Bioserotype Location Source 52203 4/O:3 The Pasteur Institute, Fr

Bioserotype Location Source 52203 4/O:3 The Pasteur Institute, France Purchased from the Pasteur Institute by the Institute of Chinese Biomedicine. 52212 4/O:9     52211 1B/O:8     Pa40134 4/O:3 Japan Provided by Dr. H. Fukushima (Public Health Institute of Shimane Prefecture, Matsue, Japan). ye3vp-/03 3/O:3     ye3vp5/03

click here 3/O:3     ye4/03 4/O:3     D92 2/O:5,27     Pa12986 1B/O:8     Ye92010 1BO:8     8081 1B/O:8 Complete genome sequence of the highly pathogenic Yersinia enterocolitica subsp. enterocolitica 8081 (Genbank: NC_008800). Primer nucleotide sequences The primers for ail and foxA were designed in our laboratory, referencing sequences from GenBank (ail: M29945, foxA: X60447), and synthesized by Shanghai Sangon Biological Engineering & Technology and Service Co., Ltd, China. The primers for ail amplify the entire ORF, while those for foxA amplify the ORF coding region from nt 28 to nt 1,461 (Table 3). Table 3 Primer sequences and annealing temperatures

for ail and foxA. Target gene and primer direction Primer Sequences (5′→ 3′) GenBank no. Location (nt) Amplicon length Annealing temp. ail Forward GGT TAT TGT ATT AGT ATT DNA Damage inhibitor GTT M29945 AZD8186 446-466 585 bp 57°C   Reverse CAG GTG GGT TTT CAC TAT CTG   1031-1051     foxA Forward CTC TGC GGA AGA TAA CTA TG X60447 389-408 1532 bp 58°C   Reverse ATC CGG GAA TAA ACT TGG CGT A

  1899-1920     PCR, DNA sequencing and sequence analysis Bacteria were cultured as previously described [18]. The bacterial DNA was extracted using a Blood & Tissue Kit (QIAGEN, USA). PCR was performed in a 200 μl volume containing 10 ng DNA template, 5U Taq DNA polymerase (TaKaRa, China), 0.2 mM of each dNTP, 1 μM of each forward and reverse primer, 1.5 mM MgCl2, 50 mM KCl, and 10 mM Tris-HCl (pH 8.3). Thermal cycling was done in a MJ PTC200 (Bio-Rad, USA) and the conditions were: one cycle of denaturation at 94°C for 5 min, followed by 25 cycles of melting at 94°C for 15 s, annealing for 30 s at various temperatures depending on the primers used (Table 3), elongation at 72°C for 30 s, and a final extension at 72°C for 10 min. Five microliters of PCR product was electrophoresed on a 1.5% agarose gel. The gel image was captured using a Gel Documentation 2000 (Bio-Rad, USA).

In Pseudomonas syringae, the GacS/GacA two-component system regul

In Pseudomonas syringae, the GacS/GacA two-component system regulates the production of the phytotoxins syringomycin and syringopeptin [18–20], tabtoxin [21, 22] and phaseolotoxin [23]. In P. syringae pv. tomato DC3000, GacS/GacA regulate the hrpR, hrpS, and hrpL genes, which are required for the activation of the Hrp type III secretion and

effector genes [24, 25]. However, in P. syringae pv. syringae B728a, GacA appears not to be required for hrp gene expression [25]. The mgo operon is composed of four genes, mgoBCAD[4, 7]. Mutants in each gene belonging to the mgo operon showed an alteration (mgoB mutant) or lack of mangotoxin production (mgoC, mgoA and mgoD mutants). These genes GDC-0994 mw encode for different hypothetical proteins with predicted domains for a haem oxygenase (MgoB), a p-aminobenzoate N-oxygenase (MgoC), a nonribosomal peptide synthetase (MgoA), and a polyketide cyclase/dehydrase or lipid transporter (MgoD) [4, 7]. The predicted amino MI-503 purchase acid sequence of MgoA suggests only one amino acid activation module and 14 conserved domains, including aminoacyl adenylation, condensation, thiolation, and additional

reduction domains [4]. Genes homologous to the mgo operon have been found in the genomes of most Pseudomonas spp., with the exception of P. protegens Pf-5 and CHAO [26, 27]. Recent studies on the pvf gene cluster in P. entomophila, a homologue of the mgo operon, suggested that it affects virulence [28]. Almost all the fluorescent Pseudomonas spp. lack the mbo operon [29, 30], but the mgo operon is conserved in all of them (except P. protegens Pf-5) [4, 7, 26–28]. To date, however, the functions of mgo operon are yet unknown. The overall objective of this study was

