EasyLCMS: an asynchronous web application for the automated quantification of LC-MS data

Metabolomic responses of mussel Mytilus galloprovincialis to fluoranthene exposure under different nutritive conditions

Biomarkers are useful tools to assess biological effects of pollutants that are extensively used in monitoring programs to assess ecosystem health. However, they are strongly affected by mussel physiological state, especially nutritive status, which has led to the search of new biological indicators of chemical pollutants exposition. Environmental metabolomics is an approach for examining the metabolic responses (measurement of low molecular weight endogenous metabolites) of an organism to both natural and anthropogenic stressors that can occur in its environment. The aim of the present work was to assess the effect of the polycyclic aromatic hydrocarbon fluoranthene (FLU) exposure on the metabolomic profiles of mussel digestive glands under different nutritive conditions. To achieve this objective, mussels were reared, for a period of 56 days, under three different food rations in order to obtain a gradient of nutritive status (negative, zero and positive energy balance), and after that, they were exposed, during 3 weeks, to a nominal concentration of 3 μg FLU L^-1. A total of 43 metabolites, including aminoacids (Ala, Val, Leu, Ile, etc.), energy metabolism related metabolites (ATP, AMP, etc.), organic osmolytes (taurine, etc.), redox metabolism (GSH, NADP+) and nucleotides, were identified and quantified in the digestive glands of the mussels. Principal Component Analysis (PCA) defined two principal components (PC1 and PC2) that explained 55.6% of the total variance, although the first component explains more than 80% of this variance, this being related to the mussel nutritive condition. The effect of the toxicant, explained by the PC2, is similar to that produced under conditions of food restriction, which masks the effect of the toxicant under these conditions. As the feeding conditions are more favorable, the toxic effect becomes more apparent. Therefore, the great influence of nutritive condition on mussel metabolome implies a handicap for the use of metabolomic biomarkers, as previously demonstrated for biochemical and other molecular biomarkers, in large-scale monitoring programs in which several food conditions coexist with pollution levels.

From chromatogram to analyte to metabolite. How to pick horses for courses from the massive web resources for mass spectral plant metabolomics

The grand challenge currently facing metabolomics is the expansion of the coverage of the metabolome from a minor percentage of the metabolic complement of the cell toward the level of coverage afforded by other post-genomic technologies such as transcriptomics and proteomics. In plants, this problem is exacerbated by the sheer diversity of chemicals that constitute the metabolome, with the number of metabolites in the plant kingdom generally considered to be in excess of 200 000. In this review, we focus on web resources that can be exploited in order to improve analyte and ultimately metabolite identification and quantification. There is a wide range of available software that not only aids in this but also in the related area of peak alignment; however, for the uninitiated, choosing which program to use is a daunting task. For this reason, we provide an overview of the pros and cons of the software as well as comments regarding the level of programing skills required to effectively exploit their basic functions. In addition, the torrent of available genome and transcriptome sequences that followed the advent of next-generation sequencing has opened up further valuable resources for metabolite identification. All things considered, we posit that only via a continued communal sharing of information such as that deposited in the databases described within the article are we likely to be able to make significant headway toward improving our coverage of the plant metabolome.

Metabolomic responses in caged clams, Ruditapes decussatus, exposed to agricultural and urban inputs in a Mediterranean coastal lagoon (Mar Menor, SE Spain)

The Mar Menor is a coastal lagoon affected by the growth of intensive agriculture and urban development in the surrounding area. Large amounts of chemical pollutants from these areas are discharged into El Albujón, a permanent water-course flowing into the lagoon. Biomarkers such as the activity of acetylcholinesterase or antioxidant enzymes have been previously tested in this lagoon demonstrating the presence of neurotoxicity and oxidative stress in clams transplanted in sites affected by the dispersion of the effluent from El Albujón. To complete this traditional toxicology work, a metabolomic profiling of these transplanted organisms has been carried out for the detection of metabolic biomarkers induced by agricultural/urban pollutants. More than 70 metabolites have been quantified using a targeting metabolomics platform based on HPLC-MS. The intracellular metabolic pattern was analyzed by PCA from the digestive gland of clams after 7 and 22 days of transplantation. Results showed a different profile of metabolite between organisms collected from control and exposed sites. At the shorter exposure time, there was an increase in several metabolites in the latter when compared with those from control sites, whereas metabolic profiling at 22 days showed that those metabolites were drastically diminished, with even lower levels than at control sites. These metabolites included: (i) 12 amino acids from the 21 proteogenic and HomoSer, (ii) osmotic protectants such as γ-butyrobetaine and taurine and (iii) nucleotides such as ITP. Regarding sulfur-containing molecules, taurine could be highlighted as a potential biomarker since its concentration was reduced by more than 30 times after 22 days of exposure, whereas the antioxidant glutathione remained constant in the organisms from both control and exposed sites. Although targeted metabolomics has been shown as an early technique of pollutant effect detection, the two-phase pattern could highlight a more complicated metabolite response to pollutants than classical biomarkers.

