Label-free visualization of fruit lignification: Raman molecular imaging of loquat lignified cells

Abstract

BackgroundFlesh lignification, leading to increased fruit firmness, has been reported in several kinds of fruit. Understanding the mechanisms underlying fruit lignification is important to optimize the postharvest storage strategies and reduce the quality deterioration of postharvest fruit. Especially cellular level investigation of lignin deposition in fruits provides novel insight for deciphering the mechanisms underlying fruit lignification. The primary objective of this study was to establish a procedure of using Raman microspectroscopy technique to depict fruit lignification at the cell level.ResultsLignified cells, a special kind of cells contained high lignin content, were found abundantly scattered in red-fleshed ‘Luoyangqing’ loquat. Whereas these special lignified cells were barely detected in ‘Baisha’ loquat flesh. Dominant Raman bands of lignified cells were found primarily attributed to lignin (1664, 1628, 1603, 1467, and 1272 cm−1), cellulose (1383, 1124 and 1098 cm−1) and pectin (852 and 1740 cm−1). The band intensity correlation analysis indicated the peak at 1335 cm−1 assigned to either lignin or cellulose in previous works was related to lignin for the lignified cells. Multi-peaks Gaussian fitting successfully resolved the overlapped fingerprint peaks of lignin in 1550–1700 cm−1 into three independent peaks, which were assigned to different functional groups of lignin. Furthermore, the spatially resolved Raman images of lignified cells were generated, indicating that lignin and cellulose saturated the whole lignified cells, pectin mainly located in the cell corner, and the parenchyma cells contained little lignin. In addition, both phloroglucinol-HCl staining and autofluorescence analysis confirmed the results of lignin distribution of Raman microscopic analysis.ConclusionsA procedure for the simultaneous visualization of the main components of the flesh cells without labeling by high-resolution Raman microspectroscopy has been established. With Raman microscopic imaging technique, we can add a microscopic level to cell compositions, essential for a detailed molecular understanding of loquat lignification. Such method can be further used to chemically monitor the textural changes during the ripening process or postharvest storage of other fruits and vegetables.Electronic supplementary materialThe online version of this article (10.1186/s13007-018-0328-1) contains supplementary material, which is available to authorized users.

Hybrid Label-Free Molecular Microscopies for Simultaneous Visualization of Changes in Cell Wall Polysaccharides of Peach at Single- and Multiple-Cell Levels during Postharvest Storage

“…In addition, the RS characteristic bands of cellulose also included 1383 and 1480 cm −1 . The 1383 cm −1 band came from the HCH and HOC bending, and the 1480 cm −1 band was assigned to the HCC, HCO, and HOC bending [12]. The most significant characteristic bands of xyloglucan were assigned as the peaks centered at 757 cm −1 [9].…”

“…The methods of CRM hyperspectral imaging and the reference RS of the cellulose and pectin were performed according to our previous work [12]. A Renishaw inVia Reflex Raman Microscopy System (Renishaw Plc., Wotton-Under-Edge, UK) equipped with a 532 nm diode laser and an air-cooled charge-coupled device was used.…”

“…All the original RS data of the parenchymal cell wall of peach flesh were eliminated random noise by Savitzky-Golay [12] ( Figure S1a), and deduct the interference of the fluorescence background…”

“…All the original RS data of the parenchymal cell wall of peach flesh were eliminated random noise by Savitzky-Golay [12] ( Figure S1a), and deduct the interference of the fluorescence background to the RS analysis signal and achieve baseline correction by adaptive iteratively reweighted penalized least squares [31] ( Figure S1b). A typical RS profile of the parenchymal cell wall of peach flesh at 0 d is shown in Figure S2.…”

“…The combination of RS/IR and microscopy provides more detailed and robust information to characterize samples at the micro scale. CRM has been applied to the observation of fruit samples, such as carotenoids in tomato [11], polysaccharide changes in the cell wall of apple [9], lignification of loquat fruit [12], and chemical compositions in the cell wall of pear infected by fungi [13]. FTIRM has been used to study plants such as Arabidopsis petals [14], crops [15], and olive fruit [16], but not for the postharvest storage of fruit research.…”