Our results imply that there are no E. coli strains that have generally high or low levels of persisters; instead, there are different types of persister cells within populations, and each type may be more or less persistent to different antibiotics. Importantly, the variation in persister fractions exists even for antibiotics with nearly identical modes of LDN-193189 action (ciprofloxacin and nalidixic acid). Mechanistically, this suggests that persistence through cell dormancy is not a single, general phenomenon. Instead, check details there

may be distinct physiological states of dormancy, each of which is differently susceptible to a particular antibiotic. The idea that there are different types of persister cells that arise from a variety of mechanisms has also been proposed in a recently published study [34]. We note that one complicating factor in this interpretation is that these different persister populations may have different Eltanexor order propensities to form colonies, and that this might explain some of the differences in the shapes of the kill curves that we observed. However, given the range of persister fractions that we observed (over four orders of magnitude), we do not think that this mechanism can fully explain the patterns that we find. It is also possible that

although the isolates that we studied have similar MIC values, they differ in their pharmacodynamics [35]. However, the persister fraction should largely be independent of

the pharmacodynamic behavior; thus this is unlikely to account for the differences that we observe between isolates [34]. Evidence of two different types of persister cells has been shown previously by Balaban et al. [6], and genotypic changes at different loci were associated with each phenotype. Similarly, genetic differences between different E. coli isolates, such as the presence or absence of TA various modules, may affect the production of persister cells (Figure 6). Gefen et al. [36] suggested that large differences in the measurement of persister fractions might arise because antibiotic Ponatinib in vitro exposure begins at different stages of exponential growth (before or after 1.5 hours of growth). However, by growing the cells for four hours, we hope to have minimized such effects, and propose that the large differences we find in persister fractions are not due to differences in growth stage, but to fundamental differences in the mechanisms of persister production. We note that the set of environment isolates that we have used are not known to be pathogenic, suggesting that many of them have had less exposure to antibiotics and the concomitant selection for resistant or persister phenotypes that arises from such exposure.

According to our Northern blot findings and previously published microarray data [35], gudB, encoding glutamate dehydrogenase, and rocD, encoding ornithine aminotransferase, seemed https://www.selleckchem.com/products/byl719.html to be co-transcribed. Interestingly, this operon contains three putative cre-sites (see Additional file 3: CcpA-dependent

down-regulation by glucose), suggesting a complex transcriptional regulation by CcpA, which could be confirmed by our Northern blot analyses, showing that rocD/gudB-transcription is largely affected by CcpA in response to glucose. Similarly, aldA, arg, and rocA transcription patterns determined by Northern analyses showed the same tendency as our microarray data (Fig. 2). Table 4 shows genes coding for transporters or lipoproteins which were regulated by glucose in a CcpA-dependent manner or which were partially controlled by CcpA. Seven of these genes contained putative cre-sites in their promoter regions, or as in the case of SA0186, SA0302, and

gntP, belonged to an operon which contained a putative cre-site and were probably under the direct control of CcpA. The up-regulation of the glucose uptake protein homologue (SA2053) may contribute to the rapid glucose consumption observed in the wild-type (Fig. 1). Many putative non-sugar-transporters were found to be regulated by CcpA: MM-102 research buy Amongst them, the selleck opu-operon, which is preceded by a putative cre-site and consists of opuCA-opuCB-opuCC-opuCD, coding for a glycine-betaine/carnitine/choline ABC transporter, acting in osmoprotection [36], was up-regulated by glucose. Interestingly, the same operon is also up-regulated in femAB mutants, due to a secondary effect compensating for an impaired cell envelope [37]. S. aureus possesses two systems involved in osmoprotection [36], the second system encoded

