2006; Aroca et al. 2010). However, if pioneer esca species were indeed fungal saprobes specialized in wood decay, grapevine healthy shoots of the rootstock mother plant and of the selected cultivar used for grafting are unlikely to host any of these fungi. Once the grafting process terminated, nursery plants

do contain damaged tissues that can PHA-848125 in vivo be invaded by these fungal saprobes. In fact, several earlier studies reported Phaeomoniella chlamydospora and Phaeoacremonium species from nursery plants (Chicau et al. 2000; Edwards and Pascoe 2004; Giménez-Jaime et al. 2006; Halleen et al. 2003). However, Halleen et al. (2003) observed that these esca-associated fungal species were mostly associated with either the rootstock or the graft union. We concur with Halleen et al.

(2003) in that the best explanation for this result was the availability of sufficient weakened plant tissue due to the grafting process or through aerial contamination by fungal spores during the grafting process. Weeds sampled in grapevine rootstock mother PLX3397 fields have been shown to host Phaeomoniella chlamydospora, Cylindrocarpon macrodidymum and Cadophora luteo-olivacea (Agustí-Brisach et al. 2011). The high OICR-9429 in vivo occurrence of Cylindrocarpon in newly planted grapevines has been attributed to mechanical injuries of the young root callus during the planting process, exposing grapevine cuttings to infection by these soil-borne fungi (Halleen et al. 2003). A presumed saprotrophy for the esca fungi is also in line with observations that esca development is generally patchy in a vineyard and does not spread from a particular point of infection (Mugnai et al. 1999; Surico et al. 2006). Disease incidence and identity of presumed trunk disease-associated fungi have been shown to vary in function of studied grapevine cultivars, geography, soil type

and climate (Armengol et al. 2001; Bertsch et al. 2009; Casieri et al. 2009; Edwards et al. 2001; Larignon 2012; Larignon and Dubos 1997; Marchi 2001; Mugnai et al. 1999; Surico et al. 2006). At the same time, the host specificity of esca-associated fungal species is very broad and nearly all Cell Penetrating Peptide identified fungi that were recovered in this study have also been reported from other hosts (Online Resource 2). Therefore, fungal infection should be primarily dependent on the environmentally available species pool, including the presumed trunk disease associated species, and this for both young and adult grapevine plants. In more general terms, our study questions the presumed pathogenic status of fungi involved in other newly emerging diseases of plants and animals in cases where no significant differences were observed between the fungal communities that inhabit healthy and diseased individuals.

6 mm × 250 mm, Macherey Nagel,

Düren, Germany). Separation of the organic acid was performed this website with 1 mM H3PO4 in an isocratic water-acetonitrile eluent (45/55 (v/v)) at 1 mL/min and 25°C. Intermediary, the column was cleaned with water-acetonitrile (20/80 (v/v)). UV detection was performed at 215 nm. Acknowledgements We thank Robert Marmulla and Maria Grünberg for their technical mTOR inhibitor assistance in the construction of C. defragrans Δldi. This study was financed by the Max Planck Society. Electronic supplementary material Additional file 1: Additional Material. (PDF 889 KB) References 1. Lathiere J, Hauglustaine DA, Friend AD, De Noblet-Ducoudrè N, Viovy N, Folberth GA: Impact of climate variability and land use changes on global biogenic volatile organic compound

