5 Tumor location             Colon 77 65.3 6 5.1 71 60.2 Rectum 40 33.9 5 4.2 35 29.7 Both 1 0.8 0 0 1 0.8 Ethnic status             Caucasian 98 83.1 10 8.5 88 7.5 African American 14 11.9 1 0.8 13 11.0 Asian 3 2.5 0 0 3 2.5 Hispanic 3 2.5 0 0 3 2.5 Stage at diagnosis             Stage 1 11 9.3 1 0.8 10 8.5 Stage 2 30 25.4 5 4.2 25 21.2 Stage 3 44 37.3 1 0.8 43 36.4 Stage 4 33 28.0 4 3.4 29 24.6 Family history             No 76 64.4 7 5.9

69 58.5 Yes 34 28.8 3 2.5 31 26.3 Unknown 8 6.8 1 0.8 7 5.9 Association of TGFBR1 SNPs with TGFBR1 allele-specific expression Three SNPs in linkage disequilibrium with each other were strongly associated with TGFBR1 ASE: rs7034462 (p = 7.2 × 10-4), TGFBR1*6A (p = 1.6 × 10-4) and rs11568785 (p = 1.4 × 10-4) (Table 2). TGFBR1*6A is located within the coding sequence of exon 1 and the other two SNPs are located within introns. rs7034462 is located 9.2 kb upstream of exonn 1 and rs11568785 is located Selleck RXDX-106 850 bp downstream of exonn 5 and 1.18 kb upstream of exonn 6. These results are consistent with our earlier findings as each of these SNPs was significantly

associated with TGFBR1 ASE in our original study. PLX4032 For example, in this study six (54.5%) of the 11 patients with TGFBR1 ASE carried the TGFBR1*6A allele. In our previous report 14 (48.3%) of the 29 patients with TGFBR1 ASE carried the TGFBR1*6A allele. This provides additional evidence of a central role for TGFBR1*6A in colorectal cancer, especially as it relates to the TGFBR1 ASE phenotype. Studies are currently in progress to validate the association of TGFBR1

SNPs with colorectal cancer risk. Table 2 Association of TGFBR1 SNPs with constitutively decreased TGFBR1 allelic expression (TGFBR1 ASE).   Frequency Allele 2     SNP ASE < 0.67 or > 1.5 1.5 > ASE > 0.67 P OR rs4742761 0.14 0.25 0.38 0.5 rs2416666 0.19 0.19 0.98 1.0 rs7874183 0.13 0.28 0.20 0.4 rs7034462 0.31 0.05 7.2 × 10-4 8.3 rs10819634 0.06 0.26 0.08 0.2 rs1888223 0.50 0.30 0.11 2.3 9A/6A 0.31 0.04 1.6 × 10-4 10.9 rs10988705 0.00 0.04 0.42 n/a rs6478974 0.50 0.47 0.82 1.1 rs10739778 0.38 0.36 0.89 1.1 rs2026811 0.25 0.32 0.57 0.7 rs10512263 0.00 0.11 0.16 n/a rs11568785 0.25 0.02 1.4 × 10-4 16.0 rs334348 0.31 0.39 0.55 0.7 rs7871490 Amobarbital 0.50 0.46 0.77 1.2 rs334349 0.25 0.43 0.19 0.5 rs7850895 0.07 0.06 0.87 1.2 rs1590 0.25 0.39 0.28 0.5 rs1626340 0.25 0.32 0.57 0.7 Discussion These findings confirm the relatively high frequency of the TGFBR1 ASE phenotype in patients with colorectal cancer. The phenotype frequency among Caucasian patients included in this study (10.2%) is similar to that of the Caucasian patients studied in our earlier report (12.0%)[14]. Intriguingly, Guda et al.