by the opuD gene did not appear to be regulated by CcpA. Table 4 CcpA-dependent genes coding for transport/binding proteins and lipoproteins regulated by glucose ID   Producta wt mut N315 Newman common   +/- Dolutegravir molecular weight b +/- b Down-regulated by glucose SA0100 NWMN_0049   similar to Na+ Pi-cotransporter 0.2 1.7 *SA0186 NWNM_0136   sucrose-specific PTS tranporter IIBC component protein 0.4 1.2 *SA0302 NWNM_0255   probable pyrimidine nucleoside transport protein 0.4 1.8 SA1848 NWNM_1950 nrgA probable ammonium transporter 0.4 0.8 SA2226 NWNM_2337   similar to D-serine/D-alanine/glycine transporter 0.2 0.9 SA2227 NWNM_2337   amino acid ABC transporter homologue 0.1 0.9 Up-regulated by glucose SA0166 NWNM_0116   similar to nitrate transporter 2.8 1.1 SA0167 NWNM_0117   similar to membrane lipoprotein SrpL 2.8 1.6 SA0168 NWNM_0118   similar to probable permease of ABC transporter 2.3 1.1 SA0214 NWMN_0158 uhpT hexose phosphate transport protein 2.1 1.1 SA0335 NWMN_0340   twin-arginine translocation protein TatA 2.2 1.4 SA0374 NWNM_0379 pbuX xanthine permease 7.2 1.1 *SA0655 NWNM_0669 fruA fructose specific permease 2.4 1.

Primers used for sequencing are displayed in Additional file 2 Table S2. PCR products were purified by using ExoSAP-IT (USB, Cleveland, USA) and DNA sequencing reactions were performed in both directions using BigDyeTerminator v3.1 (Applied Biosystems, Selleckchem CA4P Nieuwerkerk a/d IJssel, the Netherlands)

on a 48-capillary 3730 DNA Analyzer sequencer (Applied Biosystems, Nieuwerkerk a/d IJssel, the Netherlands). Accession numbers: HQ222846 to HQ222861 and HQ606074. PCR and real-time qPCR Oligonucleotides were synthesized by Biolegio (Biolegio, Nijmegen, the Netherlands). Conventional PCR was used to produce amplicons from signature sequences. Amplification was carried out using the HotStar Taq Master Mix Kit (Qiagen, Westburg, the Netherlands) and 400 nM primers in a total reaction volume of 50 μl. Primer sets were designed using Visual OMP software (Additional file 2 Table S2). Thermocycling conditions Temsirolimus mouse were as follows: 95°C for 15 min, 40 cycles at 95°C for 30 sec, 55°C for 30 sec and 72°C for 30 sec, followed by a final step at 72°C for 7 min.

Thermocycling reactions were carried out in a Px2 thermal cycler (Thermo Electron Corporation, Breda, the Netherlands). All qPCR reactions were carried out in a final volume of 20 μl containing iQ Multiplex Powermix (Bio-Rad, Veenendaal, the Netherlands), 200 nM of each primer and 100-300 nM hydrolysis probes and 3 μl of DNA template. Probes concentrations had been optimized to yield minimal spectral overlap between fluorescence level of the reporter dyes for each target in a multiplex assay and were 100, 200, 300 and 300 nM for FAM, JOE, CFR590 and Cy5 labeled probes respectively. The multiplex real-time qPCR selleck inhibitor assays had been designed for an optimal annealing temperature of 60°C and the thermal cycling conditions were as follows: First enzyme activation at 95°C for 5 min, followed by amplification and detection by 45 cycles at 95°C for 5 sec and 60°C for 35 sec. Each real-time

qPCR experiment included a negative (no template) control. Measurements were carried out on a Lightcycler 480 3-mercaptopyruvate sulfurtransferase (Roche, Almere, the Netherlands). An iQ5 (Bio-Rad) instrument was used for routine screening purposes. Analyses were performed on the instruments software: LightCycler 480 Software release 1.5.0. SP3 and iQ5 Optical Systems Software version 2.0. Cq values were calculated using the second derivative method on the LightCycler and the Base Line Subtracted Curve Fit method on the iQ5. Color compensations were carried out on both instruments as follows. PCR amplifications were performed using single primer-probe sets for each reporter dye and under identical reaction conditions as during multiplex amplification. The PCR reactions thus produced contained single dyes in relevant concentrations and these were used for color compensation runs according to the manufacturers’ guidelines.