emissions. Atmos Chem Phys 2006, 6:2129–2146.CrossRef 2. Kesselmeier J, Staudt M: Biogenic volatile organic compounds (VOC): an overview on emission, physiology and ecology. J Atmos Chem 1999, 33:23–88.CrossRef 3. Dudareva N, Negre F, Nagegowda DA, Orlova I: Plant volatiles: recent advantages and future perspectives. Crit Rev Plant Sci 2006, 25:417–440.CrossRef 4. Sharkey TD, Wiberly AE, Donohue AR: Isoprene emission from plants: why and how. Ann Bot 2008, 101:5–18.PubMedCrossRef 5. Smolander A, Ketolab RA, Kotiahod T, Kanervaa S, Suominene K, Kitunena V: Volatile monoterpenes in soil atmosphere see more under birch and conifers: effects on soil N transformations. Soil Biol Biochem 2006, 38:3436–3442.CrossRef 6. Hayward S, Muncey RJ, James AE, Halsall CJ, Hewitt CN: Monoterpene emissions Y-27632 2HCl from soil in a Sitka spruce forest. Atmos Environ 2001, 35:4081–4087.CrossRef 7. Lin C, Owen SM, Penuelas J: Volatile organic compounds in the roots and rhizosphere of pinus spp. Soil Biol Biochem 2007, 39:951–960.CrossRef 8. Ramirez KS, Lauber CL, Fierer N: Microbial consumption and production of volatile organic compounds at the soil-litter interface. Biogeochemistry 2010, 99:97–107.CrossRef 9. Vokou D, Douvli P, Blionis GJ, Halley JM: Effects of monoterpenoids, acting alone or in pairs, on seed germination and

subsequent seedling growth. J Chem Ecol 2003, 29:2281–2301.PubMedCrossRef 10. Leff JW, Fierer N: Volatile organic compound (VOC) emissions from soil and litter samples. Soil Biol Biochem 2008, 40:1629–1636.CrossRef 11. Vokou D, Chalkos D, Karamanlidou G, Yiangou M: Activation of soil respiration and shift of the microbial population balance in soil as a response to lavendula stoechas essential oil. J Chem Ecol 2002, 28:755–768.PubMedCrossRef 12. Ajikumar PA, Tyo K, Carlsen S, Mucha O, Phon TH, Stephanopoulos G: Terpenoids: opportunities for biosynthesis of natural product drugs using engineered microorganisms. Mol Pharm 2008, 5:167–190.PubMedCrossRef 13. Flesch G, Rohmer M: Prokaryotic hopanoids: the biosynthesis of the bacteriohopane skeleton – formation of isoprenic units from two distinct acetate pools and a novel type of carbon/carbon linkage between a triterpene and D-ribose.

With regard to the last point, prospectively specified analysis plans for randomized phase III studies are

fundamental to achieve reliable results. Paradoxically, many of the currently ongoing trials for adjuvant treatment of resected NSCLC are designed in order to select patients on the basis of genetic features when ‘old-fashioned’ chemotherapeutics are experimented (i.e. the Spanish Customized Adjuvant Treatment, SCAT, randomizing patients on the basis of BRCA overexpression, the and the International TAilored Chemotherapy Adjuvant trial, ITACA, with a two-step randomization taking into account both levels of ERCC1 and TS tissue expression), and with a non-selection strategy, when adopting ‘new and targeted’ agents (i.e. erlotinib and bevacizumab in the RADIANT, Screening Library purchase and in the ECOG E1505 trial, respectively). In an ideal scenario, when complete information on predictive factors and proper selection of patients can be definitely obtained in the early phases of drug development, the conduction of subsequent phase III study could be optimized. Unfortunately, this ideal scenario occurs rarely, also with molecularly targeted agents. BGB324 supplier When planning a phase III trial comparing an experimental treatment with the standard, we

often have evidence supporting a predictive role of a marker (M) about the efficacy of the experimental treatment: according to that evidence, patients with expression of the marker (M+)

are expected to potentially benefit of the experimental treatment, and patients with absence of expression of the marker (M-) are not [32]. In such a scenario, different strategies based on prospective determination of marker CHIR98014 order status are theoretically possible: (a) “” randomize-all “” strategy, randomization between standard and experimental treatment without selection, bu with stratification based on the status of the marker; (b) “” targeted “” design, randomization between standard and experimental treatment only in patients selected according to the status of the marker; (c) “” customized “” strategy (also called “” marker-based strategy “”), randomization between standard arm, in which the treatment is the same for all patients, and a personalized arm, in which treatment is chosen based on the marker oxyclozanide status of each patient. The “” randomize-all “” strategy is useful if investigators are not sure of the complete lack of efficacy of experimental treatment in M- patients. Marker is prospectively assessed in all patients, allowing stratification, but all patients are randomized, regardless of the marker status. Interaction between marker status and treatment effect can be formally tested by an interaction test. On the contrary, predictive role of the marker should not be addressed with separate comparison in M+ and M- patients, because this approach, as stated before, would be associated with a high risk of false results [29].

