Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Safety assessment of novel foods using omics profiling combined with one-class classifiers

ABSTRACT: Food safety evaluation of new, genetically modified (GM) plant varieties has led to basic questions regarding the safety assessment of new plant varieties and whole foods derived thereof. An important part of the hazard identification in the European approach is a targeted compositional analysis of new GM plant varieties compared to one or more conventional reference varieties. Comparative analysis will become much more informative with unbiased analytical approaches, such as omics profiling. Analysis tools that estimate the similarity of new varieties to the reference would in turn greatly facilitate hazard identification. Further in-depth biological, functional and eventually toxicological analysis of the data would then only be necessary for varieties that fall outside the scale of those with a history of safe human consumption. For this purpose, the use of a one-class classifier tool was explored in this study to assess and classify transcriptome profiles of potato varieties. Five potato varieties were grown in the Netherlands during the same year (NL samples) and included four biological replicates for four varieties or two biological replicates for the fifth one. They were all analysed in 2011. A sixth variety was grown in the UK in a previous study and a previous year, for which the data are submitted in E-MTAB-605. The two UK samples were analysed in the original study in 2008 and again together with the NL samples in the present study, resulting in four profiles for two samples.

ORGANISM(S): Solanum tuberosum

SUBMITTER: Jeroen van Dijk

PROVIDER: E-MTAB-1707 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:We used iTRAQ technology to investigate the protein expression characteristics of S-RNases in S-gene homozygous germplasm. By using MaxQuant to search the raw mass spectrometry data files against the protein database, a total of 30,503 identified spectra, 13,568 peptides, and 4,472 proteins were identified in the styles of Huanghua (S1S2) and its homozygous S-genotype offspring (S1S1 and S2S2). These identified proteins were predicted to be located in extracellular regions, cytoplasm, nucleus, mitochondria, Golgi apparatus, endoplasmic reticulum, peroxisomes, vacuoles, nucleoplasm, and other cellular compartments. The number of DEPs among the three varieties was calculated. According to the overall distribution of these proteins, the highest number of DEPs was between S2S2 and S1S2, while the lowest number of DEPs was between S2S2 and S1S1. This indicated that the protein expression patterns of S2S2 and S1S1 were more similar to each other, while both offspring samples showed significant differences in protein expression when compared with the parent S1S2. In this study, we conducted DEP analyses focusing on S-RNases and the proteins that interact with them in the styles of the three pear varieties. Figure 6 shows the heat-map of the expression levels of the 13 identified S-RNase-related proteins, which reflects their differences in expression levels across the three samples. In terms of the overall expression trend, using the offspring sample S1S1 as a normal expression standard, most of the S-RNase-related proteins were down-regulated in the parent S1S2. In contrast, in the offspring sample S2S2, most of the S-RNase-related proteins were up-regulated relative to their levels in the other offspring sample S1S1, with only a few exceptions. Compared with the parent S1S2, both offspring samples, S1S1 and S2S2, showed up-regulated expression of 12 out of the 13 S-RNase-related proteins, except for S1-RNase. Comparing S1S1 and S2S2, the expression levels of F-box/WD-repeat_TBL1XR1, SKP1-like_1A_2, and S2-RNase were higher in S1S1 than in S2S2, while the expression levels of the other 10 S-RNase-related proteins were higher in S2S2 than in S1S1.

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Safety assessment of novel foods using omics profiling combined with one-class classifiers

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