Neither Wolbachia nor B. malayi have a life-cycle that can be maintained in vitro. Because of this, traditional drug discovery by high throughput compound screening is not feasible, nor are the basic gene essentiality experiments which are informative to rational drug design. The genomes of both B. malayi and wBm have been sequenced [27, 28]; however, only B. malayi has a closely related, well characterized model organism,

Caenorhabditis elegans. Previous work has used C. elegans functional genomics data to predict drug targets in B. malayi [9]. Wolbachia, however, has no close relatives in which functional genomics data is available. Functional genomics information from a large number of more distantly related bacteria can be used to infer similar information CHIR98014 in vivo in an intractable species [29, 30]. Here we present such an approach, utilizing bioinformatic techniques to rank the likelihood of gene essentiality across the DNA Damage inhibitor wBm genome, for the purpose of facilitating the selection of potential new drug targets. A combination of approaches were used to predict genes likely to be important to the survival of wBm. First, we used comparative sequence analysis to identify wBm genes with strong protein sequence similarity to experimentally identified essential genes in more distantly related bacteria. Second, in order to identify genes important to the biological

niche inhabited by wBm, gene conservation across its parent order, Rickettsiales was evaluated. The first approach identifies genes broadly important across bacterial life. The second approach reinforces the genes identified by the first, while additionally identifying genes likely to have importance specifically within Rickettsiales. Consideration of these properties during

drug target selection can optimize for development of either a more broad spectrum antibiotic, or a more targeted compound, reducing the side effects related to clearing of the natural biotic flora. Results Predicting essential genes in wBm by protein sequence comparison to essential genes in distantly related bacteria While wBm is not amenable to experimental gene essentiality analysis, knockout and knockdown studies in multiple other bacterial species can serve as a proxy. The why results of a number of these analyses are compiled in a publicly Ku 0059436 available resource called the Database of Essential Genes (DEG). This database contains 5,260 genes from 15 different bacterial strains [3] (Table 1). In most cases, the genes within DEG were identified by large scale knock-out or knock-down screens performed under rich media conditions. Rich media conditions are thought to approximate the growth environment of intracellular bacteria [16]. This makes the collection of genes within DEG a useful model for the gene requirements of wBm. DEG contains a binary description of gene essentiality.

aureus strains isolated from hospitalized patients (4 MRSA and 4 MSSA) examined with respect of their ability to survive after PDI treatment, showed different pattern of response. Based on statistical analysis we divided those strains into two groups: sensitive and resistant to PDI. In the group of resistant strains (2002, 4246, click here 1397, 7259) the drop in the survival rate did not exceed 1.5 log10 units. In the second group of strains, called sensitive, (472, 80/0, 2288, 5491) the drop in survival rate was at least 1.5 log10 units reduction in viable counts. In our previous reports we already showed a strain-dependent response to PDI targeted

S. aureus cells, where the observed efficacy of photokilling reached even 5 log10 units reduction. The differences between our previous studies and the one presented

here might have probably resulted from a different photosensitizer used – PpIX vs. protoporphyrin IX diarginate (PpIXArg2) [24, 25]. Other groups also observed the phenomenon of PDI-strain dependence, however, the mechanism underlying the diverse response to PDI was not explored [43, 44]. Our data shows that at lower concentration of a photosensitizer (10 μM) a substantial drop in bacterial survival occurred, whereas at 17-AAG supplier higher NU7441 manufacturer concentrations (25-50 μM), no further decrease in survival was noticed. We associate this phenomenon with poor solubility of PpIX in water solutions but the solubility itself does not justify the observed variability in killing curves. Similar results were obtained by the group of Wilson (2008). In the study they used another anionic photosensitizer, indocyanine green (ICG) against S. aureus and observed that the concentration of 25 μg/ml resulted in 6 log10 units reduction in viable counts, but higher ICG concentrations (50 Etoposide chemical structure and 100 μg/ml), resulted in lesser, about 4 and 5 log10 units reduction in survival counts, respectively [45]. Possible explanation of this phenomenon may be the self shielding effect of the non-bound PS in solution at higher concentrations. Effective