PubMedCrossRef 23. Machida M, Asai K, Sano M, Tanaka T, Kumagai T, Terai G, Kusumoto K, Arima T, Akita O, Kashiwagi Y, et al.: Genome sequencing and selleck kinase inhibitor analysis of Aspergillus oryzae. Nature 2005,438(7071):1157–1161.PubMedCrossRef 24. Payne GA, Nierman WC, Wortman JR, Pritchard BL, Brown D, Dean RA, Bhatnagar

D, Cleveland TE, Machida M, Yu J: Whole genome comparison of Aspergillus flavus and A. oryzae. Med Mycol 2006, 44:S9-S11.CrossRef 25. Pel HJ, de Winde JH, Archer DB, Dyer PS, Hofmann G, Schaap PJ, Turner G, de Vries RP, Albang R, Albermann K, et al.: Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88. Nat Biotechnol 2007,25(2):221–231.PubMedCrossRef 26. Haynes KA, Latge JP, Rogers TR: Detection of Aspergillus antigens associated with invasive infection. J Clin Microbiol 1990,28(9):2040–2044.PubMed 27. Yu B, Niki Y, Armstrong D: Use of immunoblotting to detect Aspergillus fumigatus antigen in sera and urines of rats with experimental invasive aspergillosis. J Clin Microbiol 1990,28(7):1575–1579.PubMed

28. Beauvais A, Monod M, BIBW2992 molecular weight Debeaupuis JP, Diaquin M, Kobayashi H, Latge JP: Biochemical and antigenic characterization of a new dipeptidyl-peptidase isolated from Aspergillus fumigatus. J Biol Chem 1997,272(10):6238–6244.PubMedCrossRef 29. Benndorf D, Muller A, Bock K, Manuwald O, Herbarth O, von Bergen M: Identification of spore allergens from the indoor mould Aspergillus versicolor. Allergy 2008,63(4):454–460.PubMedCrossRef 30. Kumar A, Ahmed R, Singh PK, Shukla PK: Identification of virulence factors and diagnostic markers using ACY-1215 solubility dmso immunosecretome of Aspergillus fumigatus. J Proteomics 2011,74(7):1104–1112.PubMedCrossRef

31. Singh B, Oellerich M, Kumar R, Kumar M, Bhadoria DP, Reichard U, Gupta VK, Sharma GL, Asif AR: Immuno-reactive molecules identified from the secreted proteome of Aspergillus fumigatus. J Proteome Res 2010,9(11):5517–5529.PubMedCrossRef 32. Pitarch A, Abian J, Carrascal M, Sanchez M, Nombela Mannose-binding protein-associated serine protease C, Gil C: Proteomics-based identification of novel Candida albicans antigens for diagnosis of systemic candidiasis in patients with underlying hematological malignancies. Proteomics 2004,4(10):3084–3106.PubMedCrossRef 33. Gozalbo D, Gil-Navarro I, Azorin I, Renau-Piqueras J, Martinez JP, Gil ML: The cell wall-associated glyceraldehyde-3-phosphate dehydrogenase of Candida albicans is also a fibronectin and laminin binding protein. Infect Immun 1998,66(5):2052–2059.PubMed 34. Klotz SA, Pendrak ML, Hein RC: Antibodies to alpha5beta1 and alpha(v)beta3 integrins react with Candida albicans alcohol dehydrogenase. Microbiol (Reading, England) 2001,147(Pt 11):3159–3164. 35. Sarfati J, Monod M, Recco P, Sulahian A, Pinel C, Candolfi E, Fontaine T, Debeaupuis JP, Tabouret M, Latge JP: Recombinant antigens as diagnostic markers for aspergillosis. Diagn Microbiol Infect Dis 2006,55(4):279–291.PubMedCrossRef 36.

