Activité antimicrobienne de produits naturels originaires du Nord de l’Ontario

La multirésistance microbienne pose de grands problèmes au niveau de la santé publique. En fait, il ne reste que peu d’agents antimicrobiens effectifs contre certains microbes multirésistants. Les scientifiques sont donc à la recherche de nouveaux produits antimicrobiens. Cette recherche a évalué l’activité antimicrobienne de substances naturelles provenant de plantes originaires du Nord de l’Ontario. Vingt-cinq extraits, dix fractions et dix-neuf composés purs ont été testés contre des microbes pathogènes, soientEscherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa et Candida albicans. L’activité antimicrobienne des produits naturels a été observée en utilisant la technique de dosage sur microplaque qui emploie le résazurin, et la concentration minimale inhibitrice (CMI) des produits a été déterminée. Afin de démontrer que l’activité antimicrobienne des substances naturelles n’était pas limitée à une seule espèce, certains composés purs ont été testés contre des microbes secondaires, soient Streptococcus lactis, Mycobacterium phlei et Schizosaccharomyces octosporus. Quatre extraits de plantes (Chimaphila umbellata, Betula papyrifera, Rhus typhina et Fraxinus pennsylvanica) et six composés purs (acide gallique, éthyle gallate, acide cafféique, acide synapique, acide gentisique et acide chlorogénique) ont démontré une activité antibactérienne ou antifongique. Ces résultats démontrent que ces produits naturels ont le potentiel d’être développés en nouveaux agents antimicrobiens

Using machine learning to build temperature-based ozone parameterizations for climate sensitivity simulations

A number of studies have demonstrated the importance of ozone in climate change simulations, for example concerning global warming projections and atmospheric dynamics. However, fully interactive atmospheric chemistry schemes needed for calculating changes in ozone are computationally expensive. Climate modelers therefore often use climatological ozone fields, which are typically neither consistent with the actual climate state simulated by each model nor with the specific climate change scenario. This limitation applies in particular to standard modeling experiments such as preindustrial control or abrupt 4xCO2 climate sensitivity simulations. Here we suggest a novel method using a simple linear machine learning regression algorithm to predict ozone distributions for preindustrial and abrupt 4xCO2 simulations. Using the atmospheric temperature field as the only input, the regression reliably predicts three-dimensional ozone distributions at monthly to daily time intervals. In particular, the representation of stratospheric ozone variability is much improved compared with a fixed climatology, which is important for interactions with dynamical phenomena such as the polar vortices and the Quasi-Biennial Oscillation. Our method requires training data covering only a fraction of the usual length of simulations and thus promises to be an important stepping stone towards a range of new computationally efficient methods to consider ozone changes in long climate simulations. We highlight key development steps to further improve and extend the scope of machine learning-based ozone parameterizations

Nitrate Respiration Protects Hypoxic Mycobacterium tuberculosis Against Acid- and Reactive Nitrogen Species Stresses

There are strong evidences that Mycobacterium tuberculosis survives in a non-replicating state in the absence of oxygen in closed lesions and granuloma in vivo. In addition, M. tuberculosis is acid-resistant, allowing mycobacteria to survive in acidic, inflamed lesions. The ability of M. tuberculosis to resist to acid was recently shown to contribute to the bacillus virulence although the mechanisms involved have yet to be deciphered. In this study, we report that M. tuberculosis resistance to acid is oxygen-dependent; whereas aerobic mycobacteria were resistant to a mild acid challenge (pH 5.5) as previously reported, we found microaerophilic and hypoxic mycobacteria to be more sensitive to acid. In hypoxic conditions, mild-acidity promoted the dissipation of the protonmotive force, rapid ATP depletion and cell death. Exogenous nitrate, the most effective alternate terminal electron acceptor after molecular oxygen, protected hypoxic mycobacteria from acid stress. Nitrate-mediated resistance to acidity was not observed for a respiratory nitrate reductase NarGH knock-out mutant strain. Furthermore, we found that nitrate respiration was equally important in protecting hypoxic non-replicating mycobacteria from radical nitrogen species toxicity. Overall, these data shed light on a new role for nitrate respiration in protecting M. tuberculosis from acidity and reactive nitrogen species, two environmental stresses likely encountered by the pathogen during the course of infection

Characterizing planetary systems with SPIRou: M-dwarf planet-search survey and the multiplanet systems GJ 876 and GJ 1148