to get insight into the role of the mgo operon in regulation of mangotoxin production in P. syringae pv. syringae UMAF0158 and unravel the interplay between mgo, mbo and the gacS/gacA two-component regulatory system. Methods Bacterial strains and culture conditions The wild type strain P. syringae pv. syringae UMAF0158 (CECT 7752) and the collection of selected derivative mutants used in this study (Table 1) were grown on Pseudomonas agar F (Difco) plates, in liquid King’s medium B (KMB) [31] or in Pseudomonas minimal medium Resveratrol (PMS) [32] at 28°C. Escherichia coli strain DH5α was used as a host for plasmid complementation experiments. It was routinely grown on Luria-Bertani (LB) plates or in LB broth at 37°C. Antibiotics for selection of P. syringae pv. syringae UMAF0158 and E. coli derivatives were ampicillin (100 mg L-1), kanamycin (50 mg L-1), gentamycin (30 mg L-1) or tetracycline (25 mg L-1). Table 1 Bacterial strains and plasmids used in this study Strain or plasmid Relevant characteristics Reference/source Strains     E. coli     DH5α E. coli [F’ Φ80lacZ ∆M15 ∆(lacZYA-argF)U169 deoR recA endA1 hsdR17 (rK-mK+)phoA supE44 lambda- thi-1] [33] CECT831 Indicator strain for mangotoxin production CECTa P. syringae pv.

Environ Toxicol 24:343–356CrossRef

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Infect Immun 2009,77(6):2447–2454 CrossRefPubMed 26 Zarnowski R,

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A full description of this capacity to interact with another euka

A full description of this capacity to interact with another eukaryotic host will undoubtedly contribute to a clearer understanding of taylorellae biology and provide new insight into the evolution of these microorganisms. Acknowledgements Julie Allombert was supported by a PhD Selleck Selumetinib fellowship from the French Ministry of Higher Education and Research. This work was supported by grants from the European Regional Development Fund and by the Basse-Normandie Regional Council (http://​www.​cr-basse-normandie.​fr). ANSES’s Dozulé Laboratory for Equine Diseases is a member of the Hippolia Foundation. We also wish to thank Delphine Libby-Claybrough, professional

translator and native English speaker, for reviewing this article prior to publication. References 1. Wakeley PR, Errington J, Hannon S, Roest HIJ, Carson T, Hunt B, Sawyer J, Heath P: Development of a real time PCR for the detection of Taylorella equigenitalis directly from genital swabs and discrimination from Taylorella asinigenitalis . Vet Microbiol 2006,118(3–4):247–254.PubMedCrossRef 2. Timoney PJ: Horse species

symposium: contagious equine metritis: an insidious threat to the horse breeding industry in the United States. J Anim Sci 2011,89(5):1552–1560.PubMedCrossRef 3. Matsuda M, Moore JE: Recent advances in molecular epidemiology and detection of Taylorella equigenitalis associated with contagious equine this website metritis (CEM). Vet Microbiol 2003,97(1–2):111–122.PubMedCrossRef 4. Luddy S, Kutzler MA: Contagious equine metritis within the United States: a review of the 2008 outbreak. J Equine Vet Sci 2010,30(8):393–400.CrossRef 5. Crowhurst RC: Genital infection in mares. Vet Rec 1977,100(22):476.PubMedCrossRef 6. Timoney PJ, Ward J, Kelly P: A contagious genital infection of mares. Vet Rec 1977,101(5):103.PubMedCrossRef 7. Schulman ML, May CE, Keys B, Guthrie AJ: Contagious equine metritis: artificial

reproduction changes the epidemiologic paradigm. Vet Microbiol 2013,167(1–2):2–8.PubMedCrossRef 8. Jang S, Donahue J, Arata A, Goris J, Hansen L, Earley D, Vandamme P, Timoney P, Hirsh D: Taylorella asinigenitalis from sp. nov., a bacterium isolated from the genital tract of male donkeys ( Equus asinus ). Int J Syst Evol Microbiol 2001,51(3):971–976.PubMedCrossRef 9. Katz JB, Evans LE, Hutto DL, Schroeder-Tucker LC, Carew AM, Donahue JM, Hirsh DC: Clinical, bacteriologic, serologic, and pathologic features of infections with atypical Taylorella equigenitalis in mares. J Am Vet Med Assoc 2000,216(12):1945–1948.PubMedCrossRef 10. Hébert L, Moumen B, Pons N, Duquesne F, Breuil M-F, Goux D, Batto J-M, Laugier C, Renault P, Petry S: Genomic characterization of the Taylorella genus. PLoS One 2012,7(1):e29953.PubMedCentralPubMedCrossRef 11. Donahue JM, Timoney PJ, Carleton CL, Marteniuk JV, Sells SF, Meade BJ: Prevalence and persistence of Taylorella asinigenitalis in male donkeys. Vet Microbiol 2012,160(3–4):435–442.PubMedCrossRef 12.

