4500 q trap

The above sample extracts were analyzed by an UPLC-ESI-MS/MS system (UPLC, SHIMADZU Nexera X2; MS, Applied Biosystems 4500 QTRAP),. The column of UPLC was an Agilent SB-C18 (1.8 µm, 2.1 mm × 100 mm) and the mobile phase consisted of solvent A (pure water containing 0.1% formic acid) and solvent B (acetonitrile containing 0.1% formic acid). Sample measurements were performed with a gradient program using the starting conditions of 95% A and 5% B. Within 9min, a linear gradient to 5% A, 95% B was programmed, and held for 1 min. Subsequently, it was adjusted to a mixture of 95% A, 5.0% B within 1.1 min and held for 2.9 min. The injection volume of UPLC was 4 μL, the flow velocity was set to 0.35 mL/min, the column temperature was set to 40°C. The effluent was alternatively connected to an ESI-triple quadrupole-linear ion trap (QTRAP)-MS for subsequent determination.

A set of leaf samples of mock and infection at 4 dpi were collected for metabolite quantification. The freeze-dried tissue was crushed to fine powder, and 100 mg was extracted with 0.6 mL of 70% aqueous methanol and then filtrated and subjected to UPLC-MS/MS system (UPLC, Shim-pack UFLCSHIMADZU CBM30A system; MS, Applied Biosystems 4500 Q TRAP) for detection and quantification. Metabolites were extracted and identified using Metware database (METWARE, Wuhan, China). Metabolites showing significant accumulation were filtered by R package MetaboAnalystR version 1.01 (Montreal, QC, Canada) [29 (link)], with parameters of absolute log2FoldChange > 1 and variable importance in projection (VIP) over 1. Principal component analysis (PCA) was performed by a statistics function within R. All charts were illustrated with R package ggplot2.

The sample extracts were analyzed using a UPLC-ESI-MS/MS system (UPLC, SHIMADZU Nexera X2, www.shimadzu.com.cn/, accessed on 8 June 2021; MS, Applied Biosystems 4500 Q TRAP, www.appliedbiosystems.com.cn/ accessed on 8 June 2021). The analytical conditions were as follows: UPLC: column, Agilent SB-C18 (1.8 µm, 2.1 × 100 mm). The mobile phase consisted of solvent A, pure water with 0.1% formic acid, and solvent B, acetonitrile with 0.1% formic acid. Sample measurements were performed with a gradient program that employed the starting conditions of 95% A, 5% B. Within 9 min, a linear gradient to 5% A, 95% B was programmed, and a composition of 5% A, 95% B was kept for 1 min. Subsequently, a composition of 95% A, 5.0% B was adjusted within 1.10 min and kept for 2.9 min. The flow velocity was set as 0.35 mL per min. The column oven was set to 40 °C, and the injection volume was 4 μL. The effluent was connected to an ESI-triple quadrupole-linear ion trap (QTRAP)-MS [21 (link)]. The analytical conditions were adapted from Chen et al. [17 (link)]. Metabolite quantification was conducted using multiple-reaction monitoring (MRM) [22 (link)] and the self-built MetWare database (MWDB) based on their standard metabolic operating procedures [15 (link),17 (link)].

For further metabolomics analysis of secondary metabolites, 2-year-old C. paliurus seedlings of resistant (Wufeng) and susceptible (Jinggangshan) cultivars were inoculated following the IPI method as described earlier. The sample preparation, extract analysis, metabolite separation, and detection were conducted by MetWare Biological Science and Technology (Wuhan, China) following their standard procedures, which were previously described by Li et al. (2021) (link) and Mei et al. (2020) (link). In brief, 100 mg crushed, freeze-dried sample was extracted overnight at 4°C with 0.6 mL 70% (v/v) aqueous methanol. After centrifuging at 10,000 rpm for 10 min, the extracts were absorbed and filtered, and then analyzed on a UPLC–ESI–MS/MS system (UPLC, Shim-pack UFLC SHIMADZU CBM30A system; MS, Applied Biosystems 4500 QTRAP). Metabolite quantification was conducted utilizing the multiple reaction monitoring (MRM) method (Chen et al., 2013 (link)). Following data evaluation (quality control and PCA analysis), OPLS-DA, a supervised multivariate method, was used to maximize metabolome differences between sample pairs. Differentially accumulated metabolites (DAMs) were set at fold change (FC) > 2 or FC < 0.5 and OPLS-DA VIP ≥ 1. The identified DAMs were further annotated using the KEGG compound database to reveal the function and content variation of these metabolites.

The HPLC effluent was connected to an electrospray ionization (ESI)-triple quadrupole-linear ion trap–MS/MS system (Applied Biosystems 4500 Q TRAP). Metabolite identification and quantification were carried out following Chen et al. (2013 (link)). In brief, the inspected mass spectra were 50–1,000 m/z. Nitrogen was used as both the nebulizer/auxiliary and collision gas. The ESI source was set to positive ionization mode, the source temperature was held at 550°C; the capillary voltage was 5.5 kV. The monitoring mode was set to multiple-reaction monitoring (MRM).
Metabolite identification was based on the primary and secondary spectral data annotated against public databases, namely MassBank (http://www.massbank.jp/), KNAPSAcK (http://kanaya.naist.jp/KNApSAcK/), HMDB (http://www.hmdb.ca/), MoToDB (http://www.ab.wur.nl/moto/), and METLIN (http://metlin.scripps.edu/index.php), following the standard metabolic operating procedures. Metabolite quantification was carried out using MRM. Partial least squares discriminant analysis (PLS–DA) was carried out with the identified metabolites. Metabolites with significant differences in content were set with thresholds of variable importance in projection (VIP) ≥ 1 and fold change ≥ 2 or ≤ 0.5.

The sample preparation, extraction analysis, metabolite identification, and quantitative analysis were conducted at Metware Biotechnology Co., Ltd. (Wuhan, China) following their standard procedures and previously fully described by Yuan et al. [41 (link)]. Specifically, flavonoid extracts were analyzed using ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) (Shim-pack UFLC SHIMADZU CBM30A, Applied Biosystems 4500 QTRAP, Waltham, MA, USA). Then, metabolite quantification was performed by multiple reaction monitoring (MRM) using a triple quadrupole mass spectrometer. Later, the identified metabolites were subjected to orthogonal partial least-squares discriminate analysis (OPLS-DA), and metabolites with |log2FC| ≥ 1, p < 0.05, and variable importance in projection (VIP) score ≥ 1 were considered as differentially accumulated flavonoids (DAFs).

The sample extracts were analyzed using an UPLC−ESI−MS/MS system (UPLC, Shim−pack UFLC SHIMADZU CBM30A system; MS, Applied Biosystems 4500 Q TRAP) [64 (link)]. The analytical conditions were as follows: UPLC column, Waters ACQUITY UPLC HSS T3 C18 (1.8 µm, 2.1 mm × 100 mm); the mobile phase consisted of 0.04% acetic acid aqueous solution solvent A and 0.04% acetic acid acetonitrile solvent B; the gradient procedure was used for sample measurement, and the initial conditions were 95% A and 5% B. Within 10 min, the combination of linear gradient to 5% A, 95% B, 5% A and 95% B were maintained for 1 min.