Inhibition of Fungi and Gram-Negative Bacteria by Bacteriocin BacTN635 Produced by Lactobacillus plantarum sp. TN635

The aim of this study was to evaluate 54 lactic acid bacteria (LAB) strains isolated from meat, fermented vegetables and dairy products for their capacity to produce antimicrobial activities against several bacteria and fungi. The strain designed TN635 has been selected for advanced studies. The supernatant culture of this strain inhibits the growth of all tested pathogenic including the four Gram-negative bacteria (Salmonella enterica ATCC43972, Pseudomonas aeruginosa ATCC 49189, Hafnia sp. and Serratia sp.) and the pathogenic fungus Candida tropicalis R2 CIP203. Based on the nucleotide sequence of the 16S rRNA gene of the strain TN635 (1,540 pb accession no FN252881) and the phylogenetic analysis, we propose the assignment of our new isolate bacterium as Lactobacillus plantarum sp. TN635 strain. Its antimicrobial compound was determined as a proteinaceous substance, stable to heat and to treatment with surfactants and organic solvents. Highest antimicrobial activity was found between pH 3 and 11 with an optimum at pH?=?7. The BacTN635 was purified to homogeneity by a four-step protocol involving ammonium sulfate precipitation, centrifugal microconcentrators with a 10-kDa membrane cutoff, gel filtration Sephadex G-25, and C18 reverse-phase HPLC. SDS-PAGE analysis of the purified BacTN635, revealed a single band with an estimated molecular mass of approximately 4 kDa. The maximum bacteriocin production (5,000 AU/ml) was recorded after a 16-h incubation in Man, Rogosa, and Sharpe (MRS) medium at 30?°C. The mode of action of the partial purified BacTN635 was identified as bactericidal against Listeria ivanovii BUG 496 and as fungistatic against C. tropicalis R2 CIP203.     

Le complexe motivique de De Rham

Résumé  Sur un corps de caractéristique 0, nous construisons un complexe motivique de De Rham qui permet de généraliser la cohomologie de De Rham d’une variété lisse à tout motif au sens de Voevodsky.

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Mechanism of delayed double ionization in a strong laser field

When intense laser pulses release electrons nonsequentially, the time delay between the last recollision and the subsequent ionization may last longer than what is expected from a direct impact scenario [recollision excitation with subsequent ionization (RESI)]. We show that the resulting delayed ionization stems from the inner electron being promoted to a sticky region. We identify the mechanism that traps and releases the electron from this region. As a signature of this mechanism, we predict oscillations in the ratio of RESI to double ionization yields versus laser intensity.     

Critical parameters for the analysis of anionic oligosaccharides by desorption electrospray ionization mass spectrometry

Sulfated oligosaccharides derived from glycosaminoglycans (GAGs) are fragile compounds, highly polar and anionic. We report here on the rare but successful application of desorption electrospray ionization (DESI) - LTQ-Orbitrap mass spectrometry (MS) to the high-resolution analysis of anionic and sulfated oligosaccharides derived from the GAGs hyaluronic acid and heparin. For that purpose, key parameters affecting DESI performance, comprising the geometric parameters of the DESI source, the probed surface and the spraying conditions, applied spray voltage, flow rates and solvent composition were investigated. Under suitable conditions, the DESI technique allows the preservation of the structural integrity of such fragile compounds. DESI enabled the sensitive detection of anionic hyaluronic acid and heparin oligosaccharides with a limit of detection (LOD) down to 5 fmol (≈10?pg) for the hyaluronic acid decasaccharide. Detection of hyaluronic acid oligosaccharides in urine sample was also successfully achieved with LOD values inferior to the ng range. Multistage tandem mass spectrometry (MS(n) ) through the combination of the DESI source with a hybrid linear ion trap-orbitrap mass spectrometer allowed the discrimination of isomeric sulfated oligosaccharides and the sequence determination of a hyaluronic acid decasaccharide. These results open promising ways in glycomic and glycobiology fields where structure-activity relationships of bioactive carbohydrates are currently questioned. Copyright ? 2012 John Wiley & Sons, Ltd.     

