New plant breeding techniques and their regulatory implications: An opportunity to advance metabolomics approaches

The study discusses the importance of metabolomics techniques for the assessment of plants that have been altered by genome editing techniques. Metabolomics methods make it possible to analyze changes in metabolic products (= metabolites) in cells.

Explanation of some biological principles
The DNA of higher living beings is located in the cell nucleus and contains the genetic information for all proteins that an organism can produce. Firstly, a gene in the genome must be expressed, generating the corresponding messenger RNA (mRNA). The mRNA carries the genetic information for the construction of a certain protein. Thus, the mRNA is translated into the relevant protein. Proteins have a variety of tasks in the cells and are involved in the production of various metabolic products that are required, for example, as messenger substances, as components of the cell wall or in cell metabolism.

Omics techniques
There are a number of techniques that can be used to analyze the different molecular levels of a cell:

  1. Analysis methods that can examine the entire DNA sequence of an organism, for example, by genome sequencing, are collectively known as genomics.
  2. Transcriptomics is a term used to signify different analysis methods with which the composition of all the RNA molecules of a cell can be determined at a certain point in time.
  3. Proteomics are analysis methods of all proteins present in a cell at a specific point in time. Proteomics include techniques of mass spectrometry.
  4. Metabolomics include analysis methods with which the composition of the metabolic products of a cell can be analyzed.

The analytical methods referred to above are known collectively as omics. These methods have the potential to elucidate the complex interaction networks within a cell. In addition, methods for analyzing the epigenome, i.e. the totality of all epigenetic markers and methods to decipher the composition of the microbiome of an organism, are often counted among the omics.

Focus: Metabolomics
This study focusses on the methods of metabolomics. Metabolic products such as sugars, fatty acids, amino acids, alcohols, etc. are diverse and occur in different amounts within an organism. Metabolomics methods must overcome significant analytical challenges, for example, in order to investigate the composition and the amount of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy (NMR) methods are mainly used for this purpose.

Metabolomics for the analysis of genome-edited plants
The analysis of the metabolome of plants has gained in importance in recent years, but further development of these methods has not occurred to the extent that was, for example, the case with genomics. The metabolome represents the composition of the constituents of a plant and is still detectable in food and feed, whereas the composition of the DNA and proteins can be incomplete. Metabolomics are therefore promising methods for comparative studies of unchanged and genome-edited plants and their products. In a previous study, it was already suggested that metabolomics methods could be used to analyze and, if necessary, detect genome-edited plants, even if only small changes in the genome were caused by SDN-1 applications (see Fraser et al., 2020).
A metabolomics analysis can resolve the composition of precursor molecules, intermediates, end products and their derivatives in many different metabolic pathways. The more information is known about the changed metabolic pathway(s), the easier and more targeted it is to analyze the composition of the metabolites and, if necessary, provide for the detection of certain metabolic products. If, for example, the fatty acid biosynthesis is altered and an enzyme for the formation of a certain fatty acid is knocked out, the composition of all cellular lipids can be examined with the help of so-called lipidomics methods. If it is not known which target gene and thus which metabolic pathway has been affected, an untargeted metabolomics study needs to be carried out that is not designed for a specific metabolite type. The analysis is broader, but less extensive in the various types of metabolites (e.g. fats, sugars, amino acids, etc.). The study emphasizes that the further development of the metabolic methods must progress to a point where they might be used to detect genome edited plants.
The authors refer to a study by Zsogon et al, 2018, in which a genome-edited tomato was presented that had been altered by CRISPR/Cas in several different regions of the genome. This application of the gene scissors is also known as multiplexing. As a starting point, a wild tomato species was used, which was then to be adapted to modern breeding successes. This approach is also known as de novo domestication. The intention is to preserve the positive properties of wild species, such as certain resistances, and to adapt them to the demands of modern consumers. The authors cite this genome-edited tomato as an informative example that could be studied using metabolomics techniques to compare the genome-edited plant with its native wild form and other modern varieties. However, Enfissi et al, 2021, only discuss the benefits of using metabolomics to analyze genome edited plants and make suggestions for experimental pipelines. No results from metabolomics analyzes on genome-edited plants are presented in this study.

Enfissi EMA, Drapal M, Perez-Fons L, Nogueira M, Berry HM, Almeida J, Fraser PD (2021) New plant breeding techniques and their regulatory implications: An opportunity to advance metabolomics approaches. Journal of Plant Physiology 258-259:153378. doi:
Fraser PD, Aharoni A, Hall RD, Huang S, Giovannoni JJ, Sonnewald U, Fernie AR (2020) Metabolomics should be deployed in the identification and characterization of gene-edited crops. Plant J. doi:10.1111/tpj.14679
Zsogon A, Cermak T, Naves ER, Notini MM, Edel KH, Weinl S, Freschi L, Voytas DF, Kudla J, Peres LEP (2018) De novo domestication of wild tomato using genome editing. Nat Biotechnol 36:1211-1216. doi:10.1038/nbt.4272