A novel metabolomic approach used for the comparison of Staphylococcus aureus planktonic cells and biofilm samples

Introduction: Bacterial cell characteristics change significantly during differentiation between planktonic and biofilm states. While established methods exist to detect and identify transcriptional and proteomic changes, metabolic fluctuations that distinguish these developmental stages have been less amenable to investigation. Objectives: The objectives of the study were to develop a robust reproducible sample preparation methodology for high throughput biofilm analysis and to determine differences between Staphylococcus aureus in planktonic and biofilm states. Methods: The method uses bead beating in a chloroform/methanol/water extraction solvent to both disrupt cells and quench metabolism. Verification of the method was performed using liquid-chromatography-mass spectrometry. Raw mass-spectrometry data was analysed using an in-house bioinformatics pipe-line incorporating XCMS, MzMatch and in-house R-scripts, with identifications matched to internal standards and metabolite data-base entries. Results: We have demonstrated a novel mechanical bead beating method that has been optimised for the extraction of the metabolome from cells of a clinical Staphylococcus aureus strain existing in a planktonic or biofilm state. This high-throughput method is fast and reproducible, allowing for direct comparison between different bacterial growth states. Significant changes in arginine biosynthesis were identified between the two cell populations. Conclusions: The method described herein represents a valuable tool in studying microbial biochemistry at a molecular level. While the methodology is generally applicable to the lysis and extraction of metabolites from Gram positive bacteria, it is particularly applicable to biofilms. Bacteria that exist as a biofilm are shown to be highly distinct metabolically from their ‘free living’ counterparts, thus highlighting the need to study microbes in different growth states. Metabolomics can successfully distinguish between a planktonic and biofilm growth state. Importantly, this study design, incorporating metabolomics, could be optimised for studying the effects of antimicrobials and drug modes of action, potentially providing explanations and mechanisms of antibiotic resistance and to help devise new antimicrobials

Genomic analysis of diet composition finds novel loci and associations with health and lifestyle

We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10−8), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10−5) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (rg ≈ 0.15–0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|rg| ≈ 0.1–0.3) and positive genetic correlations with physical activity (rg ≈ 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (rg ≈−0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction

Evidence for Positive Selection in Putative Virulence Factors within the Paracoccidioides brasiliensis Species Complex

Paracoccidioides brasiliensis is a dimorphic fungus that is the causative agent of paracoccidioidomycosis, the most important prevalent systemic mycosis in Latin America. Recently, the existence of three genetically isolated groups in P. brasiliensis was demonstrated, enabling comparative studies of molecular evolution among P. brasiliensis lineages. Thirty-two gene sequences coding for putative virulence factors were analyzed to determine whether they were under positive selection. Our maximum likelihood–based approach yielded evidence for selection in 12 genes that are involved in different cellular processes. An in-depth analysis of four of these genes showed them to be either antigenic or involved in pathogenesis. Here, we present evidence indicating that several replacement mutations in gp43 are under positive balancing selection. The other three genes (fks, cdc42 and p27) show very little variation among the P. brasiliensis lineages and appear to be under positive directional selection. Our results are consistent with the more general observations that selective constraints are variable across the genome, and that even in the genes under positive selection, only a few sites are altered. We present our results within an evolutionary framework that may be applicable for studying adaptation and pathogenesis in P. brasiliensis and other pathogenic fungi

Targeting of PI3K/AKT/mTOR pathway to inhibit T cell activation and prevent graft-versus-host disease development

Producción CientíficaBackground: Graft-versus-host disease (GvHD) remains the major obstacle to successful allogeneic hematopoietic stem cell transplantation, despite of the immunosuppressive regimens administered to control T cell alloreactivity. PI3K/AKT/mTOR pathway is crucial in T cell activation and function and, therefore, represents an attractive therapeutic target to prevent GvHD development. Recently, numerous PI3K inhibitors have been developed for cancer therapy. However, few studies have explored their immunosuppressive effect. Methods: The effects of a selective PI3K inhibitor (BKM120) and a dual PI3K/mTOR inhibitor (BEZ235) on human T cell proliferation, expression of activation-related molecules, and phosphorylation of PI3K/AKT/mTOR pathway proteins were analyzed. Besides, the ability of BEZ235 to prevent GvHD development in mice was evaluated. Results: Simultaneous inhibition of PI3K and mTOR was efficient at lower concentrations than PI3K specific targeting. Importantly, BEZ235 prevented naïve T cell activation and induced tolerance of alloreactive T cells, while maintaining an adequate response against cytomegalovirus, more efficiently than BKM120. Finally, BEZ235 treatment significantly improved the survival and decreased the GvHD development in mice. Conclusions: These results support the use of PI3K inhibitors to control T cell responses and show the potential utility of the dual PI3K/mTOR inhibitor BEZ235 in GvHD prophylaxis.Asociación Española Contra el Cáncer (Proyecto AIOA110296BLAN).Gerencia Regional de Salud de Castilla y León (Proyecto GRS 726/A13

Genomic analysis of diet composition finds novel loci and associations with health and lifestyle

We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 x 10(-8)), while five of the 21 lead SNPs reach suggestive significance (P < 1 x 10(-5)) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (r(g) approximate to 0.15-0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|r(g)| approximate to 0.1-0.3) and positive genetic correlations with physical activity (r(g) approximate to 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (r(g) approximate to-0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction.Public Health and primary carePrevention, Population and Disease management (PrePoD

Genomic analysis of diet composition finds novel loci and associations with health and lifestyle

Abstract: We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10−8), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10−5) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (rg ≈ 0.15–0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|rg| ≈ 0.1–0.3) and positive genetic correlations with physical activity (rg ≈ 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (rg ≈−0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction