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Abstract

Actin-depolymerizing factor (ADF)/cofilin proteins are key players in controlling the temporal and spatial extent of actin dynamics, which is crucial for mediating host–pathogen interactions. Pathogenic microbes have evolved molecular mechanisms to manipulate cofilin activity to subvert the actin cytoskeletal system in host cells, promoting their internalization into the target cells, modifying the replication niche and facilitating their intracellular and intercellular dissemination. The study of how these pathogens exploit cofilin pathways is crucial for understanding infectious disease and providing potential targets for drug therapies.  相似文献   
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The rate at which nonsynonymous single nucleotide polymorphisms (nsSNPs) are being identified in the human genome is increasing dramatically owing to advances in whole‐genome/whole‐exome sequencing technologies. Automated methods capable of accurately and reliably distinguishing between pathogenic and functionally neutral nsSNPs are therefore assuming ever‐increasing importance. Here, we describe the Functional Analysis Through Hidden Markov Models (FATHMM) software and server: a species‐independent method with optional species‐specific weightings for the prediction of the functional effects of protein missense variants. Using a model weighted for human mutations, we obtained performance accuracies that outperformed traditional prediction methods (i.e., SIFT, PolyPhen, and PANTHER) on two separate benchmarks. Furthermore, in one benchmark, we achieve performance accuracies that outperform current state‐of‐the‐art prediction methods (i.e., SNPs&GO and MutPred). We demonstrate that FATHMM can be efficiently applied to high‐throughput/large‐scale human and nonhuman genome sequencing projects with the added benefit of phenotypic outcome associations. To illustrate this, we evaluated nsSNPs in wheat (Triticum spp.) to identify some of the important genetic variants responsible for the phenotypic differences introduced by intense selection during domestication. A Web‐based implementation of FATHMM, including a high‐throughput batch facility and a downloadable standalone package, is available at http://fathmm.biocompute.org.uk .  相似文献   
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We have demonstrated that mannose-binding lectin (MBL) recognizes various slow-growing, pathogenic mycobacteria [Mycobacterium tuberculosis (MTB), M. bovis, M. kansasii, M. gordonae] as well as non-pathogenic M. smegmatis. Recognition resulted in activation of the lectin pathway (LP) of complement and an enhancement of phagocytosis (shown for M. tuberculosis). Although MBL may be considered the main factor activating the LP upon recognition of mycobacteria, involvement of ficolins has also to be considered. Interaction of ficolin-3 with M. tuberculosis, M. bovis and M. kansasii, and ficolin-1 with M. tuberculosis and M. bovis was shown for the first time. Binding of recombinant MBL or ficolin-3 to MTB H37Rv led to the agglutination of bacteria and promoted their phagocytosis, but little effect was apparent with ficolin-1 or ficolin-2. Data from Western blots suggest mannosylated lipoarabinomannan (ManLAM) to be one of the main cell components of slow-growing mycobacteria, involved in LP activation. However, the LP was also activated by other cell fractions. Results presented here supplement considerably the data concerning the ability of complement-activating lectins to interact with mycobacteria. Ficolins (especially ficolin-3) might influence host response to infection and thus have clinical significance, at least as disease modifiers.  相似文献   
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