Targeted and Untargeted Mass Spectrometry-Based Metabolomics for Chemical Profiling of Three Coffee Species

While coffee beans have been studied for many years, researchers are showing a growing interest in coffee leaves and by-products, but little information is currently available on coffee species other than Coffea arabica and Coffea canephora. The aim of this work was to perform a targeted and untargeted metabolomics study on Coffea arabica, Coffea canephora and Coffea anthonyi. The application of the recent high-resolution mass spectrometry-based metabolomics tools allowed us to gain a clear overview of the main differences among the coffee species. The results showed that the leaves and fruits of Coffea anthonyi had a different metabolite profile when compared to the two other species. In Coffea anthonyi, caffeine levels were found in lower concentrations while caffeoylquinic acid and mangiferin-related compounds were found in higher concentrations. A large number of specialized metabolites can be found in Coffea anthonyi tissues, making this species a valid candidate for innovative healthcare products made with coffee extracts.     

Learning PDE to Model Self-Organization of Matter

A self-organization hydrodynamic process has recently been proposed to partially explain the formation of femtosecond laser-induced nanopatterns on Nickel, which have important applications in optics, microbiology, medicine, etc. Exploring laser pattern space is difficult, however, which simultaneously (i) motivates using machine learning (ML) to search for novel patterns and (ii) hinders it, because of the few data available from costly and time-consuming experiments. In this paper, we use ML to predict novel patterns by integrating partial physical knowledge in the form of the Swift-Hohenberg (SH) partial differential equation (PDE). To do so, we propose a framework to learn with few data, in the absence of initial conditions, by benefiting from background knowledge in the form of a PDE solver. We show that in the case of a self-organization process, a feature mapping exists in which initial conditions can safely be ignored and patterns can be described in terms of PDE parameters alone, which drastically simplifies the problem. In order to apply this framework, we develop a second-order pseudospectral solver of the SH equation which offers a good compromise between accuracy and speed. Our method allows us to predict new nanopatterns in good agreement with experimental data. Moreover, we show that pattern features are related, which imposes constraints on novel pattern design, and suggest an efficient procedure of acquiring experimental data iteratively to improve the generalization of the learned model. It also allows us to identify the limitations of the SH equation as a partial model and suggests an improvement to the physical model itself.     

Structure and Computational Studies of New Sulfonamide Compound: {(4-nitrophenyl)sulfonyl}tryptophan

Synthesis of sulfonamide through an indirect method that avoids contamination of the product with no need for purification has been carried out using the indirect process. Here, we report the synthesis of a novel sulfonamide compound, ({4-nitrophenyl}sulfonyl)tryptophan (DNSPA) from 4-nitrobenzenesulphonylchloride and L-tryptophan precursors. The slow evaporation method was used to form single crystals of the named compound from methanolic solution. The compound was characterized by X-ray crystallographic analysis and spectroscopic methods (NMR, IR, mass spectrometry, and UV-vis). The sulfonamide N-H NMR signal at 8.07–8.09 ppm and S-N stretching vibration at 931 cm⁻¹ indicate the formation of the target compound. The compound crystallized in the monoclinic crystal system and P2₁ space group with four molecules of the compound in the asymmetric unit. Molecular aggregation in the crystal structure revealed a 12-molecule aggregate synthon sustained by O-H⋯O hydrogen bonds and stabilised by N-H⋯O intermolecular contacts. Experimental studies were complemented by DFT calculations at the B3LYP/6-311++G(d,p) level of theory. The computed structural and spectroscopic data are in good agreement with those obtained experimentally. The energies of interactions between the units making up the molecule were calculated. Molecular docking studies showed that DNSPA has a binding energy of −6.37 kcal/mol for E. coli DNA gyrase (5MMN) and −6.35 kcal/mol for COVID-19 main protease (6LU7).     

Lateral Deprotometallation-Trapping Reactions on Methylated Pyridines,Quinolines and Quinoxalines Using Lithium Diethylamide

The functionalization of methylated azines and diazines has aroused the interest of chemists given the structural diversity that it affords. Hindered lithium dialkylamides have been used to deprotometallate these substrates chemoselectively. In contrast, it can be observed that, despite some promising work, lithium diethylamide has been used very little for this purpose. Our objective here is on the one hand to make an inventory of what reagents have been used to deprotometallate methylpyridines, -quinolines and -quinoxalines, and on the other hand to describe the results obtained by seeking to functionalize a series of substrates with lithium diethylamide (picolines, 2,4-lutidine, methylquinolines and 2-methylquinoxaline). Our efforts to take advantage of the use of an in-situ trap (a zinc chloride chelate) in these reactions are also described.