234 ± 0.014 0.223 ± 0.024 0.234 ± 0.048 0.241 ± 0.021 0.240 ± 0.015 0.278 ± 0.027 0.263 ± 0.054 0.215 ± 0.020 Ka 0.035 ± 0.003 0.028 ± 0.004 0.088

± 0.015 0.030 ± 0.005 0.034 ± 0.003 0.039 ± 0.005 0.062 ± 0.014 0.027 ± 0.004 Ka/Ks 0.150 ± 0.017† 0.125 ± 0.024 0.374 ± 0.100 0.125 ± 0.022 0.142 ± 0.016† 0.139 ± 0.023 0.234 ± 0.072 0.127 ± 0.024 * Out-of-frame sequences were excluded. Mol., molecular No., number nt, nucleotides Ks, Synonymous substitutions Ka, Non-synonymous substitutions Pictilisib purchase † PZ-Test <0.001 for purifying selection hypothesis (Ka/Ks <1). &Value ± Standard Error. Bold print highlights the higher molecular distance, Ka and Ka/Ks observed for segment 2, compared to the entire gene and to segments 1

and 3. Analysis of the similarity plot of the 124 nucleotide sequences of homB and homA genes showed the existence of three distinct regions in both genes, named segments 1, 2 and 3, corresponding to the 5, middle and 3′ regions of the genes, respectively AZD0530 manufacturer (Fig. 3). The analysis performed independently on the three segments of each gene showed that segment 2 displayed the highest molecular distance as well as the highest Ka, even when compared to the entire gene (Table 1). These results were confirmed by the analysis of the nucleotide substitution rate over a sliding window, which also showed a significant increase in the Ka in segment 2 of homB gene. In fact, the mean Ka for this region (0.191 ± 0.059) was five fold higher than for second the rest of the gene (0.037 ± 0.023). The same result was observed for homA gene (data not shown). These observations reveal a higher level of diversity of segment 2 in both genes. Figure 3 Similarity plot representation of homB (black lines) and homA (grey lines) genes of various Helicobacter pylori strains. The plot

was generated by using 16 strains representative of each gene, with the Jukes-Cantor correction (1-parameter), a 200-bp window, a 20-bp step, without Gap Strip and the jhp870 gene sequence as reference (GenBank accession number NC_000921). The arrow delineates the region which discriminates between homB and homA genotypes. bp, base pair. A phylogenetic analysis on each gene segment of 24 strains carrying one copy of each gene was also performed. The phylogenetic reconstruction of segment 1 showed that homB presented the highest similarity between orthologous genes, i.e., each homB was closely related to the homB in the other strains (Fig. 4A). A similar result was obtained for homA gene (Fig. 4A). In contrast, for segment 3, each homB was strongly correlated with the corresponding homA present in the same strain, indicating similarity between paralogous genes (Fig. 4B). The mean molecular distance and mean synonymous and non-synonymous substitution rates were calculated for all possible pairs of paralogous and orthologous genes, within the same strain and between strains.

This result indicated that it is the normal endogenous activity of RhoA and Rac1 that defines the efficiency of cell invasion by T. Raf inhibitor gondii tachyzoites, but not the amount of these proteins. This requirement is also reported in other intracellular pathogens. Shigella entry into HeLa cells induces membrane ruffling

at the bacterial entry site, and the three Rho isoforms were recruited into bacterial entry sites. This membrane folding caused by invasion was abolished by using a Rho-specific inhibitor, and bacterial entry was impaired accordingly [34]. Hela cells transfected with the dominant negative versions of Rac1 or RhoA reduced group B Streptococcus invasion by 75% and 51%, respectively, suggesting that Rho GTPases are indispensable for efficient invasion of HeLa cells by this bacterium [35]. In MDCK cells, RhoA and Rac1were activated during Trypanosoma cruzi invasion and then triggered the reorganization of F-actin cytoskeleton, especially distinct

