Combining metabolomic non-targeted GC×GC-ToF-MS analysis and chemometric ASCA-based study of variances to assess dietary influence on type 2 diabetes development in a mouse model.

Insulin resistance (IR) lies at the origin of type 2 diabetes. It induces initial compensatory insulin secretion until insulin exhaustion and subsequent excessive levels of glucose (hyperglycemia). A high-calorie diet is a major risk factor contributing to the development of this metabolic disease. For this study, a time-course experiment was designed that consisted of two groups of mice. The aim of this design was to reproduce the dietary conditions that parallel the progress of IR over time. The first group was fed with a high-fatty-acid diet for several weeks and followed by 1 week of a low-fatty-acid intake, while the second group was fed with a low-fatty-acid diet during the entire experiment. The metabolomic fingerprint of C3HeB/FeJ mice liver tissue extracts was determined by means of two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-ToF-MS). This article addresses the application of ANOVA-simultaneous component analysis (ASCA) to the found metabolomic profile. By performing hyphenated high-throughput analytical techniques together with multivariate chemometric methodology on metabolomic analysis, it enables us to investigate the sources of variability in the data related to each experimental factor of the study design (defined as time, diet and individual). The contribution of the diet factor in the dissimilarities between the samples appeared to be predominant over the time factor contribution. Nevertheless, there is a significant contribution of the time-diet interaction factor. Thus, evaluating the influences of the factors separately, as it is done in classical statistical methods, may lead to inaccurate interpretation of the data, preventing achievement of consistent biological conclusions

Untargeted identification of wood type-specific markers in particulate matter from wood combustion.

Residential wood combustion emissions are one of the major global sources of particulate and gaseous organic pollutants. However, the detailed chemical compositions of these emissions are poorly characterized due to their highly complex molecular compositions, non-ideal combustion conditions and sample preparation steps. In this study, the particulate organic emissions from a masonry heater using three types of wood logs, namely, beech, birch and spruce, were chemically characterized using thermal desorption in situ derivatization coupled to a GCxGC-ToF/MS system. Untargeted data analyses were performed using the comprehensive measurements. Univariate and multivariate chemometric tools, such as analysis of variance (ANOVA), principal component analysis (PCA) and ANOVA simultaneous component analysis (ASCA), were used to reduce the data to highly significant and wood type-specific features. This study reveals substances not previously considered in the literature as meaningful markers for differentiation among wood types

The impact of blood on liver metabolite profiling - a combined metabolomic and proteomic approach.

Metabolomics has entered the well-established omic sciences as it is an indispensable information resource to achieve a global picture of biological systems. The aim of the present study was to estimate the influence of blood removal from mice liver as part of sample preparation for metabolomic and proteomic studies. For this purpose, perfused mice liver tissue (i.e. with blood removed) and unperfused mice liver tissue (i.e. containing blood) were compared by two-dimensional gas chromatography time of flight mass spectrometry (GC × GC-TOFMS) for the metabolomic part, and by liquid chromatography tandem mass spectrometry (LC-MS/MS) for the proteomic part. Our data showed significant differences between the unperfused and perfused liver tissue samples. Furthermore, we also observed an overlap of blood and tissue metabolite profiles in our data, suggesting that the perfusion of liver tissue prior to analysis is beneficial for an accurate metabolic profile of this orga

ESICM LIVES 2016: part two : Milan, Italy. 1-5 October 2016.

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