Metabolomics responses and tolerance of Pseudomonas aeruginosa under acoustic vibration stress

Sound has been shown to impact microbial behaviors. However, our understanding of the chemical and molecular mechanisms underlying these microbial responses to acoustic vibration is limited. In this study, we used untargeted metabolomics analysis to investigate the effects of 100-Hz acoustic vibration on the intra- and extracellular hydrophobic metabolites of P. aeruginosa PAO1. Our findings revealed increased levels of fatty acids and their derivatives, quinolones, and N-acylethanolamines upon sound exposure, while rhamnolipids (RLs) showed decreased levels. Further quantitative real-time polymerase chain reaction experiments showed slight downregulation of the rhlA gene (1.3-fold) and upregulation of fabY (1.5-fold), fadE (1.7-fold), and pqsA (1.4-fold) genes, which are associated with RL, fatty acid, and quinolone biosynthesis. However, no alterations in the genes related to the rpoS regulators or quorum-sensing networks were observed. Supplementing sodium oleate to P. aeruginosa cultures to simulate the effects of sound resulted in increased tolerance of P. aeruginosa in the presence of sound at 48 h, suggesting a potential novel response-tolerance correlation. In contrast, adding RL, which went against the response direction, did not affect its growth. Overall, these findings provide potential implications for the control and manipulation of virulence and bacterial characteristics for medical and industrial applications

Body Fat Free Mass Is Associated with the Serum Metabolite Profile in a Population-Based Study

To characterise the influence of the fat free mass on the metabolite profile in serum samples from participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg) S4 study. Analyses were based on metabolite profile from 965 participants of the S4 and 890 weight-stable subjects of its seven-year follow-up study (KORA F4). 190 different serum metabolites were quantified in a targeted approach including amino acids, acylcarnitines, phosphatidylcholines (PCs), sphingomyelins and hexose. Associations between metabolite concentrations and the fat free mass index (FFMI) were analysed using adjusted linear regression models. To draw conclusions on enzymatic reactions, intra-metabolite class ratios were explored. Pairwise relationships among metabolites were investigated and illustrated by means of Gaussian graphical models (GGMs). We found 339 significant associations between FFMI and various metabolites in KORA S4. Among the most prominent associations (p-values 4.75 × 10(-16)-8.95 × 10(-06)) with higher FFMI were increasing concentrations of the branched chained amino acids (BCAAs), ratios of BCAAs to glucogenic amino acids, and carnitine concentrations. For various PCs, a decrease in chain length or in saturation of the fatty acid moieties could be observed with increasing FFMI, as well as an overall shift from acyl-alkyl PCs to diacyl PCs. These findings were reproduced in KORA F4. The established GGMs supported the regression results and provided a comprehensive picture of the relationships between metabolites. In a sub-analysis, most of the discovered associations did not exist in obese subjects in contrast to non-obese subjects, possibly indicating derangements in skeletal muscle metabolism. A set of serum metabolites strongly associated with FFMI was identified and a network explaining the relationships among metabolites was established. These results offer a novel and more complete picture of the FFMI effects on serum metabolites in a data-driven network

Pseudochelin A, a siderophore of Pseudoalteromonas piscicida S2040

A new siderophore containing a 4,5-dihydroimidazole moiety was isolated from Pseudoalteromonas piscicida S2040 together with myxochelins A and B, alteramide A and its cycloaddition product, and bromo- and dibromoalterochromides. The structure of pseudochelin A was established by spectroscopic techniques including 2D NMR and MS/MS fragmentation data. In bioassays selected fractions of the crude extract of S2040 inhibited the opportunistic pathogen Pseudomonas aeruginosa. Pseudochelin A displayed siderophore activity in the chrome azurol S assay at concentrations higher than 50 μM, and showed weak activity against the fungus Aspergillus fumigatus, but did not display antibacterial, anti-inflammatory or anticonvulsant activity

Metabolomics-Based Discovery of Diagnostic Biomarkers for Onchocerciasis

Onchocerciasis, caused by the filarial parasite Onchocerca volvulus, afflicts millions of people, causing such debilitating symptoms as blindness and acute dermatitis. There are no accurate, sensitive means of diagnosing O. volvulus infection. Clinical diagnostics are desperately needed in order to achieve the goals of controlling and eliminating onchocerciasis and neglected tropical diseases in general. In this study, a metabolomics approach is introduced for the discovery of small molecule biomarkers that can be used to diagnose O. volvulus infection. Blood samples from O. volvulus infected and uninfected individuals from different geographic regions were compared using liquid chromatography separation and mass spectrometry identification. Thousands of chromatographic mass features were statistically compared to discover 14 mass features that were significantly different between infected and uninfected individuals. Multivariate statistical analysis and machine learning algorithms demonstrated how these biomarkers could be used to differentiate between infected and uninfected individuals and indicate that the diagnostic may even be sensitive enough to assess the viability of worms. This study suggests a future potential of these biomarkers for use in a field-based onchocerciasis diagnostic and how such an approach could be expanded for the development of diagnostics for other neglected tropical diseases

Serum Metabolome and Lipidome Changes in Adult Patients with Primary Dengue Infection

10.1371/journal.pntd.0002373PLoS Neglected Tropical Diseases78

Pair-wise multicomparison and OPLS analyses of cold-acclimation phases in Siberian spruce

Analysis of metabolomics data often goes beyond the task of discovering biomarkers and can be aimed at recovering other important characteristics of observed metabolomic changes. In this paper we explore different methods to detect the presence of distinctive phases in seasonal-responsive changes of metabolomic patterns of Siberian spruce (Picea obovata) during cold acclimation occurred in the period from mid-August to January. Multivariate analysis, specifically orthogonal projection to latent structures discriminant analysis (OPLSDA), identified time points where the metabolomic patterns underwent substantial modifications as a whole, revealing four distinctive phases during acclimation. This conclusion was re-examined by a univariate analysis consisting of multiple pair-wise comparisons to identify homogeneity intervals for each metabolite. These tests complemented OPLS-DA, clarifying biological interpretation of the classification: about 60% of metabolites found responsive to the cold stress indeed changed at one or more of the time points predicted by OPLS-DA. However, the univariate approach did not support the proposed division of the acclimation period into four phases: less than 10% of metabolites altered during the acclimation had homogeneous levels predicted by OPLS-DA. This demonstrates that coupling the classification found by OPLS-DA and the analysis of dynamics of individual metabolites obtained by pair-wise multicomparisons reveals a more correct characterization of biochemical processes in freezing tolerant trees and leads to interpretations that cannot be deduced by either method alone. The combined analysis can be used in other ‘omics’-studies, where response factors have a causal dependence (like the time in the present work) and pairwise multicomparisons are not conservative.Published online 11 april 2011. Copywright, The Author(s) 2011. This article is published with open access at Springerlink.co