La licéité de la vente d'un bien public sous condition suspensive de déclassement

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La résiliation d’un contrat administratif relatif aux prestations d’un commissaire aux comptes peut dépendre d’une décision du tribunal de commerce

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Détection hématologique de la leucose lymphoïde bovine dans le Gers

Lombard Charles, Dupin Frédéric. Détection hématologique de la leucose lymphoïde bovine dans le Gers. In: Bulletin de l'Académie Vétérinaire de France tome 120 n°8, 1967. pp. 407-410

Biosynthesis and physiology of coenzyme Q in bacteria.

International audienceUbiquinone, also called coenzyme Q, is a lipid subject to oxido-reduction cycles. It functions in the respiratory electron transport chain and plays a pivotal role in energy generating processes. In this review, we focus on the biosynthetic pathway and physiological role of ubiquinone in bacteria. We present the studies which, within a period of five decades, led to the identification and characterization of the genes named ubi and involved in ubiquinone production in Escherichia coli. When available, the structures of the corresponding enzymes are shown and their biological function is detailed. The phenotypes observed in mutants deficient in ubiquinone biosynthesis are presented, either in model bacteria or in pathogens. A particular attention is given to the role of ubiquinone in respiration, modulation of two-component activity and bacterial virulence. This article is part of a Special Issue entitled: 18th European Bioenergetic Conference

A new gene involved in coenzyme Q biosynthesis in Escherichia coli: UbiI functions in aerobic C5-hydroxylation

International audienceCoenzyme Q (ubiquinone or Q) is a redox-active lipid found in organisms ranging from bacteria to mammals in which it plays a crucial role in energy-generating processes. Q biosynthesis is a complex pathway that involves multiple proteins. In this work, we show that the uncharacterized conserved visC gene is involved in Q biosynthesis in Escherichia coli, and we have renamed it ubiI. Based on genetic and biochemical experiments, we establish that the UbiI protein functions in the C5-hydroxylation reaction. A strain deficient in ubiI has a low level of Q and accumulates a compound derived from the Q biosynthetic pathway, which we purified and characterized. We also demonstrate that UbiI is only implicated in aerobic Q biosynthesis and that an alternative enzyme catalyzes the C5-hydroxylation reaction in the absence of oxygen. We have solved the crystal structure of a truncated form of UbiI. This structure shares many features with the canonical FAD-dependent para-hydroxybenzoate hydroxylase and represents the first structural characterization of a monooxygenase involved in Q biosynthesis. Site-directed mutagenesis confirms that residues of the flavin binding pocket of UbiI are important for activity. With our identification of UbiI, the three monooxygenases necessary for aerobic Q biosynthesis in E. coli are known

Coherent beam combining with an ultrafast multicore Yb-doped fiber amplifier

International audienceActive coherent beam combination using a 7-non-coupled core,polarization maintaining, air-clad, Yb-doped fiber is demonstrated as amonolithic and compact power-scaling concept for ultrafast fiber lasers. Amicrolens array matched to the multicore fiber and an active phasecontroller composed of a spatial light modulator applying a stochasticparallel gradient descent algorithm are utilized to perform coherentcombining in the tiled aperture geometry. The mitigation of nonlineareffects at a pulse energy of 8.9 μJ and duration of 860 fs is experimentallyverified at a repetition rate of 100 kHz. The experimental combiningefficiency results in a far field central lobe carrying 49% of the total power,compared to an ideal value of 76%. This efficiency is primarily limited bygroup delay differences between cores which is identified as the maindrawback of the system. Minimizing these group delay issues, e.g. by usingshort and straight rod-type multicore fibers, should allow a practical powerscaling solution for femtosecond fiber systems

