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  • 1
    Publication Date: 2015-10-20
    Description: Enterococcus faecalis is both a common commensal of the human gastrointestinal tract and a leading cause of hospital-acquired infections. Systemic infections with multidrug-resistant enterococci occur subsequent to gastrointestinal colonization. Preventing colonization by multidrug-resistant E. faecalis could therefore be a valuable approach towards limiting infection. However, little is known about the mechanisms E. faecalis uses to colonize and compete for stable gastrointestinal niches. Pheromone-responsive conjugative plasmids encoding bacteriocins are common among enterococcal strains and could modulate niche competition among enterococci or between enterococci and the intestinal microbiota. We developed a model of colonization of the mouse gut with E. faecalis, without disrupting the microbiota, to evaluate the role of the conjugative plasmid pPD1 expressing bacteriocin 21 (ref. 4) in enterococcal colonization. Here we show that E. faecalis harbouring pPD1 replaces indigenous enterococci and outcompetes E. faecalis lacking pPD1. Furthermore, in the intestine, pPD1 is transferred to other E. faecalis strains by conjugation, enhancing their survival. Colonization with an E. faecalis strain carrying a conjugation-defective pPD1 mutant subsequently resulted in clearance of vancomycin-resistant enterococci, without plasmid transfer. Therefore, bacteriocin expression by commensal bacteria can influence niche competition in the gastrointestinal tract, and bacteriocins, delivered by commensals that occupy a precise intestinal bacterial niche, may be an effective therapeutic approach to specifically eliminate intestinal colonization by multidrug-resistant bacteria, without profound disruption of the indigenous microbiota.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Kommineni, Sushma -- Bretl, Daniel J -- Lam, Vy -- Chakraborty, Rajrupa -- Hayward, Michael -- Simpson, Pippa -- Cao, Yumei -- Bousounis, Pavlos -- Kristich, Christopher J -- Salzman, Nita H -- AI057757/AI/NIAID NIH HHS/ -- AI081692/AI/NIAID NIH HHS/ -- AI097619/AI/NIAID NIH HHS/ -- GM099526/GM/NIGMS NIH HHS/ -- OD006447/OD/NIH HHS/ -- England -- Nature. 2015 Oct 29;526(7575):719-22. doi: 10.1038/nature15524. Epub 2015 Oct 19.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Division of Gastroenterology, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA. ; Department of Microbiology and Molecular Genetics, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA. ; Division of Quantitative Health Sciences, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26479034" target="_blank"〉PubMed〈/a〉
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 2
    Publication Date: 2012-06-23
    Description: Defensins are antimicrobial peptides that contribute broadly to innate immunity, including protection of mucosal tissues. Human alpha-defensin (HD) 6 is highly expressed by secretory Paneth cells of the small intestine. However, in contrast to the other defensins, it lacks appreciable bactericidal activity. Nevertheless, we report here that HD6 affords protection against invasion by enteric bacterial pathogens in vitro and in vivo. After stochastic binding to bacterial surface proteins, HD6 undergoes ordered self-assembly to form fibrils and nanonets that surround and entangle bacteria. This self-assembly mechanism occurs in vivo, requires histidine-27, and is consistent with x-ray crystallography data. These findings support a key role for HD6 in protecting the small intestine against invasion by diverse enteric pathogens and may explain the conservation of HD6 throughout Hominidae evolution.