Acknowledgments The authors are grateful to Mrs. Manuela Breiter, Mrs. Birgitt Hartmann, Mrs. Ilona Marquardt, and Mr. Joachim Döll, all from Ilmenau University of Technology, for their help with the sample preparation. This work was partially supported by a grant (NanoBatt TNA VII-1/2012) from the state of Thuringia (TMWAT by LEG Thüringen) and co-financed by the European Union within the frame of the European Funds for Regional Development (EFRD). Electronic supplementary material Additional

file 1: Supporting information. Ordered arrays of nanoporous silicon nanopillars and silicon nanopillars with nanoporous shells. (PDF 2 MB) References 1. Schmidt V, Riel H, Senz S, Karg S, Riess W, Gösele U: Realization of a silicon nanowire vertical surround-gate OSI-027 price field-effect transistor. Small 2006, 2:85–88.https://www.selleckchem.com/products/torin-2.html CrossRef 2. Goldberger J, Hochbaum AI, Fan R, Yang P: Silicon vertically integrated nanowire Pifithrin-�� nmr field effect transistors. Nano Lett 2006, 6:973–977.CrossRef 3. Kanemitsu Y: Light emission from porous silicon and related materials. Phys Rep 1995, 263:1–91.CrossRef 4. Hochbaum AI, Chen R, Delgado RD, Liang W, Garnett EC, Najarian M, Majumdar A, Yang P: Enhanced thermoelectric performance of rough silicon nanowires. Nature 2008, 451:163–167.CrossRef 5. Tian B, Zheng X, Kempa TJ, Fang Y, Yu N, Yu G, Huang J, Lieber CM: Coaxial silicon nanowires as solar cells and nanoelectronic power sources. Nature 2007, 449:885–889.CrossRef

6. Cui Y, Wei Q, Park H, Lieber CM: Nanowire nanosensors for highly sensitive and selective detection of biological and chemical species. Science 2001, 293:1289–1292.CrossRef 7. Chang SW, Oh J, Boles ST, Thompson CV: Fabrication 3-mercaptopyruvate sulfurtransferase of silicon nanopillar-based nanocapacitor arrays. Appl Phys Lett 2010, 96:153108–3.CrossRef 8. Chan CK, Peng H, Liu G, McIlwrath K, Zhang XF, Huggins RA, Cui Y: High-performance lithium battery anodes using silicon nanowires. Nat Nano 2008, 3:31–35.CrossRef 9. Cullis AG, Canham LT, Calcott PDJ: The structural and luminescence properties of porous silicon. J Appl Phys 1997, 82:909–965.CrossRef 10. Archer RJ: Stain films on silicon.

J Phys Chem Solids 1960, 14:104–110.CrossRef 11. Li X, Bohn PW: Metal-assisted chemical etching in HF/H2O2 produces porous silicon. Appl Phys Lett 2000, 77:2572–2574.CrossRef 12. Chartier C, Bastide S, Lévy-Clément C: Metal-assisted chemical etching of silicon in HF-H2O2. Electrochim Acta 2008, 53:5509–5516.CrossRef 13. Peng KQ, Hu JJ, Yan YJ, Wu Y, Fang H, Xu Y, Lee ST, Zhu J: Fabrication of single-crystalline silicon nanowires by scratching a silicon surface with catalytic metal particles. Adv Funct Mater 2006, 16:387–394.CrossRef 14. Huang Z, Geyer N, Werner P, de Boor J, Gösele U: Metal-assisted chemical etching of silicon: a review. Adv Mater 2011, 23:285–308.CrossRef 15. Hochbaum AI, Gargas D, Hwang YJ, Yang P: Single crystalline mesoporous silicon nanowires. Nano Lett 2009, 9:3550–3554.CrossRef 16.

This observation is concordant with the parallel increment in specificity, and indicates that environmental selectivity manifests mainly at genus or species level. Focusing in families, Figure 2 illustrates their representation in the

diverse environments. It is apparent that most families can be found in many different environments, with only a few presenting a clear-cut specificity. According to the specificity criterion cited above, just 3 out of the 211 families (1.4%, see Figure 2) will be specific for environmental types: two Clostridia (Lachnospiraceae and Oscillospiraceae), SB-715992 research buy and the gamma-proteobacterial family Succinivibrionaceae, all of them specific for the gastro-intestinal tract of animals (Additional file 1, Table S1). These are strictly anaerobic chemoorganotrophs that are found in the rumen

