. Marais BJ, Victor TC, Hesseling AC, Barnard M, Jordaan A, Brittle W, Reuter H, Beyers N, van Helden PD, Warren RM, Schaaf HS: Beijing and Haarlem genotypes are overrepresented among children with drug-resistant tuberculosis in the Western Cape Province of South Africa. J Clin Microbiol 2006,44(10):3539–43.CrossRefPubMed 13. Lipin MY, Stepanshina VN, Shemyakin IG, Shinnick TM: Association of specific

mutations in kat G, rpoB, rpsL and rrs genes with spoligotypes of multidrug-resistant GSK1838705A in vitro Mycobacterium tuberculosis isolates in Russia. Clin Microbiol Infect 2007,13(6):620–6.CrossRefPubMed 14. Middlebrook G, Cohn ML: Some observations on the pathogenicity of isoniazid-resistant variants of tubercle bacilli. Science 1953, 118:297–299.CrossRefPubMed 15. Zhang M, Yue J, Yang Y, Zhang H, Lei J, Jin R, Zhang X, Wang H: Detection of Mutations Associated with Isoniazid Resistance in Mycobacterium tuberculosis Isolates from China. J Clin Microbiol 2005, 43:5477–5482.CrossRefPubMed 16. Sherman

DR, Mdluli K, Hickey MJ, Arain TM, Morris SL, Barry CE, Stover CK: Compensatory ahp C gene expression in isoniazid-resistant Mycobacterium tuberculosis. Science 1996, 272:1641–1643.CrossRefPubMed 17. Marttila HJ, Soini H, Eerola E, Vyshnevskaya E, Vyshnevskiy BI, Otten TF, Vasilyef AV, Viljanen MK: MycoClean Mycoplasma Removal Kit A Ser315Thr substitution in Kat G is predominant in genetically heterogeneous multidrug-resistant Mycobacterium tuberculosis isolates originating from the St Petersburg area in Russia. Antimicrob Agents Chemother 1998, 42:2443–2445.PubMed 18. van Soolingen D, de Haas PE, van Doorn HR, Kuijper E, Rinder H, Borgdorff MW: Mutations at amino acid position 315 of the kat G gene are associated with high-level resistance to isoniazid, other drug resistance, and successful transmission of Mycobacterium tuberculosis in the Netherlands. J Infect Dis 2000, 182:1788–1790.CrossRefPubMed 19. Pym AS, Saint-Joanis B, Cole ST: Effect of kat G Mutations on the Virulence of Mycobacterium tuberculosis and the Implication for Transmission in Humans. Infection and Immunity 2002, 70:4955–4960.CrossRefPubMed 20.

32-qter (17%) was observable in all passages of a series (case number 445). The genomic region 1q21.1-qter frequently displayed gain. Changes in copy number were acquired during the growth period of xenografts including gains at 2q35-q37.3, 4q13.3-qter, 8p11.21-p21.2 and 8q and losses at 8p, 17p, 13, Xq21.1, 1p13.3-p31.1, 5q, 11q13.4-q24.3, Xq12-q26.3 and 16q. In one xenograft Selleckchem Target Selective Inhibitor Library series (Case number 488), loss of 17q12-q21.32, that was present in the early passages, disappeared

during the growth process. The loss of 1p36.12-pter in the first two passages originating from lung metastasis (1 and 4) changed to loss of 1p36.21-pter in the last three passages (14, 21, and 30). The lung metastasis xenografts showed 9 copy number changes, whereas only 3 of these aberrations were observable in the xenograft passages from its primary tumor. Table 2 The copy number changes present in all the passages of each xenograft series Case No. (Nude) Array CGH results 488 (15) +1q21.1-qter, -13q14.12-qter

