79 research outputs found

    Combined 1H-Detected solid-state NMR spectroscopy and electron cryotomography to study membrane proteins across resolutions in native environments

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    Membrane proteins remain challenging targets for structural biology, despite much effort, as their native environment is heterogeneous and complex. Most methods rely on detergents to extract membrane proteins from their native environment, but this removal can significantly alter the structure and function of these proteins. Here, we overcome these challenges with a hybrid method to study membrane proteins in their native membranes, combining high-resolution solid-state nuclear magnetic resonance spectroscopy and electron cryotomography using the same sample. Our method allows the structure and function of membrane proteins to be studied in their native environments, across different spatial and temporal resolutions, and the combination is more powerful than each technique individually. We use the method to demonstrate that the bacterial membrane protein YidC adopts a different conformation in native membranes and that substrate binding to YidC in these native membranes differs from purified and reconstituted system

    Factors confounding the assessment of reflection: a critical review

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    BACKGROUND: Reflection on experience is an increasingly critical part of professional development and lifelong learning. There is, however, continuing uncertainty about how best to put principle into practice, particularly as regards assessment. This article explores those uncertainties in order to find practical ways of assessing reflection. DISCUSSION: We critically review four problems: 1. Inconsistent definitions of reflection; 2. Lack of standards to determine (in)adequate reflection; 3. Factors that complicate assessment; 4. Internal and external contextual factors affecting the assessment of reflection. SUMMARY: To address the problem of inconsistency, we identified processes that were common to a number of widely quoted theories and synthesised a model, which yielded six indicators that could be used in assessment instruments. We arrived at the conclusion that, until further progress has been made in defining standards, assessment must depend on developing and communicating local consensus between stakeholders (students, practitioners, teachers, supervisors, curriculum developers) about what is expected in exercises and formal tests. Major factors that complicate assessment are the subjective nature of reflection's content and the dependency on descriptions by persons being assessed about their reflection process, without any objective means of verification. To counter these validity threats, we suggest that assessment should focus on generic process skills rather than the subjective content of reflection and where possible to consider objective information about the triggering situation to verify described reflections. Finally, internal and external contextual factors such as motivation, instruction, character of assessment (formative or summative) and the ability of individual learning environments to stimulate reflection should be considered

    Accurate Prediction of Secreted Substrates and Identification of a Conserved Putative Secretion Signal for Type III Secretion Systems

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    The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates—effector proteins—are not. We have used a novel computational approach to confidently identify new secreted effectors by integrating protein sequence-based features, including evolutionary measures such as the pattern of homologs in a range of other organisms, G+C content, amino acid composition, and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from the plant pathogen Pseudomonas syringae and validated on a set of effectors from the animal pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) after eliminating effectors with detectable sequence similarity. We show that this approach can predict known secreted effectors with high specificity and sensitivity. Furthermore, by considering a large set of effectors from multiple organisms, we computationally identify a common putative secretion signal in the N-terminal 20 residues of secreted effectors. This signal can be used to discriminate 46 out of 68 total known effectors from both organisms, suggesting that it is a real, shared signal applicable to many type III secreted effectors. We use the method to make novel predictions of secreted effectors in S. Typhimurium, some of which have been experimentally validated. We also apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis, identifying the majority of known secreted proteins in addition to providing a number of novel predictions. This approach provides a new way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal
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