of cattle, SAR302503 purchase sheep and other animals. The distribution of different species within these families can nevertheless be quite heterogeneous depending on the diet of the animal, according to the available carbon and energy sources [24]. When using the broader classification of environmental supertypes with the same criteria, we found specificity for 13 families (6.1%), mainly from thermal and host-associated habitats (Figure 2, and Additional file 1, Table S1). No specific families were found, however, when using the most detailed classification of environmental subtypes. Hence, we can say that under this criterion, specificity is a rare event in taxonomic families. If we relax Monoiodotyrosine the specificity criterion,

the number of putative specific families increases, but such criteria are probably too loose and inadequate for determining specificity. Figure 2 Distribution of individual taxonomic families in the different environment types. The phylogenetic tree shown in the inner circle was created by taking one representative sequence from each family, and was arbitrarily rooted in the branch separating bacteria from archaea. Families are coloured by its corresponding phyla, and only families with 10 or more observations have been considered. The bars in the outer circle indicate the number of times that each family has been observed in a sample from a particular environment. The bars marked with stars have been reduced to one third of their original size, for clarity purposes. This figure was done using iTOL server[42]. In contrast, cosmopolitanism seems to be more common for families, with their members well distributed in most environments. Two clear examples can be found in Pseudomonadaceae or Flavobacteriaceae. By defining a cosmopolitan family as having five or more observations in 90% of the environments, we found that 111, 23 and 4 families met these criteria for environmental supertypes, types and subtypes, respectively (Figure 2 and Additional file 1, Table S1). Therefore, for that taxonomic level, there is more likelihood of https://www.selleckchem.com/products/ABT-888.html finding instances of cosmopolitanism than of specificity.

However, such events may not be observed if an identical cycling program is adopted. Perhaps, more exercise sessions, or sessions of greater duration may be undertaken with cycling as an exercise medium, before a significant increase in basal hepcidin levels is recorded. Additionally, despite any variations in hepcidin, this did not appear to influence serum iron parameters in RTB and CTB. This study supports the idea that basal hepcidin levels may increase (due to an accumulation of

acute exercise-induced responses) over the course of an extended training program; although Adriamycin it remains to be see more established if such a response may compromise an individual’s ability to absorb and recycle iron, which may explain the high incidence of iron selleckchem deficiency commonly reported in athletes. Acknowledgements Debbie Trinder is the recipient of a Senior Research Fellowship from the National Health and Medical Research Council of Australia (APP1020437). References 1. Lukaski HC: Vitamin and mineral status: effects on physical performance. Nutrition 2004,20(7–8):632–644.PubMedCrossRef 2. Peeling P, Dawson B, Goodman C, Landers G, Trinder D: Athletic induced

iron deficiency: new insights into the role of inflammation, cytokines and hormones. Eur J Appl Physiol 2008,103(4):381–391.PubMedCrossRef 3. Newlin MK, Williams S, McNamara T, Tjalsma H, Swinkels DW, Haymes EM: The effects of acute exercise bouts on hepcidin in women. Int J Sport Nutr Exer Metab 2012,22(2):79–88. 4. Peeling P, Dawson B, Goodman C, Landers G, Wiegerinck E, Swinkels D, Trinder D: Training surface and intensity: inflammation, hemolysis, and hepcidin expression. Med Sci Sport Exer 2009,41(5):1138–1145.CrossRef 5. Peeling P, Dawson B, Goodman C, Landers

G, Wiegerinck E, Swinkels D, Trinder D: Cumulative effects of consecutive running sessions on hemolysis, inflammation and hepcidin activity. Eur J Appl Physiol 2009,106(1):51–59.PubMedCrossRef 6. Peeling P, Dawson B, Goodman C, Landers G, Wiegerinck E, Swinkels D, Trinder D: Effects of exercise on hepcidin response and iron metabolism during recovery. Int J Sport Nutr Exer Metab 2009,19(6):583–597. 7. Sim M, Dawson B, Landers G, Swinkels DW, Tjalsma H, Trinder D, Peeling P: check Effect of exercise modality and intensity on post-exercise interleukin-6 and hepcidin levels. Int J Sport Nutr Exer Metab 2013,23(2):178–186. 8. Sim M, Dawson B, Landers G, Swinkels DW, Tjalsma H, Yeap BB, Trinder D, Peeling P: Oral contraception does not alter typical post-exercise interleukin-6 and, hepcidin levels in females. J Science Med Sport 2013. in press 9. Sim M, Dawson B, Landers G, Wiegerinck ET, Swinkels DW, Townsend M-A, Trinder D, Peeling P: The effects of carbohydrate ingestion during endurance running on post-exercise inflammation and hepcidin levels. Eur J Appl Physiol 2012,112(5):1889–1898.PubMedCrossRef 10.

