GNPS-CCFA_Complex_food_Spiking
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Q Exactive
ORGANISM(S): Food Samples
SUBMITTER: 
Pieter Dorrestein
PROVIDER: MSV000097994 | GNPS | Mon May 26 10:21:00 BST 2025
REPOSITORIES: GNPS
Similar Datasets
Project description:This study aims at assessing the capability of comparing and combining different instrumental platforms in an untargeted approach with a view of detecting chemical contaminants in food matrices at low levels. A strategy based on liquid chromatography-high resolution mass spectrometry (LC-HRMS) and chemometrics has been applied on two different complex food contamination scenarios, with tea as study product. The first scenario aimed at mimic the presence of a dozen of contaminants at levels just above regulatory limits (i.e. 10 and 30 μg/kg); the second scenario, more complex, aimed at simulate the presence of several different contaminations at levels close to regulatory limits (10 μg/kg) in different samples. This work was carried on two LC-HRMS platforms (with respectively ToF and Orbitrap mass analyzer technologies), and a highly automated data treatment workflow was implemented to deal with data acquired on both platforms. The untargeted approach performed well on all scenarios (even the most complex) and analytical platforms. Performance comparison between LC-HRMS technologies was made possible thanks to a vendor-neutral data treatment process. </br><br/> Sub-samples of black tea (Keemun type, gross, China) were spiked at 10 µg/kg levels with two different spiking mixes: Three sub-samples were spiked with a pool of 11 contaminants (spiking mix n°1); and Three sub-samples were spiked with 3 others contaminants (malathion, OTA, BPS, spiking mix n°2). Samples were then extracted with a generic method and analyzed by LC-HRMS (in both positive and negative ionization modes) on two platforms (respectively Orbitrap and ToF to generate a total of four data sets. </br></br> Black tea spiked with contaminants is reported in the current study MTBLS772. </br> Green tea spiked with contaminants is reported in MTBLS771. </br><br/> Linked Studies: <a href='https://www.ebi.ac.uk/metabolights/MTBLS771' target='_blank'><span class='label label-success'>MTBLS771</span></a>
2019-02-12 | MTBLS772 | MetaboLights
Project description:The silkworm (Bombyx mori) has long been considered a source of food and medicine due to its high nutritional, medicinal, and economic value in East Asia. However, in some sensitive individuals, silkworm consumption can cause allergenic reactions such as vomiting, asthma, and anaphylaxis. Therefore, the development of a reliable method for silkworm detection is required to avoid such allergenic incidents. In this study, two different methods (liquid chromatography combined with mass spectrometry [LC-MS/MS] and real-time polymerase chain reaction [PCR]) were developed to determine an efficient technique for silkworm detection in foods. The developed methods demonstrated high sensitivity in detecting the silkworm in processed foods. Silkworm-spiked model cookies were used to confirm the sensitivity of both LC-MS/MS (0.0005%) and real-time PCR (0.001%). These methods were found to be useful for detecting the silkworm in foods and avoiding allergenic reactions. To the best of our knowledge, this is the first study to compare LC-MS/MS and real-time PCR for silkworm detection in complex processed foods.
2024-05-24 | PXD042494 | Pride
Project description:Lactobacillus helveticus is a rod-shaped lactic acid bacterium that is widely used in the manufacture of fermented dairy foods and for production of bioactive peptides from milk proteins. Although L. helveticus is commonly associated with milk environments, phylogenetic studies show it is closely related to an intestinal species, Lactobacillus acidophilus, which has been shown to impart probiotic health benefits to humans. This relationship has fueled a prevailing hypothesis that L. helveticus is a highly specialized derivative of L. acidophilus which has adapted to acidified whey. However, L. helveticus has also been sporadically recovered from non-dairy environments, which argues the species may not be as highly specialized as is widely believed. This study employed genome sequence analysis and comparative genome hybridizations to investigate genomic diversity among L. helveticus strains collected from cheese, whey, and whiskey malt, as well as commercial cultures used in manufacture of cheese or bioactive dairy foods. Results revealed considerable variability in gene content between some L. helveticus strains, and indicated the species should not be viewed as a strict dairy-niche specialist. In addition, comparative genomic analyses provided new insight on several industrially and ecologically important attributes of L. helveticus that may facilitate commercial strain selection.
2013-08-16 | GSE23660 | GEO
Project description:Protein extracts of Saccharomyces cerevisiae CEN.PK113-7D cultivated in chemostats under different conditions. Representative samples containing aliquots of all conditions were spiked with UPS2 standard (Sigma) to estimate absolute values in fmol. The conditions for Saccharomyces cerevisiae CEN.PK113-7D are: T2- Standard condition : 30°C, pH 5.5 T3- High temperature: 36°C, pH 5.5 T4- Low pH: 30°C, pH 3.5 T5- Osmotic stress : 30°C, pH 5.5, 1M KCl T6- Anaerobic condition Furthermore, representative samples pooling aliquots of each condition are indicated as "bulk" samples. These samples were spiked with UPS proteins. A validation step was carried out by spiking 4 external proteins at known concentrations within the yeast and UPS proteins mixture
2022-02-15 | PXD014765 | Pride
Project description:Analysis of Lactobacillus plantarum stains isolated from different cheese type
2017-07-12 | GSE101169 | GEO
Project description:To provide useful data for development and validation of the PyMS Mass Spectrometry software, a test dataset was run at Metabolomics Australia. A biologically complex mix of a biological background material (foetal calf serum), spiked with 2-fold increasing amounts of a mix of metabolite standards. In addition, a single sample consisting of a simple mix of 45 metabolites representing a variety of chemical classes (sufars, organic acids, amino acids, sugar phosphates), was run through a standard Metabolomics Australia GC-MS analysis. The resulting data is a valuable tool in testing GC-MS data analysis software.
