RESUMEN
The yeast mating response uses a G-protein coupled receptor (GPCR), Ste2, to detect mating pheromone and initiate mating projection morphogenesis. The septin cytoskeleton plays a key role in the formation of the mating projection, forming structures at the base of the projection. Desensitization of the Gα, Gpa1, by the Regulator of G-protein Signaling (RGS), Sst2, is required for proper septin organization and morphogenesis. In cells where the Gα is hyperactive, septins are mislocalized to the site of polarity, and the cells are unable to track a pheromone gradient. We set out to identify the proteins that mediate Gα control of septins during the Saccharomyces cerevisiae mating response by making mutations to rescue septin localization in cells expressing the hyperactive Gα mutant gpa1G302S. We found that single deletions of the septin chaperone Gic1, the Cdc42 GAP Bem3, and the epsins Ent1 and Ent2 rescued the polar cap accumulation of septins in the hyperactive Gα. We created an agent-based model of vesicle trafficking that predicts how changes in endocytic cargo licensing alters localization of endocytosis that mirrors the septin localization we see experimentally. We hypothesized that hyperactive Gα may increase the rate of endocytosis of a pheromone responsive cargo, thereby altering where septins are localized. Both the GPCR and the Gα are known to be internalized by clathrin-mediated endocytosis during the pheromone response. Deletion of the GPCR C-terminus to block internalization partially rescued septin organization. However, deletion of the Gpa1 ubiquitination domain required for its endocytosis completely abrogated septin accumulation at the polarity site. Our data support a model where the location of endocytosis serves as a spatial mark for septin structure assembly and that desensitization of the Gα delays its endocytosis sufficiently that septins are placed peripheral to the site of Cdc42 polarity.
RESUMEN
Colleges and other organizations are considering testing plans to return to operation as the COVID-19 pandemic continues. Pre-symptomatic spread and high false negative rates for testing may make it difficult to stop viral spread. Here, we develop a stochastic agent-based model of COVID-19 in a university sized population, considering the dynamics of both viral load and false negative rate of tests on the ability of testing to combat viral spread. Reported dynamics of SARS-CoV-2 can lead to an apparent false negative rate from ~ 17 to ~ 48%. Nonuniform distributions of viral load and false negative rate lead to higher requirements for frequency and fraction of population tested in order to bring the apparent Reproduction number (Rt) below 1. Thus, it is important to consider non-uniform dynamics of viral spread and false negative rate in order to model effective testing plans.
Asunto(s)
Prueba Serológica para COVID-19/métodos , COVID-19/virología , Modelos Biológicos , Carga Viral , COVID-19/diagnóstico , COVID-19/etiología , COVID-19/transmisión , Portador Sano , Trazado de Contacto , Reacciones Falso Negativas , Humanos , Modelos Estadísticos , Procesos EstocásticosRESUMEN
Colleges and other organizations are considering testing plans to return to operation as the COVID19 pandemic continues. Pre-symptomatic spread and high false negative rates for testing may make it difficult to stop viral spread. Here, we develop a stochastic agent-based model of COVID19 in a university sized population, considering the dynamics of both viral load and false negative rate of tests on the ability of testing to combat viral spread. Reported dynamics of SARS-CoV-2 can lead to an apparent false negative rate from ~17% to ~48%. Nonuniform distributions of viral load and false negative rate lead to higher requirements for frequency and fraction of population tested in order to bring the apparent Reproduction number (Rt) below 1. Thus, it is important to consider non-uniform dynamics of viral spread and false negative rate in order to model effective testing plans.