Effect of stacking insecticidal cry and herbicide tolerance epsps transgenes on transgenic maize proteome

Abstract

Background: The safe use of stacked transgenic crops in agriculture requires their environmental and health risk assessment, through which unintended adverse effects are examined prior to their release in the environment. Molecular profiling techniques can be considered useful tools to address emerging biosafety gaps. Here we report the first results of a proteomic profiling coupled to transgene transcript expression analysis of a stacked commercial maize hybrid containing insecticidal and herbicide tolerant traits in comparison to the single event hybrids in the same genetic background.

Results: Our results show that stacked genetically modified (GM) genotypes were clustered together and distant from other genotypes analyzed by PCA. Twenty-two proteins were shown to be differentially modulated in stacked and single GM events versus non-GM isogenic maize and a landrace variety with Brazilian genetic background. Enrichment analysis of these proteins provided insight into two major metabolic pathway alterations: energy/carbohydrate and detoxification metabolism. Furthermore, stacked transgene transcript levels had a significant reduction of about 34% when compared to single event hybrid varieties.

Conclusions: Stacking two transgenic inserts into the genome of one GM maize hybrid variety may impact the overall expression of endogenous genes. Observed protein changes differ significantly from those of single event lines and a conventional counterpart. Some of the protein modulation did not fall within the range of the natural variability for the landrace used in this study. Higher expression levels of proteins related to the energy/carbohydrate metabolism suggest that the energetic homeostasis in stacked versus single event hybrid varieties also differ. Upcoming global databases on outputs from "omics" analyses could provide a highly desirable benchmark for the safety assessment of stacked transgenic crop events. Accordingly, further studies should be conducted in order to address the biological relevance and implications of such changes.

Figure 1

Transgene transcripts normalized relative expression levels measured by delta-delta Cq method and Pffafl [ 19] correction equation. The epsps, cry1A.105 and cry2Ab2 transgenes were quantified from stacked versus single transgenic maize events grown under controlled conditions at V3 stage. Experiment 1 (A) and under the same conditions in Experiment 2 (B). Samples are means of three pools, each derived from five different plants. ‘RR’ samples are transgenic maize seedlings from MON-ØØ6Ø3-6 event, ‘Bt’ samples are from MON-89Ø34-3 event, and ‘RRxBt’ samples are transgenic maize seedlings from MON-89Ø34-3 x MON-ØØ6Ø3-6 event. Bars indicate standard deviation and statistically significant values (P < 0.05) are represented by ‘*’.

Figure 2

PCA score plots of proteome data of genetically modified stacked and single events, non-genetically modified near-isogenic variety, and landrace maize variety. Proteome data was obtained by 2D-DIGE analysis from leaf material of maize plants grown under controlled conditions. PC1 and PC2 (A) and PC1 and PC3 (B) show the results of ‘RR’ samples (transgenic maize seedlings from MON-ØØ6Ø3-6 event, filled squares), ‘Bt’ samples (MON-89Ø34-3 event, filled circles), ‘RRxBt’ samples (transgenic maize seedlings from MON-89Ø34-3 x MON-ØØ6Ø3-6 event, filled triangles), ‘CONV’ samples (conventional non-transgenic near isogenic maize variety, blank triangles), and ‘landrace’ (Pixurum 5 landrace variety, blank squares).

Figure 3

Representative 24 cm two-dimensional gel electrophoresis (2D-DIGE) image of the proteome of genetically modified maize plant leaves AG8025 hybrid varieties MON-89Ø34-3 and MON-ØØ6Ø3-6 single events, and MON-89Ø34-3 x MON-ØØ6Ø3-6 stacked event, and non-modified maize (conventional counterpart AG8025 hybrid variety and landrace Pixurum 5 variety) grown under controlled conditions. Two random replicate samples were run together with an internal standard sample, each labeled with a different fluorescence. Individualgel images were obtained and plotted together using ImageQuant TL software from GE healthcare. Linear isoelectric focusing pH 4–7 for the first dimension and 12% SDS–PAGE gels in the second dimension were used. Molecular mass standard range from 250 to 10 kDa are given on the left side. Red arrows point to differentially expressed protein spots selected for mass spectrometry identification. ID of identified proteins from Table 2 are indicated in red numbers.