in the invasion position on the cell membrane. The invasion of T. cruzi G strain extracellular amastigotes was specifically learn more inhibited in Rac1-N17 dominant-negative cells [36, 37]. After the invasion of the rabbit corneal epithelial cells (SIRC) by Candida albicans, host cell actin filaments formed a rigid ring-like structure in the host cell. Immunochemical staining of actin and the expression of chimeric green fluorescent protein (GFP)-GTPases (RhoA, Rac1) showed the colocalization Non-specific serine/threonine protein kinase of the GTPases with actin at invasion and actin polymerization sites, but this colocalization was not seen in SIRC cells expressing a GFP-tagged dominant-negative mutant of GTPases. Inhibition of invasion was observed in SIRC cells expressing dominant-negative mutants of Rac1

and RhoA GTPases [38]. These findings suggest that many pathogens may employ conserved pathways for invasion. The Rho and Rac cell signaling involved in the cytoskeleton reorganization triggered by T. gondii invasion When epithelial cells are stimulated by EGF, c-Src is activated by EGF-induced EGF receptor activation [39]. After the activation of c-Src, Ephexin, VAV-2 and Tiam 1 are rapidly phosphorylated by c-Src [40, 41]. Phosphorylation of Ephexin promotes its GTPase activity toward RhoA [42, 43], and RhoA downstream effector Rho-associated kinase ROCK directly phosphorylates LIM-kinases LIMK1 and LIMK2, which in turn phosphorylates actin-depolymerizing factor destrin and actin-associated protein cofilin [44]. ROCK2 kinase phosphorylates CRMP2, and the phosphorylation of CRMP2 reduces its tubulin-heterodimer binding and the promotion of microtubule assembly [45, 46]. Activation of VAV-2 activates RhoA and Rac1 [47]. Downstream of Rac1, p21-activated kinase 1 (PAK1) activates LIMK1, and regulates the actin cytoskeletal reorganization through the phosphorylation of the actin-depolymerizing factors cofilin and destrin and their actin-depolymerizing activities [48, 49].

Kühn I, Albert MJ, Ansaruzzaman M, Bhuiyan NA, Alabi SA, Islam MS, Neogi PK, Huys G, Janssen P, Kersters K, Möllby R: Characterization of Aeromonas spp. isolated from humans

with diarrhea, from healthy controls, and from surface water in Bangladesh. J Clin Microbiol 1997, 35:369–373.PubMed 8. Albert MJ, Ansaruzzaman M, Talukder KA, Chopra AK, Kuhn I, Rahman M, Faruque AS, Islam MS, Sack RB, Mollby R: Prevalence of enterotoxin genes in Aeromonas spp. isolated from children with diarrhea, healthy controls, and the environment. J Clin Microbiol 2000, 3790:3785. 9. Romano S, Aujoulat F, Jumas-Bilak PD0325901 E, Masnou A, Jeannot J-L, Falsen E, Marchandin H, Teyssier C: Multilocus sequence typing supports the hypothesis that Ochrobactrum anthropi displays a human-associated subpopulation. BMC Microbiol 2009, 9:267.PubMedCrossRef 10. van Mansfeld R, Jongerden I, Bootsma M, Buiting A, Bonten M, Willems R: The population genetics of Pseudomonas aeruginosa isolates from different patient populations PD-0332991 in vitro exhibits high-level host specificity. PLoS One 2010, 5:e13482.PubMedCrossRef 11. Aujoulat F, Jumas-Bilak E, Masnou A, Sallé F, Faure D, Segonds C, Marchandin H, Teyssier C: Multilocus sequence-based analysis delineates a clonal population of Agrobacterium (Rhizobium) radiobacter (Agrobacterium tumefaciens) of human origin. J Bacteriol 2011, 193:2608–2618.PubMedCrossRef 12. Bidet P, Mahjoub-Messai F, Blanco J, Blanco J, Dehem

