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

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

Source analysis of beta-synchronisation and cortico-muscular coherence after movement termination based on high resolution electroencephalography

We hypothesized that post-movement beta synchronization (PMBS) and cortico-muscular coherence (CMC) during movement termination relate to each other and have similar role in sensorimotor integration. We calculated the parameters and estimated the sources of these phenomena.We measured 64-channel EEG simultaneously with surface EMG of the right first dorsal interosseus muscle in 11 healthy volunteers. In Task1, subjects kept a medium-strength contraction continuously; in Task2, superimposed on this movement, they performed repetitive self-paced short contractions. In Task3 short contractions were executed alone. Time-frequency analysis of the EEG and CMC was performed with respect to the offset of brisk movements and averaged in each subject. Sources of PMBS and CMC were also calculated.High beta power in Task1, PMBS in Task2-3, and CMC in Task1-2 could be observed in the same individual frequency bands. While beta synchronization in Task1 and PMBS in Task2-3 appeared bilateral with contralateral predominance, CMC in Task1-2 was strictly a unilateral phenomenon; their main sources did not differ contralateral to the movement in the primary sensorimotor cortex in 7 of 11 subjects in Task1, and in 6 of 9 subjects in Task2. In Task2, CMC and PMBS had the same latency but their amplitudes did not correlate with each other. In Task2, weaker PMBS source was found bilaterally within the secondary sensory cortex, while the second source of CMC was detected in the premotor cortex, contralateral to the movement. In Task3, weaker sources of PMBS could be estimated in bilateral supplementary motor cortex and in the thalamus. PMBS and CMC appear simultaneously at the end of a phasic movement possibly suggesting similar antikinetic effects, but they may be separate processes with different active functions. Whereas PMBS seems to reset the supraspinal sensorimotor network, cortico-muscular coherence may represent the recalibration of cortico-motoneuronal and spinal systems

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