This work aimed to use controlled engineered cell

This work aimed to use controlled engineered cell environments to improve the understanding of the role of external cues on drug response. We used a microwell array, previously developed in our group [4], which enables the culture of cells in a 3D environment with control of cell cluster size down to the single cell level. It also allows the control of the biochemical interface with the cells. Initially we studied the influence of

dimensionality on the response to taxol on the breast carcinoma cell line, MCF-7. Cancer cells cultured in microwells showed an increased resistance to taxol in comparison to cells cultured on flat substrates. A similar change in drug response was observed for cells in cell-derived fibronectin matrices. These results in two 3D systems,

of different complexity, LCZ696 ic50 demonstrate that dimensionality is an important factor for determining the responsiveness of cells to drugs. In addition, the results showed that the microwell array can be used as an in vivo mimic, and is therefore a promising tool for the screening of MK5108 cell line anti-cancer drugs. References: 1. Bissell, M. J., Differentiation, 70, 537–546, 2002. 2. Serebriiski et al., Matrix Biology, 27, 1074–1077, 2007. 3. Aoudjit, F. et al., Oncogene, 20, 4995–5004, 2001. 4. Ochsner, M. et al., Lab Chip, 7, 1074–1077, 2007. Poster No. 149 FAP-positive Fibroblasts Express FGF1 and Increases OSI-027 price Migration and Invasion of Colon Cancer Cells Maria L. Henriksson 1 , Sofia Edin1, Anna M. Dahlin1, Per-Arne Oldenborg2, Åke Öberg3, Bethany Van Guelpen1, Jörgen Rutegård3, Roger Stenling1, Richard Palmqvist1 1 Department of Medical Biosciences/Pathology, Umeå Universtiy, Umeå, Sitaxentan Sweden, 2 Department of Integrative Medical Biology, Section for Histology and Cell Biology, Umeå Universtiy, Umeå,

Sweden, 3 Department of Surgical and Perioperative Sciences, Surgery, Umeå Universtiy, Umeå, Sweden Background: Colorectal cancer is one of the leading causes of cancer deaths in western countries, with death generally resulting from metastatic disease. In recent years, the importance of the tumor microenvironment, including tumor-associated fibroblasts, has paid increasing attention. Aim: To analyze the effect of Fibroblast activation protein (FAP)-expressing fibroblasts on colon cancer cell migration and invasion in experimental cell studies. We also investigated the expression pattern of FAP in tumor-associated fibroblasts during transformation from benign to malign colorectal tumors. Methods and results: In immunohistochemical analyses, FAP was expressed in fibroblasts in all carcinoma samples examined (n = 61), whereas all normal colon (n = 12), hyperplastic polyps (n = 16) or adenoma (n = 55) samples were negative for FAP. In in vitro studies, conditioned medium from HCT-116 colon cancer cells, but not LT97 adenoma cells, induced FAP expression in colon fibroblasts.

These results indicated that a basic locus for pWTY27 replication

These results indicated that a basic locus for pWTY27 replication was pWTY27.1c (designated repA), pWTY27.2c (repB) and a 300-bp (from 321 to 620 bp) ncs. Figure 1 Identification of a pWTY27 locus required for replication in Streptomyces lividans. (a). Identification of a replication locus. Plasmids were constructed in E. coli (see Methods and A-1210477 nmr Table 1), and introduced by transformation into S. lividans ZX7. Positions of these cloned fragments on pWTY27 and transformation frequencies are shown. The ncs is indicated by striped boxes, relevant genes by open arrowheads and the two replication genes by filled arrowheads. (b). RT-PCR of a transcript

overlapping the consecutive replication genes. RNA of strain Y27 was isolated and reverse-transcribed into cDNA. The cDNA, RNA and Y27 genomic DNA were used as templates for PCR amplification and their products were electrophoresed in 1.5% agarose gel at 20 V/cm for 1 h. pWT26 was introduced XAV939 by conjugation from E. coli Repotrectinib ET12567 (pUZ8002) into 10 randomly-selected endophytic Streptomyces strains (different 16S rRNA sequences, e.g. Y22, Y45, Y19,

