Machine Learning-Based Virtual Screening of Antibacterial Agents against Methicillin-Susceptible and Resistant Staphylococcus aureus.

The application of computer-aided drug discovery (CADD) approaches has enabled the discovery of new antimicrobial therapeutic agents in the past. The high prevalence of methicillin-resistantStaphylococcus aureus(MRSA) strains promoted this pathogen to a high-priority pathogen for drug development. In this sense, modern CADD techniques can be valuable tools for the search for new antimicrobial agents. We employed a combination of a series of machine learning (ML) techniques to select and evaluate potential compounds with antibacterial activity against methicillin-susceptible S. aureus (MSSA) and MRSA strains. In the present study, we describe the antibacterial activity of six compounds against MSSA and MRSA reference (American Type Culture Collection (ATCC)) strains as well as two clinical strains of MRSA. These compounds showed minimal inhibitory concentrations (MIC) in the range from 12.5 to 200 µM against the different bacterial strains evaluated. Our results constitute relevant proven ML-workflow models to distinctively screen for novel MRSA antibiotics.

Metabolic alterations in conventional and genetically modified soybean plants with GmDREB2A;2 FL and GmDREB2A;2 CA transcription factors during water deficit.

Water deficit is one of the main abiotic stress that affects plant growth and productivity. The GmDREB2A;2 (Glyma14g06080) gene is an important transcription factor involved in regulating the plants' responses under water deficit. In previous studies, soybean plants overexpressing full-length (GmDREB2A;2 FL) and constitutively active (GmDREB2A;2 CA) forms of the GmDREB2A;2 gene, presented higher tolerance to water deficit when compared with the conventional cultivar BRS 283. Therefore, identifying the changes in metabolite profile in these tolerant genotypes can contribute to the understanding of the metabolic pathways involved in the tolerance mechanism. In this work, the metabolic changes in roots and leaves of genetically modified (GM) soybean plants subjected to water deficit were elucidated by 1H-NMR spectroscopy. Three events were analyzed, one containing the gene in FL form (GmDREB2A;2 FL) and two presenting its CA form (GmDREB2A;2 CA-1 and GmDREB2A;2 CA-2) and compared with the conventional cultivar BRS 283. The results indicated different responses between leaves and roots for all genotypes. Most of these metabolic variations were related to carbohydrate and amino acid pathways. BRS 283 stood out with higher accumulation of amino acids in leaves under water deficit. The results also showed that the events GmDREB2A;2 FL and GmDREB2A;2 CA-1 presented higher concentrations of ß-glucose and fructose in leaves, whereas BRS 283 accumulated more sucrose and pinitol. In roots, the GM events accumulated higher ß-glucose, fructose, asparagine and phenylalanine, when compared with the conventional cultivar. These insights can add information on how the transcription factor (TF) DREB2A acts in soybean plants triggering and controlling a network of complex responses to drought.

Identification of primary and secondary metabolites and transcriptome profile of soybean tissues during different stages of hypoxia.

NMR and chromatography methods combined with mass spectrometry are the most important analytical techniques employed for plant metabolomics screening. Metabolomic analysis integrated to transcriptome screening add an important extra dimension to the information flow from DNA to RNA to protein. The most useful NMR experiment in metabolomics analysis is the proton spectra due the high receptivity of 1H and important structural information, through proton-proton scalar coupling. Routinely, databases have been used in identification of primary metabolites, however, there is currently no comparable data for identification of secondary metabolites, mainly, due to signal overlap in normal 1H NMR spectra and natural variation of plant. Related to spectra overlap, alternatively, better resolution can be find using 1H pure shift and 2D NMR pulse sequence in complex samples due to spreading the resonances in a second dimension. Thus, in data brief we provide a catalogue of metabolites and expression levels of genes identified in soy leaves and roots under flooding stress.

Characterization of new exopolysaccharide production by Rhizobium tropici during growth on hydrocarbon substrate.

Exopolysaccharide (EPS) are produced by a diverse of rhizobia species and has been demonstrated to be a bioemulsifier with potential applications in the degradation of hydrocarbons. In the present study, attempts were made to obtain the new exopolysaccharide production by Rhizobium tropici (SEMIA 4080 and MUTZC3) strains during growth on hydrocarbon substrate. Under the different cultivation conditions, the high molecular weight exopolysaccharides from Rhizobium tropici strains cultivated for 96h mainly consisted of carbohydrates (79-85%) and a low percentage of protein. The EPSC3-D differed from the others, with only 60% of carbohydrate. However, all strains produced polymers with distinct rheology properties, such as viscosity of each EPS sample, suitable for different applications. In addition, RP-HPLC, FTIR and NMR studies revealed EPS produced by rhizobia strains were similar indicating minimal difference between EPS compositions.

Gas Chromatography-Mass Spectrometry (GC-MS) and evaluation of antioxidant and antimicrobial activities of essential oil of Campomanesia adamantium (Cambess.) O. Berg (Guavira) / Cromatografia Gasosa-Espectrometria de Massas (CG-EM) e avaliação da atividade antioxidante e antimicrobiana do óleo essencial de Campomanesia adamantium (Cambess.) O. Berg (guavira)

The essential oils from Campomanesia adamantium (Cambess.) O. Berg leaves, collected in the reproductive (flowering and fruit-bearing) and vegetative stages, were characterized by GC-MS (Gas Chromatography-Mass Spectrometry). A total of 95 compounds of the essential oils were identified. In the reproductive stage (flowering) the major constituents were monoterpenes (limonene, α-pinene and β-pinene) while during the vegetative stage the major constituents were the sesquiterpenes (bicyclogermacrene and globulol). The essential oil of the reproductive stage shows high antimicrobial activity against Staphylococcus aureus, Pseudomonas aeruginosa and Candida albicans, and all show moderate activity against Escherichia coli. The essential oils were also evaluated for their radical-scavenging activity by DPPH. The chemogeographical variations of the oil composition from the four distinct localities studied all contained α-pinene, β-pinene, limonene, linalool, β-caryophyllene, germacrene D and bicyclogermacrene, however the samples from Jardim city contained neither limonene nor linalool.

Os óleos essenciais obtidos das folhas de Campomanesia adamantium foram caracterizados através da combinação de CG-EM e índice de retenção, sendo identificado um total de 95 compostos. Na floração as substâncias majoritárias foram monoterpenos (limoneno, α-pineno e β-pineno) e durante o estágio vegetativo as substâncias majoritárias foram sesquiterpenos (biciclogermacreno e globulol). Os óleos essenciais obtidos da floração e frutificação mostraram alta atividade contra Staphylococcus aureus, Pseudomonas aeruginosa e Candida albicans e moderada contra Escherichia coli em todos os estágios. Foi avaliada a atividade antioxidante dos óleos essenciais usando o método do DPPH. O óleo essencial das 4 cidades mostrou a presença de α-pineno, β-pineno, limoneno, linalol, β-cariofileno, germacreno D e biciclogermacreno, mas a amostra da cidade de Jardim não apresentou limoneno e linalol.