Study on Browning Mechanism of Fresh-Cut Eggplant (Solanum

www.nature.com/scientificreports OPEN Study on browning mechanism of fresh‑cut eggplant (Solanum melongena L.) based on metabolomics, enzymatic assays and gene expression Xiaohui Liu1,2,3,5, Aidong Zhang1,2,5, Jing Shang1,2,3, Zongwen Zhu2,3, Ye Li4, Xuexia Wu2,3* & Dingshi Zha2,3* Enzymatic browning is one of the crucial problems compromising the favor and texture of fresh‑ cut fruit and vegetables. In this study, an untargeted metabolomics approach based on liquid chromatography‑mass spectrometry (LC–MS) was used to explore the browning mechanism in fresh‑cut eggplant. Metabolomics studies showed that with the increase of fresh‑cut time, the contents of 946 metabolites changed dynamically. The metabolites having the same trend share common metabolic pathways. As an important browning substrate, the content of chlorogenic acid increased signifcantly, suggesting that may be more important to fresh‑cut eggplant browning; all 119 common diferential metabolites in 5 min/CK and 3 min/CK contrastive groups were mapped onto 31 KEGG pathways including phenylpropanol metabolism, glutathione metabolism pathway, et al. In physiological experiments, results showed that the Phenylpropanoid‑Metabolism‑Related enzymes (PAL, C4H, 4CL) were changed after fresh‑cut treatment, the activities of three enzymes increased frst and then decreased, and reached the maximum value at 5 min, indicating the accumulation of phenolic substances. At the same time, ROS were accumulated when plant tissue damaged by cutting, the activities of related antioxidant enzymes (SOD, APX and CAT) changed dynamically after oxidative damage. SOD and APX content increased signifcantly and reached the maximum value at 10 min after cutting, and then showed a downward trend. However, CAT activity increased sharply and reached the maximum value within 3 min after cutting, then maintained the same activity, and showed a downward trend after 30 min. These data fully demonstrated that the activities of browning related enzymes and gene expression increased with the prolonging of fresh cutting time. We explained the browning mechanism of fresh‑cut eggplant by combining metabolomics and physiology, which may lay the foundation for better understanding the mechanism of browning during the fruits and vegetables during processing. Solanum melongena L. is commonly known as eggplant, and belongs to genus Solanum, which is one of the largest genera within family Solanaceae with over 1550 species 1. It is a common vegetable, rich in polyphenols, dietary fber, vitamins and other nutrients; it provides a variety of health benefts such as lowering blood lipids, protecting the liver, and as an antioxidant, and thus, it is favored by consumers2. However, browning of eggplant occurs easily afer peeling, which afects its sensory quality and nutritional value, leading to a decline in edibility and reduced value as a commodity. Browning is the result of a series of physiological and biochemical processes in fruits under aging or adverse conditions. Browning reactions can be divided into two categories, namely enzymatic browning and non-enzymatic browning 3. Enzymatic browning is a common phenomenon in the processing of fruits and vegetables. Factors involved in browning reactions of fruits and vegetables, such as apple 4, pear5, lufa6 and potato7, have been extensively. 1Horticultural Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China. 2Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai 201403, China. 3Shanghai Ocean University, Shanghai 201306, China. 4Harbin Academy of Agricultural Sciences, Harbin 150070, China. 5These authors contributed equally: Xiaohui Liu and Aidong Zhang. *email: [email protected]; [email protected] Scientifc Reports | (2021) 11:6937 | https://doi.org/10.1038/s41598-021-86311-1 1 Vol.:(0123456789) www.nature.com/scientificreports/ Researchers have found that the primary reason for browning may be the disruption of the membrane system8. When fruits and vegetables are damaged mechanically or in an adverse environment, polyphenols inside them will oxidize under the catalytic action of polyphenol oxidase (PPO) and turn brown 9, and this requires the par- ticipation of oxygen, enzymes and substrates. Peroxidase (POD) and lipoxygenase (LOX) are also key enzymes that cause the browning of fruits and vegetables. Phenolic enzymes and phenolic substances in healthy fruits are regionally distributed in cells; they cannot come into contact when the cells are intact, and no browning reaction occurrs10. When the cells sufer adversity, the activities of reactive oxygen scavenging enzymes such as superoxide dismutase (SOD), catalase (CAT) and ascorbate peroxidase (APX) are reduced, which decreases the fruit’s ability to scavenge