445 (22) -2q35-q37.3 (uncontinuous), + 8, +15, +17q21.32-qter 451 (53) -1q24.3-q25.2, – 3p12.3-p24.3, -9p21.3 455 (199) +1q, -16q, -9p21.3 430 (PRI) (230) -9p21.3 430 (MET) (248) -1p36.12-pter, -9p21.3 PRI = Primary Tumor, MET = Lung Metastasis Table 3 Copy number changes present in only part of the passages of each xenograft series Case Nude- Passage Array CGH result 488 15- 2, 4, 7, 11, 14 -2q35-q37.3 488 15- 1, 2, 4, 7 -17q12-q21.32 488 15- 14 +17 451 53- 11, 15,18, 21 +4q13.3-qter, -17p 455 199- 5, 11, 17, 25 -13 455 199- 25 -Xq21.1 430 (PRI) 230- Tipifarnib 1, 4, 9, 19 +8p11.21-p21.2, +8q 430 (MET) 248- 1, 4 -1p36.12-pter 430 (MET) 248- 14, 21, 30 -1p36.21-pter, -1p13.3-p31.1, -5q,     -11q13.4-q24.3, -Xq12-q26.3 430 (MET) 248- 21, 30 +8p11.21-p21.2, +8q 430 (MET) 248- 30 -16q PRI = Primary Tumor, MET = Lung Metastasis Figure 1 Copy number changes on each chromosome were ordered using hierarchical clustering. Most of the

xenograft passages of each series clustered together and also with the passage 0, its corresponding primary tumor. MicroRNA alterations in xenografts Differences in miRNA expression between xenografts and control samples were detected upon analysis (Figure 2). Exclusively expressed miRNAs were detected; two in control samples Dimethyl sulfoxide (miR-31, miR-31*) and 46 in all xenograft passages (Table 4). In addition, 5 miRNAs (miR-106b, miR-93, miR-181b, miR-101, miR-30b) were significantly over-expressed (q-value < 0.05), while 6 miRNAs (miR-145, miR-193a-3p, miR-100, miR-22, miR-21, miR-574-3p) were significantly under-expressed across the xenograft passages in relation to the controls (q-value < 0.05). Xenografts from primary and control samples were compared to xenograft passages from the lung metastasis (Case number 430), to determine differences in miRNA expression.

Different genes with the same predicted function, such as putative metallopeptidases (LIC11149 and LIC10271),

sensor or receiver proteins of two-component response regulators (LIC20012, LIC11201, LIC12807, LIC12979 and LIC13289), and adenylate/guanylate cyclase (LIC10900 and LIC11095) were found to be regulated in opposite directions. buy RXDX-101 LIC20012, an ortholog of hklep encoding a sensor kinase of the Hklep/Rrlep two-component system involved in heme biosynthesis in L. biflexa [54], was down-regulated. However, an ortholog of rrlep regulator (LIC20013) was not differentially expressed. Moreover, predicted anti-sigma factor (LIC13344) and anti-sigma factor antagonists (LIC10344 and LIC20108) were down-regulated in response to serum. Bacterial anti-sigma factors and anti-sigma factor antagonists are regulatory proteins that control sigma-factor functions in promoter recognition and initiation of RNA polymerase required for cell viability and stress response [55]. Anti-sigma factors bind to and block their cognate sigma factors, while anti-sigma factor antagonists

(or anti-anti-sigma factors) form complexes with anti-sigma factors to inhibit their activity. These findings may be attributed to the fact that the genome of L. interrogans is predicted to contain at least 79 genes encoding two-component sensor histidine kinase-response RG7420 mw regulator proteins, 9 anti-sigma factors, and 19 anti-sigma factor antagonists required for response to various environmental signals [34]. Therefore, complex stimuli in serum encountered by Leptospira may simultaneously cause induction and repression of multiple genes involved in signal transduction networks and transcriptional regulation, possibly leading to expression of genes essential for survival under stress conditions and/or pathogenicity of leptospires inside the host. Detailed study of these individual genes is thus clearly warranted. The gene encoding Tau-protein kinase the LigB lipoprotein was up-regulated in response to serum. LigB interacts with fibronectin and may

