Iron toxicity-induced physiological and metabolite profile variations among tolerant and sensitive rice varieties

Figures & data

Figure 1. The effect of Fe toxicity stress on growth rate (a–b), leaf bronzing score (c), chlorophyll content (d), and malondialdehyde (MDA) (e–f) in four rice varieties. Bars represent standard error. Control = 0 ppm FeSO₄^.7H₂O; Fe = 400 ppm FeSO₄^.7H₂O.

Figure 2. The comparison of metabolite in each vegetative organ (a) and each variety (b) under control and Fe toxicity stress. 0 ppm = control; 400 ppm = Fe toxicity stress.

Figure 3. The comparison of metabolite composition of roots and shoots based on its compound group. The categorization based on various databases, i.e. PubChem (https://pubchem.ncbi.nlm.nih.gov/), KEGG Pathway (https://www.genome.jp/kegg/pathway.html), HMDB (http://www.hmdb.ca/), LIPID MAPS (http://lipidmaps.org/data/structure/LMSDSearch.php), CAMEO (https://cameochemicals.noaa.gov/search/simple), ChemSpider (http://www.chemspider.com/).

Figure 4. Heatmap analysis combined with hierarchical clustering analysis of metabolites in the roots of rice under control and Fe toxicity stress. Analysis using normalized data with mean-centered via http://www.metaboanalyst.ca. 0 = 0 ppm (control); 400 = 400 ppm FeSO₄^.7H₂O.

Figure 5. Heatmap analysis combined with hierarchical clustering analysis of metabolites in the shoots of rice under control and Fe toxicity stress. Analysis using normalized data with mean-centered via http://www.metaboanalyst.ca. 0 = 0 ppm (control); 400 = 400 ppm FeSO₄^.7H₂O.

Table 1. Partial least-squares discriminant analysis (PLS-DA) parameter as distinguishing between control and Fe toxicity stress condition in four rice varieties based on their metabolite profile.

Tissues	Varieties	PLS-DA parameter
		Component^a	Q^2	R^2	Q^2/R^2
Root	IR64	3	0.93	1.00	0.93
	Inpara 5	2	0.42	0.98	0.43
	Inpara 2	1	0.68	0.91	0.75
	Pokkali	1	0.95	0.98	0.97
Shoot	IR64	2	0.98	1.00	0.98
	Inpara 5	1	0.96	1.00	0.97
	Inpara 2	4	0.99	1.00	0.99
	Pokkali	2	0.95	1.00	0.95

Q² = predictive capability of model; R² = correlation coefficient of model; ^aThe value in component column based on the best classifier of Q² value to classify the sample using leave-one-out cross-validation (LOOCV).

Figure 6. The difference of tolerance level of rice based on their metabolite profile in shoot (a), root (b), and each variety (c). The analyses were performed by principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). 0 ppm = control; 400 ppm = Fe toxicity stress.

Table 2. The significant level of each selected metabolites to the given treatments.

Tissues	Metabolites	Group	p-Value^a
Root	1-Chloroheptacosane	Unknown	2.3E-03
	8-2-Octylcyclopropyloctanal	Fatty aldehydes	9.5E-03
	9-Icosyne	Hydrocarbons	2.6E-21
	E,E-2,13-Octadecadien-1-ol	Fatty alcohols	6.3E-04
	Elaidic Acid	Fatty acids	9.6E-04
	Linoelaidic acid	Fatty acids	1.1E-04
	Linoleic acid	Fatty acids	1.0E-04
	Linolelaidic acid ethyl ester	Fatty esters	1.2E-02
	Nonacosane	Hydrocarbons	1.6E-02
	Palmitic acid	Fatty acids	1.5E-01
Shoot	1-Hexacosene	Hydrocarbons	6.9E-21
	2-Diethylamino naphtho 2,3-b furan-4,9-dione	Carboxylic acid	1.3E-26
	2-Nonanone	Oxygenated hydrocarbons	6.6E-27
	2-Tridecanone	Oxygenated hydrocarbons	1.3E-15
	4-Cyclohexyleicosane	Hydrocarbons	2.9E-23
	5-Hydroxymethyl furan-2-carbaldehyde	Unknown	9.4E-22
	Ethyl oleate	Fatty esters	2.2E-24
	Linoelaidic acid	Fatty acids	4.2E-21
	Linolenic acid	Fatty acids	6.1E-06
	Methapyrilene	Amine, organosulfide	3.2E-26
	Methyl 2,4,6,8-tetramethyl-13-tetradecenoate	Fatty esters	4.1E-26
	Phytol	Isoprenoids	2.6E-04

^ap-Value < 0.05 showed a significant effect of given treatments and rice varieties according to Duncan’s Multiple Range Test.

Table 3. Pathway analysis between tissues and rice varieties based on the selected metabolites to the given treatments.

Tissues	Metabolism pathway	Total^a	Hits^b	Metabolites	Raw P
Root	Fatty acid biosynthesis	47	2	Elaidic acid and palmitic acid	0.010
	Linoleic acid metabolism	5	1	Linoleic acid	0.017
	Fatty acid elongation in mitochondria	13	1	Palmitic acid	0.045
	Fatty acid metabolism	37	1	Palmitic acid	0.124
Shoot	Alpha-Linolenic acid metabolism	18	1	Linolenic acid	0.047

^aTotal indicated as metabolite number which involved on the metabolism pathway; ^bHits indicated as detected metabolites number based on this present study; ^cRaw P indicated as a significant level of mapped metabolites on the metabolism pathway based on the Fisher’s exact test using pathway analysis module in the http://www.metaboanalyst.ca.

Figure 7. The comparison of elaidic acid in root (a), linoleic acid in root (b), and linolenic acid in shoot (c) between control and Fe toxicity stress. 0 ppm = control; 400 ppm = Fe toxicity stress. Bars represent standard error.

Figure 8. The correlation analysis between morpho-physiological responses and fatty acid (elaidic-, linoleic-, and linolenic acid) concentration in control (a) and Fe toxicity stress (b). RRGR = root growth rate; MDAR = MDA concentration in root; SRGR = shoot growth rate; CHL = chlorophyll; MDAS = MDA concentration in shoot; LBS10 = leaf bronzing score 10 d after treatment; LINOLEIC_R = linoleic acid concentration in root; ELAIDIC_R = elaidic acid concentration in root; LINOLENIC_S = linolenic acid concentration in shoot.