High-spatial resolution mass spectrometry imaging reveals the genetically programmed, developmental modification of the distribution of thylakoid membrane lipids among individual cells of the maize leaf

Publication

Publication Type:

Journal Article

Source:

Plant J, Volume 89 (2017)

Abstract:

Metabolism in plants is compartmentalized among different tissues, cells and subcellular organelles. Mass spectrometry imaging (MSI) with matrix-assisted laser desorption ionization (MALDI) has recently advanced to allow for the visualization of metabolites at single-cell resolution. Here we applied 5- and 10 μm high spatial resolution MALDI-MSI to the asymmetric Kranz anatomy of Zea mays (maize) leaves to study the differential localization of two major anionic lipids in thylakoid membranes, sulfoquinovosyldiacylglycerols (SQDG) and phosphatidylglycerols (PG). The quantification and localization of SQDG and PG molecular species, among mesophyll (M) and bundle sheath (BS) cells, are compared across the leaf developmental gradient from four maize genotypes (the inbreds B73 and Mo17, and the reciprocal hybrids B73xMo17 and Mo17xB73). SQDG species are uniformly distributed in both photosynthetic cell types, regardless of leaf development or genotype; however, PG shows photosynthetic cell-specific differential localization depending on the genotype and the fatty acyl chain constituent. Overall, 16:1-containing PGs primarily contribute to the thylakoid membranes of M cells, whereas BS chloroplasts are mostly composed of 16:0-containing PGs. Furthermore, PG 32:0 shows genotype-specific differences in cellular distribution, with preferential localization in BS cells for B73, but more uniform distribution between BS and M cells in Mo17. Maternal inheritance is exhibited within the hybrids, such that the localization of PG 32:0 in B73xMo17 is similar to the distribution in the B73 parental inbred, whereas that of Mo17xB73 resembles the Mo17 parent. This study demonstrates the power of MALDI-MSI to reveal unprecedented insights on metabolic outcomes in multicellular organisms at single-cell resolution.