5 mL/min in 5 mM H2SO4 using an Aminex HPX-87H column (Bio-Rad Laboratories, Inc., Hercules, CA). RNA isolation and microarray analysis Fermentation samples for RNA isolation were harvested by spinning down ~30 mL culture in 50 mL Oak Ridge tubes at 8000 rpm and 4°C for 10-15 mins and the supernatant was discarded. The solid pellet fraction containing

cells and any residual Avicel® was resuspended in 1 mL of TRIzol (Invitrogen, Carlsbad, CA), flash frozen in liquid nitrogen and stored at -80°C until further use. Total RNA was extracted from the cell pellets as follows. Briefly, the frozen cell solution in TRIzol was thawed on ice and the cell solution (~1 mL) was added to a 2 mL tube containing 1 mL of 0.1 mm glass beads (BioSpec Products, Bartlesville, PSI-7977 mw OK) ashed at 250°C overnight. Cells were lysed by rapid agitation of the tubes at 6500 rpm for 1 min in three 20s-On/20s-Off cycles using the Precellys® bead beater (Bertin Technologies, France). Subsequently, the cell lysate (~0.8 mL) in TRIzol was phase separated by addition

of 200 μL chloroform and the RNA was precipitated by addition of 500 μL 100% isopropanol. Belnacasan The precipitated RNA pellet was washed with 1 mL of 75% ethanol and resuspended in 100 μL of RNase-free water. Any contaminating DNA was digested by in-solution DNase-I (Qiagen, Valencia, CA) treatment and the RNA sample was cleaned using the RNeasy mini kit (Qiagen, Valencia, CA) as per manufacturer’s instructions. The 6 hr time-point RNA sample was used as the reference and all other time-point samples (8, 10, 12, 14, 16 hr) were compared to the reference in cDNA/cDNA arrays. For each time-point comparison, equal amount of the extracted total RNA samples was labeled with Cy3-dUTP/Cy5-dUTP fluorescent dyes (GE Healthcare, Piscataway, NJ), mixed and hybridized

onto custom oligo-arrays in dye swap experiments as selleck described earlier [17] and microarray slides were scanned in ScanArray Express scanner (Perkin Elmer, Waltham, MA). Microarray construction and statistical data analysis Microarrays containing 2980 unique and 10 group 70-mer oligonucleotide probes representing ~97% of the 3163 Open Reading Frames (ORFs) SSR128129E in the draft assembly of C. thermocellum ATCC 27405 were constructed as described earlier [15]. The probe sequences were later compared to the completed genome sequence using reciprocal BLAST analysis and assigned new ORF numbers. Based on the comparison, 79 probes which did not have any BLAST hits and 108 probes that only had partial hits to annotated ORFs in the closed genome were either excluded or marked-up during downstream data analysis. Signals were quantified in ImaGene version 6.0 (BioDiscovery Inc., El Segundo, CA) and statistical data analysis was conducted using JMP Genomics software (SAS Institute Inc., Cary, NC). The array signal intensities were background-corrected, log2-transformed and data for duplicated probes on the arrays were averaged and normalized using the Data-Standardize method.

XD and SF assisted with in vivo experiments. MC conceived of the study and finalized the manuscript. All authors read and approved the final manuscript.”
“Background Endometriosis is a gynaecological disease defined by the histological presence of endometrial glands and stroma outside the uterine cavity. Most commonly, endometrial

structures are implanted over visceral and peritoneal surfaces, but rarely also in the pericardium, pleura, and even brain [1]. The prevalence in the general female population is 6-10%; in women with pain, infertility or both, the frequency increases to 35-60% [2]. Endometriosis is usually associated with infertility and pelvic pain such as chronic dysmenorrhea, intermestrual abdominal and pelvic pain, back pain, dysuria, dyschezia and dyspareunia [3]. Moreover, it is often associated with a decrease of ovarian reserve and reduction of ovarian selleck screening library volume [4]. Despite the fact that this disease is quite common

ARN-509 among women, it is frequently misdiagnosed, the pathogenesis is unknown and the diagnostic and therapeutic protocols are still not fully adequate [1, 3]. Currently, none of the pathogenetic theories proposed, such as retrograde menstruation, coelomic metaplasia or staminal cells, has definitively been proved [1]. Interestingly, our research group has recently demonstrated the presence of endometrial implants outside the uterus in a significant number of female human fetuses, thus demonstrating that alterations in the fine-tuning of the primitive mullerian tube formation is one of the causes of endometriosis [5–9]. The anti-mullerian hormone (AMH) is a homodimeric glycoprotein member of the transforming Chlormezanone growth factor β (TGF-β) superfamily, which is secreted by Sertoli cells in the embryonic testes and is responsible of the regression of the mullerian duct [10].