Y24, Y8, Y51, Y10, Y31, Y72 and Y3), and apramycin resistant transconjugants were obtained from eight of them, indicating a wide host range for this plasmid. RepA protein binds specifically to intact IR2 of the iteron sequence in vitro The pWTY27 RepB was predicted to be a DNA primase/polymerase and RepA a hypothetical protein. The 300-bp ncs was predicted as an iteron containing five direct repeats of 8 bp (DR1, GTGGGAAC), five direct repeats of 7 bp (DR2, TTCCCAC) and three pairs of inverted repeats (IR1–IR3, Figure 2a). To see if there was an interaction between the RepA protein and this iteron sequence, electrophoretic mobility shift assays for DNA-protein complex formation were employed. The 6His-tagged RepA protein was incubated with a [γ-32P]ATP-labeled iteron DNA, and then electrophoresed and autoradiographed. tuclazepam As shown in Figure 2b, the “shifted” DNA bands were visualized by adding RepA protein, indicating

that the RepA protein could bind to the DNA probe to form a DNA-protein complex. Formation of this complex was inhibited by adding a 15-fold excess of unlabeled probe but was not affected by adding even a 1000-fold excess of polydIdC DNA as a non-specific competitor, indicating that the binding reaction of the RepA protein with iteron DNA was highly specific. Figure 2 Characterization of the binding reaction of Rep1A protein with iteron DNA by EMSA and footprinting. (a). Iteron of pWTY27. Possible iteron sequences from 338 to 606 bp on pWTY27 and AT-rich regions are shown. DR: direct repeat; IR: inverted repeat. The RepA binding sequences determined by DNA footprinting are boxed. The binding sequences of RepA protein are indicated by shading. (b). Detection of the binding activity of RepA protein with the iteron by EMSA.

91 178 50 4   aProtein identifications were confirmed with a sign

91 178 50 4 protein identifications were confirmed with a significant MASCOT score of 71 for peptide mass fingerprint and ANOVA p ≤ 0.05, and a minimum of three matched peptides. bSignificant MS/MS score is > 54 for searches in Saccharomyces cerevisiae.

Spectra’s for single peptide identifications are supplied in Additional file 1. A general feature for all proteomes was that the proteins clustered in two regions on the gel, a region in the range of 36–42 kDa and one low molecular region from 8–20 kDa. Furthermore, a massively stained protein cluster at about pI 5.0-6.3 with a Mr of 37–42 kDa was identified in all gels. This protein cluster corresponded to the most abundant protein in beer – ATM inhibitor protein Z (Figure 3, Table 2). During fermentation of both beers, wort protein changes occurred.

The protein spots identified as LTP1 (Figure 3; spot A22-A26, Table 2) on the wort 2-DE A-1210477 ic50 gel were more intense, than the corresponding spots on the 2-DE gel for the two beers. In the same pI range as LTP1 was detected, two lower molecular protein spots (Figure 3; spot A28, A29, Table 2) were detected in wort and identified as LTP2. These two LTP2 spots were undetectable in beer (Figure 3). Another feature that occurred during fermentation was that the serpin protein cluster of protein Z was shifted towards the acidic area, dividing the serpin protein cluster into two (Figure 3; B,C). This was not observed on the wort protein 2-DE gel (Figure 3; A). Three protein spots found exclusively in beer were identified to be cell wall associated yeast proteins, Uth1 – involved in cell wall biogenesis (Figure 3; spot B1, Table 2,

Additional file 1), Exg1 – an exo-β-1,3-glucanase, (Figure 3; spot B2, C2, Table 2) and Bgl2 – endo-β-1,3-glucanase (Figure 3; spot C5, Table 2, Additional file 1). In both beers, two higher molecular protein spots with a pI of 4.8 were observed Verteporfin ic50 and identified by MALDI-TOF-MS as Uth1 (55 kDa [Figure 3; spot B1, C1, Table 2]) and Exg1 (47 kDa [Figure 3; spot B2, C2, Table 2]). Although protein spots corresponding to Uth1 were observed in both beers, Uth1 was only identified in beer brewed with WLP001 (Figure 3; spot B1). In beer brewed with KVL011 a protein spot of 34 kDa (Figure 3; spot C5) was identified as Bgl2, which was not observed in the proteome of beer brewed with WLP001. However, Exg1 was identified in the beer brewed with both brewer’s yeast strains (Figure 3; spot B2, C2). Discussion Several proteome analyses of beer [4, 5, 8, 15, 17], malt [8, 14, 22, 23] and beer related processes [6, 16] have been made, but none seem to have considered the influence of fermentation and brewer’s yeast strains on the beer proteome. To investigate if proteome changes from wort to beer were yeast strain dependent, proteins from wort and beer brewed with two different ale brewer’s yeast strains were separated by 2-DE and identified by MALDI-TOF-MS.