M, Aujard Y, Bingen E, Bonacorsi S: Combined multilocus sequence typing and O serogrouping distinguishes Escherichia coli subtypes associated with infant urosepsis and/or meningitis. J Inf Dis 2007, 196:297–303.CrossRef 13. Hoffmaster AR, Novak RT, Marston CK, Gee JE, Helsel L, Pruckler JM, Wilkins PP: Genetic diversity of clinical isolates of Bacillus cereus using multilocus

sequence typing. BMC Microbiol 2008, 8:191.PubMedCrossRef 14. Kaiser S, Biehler K, Jonas D: A Stenotrophomonas maltophilia multilocus sequence typing scheme for inferring population structure. J Bacteriol 2009, 191:2934–2943.PubMedCrossRef 15. Martino ME, Fasolato L, Montemurro F, Rosteghin M, Manfrin A, Patarnello T, learn more Novelli E, Cardazzo B: Determination of microbial diversity of aeromonas strains on the basis of multilocus sequence typing, phenotype, and presence of putative virulence genes. Appl Environ Microbiol 2011, 77:4986–5000.PubMedCrossRef 16. Martinez-Murcia AJ, Monera A, Saavedra MJ, Oncina R, Lopez-Alvarez M, Lara E, Figueras MJ: Multilocus phylogenetic analysis of the genus Aeromonas. Syst Appl Microbiol 2011, 34:189–199.PubMedCrossRef 17. Lamy B, Kodjo A, Laurent F: Prospective nationwide study of Aeromonas infections in France. J Clin Microbiol 2009, 47:1234–1237.PubMedCrossRef 18. Miranda G, Kelly C, Solorzano F, Leanos B, Coria R, Patterson JE: Use of pulsed-field gel electrophoresis typing to study an outbreak of infection due to Serratia marcescens in a neonatal intensive care unit. J Clin Microbiol 1996, 34:3138–3141.PubMed 19.

Hybridized slides were scanned using HP Scan array 5000 (PerkinElmer Inc., Waltham, MA). The images

were processed and numerical data was extracted using the microarray image analysis software, BlueFuse (BlueGnome Ltd, Cambridge) and TM4 microarray suite available through JCVI. Genes differentially regulated at a fold change of 1.5 or greater were identified at a false discovery rate of 1% by Statistical Analysis of Microarrays (SAM) program [26]. Genes that showed a fold change 1.5 or greater in all the replicate arrays were retained and reported as being up- or downregulated in the presence of iron. Realtime RT-PCR RNA isolated from MAP strains grown under iron-replete or iron-limiting growth medium was used in real time RT-PCR assays. Genes were selected based GSK3235025 on their

diverse roles and microarray expression pattern. Selected genes included siderophore transport (MAP2413c, MAP2414c), esx-3 secretion system (MAP3783, MAP3784), aconitase (MAP1201c), fatty Gemcitabine in vitro acid metabolism (MAP0150c) and virulence (MAP0216, MAP3531c, MAP1122 and MAP0475). RNA was treated with DNaseI (Ambion, Austin, TX) and one step Q-RT PCR was performed using QuantiFast SYBR Green mix (Qiagen, Valencia, CA) and gene specific primers (Additional file 1, Table S1) in a Lightcycler 480 (Roche, Indianapolis, IN). iTRAQ experiments Protein extracted from the two MAP strains grown in iron-replete or Dapagliflozin iron-limiting medium was used in iTRAQ analysis (Additional file 1, Figure S3). iTRAQ labeling and protein identification was carried out as described previously with minor modifications [27]. Briefly, cell lysate was quantified using the bicinchoninic acid (BCA) protein assay (Pierce, Rockford, IL) prior to trypsin digestion. Peptides were labeled with iTRAQ reagents (114 and 115 for MAP 1018 grown in iron-replete and iron-limiting medium respectively; 116 and 117 for MAP 7565 grown in iron-replete and iron-limiting medium respectively)

