Analyse de l’évolution conjointe de la neige et de l’écosystème de taïga au Nunavik dans un climat en réchauffement

Résumé : Cette recherche présente l'analyse spatio-temporelle de l'évolution conjointe de l'augmentation de la présence arbustive et de la dynamique de la fonte de la neige au Nunavik, Québec, Canada. Cette zone est caractérisée par la complexité de l'interaction de multiples changements simultanés de la température, de la couverture de la neige ainsi que de la pousse végétative. La première partie de ce travail consiste à faire l'analyse de l’évolution temporelle de ces multiples changements. Cette analyse a nécessité la mise en place d’une importante base de données climatiques, satellitaires et de couverture de sol à plusieurs échelles, sur une période allant jusqu'à 60 ans, soit de 1950-2012. La deuxième partie du travail consiste à faire l'analyse spatiale à haute résolution de l’influence de la fraction du couvert arbustif sur la fonte de la neige. L'analyse et l'interprétation des résultats obtenus dans la première partie montrent clairement un changement climatique significatif sur la région étudiée, découpée en 3 bandes de latitude correspondant à la toundra, la taïga ouverte et à la taïga forestière, respectivement du Nord au Sud. Ce changement de climat correspond à un réchauffement marqué, entre 0.75°C et 1.57°C par décade entre les zones 1 (toundra) et 3 (taïga forestière) respectivement. On peut noter que la hauteur de neige maximale annuelle a diminué dans les trois zones alors que les précipitations hivernales ont augmenté en zone 1 et 3 sur les 45 dernières années. Les résultats montrent une nette augmentation de la végétation arbustive dans les zones 2 et 3 (LAI plus élevé de 100% dans la zone 3 par rapport à la zone 1). L'impact de la végétation a été analysé à partir de la durée de fonte relative entre le début de la fonte et la disparition de la neige. Il apparait clairement que la végétation active la fonte précocement, allongeant ainsi significativement la durée de fonte (+600%). Cependant, l'impact de la végétation ne retarde pas la date de fin du couvert nival qui est de plus en plus précoce pour les zones 2 et 3. L'analyse spatiale à haute résolution montre que la présence arbustive entraine une date de fin de neige plus précoce par rapport au sol nu. Cette étude démontre clairement que la croissance de la végétation qui résulte du réchauffement climatique impacte la dynamique du couvert nival, aussi affectée par ce réchauffement. Une étude approfondie des processus en causes avec des mesures in situ appuyées par leur modélisation permettrait de mieux comprendre ces phénomènes. // Abstract : This study presents a spatial-temporal analysis of the joint evolution of the increase of shrubiness and the dynamics of snowmelt in Nunavik, Quebec, Canada. This zone is characterized by the complexity of the interaction of multiple changes of temperature, snow cover and vegetation growth. The first part of this study analyzes the temporal evolution of these changes. The analysis required the use of a large database on climate, satellite data and ground cover at multiple scales over a period of up to 60 years, from 1950 to 2012. The second part of the study consists of a spatial high-resolution analysis of the influence of the fraction of shrub cover on snowmelt. The analysis and interpretation of the results clearly show a significant climate change over the study area, divided into three latitudinal transects corresponding to tundra, open taiga and forested taiga. A significant warming of 0.75 ° C and 1.57 ° C per decade was experienced between zones 1 (tundra) and 3 (forested taiga) respectively. The maximum annual snow depth on the ground decreased over the 3 zones studied while winter precipitations increased in zones 1 and 3 over the last 45 years. The results show a significant increase in shrub vegetation in zones 2 and 3. The impact of the vegetation on snow was analyzed with melt duration (from melt onset to complete melt). It appears clearly that the vegetation triggers the melting process earlier and significantly extends the melt duration (+600%). However, the impact of vegetation does not delay the date of the snow cover disappearance. The high-resolution spatial analysis showed that shrubs cause an earlier snow cover disappearance date than bare soil. This study clearly demonstrates that vegetation growth resulting from global warming impacts the snow cover dynamics, which are also affected by global warming. A thorough study of the processes with in-situ measurements supported by models would help gaining a better comprehension of these phenomena