serve as an adhesin by binding to host extracellular matrix during the early stages of infection [56–58]. However, recent studies with site-directed mutagenesis of ligB did not show attenuation of a ligB mutant in the hamster model of leptospirosis [59]. This finding does not exclude the role of LigB as a virulence determinant, since previous studies have shown redundancy in extracellular matrix-binding function of leptospiral proteins including a 36-kDa fibronectin-binding protein [60], Lsa24 (also known as LfhA and LenA)[61, 62], LigA [16], Len proteins [62], LipL32 [63], and Lsa21 [17]. Our finding is therefore consistent with the hypothesis that LigB plays a role in virulence, but is not essential. The lpxD (LIC13469) gene encoding UDP-3-O-(3-hydroxymyristoyl) glucosamine N-acyltransferase, which catalyzes the third step of lipid A biosynthesis [64], was up-regulated in response to serum.

Singapore Med J 2000, 41:177–178.PubMed 24. Wu A-B, Wang https://www.selleckchem.com/products/epoxomicin-bu-4061t.html M-C, Tseng C-C, et al.: Clinical and microbiological characteristics of community-acquired Staphylococcus lugdunensis infections in Southern Taiwan. J Clin Microbiol 2011, 49:3015–3018.PubMedCrossRef 25. Pereira EM, Teixeria CA, Alvarenga AL,

et al.: A Brazilian lineage of Staphylococcus lugdunensis presenting rough colony morphology may adhere to and invade lung epithelial cells. J Med Microbiol 2012, 61:463–469.PubMedCrossRef 26. Chatzigeorgious KS, Siafakas N, Peinaki E, Zerva L: fbl gene as a species-specific target for Staphylococcus lugdunensis identification. J Clin Lab Anal 2010, 24:119–122.CrossRef 27. Schnitzler N, Meilicke R, Conrads G, Frank D, Haase G: Staphylococcus lugdunensis: Report of a case of peritonitis and an easy-to-perform

screening strategy. J Clin Microbiol 1998, 36:812–813.PubMed 28. Frank KL, Hanssen AD, Patel R: icaA is not a useful diagnostic marker for prosthetic joint infection. J Clin Microbiol 2004, 42:4846–4849.PubMedCrossRef 29. Trampuz A, Piper KE, Jacobson MJ, et al.: Sonication of removed hip and knee prostheses for diagnosis of infection. N Engl J Med 2007, 357:654–663.PubMedCrossRef 30. Becker K, Pagnier I, Schuhen B, et al.: Does nasal cocolonization by methicillin-resistant coagulase-negative www.selleckchem.com/products/MK-2206.html staphylococci and methicillin-susceptible Staphylococcus aureus strains occur frequently enough to represent a risk of false-positive methicillin-resistant S. aureus determinations by molecular methods? J Clin Microbiol 2006,

44:229–231.PubMedCrossRef 31. Pereira EM, Schuenck RP, Nouer SA, et al.: Methicillin-resistant Staphylococcus lugdunensis carrying SCCmec type V misidentified as MRSA. Braz J Infect Dis 2011, 15:293–295.PubMed 32. van der Mee-Marquet N, Achard A, Mereghetti L, et al.: Staphylococcus lugdunensis infections: high frequency of inguinal area cartilage. J Clin Microbiol 2003, 41:1404–1409.PubMedCrossRef 33. Zhang Z, Schwartz S, Wagner L, Miller W: A greedy algorithm for aligning DNA sequences. J Comput Biol 2000, 7:203–214.PubMedCrossRef 34. Clinical and Laboratory Standards Institute: Performance standards for antimicrobial susceptibility testing: 19th informational supplement. CLSI document M100-S21. Clinical and Laboratory Standards Institute, Carnitine dehydrogenase Wayne, PA; 2011. 35. Lina G, Quaglia A, Reverdy ME, Leclercq R, Vandenesch F, Etienne J: Distribution of genes encoding resistance to macrolides, lincosamides, and streptogramins among staphylococci. Antimicrob Agents Chemother 1999, 43:1062–1066.PubMed 36. Khan SA, Nawaz MS, Khan AA, Cerniglia CE: Simultaneous detection of erythromycin-resistant methylase genes ermA and ermC from Staphylococcus spp. by multiplex-PCR. Mol Cell Probes 1999, 13:381–387.PubMedCrossRef 37. Rohrer S, Tschierske M, Zbinden R, Berger-Bächi B: Improved methods for detection of methicillin-resistant Staphylococcus aureus. Eur J Clin Microbiol 2001, 20:267–270.

