35 research outputs found

    Microarray analysis of the Ler regulon in enteropathogenic and enterohaemorrhagic Escherichia coli strains

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    The type III protein secretion system is an important pathogenicity factor of enteropathogenic and enterohaemorrhagic Escherichia coli pathotypes. The genes encoding this apparatus are located on a pathogenicity island (the locus of enterocyte effacement) and are transcriptionally activated by the master regulator Ler. In each pathotype Ler is also known to regulate genes located elsewhere on the chromosome, but the full extent of the Ler regulon is unclear, especially for enteropathogenic E. coli. The Ler regulon was defined for two strains of E. coli: E2348/69 (enteropathogenic) and EDL933 (enterohaemorrhagic) in mid and late log phases of growth by DNA microarray analysis of the transcriptomes of wild-type and ler mutant versions of each strain. In both strains the Ler regulon is focused on the locus of enterocyte effacement – all major transcriptional units of which are activated by Ler, with the sole exception of the LEE1 operon during mid-log phase growth in E2348/69. However, the Ler regulon does extend more widely and also includes unlinked pathogenicity genes: in E2348/69 more than 50 genes outside of this locus were regulated, including a number of known or potential pathogenicity determinants; in EDL933 only 4 extra-LEE genes, again including known pathogenicity factors, were activated. In E2348/69, where the Ler regulon is clearly growth phase dependent, a number of genes including the plasmid-encoded regulator operon perABC, were found to be negatively regulated by Ler. Negative regulation by Ler of PerC, itself a positive regulator of the ler promoter, suggests a negative feedback loop involving these proteins

    An item response theory approach to longitudinal analysis with application to summer setback in preschool language/literacy

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    Background: As the popularity of classroom observations has increased, they have been implemented in many longitudinal studies with large probability samples. Given the complexity of longitudinal measurements, there is a need for tools to investigate both growth and the properties of the measurement scale. Methods: A practical IRT model with an embedded growth model is illustrated to examine the psychometric characteristics of classroom assessments for preschool children, and also to show how nonlinear learning over time can be investigated. This approach is applied to data collected for the Academic Rating Scale (ARS) in the literacy domain, which was administered on four occasions over two years. Results: The model enabled an effective illustration of overall and individual gains over two academic years. In particular, a significant de-acceleration in latent literacy skills during summer was observed. The results also provided psychometric support for the argument that ARS literacy can be used to assess developmental skill levels consistent with theories of early literacy acquisition. Conclusions: The proposed IRT approach provided growth parameters that are estimated directly, rather than obtaining these coefficients from estimated growth scoresβ€”which may result in biased and inconsistent estimates of growth parameters. The model is also capable of simultaneously representing parameters of items and persons
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