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      Approach strategies and application of metabolomics to biotechnology in plants

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          Abstract

          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.

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          Humans heavily rely on dozens of domesticated plant species that have been further improved through intensive breeding. To evaluate how breeding changed the tomato fruit metabolome, we have generated and analyzed a dataset encompassing genomes, transcriptomes, and metabolomes from hundreds of tomato genotypes. The combined results illustrate how breeding globally altered fruit metabolite content. Selection for alleles of genes associated with larger fruits altered metabolite profiles as a consequence of linkage with nearby genes. Selection of five major loci reduced the accumulation of anti-nutritional steroidal glycoalkaloids in ripened fruits, rendering the fruit more edible. Breeding for pink tomatoes modified the content of over 100 metabolites. The introgression of resistance genes from wild relatives in cultivars also resulted in major and unexpected metabolic changes. The study reveals a multi-omics view of the metabolic breeding history of tomato, as well as provides insights into metabolome-assisted breeding and plant biology.
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            Points of Significance: Principal component analysis

            PCA helps you interpret your data, but it will not always find the important patterns.
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              NMR Spectroscopy for Metabolomics Research

              Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                11 August 2023
                2023
                : 14
                : 1192235
                Affiliations
                [1] Division of Biosafety, National Institute of Agricultural Sciences, Rural Development Administration , Jeonju, Jeollabuk-do, Republic of Korea
                Author notes

                Edited by: Sehrish Manan, Jiangsu University, China

                Reviewed by: Dan-Dan Zhao, Crop Foundation Research Division, National Institute of Crop Science, Rural Development Administration, Republic of Korea; Kirk L. Pappan, GeneCentric Therapeutics, Inc., United States

                *Correspondence: Seon-Woo Oh, ohsw0507@ 123456korea.kr

                †These authors have contributed equally to this work

                Article
                10.3389/fpls.2023.1192235
                10451086
                37636096
                8e9a15c1-fa6c-48cd-8dd0-59b3b33c6711
                Copyright © 2023 Oh, Imran, Kim, Park, Lee, Park, Jung and Ryu

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 23 March 2023
                : 24 July 2023
                Page count
                Figures: 4, Tables: 5, Equations: 0, References: 100, Pages: 17, Words: 9295
                Funding
                Funded by: Rural Development Administration , doi 10.13039/501100003627;
                This study was funded by the 2023 Research and Development Program of the Rural Development Administration (No: PJ0160972023).
                Categories
                Plant Science
                Review
                Custom metadata
                Plant Metabolism and Chemodiversity

                Plant science & Botany
                metabolomics,plants biotechnology,analytics,analytical instruments,safety assessment

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