photodynamic therapy is a result of a combination of several factors. Beside the biophysical properties of a sensitizer itself, also total light delivered, time of incubation with a photosensitizer, presence of additional proteins are crucial. In our work we did not focused on examining the dependence of killing rate vs. light dose. We performed all photodynamic inactivation studies on one light dose (12 J/cm2) chosen as optimal based on our previously published data concerning S. aureus photoinactivation as well as phototoxicity assays performed on dermal human fibroblasts [46, 47]. In our previous attempts to explore the differences of porphyrin-based photokilling towards S. aureus cells, we found biofilm production ability to correlate with higher resistance to PDI treatment. However, it was also noted that among S. aureus isolates with elevated resistance to PDI, biofilm non-producing strains were also observed.

As illustrated in Fig 2, the 4 most predominant lineages comprised both PGG1 and PGG2/3 lineages: Latin-American Mediterranean (LAM), n = 165 or 37.1% (PGG 2/3); ancestral East African-Indian (EAI), n = 132 or 29.7% (PGG1); an evolutionary recent but yet ill-defined T clade, n = 52 or 11.7% (PGG 2/3); and the globally-emerging Beijing clone, n = 31 or 7% (PGG1). The rest of the lineages were in the following order: Haarlem (H), n = 14 or 3.1% (PGG2/3); X clade, n = 13 or 2.9% (PGG2/3); Central Asian (CAS), n = 11 or 2.5% (PGG1). Moreover, we found 5 isolates with Manu patterns (2 isolates with Manu1 pattern and 3 isolates with Manu2 pattern) or 1.1% (PGG1),

that were further investigated for Region of Difference (RD) 105 polymorphism. A high spoligotype diversity was documented for EAI, LAM and T lineages (Fig 2). Indeed, GDC-0994 datasheet out of the 12 sublineages reported so far worldwide for the LAM clade [5], a total of 8 sublineages were present in our 1 year recruitment. BX-795 chemical structure A high diversity was also evidenced for other PGG1 clades (CAS), as well as PGG2/3 clades (X clade

and H). Furthermore, no M. africanum or M. bovis were found in this study. We also attempted to describe the worldwide distribution of predominant SITs (and lineages) encountered in this study. As shown in Table 1, we observed that many of the predominant SITs in our study belonging both to ancient PGG1 strains (SIT8/EAI5, SIT48/EAI1-SOM, SIT129/EAI6-BGD, SIT702/EAI6-BGD1, SIT806/EAI1-SOM) and evolutionary recent PGG2/3 strains (SIT33/LAM3, SIT59/LAM11-ZWE, SIT92/X3, SIT811/LAM11-ZWE, SIT815/LAM11-ZWE) were more frequently