Third, our study only involved the ingestion of isolated carbohydrate (in the form of dextrose) and lipid (in the form of heavy whipping

cream) meals. The inclusion of protein meals [40], or mixed meals [1], may have resulted in different findings. Fourth, we only included a measure of total testosterone, and not free testosterone, which is the most biologically active state of testosterone comprising about 0.2-2% of total testosterone [34]. It is possible that free testosterone may have responded differently to feeding. Fifth, other hormones involved in anabolism and catabolism, such as growth hormone, were not measured. Measurement of additional hormones may have provided further insight into the impact of feeding on postprandial hormonal response. MK0683 research buy Finally, the inclusion of exercise within the research design could have introduced another variable which may have impacted our findings [6]. Further research in this area may consider the above limitations in order to improve upon the study design. Conclusions Our data indicate HSP inhibitor that acute feeding of either lipid or carbohydrate of varying size has

little impact on serum testosterone or cortisol during the acute postprandial period. Serum insulin is significantly increased by carbohydrate feedings, but not lipid feedings. Future work should consider the inclusion of older and metabolically compromised individuals, as well Elongation factor 2 kinase as women, in an effort to determine their response to single macronutrient feeding of different loads. These

studies may also consider the use of multiple meals of a particular macronutrient to gather data regarding how these hormones are affected during a 24 hour cycle. This would further clarify whether the changes in cortisol and testosterone are indeed impacted by feeding or if they simply follow their diurnal cycle. References 1. Habito RC, Ball MJ: Postprandial changes in sex hormones after meals of different composition. Metabolism 2001, 50:505–511.PubMedCrossRef 2. Mikulski T, Ziemba A, Nazar K: Metabolic and hormonal responses to body carbohydrate store depletion followed by high or low carbohydrate meal in sedentary and physically active subjects. J Physiol Pharmacol 2010, 61:193–200.PubMed 3. El Khoury D, Hwalla N: Metabolic and appetite BKM120 clinical trial hormone responses of hyperinsulinemic normoglycemic males to meals with varied macronutrient compositions. Ann Nutr Metab 2010, 57:59–67.PubMedCrossRef 4. Martens MJ, Rutters F, Lemmens SG, Born JM, Westerterp-Plantenga MS: Effects of single macronutrients on serum cortisol concentrations in normal weight men. Physiol Behav 2010, 101:563–567.PubMedCrossRef 5. Meikle AW, Cardoso de Sousa JC, Hanzalova J, Murray DK: Oleic acid inhibits cholesteryl esterase and cholesterol utilization for testosterone synthesis in mouse Leydig cells. Metabolism 1996, 45:293–299.PubMedCrossRef 6.

The ribonucleoside monophosphates are further phosphorylated to their RXDX-101 datasheet triphosphate forms, and are then incorporated into RNA, or the diphosphate forms can be reduced by ribonucleotide reductase to produce precursors for DNA synthesis https://www.selleckchem.com/products/azd5363.html (Figure 4). Of 17 genes involved in nucleotide biosynthesis, 15 are essential [33, 34]. Therefore, it has been suggested that this

pathway may be a therapeutic target for future development of antibiotics [42]. Figure 4 Schematic overview of M. pneumoniae nucleotide biosynthesis . Hx, hypoxanthine; Gua, guanine; Ura, uracil; Thy, thymine; dT, thymidine; dA, deoxyadenosine; dC deoxycytidine; dG, deoxyguanosine; PRPP, selleck phosphoribosyl pyrophosphate; NMP, nucleoside monophosphate; NDP, nucleoside diphosphate, NTP, nucleoside triphosphate; dNDP, deoxynucleoside diphosphate; dNTP, deoxynucleoside