Authors’ contributions AB designed portions of the study, conducted all the experiments, and wrote the manuscript. JACH analyzed and interpreted data and critically revised the manuscript. MSF participated in data analysis. ANH coordinated the project, designed portions of the study, and helped draft and revise the manuscript. All authors have read and approved the final manuscript.”
“Background Sinorhizobium meliloti is a soil-born α-proteobacterium that can enter a nitrogen-fixing symbiosis with

Medicago sativa (alfalfa) and related legumes. The establishment of the symbiosis relies on a complex molecular dialogue between the two partners that triggers two essential and overlapping steps, nodulation and infection (see [1, 2] for reviews).

During the infection process, bacteria colonize root hairs forming Infection CHIR-99021 mw Threads (ITs) that extend and proliferate towards the nodule primordium that is formed in the root cortex. Ultimately, rhizobia find more are released from ITs within nodule cells where they fix molecular dinitrogen. Nodulation and infection are tightly controlled processes and we have shown recently that bacterial adenylate cyclases (ACs) contribute to the negative autoregulation of infection [3]. ACs (EC 4.6.1.1) are enzymes that synthesize cAMP (3′, 5′-cyclic adenosine monophosphate) from ATP. There are 6 non-homologous classes of ACs as a typical example of convergent evolution [4, 5]. Class III is the universal class whose members can be found in both prokaryotes and eukaryotes although, to our knowledge, their presence in plants has not been established [6]. The number of class III ACs strikingly varies in bacteria. E. coli has none whereas cyanobacteria, mycobacteria and rhizobia, a group of phylogenetically-diverse bacteria [7], have many, up to 32 in the soybean symbiont Bradyrhizobium japonicum. triclocarban The biological function of class III ACs in bacteria remains poorly understood. Class III ACs synthesize cAMP in response to environmental cues such as light, oxygen, nitrogen and pH in Cyanobacteria [8] or high osmotic pressure in Myxococcus xanthus[9, 10]. Class III

ACs are also involved in biotic interactions as they contribute to virulence in M. tuberculosis, P. aeruginosa and in some fungal pathogens [5, 11–13]. CO2 and Ca2+ are signals used by pathogens to sense their host environment through their AC–cAMP signaling systems. Candida albicans and mycobacteria express CO2-responsive ACs [5, 14] whereas CyaB from P. aeruginosa is Ca2+ sensitive. Another example of cAMP-associated signal being used by the human fungal pathogen C. albicans to sense the host environment is the bacterial peptidoglycan present in blood serum [15]. We have recently described the first instance of class III ACs contributing to a symbiotic (mutualistic) interaction, between Sinorhizobium meliloti and its host plant Medicago sativa[3]. S.

5 %) tumor tissues, while the increased expression of EGFR protein was found in 41 (34.2 %) tumor tissues. In lung adenocarcinoma, the increased expression of EGFR protein was found in 19 (40.4 %) tumor cases and, in squamous cell carcinoma, 22 (30.1 %) cases had LY2835219 cell line overexpressed EGFR protein (P = 0.246). Furthermore, we found that the

increased expression of EGFR protein was more frequent in lymph node metastasis of NSCLC compared to non-metastatic NSCLCs (27 vs. 14 or 45 % vs. 23.3 %; P = 0.009). Expression of EGFR protein also associated with tumor stages. Increase EGFR protein expression was more frequently observed in patients with IIIA and IIIB compared to those in I and IIA. But there was no association AZD8186 ic50 of EGFR expression with other clinicopathological data from NSCLC patients (Table 1). Differential expression of KRAS mRNA and protein in NSCLC Expression of KRAS mRNA and protein in 120 cases of NSCLC and adjacent normal tissue specimens is summarized in Figure 1A and Figure 2A. By comparison of normal and tumor expression of KRAS mRNA and protein at a ratio of 2.0 as a cutoff point, we found that expression of KRAS mRNA and protein was significantly increased in NSCLC compared the non-tumor tissues (P = 0.03 and P = 0.018, respectively). Specifically,