present in Eastern and Gemcitabine molecular weight Southern Africa (mostly among its immediate neighbours Zimbabwe, Zambia, South Africa, Malawi, and to a lesser extent to Tanzania, Namibia, and PF299 order Somalia). Furthermore, 8 lineages or sublineages in Table 1 were made-up of their prototypes in the SITVIT2 database; these concerned SIT20 for LAM1, SIT33 for LAM3, SIT42 for LAM9, SIT48 for EAI1-SOM, SIT53 for T1, SIT59 for LAM11-ZWE, and SIT92 for X3 sublineages. Table 1 Description of predominant SITs (representing 8 or more strains) in our study, and their worldwide distribution SIT (Clade) Number (%) in this study % in this study as compared to SITVIT2 Distribution in Regions with 5% of a given SITs * Distribution in countries with ≥5% of a given SITs ** 1 (Beijing) 30 (6.74) 0.46 AMER-N 30.72, ASIA-SE 13.92, AFRI-S 11.76, ASIA-E 11.21, ASIA-N 8.36 USA 30.65, ZAF 11.77, RUS 8.36, JPN 8.19, VNM 5.96 8 (EAI5) 12 (2.70) 10.26 AFRI-E 26.50, EURO-N 24.79, AMER-N 24.79, ASIA-W 6.84, AFRI-S 5.13 USA 24.79, DNK 13.68, MOZ 10.26, TZA 9.40, GBR 8.55, ZMB 6.84, SAU 5.13, ZAF 5.13 20 (LAM1) 14 (3.15) 2.02 AMER-S 24.68, AMER-N 24.68, AFRI-S 12.84, EURO-S 11.40, EURO-W 8.23, CARI 6.20, AFRI-E 5.05 USA 22.94, BRA 14.29, NAM 8.95, PRT 7.07, VEN 6.06 33 (LAM3) 8 (1.80) 0.83 AFRI-S 32.60, AMER-S 23.33, AMER-N 16.77, EURO-S 14.37, EURO-W 5.73 ZAF 32.60, USA 16.56, BRA 9.48, ESP 9.

28 ± 1.14 c 2 5.04 ± 1.17

e 18.08 ± 1.15 ab 3 6.10 ± 0.22 d 16.43 ± 1.21 b 4 5.91 ± 0.27 de 16.29 ± 1.15 b 5 5.51 ± 0.53 e 16.12 ± 0.96 b 6 9.72 ± 0.14 b 8.82 ± 1.26 d 7 10.76 ± 0.83 a 7.59 ± 0.99 e 8 10.38 ± 0.83 ab 8.33 ± 1.12 de 9 10.57 ± 1.31 ab 8.23 ± 1.39 de *Means (±SE) of 3 repetitions followed by different lowercase letters in the same column were Selleckchem ICG-001 significantly different at the Tipifarnib cell line p < 0.05 level according to the ANOVA table and Tukey's multiple range test. Table 2 Correlation coefficients (R) of treatments and cellular components   Dry-heat(R) Wet-heat(R) Trehalose(R) mRNA(R) mRNA -0.9818 -0.890 -0.831 1.000 Trehalose 0.873 0.898 1.000 Fer-1 research buy -0.831 Trehalase -0.889 -0.905 -0.867 0.816 Ntl affects conidiospore thermotolerance After wet-heat exposure at 45°C, the germination rate of conidia declined with increasing exposure time and the conidia germination rates of the wild-type strain and mutants appeared to be significantly reduced for each succeeding 0.5-hour interval (Figure 3). The conidia germination rate of the wild-type strain was significantly higher than that of the over-expression mutants (p < 0.05) and lower than that of the RNAi mutants (p < 0.05). Similar results were observed after dry-heat exposure at 65°C for 0, 1, 2, 3, 4, or 5 hours. Accordingly, the inhibition time value for 50% germination (IT50) of the wild-type strain was longer than that of the over-expression mutants (p < 0.05) and shorter than that of the RNAi mutants (p < 0.05) (Figure 4). These data showed that the Ntl over-expression Interleukin-3 receptor mutants were significantly more sensitive to heat compared with the wild-type strain (p < 0.05). Contrary to that of the over-expression mutants, the thermotolerance of the Ntl RNAi mutants was significantly higher than that of the wild-type strain (p < 0.05). Figure 3 Germination rates of M. acridum wild-type strain and Ntl mutants. Wet-heat: aqueous conidial

suspensions exposed to 45°C for 0, 0.5, 1, 1.5, 2, or 2.5 hours; dry-heat: dried conidia exposed to 65°C for 0, 1, 2, 3, 4, or 5 hours. 1: wild-type strain; 2-5: over-expression mutants; 6-9: RNAi mutants. Standard error bars (SE) show averages for three independent experiments. Significant differences are designated by the lowercase letters on the bars of each group (p < 0.05). Figure 4 IT 50 of M. acridum wild-type strain and Ntl mutants. IT50: inhibition time values for 50% germination of aqueous conidial suspensions exposed to 45°C and dried conidia exposed to 65°C, respectively. 1: wild-type strain; 2-5: over-expression mutants; 6-9: RNAi mutants. Standard error (SE) bars show averages for three independent experiments. Significant differences are designated by the different lowercase letters on the bars of each group in the wet-heat or dried-heat test (p < 0.05).