at lysine and arginine amino terminal groups. The labeled peptides were pooled, dried and re-suspended in 0.2% formic acid. The re-suspended peptides were passed through Oasis® MCX 3CC (60 mg) extraction cartridges per manufacturer recommendations (Waters Corporation, Milford, MA) for desalting prior to strong cation exchange (SCX) fractionation. Eluted peptides were dried and dissolved in SCX buffer A (20% v/v ACN and 5 mM KH2PO4 pH 3.2, with phosphoric acid) and fractionated using a polysulfoethyl A column (150 mm length × 1.0 mm ID, 5 μm particles, 300 Å pore size) (PolyLC Inc., Columbia, MD) on a magic 2002 HPLC system (Michrom BioResources, Inc., Auburn, CA). Peptides were eluted by running a 0-20% buffer B gradient for greater than 55 min. and 20%-100% buffer B (20% v/v ACN, 5 mM KH2PO4 pH 3.2, 500 mM KCL) for 20 min. at a column flow rate of 50 μl/min.

For translation into the clinic it is important to observe that besides NK cells, relatively small numbers of NKT and T cells are expanded in this system. These cell populations may mediate GvHD when infused together with NK cells in adoptive allogeneic immunotherapy protocols. GvHD is a serious, potentially life-threatening, condition resulting from transplanted or infused allogeneic donor cell recognition of the recipients’ tissues as non-self, and is predominantly mediated by CD3+ T cells [30]. These cells are often depleted to prevent GvHD, as could be accomplished with the cells expanded by the protocol

presented here. Depletion of T cells from the NK cell product before administration to the host is likely to be less critical in the autologous setting. An important observation SAR245409 cost in our studies was that the expanded NK cells did not kill autologous and allogeneic PBMC, an indication that despite the increase in surface expression of activating receptors on the NK cells, the inhibitory ligands expressed on normal PBMC were dominant and able to control cytolytic activity against non-malignant cells. This is further illustrated in that both AZD1152-HQPA supplier gastric tumor

cell lines were susceptible to autologous cytotoxicity Oxalosuccinic acid despite the expression of high levels of inhibitory classical and non-classical HLA class I molecules. These data suggest that, under certain conditions, activating receptor-ligand recognition may override receptor-ligand interactions that inhibit NK activity. Emerging data indicates that important triggers in this

interaction are surface structures (ligand) that are expressed on cells that have undergone malignant transformation. In addition, it is well recognized that HLA class I expression the major NK cell inhibitory structure, is often down regulated in many solid tumors. In the case of autologous NK cell cytotoxicity against PBMC, inhibitory signals still predominated over activating signals, since no cytotoxicity of NK cells against autologous or allogeneic PBMC was observed. Our results indicate that the NK cells expanded and activated by the methods described do not recognize and kill non-transformed cells. In addition, while significantly higher levels of the inhibitory CD94/NKG2A complex were expressed after ex-vivo cell expansion, it did not affect the potential of autologous gastric tumor cell recognition. The CD94/NKG2A complex is reported to directly inhibit NK cell cytotoxicity through recognition of HLA-E [31].

Similarities between restriction endonuclease digestion profiles were buy Nutlin-3 analyzed by using Unweighted Pair Group Method with Arithmetic Mean (UPGMA) of BioNumerics

software (Applied Maths, Kortrijk, Belgium). Multi-locus sequence typing and phylogenetic analysis The MLST scheme available at http://​www.​pasteur.​fr/​recherche/​genopole/​PF8/​mlst/​Lmono.​html was used. The nucleotide sequences of internal fragment of the following genes, acbZ (ABC transporter), bglA (beta-glucosidase), cat (catalase), dapE (succinyl diaminopimelate desuccinylase), dat (D-amino acid aminotransferase), ldh (L-lactate dehydrogenase), and lhkA (histidine kinase), were obtained by PCR using published primers (Table  1) with the exception of primers for lhkA. A new pair of primers for lhkA (lhkAF 5′-GTTTTCCCAGTCACGACGTTGTATTATCAAAGCAAGTAGATG-3′ and lhkAR 5′-TTGTGAGCGGATAACAATTTCTTTCACTTTTTGGAATAATAT-3′) were designed to amplify the lhkA gene from the isolates which had no amplification products when the published primers were used. A 50-μl reaction was composed as follows: 5.0 μl of 10 × pfu buffer with 1.5 mM MgCl2, 125 μM each of deoxynucleoside triphosphate mix, 0.2 μM forward and reverse primers, 0.5U of pfu DNA polymerase, and 2U of rTaq DNA polymerase.