In the female fetus ovarian granulosa cells begin to secrete low levels of AMH starting from the 32 week of gestation. Levels surge at the time of puberty to approximately 5-8 ng/mL but then gradually decline throughout reproductive life until they this website become undetectable by menopause. Therefore, AMH levels are considered good indicators of the ovarian reservoir [11]. Recent studies have demonstrated that AMH, as well as AMHRII (one of its receptors), are expressed in the adult female also in the endometrium, where, probably, act in a paracrine fashion and that negatively regulates cellular viability in the endometrium [12]. Leaving from this background, we decided to deeply investigate the potential role of AMH in regulating cell viability and proliferation of endometriosis cells, taking advantage of an in vitro model of epithelial and stromal endometriosis cells, recently generated in our laboratory [13].

p.i.. The colour bar indicates photon emission with 4 min integration time in photons/s/cm2/sr. Uninfected Ifnb1 tm2.2Lien reporter mice are shown as controls at the top in (B). (C) Quantification of firefly luciferase light signals presented in (B) in Lmo-EGDe-lux (grey columns) and Lmo-InlA-mur-lux (black columns) infected IFN-β-reporter mice by measuring luminescence BMS202 supplier intensity in an identical selected region in each animal as indicated on the left. Data represent means ± SEM. Bacterial

luciferase photon emission was subtracted from firefly BLI signals to generate the graph shown in (C). One out of two representative experiments is shown (A-C). Oral infection challenge with ‘murinised’ Listeria does not result in increased neuroinvasion into the brain L. monocytogenes can induce meningitis, meningoencephalitis, and rhombenencephalitis in infected humans and animals [33]. It is currently not well understood which virulence factors of L. monocytogenes control the invasion of the pathogen into the central nervous system (CNS). InlA- and InlB-dependent uptake mechanisms have been suggested for direct invasion of L. monocytogenes into brain microvascular endothelial

cells and choroid plexus epithelial cells [34, 35]. Our Poziotinib clinical trial murinised Listeria infection model is permissive for InlA- and InlB-mediated invasion mechanisms and allows investigation of the role of InlA-Cdh1 interactions in listerial brain tropism. To test the hypothesis that InlA-Cdh1 interactions contribute to the invasion of L. monocytogenes into the brain we paid particular attention to the development of https://www.selleckchem.com/products/azd3965.html neurological abnormalities MRIP in Lmo-InlA-mur-lux and Lmo-EGD-lux infected mice. Interestingly, mice displaying abnormal neurological behaviour such as circling, head tilting or ataxia were very rarely

observed. From a total of 290 mice that were orally challenged with Lmo-InlA-mur-lux and Lmo-EGD-lux (5 × 109 CFU) and monitored for clinical symptoms only 3 animals developed neurological phenotypes (Table 1). These affected mice were identified in the A/J, BALB/cJ, and C57BL/6J inbred strains and occurred with equally low frequency in both Lmo-InlA-mur-lux and Lmo-EGD-lux challenged animals (Table 1). In these cases the appearance of neurological symptoms occurred at 7 d.p.i.. As described above, no major differences in bacterial brain loads were observed between Lmo-InlA-mur-lux and Lmo-EGD-lux challenged mice across the different investigated inbred strains (Figure 3). This was also true for the 7 d.p.i. timepoint when we did observe the above described rare neurological phenotypes in single mice of the C57BL/6J, A/J and BALB/cJ inbred strains but no differences in brain CFU loads among all cohorts of Lmo-InlA-mur-lux and Lmo-EGD-lux infected mice were detected (data not shown).

