Metabolomic Responses of Maize Shoots and Roots Elicited by Combinatorial Seed Treatments With Microbial and Non-microbial Biostimulants

Abstract

Microbial and non-microbial plant biostimulants have been successfully used to improve agriculture productivity in a more sustainable manner. Since the mode of action of biostimulants is still largely unknown, the present work aimed at elucidating the morpho-physiological and metabolomic changes occurring in maize (Zea mays L.) leaves and roots following seed treatment with (i) a consortium of two beneficial fungi [arbuscular mycorrhizal fungi (AMF) and Trichoderma koningii TK7] and rhizobacteria, (ii) a protein hydrolyzate-based biostimulant (PH) alone, or (iii) in combination with a consortium of T. koningii TK7 and rhizobacteria. The application of PH alone or in combination with Trichoderma elicited significant increases (+16.6%) in the shoot biomass compared to untreated maize plants, whereas inoculation with AMF + Trichoderma elicited significant increases in root dry biomass (+48.0%) compared to untreated plants. Distinctive metabolomic signatures were achieved from the different treatments, hence suggesting that different molecular processes were involved in the plants response to the biostimulants. The metabolic reprogramming triggered by the treatments including the protein hydrolyzate was hierarchically more pronounced than the application of microorganisms alone. Most of the differential metabolites could be ascribed to the secondary metabolism, with phenylpropanoids and terpenes being the most represented compounds. The application of PH triggered an accumulation of secondary metabolites, whereas the opposite trend of accumulation was seen in the case of microorganisms alone. The increase in biomass could be related to two processes, namely the modulation of the multilayer phytohormone interaction network and a possible increase in nitrogen use efficiency via the GS-GOGAT system.

Keywords: Trichoderma; Zea mays L.; mycorrhiza; phytohormones; plant metabolomics; protein hydrolyzate.

FIGURE 1

Unsupervised hierarchical cluster analysis carried out from UHPLC-ESI/QTOF-MS metabolomic analysis of leaves (A) and roots (B) of maize plants treated with a consortium of arbuscular mycorrhizal fungi (AMF), Trichoderma koningii TK7, and rhizosphere bacteria or with a consortium of Trichoderma koningii TK7 and rhizosphere bacteria (Tricho) plus a protein hydrolyzate-based biostimulant (PH), or with a protein hydrolyzate-based biostimulant (PH). The fold-change based heat map was used to build hierarchical clusters (linkage rule: Ward; distance: Euclidean).

FIGURE 2

Orthogonal projection to latent structures discriminant analysis (OPLS-DA) supervised modeling of leaves (A) and roots (B) of maize plants treated with a consortium of arbuscular mycorrhizal fungi (AMF), Trichoderma koningii TK7, and rhizosphere bacteria or with a consortium of Trichoderma koningii TK7 and rhizosphere bacteria (Tricho) plus a protein hydrolyzate-based biostimulant (PH), or with a protein hydrolyzate-based biostimulant (PH). The metabolomic dataset produced through UHPLC-ESI/QTOF-MS was Pareto scaled and then used for the multivariate OPLS-DA modeling.

FIGURE 3

Biosynthesis processes which take place in leaves of maize plants treated with a consortium of arbuscular mycorrhizal fungi (AMF), Trichoderma koningii TK7, and rhizosphere bacteria or with a consortium of Trichoderma koningii TK7 and rhizosphere bacteria (Tricho) plus a protein hydrolyzate-based biostimulant (PH), or with a protein hydrolyzate-based biostimulant (PH). The metabolomic dataset produced through UHPLC-ESI/QTOF-MS was subjected to a Volcano Plot analysis (P < 0.01, fold-change > 1.2) and differential metabolites were loaded into PlantCyc Pathway Tool (https://www.plantcyc.org/). The x-axis represents each set of subcategories while the y-axis corresponds to the cumulative fold-change.

FIGURE 4

Biosynthesis processes which take place in roots of maize plants treated with a consortium of arbuscular mycorrhizal fungi (AMF), Trichoderma koningii TK7, and rhizosphere bacteria or with a consortium of Trichoderma koningii TK7 and rhizosphere bacteria (Tricho) plus a protein hydrolyzate-based biostimulant (PH), or with a protein hydrolyzate-based biostimulant (PH). The metabolomic dataset produced through UHPLC-ESI/QTOF-MS was subjected to a Volcano Plot analysis (P < 0.01, fold-change > 1.2) and differential metabolites were loaded into PlantCyc Pathway Tool (https://www.plantcyc.org/). The x-axis represents each set of subcategories while the y-axis corresponds to the cumulative fold-change.