Optimization Of Promoter Sequences In Order To Mimic Physiological Pde6b Expression

Purpose: Many retinal degenerations result from defective retina-specific gene expressions. Thus, it is important to understand how the expression of a photoreceptor-specific gene is regulated in vivo in order to achieve successful gene therapy. The present study aims to design an AAV2/8 vector that can regulate the transcript level in a physiological manner to replace missing PDE6b in Rd1 and Rd10 mice. In previous studies (Ogieta, et al., 2000), the short 5' flanking sequence of the human PDE6b gene (350 bp) was shown to be photoreceptor-specific in transgenic mice. However, the efficiency and specificity of the 5' flanking region of the human PDE6b was not investigated in the context of gene therapy during retinal degeneration. In this study, two different sequences of the 5' flanking region of the human PDE6b gene were studied as promoter elements and their expression will be tested in wild type and diseased retinas (Rd 10 mice).Methods: Two 5' flanking fragments of the human PDE6b gene: (-93 to +53 (150 bp) and -297 to +53 (350 bp)) were cloned in different plasmids in order to check their expression in vitro and in vivo by constructing an AAV2/8 vector. These elements drove the activity of either luciferase (pGL3 plasmids) or EGFP. jetPEI transfection in Y 79 cells was used to evaluate gene expression through luciferase activity. Constructs encoding EGFP under the control of the two promoters were performed in AAV2.1-93 (or 297)-EGFP plasmids to produce AAV2/8 vectors.Results: When pGL3-93 (150 bp) or pGL3-297 (350 bp) were transfected in the Y-79 cells, the smaller fragment (150 bp) showed higher gene expression compared to the 350 bp element and to the SV40 control, as previously reported. The 350 bp drove similar levels of expression when compared to the SV40 promoter. In view of these results, the fragments (150 bp or 350 bp) were integrated into the AAV2.1-EGFP plasmid to produce AAV2/8 vector, and we are currently evaluating the efficiency and specificity of the produced constructs in vivo in normal and diseased retinas.Conclusions: Comparisons of these vectors with vectors bearing ubiquitous promoters should reveal which construct is the most suitable to drive efficient and specific gene expression in diseased retinas in order to restore a normal function on the long term.

Functional homogenization of bumblebee communities in alpine landscapes under projected climate change

Background: Bumblebees represent an active pollinator group in mountain regions and assure the pollination of many different plant species from low to high elevations. Plant-pollinator interactions are mediated by functional traits. Shift in bumblebee functional structure under climate change may impact plant-pollinator interactions in mountains. Here, we estimated bumblebee upward shift in elevation, community turnover, and change in functional structure under climate change. Method: We sampled bumblebee species at 149 sites along the elevation gradient. We used stacked species distribution models (S-SDMs) forecasted under three climate change scenarios (A2, A1B, RCP3PD) to model the potential distribution of the Bombus species. Furthermore, we used species proboscis length measurements to assess the functional change in bumblebee assemblages along the elevation gradient. Results: We found species-specific response of bumblebee species to climate change. Species differed in their predicted rate of range contraction and expansion. Losers were mainly species currently restricted to high elevation. Under the most severe climate change scenarios (A2), we found a homogenization of proboscis length structure in bumblebee communities along the elevation gradient through the upward colonization of high elevation by species with longer proboscides. Conclusions: Here, we show that in addition to causing the shift in the distribution of bumblebee species, climate change may impact the functional structure of communities. The colonization of high elevation areas by bumblebee species with long proboscides may modify the structure of plant-pollination interaction networks by increasing the diversity of pollination services at high elevation.

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.