Mass Spectrometry Imaging for Spatial Chemical Profiling of Vegetative Parts of Plants

Abstract

The detection of chemical species and understanding their respective localisations in tissues have important implications in plant science. The conventional methods for imaging spatial localisation of chemical species are often restricted by the number of species that can be identified and is mostly done in a targeted manner. Mass spectrometry imaging combines the ability of traditional mass spectrometry to detect numerous chemical species in a sample with their spatial localisation information by analysing the specimen in a 2D manner. This article details the popular mass spectrometry imaging methodologies which are widely pursued along with their respective sample preparation and the data analysis methods that are commonly used. We also review the advancements through the years in the usage of the technique for the spatial profiling of endogenous metabolites, detection of xenobiotic agrochemicals and disease detection in plants. As an actively pursued area of research, we also address the hurdles in the analysis of plant tissues, the future scopes and an integrated approach to analyse samples combining different mass spectrometry imaging methods to obtain the most information from a sample of interest.

Keywords: chemical imaging; mass spectrometry; plant.

Figure 1

General workflow in an MSI experiment of plant tissues. A suitable sample (for example, a leaf section) from a plant is collected and prepared. With the aid of MS instruments such as MALDI, DESI, SIMS and LAESI with varying ionisation sources, the surface can be mapped for the constituent chemicals. The mass spectra obtained from each point in the sample along with the positional information can be used to create several ion images showing localisation for numerous chemicals of interest from a single scan.

Figure 2

Quantification of glucosinolates on the surface of A. thaliana leaves. For the quantification study with MALDI-MSI: (a) A solution of internal standard (2-propenylglucosinolate) was mixed with a fluorescent dye and transferred with a pin array spotter to the leaf surface; (b) The quality of spotting was checked by a fluorescence scan; (c) The spotted leaves were covered with 9-aminoacridine matrix by sublimation and measured by MALDI-TOF mass spectrometry in the negative mode; (d) Collected data were analysed with Biomap software. Figure reproduced with permission from Shroff et al. [79].

Figure 3

Cross-sections of ginkgo leaves imaged in positive mode MALDI showing images of selected flavonoid ions, including aglycones (m/z 271.0601–317.0655), biflavonoids (m/z 539.0973– 583.1235), glycosides (m/z 617.1477–795.1745) and biginkgosides (m/z 1519.3537–1551.3435) in ginkgo leaf. Ion images were recorded with a step size of 50 μm. The mass accuracy was less than 2 ppm and a bin width of m/z = ±5 ppm was used for image generation. Images represent the protonated, sodium and potassium adducts of metabolites. Glc: glucoside/glucosyl moiety; K: kaempferol; Rha: rhamnoside/rhamnosyl moiety; Q: quercetin. Figure reproduced with permission from Li et al. [101].

Figure 4

DESI MS spectrum and images of barley leaf under different sample preparation conditions: (a) DESI MS spectrum of a barley leaf (cv Mentor) treated with chloroform; (b) DESI MS spectrum of the Teflon imprint of the leaf epidermis; (c) DESI MS spectrum of the Teflon imprint of the intact leaf. DESI images are of the hydroxynitrile glucosides of m/z = 276, 298 and 300 from barley (cv Mentor); (d) Direct DESI images of the isolated epidermis; (e) Indirect DESI images of the isolated epidermis; (f) Indirect DESI images of the intact leaf; (g) Photo of the transparent leaf epidermis mounted on double-sided tape. All spectra were recorded in positive ion mode. The pixel size is 100 μm and the acquisition times were 120 min. Figure has been adapted with permission from Li et al. [47].

Figure 5

LAESI 3D imaging MS of A.squarossa leaf tissue where metabolites in relation to tissue architecture captured. Optical image of A. squarrosa leaves (A) before and (B) after analysis; (C) LAESI 3D imaging MS distribution of kaempferol/luteolin with m/z 287.0 (yellow/orange scale) followed the variegation pattern. Chlorophyll a with m/z 893.5 (blue scale) accumulated in the mesophyll layers; (D) Acacetin with m/z 285.0 showed higher abundance in the yellow sectors of the second and third layers with a homogeneous distribution in the others; (E) Kaempferol-(diacetyl coumarylrhamnoside) with m/z 663.2 accumulated in the mesophyll layers (third and fourth) with uniform lateral distributions. Figure reproduced with permission from Nemes et al. [34].

Figure 6

Images obtained from the dimethoate experiment on Kalanhoe blossfeldiana to see root uptake: (a) DESI mass spectrum of protonated dimethoate and sodium adduct detected in spiked soil; (b) Optical image of Kalanchoe stem cross-section; (c) Enlarged area of stem section to improve visualisation of xylem and phloem area; (d–f) Distribution of dimethoate in the plant stem, detected as protonated species, sodium and potassium adduct; (g–i) DESI-MS images of different naturally occurring substances. Pixel size of the DESI-MSI experiment was set to 60 μm. Figure reproduced with permission from Gerbig et al. [133].

Figure 7

Images acquired for the various biomarkers identified for HLB disease with DESI MSI in positive ion mode. In the images acquired, the red colour indicates the ion distribution on the abaxial leaf surface in asymptomatic, symptomatic and healthy samples. The images acquired were at: (a) m/z 403; (b) m/z 166; (c) m/z 343 and (d) m/z 193, which were the exact masses found in Xcalibur software (m/z 403.1387, m/z 166.0863, m/z 343.1235, and m/z 193.0712) corresponding to nobiletin, phenylalanine, sucrose and quinic acid, respectively. Figure reproduced with permission from de Moraes Pontes et al. [48].