2012-03-29 | MTBLS6 | MetaboLights
Project description:This study uses spiked-in transcript in order to compares various bioinformatics approaches and tools to assemble, quantify abundance and detect differentially expressed transcripts using RNA-Seq data. Mouse total RNA seq was extracted from embryonic stem cells (ES) before (designated as day 0) and four days after the addition of retinoic acid. 48 spikes were made in vitro from plasmid constructs and added to the total RNA in different concentrations (each mix has a set of different spike concentrations, see paper's method). We found that detection of differential expression at the gene level is acceptable, yet on the transcript-isofom level all tools tested were lacking accuracy and precision.
2016-04-26 | GSE71802 | GEO
Project description:Lactobacillus helveticus is a rod-shaped lactic acid bacterium that is widely used in the manufacture of fermented dairy foods and for production of bioactive peptides from milk proteins. Although L. helveticus is commonly associated with milk environments, phylogenetic studies show it is closely related to an intestinal species, Lactobacillus acidophilus, which has been shown to impart probiotic health benefits to humans. This relationship has fueled a prevailing hypothesis that L. helveticus is a highly specialized derivative of L. acidophilus which has adapted to acidified whey. However, L. helveticus has also been sporadically recovered from non-dairy environments, which argues the species may not be as highly specialized as is widely believed. This study employed genome sequence analysis and comparative genome hybridizations to investigate genomic diversity among L. helveticus strains collected from cheese, whey, and whiskey malt, as well as commercial cultures used in manufacture of cheese or bioactive dairy foods. Results revealed considerable variability in gene content between some L. helveticus strains, and indicated the species should not be viewed as a strict dairy-niche specialist. In addition, comparative genomic analyses provided new insight on several industrially and ecologically important attributes of L. helveticus that may facilitate commercial strain selection. 42 samples were hybridized to the microarray chip, which contains probe sequences from L. helveticus CNRZ32. CNRZ32 was also hybridized and used as the reference sample. Data from the microarray was statistically analyzed using the R software. Samples were compared to the reference (CNRZ32) to investigate genome diversity amoung L. helveticus strains,
2013-08-16 | E-GEOD-23660 | biostudies-arrayexpress
Project description:Powerful data pretreatment strategies inspired from the field of metabolomics were adapted to chemical food safety context to enable samples discrimination by multivariate methods based on low abundance ions. A highly automated workflow was produced. The open-source XCMS package was used and efficient data filtration strategies were set up. Data were treated using Independent Components Analysis, and data mining strategies developed to automatically detect and annotate ions of low abundance by coupling blind data exploration strategies with a broad scale database approach. Our method was efficient in discriminating tea samples based on their contamination levels (even at 10µg/kg) and detecting unexpected impurities in the spiking mix. Several “tracer” contaminants were considered, covering a broad range of physicochemical properties and structural diversity with overall 66% detected and annotated blindly. The methodology was successfully applied to a data set exhibiting only 3 “tracer” contaminants (at 50µg/kg) and more product diversity. </br></br> Dataset 1 with 1 tea spiked with 32 contaminants and referred to as the Development dataset is reported in the current study MTBLS752. </br> Dataset 2 with 2 teas spiked with 3 contaminants and referred to as the Validation dataset is reported in MTBLS754. </br><br/> Linked Studies: <a href='https://www.ebi.ac.uk/metabolights/MTBLS754' target='_blank'><span class='label label-success'>MTBLS754</span></a>
2018-10-26 | MTBLS752 | MetaboLights
Project description:Powerful data pretreatment strategies inspired from the field of metabolomics were adapted to chemical food safety context to enable samples discrimination by multivariate methods based on low abundance ions. A highly automated workflow was produced. The open-source XCMS package was used and efficient data filtration strategies were set up. Data were treated using Independent Components Analysis, and data mining strategies developed to automatically detect and annotate ions of low abundance by coupling blind data exploration strategies with a broad scale database approach. Our method was efficient in discriminating tea samples based on their contamination levels (even at 10µg/kg) and detecting unexpected impurities in the spiking mix. Several “tracer” contaminants were considered, covering a broad range of physicochemical properties and structural diversity with overall 66% detected and annotated blindly. The methodology was successfully applied to a data set exhibiting only 3 “tracer” contaminants (at 50µg/kg) and more product diversity. </br></br> Dataset 2 with 2 teas spiked with 3 contaminants and referred to as the Validation datase is reported in the current study MTBLS754. </br> Dataset 1 with 1 tea spiked with 32 contaminants and referred to as the Development dataset is reported in MTBLS752. </br><br/> Linked Studies: <a href='https://www.ebi.ac.uk/metabolights/MTBLS752' target='_blank'><span class='label label-success'>MTBLS752</span></a>
2018-10-26 | MTBLS754 | MetaboLights