Probing the Response of the Amphibious Plant Butomus umbellatus to Nutrient Enrichment and Shading by Integrating Eco-Physiological With Metabolomic Analyses

Abstract

Amphibious plants, living in land-water ecotones, have to cope with challenging and continuously changing growth conditions in their habitats with respect to nutrient and light availability. They have thus evolved a variety of mechanisms to tolerate and adapt to these changes. Therefore, the study of these plants is a major area of ecophysiology and environmental ecological research. However, our understanding of their capacity for physiological adaptation and tolerance remains limited and requires systemic approaches for comprehensive analyses. To this end, in this study, we have conducted a mesocosm experiment to analyze the response of Butomus umbellatus, a common amphibious species in Denmark, to nutrient enrichment and shading. Our study follows a systematic integration of morphological (including plant height, leaf number, and biomass accumulation), ecophysiological (photosynthesis-irradiance responses, leaf pigment content, and C and N content in plant organs), and leaf metabolomic measurements using gas chromatography-mass spectrometry (39 mainly primary metabolites), based on bioinformatic methods. No studies of this type have been previously reported for this plant species. We observed that B. umbellatus responds to nutrient enrichment and light reduction through different mechanisms and were able to identify its nutrient enrichment acclimation threshold within the applied nutrient gradient. Up to that threshold, the morpho-physiological response to nutrient enrichment was profound, indicating fast-growing trends (higher growth rates and biomass accumulation), but only few parameters changed significantly from light to shade [specific leaf area (SLA); quantum yield (φ)]. Metabolomic analysis supported the morpho-physiological results regarding nutrient overloading, indicating also subtle changes due to shading not directly apparent in the other measurements. The combined profile analysis revealed leaf metabolite and morpho-physiological parameter associations. In this context, leaf lactate, currently of uncertain role in higher plants, emerged as a shading acclimation biomarker, along with SLA and φ. The study enhances both the ecophysiology methodological toolbox and our knowledge of the adaptive capacity of amphibious species. It demonstrates that the educated combination of physiological with metabolomic measurements using bioinformatic approaches is a promising approach for ecophysiology research, enabling the elucidation of discriminatory metabolic shifts to be used for early diagnosis and even prognosis of natural ecosystem responses to climate change.

Keywords: Butomus umbellatus; abiotic plant stresses; amphibious plants; eco-metabolomics; ecophysiology; nutrient enrichment; shading effect; systems biology.

Figure 1

Scatter (XY) plots plots with standard deviation (±SD) of the mean (A) below-ground biomass and (B) above-ground biomass, (C) plant height, and (D) relative growth rate (RGR) at the various nutrient levels and light regimes. NL, nutrient level; DW, dry weight. Filled black circles, shade treatments; gray open circles, open treatments. SD estimated over n = 3 mesocosms per treatment.

Figure 2

Scatter (XY) plots plots with standard deviation (± SD) of the mean (A) light-saturated photosynthesis rate, P_max; (B) quantum yield, φ; (C) dark respiration, Rd; and (D) light saturation point, Ik at the various nutrient levels and light regimes; NL, nutrient level. Black filled circles, shade treatments; gray open circles, open treatments. SD estimated over n = 3 mesocosms per treatment.

Figure 3

Principal component analysis (PCA) graph of the standardized leaf metabolic profiles at NL1, NL4, and NL5 for both light regimes. A large difference is observed in the metabolic profiles of NL4 and NL5 with respect to NL1 in both light regimes (manifested on PC1 axis), while the distinction between the profiles of the shade and open treated samples is apparent on PC2.

Figure 4

Hierarchical clustering analysis (HCL) heat map of the standardized leaf combined profiles at NL1, NL4, and NL5 for both light regimes. The colored vertical bars indicate clusters of parameters/metabolites with similar profiles over the investigated treatments. Pearson correlation coefficient distance metric was used. Negative (colored in shades of green) or positive (colored in shades of red) standardized value indicates that a parameter/metabolite is of lower or higher, respectively, value/abundance at the particular treatment compared to its mean value over all treatments. The image has been created in and saved from TM4 MeV software.

Figure 5

Τhe clusters of morpho-physiological factors and metabolites identified by k-means clustering of the standardized combined profiles at NL1, NL4, and NL5 for both light regimes.. The mean profile in every cluster is shown in purple. Euclidean distance metric was used. Cluster numbers and colors refer to the corresponding HCL-identified in Figure 4. The image has been created in and saved from TM4 MeV software.

Figure 6

Morpho-physiological parameters and metabolite abundances identified as significantly changing in the shade versus the open treatments. Results are based on significance analysis for microarrays (SAM), and the parameters are clustered based on their profile through all treatments. The indication POS or NEG next to the name of each parameter/metabolite differentiates, respectively, the positively from the negatively significant in the shade compared to the open treatments; the number depicts the significance hierarchy of each parameter/metabolite in its respective group..