06 (0.52, 2.12) 0.91 (0.45, 1.85)   Raising 227 454 2.08 (1.76, 2.45) 1.75 (1.48, 2.08)  Orthostatic hypotensive

properties           Low 97 157 2.55 (1.98, 3.29) 2.08 (1.60, 2.71)   Medium 92 257 1.49 (1.17, 1.90) 1.27 (0.99, 1.64)   High 48 79 2.50 (1.74, 3.59) 2.19 (1.51, 3.18) aWhen more than one antipsychotic was dispensed simultaneously before the index date, then the antipsychotic with the most severe side effect was selected. For current, recent, and past users, the last antipsychotic was dispensed respectively within 30 days, between 31 and 182 days, and more than 182 days prior to the index date bAdjusted for confounders as before Discussion The findings of this study have demonstrated an increased NSC23766 risk of Selleckchem Emricasan hip/femur fracture with the use of antipsychotics. The risk was highest for current users, especially the most elderly. The use of conventional antipsychotics appeared to account for the increased risk, and there was evidence for an increased risk with prolactin-raising antipsychotics and those with greater potential to affect the extrapyramidal system. We did not find evidence to support an association between the average daily dose of antipsychotic and the risk of hip/femur

fracture. Our findings confirm an association described in other epidemiological studies on the risk of hip/femur fracture with the use of antipsychotics [13–19]. The 1.7-fold increased risk of fracture among current users and declining risk after discontinuation of use selleck kinase inhibitor agrees with the findings of others. Hugenholtz et al. [18] reported a 1.3-fold increased adjusted Rebamipide risk of fracture among current users who had been using antipsychotics long term, and produced a plot similar to ours for risk with cumulative days of treatment (Fig. 1). Ray et al. [16] reported a doubling of risk among current users (OR 2.0 [95% CI 1.6, 2.6]), although that risk estimate

may have been reduced with adjustment for more potential confounding variables. In agreement with other recent studies, we did not find an association between the average daily dose of antipsychotic and the risk of hip/femur fracture for current users [17, 18]. Vestergaard et al. [17] described a dose–response relationship for all users of antipsychotics before the index date but the association was not apparent for current users and the elapsed time between the last dispensing and the index date could have been as much as 4 years. Although we found a higher fracture risk for men currently using antipsychotics, the difference between the sexes was not significant. A greater fracture risk for men using antipsychotics has been reported before [13], however, which could reflect the effects of antipsychotic use and physiological processes promoting bone loss [9].

Because of a general lack of starting material, analysis of the skin microbiome mostly has been limited to analysis of those microbes on skin swabs or scrapings [20–22]. To analyze skin viral populations, Foulongne et al. recently used high-throughput sequencing techniques to sequence the skin metagenome, and to analyze those viruses present by targeted analysis of viral reads [23]. In most human sample types, the majority of the viruses Selleck PF 01367338 present have been identified as bacteriophage [1–3, 19], which may reflect the 10 to 1 proportion

of bacterial to human cells in these environments. In analysis of the skin virome, however, bacteriophage constituted only a small proportion of the metagenome sequences [23]. By examining the CRISPR spacer profiles of the skin, we may improve our understanding of the sequence features of viruses to which skin bacteria have previously encountered. Study of the human microbiome has detailed unique populations of microbes inhabiting different body surfaces. While the oral cavity and the skin Alvocidib chemical structure surfaces differ substantially in their bacterial constituents, they share some bacterial genera including some species from the genus Streptococcus[24]. Streptococci generally are present on the skin and in the saliva of most humans [25–28], and represent a substantial proportion

of the oral microbiota and a much smaller proportion of the skin microbiota [29–33]. The human oral cavity is known to harbor various types of viridans streptococci, including S. mutans, S. gordonii, S. oralis, S. mitis, PCI-32765 in vivo S. milleri (includes S. anginosus, S. constellatus, and S. intermedius), S. sanguinis, and S. parasanguinis, and also some non-viridans streptococci, including S. bovis (includes S. gallolyticus, S. equinus, and S. infantarius, among others). selleck products The skin generally harbors different species of streptococci, including S. pyogenes and S. agalactiae, which

belong to Lancefield groups A and B, respectively. The skin also is known to harbor streptococci that belong to Lancefield groups C and G [24]. In this study, we sought to characterize the CRISPR profiles present in a cohort of human subjects on both their skin and in their oral cavities. Our goals were to determine whether there were similar CRISPR profiles among streptococci on human skin and saliva, whether CRISPR content on the skin and saliva was relatively conserved over time, and whether there were CRISPR spacers present on human skin that matched viruses present in saliva. Results CRISPR spacer sequencing We sampled 4 human subjects with good overall cutaneous and periodontal health, collecting skin swabs and saliva samples 3 times per day on days #1, #2, #4, #14, #28, and week #8. Skin and saliva samples were collected at the same time in the AM prior to breakfast or oral hygiene (AM), approximately noon each day before lunch (Noon), and in the early evening prior to dinner [34].