The PCR amplification conditions were as follow: 94°C for 4 min and 30 cycles of 94°C for 30 s, 52°C for 30s, and 72°C for 2 min, followed by one cycle of 72°C for BGJ398 mouse 10 min and hold Methocarbamol indefinitely at 4°C. The purified PCR products were sent for sequencing commercially. For each isolate, the allele combination at the 7 loci defines

an allelic profile or sequence type (ST). Minimum spanning tree (MST) analysis was used to infer relationships among the isolates and was done using BioNumerics (Applied Maths, Belgium). Neighbor-joining tree of the seven concatenated housekeeping gene sequences was constructed using MEGA 4.0 [30]. A clonal complex (CC) is defined based on eBURST algorithm with member STs differing by only one of the 7 MLST genes [23]. Results Serotyping The 212 isolates used in this study were typed into seven of the 13 known serotypes: 1/2a, 1/2b, 1/2c, 3a, 3b, 4b and 4c. The most frequent serotypes are 1/2c, 1/2a and 1/2b with a frequency of 36.8%, 33.5% and 19.8% respectively. The remaining 4 serotypes account for only 9.9% of the total isolates. Pulsed-field gel electrophoresis PFGE analysis divided the 212 isolates into 61 pulse types (PTs). PTGX6A16.0004 was predominant and accounts for 26.5% of the isolates, followed by GX6A16.0011 (17 isolates), and GX6A16.0009 (13 isolates). Thirty two PTs (52.5%) were represented by only a single isolate. A UPGMA dendrogram was constructed for the 61 PTs based on presence or absence of bands. The PTs are divided into 3 clusters. Cluster I contained all serotype 1/2c isolates, the majority of serotype 1/2a isolates. Cluster II contained all serotype 4b and 1/2b isolates and the remaining serotype 1/2a isolates.

In addition to TPP, the negative groups on the surface

of ASNase II were counteracted with the positively charged -NH3 + groups of CS during the cross-linking process. Moreover, TPP could counteract with the positively charged -NH3 + groups on the surface of ASNase II and compact the enzyme both inside and on the surface of the particle. Particles possessing a zeta potential of about 20 to 25 mV may sometimes be considered relatively stable [37]. However, having a sufficient KU-57788 ic50 zeta potential is extremely important for the role of nanoparticles as carriers for drugs or proteins; the nanoparticles must be capable of ionically holding active molecules or biomolecules. Nanoparticle used for the final characterization were loaded with 4 mg lyophilized ASNase II. Fourier transform infrared spectrometry analysis The FTIR spectra for ASNase II (a), CS (b), CSNPs (c), and ASNase II-loaded CSNPs (d) are shown in Figure 2. The peaks at find more 3,291 cm−1 in the ASNase II spectrum (a) and at 3,288 cm−1 in the CS spectrum (b) relate to the stretching of O-H and N-H bonds. In the CSNPs spectrum (c), a shift from 3,288 to 3,299 cm−1 is seen and the peak at 3,299 cm−1 becomes more intense; this indicates the -NH3 + interactions with TPP. A corresponding peak in the ASNase II-loaded CSNPs (d) at 3,294 cm−1 becomes wider; this effect is attributable to the participation

of ASNase II in hydrogen bonding and -NH group interactions [38]. In CSNPs, a new sharp peak appears at 1,409 cm−1 and the 1,594 cm−1 peak of -NH2 bending vibration shifts to 1,536 cm−1.

