A non-directed approach to the differential analysis of multiple LC–MS-derived metabolic profiles

Abstract

An essential element of any strategy for non-targeted metabolomics analysis of complex biological extracts is the capacity to perform comparisons between large numbers of samples. As the most widely used technologies are all based on mass spectrometry (e.g. GCMS, LCMS), this entails that we must be able to compare reliably and (semi)automatically large series of chromatographic mass spectra from which compositional differences are to be extracted in a statistically justifiable manner. In this paper we describe a novel approach for the extraction of relevant information from multiple full-scan metabolic profiles derived from LC-MS analyses. Specifically-designed software has made it possible to combine all mass peaks on the basis of retention time and m/z values only, without prior identification, to produce a data matrix output which can then be used for multivariate statistical analysis. To demonstrate the capacity of this approach, aqueous methanol extracts from potato tuber tissues of eight contrasting genotypes, harvested at two developmental stages have been used. Our results showed that it is possible to discover reproducibly discriminatory mass peaks related both to the genetic origin of the material as well as the developmental stage at which it was harvested. In addition the limitations of the approach are explored by a careful evaluation of the alignment quality.

A Liquid Chromatography-Mass Spectrometry-Based Metabolome Database for Tomato

“…First, reproducibility of sample preparation and subsequent automated extraction and comparison of mass signal intensities, expressed as peak height using metAlign software Vorst et al, 2005), was performed on a dataset obtained from LC-MS analysis of eight replicate extractions of tomato peel. The retention time correction used by the software to align all mass signals was, on average, 2.5 s, which is in accordance to the retention shift observed on manual inspection of the chromatograms (Table II).…”

“…Specifically, high resolution accurate mass MS enables the detection of large numbers of parent ions present in a single extract and can provide valuable information on the chemical composition and thus the putative identity of large numbers of metabolites. Recently, accurate mass LC-MS was performed to detect secondary metabolites present in roots and leaves of Arabidopsis (Arabidopsis thaliana; von RoepenackLahaye et al, 2004), to study metabolic alterations in a light-hypersensitive mutant of tomato (Solanum lycopersicum; Bino et al, 2005), and to compare tubers of potato (Solanum tuberosum) of different genetic origin and developmental stages (Vorst et al, 2005). The variety of LC-MS systems, and the generally poorer retention time reproducibility of LC compared to GC, limits the establishment of a single optimized analytical procedure and hampers the comparison of LC-MS chromatograms between laboratories.…”

An introduction to liquid chromatography–mass spectrometry instrumentation applied in plant metabolomic analyses

“…The sample is introduced either by manual direct infusion (DI) or via HPLC or UHPLC followed by DI, following which the sample is delivered to the probe via a capillary; the probe functions to translocate the liquid sample from the capillary to the needle of the ion source. Two ionisation sources are generally employed in LC-MS based metabolomics: electrospray ionisation (ESI) is the most commonly employed (Tolstikov et al, 2003;Jander et al, 2004;von Roepenack-Lahaye et al, 2004;Vorst et al, 2005;Moco et al, 2006;Rischer et al, 2006;De Vos et al, 2007;Hanhineva et al, 2008) and is particularly well suited to the ionisation of a wide range of metabolites including, drug compounds (Chen et al, 2007), amino and organic acids Figure 3. The relationship between column stationary phase particle size, fl ow velocity and the height equivalent to the theoretical plate (HETP) value as an expression of chromatographic separation effi ciency.…”

“…These latter methods can be extremely useful for detecting certain classes of compound that either absorb UV or fl uoresce (e.g. kaempferols, quercetins, spermidines); indeed PDA detectors have frequently been linked online to HPLC or UHPLC prior to MS in plant metabolomics studies to provide a further dimension to aid in the characterisation of the detected analyte species (HPLC/UHPLC-PDA-MS; Vorst et al, 2005;Moco et al, 2006;De Vos et al, 2007;Hanhineva et al, 2008). However, to acquire the volume of information from an analyte required for full structural elucidation, it is a necessity to employ MS and/or NMR spectroscopy detectors.…”

“…chromatography combined with mass spectrometry (MS) or nuclear magnetic resonance (NMR) spectroscopy is capable of detecting all metabolites within a given biological sample Hall, 2006;Allwood et al, 2008). Over the past decade many methods for the high-throughput metabolomic analysis of plant derived samples have been established for gas chromatography combined with MS (GC-MS; Fiehn et al, 2000;Fernie et al, 2004;Lisec et al, 2006), direct injection mass spectrometry (DIMS; Goodacre et al, 2003;Catchpole et al, 2005;Allwood et al, 2006), liquid chromatography MS (LC-MS; Tolstikov et al, 2003;Jander et al, 2004;von Roepenack-Lahaye et al, 2004;Vorst et al, 2005;Moco et al, 2006;Rischer et al, 2006;De Vos et al, 2007), capillary electrophoresis MS (CE-MS; Sato et al, 2004), and 1 H-NMR (Ratcliff e and Shachar-Hill, 2001;Le Gall et al, 2003;Ward et al, 2003;Choi et al, 2004Choi et al, , 2006. 1 H-NMR has proven to be an appropriate tool for untargeted plant metabolomics, especially where studies focus upon samples that contain highly abundant bulk metabolite species, for example sugars in fruits (Biais et al, 2009).…”