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. 2020 Sep 2;21(17):6381.
doi: 10.3390/ijms21176381.

The Metabolic Reprogramming Induced by Sub-Optimal Nutritional and Light Inputs in Soilless Cultivated Green and Red Butterhead Lettuce

Begoña Miras-Moreno  1 , Giandomenico Corrado  2 , Leilei Zhang  1 , Biancamaria Senizza  1 , Laura Righetti  3 , Renato Bruni  3 , Christophe El-Nakhel  2 , Maria Isabella Sifola  2 , Antonio Pannico  2 , Stefania De Pascale  2 , Youssef Rouphael  2 , Luigi Lucini  1   4
Affiliations

The Metabolic Reprogramming Induced by Sub-Optimal Nutritional and Light Inputs in Soilless Cultivated Green and Red Butterhead Lettuce

Begoña Miras-Moreno et al. Int J Mol Sci. .

Abstract

Sub-optimal growing conditions have a major effect on plants; therefore, large efforts are devoted to maximizing the availability of agricultural inputs to crops. To increase the sustainable use of non-renewable inputs, attention is currently given to the study of plants under non-optimal conditions. In this work, we investigated the impact of sub-optimal macrocations availability and light intensity in two lettuce varieties that differ for the accumulation of secondary metabolites (i.e., 'Red Salanova' and 'Green Salanova'). Photosynthesis-related measurements and untargeted metabolomics were used to identify responses and pathways involved in stress resilience. The pigmented ('Red') and the non-pigmented ('Green Salanova') lettuce exhibited distinctive responses to sub-optimal conditions. The cultivar specific metabolomic signatures comprised a broad modulation of metabolism, including secondary metabolites, phytohormones, and membrane lipids signaling cascade. Several stress-related metabolites were altered by either treatment, including polyamines (and other nitrogen-containing compounds), phenylpropanoids, and lipids. The metabolomics and physiological response to macrocations availability and light intensity also implies that the effects of low-input sustainable farming systems should be evaluated considering a range of cultivar-specific positive and disadvantageous metabolic effects in addition to yield and other socio-economic parameters.

Keywords: Lactuca sativa; light intensity; macrocations; metabolomics; sub-optimal response.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Score plot of orthogonal projection to latent structures discriminant analysis (OPLS-DA) supervised modeling carried out on untargeted metabolomics profiles of ‘Red’ (A) (R2Y = 0.99, Q2Y = 0.91) and ‘Green Salanova’ (B) (R2Y = 0.97, Q2Y = 0.69) subjected to different nutrient solutions.
Figure 2
Figure 2
Processes affected by the macrocation concentration in ‘Red’ (A) and ‘Green Salanova’ (B). Differential metabolites and their fold-change (FC) values were elaborated using the Omic Viewer Dashboard of the PlantCyc pathway Tool software (www.pmn.plantcyc.com). In each class, the large dot represents the average (mean) logFC of the metabolites. Small dots represent the individual logFC for each metabolite. The abbreviated subcategory names on the x-axis correspond to: Nucleo: nucleosides and nucleotides; FA/Lipids: fatty acids and lipids; Amines: amines and polyamines; Carbohyd: carbohydrates; Cofactors: cofactors, prosthetic groups, electron carriers, and vitamins.
Figure 3
Figure 3
Score plot of OPLS-DA supervised modeling carried out on untargeted metabolomics profiles of ‘Red’ (A) (R2Y = 0.99, Q2Y = 0.92) and ‘Green’ (B) (R2Y = 1, Q2Y = 0.92) Salanova under optimal and sub-optimal light conditions.
Figure 4
Figure 4
Processes affected by the light intensity in ‘Red’ (A) and ‘Green Salanova’ (B). Differential metabolites and their fold-change (FC) values were elaborated using the Omic Viewer Dashboard of the PlantCyc pathway Tool software (www.pmn.plantcyc.com). In each class, the large dot represents the average (mean) logFC of the metabolites. Small dots represent the individual logFC for each metabolite. The abbreviated subcategory names reported on the x-axis correspond to: Nucleo: nucleosides and nucleotides; FA/Lipids: fatty acids and lipids; Amines: amines and polyamines; Carbohyd: carbohydrates; Cofactors: cofactors, prosthetic groups, electron carriers and vitamins.
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