Approach strategies and application of metabolomics to biotechnology in plants.

Metabolomics refers to the technology for the comprehensive analysis of metabolites and low-molecular-weight compounds in a biological system, such as cells or tissues. Metabolites play an important role in biological phenomena through their direct involvement in the regulation of physiological mechanisms, such as maintaining cell homeostasis or signal transmission through protein-protein interactions. The current review aims provide a framework for how the integrated analysis of metabolites, their functional actions and inherent biological information can be used to understand biological phenomena related to the regulation of metabolites and how this information can be applied to safety assessments of crops created using biotechnology. Advancement in technology and analytical instrumentation have led new ways to examine the convergence between biology and chemistry, which has yielded a deeper understanding of complex biological phenomena. Metabolomics can be utilized and applied to safety assessments of biotechnology products through a systematic approach using metabolite-level data processing algorithms, statistical techniques, and database development. The integration of metabolomics data with sequencing data is a key step towards improving additional phenotypical evidence to elucidate the degree of environmental affects for variants found in genome associated with metabolic processes. Moreover, information analysis technology such as big data, machine learning, and IT investment must be introduced to establish a system for data extraction, selection, and metabolomic data analysis for the interpretation of biological implications of biotechnology innovations. This review outlines the integrity of metabolomics assessments in determining the consequences of genetic engineering and biotechnology in plants.

Silencing of the Target of Rapamycin Complex Genes Stimulates Tomato Fruit Ripening.

The target of rapamycin complex (TORC) plays a key role in plant cell growth and survival by regulating the gene expression and metabolism according to environmental information. TORC activates transcription, mRNA translation, and anabolic processes under favorable conditions, thereby promoting plant growth and development. Tomato fruit ripening is a complex developmental process promoted by ethylene and specific transcription factors. TORC is known to modulate leaf senescence in tomato. In this study, we investigated the function of TORC in tomato fruit ripening using virus-induced gene silencing (VIGS) of the TORC genes, TOR, lethal with SEC13 protein 8 (LST8), and regulatory-associated protein of TOR (RAPTOR). Quantitative reverse transcription-polymerase chain reaction showed that the expression levels of tomato TORC genes were the highest in the orange stage during fruit development in Micro-Tom tomato. VIGS of these TORC genes using stage 2 tomato accelerated fruit ripening with premature orange/red coloring and decreased fruit growth, when control tobacco rattle virus 2 (TRV2)-myc fruits reached the mature green stage. TORC-deficient fruits showed early accumulation of carotenoid lycopene and reduced cellulose deposition in pericarp cell walls. The early ripening fruits had higher levels of transcripts related to fruit ripening transcription factors, ethylene biosynthesis, carotenoid synthesis, and cell wall modification. Finally, the early ripening phenotype in Micro-Tom tomato was reproduced in the commercial cultivar Moneymaker tomato by VIGS of the TORC genes. Collectively, these results demonstrate that TORC plays an important role in tomato fruit ripening by modulating the transcription of various ripening-related genes.

Metabolomic Variability of Different Soybean Genotypes: ß-Carotene-Enhanced (Glycine max), Wild (Glycine soja), and Hybrid (Glycine max × Glycine soja) Soybeans.

We obtained a new hybrid soybean (Hybrid) by hybridizing ß-carotene-enhanced soybean (BCE; Glycine max L.) containing the phytoene synthase-2A-carotene desaturase gene and wild-type soybean (Wild; Glycine soja). To investigate metabolic changes between variants, we performed metabolic profiling of leaves (three growth stages) and seeds. Multivariate analyses revealed significant metabolic differences between genotypes in seeds and leaves, with seeds showing accumulation of phytosterols, tocopherols, and carotenoids (BCE only), indicating co-induction of the methylerythritol 4-phosphate and mevalonic acid pathways. Additionally, Hybrid produced intermediate levels of carotenoids and high levels of amino acids. Principal component analysis revealed metabolic discrimination between growth stages of soybean leaves and identified differences in leaf groups according to different genotypes at 8, 12, and 16 weeks, with Wild showing higher levels of environmental stress-related compounds relative to BCE and Hybrid leaves. The metabolic profiling approach could be a useful tool to identify metabolic links in various soybean cultivars.