triphosphate; TFT, trifluorothymidine; TFT-MP, trifluorothymidine monophosphate; TFT-TP, trifluorothymidine triphosphate; 5FdU-MP, 5-fluorodeoxyuridine monophosphate; 5FdU-TP, 5-fluorodeoxyuridine triphosphate; dFdC-DP, gemcitabine diphosphate; dFdC-TP, gemcitabine triphosphate; 6-TG, 6-thioguanine; 6-TG-TP, 6-thioguanine triphosphate. Enzymes: hpt, hypoxanthine guanine phosphoribosyl transferase (MPN672); apt, adenine phosphoribosyl transferase (MPN395); upp, uracil phosphoribosyl transferase (MPN033); deoA, thymidine phosphorylase (MPN064); tdk, thymidine kinase (MPN044); thyA, thymidylate synthase (MPN320); tmk, thymidylate kinase (MPN006); adk, adenylate kinase (MPN185); gmk, guanylate kinase (MPN246); cmk, cytidylate kinase (MPN476); nrdE/nrdF, ribonucleotide reductase (MPN322 and MPN324); pyrH, uridylate kinase (MPN632); deoxyadenosine kinase (MPN386). I = inhibition. Our screening of 30 FDA-approved anticancer and antiviral nucleoside analogs revealed seven potent inhibitors of Mpn growth with MIC values at clinically check details achievable plasma concentrations. Nucleoside and nucleobase analogs

used in anticancer and antiviral therapy are prodrugs. In order to exert their therapeutic potential they have to compete with natural substrates for uptake (e.g. transport across plasma membrane) and metabolism (e.g. enzymes that activate them to their active forms). Once phosphorylated these analogs are trapped inside the cells and further metabolized to their active form by cellular enzymes, therefore, competition/inhibition of enzymes (e.g. TK or HPRT) in the initial phosphorylation step would also affect the uptake and metabolism of these compounds, and thus their cytotoxic effect (Figure 4). As shown in Table 2, dipyridamole and 6-TG inhibited Hx and Gua uptake and metabolism but not Ade or Ura, suggesting that HPRT may be an immediate target. Pyrimidine nucleoside analogs e.g.

It is known that for

the preservation of muscle and an adequate level of physical performance during a restricted diet a minimum of 135 g of protein per day is necessary Transmembrane Transporters inhibitor for a subject of 80 kg. Eaton suggests that in ancestral humans, protein provided about 30% of daily energy intake (which corresponds to an intake of approximately 3 g/kg per day for a 70 kg individual consuming 12 500 kJ (3000 kcal)/d [63]. In our study, it can be observed that despite a significant decrease of fat percentage and fat absolute amount, the strength performances remained stable after 30 days of VLCKD. Recently we have summarized the factors involved in the fat loss effect of VLCKD diets [12]: 1. Satiety effect of proteins leading to appetite reduction in which also ketone bodies AZD8931 research buy may have a role, although the mechanism is not clear;   2. >Reduction in lipid synthesis and increased lipolysis mechanisms;   3. Reduction in at rest respiratory quotient and therefore an increase in fat metabolism for energy use;   4. Increased metabolic expenditure caused by gluconeogenesis and the thermic effect of proteins.   The maintenance (or strictly speaking

the visible increase, albeit not significant) of the amount of lean body mass, muscle and percentage of muscle during the period of VLCKD needs to be underlined and this muscle sparing effect can be explained through the mechanism of ketosis. As stated before, fatty acids which are normally used as a major PTK6 fuel for some tissues such as muscle, cannot be used by the CNS because they cannot cross the blood–brain barrier. During starvation (fasting) this becomes a problem, particularly for organisms such as humans in which CNS metabolism constitutes a major portion of the resting basal metabolic rate (~20%). During the initial fasting period our body provides glucose for the metabolic needs of the CNS via break down of muscle tissue to provide the amino acid precursors

for gluconeogenesis. Obviously the organism could not survive long under such wasting conditions and ketone bodies (KB) therefore represent an alternate fat-based fuel source that spares muscle protein [12]. It is noteworthy that the mechanism underlying the increase of body fat Cell Cycle inhibitor utilization has some pathways in common with mechanisms contributing to the lack of muscle mass increase. The use of FFA and ketones for muscle fuel spares muscle protein and is thus anti-catabolic. During the ketogenic period, whilst blood glucose decreases by a small amount, remaining at around 80–90 mg/dl, insulin remains at very low levels (7 mU/L) [58, 64, 65]. Insulin is involved in increased liposynthesis and decreased lipolysis so a reduction in insulin levels facilitates mobilization from fat stores; on the other hand insulin is fundamental for the muscle growth pathway (via IGF-1, mTOR, AKT etc.).