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4332406/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4332406/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Chu, Hiutung -- Pazgier, Marzena -- Jung, Grace -- Nuccio, Sean-Paul -- Castillo, Patricia A -- de Jong, Maarten F -- Winter, Maria G -- Winter, Sebastian E -- Wehkamp, Jan -- Shen, Bo -- Salzman, Nita H -- Underwood, Mark A -- Tsolis, Renee M -- Young, Glenn M -- Lu, Wuyuan -- Lehrer, Robert I -- Baumler, Andreas J -- Bevins, Charles L -- AI032738/AI/NIAID NIH HHS/ -- AI040124/AI/NIAID NIH HHS/ -- AI044170/AI/NIAID NIH HHS/ -- AI050843/AI/NIAID NIH HHS/ -- AI057757/AI/NIAID NIH HHS/ -- AI070726/AI/NIAID NIH HHS/ -- AI072732/AI/NIAID NIH HHS/ -- AI073120/AI/NIAID NIH HHS/ -- AI076246/AI/NIAID NIH HHS/ -- AI082320/AI/NIAID NIH HHS/ -- AI088122/AI/NIAID NIH HHS/ -- HD059127/HD/NICHD NIH HHS/ -- R01 AI032738/AI/NIAID NIH HHS/ -- R01 AI050843/AI/NIAID NIH HHS/ -- R01 AI057757/AI/NIAID NIH HHS/ -- R01 AI076246/AI/NIAID NIH HHS/ -- R01 GM099526/GM/NIGMS NIH HHS/ -- T32AI060555/AI/NIAID NIH HHS/ -- New York, N.Y. -- Science. 2012 Jul 27;337(6093):477-81. doi: 10.1126/science.1218831. Epub 2012 Jun 21.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Microbiology and Immunology, School of Medicine, University of California, Davis, CA 95616, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22722251" target="_blank"〉PubMed〈/a〉
    Keywords: Adhesins, Bacterial/metabolism ; Animals ; Bacterial Proteins/metabolism ; Cell Line ; Humans ; *Immunity, Innate ; *Immunity, Mucosal ; Intestinal Mucosa/immunology/microbiology/ultrastructure ; Intestine, Small/*immunology/microbiology/ultrastructure ; Macromolecular Substances/chemistry/immunology/metabolism ; Mice ; Mice, Transgenic ; Microscopy, Electron, Scanning ; Models, Molecular ; Nanostructures ; Paneth Cells/immunology/metabolism ; Peptides/chemistry/metabolism ; Protein Binding ; Protein Multimerization ; Protein Structure, Quaternary ; Salmonella Infections, Animal/immunology/microbiology ; Salmonella typhimurium/immunology/pathogenicity/ultrastructure ; Yersinia enterocolitica/immunology/pathogenicity ; alpha-Defensins/*chemistry/immunology/*metabolism ; env Gene Products, Human Immunodeficiency Virus/metabolism
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 3
    Publication Date: 2010-08-02
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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  • 4
  • 5
    Publication Date: 2015-05-12
    Description: Motivation: Establishment of a statistical association between microbiome features and clinical outcomes is of growing interest because of the potential for yielding insights into biological mechanisms and pathogenesis. Extracting microbiome features that are relevant for a disease is challenging and existing variable selection methods are limited due to large number of risk factor variables from microbiome sequence data and their complex biological structure. Results: We propose a tree-based scanning method, Selection of Models for the Analysis of Risk factor Trees (referred to as SMART-scan), for identifying taxonomic groups that are associated with a disease or trait. SMART-scan is a model selection technique that uses a predefined taxonomy to organize the large pool of possible predictors into optimized groups, and hierarchically searches and determines variable groups for association test. We investigate the statistical properties of SMART-scan through simulations, in comparison to a regular single-variable analysis and three commonly-used variable selection methods, stepwise regression, least absolute shrinkage and selection operator (LASSO) and classification and regression tree (CART). When there are taxonomic group effects in the data, SMART-scan can significantly increase power by using bacterial taxonomic information to split large numbers of variables into groups. Through an application to microbiome data from a vervet monkey diet experiment, we demonstrate that SMART-scan can identify important phenotype-associated taxonomic features missed by single-variable analysis, stepwise regression, LASSO and CART. Availability and implementation: The SMART-scan approach is implemented in R and is available at https://dsgweb.wustl.edu/qunyuan/software/smartscan/ Contact : qunyuan@wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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