Alexeyev MF, Shokolenko IN, Croughan TP: Improved antibiotic-resistance gene cassettes and omega elements for Escherichia coli vector construction and in vitro deletion/insertion mutagenesis. Mdm2 antagonist Gene 1995,160(1):63–67.PubMedCrossRef 37. Jefferson RA, Burgess SM, Hirsh D: Beta-glucuronidase from Escherichia coli as a gene-fusion marker. Proc Natl Acad Sci USA 1986,83(22):8447–8451.PubMedCrossRef 38. Yost CK, Del Bel KL, Quandt J, Hynes MF: Rhizobium leguminosarum methyl-accepting chemotaxis protein genes are down-regulated in the pea nodule. Arch Microbiol 2004,182(6):505–513.PubMedCrossRef 39. Ames P, Schluederberg SA, Bergman K: Behavioral mutants of Rhizobium meliloti . J Bacteriol 1980,141(2):722–727.PubMed

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protein abundance index (emPAI) for estimation of absolute protein amount in proteomics by the number of sequenced peptides per protein. Mol Cell Proteomics 2005,4(9):1265–1272.PubMedCrossRef 44. Ishihama Y, Schmidt T, Rappsilber J, Mann M, Hartl FU, Kerner MJ, Frishman D: Protein abundance profiling of the ARS-1620 chemical structure Escherichia coli cytosol. BMC Genomics 2008, 9:102.PubMedCrossRef 45. Young JPW, Crossman LC, Johnston AW, Thomson NR, Ghazoui ZF, Hull KH, Wexler M, Curson AR, Todd JD, Poole PS, et al.: The genome of Rhizobium leguminosarum has recognizable core and accessory components. Genome Biol 2006,7(4):R34.PubMedCrossRef 46. Capela D, Barloy-Hubler F, Gouzy J, Bothe G, Ampe F, Batut J, Boistard P, Becker A, Boutry M, Cadieu E, et al.: Analysis of the chromosome sequence of the legume symbiont Sinorhizobium meliloti strain 1021. Proc

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Using a Bigelow-type model, this increase corresponds to z-values ranging from 15°C to 19°C DZNeP molecular weight according to the RT-qPCR assays for the PMA-RT-qPCR method and of 28°C for the infectious titration method. For the Wa strain and EMA-RT-qPCR, the large confidence interval observed for k max did not make it possible to detect a temperature effect. Very fast inactivation of Wa strain, (after 1 minute of treatment, infectious titers were below the limit of detection (LOD)) only allows to argue that k max

values were higher than 8. In conclusion, assays conducted IAP inhibitor to examine the efficiency of pre-treatment RT-qPCR in minimizing detection signals from thermally-inactivated viruses were dependent on virus species, on the temperature of inactivation and on the RT-qPCR assays. Discussion and conclusion Foodborne viruses have emerged as a major cause of outbreaks worldwide. Among the factors that affect virus survival, temperature has a great influence on virus stability in food as in any other matrix. Therefore, food industries

widely apply temperature as a virus-inactivating factor. Natural or added constituents of food and the virus species may influence the rate of virus inactivation by temperature but higher temperatures provided more pronounced virus decay [24]. The primary model that was found to effectively describe thermal virus inactivation in our study, (i.e. the log-linear + tail primary inactivation MRIP model), was similar to the one chosen to describe thermal inactivation of HAV Crenigacestat in raspberries [25]. The infectivity of enteric viruses requires the functional integrity of two major components, the capsid and the genome [26]. While quantitative RT-PCR is a specific and sensitive tool for determining the quantities of viral genomes in the environment and food samples, it does not discriminate between infectious viruses and non-infectious viruses that do not pose a threat to health. Moreover, the virus genome was shown to be more resistant than the infectious virus. So, methods