Functional classification of genes regulated in an RpoH1-dependent manner The 101 genes that had distinct expression profiles in the rpoH1 mutant arrays in comparison to the wild type, ergo genes that presented an RpoH1-dependent

expression, were also grouped according to their COG classification. The COG classification distributes genes in orthologous groups on basis of functional predictions and patterns of sequence similarities [45]. The RpoH1-dependent genes were assigned to 18 functional categories, indicating a global effect on gene expression dependent on RpoH1 upon pH shock. Among BMN 673 mw the known most representative classes were protein turnover and chaperones, followed by translation, transcription and by transport and

metabolism of carbohydrates, nucleotides and amino acids (Figure 7). There C646 purchase is indeed a dramatic increase in the expression of chaperone proteins and heat shock genes in response to pH shock. A total of 24 genes that presented an RpoH1-dependent upregulation following acid shift are involved in heat shock and stress response. Among the proteases, the genes coding for HtpX, a membrane-bound and stress-controlled protease well characterized in E. coli [46], as well as those coding for ClpB and ClpP2, responsible for disassembling protein aggregates that accumulate in the cytoplasm under stress conditions [25], were expressed in dependence of RpoH1. The operon formed by the genes hslUV, which codes for an intrinsic URMC-099 nmr ATP-dependent proteasome system for degradation of misfolded proteins in the cytoplasm, was Thymidine kinase also upregulated in an RpoH1-dependent fashion. Among the induced chaperones were also the gene Smc00699, coding for a heat shock DnaJ-like protein, as well as the

gene coding for GrpE, which is part of the cellular chaperone machinery capable of repairing heat-induced protein damage [47]. Moreover, there was an RpoH1-dependent upregulation of the operon that codes for the only GroELS proteins specialized in stress response in S. meliloti, GroELS5 [25]. The gene coding for the small heat shock protein IbpA [48] was also upregulated. Genes like groEL5 and clpB have already been described as genes whose transcription is RpoH1-dependent in S. meliloti [22, 25]. The group of proteins shown to be involved in the heat shock response under the transcriptional control of RpoH usually includes chaperones, proteases, and regulatory factors [49]. The mutation in the rpoH1 gene in S. meliloti and its characterization under pH stress revealed indeed a lack of activation of all major types of regulatory chaperones and key heat shock proteins usually activated in stress conditions. In the present study, we have seen representatives of all of those groups to be involved in pH stress response. We hence attest to the role of rpoH1 in S. meliloti pH stress response as being evidenced by the activation of acid-induced heat shock proteins and chaperones in dependence of rpoH1 expression.

Triplicate wells were treated with CCNSs, free etoposide, and ECC

Triplicate wells were treated with CCNSs, free etoposide, and ECCNSs in different concentrations of 5, 10, 20, and 40 μg/mL. These SGC-7901 cells were incubated as described above for 24 and 48 h. MTT of 20 μL (5 mg/mL) was added to each well before the cells were incubated for 4 h at 37°C under light-blocking condition. After the removal of the MTT dye solution, cells were treated with 150 μL DMSO. Absorbance was measured at 490 nm using ELX 800 reader, and inhibition against

