62 research outputs found

    Molecular Approaches to Address Intended and Unintended Effects and Substantial Equivalence of Genetically Modified Crops

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    The release of GM organisms into the environment and marketing of GM crops have resulted in public debate in many parts of the world. This debate is likely to continue, probably in the broader context of plant biotechnology and consequences for human societies. The general issues under debate include cost–benefit analysis and safety issues, but might exhibit regional differences and crop-specific nuances. This chapter addresses an in-depth understanding of events involved in transgene insertion, but also the unintended effects of transformation following the production of genetically enhanced plants. In order to dissect this topic, a foundational overview is given on biolistic- and Agrobacterium-based techniques. Background information of possible transformation-induced unintended alterations to transgenic plant genomes is reviewed and aspects that collectively constitute possible unintended transformation - and post-transformation events are described. This is followed by an overview of molecular techniques to study gene insertion and – expression with special focus on differential gene expression analysis techniques to investigate unintended effects of genetic transformation. Historical and current safety assessment guidelines and requirements are also briefly discussed

    Unravelling the metabolic reconfiguration of the post-challenge primed state in Sorghum bicolor responding to Colletotrichum sublineolum infection

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    Priming is a natural phenomenon that pre-conditions plants for enhanced defence against a wide range of pathogens. It represents a complementary strategy, or sustainable alternative that can provide protection against disease. However, a comprehensive functional and mechanistic understanding of the various layers of priming events is still limited. A non-targeted metabolomics approach was used to investigate metabolic changes in plant growth-promoting rhizobacteria (PGPR)-primed Sorghum bicolor seedlings infected with the anthracnose-causing fungal pathogen, Colletotrichum sublineolum, with a focus on the post-challenge primed state phase. At the 4-leaf growth stage, the plants were treated with a strain of Paenibacillus alvei at 108 cfu mL1. Following a 24 h PGPR application, the plants were inoculated with a C. sublineolum spore suspension (106 spores mL1), and the infection monitored over time: 1, 3, 5, 7 and 9 days post-inoculation. Non-infected plants served as negative controls. Intracellular metabolites from both inoculated and non-inoculated plants were extracted with 80% methanol-water. The extracts were chromatographically and spectrometrically analysed on an ultra-high performance liquid chromatography (UHPLC) system coupled to high-definition mass spectrometry. The acquired multidimensional data were processed to create data matrices for chemometric modelling. The computed models indicated time-related metabolic perturbations that reflect primed responses to the fungal infection. Evaluation of orthogonal projection to latent structure-discriminant analysis (OPLS-DA) loading shared and unique structures (SUS)-plots uncovered the di erential stronger defence responses against the fungal infection observed in primed plants. These involved enhanced levels of amino acids (tyrosine, tryptophan), phytohormones (jasmonic acid and salicylic acid conjugates, and zeatin), and defence-related components of the lipidome. Furthermore, other defence responses in both naïve and primed plants were characterised by a complex mobilisation of phenolic compounds and de novo biosynthesis of the flavones, apigenin and luteolin and the 3-deoxyanthocyanidin phytoalexins, apigeninidin and luteolinidin, as well as some related conjugates.Supplementary Material: Figure S1: Evaluation of disease symptoms in Colletotrichum sublineolum infected sorghum plants; Figure S2: Representative BPI MS chromatograms of ESI(+) data (3 d.p.i.); Figure S3: Unsupervised chemometric modelling of ESI(-) data; Figure S4: OPLS-DA modelling and variable/feature selection. Table S1: Annotated (MSI-level 2) metabolites reported in Table 1, with fragmentation information.The South African National Research Foundation (NRF)http://www.mdpi.com/journal/metabolitesam2020Plant Production and Soil Scienc