# Metabolite Profiling of _Christia__vevertilionis_ Leaf Metabolome via Molecular Network Approach
## 3 Results and Discussion  
Metabolite Profiling of the Leaf Metabolome of the Green-Lafed Variety of Christia vespertilionis via Untargeted Tandem Mass Spectrometry-Based Molecular Networking  
The UHPLC-MS/MS spectral data of the methanolic leaf extract of C. _vespertilionis_ was successfully acquired as the first step towards establishing a detailed phytochemical composition of the leaf metabolome. More than 300 MS/MS spectra over the mass range of \(m/z\) 120 to 1500 were generated in both positive and negative ion modes. The respective total ion chromatograms (TICs) and photodiode array chromatograms (PDAs) obtained are presented in Figure S1a,b. The plant leaves' chemical space was further analyzed in detail by mapping structurally related compounds into molecular networks. To achieve this, the acquired large datasets of MS/MS fragmentation spectra were processed and organized as molecular networks (MNs) according to the online workflow provided by the Global Natural Products Social Molecular Networking (GNPS) platform ([[http://gnps.ucsd.edu](http://gnps.ucsd.edu)]([http://gnps.ucsd.edu](http://gnps.ucsd.edu)), accessed on 20 December 2019). The MNs generated from the mass spectral data of the extract are depicted in Figure 1, where the consensus MS/MS spectrum of each detected molecular ions, generated by the aid of the MS-Cluster algorithm, was visualized as a node (blue circles), while the edge (grey lines) connecting the nodes indicated that they possess a homologous MS/MS fragmentation pattern, hence, allowing them to be mapped together within the same cluster (node \(\geq\) 2) as a molecular family. Visual inspection of this generated molecular network map permitted the annotation of various clusters of metabolites comprising phenolic acids, mono- and dihydroxyflavones, C-glycosflavone derivatives, flavonoid 3-O-glycos, benzyltetrahydrodoiquinoline-type alkaloids, hydroxyjasonic acid derivatives, phenethyl derivatives, monoacylglycerollycerols, fatty acid amides, chlorophyll derivatives, and carotenoids, as well as some of the \"self-loop\" nodes, including organic acids, nucleoside, amino acids, and flavone-_C_,_O_-diglycoside. In brief, a total of 60 metabolites were characterized and tentatively identified based on the diagnostic MS/MS fragment ions, MS/MS spectral data matched with published literatures, structural hits obtained from GNPS spectral library matching, and by interpreting the MS/MS spectra of unknown compounds by comparison to the MS/MS spectra of their close structural analogs (tentative candidates). From these, 58 compounds are reported for the first time in the leaf metabolome of this plant. Notably, 16 of the compounds are proposed as new structures based on a detailed inspection of their MS/MS data, which include 2 derivatives of phenolic acid ester, 2 derivatives of dihydroxybenzoic acid, 2 derivatives of dihydroxyflavone, 4 derivatives of apigenin 6-C-glucose, 2 derivatives of benzyltetrahydrodoiquinoline-type alkaloid, 2 derivatives and 1 isomer of hydroxyjasonic acid, and a derivative of phenethyl. The characteristic fragmentation patterns of the proposed new structures are discussed in detail. From the results of the semiquantitative analysis, it is worth mentioning that flavonoids were the major class of metabolites in the leaf metabolome, representing 78.48% of the identified metabolites. This was followed by phenolic acids (7.61%), miscellaneous compounds (6.35%), and carotenoids (3.20%). The other chemical classes were present at lower relative percentages. All the identified metabolites, along with their respective retention times (RT), molecular formula, precursor ion (\(m/z\)), key fragments data, and relative abundance (%), are listed in Table 1. The following subsections discuss the annotation of the metabolites of selected clusters and \"self-loop\" nodes mapped in the network.