Haystack, a web-based tool for metabolomics research

Background

Liquid chromatography coupled to mass spectrometry (LCMS) has become a widely used technique in metabolomics research for differential profiling, the broad screening of biomolecular constituents across multiple samples to diagnose phenotypic differences and elucidate relevant features. However, a significant limitation in LCMS-based metabolomics is the high-throughput data processing required for robust statistical analysis and data modeling for large numbers of samples with hundreds of unique chemical species.

Results

To address this problem, we developed Haystack, a web-based tool designed to visualize, parse, filter, and extract significant features from LCMS datasets rapidly and efficiently. Haystack runs in a browser environment with an intuitive graphical user interface that provides both display and data processing options. Total ion chromatograms (TICs) and base peak chromatograms (BPCs) are automatically displayed, along with time-resolved mass spectra and extracted ion chromatograms (EICs) over any mass range. Output files in the common .csv format can be saved for further statistical analysis or customized graphing. Haystack's core function is a flexible binning procedure that converts the mass dimension of the chromatogram into a set of interval variables that can uniquely identify a sample. Binned mass data can be analyzed by exploratory methods such as principal component analysis (PCA) to model class assignment and identify discriminatory features. The validity of this approach is demonstrated by comparison of a dataset from plants grown at two light conditions with manual and automated peak detection methods. Haystack successfully predicted class assignment based on PCA and cluster analysis, and identified discriminatory features based on analysis of EICs of significant bins.

Conclusion

Haystack, a new online tool for rapid processing and analysis of LCMS-based metabolomics data is described. It offers users a range of data visualization options and supports non-biased differential profiling studies through a unique and flexible binning function that provides an alternative to conventional peak deconvolution analysis methods.

Systematic production of inactivating and non-inactivating suppressor mutations at the relA locus that compensate the detrimental effects of complete spot loss and affect glycogen content in Escherichia coli

In Escherichia coli, ppGpp is a major determinant of growth and glycogen accumulation. Levels of this signaling nucleotide are controlled by the balanced activities of the ppGpp RelA synthetase and the dual-function hydrolase/synthetase SpoT. Here we report the construction of spoT null (ΔspoT) mutants obtained by transducing a ΔspoT allele from ΔrelAΔspoT double mutants into relA⁺ cells. Iodine staining of randomly selected transductants cultured on a rich complex medium revealed differences in glycogen content among them. Sequence and biochemical analyses of 8 ΔspoT clones displaying glycogen-deficient phenotypes revealed different inactivating mutations in relA and no detectable ppGpp when cells were cultured on a rich complex medium. Remarkably, although the co-existence of ΔspoT with relA proficient alleles has generally been considered synthetically lethal, we found that 11 ΔspoT clones displaying high glycogen phenotypes possessed relA mutant alleles with non-inactivating mutations that encoded stable RelA proteins and ppGpp contents reaching 45–85% of those of wild type cells. None of the ΔspoT clones, however, could grow on M9-glucose minimal medium. Both Sanger sequencing of specific genes and high-throughput genome sequencing of the ΔspoT clones revealed that suppressor mutations were restricted to the relA locus. The overall results (a) defined in around 4 nmoles ppGpp/g dry weight the threshold cellular levels that suffice to trigger net glycogen accumulation, (b) showed that mutations in relA, but not necessarily inactivating mutations, can be selected to compensate total SpoT function(s) loss, and (c) provided useful tools for studies of the invivo regulation of E. coli RelA ppGpp synthetase.

Effect of partially protected butyrate used as feed additive on growth and intestinal metabolism in sea bream (Sparus aurata)

Butyrate is a short-chain fatty acid extensively used in animal nutrition since it promotes increases in body weight and other multiple beneficial effects on the intestinal tract. Although such effects have been demonstrated in several species, very few studies have assessed them in fish. On the other hand, little is known about the metabolic processes underlying these effects. In the present work, growth parameters and changes in more than 80 intestinal metabolites (nucleotides, amino acids and derivatives, glycolytic intermediates, redox coenzymes and lipid metabolism coenzymes) have been quantified in juvenile sea bream fed a butyrate-supplemented diet. Results showed a significant increase in the weight of fish receiving butyrate, while metabolomics provided some clues on the suggested effects of this feed additive. It seems that butyrate increased the availability of several essential amino acids and nucleotide derivatives. Also, the energy provision for enteric cells might have been enhanced by a decrease in glucose and amino acid oxidation related to the use of butyrate as fuel. Additionally, butyrate might have increased transmethylation activity. This work represents an advance in the knowledge of the metabolic consequences of using butyrate as an additive in fish diets.