SGC-7901 cells was calculated by the following equation: Fluorescence activated cell sorter analysis The number of the apoptosis cells was determined with the Annexin V-PI detection kit (KeyGEN Biotech). SGC-7901 cells with 1 × 106 were cultured, suspended in RPMI-1640 with 10% pasteurized FCS, and seeded on a 24-well flat-bottomed plate and incubated for 24 h at 37°C. The free etoposide, ECCNSs, and culture medium were only GSK872 solubility dmso added to each group with

the concentration of 30 μg/mL. Based on the drug encapsulation efficiency, the same quantity of etoposide was applied to all formulations for the apoptosis analysis. The incubation continued for 24 h at 37°C. Then, the cells were harvested and washed with PBS, and then PI and Annexin V were added directly to the cell suspended in the binding buffer (10 mM HEPES, 140 mM NaCl, 2.5 mM CaCl2, pH 7.4). The cells were incubated in the dark for 15 min at 37°C and submitted to FACS analysis on a Beckton-Dickinson (Mountain View, CA, USA) spectrophotometer. Confocal laser scanning microscopy CLSM images of the ECCNSs and etoposide were obtained using confocal laser scanning microscope (Leica, Wetzlar, Germany) equipped with an oil immersion GSK126 concentration objective (60×, Zeiss, Oberkochen, Germany). A suspension of the particles was placed on a glass slide and dried prior to use. Fluorescence images were obtained at an excitation wavelength of 488 nm (fluorescein isothiocyanate click here (FITC)) and 405 nm (4′,6-diamidino-2-phenylindole (DAPI)). Results and

discussion As shown in Figure 1, CCNSs were obtained by a multistage self-assembled strategy. In this study, a series of intermediates were trapped, in order to confirm the formation process of the CCNSs. It was found that the nanoparticles firstly concentrated and arranged in a line at an early stage. Then, the particles grew rapidly into the broom shape via crystallization of nanoparticles coupled with a simultaneous multiscale assembly. With the PF-562271 cost reaction going on, the broom-like structure formed into a high-order spherical structure, as shown in Figure 2. The CCNSs were synthesized by a binary solvent method. Firstly, the reaction of citric acid with HCO3 − ions generates CO2 bubbles and H2O. And then, the CO2 bubbles serve as not only the template of engineered nanospheres but also the reactive materials (reaction formulas listed below). Furthermore, citric acid acts as a crystal modifier to control the selectivity of polymorph and crystal morphology.

Our and others’ studies have indicated that HIF-1α played a vital

Our and others’ studies have indicated that HIF-1α played a vital role for the angiogenesis and VM under hypoxia [11, 26–28]. To determine the origin of the change in VEGF and Flk-1 expression, we used the Sirolimus to inhibit the activity of HIF-1α. Sirolmus, known as rapamycin, is proved to be as the inhibitor of HIF-1α [26, 29, 30]. Consistent with other researches, the changes in the expression of VEGF, Flk-1 and

Cyclin D1 were HIF-1α transcriptional dependent [10, 31]. However, the change in the expression of p53 was HIF-1α transcriptional independent. Conclusion In summary, the ovarian cancer cells could be induced into ELs which seemed similarly to progenitor endothelial cells by hypoxia. After induced, the ELs would get some characteristics of endothelial cells

and would lose some malignant characteristics of the original cancer cells. The increased expression of HIF-1a, and HIF-1α find more depended VEGF and Flk-1 might contribute to the VM and the vasculogenesis. During the transition, HIF-1α took an important role in the molecular mechanisms, while there still has other HIF-1α-independent mechanism in this process. Acknowledgements This study was selleck kinase inhibitor supported by National Natural Science Foundation of China grants 30471806, 30470689 and 30900716, Postdoctoral Science Foundation of China grant 20040350454, and Science and Technology Commission of Shanghai Municipalitygrant 04JC14021. References 1. Huang S, Robinson JB, Deguzman A, Bucana CD, Fidler IJ: Blockade of nuclear factor-kappaB signaling inhibits angiogenesis and tumorigenicity of human ovarian cancer cells by suppressing expression of vascular endothelial