which provide information about the infectivity are particularly useful for the detection of enteric viruses and would be an advantage in a public health perspective [27]. Recently, ethidium monoazide (EMA) and propidium monoazide (PMA), which are intercalating dyes, have been used combined with PCR or real-time PCR for the selective detection of viable microorganisms. In this study, monoazides were tested in association with surfactants in order to develop a technique for determining the residual infectivity of thermally inactivated enteric viruses. These assays are based on the penetration of monoazide, potentially facilitated by the action of surfactants, through damaged or compromised capsids and its covalent binding to viral RNA, which makes the genome unavailable for amplification by RT-qPCR.

These findings provide support to the

theory that glucosamine and chondroitin supplementation may provide some therapeutic benefits to patients with knee OA. In the present study, this website subjects ingested in a double blind and randomized manner a placebo or a dietary supplement containing 1,500 mg/d of glucosamine, 1,200 mg/d of chondroitin sulfate, and 900 mg/d of MSM. We found that symptom-limited peak aerobic capacity was increased to a greater degree in participants ingesting the GCM supplement with the greatest effects observed in the HP-GCM group. In addition, mean group upper extremity muscular endurance was greater in the GCM group compared to the P group. However, GCM supplementation did not significantly affect remaining markers of isotonic or isokinetic strength, balance, functional capacity, markers of health, self-reported perceptions of pain, or indicators of quality of life. These findings indicate that GCM supplementation provides only marginal additive benefit to a resistance-based

exercise and weight loss program. The lack of additive benefits observed could be due to limitations in sample size, length of the intervention, and/or the fact that the exercise intervention resulted in marked improvement in functional capacity and perceptions of pain thereby minimizing the impact of dietary supplementation of GCM. However, additional research is needed ICG-001 in vitro to examine the influence of GCM supplementation during a selleck products training and weight loss program below before definitive conclusions can be drawn. Conclusions Present findings indicate that adherence to a resistance-based circuit training and weight loss program

promoted weight and fat loss, increased strength and functional capacity, and improved markers of health in sedentary obese women with clinically-diagnosed knee osteoarthritis. These findings support contentions that exercise and weight loss may have therapeutic benefits for women with knee osteoarthritis. Although some trends were observed, the type of diet and dietary supplementation of GCM provided marginal additive benefits. However, since diet and GCM supplementation appeared to affect symptom-limited peak aerobic capacity and some moderate to large effect sizes were noted in key variables, additional research with a larger sample size is needed to determine whether type of diet and/or GCM supplementation while participating in an exercise and weight loss program may provide therapeutic benefits in this population. Acknowledgements We would like to thank the individuals who participated in this study as well as all of the students and administrative support staff’s at Baylor University and Texas A&M University that assisted in conducting this study. We would also like thank Rodney Bowden and Beth Lanning for their input on selecting the QOL questionnaire used in this study; Mike Greenwood for his assistance in overseeing the study and mentoring doctoral students who assisted in this study; and, Dr.

longipalpis SGE on the course of L. braziliensis infection. BALB/c mice inoculated i.d. once (SGE-1X) or three times (SGE-3X) with Lutzomyia longipalpis SGE or with PBS (control) were challenged with 105 L. braziliensis stationary phase promastigotes forms. The course of infection was monitored weekly by measuring

the ear lesion size with a metric caliper. In A , the lesion size was determined by the difference between the infected ear and the opposite uninfected ear given in millimeters (mm) (n = 5 mice per group). Data represent the mean ± SEM and are representative of two independent experiments. # P < 0.05 compared with PBS. *P < 0.05 compared with the SGE1-X PND-1186 or SGE-3X group. Ear parasitic burden at the 3rd and 7th week post-infection were determined by a limiting-dilution assay (B). The data shown represent the mean ± SEM of two independent experiments, and each experiment was performed with five mice per group (n = 5). # P < 0.05 MK-8931 cost compared with PBS group. & P < 0.05 compared with PBS group. *P < 0.05 compared with the SGE-1X group.