Methods Sampling & experimental procedures To explore the relatio

Methods Sampling & experimental procedures To explore the relationship between host genetic differentiation and microbiome composition in response to environmental stress we collected oysters on 18th and 23rd of January 2008 from PD-1 phosphorylation three oyster beds in the northern Wadden Sea covering two tidal basins, the Sylt-Rømø-Bight (Diedrichsenbank – DB 55° 02′ 32.13″ N, 08° 27′ 02.86″ E, Oddewatt OW 55° 01′ 41.20″ N,

08° 26′ 17.31″ E) and the Hörnum Deep (Puan Klent PK 54° 47′ 29.59″ N, 08° 18′ 18.52″ E, see Figure 1). We chose to collect oysters in winter because diversity and abundance of pathogenic strains are correlated with temperature [27] and the input of transient open water pathogens could potentially be minimised this way. From each bed we collected 20 oysters by picking single, unattached individuals from soft-bottom mud flats. After collection half of the oysters were frozen (−20°C) while the other half was transferred to large buckets (20 L) filled with sand-filtered seawater (salinity 29‰). We kept groups of oysters in these buckets under constant aeration at densities of

10 oyster/bucket. To minimise allochthonous input of microbes and facilitate spread of potential pathogens we decided to use static conditions with no flow-through and did not feed the oysters during the experimental treatment. All experimental animals were exposed to a heat-shock treatment by increasing water temperature from ambient 2°C to 26°C over a time span of 10 days, before individuals were frozen at −20°C. We chose this steep temperature increase to maximise heat-induced stress for the host selleck chemicals llc and to allow potential pathogens to proliferate since temperatures of >20° are often associated with pathogen induced mass mortalities

[24, 28]. Our disturbance treatment thus combined aspects of transfer, food and heat stress. All experiments complied with German legal standards. For genetic analyses a small piece of gill tissue was removed from each individual oyster and DNA was extracted using the Wizard Genomic DNA Purification kit (Promega, Mannheim) following the manufacturer’s instructions. Niclosamide We decided to use gill tissue because gills constitute large contact surfaces to the surrounding water and should thus capture both, resident bacteria as well as bacteria from the environment. Furthermore, it has been shown that gill microbiota of Mediterranean oysters are more distinct from surrounding waters than those associated with gut tissue [18]. We used 14 oysters per bed (7 ambient ones frozen immediately and 7 exposed to disturbance treatment in the lab) for genetic analysis and microbiome sequencing. Figure 1 Geographic location and genetic differentiation between investigated oyster beds. Stars indicate the location of the oyster beds and boxes the pairwise genetic differentiation (F ST ) between host populations.

Microbial heterogeneity in natural aquatic samples is well known;

Microbial heterogeneity in natural aquatic samples is well known; bacteria and viruses have been shown to form aggregates or be in close association with organic particles [16, 17]. Table 2 Comparison of back-staining and pre-staining of Anodisc membranes in VLP enumeration of three sample types Sample Filtera Staining method Rinse VLP b CV c   Ano 25 Back No 1.32 × 106 (0.08) 5.7   Ano 25 Back Yes 1.32 × 106 (0.10) 7.5 Cyanophage lysate Ano 25 Pre No 1.63 this website × 106 (0.07) 4.5   Ano 25 Pre Yes 1.54 × 106 (0.15) 9.6   Ano 13 Pre No 1.29 × 106 (0.13) 10.1   Ano 13 Pre Yes 1.26 × 106 (0.07) 5.8   Ano 25 Back No 9.59 × 105 (1.86) 19.4   Ano 25 Back Yes 1.66 × 105 (0.37) 22.5 Sargasso Sea water

Ano 25 Pre No 7.50 × 105 (1.30) 17.3   Ano 25 Pre Yes 1.75 × 105 (0.17) 9.7   Ano 13 Pre No 5.93 × 105 (1.15) 19.3   Ano 13 Pre Yes 2.28 × 105 (0.54) 23.5   Ano 25 Back No 14.99 × 105 (0.45) 3.0   Ano 25 Back Yes 3.22 × 105 (1.06) 32.9 Southeastern US coastal waters Ano 25 Pre No 4.41 × 105 (0.62)

