Quality control for plant metabolomics: reporting MSI‐compliant studies

Abstract

SummaryThe Metabolomics Standards Initiative (MSI) has recently released documents describing minimum parameters for reporting metabolomics experiments, in order to validate metabolomic studies and to facilitate data exchange. The reporting parameters encompassed by MSI include the biological study design, sample preparation, data acquisition, data processing, data analysis and interpretation relative to the biological hypotheses being evaluated. Herein we exemplify how such metadata can be reported by using a small case study -the metabolite profiling by GC-TOF mass spectrometry of Arabidopsis thaliana leaves from a knockout allele of the gene At1g08510 in the Wassilewskija ecotype. Pitfalls in quality control are highlighted that can invalidate results even if MSI reporting standards are fulfilled, including reliable compound identification and integration of unknown metabolites. Standardized data processing methods are proposed for consistent data storage and dissemination via databases.

Trichoderma gamsii affected herbivore feeding behaviour on Arabidopsis thaliana by modifying the leaf metabolome and phytohormones

“…Internal standards C08‐C30 fatty acid methyl esters (FAMEs) were added, and the sample was derivatized by methoxyamine hydrochloride in pyridine and subsequently by N‐methyl‐N‐trimethylsilyltrifluoroacetamide for trimethylsilylation of acidic protons (Broeckling et al ., 2005). Samples were analysed according to the methods of Feihn (Fiehn et al ., 2008) by GC‐TOF primary metabolite analysis at West Coast Metabolomics Center, UC‐DAVIS. Mass spectrometry parameters were used as follows: a Leco Pegasus IV mass spectrometer was used with unit mass resolution at 17 spectra s −1 from 80–500 Da at −70 eV ionization energy and 1800 V detector voltage with a 230°C transfer line and a 250°C ion source.…”

Dealing with the unknown: Metabolomics and Metabolite Atlases

“…This can be accomplished by following the reporting standards defined by the metabolomics community [21][22][23]. For example, experimental details should be linked to the metabolite features, which can also be linked to metabolite databases, i.e., METLIN [5], KEGG [6], MetaCyc [7], the Golm Metabolome Database [8], HMDB [9], LIPID-MAPS [10], and MassBank (URL: http://www.massbank.…”

Effects of facultative symbionts and heat stress on the metabolome of pea aphids

“…Pellets were washed in 500 ml of 50% acetonitrile:water to remove membrane and storage lipids and dried again. Thirty external standards were used to check for instrument performance in calibration series before and after the runs to ensure instrument drifts or other effects that would compromise quantification differences did not occur; 2 ml of internal retention index markers were added to the dried extracts (for automatic retention index calculation to allow for compound identifications) and derivatized as described by Fiehn et al (2008). An agilent 6890 gas chromatograph (Santa Clara, CA, USA) and a Leco Pegasus IV time of flight spectrometer were used, controlled by the Leco ChromaTOF software vs 2.32 (St Joseph, MI, USA); 0.5 ml of sample was injected in split mode with a 1:5 ratio.…”

“…An agilent 6890 gas chromatograph (Santa Clara, CA, USA) and a Leco Pegasus IV time of flight spectrometer were used, controlled by the Leco ChromaTOF software vs 2.32 (St Joseph, MI, USA); 0.5 ml of sample was injected in split mode with a 1:5 ratio. Injector and oven temperatures, column specifications, ionization, and mass spectrometry were performed as described in Fiehn et al (2008). ChromaTOF vs 2.32 was used for data preprocessing and resulting files were exported and further processed by a filtering algorithm implemented in the metabolomics BinBase database (Fiehn et al, 2005).…”