Blind frame synchronization of Reed-salomon codes

International audienceWe consider in this paper the problem of blind frame synchronization of systems using reed-Solomon (RS) codes and other related families. We present first of all three techniques of blind frame synchronization based on the non-binary parity check matrix of RS codes. While the first two techniques involve the calculation of hard and soft values of the syndrome elements respectively, the third one perform an adaptation step of the parity check matrix before applying the soft criterion. Although RS codes are constructed from non-binary symbols, we show in this paper that it is also possible to synchronize them using the binary image expansion of their parity check matrix. Simulation results show that the synchronization algorithm based on the adaptation of the binary parity check matrix of RS codes has the best synchronization performance among all other techniques. Furthermore, the Frame Error Rate (FER) curves obtained after synchronization and decoding are very close to the perfect synchronization curves

Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs

BACKGROUND: In bacteria, sigma factors and other transcriptional regulatory proteins recognize DNA patterns upstream of their target genes and interact with RNA polymerase to control transcription. As a consequence of evolution, DNA sequences recognized by transcription factors are thought to be enriched in intergenic regions (IRs) and depleted from coding regions of prokaryotic genomes. RESULTS: In this work, we report that genomic distribution of transcription factors binding sites is biased towards IRs, and that this bias is conserved amongst bacterial species. We further take advantage of this observation to develop an algorithm that can efficiently identify promoter boxes by a distribution-dependent approach rather than a direct sequence comparison approach. This strategy, which can easily be combined with other methodologies, allowed the identification of promoter sequences in ten species and can be used with any annotated bacterial genome, with results that rival with current methodologies. Experimental validations of predicted promoters also support our approach. CONCLUSION: Considering that complete genomic sequences of over 1000 bacteria will soon be available and that little transcriptional information is available for most of them, our algorithm constitutes a promising tool for the prediction of promoter sequences. Importantly, our methodology could also be adapted to identify DNA sequences recognized by other regulatory proteins

Synchronisation Trame Aveugle sur Canal Gaussien

Nous proposons dans cet article l'adaptation, au cas d'un canal Gaussien, d'une méthode de synchronisation trame aveugle initialement proposée pour un canal binaire symétrique. Cette nouvelle méthode se base sur le calcul des Logarithmes de Rapport de Vraisemblance (LRV) des éléments du syndrome. Une comparaison entre les performances des deux approches sera effectuée et les probabilités théoriques de fausse synchronisation seront données pour les deux méthodes

Investigation of the DNA damage response to SFOM-0046, a new small-molecule drug inducing DNA double-strand breaks

2-Ethylphenyl 4-(3-ethylureido)benzenesulfonate (SFOM-0046) is a novel anticancer agent that arrests cell cycle in S-phase and causes DNA replication stress leading to the phosphorylation of H2AX into -H2AX. First, using the M21, HT29, HT-1080 and HeLa cell lines, we confirmed that S-phase cell cycle arrest and -H2AX foci induction by SFOM-0046 is a general mechanism occurring in diverse cancer cell lines. In addition to γ-H2AX, SFOM-0046 activates preferentially ATR-Chk1 in M21 and HT29 cells while both ATR-Chk1 and ATM-Chk2 pathways are activated in HCT116 cells. Colocalization of SFOM-0046-induced 53BP1 foci with -H2AX foci validates that the DNA damage generated corresponds to double-strand-breaks (DSBs). Consistent with an S-phase arrest, SFOM-0046 treatment induces RAD51 foci formation but not DNA-PKcs foci, confirming that homologous recombination is the major DSB repair pathway targeted by the drug. Furthermore, using isogenic HCT116 p53+/+ and HCT116 p53-/- cells, we showed that p53 plays a key role in the survival mechanism to SFOM-0046. Finally, SFOM-0046 exhibits a dose-dependent antitumor activity on human fibrosarcoma HT-1080 tumours grafted onto chick chorioallantoic membranes without showing embryo toxicity even at high doses. Altogether, our results highlight SFOM0046 as a very promising drug that induces a replication stress response

Life in mine tailings: microbial population structure across the bulk soil, rhizosphere, and roots of boreal species colonizing mine tailings in northwestern Québec

