53 research outputs found

    Architecture and roles of periplasmic adaptor proteins in tripartite efflux assemblies.

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    Recent years have seen major advances in the structural understanding of the different components of tripartite efflux assemblies, which encompass the multidrug efflux (MDR) pumps and type I secretion systems. The majority of these investigations have focused on the role played by the inner membrane transporters and the outer membrane factor (OMF), leaving the third component of the system - the Periplasmic Adaptor Proteins (PAPs) - relatively understudied. Here we review the current state of knowledge of these versatile proteins which, far from being passive linkers between the OMF and the transporter, emerge as active architects of tripartite assemblies, and play diverse roles in the transport process. Recognition between the PAPs and OMFs is essential for pump assembly and function, and targeting this interaction may provide a novel avenue for combating multidrug resistance. With the recent advances elucidating the drug efflux and energetics of the tripartite assemblies, the understanding of the interaction between the OMFs and PAPs is the last piece remaining in the complete structure of the tripartite pump assembly puzzle

    Structure and in situ organisation of the Pyrococcus furiosus archaellum machinery

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    This is the final version of the article. Available from the publisher via the DOI in this record.The archaellum is the macromolecular machinery that Archaea use for propulsion or surface adhesion, enabling them to proliferate and invade new territories. The molecular composition of the archaellum and of the motor that drives it appears to be entirely distinct from that of the functionally equivalent bacterial flagellum and flagellar motor. Yet, the structure of the archaellum machinery is scarcely known. Using combined modes of electron cryo-microscopy (cryoEM), we have solved the structure of the Pyrococcus furiosus archaellum filament at 4.2 Å resolution and visualise the architecture and organisation of its motor complex in situ. This allows us to build a structural model combining the archaellum and its motor complex, paving the way to a molecular understanding of archaeal swimming motion.This project was funded by the Max Planck Society (BD, JV, WK), the University of Exeter Research Fellow’s Startup grant (BD), the ERC starting grant ‘ARCHAELLUM’ (511323; SVA) and the University of Regensburg (ReR, RaR, AB

    Comparative analyses of transport proteins encoded within the genomes of Leptospira species

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    Select species of the bacterial genus Leptospira are causative agents of leptospirosis, an emerging global zoonosis affecting nearly one million people worldwide annually. We examined two Leptospira pathogens, L. interrogans serovar Lai str. 56601 and L. borgpetersenii serovar Hardjo-bovis str. L550, as well as the free-living leptospiral saprophyte, L. biflexa serovar Patoc str. ‘Patoc 1 (Ames)’. The transport proteins of these leptospires were identified and compared using bioinformatics to gain an appreciation for which proteins may be related to pathogenesis and saprophytism. L. biflexa possesses a disproportionately high number of secondary carriers for metabolite uptake and environmental adaptability as well as an increased number of inorganic cation transporters providing ionic homeostasis and effective osmoregulation in a rapidly changing environment. L. interrogans and L. borgpetersenii possess far fewer transporters, but those that they all have are remarkably similar, with near-equivalent representation in most transporter families. These two Leptospira pathogens also possess intact sphingomyelinases, holins, and virulence-related outer membrane porins. These virulence-related factors, in conjunction with decreased transporter substrate versatility, indicate that pathogenicity arose in Leptospira correlating to progressively narrowing ecological niches and the emergence of a limited set of proteins responsible for host invasion. The variability of host tropism and mortality rates by infectious leptospires suggests that small differences in individual sets of proteins play important physiological and pathological roles

    Comparative genomic analyses of transport proteins encoded within the genomes of Leptospira species

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    Select species of the bacterial genus Leptospira are causative agents of leptospirosis, an emerging global zoonosis affecting nearly one million people worldwide annually. We examined two Leptospira pathogens, L. interrogans serovar Lai str. 56601 and L. borgpetersenii serovar Hardjo-bovis str. L550, as well as the free-living leptospiral saprophyte, L. biflexa serovar Patoc str. ‘Patoc 1 (Ames)’. The transport proteins of these leptospires were identified and compared using bioinformatics to gain an appreciation for which proteins may be related to pathogenesis and saprophytism. L. biflexa possesses a disproportionately high number of secondary carriers for metabolite uptake and environmental adaptability as well as an increased number of inorganic cation transporters providing ionic homeostasis and effective osmoregulation in a rapidly changing environment. L. interrogans and L. borgpetersenii possess far fewer transporters, but those that they have are remarkably similar, with near-equivalent representation in most transporter families. These two Leptospira pathogens also possess intact sphingomyelinases, holins, and virulence-related outer membrane porins. These virulence-related factors, in conjunction with decreased transporter substrate versatility, indicate that pathogenicity was accompanied by progressively narrowing ecological niches and the emergence of a limited set of proteins responsible for host invasion. The variability of host tropism and mortality rates by infectious leptospires suggests that small differences in individual sets of proteins play important physiological and pathological roles

    Laminar flow devices for the measurement of diffusional coefficients of proteins and protein complexes

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    The type II secretion system – a dynamic fiber assembly nanomachine

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    International audienceType II secretion systems (T2SSs) share common origins and structure with archaeal flagella (archaella) and pili, bacterial competence systems and type IV pili. All of these systems use a conserved ATP-powered machinery to assemble helical fibers that are anchored in the plasma membrane. The T2SSs assemble pseudopili, periplasmic filaments that promote extracellular secretion of folded periplasmic proteins. Comparative analysis of T2SSs and related fiber assembly nanomachines might provide important clues on their functional specificities and dynamics. This review focuses on recent developments in the study of pseudopilus structure and biogenesis, and discusses mechanistic models of pseudopilus function in protein secretion

    An automatic tool to analyze and cluster macromolecular conformations based on self-organizing maps.

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    International audienceSampling the conformational space of biological macromolecules generates large sets of data with considerable complexity. Data-mining techniques, such as clustering, can extract meaningful information. Among them, the self-organizing maps (SOMs) algorithm has shown great promise; in particular since its computation time rises only linearly with the size of the data set. Whereas SOMs are generally used with few neurons, we investigate here their behavior with large numbers of neurons. We present here a python library implementing the full SOM analysis workflow. Large SOMs can readily be applied on heavy data sets. Coupled with visualization tools they have very interesting properties. Descriptors for each conformation of a trajectory are calculated and mapped onto a 3D landscape, the U-matrix, reporting the distance between neighboring neurons. To delineate clusters, we developed the flooding algorithm, which hierarchically identifies local basins of the U-matrix from the global minimum to the maximum. Availability and implementation: The python implementation of the SOM library is freely available on github: https://github.com/bougui505/SOM. [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online
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