Formation of native prions from minimal components in vitro

The conformational change of a host protein, PrPC, into a disease-associated isoform, PrPSc, appears to play a critical role in the pathogenesis of prion diseases such as Creutzfeldt–Jakob disease and scrapie. However, the fundamental mechanism by which infectious prions are produced in neurons remains unknown. To investigate the mechanism of prion formation biochemically, we conducted a series of experiments using the protein misfolding cyclic amplification (PMCA) technique with a preparation containing only native PrPC and copurified lipid molecules. These experiments showed that successful PMCA propagation of PrPSc molecules in a purified system requires accessory polyanion molecules. In addition, we found that PrPSc molecules could be formed de novo from these defined components in the absence of preexisting prions. Inoculation of samples containing either prion-seeded or spontaneously generated PrPSc molecules into hamsters caused scrapie, which was transmissible on second passage. These results show that prions able to infect wild-type hamsters can be formed from a minimal set of components including native PrPC molecules, copurified lipid molecules, and a synthetic polyanion

Combining correlative and mechanistic habitat suitability models to improve ecological compensation.

International audience: Only a few studies have shown positive impacts of ecological compensation on species dynamics affected by human activities. We argue that this is due to inappropriate methods used to forecast required compensation in environmental impact assessments. These assessments are mostly descriptive and only valid at limited spatial and temporal scales. However, habitat suitability models developed to predict the impacts of environmental changes on potential species' distributions should provide rigorous science-based tools for compensation planning. Here we describe the two main classes of predictive models: correlative models and individual-based mechanistic models. We show how these models can be used alone or synoptically to improve compensation planning. While correlative models are easier to implement, they tend to ignore underlying ecological processes and lack accuracy. On the contrary, individual-based mechanistic models can integrate biological interactions, dispersal ability and adaptation. Moreover, among mechanistic models, those considering animal energy balance are particularly efficient at predicting the impact of foraging habitat loss. However, mechanistic models require more field data compared to correlative models. Hence we present two approaches which combine both methods for compensation planning, especially in relation to the spatial scale considered. We show how the availability of biological databases and software enabling fast and accurate population projections could be advantageously used to assess ecological compensation requirement efficiently in environmental impact assessments