growth factor and interleukin 8. Cancer Res 2000, 60:5334–5339.PubMed 2. Demeter A, Varkonyi T, Csapo Z, Szantho A, Olah J, Papp Z: [Assessment of prognostic factors in common ovarian tumors of varying malignancy]. Magy Onkol 2004, 48:259–265.PubMed 3. Janic B, Arbab Cediranib (AZD2171) AS: The role and therapeutic potential of endothelial progenitor cells in tumor neovascularization. ScientificWorldJournal 2010, 10:1088–1099.PubMed 4. Fidler IJ, Ellis LM: The implications of angiogenesis for the biology and therapy of cancer metastasis. Cell 1994, 79:185–188.PubMedCrossRef 5. Folkman J: Seminars in Medicine of the Beth Israel Hospital, Boston. Clinical applications of research on angiogenesis. N Engl J Med 1995, 333:1757–1763.PubMedCrossRef 6. Rasila KK, Burger RA, Smith H, Lee FC, Verschraegen C: Angiogenesis in gynecological oncology-mechanism of tumor progression and therapeutic targets. Int J Gynecol Cancer 2005, 15:710–726.PubMedCrossRef 7. Millimaggi D, Mari M, D’ Ascenzo S, Giusti I, Pavan A, Dolo V: Vasculogenic mimicry of human ovarian cancer cells: role of CD147. Int J Oncol 2009, 35:1423–1428.PubMed 8. Folberg R, Hendrix MJ, Maniotis AJ: Vasculogenic mimicry and tumor angiogenesis. Am J Pathol 2000, 156:361–381.PubMedCrossRef 9. Tang HS, Feng YJ, Yao LQ: Angiogenesis, vasculogenesis, and vasculogenic mimicry in ovarian cancer.

Next, in order to identify differentially expressed genes, the SA

Next, in order to identify differentially expressed genes, the SAM (Significance Analyses of Microarray) statistical package was CHIR-99021 in vitro used to compare the levels of gene expression among the following groups: (1) uninfected C57BL/6 and CBA macrophages; (2) L. amazonensis-infected C57BL/6 macrophages and uninfected cells; (3) L. amazonensis-infected CBA macrophages and uninfected cells; (4)

L. amazonensis-infectedC57BL/6 and CBA macrophages. In order to enhance confidence in the statistical analysis of microarray data, experiment variables of incubation and infection time were not considered when comparing gene expression among groups (1) to (4). SAM software uses a modified t-test measurement which corrects for

multiple comparisons by means of a False Discovery Rate (FDR) approach [27]. The q-values, or the minimum FDRs at which a statistical test may be called significant [28], have been provided for each selleck chemicals differentially expressed gene in Tables S1, S2 and S3 (See Additional file 1: Table S1; Additional file 2: Table S2 and Additional file 3: Table S3, respectively). Finally, differentially expressed genes were analyzed and grouped in functional networks using the Ingenuity Pathway Analysis program v8.8 (IPA-Ingenuity Systems®, http://​www.​ingenuity.​com). Possible networks and pathways were scored and modeled considering the sets of differentially expressed genes triclocarban derived from the four comparisons described above. To calculate the probability of associations between genes from the functional networks and pathways generated by IPA®, Fisher’s exact test was used with a 0.05 threshold value. Total macrophage mRNA extraction and mRNA quantification by RT-qPCR In order to perform reverse transcriptase-quantitative polymerase chain reactions (RT-qPCR), RNA was initially extracted from uninfected or infected macrophages using a QIAGEN Mini Kit (RNAeasy) in accordance

with manufacturer Entospletinib order directions. An optical density reading was taken following extraction procedures and RNA integrity was verified using an agarose gel. Complementary DNA (cDNA) was synthesized by reverse transcription in a final volume of 20 μL containing 5 mM MgCl2 (Invitrogen), PCR buffer 1× (Invitrogen), deoxyribonucleotide triphosphates each at 1 mM (dNTPs – Invitrogen), 0.5 mM oligonucleotide (oligo d(T) – Invitrogen), 1 UI RNase inhibitor (RNase Out – Invitrogen), 2.5 UI reverse transcriptase (MuLVRT- Invitrogen) and 1 μg of sample RNA in RNAse-Free Distilled Water. All reaction conditions consisted of a single cycle at 42°C for 50 min, followed by 70°C for 15 min and, finally, 4°C for at least 5 min. Following reverse transcription, the synthesized cDNA was aliquoted and frozen at -20°C. The cDNA aliquots were later thawed and amplified by qPCR in order to perform gene quantification.