We suppose that the SDHB phosphoric groups of TPP are linked with -NH3 + group of CS; inter- and intra-molecular interactions are enhanced in CSNPs [39]. A shift from 1,027 cm−1 to the sharper peak at 1,032 cm−1 corresponds to the stretching vibration of the P = O groups in CSNPs. Two peaks at 1,636 cm−1 (amide I bending) and 1,544 cm−1 (amide II bending) in ASNase II-loaded CSNPs correspond to the high intensity peaks at 1,638 and 1,536 cm−1 in the ASNase II spectra; this result proves successful loading of ASNase II in CSNPs and also indicates some interactions between CS with TPP and ASNase II [40]. Figure 2 FTIR spectra of (A) ASNase II, (B) CS, (C) CSNPs, and (d) ASNase II-loaded CSNPs. Morphology studies for the nanoparticles Figure 3 shows the TEM images of CSNPs and ASNase II-loaded CSNPs. From the TEM images, both CSNPs (Figure 3A) and ASNase II-loaded CSNPs (Figure 3B) are spherical and exist as discrete spheres, along with a few partial cohesive spheres. The dark core of nanoparticles is due to the fact that the staining reagent has penetrated through the particle. In Figure 3A, a fairly uniform size (the average size 250 ± 11 nm, PDI ~ 0.48) distribution and the smooth border around the CSNPs could be observed. In Figure 3B, ASNase II-loaded CSNPs exhibit an irregular surface with a core surrounded by a fluffy coat made of ASNase II.

We previously identified SiaR as a repressor for these two operons, in addition to the role of CRP in activating the expression of the transporter [14]. In this study, we present data that expands on our previous work, providing Smoothened Agonist key details about the unique regulation of these adjacent operons. The two operons required for the transport and catabolism of

sialic acid were found to be simultaneously regulated by SiaR and CRP in a novel mechanism for cooperative regulation. SiaR functions as both a repressor and activator, utilizes GlcN-6P as a co-activator, and interacts with CRP to regulate two adjacent and divergently transcribed promoters. Since H. influenzae cannot transport the intermediates of the sialic acid catabolic pathway [13, 18], mutants in each gene of the pathway were used to examine the role of the sugar and phosphosugar intermediates in the expression of the SiaR-regulated operons. Increased expression of the nan operon in the 2019ΔcyaA ΔnagB double mutant suggested that GlcN-6P functions as a co-activator. This is unusual because catabolic pathways are typically regulated by the presence of the substrate. SiaR likely uses GlcN-6P as a co-activator because

sialic acid is utilized rapidly after transport by H. influenzae, either by activation with SiaB or catabolism beginning with NanA. Thus, sialic acid never BGB324 datasheet accumulates to levels that would allow for sufficient expression of the transporter. In contrast, using GlcN-6P allows for moderate activation of siaPT to provide for transport of sialic acid. Since GlcN-6P can

also be synthesized by the cell, expression of the transporter is not reliant on the presence of high levels of sialic acid, while increased sialic acid and catabolism will elevate levels of GlcN-6P and increase expression of the nan and siaPT operons. Even though GlcN-6P is not an endpoint in the catabolic pathway, transient levels of the phosphosugar likely allow for sufficient expression PI-1840 of the two operons. In addition to identifying GlcN-6P as a co-activator, we found that SiaR and CRP interact to regulate both the nan and siaPT operons. Both regulators were able to bind to their operators simultaneously, demonstrating that binding of one protein does not prevent the binding of the other. cAMP-dependent activation of nanE requires SiaR. Furthermore, regulation of the two operons was uncoupled by the insertion of one half-turn of DNA between the SiaR and CRP operators. This insertion resulted in the loss of SiaR influence on siaPT expression and the loss of nan induction by cAMP. Based on this data and the proximity of the two operators, it can be concluded that SiaR and CRP interact to impact the expression of the two operons. This interaction may be the result of direct contacts between the two regulators or cooperative effects on DNA topography, however we cannot make any conclusions on the mechanism at this time.

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