High-resolution metabolic mapping of cell types in plant roots

Abstract

Metabolite composition offers a powerful tool for understanding gene function and regulatory processes. However, metabolomics studies on multicellular organisms have thus far been performed primarily on whole organisms, organs, or cell lines, losing information about individual cell types within a tissue. With the goal of profiling metabolite content in different cell populations within an organ, we used FACS to dissect GFP-marked cells from Arabidopsis roots for metabolomics analysis. Here, we present the metabolic profiles obtained from five GFP-tagged lines representing core cell types in the root. Fifty metabolites were putatively identified, with the most prominent groups being glucosinolates, phenylpropanoids, and dipeptides, the latter of which is not yet explored in roots. The mRNA expression of enzymes or regulators in the corresponding biosynthetic pathways was compared with the relative metabolite abundance. Positive correlations suggest that the rate-limiting steps in biosynthesis of glucosinolates in the root are oxidative modifications of side chains. The current study presents a work flow for metabolomics analyses of cell-type populations.

Fig. 1.

Work flow for cell type-specific metabolite mapping in Arabidopsis roots. Following sample preparation and isolation of cells belonging to a particular cell type, cells are extracted and used for metabolomics assays by means of high-resolution MS. The third phase includes various data analysis steps in which robust mass signals and the corresponding putatively identified metabolites are extracted and used to generate metabolic profiles across different cell types.

Fig. 2.

Metabolic profiles of specific cell types in the Arabidopsis roots. (A) Representative UPLC-qTOF-MS total ion current (TIC) chromatograms of the five cell-type populations and a blank sample. The mass signal intensity is measured in values of ion current, and the y axes represent the relative peak abundances (%). The y axes of the cell population chromatograms are linked, and 100% abundance of each chromatogram corresponds to the TIC of 5⋅10⁴, to enable comparison of the different chromatograms. Selected GSLs are marked: (1) 4-methylthiobutyl GSL (4MTB; metabolite 25 in Table S1); (2) 8-methylsulfinyloctyl GSL (8MSOO; metabolite 27 in Table S1); (3) 4-methoxyindole I3M GSL (4MO-I3M: metabolite 31 in Table S1); (4) 7-methylthioheptyl GSL (7MTH; metabolite 33 in Table S1); and (5) 8-methylthio-octyl GSL (8MTO; metabolite 34 in Table S1). These nontargeted assays were carried out in core root cell populations from five GFP marker lines representing the following: endodermis, SCARECROW gene promoter; epidermis, WEREWOLF gene promoter; columella, PET111 line; cortex, CORTEX line; and stele, WOODEN LEG gene promoter. (B) Typical TIC chromatogram of an Arabidopsis whole-root extract (250 mg). This chromatogram has another y-scale, because it contains high-intensity signals, derived from a relatively much bigger sample.

Fig. 3.

Reproducibility of the cell-type metabolic profiling procedure. (A) Pearson correlation coefficient of robust masses of plant origin among replicates of all five cell-type populations is higher than 0.85 (pink, correlation >0.95; dark orange, correlation of 0.90–0.95; light orange, correlation of 0.85–0.90) (all correlations are shown in Fig. S5). (B) Principal component analysis (PCA) of robust masses (detected in the negative mode) derived from biological replicates of the different cell-type populations. The columella separates from other cell types on the PC2 component; however, this component represents 11.6% of the total variance, whereas the PC1 component represents 62.5%. (C) Scatterplot between different cell-type mass abundances (endodermis-epidermis comparison, dark blue), superimposed by a scatterplot of intrapopulation mass abundances (endodermis-endodermis comparison, pink). The high variability between the two groups is shown by the wider distribution of the blue dots, whereas a tight distribution is seen in the scatterplot of endodermis-endodermis mass intensities around the diagonal line.

Fig. 4.