Furthermore, we analyzed the ability of the Proteasome inhibitor draining lymph node cells from SGE-1X-, SGE-3X- or PBS-inoculated mice at the 7th week post-infection to produce IL-10 and IFN-γ in an attempt to understand the mechanism by which saliva exacerbates or protect mice against parasitic infection. Our results showed that the total lymph node cells from SGE-1X-inoculated mice produced more IL-10 after stimulation in vitro with parasitic antigen relative to mice inoculated with PBS or SGE-3X

(Figure  4A). On the contrary, SGE-3X-treated mice produced significantly increased levels of IFN-γ when compared with the other groups of infected mice (Figure  4B). Figure 4 Cytokine production by the draining lymph nodes after different inoculums of SGE. BALB/c mice inoculated i.d. once (SGE-1X ) or three very times (SGE-3X) with Lutzomyia longipalpis SGE or with PBS (control) were challenged with 105 L. braziliensis stationary phase promastigote forms. At the end of the 7th week post-infection, draining lymph node cells were harvested and restimulated in vitro with L. braziliensis antigen (5 μg/ml) or medium for 72 h. IL-10 (A) and IFN-γ (B) levels in the supernatant were determined by ELISA assay. The results are expressed as the mean ± SEM of at least two independent experiments using four to five mice per group (n = 4-5 mice per group). # P < 0.05 compared with medium-only stimulus. * P < 0.05 compared with the SGE-1X group. The cells that migrated to the site of parasite inoculation were identified by flow cytometry. As shown in Figure  5, L. braziliensis infection induced the recruitment of T lymphocytes such as CD4+ T and CD8+ T. Likewise, both populations were detected in the ears of SGE-1X-inoculated mice. In addition, similar numbers of CD4+ T cells and CD8+ T cells producing IFN-γ ex vivo were found in both the SGE-1X and the PBS group. By comparison, the leukocyte influx was altered in the ears of SGE-3X-inoculated mice.

Production of IL-12p70 was below the standards (data not shown). Figure 6 Cytokine concentration in chlamydiae-infected monocytes and monocyte-derived DCs. Monocytes and monocyte-derived DCs were infected with C. trachomatis serovars Ba, D and L2 (MOI-3) and mock control. Supernatants were collected 1 day post infection and the concentration of the different cytokines IL-1β, TNF, IL-6, IL-8 and IL-10 were determined by using the kit Cytometric Bead Array. The concentration is reported as pg/ml. The cytokine secreted by heat-killed sample of this website each serovar were quantified and are indicated for each dataset. The mean of 3

independent experiments is shown and each experiment is pool of 2 donors. ***P < 0.001, **P < 0.01, *P < 0.05. Pro-inflammatory cytokines IL-1β and TNF was elevated in the chlamydiae infected monocytes than the mock control, however were not statistically significant. The level of cytokines IL-6 and IL-8 in infected monocytes

showed no statistical difference with mock control. The anti-inflammatory cytokine IL-10 was induced in higher levels than the mock with serovar Ba infection secreting significant amounts compared to mock. DCs infected with serovars D and L2 showed significantly up-regulated levels of TNF. The other pro-inflammatory cytokine IL-1β although secreted in higher amounts within serovar L2 infected DCs, than the other serovars or mock, was not significant. DCs infection Blasticidin S resulted in significant production of inflammatory cytokines IL-8 and IL-6. The anti-inflammatory cytokine