A 1 2 The Drug:H+

A.1.2 The Drug:H+ Antiporter-1 (12 Spanner) (DHA1) Family drug, polyamine, neurotransmitter, sugar, nucleobase/side, siderophore, lipid (antiport); vitamin (symport) 12 9 2.A.1.3 The Drug:H+ Antiporter-2 (14 Spanner) (DHA2) Family drug, boron, bile acid, parquot, fatty acid, siderophore, amino acid (antiport); pyrimidine (symport) 49 6 2.A.1.4 The Organophosphate:Pi Antiporter (OPA) Family carbohydrate phosphate (antiport)

  1 2.A.1.6 The Metabolite:H+ Symporter (MHS) Family organic acid/base, sugar acid (symport) 6 1 2.A.1.8 The Nitrate/Nitrite Porter (NNP) family nitrate/nitrite (symport/antiport) 2 1 2.A.1.11 The Oxalate:Formate Antiporter (OFA) Family oxalate/formate (antiport) 3   2.A.1.14 The Anion:Cation Symporter (ACS) Family organic and inorganic anion, see more peptide, vitamin, amino acid, nucleotide (uniport; symport) 3   2.A.1.15 The Aromatic Acid:H+ Symporter (AAHS) Family aromatic acid, vitamin (symport) 3 1 2.A.1.17 The Cyanate Porter (CP) Family cyanate, glucose (symport) 3   2.A.1.21 The Drug:H+ Antiporter-3 (12 Spanner) (DHA3) Family drug, siderophore (antiport) 6 7 2.A.1.24 The Unknown Major Facilitator-1 (UMF1) Family unknown 1 1 2.A.1.25 Gamma-secretase inhibitor The Peptide-Acetyl-Coenzyme A Transporter (PAT) Family

peptide, glycopeptide, acyl-CoA (symport)   3 2.A.1.30 The Putative Abietane Diterpenoid Transporter (ADT) Family diterpenoid (symport) 4   2.A.1.34 The Sensor Kinase-MFS Fusion (SK-MFS) Family unknown 1   2.A.1.35 The Fosmidomycin Resistance (Fsr) Family drug (antiport) 1   2.A.1.36 The Acriflavin-sensitivity (YnfM) Family drug (symport) 2 1 2.A.1.40 The Purine Transporter, AzgA (AzgA) Family purine (symport) 2   2.A.1.49 The Endosomal Spinster (Spinster) Family unknown   1 2.A.1.54 The Unknown (Archaeal/Bacterial) Major Facilitator-9 (UMF9) Family unknown 1   2.A.1.60 The Rhizopine-related MocC (MocC) Family rhizopine 7 1 2.A.1.67 The Unidentified Major Facilitator-16 (UMF16) Family unknown 5   2.A.17 The Proton-dependent Oligopeptide Transporter (POT) Family peptide, histidine, Carnitine palmitoyltransferase II nitrate (Epoxomicin manufacturer symport; occasionally

antiport) 1 2 Representation of transporters belonging to known families within the Major Facilitator Superfamily (MFS) listed according to TC number with their substrate ranges and modes of active transport indicated. Drug exporters are prevalent in both organisms. The DHA1 Family (2.A.1.2) has 12 members in Sco and nine in Mxa, the DHA2 Family (2.A.1.3) has 49 members in Sco and six in Mxa, and the DHA3 Family (2.A.1.21) has six and seven members in these two organisms, respectively. It is clear that Sco, but not Mxa, has greatly increased its numbers of DHA2 family members, although neither did for DHA1 or DHA3 family members. The order of representation is therefore DHA2 >DHA1>DHA3 in Sco, with huge representation of DHA2 members, but DHA1 > DHA3 > DHA2 in Mxa, with much lower representation overall.