increased expression of KRAS mRNA was found in 52 (43 %) tumor tissues, while the increased expression of KRAS protein was found in 54 (45 %) tumor tissues. Moreover, the increased expression of KRAS protein was found in 17 (36.2 %) adenocarcinoma samples PLEK2 and in 37 (50.7 %) squamous cell carcinoma samples. Increased expression of KRAS protein was more frequent in squamous cell carcinomas and in lymph node metastasis compared to non-metastatic tumors (34 vs. 20 or 56.7 % vs. 33.3 %; P = 0.01). Expression of KRAS protein was associated with tumor stages and also occurred more frequently in ever-smokers (P = 0.002; Table 1). RBM5, EGFR and KRAS expression correlations in NSCLC We examined the relationship between expression of RBM5, EGFR, and KRAS in NSCLC and found that expression of RBM5 mRNA and protein

was significantly negatively correlated with expression of EGFR and KRAS mRNA and protein in NSCLC tissues (p < 0.01; Tables 2 and 3). Table 2 Association of RBM5 with EGFR and KRAS mRNA expression   EGFR-T KRAS-T RBM5-T     Correlation coefficient −0.961 −0.809 Sig.(2-tailed)A 0.000** 0.000** N 120 120 aP-values represent asymptotic two-tailed significance with asterisks denoting **P < 0.01, from the Spearman`s rho test. Table 3 Association of RBM5, EGFR, and KRAS proteins expression   EGFR-T KRAS-T RBM5-T     Correlation coefficient −0.943 −0.842 Sig. (2-tailed)A 0.000** 0.000** N 120 120 aP-values represent asymptotic two-tailed significance with asterisks denoting **P < 0.01, from the Spearman`s rho test.

This process was repeated twice to ensure purity. Phage purity was confirmed using PCR assays. Amplification of phage stocks was achieved by modifying previous methods [53]. Briefly, mid-exponential phase PAO1 cultures (100 ml) were infected with purified LES phage (MOI = 0.1), at 37°C for 2 h. Lysed cultures were filter-sterilized. Electron microscopy Phage suspensions (1×109 – 1×1010 p.f.u. ml-1) were concentrated by centrifugation, negatively stained with 2% (w/v) uranyl acetate [54], and examined by transmission electron microscopy (magnification x 200,000). Multiplex PCR to confirm pure phage stocks and lysogens Three primer sets,

LESnest1 F/R, Clust6nest F/R and 4tot1 F/R (Table 4), for the detection of LES phages 2, 3 and 4 respectively, were combined in a multiplex PCR find more assay for confirmation of each pure phage stock and each PLPL. Colony or filtered phage suspensions were used as templates in each reaction as described previously [25]. Table 4 Primer sequences Primer Sequence (5′-3′) Amplicon (bp) Cycling conditions Reference Multiplex PCR: LES1nestF tttggtgatgatcggcttagc 289 95°C,

4 min then 30 cycles: 95°C, 30 s; 58°C, 30 s; 72°C, 30 s; final extension step, 72°C, 7 min; [25] LES1nestR tgtggaagcgatcagtct       Clust6nestF ggatcgacgtggcataatctg 410   [25] Clust6nestR acgattctccggcatgcagcg       4tot1F gctcatgagtggctgacaac 105   This study 4tot1R tcttgggcagagaaccattc       Q-PCR: 2pro3F caagccctgtctggattttc 102 95°C, 10 min; then 40 cycles: 95°C, 10 s; 60°C, 15 s; 72°C s. This study 2pro3R gagacaggttgggagggagt       3tot1F cgcaggtaccaccagacttt 122   This study 3tot1R catgtccagcaggttcaaaa       3pro3F gcggatgttctcaaacgaat find protocol 134   This study 3pro3R cgggagaagcaatgacctac     Staurosporine cost   4tot1F gctcatgagtggctgacaac 105   This study 4tot1R tcttgggcagagaaccattc       4pro3F tcgtgctgtgctgatctttt 172   This study 4pro3R agcagtgccagttgatgttg       Preparation of DIG-labeled probes: φ2intDIGF tgcctatctaacggggttca 1097 95°C, 4 min. 30 cycles: 95°C, 30 s; 55°C, 30 s; 72°C, 1 min s; final extension step, 72°C, 7 min This study φ2intDIGR gaagcaaccgagaagtggag     φ3intDIGF ggatcatgtagcgggaaaga 874 This study φ3intDIGR agaacctggcgaaagtctga     φ4cIDIGF atcgttaattggcacggaat