Phorbol-myristate -acetate (PMA, 1 μM) or butyric acid (2 mM) was used as a positive control for Caco-2/ap1-luc-1 or HT-29/ap1-luc-6 reporter cells respectively. Luciferase p38 MAPK inhibitors clinical trials activity was measured using the ONE-Glo™. Luciferase Assay System (Promega) according to the manufacturer’s instructions and quantified as relative luminescence units (RLU). All measurements were performed using a microplate reader (Infinite 200, Tecan). Statistical analysis Data are expressed as a mean ± standard error (SEM) calculated over three independent

experiments performed in triplicate. Analysis of statistical significance were performed by ANOVA with Bonferroni post hoc test (adhesion and cytotoxicity assays) or Student’s t-test (IL-8 secretion, NF-κB and AP-1 activation assays) Acknowledgements This work was supported by a BRI grant (Bourse Régionale Industrielle) from the Région Haute-Normandie this website and BIOGALENYS. OL is supported by the European Community’s Seventh Framework RG7112 concentration Programme (FP7/2007-2013): MetaHIT, grant agreement HEALTH-F4-2007-201052. We thank Mihai Covasa and Christine Farmer for revising the English manuscript. References 1. Hirakata Y, Izumikawa K, Yamaguchi T, Igimi S, Furuya N, Maesaki S, Tomono K, Yamada Y, Kohno S, Yamaguchi K, et al.:

Adherence to and penetration of human intestinal Caco-2 epithelial cell monolayers by Pseudomonas aeruginosa . Infect Immun 1998,66(4):1748–1751.PubMed 2. Plotkowski selleck MC, de Bentzmann S, Pereira SH, Zahm JM, Bajolet-Laudinat O, Roger P, Puchelle E: Pseudomonas aeruginosa internalization by human epithelial respiratory cells depends on cell differentiation, polarity, and junctional complex integrity. Am J Respir Cell Mol Biol 1999,20(5):880–890.PubMed 3. Zaborina O, Kohler JE, Wang Y, Bethel C, Shevchenko O, Wu L, Turner JR, Alverdy JC: Identification of multi-drug resistant Pseudomonas aeruginosa clinical

isolates that are highly disruptive to the intestinal epithelial barrier. Ann Clin Microbiol Antimicrob 2006, 5:14.PubMedCrossRef 4. Chapalain A, Rossignol G, Lesouhaitier O, Merieau A, Gruffaz C, Guerillon J, Meyer JM, Orange N, Feuilloley MG: Comparative study of 7 fluorescent pseudomonad clinical isolates. Can J Microbiol 2008,54(1):19–27.PubMedCrossRef 5. Rajmohan S, Dodd CE, Waites WM: Enzymes from isolates of Pseudomonas fluorescens involved in food spoilage. J Appl Microbiol 2002,93(2):205–213.PubMedCrossRef 6. Wei B, Huang T, Dalwadi H, Sutton CL, Bruckner D, Braun J: Pseudomonas fluorescens encodes the Crohn’s disease-associated I2 sequence and T-cell superantigen. Infect Immun 2002,70(12):6567–6575.PubMedCrossRef 7. Sutton CL, Kim J, Yamane A, Dalwadi H, Wei B, Landers C, Targan SR, Braun J: Identification of a novel bacterial sequence associated with Crohn’s disease. Gastroenterology 2000,119(1):23–31.PubMedCrossRef 8. Dalwadi H, Wei B, Kronenberg M, Sutton CL, Braun J: The Crohn’s disease-associated bacterial protein I2 is a novel enteric t cell superantigen.