Comparative evaluation of two Fusarium oxysporum f. sp. lycopersici strains grown on two different carbon sources: LC-MS - based secretome study after in vivo 15N metabolic labeling

K. Wrobel,K. Wrobel,Bianey García Lara,Moises Guerrero Esperanza,M. Roncero,A. C. Escobosa

Published 2020 in International Journal of Mass Spectrometry

ABSTRACT

Abstract To get new insight on the pathogenicity of Fusarium oxysporum f. sp. lycopersici, metabolic labeling was performed, and secretomes of the wild type strain 4287 (W) and non-virulent mutant ΔchsV (M) were compared while switching the main carbon source from glucose (Glc) to the freeze-dried vascular tomato tissue (VTT). 14N- or 15N-containing KNO3 was used for fungal growth and two combined (14N/15N) protein extracts were obtained: 1- W + M in Glc; 2- W + M in VTT. Trypsin digests of 1 and 2 were analyzed by capHPLC-ESI-QTOF-MS and Skyline was applied to compare the abundances of individual proteins between two strains in each sample and between the samples. Protein grouping was suggested as follows: (1) seven proteins apparently adsorbing on VTT were of importance during the initial stage of invasion; (2) three adsorbing on VTT were involved in compensative mutant adjustment, in growth and nutrients supply; (3) eleven might contribute in pathogenicity without direct interaction with the plant cell wall; (4) fourteen were involved in mutant adaptation, fungal growth and nutrients supply, not excluding their role in pathogenicity. The above proteins comprised carbohydrate-active enzymes, protein/peptide- and lipid-hydrolyzing enzymes, few classified as effectors (NEP-like, serine protease, GLEYA adhesion domain, LysM domain), catalyzing redox processes and few of unknown function.

PUBLICATION RECORD

  • Publication year

    2020

  • Venue

    International Journal of Mass Spectrometry

  • Publication date

    2020-03-01

  • Fields of study

    Biology, Chemistry, Environmental Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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