Abstract Purpose Mining activities have negative effects on soil characteristics and can result in low pH, high heavy metal content, and limited levels of essential nutrients. A tailings storage area located in northwestern Québec showed natural colonization by plants from the adjacent natural environment. The objective of the study was to determine the main edaphic parameters that structured microbial populations associated with the indigenous woody plants that had naturally colonized the site. Methods Microbial populations were studied in the bulk soil, the rhizosphere, and inside plant roots using Illumina sequencing, ordination analysis (i.e., redundancy analysis (RDA) and principal coordinates analysis (PCoA)), ternary plotting, and statistical analysis (MANOVA). Results The main variables that drove the microbial community patterns were plant species and the tailings pH. Indeed, the main bacterial classes were Gammaproteobacteria and Deltaproteobacteria in both the rhizosphere and root endosphere. Analysis revealed that some dominant operational taxonomic units (e.g., Pseudomonas sp., Acinetobacter sp., and Delftia sp.) were present in increased proportions in roots for each plant species under study. This study also revealed that many of the most abundant fungal genera (e.g., Claussenomyces, Eupenicillium, and Trichoderma) were more abundant in the rhizosphere than in the root endosphere. Conclusions This comprehensive study of the microbial community dynamics in the bulk soil, rhizosphere, and root endosphere of boreal trees and shrubs could be beneficial in facilitating the rehabilitation of disturbed ecosystems

Tetraphenylethylene-based glycoclusters with aggregation-induced emission (AIE) properties as high-affinity ligands of bacterial lectins

International audienceTetraphenylethylene (TPE) is fluorescent through aggregation induced emission (AIE) in water. Herein, TPE was used as the core of glycoclusters that target the bacterial lectins LecA and LecB of Pseudomonas aeruginosa. Synthesis of these TPE-based glycoclusters was accomplished by using azide-alkyne "click" chemistry. The AIE properties of the resulting glycoclusters could be readily verified, but imaging could not be pursued due to the overlap of the fluorescence signals from cells and bacteria. Nonetheless, the glycoclusters displayed nanomolar affinities toward LecA and LecB. Further evaluation in a cell-based anti-adhesive assay highlighted a limited decrease in adhesion (20%) for the fucosylated glycocluster. This confirmed that these TPE-based glycoclusters are indeed LecA and LecB high-affinity ligands. Nevertheless, the hypotheses involving their application in imaging or anti-adhesive therapy could not be verified

The CC-Bio Project: Studying the Effects of Climate Change on Quebec Biodiversity

Anticipating the effects of climate change on biodiversity is now critical for managing wild species and ecosystems. Climate change is a global driver and thus affects biodiversity globally. However, land-use planners and natural resource managers need regional or even local predictions. This provides scientists with formidable challenges given the poor documentation of biodiversity and its complex relationships with climate. We are approaching this problem in Quebec, Canada, through the CC-Bio Project (http://cc‑bio.uqar.ca/), using a boundary organization as a catalyst for team work involving climate modelers, biologists, naturalists, and biodiversity managers. In this paper we present the CC-Bio Project and its general approach, some preliminary results, the emerging hypothesis of the northern biodiversity paradox (a potential increase of biodiversity in northern ecosystems due to climate change), and an early assessment of the conservation implications generated by our team work

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data

<div><p>Genome-scale metabolic models (GEMs) are mathematically structured knowledge bases of metabolism that provide phenotypic predictions from genomic information. GEM-guided predictions of growth phenotypes rely on the accurate definition of a biomass objective function (BOF) that is designed to include key cellular biomass components such as the major macromolecules (DNA, RNA, proteins), lipids, coenzymes, inorganic ions and species-specific components. Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a <b>B</b>iomass <b>O</b>bjective <b>F</b>unction from experimental <b>dat</b>a. BOFdat has a modular implementation that divides the BOF definition process into three independent modules defined here as steps: 1) the coefficients for major macromolecules are calculated, 2) coenzymes and inorganic ions are identified and their stoichiometric coefficients estimated, 3) the remaining species-specific metabolic biomass precursors are algorithmically extracted in an unbiased way from experimental data. We used BOFdat to reconstruct the BOF of the <i>Escherichia coli</i> model <i>i</i>ML1515, a gold standard in the field. The BOF generated by BOFdat resulted in the most concordant biomass composition, growth rate, and gene essentiality prediction accuracy when compared to other methods. Installation instructions for BOFdat are available in the documentation and the source code is available on GitHub (<a href="https://github.com/jclachance/BOFdat" target="_blank">https://github.com/jclachance/BOFdat</a>).</p></div