Identifying and quantifying metabolites by scoring peaks of GC-MS data

Background

Metabolomics is one of most recent omics technologies. It has been applied on fields such as food science, nutrition, drug discovery and systems biology. For this, gas chromatography-mass spectrometry (GC-MS) has been largely applied and many computational tools have been developed to support the analysis of metabolomics data. Among them, AMDIS is perhaps the most used tool for identifying and quantifying metabolites. However, AMDIS generates a high number of false-positives and does not have an interface amenable for high-throughput data analysis. Although additional computational tools have been developed for processing AMDIS results and to perform normalisations and statistical analysis of metabolomics data, there is not yet a single free software or package able to reliably identify and quantify metabolites analysed by GC-MS.

Results

Here we introduce a new algorithm, PScore, able to score peaks according to their likelihood of representing metabolites defined in a mass spectral library. We implemented PScore in a R package called MetaBox and evaluated the applicability and potential of MetaBox by comparing its performance against AMDIS results when analysing volatile organic compounds (VOC) from standard mixtures of metabolites and from female and male mice faecal samples. MetaBox reported lower percentages of false positives and false negatives, and was able to report a higher number of potential biomarkers associated to the metabolism of female and male mice.

Conclusions

Identification and quantification of metabolites is among the most critical and time-consuming steps in GC-MS metabolome analysis. Here we present an algorithm implemented in a R package, which allows users to construct flexible pipelines and analyse metabolomics data in a high-throughput manner.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0374-2) contains supplementary material, which is available to authorized users.     

Efficacy assessed in follow-ups of clinical trials: methodological conundrum

Increasingly, we see papers describing the long-term follow-up results of randomised clinical trials. Sometimes, like the article by Rantalaiho and colleagues in the previous issue of Arthritis Research & Therapy, the follow-up extends to more than 10 years. It is not uncommon that authors of such articles describe their results as a comparison of the original treatment groups in the original randomised clinical trial. Methodologically, such a comparison is fallible for several reasons. In this editorial, two important sources of bias that may jeopardise the results of such follow-up studies are discussed: confounding by indication and confounding by trial completion.     

Idebenone and neuroprotection: antioxidant,pro-oxidant,or electron carrier?

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Nutrient composition of culture media induces different patterns of CO2 fixation from biogas and biomass production by the microalga Scenedesmus obliquus U169

Bioprocess and Biosystems Engineering - Microalgae are considered as a promising biotechnological strategy to capture CO2 from biogas, producing biomass with valuable energetic compounds. This...     

Eine neue Mikrozuckerbestimmungsmethode durch manometrische Bestimmung der Gärungskohlensäure nach Warburg

Ohne Zusammenfassung     

AIF,reactive oxygen species,and neurodegeneration: A “complex” problem

Apoptosis-inducing factor (AIF) is a flavin-binding mitochondrial intermembrane space protein that is implicated in diverse but intertwined processes that include maintenance of electron transport chain function, reactive oxygen species regulation, cell death, and neurodegeneration. In acute brain injury, AIF acquires a pro-death role upon translocation from the mitochondria to the nucleus, where it initiates chromatin condensation and large-scale DNA fragmentation. Although harlequin mice exhibiting an 80–90% global reduction in AIF protein are resistant to numerous forms of acute brain injury, they paradoxically undergo slow, progressive neurodegeneration beginning at three months of age. Brain deterioration, accompanied by markers of oxidative stress, is most pronounced in the cerebellum and retina, although it also occurs in the cortex, striatum, and thalamus. Loss of an AIF pro-survival function linked to assembly or stabilization of electron transport chain complex I underlies chronic neurodegeneration. To date, most studies of neurodegeneration have failed to adequately separate the relative importance of the mitochondrial and nuclear functions of AIF in determining the extent of injury, or whether oxidative stress plays a causative role. This review explores the complicated relationship among AIF, complex I, and the regulation of mitochondrial reactive oxygen species levels. It also discusses the controversial role of complex I deficiency in Parkinson’s disease, and what can be learned from the AIF- and complex I-depleted harlequin mouse.     

Application of stains in clinical microbiology

Stains have been used for diagnosing infectious diseases since the late 1800s. The Gram stain remains the most commonly used stain because it detects and differentiates a wide range of pathogens. The next most commonly used diagnostic technique is acid-fast staining that is used primarily to detect Mycobacterium tuberculosis and other severe infections. Many infectious agents grow slowly on culture media or may not grow at all; stains may be the only method to detect these organisms in clinical specimens. In the hands of experienced clinical microscopists, stains provide rapid and cost-effective information for preliminary diagnosis of infectious diseases. A review of the most common staining methods used in the clinical microbiology laboratory is presented here.