Global Trends in Marine Plankton Diversity across Kingdoms of Life

35 pages, 18 figures, 1 table, supplementary information https://doi.org/10.1016/j.cell.2019.10.008.-- Raw reads of Tara Oceans are deposited at the European Nucleotide Archive (ENA). In particular, newly released 18S rRNA gene metabarcoding reads are available under the number ENA: PRJEB9737. ENA references for the metagenomics reads corresponding to the size fraction < 0.22 μm (for prokaryotic viruses) analyzed in this study are included in Gregory et al. (2019); see their Table S3. ENA references for the metagenomics reads corresponding to the size fraction 0.22-1.6/3 μm (for prokaryotes and giruses) correspond to Salazar et al. (2019) (see https://zenodo.org/record/3473199). Imaging datasets from the nets are available through the collaborative web application and repository EcoTaxa (Picheral et al., 2017) under the address https://ecotaxa.obs-vlfr.fr/prj/412 for regent data, within the 3 projects https://ecotaxa.obs-vlfr.fr/prj/397, https://ecotaxa.obs-vlfr.fr/prj/398, https://ecotaxa.obs-vlfr.fr/prj/395 for bongo data, and within the 2 projects https://ecotaxa.obs-vlfr.fr/prj/377 and https://ecotaxa.obs-vlfr.fr/prj/378 for WP2 data. A table with Shannon values and multiple samples identifiers, plus a table with flow cytometry data split in six groups are available (https://doi.org/10.17632/p9r9wttjkm.1). Contextual data from the Tara Oceans expedition, including those that are newly released from the Arctic Ocean, are available at https://doi.org/10.1594/PANGAEA.875582The ocean is home to myriad small planktonic organisms that underpin the functioning of marine ecosystems. However, their spatial patterns of diversity and the underlying drivers remain poorly known, precluding projections of their responses to global changes. Here we investigate the latitudinal gradients and global predictors of plankton diversity across archaea, bacteria, eukaryotes, and major virus clades using both molecular and imaging data from Tara Oceans. We show a decline of diversity for most planktonic groups toward the poles, mainly driven by decreasing ocean temperatures. Projections into the future suggest that severe warming of the surface ocean by the end of the 21st century could lead to tropicalization of the diversity of most planktonic groups in temperate and polar regions. These changes may have multiple consequences for marine ecosystem functioning and services and are expected to be particularly significant in key areas for carbon sequestration, fisheries, and marine conservationTara Oceans (which includes both the Tara Oceans and Tara Oceans Polar Circle expeditions) would not exist without the leadership of the Tara Ocean Foundation and the continuous support of 23 institutes (https://oceans.taraexpeditions.org/). We further thank the commitment of the following sponsors: CNRS (in particular Groupement de Recherche GDR3280 and the Research Federation for the Study of Global Ocean Systems Ecology and Evolution FR2022/Tara Oceans-GOSEE), the European Molecular Biology Laboratory (EMBL), Genoscope/CEA, the French Ministry of Research, and the French Government “Investissements d’Avenir” programs OCEANOMICS (ANR-11-BTBR-0008), FRANCE GENOMIQUE (ANR-10-INBS-09-08), MEMO LIFE (ANR-10-LABX-54), the PSL∗ Research University (ANR-11-IDEX-0001-02), as well as EMBRC-France (ANR-10-INBS-02). Funding for the collection and processing of the Tara Oceans data set was provided by NASA Ocean Biology and Biogeochemistry Program under grants NNX11AQ14G, NNX09AU43G, NNX13AE58G, and NNX15AC08G (to the University of Maine); the Canada Excellence research chair on remote sensing of Canada’s new Arctic frontier; and the Canada Foundation for Innovation. We also thank agnès b. and Etienne Bourgois, the Prince Albert II de Monaco Foundation, the Veolia Foundation, Region Bretagne, Lorient Agglomeration, Serge Ferrari, Worldcourier, and KAUST for support and commitment. The global sampling effort was enabled by countless scientists and crew who sampled aboard the Tara from 2009–2013, and we thank MERCATOR-CORIOLIS and ACRI-ST for providing daily satellite data during the expeditions. We are also grateful to the countries who graciously granted sampling permission. We thank Stephanie Henson for providing ocean carbon export data and are also grateful to the other researchers who kindly made their data available. We thank Juan J. Pierella-Karlusich for advice regarding single-copy genes. C.d.V. and N.H. thank the Roscoff Bioinformatics platform ABiMS (http://abims.sb-roscoff.fr) for providing computational resources. C.B. acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Program (grant agreement 835067) as well as the Radcliffe Institute of Advanced Study at Harvard University for a scholar’s fellowship during the 2016-2017 academic year. M.B.S. thanks the Gordon and Betty Moore Foundation (award 3790) and the National Science Foundation (awards OCE#1536989 and OCE#1829831) as well as the Ohio Supercomputer for computational support. S.G.A. thanks the Spanish Ministry of Economy and Competitiveness (CTM2017-87736-R), and J.M.G. is grateful for project RT2018-101025-B-100. F.L. thanks the Institut Universitaire de France (IUF) as well as the EMBRC platform PIQv for image analysis. M.C.B., D.S., and J.R. received financial support from the French Facility for Global Environment (FFEM) as part of the “Ocean Plankton, Climate and Development” project. M.C.B. also received financial support from the Coordination for the Improvement of Higher Education Personnel of Brazil (CAPES 99999.000487/2016-03)Peer Reviewe

Machine learning techniques to characterize functional traits of plankton from image data

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms

Aux origines de l'ordonnance du 19 avril 2017 imposant l'obligation d'une procédure de sélection préalable à l'attribution des titres domaniaux

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