is an important human pathogen whose success is largely attributed to its vast arsenal of virulence factors that facilitate its invasion into, and survival within, the human host. The expression of these virulence factors is controlled by the quorum sensing accessory gene regulator (Agr) system. However, a large proportion of clinical isolates are consistently found to have a mutationally inactivated Agr system. These mutants have a survival advantage in the host but are considered irreversible mutants. Here we show, for the first time, that a fraction of Agr-negative mutants can revert their Agr activity. By serially passaging Agr-negative strains and screening for phenotypic reversion of hemolysis and subsequent sequencing, we identified two mutational events responsible for reversion: a genetic duplication plus inversion event and a poly(A) tract alteration. Additionally, we demonstrate that one clinical Agr-negative methicillin-resistant (MRSA) isolate could reproducibly generate Agr-revertant colonies with a poly(A) tract genetic mechanism. We also show that these revertants activate their Agr system upon phagocytosis. We propose a model in which a minor fraction of Agr-negative strains are phase variants that can revert their Agr activity and may act as a cryptic insurance strategy against host-mediated stress. is responsible for a broad range of infections. This pathogen has a vast arsenal of virulence factors at its disposal, but avirulent strains are frequently isolated as the cause of clinical infections. These isolates have a mutated locus and have been believed to have no evolutionary future. Here we show that a fraction of Agr-negative strains can repair their mutated locus with mechanisms resembling phase variation. The revertants sustain an Agr OFF state as long as they exist as a minority but can activate their Agr system upon phagocytosis. These revertant cells might function as a cryptic insurance strategy to survive immune-mediated host stress that arises during infection.
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http://dx.doi.org/10.1128/mBio.00796-19 | DOI Listing |
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December 2024
Department of Physiology, Iuliu Haţieganu University of Medicine and Pharmacy, Clinicilor 1, 400006 Cluj-Napoca, Romania.
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Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.
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Department of Animal Production, Faculty of Agriculture, Menoufia University, Shibin Al Kawm, Egypt.
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View Article and Find Full Text PDFElife
January 2025
Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.
Data-driven models of neurons and circuits are important for understanding how the properties of membrane conductances, synapses, dendrites, and the anatomical connectivity between neurons generate the complex dynamical behaviors of brain circuits in health and disease. However, the inherent complexity of these biological processes makes the construction and reuse of biologically detailed models challenging. A wide range of tools have been developed to aid their construction and simulation, but differences in design and internal representation act as technical barriers to those who wish to use data-driven models in their research workflows.
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