SPIRou is a near-infrared spectropolarimeter and a high-precision velocimeter. The SPIRou Legacy Survey collected data from February 2019 to June 2022, half of the time devoted to a blind search for exoplanets around nearby cool stars. The aim of this paper is to present this program and an overview of its properties, and to revisit the radial velocity (RV) data of two multiplanet systems, including new visits with SPIRou. From SPIRou data, we can extract precise RVs using efficient telluric correction and line-by-line measurement techniques, and we can reconstruct stellar magnetic fields from the collection of polarized spectra using the Zeeman-Doppler imaging method. The stellar sample of our blind search in the solar neighborhood, the observing strategy, the RV noise estimates, chromatic behavior, and current limitations of SPIRou RV measurements on bright M dwarfs are described. In addition, SPIRou data over a 2.5-year time span allow us to revisit the known multiplanet systems GJ~876 and GJ~1148. For GJ~876, the new dynamical analysis including the four planets is consistent with previous models and confirms that this system is deep in the Laplace resonance and likely chaotic. The large-scale magnetic map of GJ~876 over two consecutive observing seasons is obtained and shows a dominant dipolar field with a polar strength of 30~G, which defines the magnetic environment in which the inner planet with a period of 1.94~d is embedded. For GJ~1148, we refine the known two-planet model.Comment: accepted in A&

Ambient levels and dry deposition fluxes of mercury to Lakes Huron, Erie and St. Clair

Ambient concentrations and dry deposition fluxes of Hg in the gas and particle phase to Lakes St. Clair, Erie and Huron were estimated with a hybrid receptor-deposition model (HRD). The ambient gas and particulate phase Hg concentrations were predicted to vary by a factor of 12 to 18 during the transport of air masses traversing the lakes. The ensemble average deposition fluxes of fine particle Hg ranged from 7 pg/m 2 -h to 15.3 pg/m 2 -h over Lake St. Clair, 0.5 to 4.2 pg/m 2 -h over Lake Huron and 5.1 to 20.6 pg/m 2 -h over Lake Erie. The deposition flux of coarse particle Hg was in the range of 50 to 84 pg/m 2 -h over Lake St. Clair, 4.7 to 24.2 pg/m 2 -h over Lake Huron and 5.1 to 20.6 pg/m 2 -h over Lake Erie. Gaseous Hg volatilized at a rate of 0.21 to 0.52 ng/m 2 -h from Lake Huron and 0.13 to 0.36 from Lake Erie. Gas phase Hg was deposited at a rate of 5.9 ng/m 2 -h and/or volatilized at a rate of 0.5 ng/m 2 -h from Lake St. Clair depending upon the location of the sampling site used in the HRD model. The effect of meteorological conditions, particle size distributions and type and location of the sampling sites played an important role in the transfer of atmospheric Hg to and/or from the lakes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43911/1/11270_2005_Article_BF01189666.pd

Optical and near-infrared stellar activity characterization of the early M dwarf Gl~205 with SOPHIE and SPIRou

The stellar activity of M dwarfs is the main limitation for discovering and characterizing exoplanets orbiting them since it induces quasi-periodic RV variations. We aim to characterize the magnetic field and stellar activity of the early, moderately active, M dwarf Gl205 in the optical and nIR domains. We obtained high-precision quasi-simultaneous spectra in the optical and nIR with the SOPHIE spectrograph and SPIRou spectropolarimeter between 2019 and 2022. We computed the RVs from both instruments and the SPIRou Stokes V profiles. We used ZDI to map the large-scale magnetic field over the time span of the observations. We studied the temporal behavior of optical and nIR RVs and activity indicators with the Lomb-Scargle periodogram and a quasi-periodic GP regression. In the nIR, we studied the equivalent width of Al I, Ti I, K I, Fe I, and He I. We modeled the activity-induced RV jitter using a multi-dimensional GP regression with activity indicators as ancillary time series. The optical and nIR RVs have similar scatter but nIR shows a more complex temporal evolution. We observe an evolution of the magnetic field topology from a poloidal dipolar field in 2019 to a dominantly toroidal field in 2022. We measured a stellar rotation period of Prot=34.4$\pm$0.5 d in the longitudinal magnetic field. Using ZDI we measure the amount of latitudinal differential rotation (DR) shearing the stellar surface yielding rotation periods of Peq=32.0$\pm$1.8 d at the stellar equator and Ppol=45.5$\pm$0.3 d at the poles. We observed inconsistencies in the activity indicators' periodicities that could be explained by these DR values. The multi-dimensional GP modeling yields an RMS of the RV residuals down to the noise level of 3 m/s for both instruments, using as ancillary time series H$\alpha$ and the BIS in the optical, and the FWHM in the nIR.Comment: 41 pages, 24 figures. Accepted for publication in A&A. Improved quality of figures and reduced size of Appendi

High Content Phenotypic Cell-Based Visual Screen Identifies Mycobacterium tuberculosis Acyltrehalose-Containing Glycolipids Involved in Phagosome Remodeling

