Autophagy induction favours the generation and maturation of the Coxiella-replicative vacuoles

Pathogens evolved mechanisms to invade host cells and to multiply in the cytosol or in compositionally and functionally customized membrane-bound compartments. Coxiella burnetii, the agent of Q fever in man is a Gram-negative gamma-proteobacterium which multiplies in large, acidified, hydrolase-rich and fusogenic vacuoles with phagolysosomal-like characteristics. We reported previously that C. burnetii phase II replicative compartments are labelled by LC3, a protein specifically localized to autophagic vesicles. We show here that autophagy in Chinese hamster ovary cells, induced by amino acid deprivation prior to infection with Coxiella increased the number of infected cells, the size of the vacuoles, and their bacterial load. Furthermore, overexpression of GFP-LC3 or of GFP-Rab24 - a protein also localized to autophagic vacuoles - likewise accelerated the development of Coxiella-vacuoles at early times after infection. However, overexpression of mutants of those proteins that cannot be targeted to autophagosomes dramatically decreased the number and size of the vacuoles in the first hours of infection, although by 48 h the infection was similar to that of non-transfected controls. Overall, the results suggest that transit through the autophagic pathway increases the infection with Coxiella by providing a niche more favourable to their initial survival and multiplication.Univ Nacl Cuyo, CONICET, Inst Histol & Embriol, Fac Ciencias Med, RA-5500 Mendoza, ArgentinaUniversidade Federal de São Paulo, Escola Paulista Med, Dept Microbiol Imunol & Parasitol, São Paulo, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, Dept Microbiol Imunol & Parasitol, São Paulo, BrazilWeb of Scienc

Manipulating the alpha level cannot cure significance testing – comments on "Redefine statistical significance"

We argue that depending on p-values to reject null hypotheses, including a recent call for changing the canonical alpha level for statistical significance from .05 to .005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable criterion levels both are problematic, it is sensible to dispense with significance testing altogether. There are alternatives that address study design and determining sample sizes much more directly than significance testing does; but none of the statistical tools should replace significance testing as the new magic method giving clear-cut mechanical answers. Inference should not be based on single studies at all, but on cumulative evidence from multiple independent studies. When evaluating the strength of the evidence, we should consider, for example, auxiliary assumptions, the strength of the experimental design, or implications for applications. To boil all this down to a binary decision based on a p-value threshold of .05, .01, .005, or anything else, is not acceptable