Molecular responses of genetically modified maize to abiotic stresses as determined through proteomic and metabolomic analyses

Abstract

Some genetically modified (GM) plants have transgenes that confer tolerance to abiotic stressors. Meanwhile, other transgenes may interact with abiotic stressors, causing pleiotropic effects that will affect the plant physiology. Thus, physiological alteration might have an impact on the product safety. However, routine risk assessment (RA) analyses do not evaluate the response of GM plants exposed to different environmental conditions. Therefore, we here present a proteome profile of herbicide-tolerant maize, including the levels of phytohormones and related compounds, compared to its near-isogenic non-GM variety under drought and herbicide stresses. Twenty differentially abundant proteins were detected between GM and non-GM hybrids under different water deficiency conditions and herbicide sprays. Pathway enrichment analysis showed that most of these proteins are assigned to energetic/carbohydrate metabolic processes. Among phytohormones and related compounds, different levels of ABA, CA, JA, MeJA and SA were detected in the maize varieties and stress conditions analysed. In pathway and proteome analyses, environment was found to be the major source of variation followed by the genetic transformation factor. Nonetheless, differences were detected in the levels of JA, MeJA and CA and in the abundance of 11 proteins when comparing the GM plant and its non-GM near-isogenic variety under the same environmental conditions. Thus, these findings do support molecular studies in GM plants Risk Assessment analyses.

Fig 1. MCIA projection plot.

(A) MCIA projection plot for Experiment 1, representing the proteomic and metabolomic datasets: PC1 = 41.35% and PC2 = 19.73%. (B) MCIA projection plot for Experiment 2, representing the proteomic and metabolomic datasets: PC1 = 47.29% and PC2 = 27.7%. PC1 is represented by the first axis (horizontal), and PC2 is represented by the second axis (vertical). Eigenvalue and Percentage graphics show the amount of variation in the dataset corresponding to each PC. Different symbols represent the respective “omics” analysis and are connected by lines where the length is proportional to the divergence between the data from a same replicate. Lines are joined by a common point, representing the reference structure, which maximizes covariance derived from the MCIA synthetic analysis. Colors represent the biological replicates.

Fig 2. Enrichment analysis of 20 differentially expressed proteins of herbicide-tolerant GM maize variety (NK603) and its non-GM near-isogenic counterpart under control and stress conditions (drought and herbicide application).

The analysis was performed using the online tool agriGO v1.2, using Single Enrichment Analysis (SEA) with the following parameters: 1) Selected species: Zea mays ssp; 2) Statistical test method: Hypergeometric; 3) Multi-test adjustment method: Hochberg (FDR); 4) Significance level of 0.05; 5) Minimum number of 5 mapping entries; and 6) Gene ontology type: Plant GO Slim.

Fig 3. Levels of plant hormones and related compounds for Experiment 1.

Levels of SA, MeJA, CA, JA, ABA and AIA in leaves of herbicide-tolerant GM maize (NK603) variety and its non-GM counterpart under control and drought stress conditions. Compound levels were considered significantly different at ANOVA P < 0.05. When significant, lowercase letters represent the horizontal comparisons in each compound from the Stress factor (non-GM D x non-GM; GM D x GM). Uppercase letters represent the vertical comparisons from the Genetic Modification factor (GM x non-GM; GM D x non-GM D)

Fig 4. Levels of plant hormones and related compounds for Experiment 2.

Levels of SA, ABA, MeJA, CA, JA, and AIA in leaves of herbicide-tolerant GM maize NK603 under drought stress conditions and herbicide application. (*) Compound level was considered significantly different at ANOVA P < 0.05.