Differential accumulation of all robust masses in the different cell types. (A) Global heat map of all robust mass signals obtained in the ESI (−) mode. Following quantile normalization (Methods), average ion mass intensities of sample replicates (logE-transformed) are presented as the ratio to the maximal intensity detected for each mass. The yellow line separates the cell layers and the whole-root samples. (B) Five representative clusters of the heat map provided in a greater detail. K-hex-deox, kaempferol hexose deoxyhexose (metabolite 46 in Table S1); Q-dideox, quercetin dideoxyhexose (metabolite 47 in Table S1); Q-O-dihex-O-deox, quercetin-O-dihexose-O-deoxyhexose (metabolite 43 in Table S1); Q-deox-hex-deox, quercetin deoxyhexose-hexose-deoxyhexose (metabolite 44 in Table S1); 7MTH, 7-methylthioheptyl GSL (metabolite 33 in Table S1); I3M (metabolite 26 in Table S1); 3BZO (metabolite 30 in Table S1); 8MTO, 8-methylthio-octyl GSL (metabolite 34 in Table S1). (C) Relative accumulation of representative metabolites of the clusters shown in B. Bars represent SEs. Statistically significant differences are represented for all pairwise comparisons using a two-way ANOVA. Pairwise comparisons are as follows: a = cortex_columella, b = cortex_epidermis, c = cortex_stele, d = cortex_endodermis, e = columella_epidermis, f = columella_stele, g = columella_endodermis, h = epidermis_stele, I = epidermis_endodermis, and j = stele_endodermis. ***P < 0.001; **P < 0.01; *P < 0.05.

Fig. 5.

Abundance of GSLs in specific cell types is tightly coregulated with transcripts encoding side chain redox enzymes. (A–C) GSLs display three distinct patterns of accumulation as determined by k-means clustering, with a Pearson correlation coefficient greater than 0.91 in all three groups. Metabolite abundance is visualized as log₁₀, and error bars represent SD. The abundance of 4-methylsulfinylbutyl GSL (4MSOB; metabolite 24 in Table S1) could not be distinguished from that of the m/z = 420.05 fragment of 4-methylthiobutyl GSL (4MTB; metabolite 25 in Table S1). MSO, methylsulfonyloctyl GSL (metabolite 28 in Table S1). (D) Expression of GSL biosynthesis genes across the Arabidopsis root (9). Red, expressed in the five cell types examined; pink, not expressed in a root cell type examined for metabolite content; gray, not expressed in roots. Blue quadrangles indicate genes whose relative expression is highly correlated with the relative abundance of GSLs. 1MO-I3M, 1-methoxyindole I3M GSL; 3MSOP, 3-methylsulfinylpropyl GSL; 4MO-I3M, 4-methoxyindole I3M GSL; 4MSOB, 4-methylsulfinylbutyl GSL; 4MTB, 4-methylthiobutyl GSL; 5MSOP, 5-methylsulfinylpentyl GSL; 6MSOH, 6-methylsulfinylhexyl GSL; 7MSOH, 7-methylsulfinyl heptyl GSL; 7MTH, 7-methylthioheptyl GSL; 8MSOO, 8-methylsulfinyloctyl GSL; 8MTO, 8-methylthio-octyl GSL.

Fig. 6.

Phenylpropanoids (PP) are enriched in the cortex cell type. A scheme of the PP pathway with relative mRNA expression and metabolite accumulation in the core five cell types examined is shown. Gene expression (9) and metabolite accumulation are colored in representations of a root transverse section and a cut-away of a root tip. (A) Expression of flavonoid biosynthesis genes (log₂) is enriched in the cortex relative to other cell types. (B) The majority of PPs show maximal abundance (log₁₀) in the cortex relative to other cell types.

Fig. 7.

Dipeptides (DPs) are highly abundant in the root endodermis and epidermis cell types. Leu-Val (metabolite 10 in Table S1) and Val-Leu (metabolite 11 in Table S1) as well as Leu-Val (metabolite 13 in Table S1) and Val-Leu (metabolite 14 in Table S1) isomers are presented together, because their mass intensities could not be separated. Error bars represent SE (see correlation matrices for DPs in all cell types in Dataset S6).