IL-10 levels were low in the infected DCs and were not statistically significant to the mock control. To understand LPS contribution in the observed cytokine responses, monocytes and DCs were infected with heat-killed C. trachomatis serovars Ba, D and L2 EBs at MOI-3 and the cytokine levels were investigated (Additional file 4: Figure S4). Heat-killed EBs for serovar Ba and D induced significantly low level of IL-8 and IL-6 in monocytes while the TNF levels were low in DCs for serovar D and L2. The most remarkable observation was the negligible induction of IL-10 by heat-killed Glutamate dehydrogenase EBs from all 3 serovars in monocytes which was highly significant. Immune gene response to C. trachomatis infected monocytes and DCs To determine the host genes activated by chlamydia infection, the immune response was analyzed by Human MK 2206 innate and Adaptive Immune response array. Genes differentially regulated 1.5 fold up or down in monocytes or monocyte-derived DCs infected with C. trachomatis serovars Ba, D and L2 24 hours p.i. were considered for further analysis (Figure 7). Figure 7 Genes up-regulated or down-regulated in response to C. trachomatis infection in monocytes and DCs. Expression of Innate and adaptive immune response genes were studied by PCR array in monocytes and DCs infected with Chlamydia trachomatis serovars Ba, D and L2.

GFAP initially appeared at 72 h for cells grown on 50-nm nanodots (Figures 6 and 7a). Decrease of GFAP expression was observed

in cells grown on 100- and 200-nm nanodots for 72 h (Figure 7a). The effects of topography on the astrocytic processes were also observed. The 10-, 50-, and 100-nm nanodots induced longer astrocytic processes after 120 h of incubation (Figure 7b). Figure 6 Immunostaining of vinculin (green) and GFAP (red) in C6 glioma cells. The cells are seeded on nanodot arrays and incubated for 24, 72, and 120 h. Images are obtained using a confocal microscope. The scale bars indicate 25 μm. Figure 7 The GFAP-stained area, total SB431542 cell line length of glial processes, and the vinculin-stained area. (a) The GFAP-stained area per cell is plotted against the nanodot diameters and grouped by incubation time. (b) Total length of glial processes per find more cell is plotted against the nanodot diameters and grouped by incubation time. Maximum process length occurs when cells are grown on 50-nm nanodots with 120 h of incubation. (c) TGF-beta/Smad inhibitor The vinculin-stained area per cell is plotted against the nanodot diameters and grouped by incubation time. Maximum staining occurs for cells grown on 10- and 50-nm nanodots. All values are expressed as the mean ± SD averaged from

at least six experiments. **p < 0.01, *p < 0.01. Vinculin is a membrane cytoskeletal protein associated with focal adhesion plaques that is involved in the linkage of integrin adhesion molecules of to actin filaments [18]. The area of focal vinculin plaques significantly increased in the 10- and 50-nm nanodot-treated

groups at 24, 72, and 120 h (Figure 7c). Nanotopography enhanced connexin43 transport Nanodot arrays control astrocyte-astrocyte interaction by regulating the function of gap junction proteins. Cx43, which composes gap junction channels (GJCs), mediates transmission and dispersion growth/suppressive factors and reveals the contact spots between astrocytes [19, 20]. The expression level of Cx43 did not show a consistent pattern regarding the dot diameter (Figure 8). The 10-nm nanodots decreased the expression of Cx43 at 24 h. The Cx43 expression level significantly increased for cells grown on 50-nm nanodots for 72 h. Figure 8 Quantitation of connexin43 expression in C6 glioma cells grown on nanodot arrays. (a) Western blotting of C6 glioma cells with anti-Cx43 antibody. GAPDH staining serves as a control. (b) Expression of Cx43 relative to GAPDH is plotted against the nanodot diameters and grouped by incubation time. Values are expressed as the mean ± SD averaged from at least three independent experiments. *p < 0.05. Nanotopography modulated the expression and transport of Cx43 protein Immunostaining was used to obtain the expression and cellular localization of Cx43 in C6 glioma cells on nanodot arrays.