13.9   Ano 25 Pre Yes 3.28 × 105 (0.35) 10.7   Ano 13 Pre No 2.58 × 105 (0.35) 13.7   Ano 13 Pre Yes 2.75 × 105 (0.41) 14.9 a Anodisc™ 25 mm (Ano 25) and 13 mm (Ano 13) membranes b Average VLP abundance from triplicate filters along with the standard deviation c The percent coefficient of variation from 3 replicate measures. Discrepancies in VLP counts due to staining method and post-rinsing are most likely a reflection of differences in concentration and composition selleck chemicals llc of viral communities (in terms of size and fluorescence) as well as organic material in the natural samples. For

example, coastal environments and other highly productive systems typically contain a higher proportion of eukaryotic algae in the plankton then do oligotrophic systems, such as the open ocean [18]. Viruses that infect algae are routinely isolated and have been shown to be quite large in size (capsid, 100-220 nm) and contain large genomes [19, 20]. A higher proportion of smaller, less fluorescent viruses in the open ocean could contribute to lower VLP counts after post-rinsing. The issue of including a post-rinse in the processing of natural samples for VLP enumeration is environment dependent and beyond the scope of this report, which is designed to illustrate the comparability of sample Metalloexopeptidase processing with the 13 mm and 25 mm Anodisc membranes. Analysis of Nuclepore membranes The same samples described in the previous section were also processed using Nuclepore filters. Due to the low flow rate of Nuclepore membranes, filtering times have been traditionally quite long (> 1 hr). To maximize flow rates, existing protocols were modified. Specialized backing filters and filter holders were used and details are provided in the methods section. VLP enumeration from natural samples using Nuclepore membranes were generally an order of magnitude lower than parallel enumerations conducted using the Anodisc membranes (data not shown).

Combining these data with the other experimental conditions descr

Combining these data with the other experimental conditions described in Brenner et al. (2005), we selected six genes (NDHC, NDHI, RPS2, RPS3, RPS11, RPOC2) that were stable (with exception of NDHI and NDHC in 15 or 120 min BA treatment) under all Antifection chemical the experimental conditions. Stability of reference genes cDNA samples from leaves of transgenic plants with elevated or diminished cytokinin content (Polanská et al. 2007; Synková et al. 1999), as well as from the respective control plants were used to amplify these candidate reference genes. Relative expression data of each cDNA sample were used for geNorm algorithm. The geNorm algoritm calculates a measure M for each reference gene, which reflects

the expression stability of the gene, compared to the other reference genes; a lower M-value Selleck JAK inhibitor means a more stable gene expression. As cytokinins influence

both nuclear- and plastid-encoded genes, it is highly important to know which reference genes (nuclear- and/or plastid-encoded) should be used to normalize our real-time PCR data. Two different geNorm analyses were performed. In a first analysis, when only the nuclear-encoded reference genes were considered, Nt-ACT9, NT-αTUB and Nt-SSU turned out to be the most stable reference genes (Fig. 1a). Analyses of the plastid-encoded reference genes resulted in Nt-RPS3, Nt-NDHC and Nt-IN1 as the best reference genes (Fig. 1b). Fig. 1 Evaluation of reference genes in Nicotiana tabacum (Pssu-ipt/ckx) with the pairwise variation measure. The pairwise variation measure ‘V n/n+1’ measured the effect of adding additional reference genes on the normalisation factor for these treatments. Stepwise exclusion of the reference genes with the highest M value resulted in a ranking of the candidate reference genes when a nuclear-encoded reference genes (18S rRNA (18S), elongationfactor

1α (elongation), actin 9 (actin9), alfa-tubulin (tubulin) and small subunit of RubisCO (rbcS)); or b plastid-encoded reference genes (ribosomal protein S2 (rps2), ribosomal protein S11 Interleukin-2 receptor (rps11), 16S rRNA (16S rRNA), RNA polymerase beta subunit 2 (rpoC2), β subunit of acetyl-CoA carboxylase (accD), NADH dehydrogeanse D3 (ndhC), NADH dehydrogenase subunit (ndhI), initiation factor 1 (ini1) and ribosomal protein S3 (rps3)) were considered The geNorm algorithm also determines the pairwise variation V n/n+1, which indicates how many reference genes should be included, by measuring the effect of adding further reference genes on the normalisation factor. The V-graph of the nuclear-encoded reference genes (Fig. 1a) shows that inclusion of a fourth gene would increase the stability of the normalization, but since this decrease in pairwise variation is not so large, we propose to use only the three most stable nuclear-encoded genes as reference genes. The V-graph of the plastid-encoded reference genes (Fig.