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Dufour, N.

Publications and source records attributed to Dufour, N..

2 recordsLinked to original sources

The JAK2-STAT3 pathway controls a beneficial proteostasis response of reactive astrocytes in Huntington disease

Huntingtons disease is a fatal neurodegenerative disease characterized by striatal neurodegeneration, aggregation of mutant Huntingtin and the presence of reactive astrocytes. Astrocytes are important partners for neurons and engage in a specific reactive response in Huntingtons disease that involves morphological, molecular and functional changes. How reactive astrocytes contribute to Huntingtons disease is still an open question, especially because their reactive state is poorly reproduced in experimental mouse models. Here, we show that the JAK2-STAT3 pathway, a central cascade controlling astrocyte reactive response, is activated in the putamen of Huntingtons disease patients. Selective activation of this cascade in astrocytes through viral gene transfer reduces the number and size of mutant Huntingtin aggregates in neurons and improves neuronal defects in two complementary mouse models of Huntingtons disease. It also reduces striatal atrophy and increases glutamate levels, two central clinical outcomes measured by non-invasive magnetic resonance imaging. Moreover, astrocyte-specific transcriptomic analysis shows that activation of the JAK2-STAT3 pathway in astrocytes coordinates a transcriptional program that increases their intrinsic proteolytic capacity, through the lysosomal and ubiquitin-proteasome degradation systems. This pathway also enhances their production and exosomal release of the co-chaperone DNAJB1, which contributes to mutant Huntingtin clearance in neurons. Together, our results show that the JAK2-STAT3 pathway controls a beneficial proteostasis response in reactive astrocytes in Huntingtons disease, which involves bi-directional signalling with neurons to reduce mutant Huntingtin aggregation, eventually improving disease outcomes.

neuroscience

Combination of in vivo phage therapy data with in silico model highlights key parameters for treatment efficacy

The clinical (re)development of phage therapy to treat antibiotic resistant infections requires grasping specific biological properties of bacteriophages (phages) as antibacterial. However, identification of optimal dosing regimens is hampered by the poor understanding of phage-bacteria interactions in vivo. Here we developed a general strategy coupling in vitro and in vivo experiments with a mathematical model to characterize the interplay between phage and bacterial dynamics during pneumonia induced by a pathogenic strain of Escherichia coli. The model estimates some key parameters for phage therapeutic efficacy, in particular the impact of dose and route of administration on phage dynamics and the synergism of phage and the innate immune response on the bacterial clearance rate. Simulations predict a low impact of the intrinsic phage characteristics in agreement with the current semi-empirical choices of phages for compassionate treatments. Model-based approaches will foster the deployment of future phage therapy clinical trials.

microbiology