Ueno Y, Shimizu R, Nozu R, Takahashi S, Yamamoto M, Sugiyama F, T

Ueno Y, Shimizu R, Nozu R, Takahashi S, Yamamoto M, Sugiyama F, Takakura A, Itoh T, Yagami K: Elimination of Pasteurella pneumotropica from a contaminated mouse colony by oral administration RG7420 ic50 of Enrofloxacin. Exp Anim 2002, 51:401–405.PubMedCrossRef 11. Boot R, Thuis H, Teppema JS: Hemagglutination by Pasteurellaceae isolated from rodents. Zentralbl Bakteriol 1993, 279:259–273.PubMed 12. Hooper A, Sebesteny A: Variation in Pasteurella pneumotropica

. J Med Microbiol 1974, 7:137–140.PubMedCrossRef 13. Sasaki H, Kawamoto E, Tanaka Y, Sawada T, Kunita S, Yagami K: Identification and characterization of hemolysin-like proteins similar to RTX toxin in Pasteurella pneumotropica . J Bacteriol 2009, 191:3698–3705.PubMedCrossRef 14. Frey J: RTX toxin-determined virulence of Pasteurellaceae. In Pasteurellaceae. Edited by: this website Kuhnert P, Christensen H. Norwich: Horizon Scientific Press; 2008:133–144. 15. Frey J, Kuhnert P: RTX toxins in Pasteurellaceae . Int

J Med Microbiol 2002, 292:149–158.PubMedCrossRef 16. Trucksis M, Galen JE, Michalski J, Fasano A, Kaper JB: Accessory cholera enterotoxin (Ace), the third toxin of a Vibrio cholerae virulence cassette. Proc Natl Acad Sci USA 1993, 90:5267–5271.PubMedCrossRef 17. Welch RA: RTX toxin structure and function: a story of numerous anomalies and few analogies in toxin biology. Curr Top Microbiol Immunol 2001, 257:85–111.PubMed 18. Balashova NV, Diaz R, Balashov SV, Crosby JA, Kachlany SC: Regulation of Aggregatibacter ( Actinobacillus ) actinomycetemcomitans Dorsomorphin leukotoxin secretion by iron. J Bacteriol 2006, 188:8658–8661.PubMedCrossRef 19. Gallant CV, Sedic M, Chicoine EA, PR-171 mw Ruiz T, Mintz KP: Membrane morphology and leukotoxin secretion are associated with a novel membrane protein of Aggregatibacter actinomycetemcomitans . J Bacteriol 2008, 190:5972–5980.PubMedCrossRef

20. Kachlany SC, Fine DH, Figurski DH: Secretion of RTX leukotoxin by Actinobacillus actinomycetemcomitans . Infect Immun 2000, 68:6094–6100.PubMedCrossRef 21. Venketaraman V, Lin AK, Le A, Kachlany SC, Connell ND, Kaplan JB: Both leukotoxin and poly-N-acetylglucosamine surface polysaccharide protect Aggregatibacter actinomycetemcomitans cells from macrophage killing. Microb Pathog 2008, 45:173–180.PubMedCrossRef 22. Ramjeet M, Cox AD, Hancock MA, Mourez M, Labrie J, Gottschalk M, Jacques M: Mutation in the LPS outer core biosynthesis gene, galU , affects LPS interaction with the RTX toxins ApxI and ApxII and cytolytic activity of Actinobacillus pleuropneumoniae serotype 1. Mol Microbiol 2008, 70:221–235.PubMedCrossRef 23. Fullner KJ, Boucher JC, Hanes MA, Haines GK, Meehan BM, Walchle C, Sansonetti PJ, Mekalanos JJ: The contribution of accessory toxins of Vibrio cholerae O1 El Tor to the proinflammatory response in a murine pulmonary cholera model. J Exp Med 2002, 195:1455–1462.PubMedCrossRef 24. Fullner KJ, Mekalanos JJ: In vivo covalent cross-linking of cellular actin by the Vibrio cholerae RTX toxin. EMBO J 2000, 19:5315–5323.

47 0 118 0 10 0 000 4 6 Rv2003c   conserved hypothetical protein

47 0.118 0.10 0.000 4.6 Rv2003c   AZD8931 price conserved hypothetical protein 1.26 0.004 0.08 0.010 15.1 Rv2004c   hypothetical protein 1.01 0.008 0.36 0.022 2.8 Rv2005c   conserved hypothetical protein 1.78 0.033 0.33 0.000 5.4 Rv2006 otsB2 trehalose-6-phosphate phosphatase 1.28 0.000 0.02 0.008 78.4 Rv2007c fdxA ferredoxin 2.56 0.137 0.64 0.026 4.0 Rv2027c dosT sensor histidine kinase 1.35 0.001 0.07 0.044 18.9 Rv2028c   conserved hypothetical protein 0.38 0.009 -0.11 0.004 Dinaciclib chemical structure -3.3 Rv2029c pfkB phosphofructokinase II 2.03 0.330 0.26 0.006 7.8 Rv2030c   conserved hypothetical protein 3.37 0.195 0.62 0.004 5.4 Rv2031c hspX 14 kD antigen, heat shock protein Hsp20 family