Tobe T, Hayashi T, Han CG, Schoolnik GK, Ohtsubo E, Sasakawa C: Complete DNA sequence and structural analysis of the enteropathogenic Escherichia coli

Selleckchem MGCD0103 adherence factor plasmid. Infect Immun 1999, 67:5455–5462.PubMed 8. Cleary J, Lai LC, Shaw RK, Straatman-Iwanowska A, Donnenberg MS, Frankel G, Knutton S: Enteropathogenic Escherichia coli (EPEC) adhesion to intestinal epithelial cells: role of bundle-forming pili (BFP), EspA filaments and intimin. Microbiology 2004, 150:527–538.CrossRefPubMed 9. Tobe T, Sasakawa C: Role of bundle-forming pilus of enteropathogenic Escherichia coli in host cell adherence and in microcolony development. Cell Microbiol 2001, 3:579–585.CrossRefPubMed 10. Bieber D, Ramer SW, Wu CY, Murray WJ, Tobe T, Fernandez R, Schoolnik GK: Type IV pili, transient bacterial aggregates, and virulence of enteropathogenic Escherichia coli. Science 1998, 280:2114–2118.CrossRefPubMed 11. Donnenberg MS, Tacket CO, James SP, Losonsky G, Nataro JP, Wasserman SS, Kaper JB, Levine MM: Role of the eaeA gene in experimental enteropathogenic Escherichia coli infection. J Clin Invest 1993, 92:1412–1417.CrossRefPubMed 12. Levine MM, Nataro JP, Karch H, Baldini MM, Kaper JB, Black RE, Clements ML, O’Brien AD: The diarrheal response of humans to some classic serotypes of enteropathogenic Escherichia

coli is dependent on a LY2109761 in vivo plasmid encoding an enteroadhesiveness factor. J Infect Dis 1985, 152:550–559.PubMed 13. Kaper JB: Defining EPEC. Rev Microbiol 1996,27(suppl 1):130–133. 14. Nguyen RN, Taylor LS, Tauschek LY3023414 molecular weight M, Robins-Browne RM: Atypical enteropathogenic Escherichia coli infection and

prolonged diarrhea in children. Emerg Infect Dis 2006, 12:597–603.PubMed 15. Afset JE, Bevanger L, Romundstad P, Bergh K: Association of atypical enteropathogenic Escherichia coli (EPEC) with prolonged diarrhoea. J Med Microbiol 2004, 53:1137–1144.CrossRefPubMed 16. Hill SM, Phillips AD, Walker-Smith JA: Enteropathogenic Escherichia coli and life threatening chronic diarrhoea. Gut 1991, 32:154–158.CrossRefPubMed 17. Bielaszewska M, Middendorf B, Kock R, Friedrich AW, Fruth A, Karch H, Schmidt MA, Mellmann A: Shiga toxin-negative attaching and effacing Escherichia coli : distinct clinical very associations with bacterial phylogeny and virulence traits and inferred in-host pathogen evolution. Clin Infect Dis 2008, 47:208–217.CrossRefPubMed 18. Hornitzky MA, Mercieca K, Bettelheim KA, Djordjevic SP: Bovine feces from animals with gastrointestinal infections are a source of serologically diverse atypical enteropathogenic Escherichia coli and Shiga toxin-producing E. coli strains that commonly possess intimin. Appl Environ Microbiol 2005, 71:3405–3412.CrossRefPubMed 19. Pohl PH, Peeters JE, Jacquemin ER, Lintermans PF, Mainil JG: Identification of eae sequences in enteropathogenic Escherichia coli strains from rabbits. Infect Immun 1993, 61:2203–2206.PubMed 20.