free radicals, and thereby allows the accumulation of reactive oxygen species (ROS)11. At the same time, the process of membrane lipid peroxidation is accelerated and membrane permeability is increased, and contact between enzymes and substrate will induce enzymatic browning12. In addition, studies have shown that transcription factors also have an impact on fruits and vegetables browning, for example, WRKY gene family may also be involved in the regulation of Lufa6 and husk of walnut13 browning. Metabolomics is a burgeoning omics technology, and complements the technologies of genomics and pro- teomics; Fiehn proposed in 2002 that metabolomics is a qualitative and quantitative analysis method for total metabolites in the body of an organism14. With the broadening base of plant metabolomics research, we have gained a better understanding of plant growth regulation, development, metabolic processes and molecular mechanisms of stress responses. In addition, plant metabolomics has become a powerful tool for probing physiology and biology all aspects of plants15. In order to explore the mechanism of climate and development regulat- ing the antioxidant system and metabolism of date palm leaves, Du et al. used the non-targeted metabolomics method based on LC–MS to fnd that young leaves may be more responsive to the environmental change 16. Using targeted metabolomics, Tang et al. found that levels of hyperoside, POD, SOD, H2O2, ascorbic acid (AsA), and expression of nine genes (MdPAL, MdCHS, MdCHI, MdANS, MdFLS, MdANR, MdUGT71K1s, MdTTG1 and MdMYB1) were lower levels in browning-sensitive apples 4. Tis study focuses on mechanisms behind the browning responsive of ‘Huqie 5′ fresh-cut eggplant fruits by combining plant physiological and metabolomics approaches. Te primary purpose of this study was to clarify the biochemical and molecular mechanism of the browning process in fresh-cut eggplant fruits, ofer a feasible theoretical foundation for the processing and production of fresh-cut fruit and vegetable, and provide a reference for further investigation into means for reducing the browning of other fresh-cut products. Results Multivariate analysis. In the data matrix, the data were subject to multivariate analysis tools (Principal Components Analysis (PCA), Partial Least Squares Discrimination Analysis (PLS-DA) and Orthogonal projec- tions to latent structures Discrimination Analysis (OPLS-DA)). PCA, PLS-DA and OPLS-DA scoring plots and validation plots of the OPLS-DA models were built for the three contrastive groups: 3 min/CK, 5 min/CK and 3 min/5 min (Fig. 1). Table 1 displays all the parameters of these models. In our results, all values for Hotelling’s T2 were 95%, Q2 were < 0 (Q2 = − 0.849 to − 0.741), R2X were > 0.4, and R2 were > 0.5, indicating that the model is reliable. Diferential metabolites. Criteria for screening diferential metabolites were variable infuence of pro- jection (VIP) > 1 for the frst principal component in the OPLS-DA, and p-value < 0 (Table S4). Among these diferential metabolites, chlorogenic acid is a diferential metabolite in 5 min/CK (Fold Change, FC = 1.64) and 5 min/3 min (FC = 1.63) (Table S4). 256 diferential metabolites were detected in the 3 min/CK comparative group, 357 in the 5 min/CK comparative group and 333 in the 3 min/5 min comparative group. Among these metabolites, 49 were common to all three groups and 119 were common between 3 min/CK and 5 min/CK. However, 253 diferential metabolites were the non-repeated between any two groups; 114, 58 and 81 metabolites were exclusive to the 3 min/CK, 5 min/CK and 3 min/5 min comparative groups, respectively (Fig. 2). Heatmap of 119 common diferential metabolites. Te 119 common diferential metabolites from the 3 min/CK and 5 min/CK groups were further divided into three categories based on STC (Subject To Clas- sifcation), and are represented by A, B and C in Table S5. Furthermore, the metabolites in these three categories were grouped into eight types of compounds (Table 2). Category A included 68 metabolites, which were mainly lipids, fatty acid and carbohydrates (Table 2). Te contents of these metabolites increased gradually. Te metabolites of category B comprised 40 compounds, and were mostly fatty acids and lipids (Table 2). Te contents of these metabolites decreased as the time from cutting increased. Tere were 11 components in category C, mainly lipids (Table 2). Interestingly, their contents and expression levels decreased at 3 min, but increased at 5 min. However, they were lower than those at 0 min (CK) as a whole. In order to express the clustering relationships between A, B and C, the peak areas of 33 metabolites were selected to construct a heatmap (Fig. 3). Metabolite content changes. Six phenols

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