An Optimized, Chemically Regulated Gene Expression System for Chlamydomonas

BACKGROUND: Chlamydomonas reinhardtii is a model system for algal and cell biology and is used for biotechnological applications, such as molecular farming or biological hydrogen production. The Chlamydomonas metal-responsive CYC6 promoter is repressed by copper and induced by nickel ions. However, induction by nickel is weak in some strains, poorly reversible by chelating agents like EDTA, and causes, at high concentrations, toxicity side effects on Chlamydomonas growth. Removal of these bottlenecks will encourage the wide use of this promoter as a chemically regulated gene expression system. METHODOLOGY: Using a codon-optimized Renilla luciferase as a reporter gene, we explored several strategies to improve the strength and reversibility of CYC6 promoter induction. Use of the first intron of the RBCS2 gene or of a modified TAP medium increases the strength of CYC6 induction up to 20-fold. In the modified medium, induction is also obtained after addition of specific copper chelators, like TETA. At low concentrations (up to 10 microM) TETA is a more efficient inducer than Ni, which becomes a very efficient inducer at higher concentrations (50 microM). Neither TETA nor Ni show toxicity effects at the concentrations used. Unlike induction by Ni, induction by TETA is completely reversible by micromolar copper concentrations, thus resulting in a transient "wave" in luciferase activity, which can be repeated in subsequent growth cycles. CONCLUSIONS: We have worked out a chemically regulated gene expression system that can be finely tuned to produce temporally controlled "waves" in gene expression. The use of cassettes containing the CYC6 promoter, and of modified growth media, is a reliable and economically sustainable system for the temporally controlled expression of foreign genes in Chlamydomonas

The Importance of Conserving Biodiversity Outside of Protected Areas in Mediterranean Ecosystems

Mediterranean-type ecosystems constitute one of the rarest terrestrial biomes and yet they are extraordinarily biodiverse. Home to over 250 million people, the five regions where these ecosystems are found have climate and coastal conditions that make them highly desirable human habitats. The current conservation landscape does not reflect the mediterranean biome's rarity and its importance for plant endemism. Habitat conversion will clearly outpace expansion of formal protected-area networks, and conservationists must augment this traditional strategy with new approaches to sustain the mediterranean biota. Using regional scale datasets, we determine the area of land in each of the five regions that is protected, converted (e.g., to urban or industrial), impacted (e.g., intensive, cultivated agriculture), or lands that we consider to have conservation potential. The latter are natural and semi-natural lands that are unprotected (e.g., private range lands) but sustain numerous native species and associated habitats. Chile has the greatest proportion of its land (75%) in this category and California-Mexico the least (48%). To illustrate the potential for achieving mediterranean biodiversity conservation on these lands, we use species-area curves generated from ecoregion scale data on native plant species richness and vertebrate species richness. For example, if biodiversity could be sustained on even 25% of existing unprotected, natural and semi-natural lands, we estimate that the habitat of more than 6,000 species could be represented. This analysis suggests that if unprotected natural and semi-natural lands are managed in a manner that allows for persistence of native species, we can realize significant additional biodiversity gains. Lasting biodiversity protection at the scale needed requires unprecedented collaboration among stakeholders to promote conservation both inside and outside of traditional protected areas, including on lands where people live and work

Metaheuristics for Transmission Network Expansion Planning

This chapter presents the characteristics of the metaheuristic algorithms used to solve the transmission network expansion planning (TNEP) problem. The algorithms used to handle single or multiple objectives are discussed on the basis of selected literature contributions. Besides the main objective given by the costs of the transmission system infrastructure, various other objectives are taken into account, representing generation, demand, reliability and environmental aspects. In the single-objective case, many metaheuristics have been proposed, in general without making strong comparisons with other solution methods and without providing superior results with respect to classical mathematical programming. In the multi-objective case, there is a better convenience of using metaheuristics able to handle conflicting objectives, in particular with a Pareto front-based approach. In all cases, improvements are still expected in the definition of benchmark functions, benchmark networks and robust comparison criteria

Un descripteur binaire robuste aux rotations basé sur la théorie de l'information

International audienceIn this paper, we propose a new data-driven approach for binary descriptor selection. In order to draw a clear analysis of common designs, we present a general information-theoretic selection paradigm. It encompasses several standard binary descriptor construction schemes, including a recent state-of-the-art one named BOLD. We pursue the same endeavor to increase the stability of the produced descriptors with respect to rotations. To achieve this goal, we have designed a novel of-fline selection criterion which is better adapted to the online matching procedure. The effectiveness of our approach is demonstrated on two standard datasets, where our descriptor is compared to BOLD and to several classical descriptors. In particular, it emerges that our approach can reproduce equivalent if not better performance as BOLD while relying on twice shorter descriptors. Such an improvement can be influential for real-time applications

Un descripteur binaire robuste aux rotations basé sur la théorie de l'information

International audienceIn this paper, we propose a new data-driven approach for binary descriptor selection. In order to draw a clear analysis of common designs, we present a general information-theoretic selection paradigm. It encompasses several standard binary descriptor construction schemes, including a recent state-of-the-art one named BOLD. We pursue the same endeavor to increase the stability of the produced descriptors with respect to rotations. To achieve this goal, we have designed a novel of-fline selection criterion which is better adapted to the online matching procedure. The effectiveness of our approach is demonstrated on two standard datasets, where our descriptor is compared to BOLD and to several classical descriptors. In particular, it emerges that our approach can reproduce equivalent if not better performance as BOLD while relying on twice shorter descriptors. Such an improvement can be influential for real-time applications