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Metabolic Aspects of Lentil- Fusarium Interactions.

Chrysanthi FotiAntonios ZambounisEvmorfia P BatakaChrysanthi KalloniatiEvangelia PanagiotakiChristos Theodoros NakasEmmanouil FlemetakisOurania I Pavli
Published in: Plants (Basel, Switzerland) (2024)
Fusarium oxysporum f. sp. lentis ( Fol ) is considered the most destructive disease for lentil ( Lens culinaris Medik.) worldwide. Despite the extensive studies elucidating plants' metabolic response to fungal agents, there is a knowledge gap in the biochemical mechanisms governing Fol -resistance in lentil. Τhis study aimed at comparatively evaluating the metabolic response of two lentil genotypes, with contrasting phenotypes for Fol -resistance, to Fol -inoculation. Apart from gaining insights into the metabolic reprogramming in response to Fol -inoculation, the study focused on discovering novel biomarkers to improve early selection for Fol -resistance. GC-MS-mediated metabolic profiling of leaves and roots was employed to monitor changes across genotypes and treatments as well as their interaction. In total, the analysis yielded 178 quantifiable compounds, of which the vast majority belonged to the groups of carbohydrates, amino acids, polyols and organic acids. Despite the magnitude of metabolic fluctuations in response to Fol -inoculation in both genotypes under study, significant alterations were noted in the content of 18 compounds, of which 10 and 8 compounds referred to roots and shoots, respectively. Overall data underline the crucial contribution of palatinitol and L-proline in the metabolic response of roots and shoots, respectively, thus offering possibilities for their exploitation as metabolic biomarkers for Fol -resistance in lentil. To the best of our knowledge, this is the first metabolomics-based approach to unraveling the effects of Fol -inoculation on lentil's metabolome, thus providing crucial information related to key aspects of lentil- Fol interaction. Future investigations in metabolic aspects of lentil- Fol interactions will undoubtedly revolutionize the search for metabolites underlying Fol -resistance, thus paving the way towards upgrading breeding efforts to combat fusarium wilt in lentil.
Keyphrases
  • healthcare
  • mass spectrometry
  • machine learning
  • deep learning
  • single cell
  • social media
  • big data