893 This study φ4cIDIGR acagcaacggatttccactc     tot = to quantify total phage copies; pro = to quantify total phage copies. Quantifying production of each LES phage from LESB58 Replication of each LES phage in response to induction of the lytic cycle was compared using Q-PCR to distinguish and enumerate each specific phage type. LESB58 induction experiments were performed on three separate occasions in the presence and absence of norfloxacin for 30 and 60 min exposure times before the 2 h recovery step. DNA was prepared from each replicate using the Bacterial and Virus DNA extraction kit (QIAGEN) and the automated QIAsymphony machine (QIAGEN; pathogen complex 200 protocol). Q-PCR was performed using six specific primer sets to differentiate between prophage and total copies of each phage.

18), and the nrfA (SO3980) genes. cymA (SO4591; ratio 0.39), the prismane protein hcp gene (SO1363), and neighboring protein hcr gene (SO1364), both of which were strongly repressed (ratios ≤ 0.13) and have been associated with the nitrate reduction pathway [24–27], did not show evidence of EtrA binding sites. Also indirectly down-regulated were the fumarate reductase genes Anlotinib ic50 frdAB (SO0398-0399) and fccA (SO0970), the ackA and the pta (SO2915-16) genes involved

in acetate production and the ppc (SO0274) gene encoding an acetate phosphoenol pyruvate carboxylase. The hyaCBA (SO2097-2099) genes encoding a quinone-reactive Ni/Fe hydrogenase were highly indirectly repressed (ratio ≤ 0.11). Among the genes identified as directly down-regulated are all the genes in the operon that encodes the anaerobic DMSO reductase (dmsAB) MLN2238 purchase (SO1428-32), the cydAB

genes (SO3285-3286) encoding a cytochrome d oxidase complex, as well as genes involved in metabolism of organic compounds such as the pflAB (SO2912-2913). Other down-regulated genes grouped in different categories included genes encoding ABC transporters (cydCD [SO3779-3780], SO4446-4448), TonB-dependent receptors (nosA [SO0630]), and L-lactate permease (lldP [SO0827]) and a putative lactate permease (SO1522). The only gene directly down-regulated from this later group is lldP (SO0827), for which an EtrA binding site was predicted (Table 3). As expected, the cDNA for etrA, shows no significant hybridization signal in EtrA7-1 mutant (ratio 0.05). Stress response caused by the etrA deletion We detected induction of

genes from Etofibrate various categories, which have been associated with stress response i.e., starvation, phage infection and oxidative stress, possibly due to accumulation of nitrogen oxide reactive species. Up-regulated genes (Additional file 1) were dominated by genes grouped in “”Other categories”". The majority of up-regulated genes were phage-related. For example, 25 genes of the LambdaSo phage (SO2940-2974), a gene encoding a viral capsid protein of the MuSo1 phage (SO0675), and genes of MuSo2 phage (SO2684-2685, SO2687, SO2702) were up-regulated. In contrast, the gene encoding the LambdaSo phage transcriptional regulator of the Cro/CI family (SO2990) was down-regulated (ratio 0.43). Transcriptional changes of most of these genes are likely indirect effects due to the deletion of the etrA gene and only for the LambdaSo phage genes S02957-2962 was an EtrA binding site predicted. The category “”Transport and binding proteins”" contains a large number of genes associated with stress response.