The ability of the tubercle bacillus to arrest phagosome maturation is considered one major mechanism that allows its survival within host macrophages. To identify mycobacterial genes involved in this process, we developed a high throughput phenotypic cell-based assay enabling individual sub-cellular analysis of over 11,000 Mycobacterium tuberculosis mutants. This very stringent assay makes use of fluorescent staining for intracellular acidic compartments, and automated confocal microscopy to quantitatively determine the intracellular localization of M. tuberculosis. We characterised the ten mutants that traffic most frequently into acidified compartments early after phagocytosis, suggesting that they had lost their ability to arrest phagosomal maturation. Molecular analysis of these mutants revealed mainly disruptions in genes involved in cell envelope biogenesis (fadD28), the ESX-1 secretion system (espL/Rv3880), molybdopterin biosynthesis (moaC1 and moaD1), as well as in genes from a novel locus, Rv1503c-Rv1506c. Most interestingly, the mutants in Rv1503c and Rv1506c were perturbed in the biosynthesis of acyltrehalose-containing glycolipids. Our results suggest that such glycolipids indeed play a critical role in the early intracellular fate of the tubercle bacillus. The unbiased approach developed here can be easily adapted for functional genomics study of intracellular pathogens, together with focused discovery of new anti-microbials

Genomic and proteomic analyses of Mycobacterium bovis BCG Mexico 1931 reveal a diverse immunogenic repertoire against tuberculosis infection

<p>Abstract</p> <p>Background</p> <p>Studies of <it>Mycobacterium bovis </it>BCG strains used in different countries and vaccination programs show clear variations in the genomes and immune protective properties of BCG strains. The aim of this study was to characterise the genomic and immune proteomic profile of the BCG 1931 strain used in Mexico.</p> <p>Results</p> <p>BCG Mexico 1931 has a circular chromosome of 4,350,386 bp with a G+C content and numbers of genes and pseudogenes similar to those of BCG Tokyo and BCG Pasteur. BCG Mexico 1931 lacks Region of Difference 1 (RD1), RD2 and N-RD18 and one copy of IS6110, indicating that BCG Mexico 1931 belongs to DU2 group IV within the BCG vaccine genealogy. In addition, this strain contains three new RDs, which are 53 (RDMex01), 655 (RDMex02) and 2,847 bp (REDMex03) long, and 55 single-nucleotide polymorphisms representing non-synonymous mutations compared to BCG Pasteur and BCG Tokyo. In a comparative proteomic analysis, the BCG Mexico 1931, Danish, Phipps and Tokyo strains showed 812, 794, 791 and 701 protein spots, respectively. The same analysis showed that BCG Mexico 1931 shares 62% of its protein spots with the BCG Danish strain, 61% with the BCG Phipps strain and only 48% with the BCG Tokyo strain. Thirty-nine reactive spots were detected in BCG Mexico 1931 using sera from subjects with active tuberculosis infections and positive tuberculin skin tests.</p> <p>Conclusions</p> <p>BCG Mexico 1931 has a smaller genome than the BCG Pasteur and BCG Tokyo strains. Two specific deletions in BCG Mexico 1931 are described (RDMex02 and RDMex03). The loss of RDMex02 (<it>fadD23</it>) is associated with enhanced macrophage binding and RDMex03 contains genes that may be involved in regulatory pathways. We also describe new antigenic proteins for the first time.</p

Computational Comparative Study of Tuberculosis Proteomes Using a Model Learned from Signal Peptide Structures

Secretome analysis is important in pathogen studies. A fundamental and convenient way to identify secreted proteins is to first predict signal peptides, which are essential for protein secretion. However, signal peptides are highly complex functional sequences that are easily confused with transmembrane domains. Such confusion would obviously affect the discovery of secreted proteins. Transmembrane proteins are important drug targets, but very few transmembrane protein structures have been determined experimentally; hence, prediction of the structures is essential. In the field of structure prediction, researchers do not make assumptions about organisms, so there is a need for a general signal peptide predictor

Glutamate mediated metabolic neutralization mitigates propionate toxicity in intracellular Mycobacterium tuberculosis

Metabolic networks in biological systems are interconnected, such that malfunctioning parts can be corrected by other parts within the network, a process termed adaptive metabolism. Unlike Bacillus Calmette-Guérin (BCG), Mycobacterium tuberculosis (Mtb) better manages its intracellular lifestyle by executing adaptive metabolism. Here, we used metabolomics and identified glutamate synthase (GltB/D) that converts glutamine to glutamate (Q → E) as a metabolic effort used to neutralize cytoplasmic pH that is acidified while consuming host propionate carbon through the methylcitrate cycle (MCC). Methylisocitrate lyase, the last step of the MCC, is intrinsically downregulated in BCG, leading to obstruction of carbon flux toward central carbon metabolism, accumulation of MCC intermediates, and interference with GltB/D mediated neutralizing activity against propionate toxicity. Indeed, vitamin B12 mediated bypass MCC and additional supplement of glutamate led to selectively correct the phenotypic attenuation in BCG and restore the adaptive capacity of BCG to the similar level of Mtb phenotype. Collectively, a defective crosstalk between MCC and Q → E contributes to attenuation of intracellular BCG. Furthermore, GltB/D inhibition enhances the level of propionate toxicity in Mtb. Thus, these findings revealed a new adaptive metabolism and propose GltB/D as a synergistic target to improve the antimicrobial outcomes of MCC inhibition in Mtb