Semi-targeted UPLC-MS analysisof phenylpropanoids in Arabidopsis

Jiří Grúz, LGR

Why phenylpropanoids?

- they affect growth, development and reproduction (Huang et al., 2010)

Why phenylpropanoids?

- they may be involved in cell proliferation and differentiation (Tamagnone et al., 1998; Tsukagoshi et al., 2011)

- they are induced by cytokinins (Deikman et al., 1995)

Semi-targeted analysis (vs. targeted)

Pros

- fast analysis of all detectable metabolites in a simple run

- effective selection of metabolites which account for the most

variability in the dataset

- most suitable for abundant compounds, such as

phenylpropanoids

Cons

- low sensitivity with many instrumentations

- complicated use of internal standards

- more technical replicates needed (pooled samples), lower column

lifetime

- challenging data processing

Semi-targeted UPLC analysis

Biological replicates

Pooled samples

Extraction

Randomiz., UPLC-MS

Data filtering,chromatogram building

& deconvolutionpeak detection & alignment

Raw data export

Data export

Statistical software,multivariate analysis (MVA)

CRITICAL!

3D chromatogram in ESI(-) mode

Differential analysis of WT vs. pal1 by

UPLC-MS

0

5

10

15

20

25

WT pal2 pal1

*

***

OR

AC

(μ

mol

trol

ox e

quiv

alen

ts g

FW

)-1

A) B)

Fig. 1 (A) Flowering phenotypes of wild-type and pal mutant plants of Arabidopsis thaliana. (B) Oxygen radical absorbance capacity (ORAC) of wild-type and pal mutant plants. Bars represent the means (±SE) of ten individual plants. Asterisks indicate significant differences between wild-type (WT) and pal-mutants as determined by Student’s t test (* P<0.05, *** P<0.001).

Flowering phenotypes of Col wild-type (WT) and pal mutant plants of Arabidopsis thaliana grown at low density (300 plants m-2). Plants were grown under SD and photos were taken 35 days after sowing.

Looking for compounds which acount for the most variability

Kaempferol--Rham-Glc

Kaempferol--Rham-Glc-Rham

Kaempferol--Coum-Rham-Rham

Looking for compounds which acount for the most variability

What is it useful for?

- to compare “all” metabolites in various genotypes or treatments

- to find compounds which are affected the most

- to identify and quantify interesting candidates

Thank you