3.94 0.043 1.50 0.079 2.6 Rv2032 acg conserved hypothetical protein 2.50 0.277 0.29 0.003 8.6 Rv2617c   hypothetical protein -0.21 0.012 -0.01 0.000 20.6 Rv2623   conserved hypothetical protein 3.02 0.151 0.15 0.132

19.8 Rv2624c   conserved hypothetical protein 1.34 0.062 0.10 0.024 13.9 Rv2625c   conserved hypothetical protein -0.03 0.016 -0.94 0.017 0.0 Rv2626c   conserved hypothetical protein 3.35 0.000 0.77 0.184 4.4 Rv2627c   conserved hypothetical protein 2.65 0.285 0.05 0.010 51.0 Rv2628   hypothetical protein 2.22 0.022 0.14 0.038 16.0 Rv2629   hypothetical protein 0.49 0.004 0.28 0.006 1.8 Rv2630   hypothetical protein 1.42 0.003 0.24 0.014 5.9 Rv2631   conserved selleck inhibitor hypothetical protein 0.70 0.015 -0.17 0.021 -4.1 Rv2830c   similar to phage P1 phd gene 0.29 0.000 -0.07 0.002 -3.9 Rv3126c   hypothetical protein 0.91 0.021 0.07 0.018 12.8 Rv3127   conserved hypothetical protein 2.15 0.044 0.51 0.000 4.2 Rv3128c   conserved hypothetical protein 0.30 0.310 0.13 0.002 2.3 Rv3129   conserved hypothetical

protein 1.09 0.002 0.03 0.035 40.6 Rv3130c tgs1 conserved hypothetical protein 3.92 0.309 0.84 0.013 4.7 Rv3131   conserved hypothetical protein 4.01 0.273 1.66 0.189 2.4 Rv3132c dosS sensor histidine kinase 2.00 0.014 0.18 0.001 11.0 Rv3133c dosR two-component response regulator 1.00 0.070 0.22 0.009 4.5 Rv3134c   conserved hypothetical protein 2.45 0.024 0.16 0.002 15.0 Rv3841 bfrB bacterioferritin 1.22 Thalidomide 0.106 1.36 0.087 0.9 Table 2 Genes differentially regulated for selected cell functions (p-value ≤ 0.05) ORF Gene Log 2expression   ORF Gene Log 2expression     merodiploid mutant     merodiploid mutant Fatty acid utilization   Ribosomal proteins   Rv0974c accD2 1.2 -0.2 Rv0056 rplI -1.0 -0.6 Rv1935c echA13 0.9 -0.2 Rv0682 rpsL -0.9 -0.9 Rv2486 echA14 1.0 -0.1 Rv0700 rpsJ -1.4 -0.5 Rv0456c echA2 1.2 -0.1 Rv0701 rplC -1.5 -0.4 Rv3550 echA20 1.1 0.2 Rv0716 rplE -1.2 -0.9 Rv0971c echA7 1.3 -0.1 Rv0722 rpmD -0.9 -0.3 Rv3546 fadA5 1.1 0.1 Rv0723 rplO -0.7 -0.2 Rv1715 fadB3 1.0 -0.1 Rv2441c rpmA -0.9 -0.5 Rv0099 fadD10 1.2 0.0 Rv3442c rpsI -0.9 -0.2 Rv1550 fadD11 1.0 0.2 Rv3443c rplM -1.6 -0.5 Rv1058 fadD14 1.2 0.0 Rv3458c rpsD -0.8 -0.5 Rv3561 fadD3 0.8 0.5 Rv3460c rpsM -1.3 -0.6 Rv0035 fadD34 1.3 0.0 Rv3461c rpmJ -1.4 -0.6 Rv0214 fadD4 0.8 -0.2 Rv3924c rpmH -1.