Structure-based identification and pathway elucidation of flavonoids in Camptotheca acuminate

Flavonoid metabolism in Camptotheca acuminate remained an untapped area for years. A tandem MS approach was used and focused on the mining and characterizing of flavonoids in mature C. acuminate. Fifteen new flavonoids and forty-three known flavonoids, including fifteen flavone analogs, sixteen flavonol analogs, seven flavanone analogs, six chalcone analogs, four xanthone analogs, ten flavane analogs were mined and identified based on their MS/MS fragments. Fifty-three of them were firstly characterized in C. acuminate. Eight biosynthetic precursors for these flavonoids were also identified. We constructed a specific metabolic map for flavonoids according to their relative contents in the flowers, fruits, stems, and leaves of C. acuminate. Furthermore, the most probable genes involved in chalcone biosynthesis, flavonoid hydroxylation, methylation, and glycosylation were further mined and fished in the gene reservoir of C. acuminate according to their conserved domains and co-expression analysis. These findings enable us to acquire a better understanding of versatile flavonoid metabolism in C. acuminate.


Introduction
Flavonoids, a type of well-known specialized metabolites, are widely distributed in nature. Numerous flavonoids serve as colored pigments and defensive agents for plants [1]. Usually, the C6-C3-C6 nucleus for flavonoids biogenetically originates from the condensation reaction between a 4-coumaroyl CoA unit (B-ring) and three malonyl CoA units (A-ring). In addition, a linkage ring (C-ring) usually forms through C3 unit cyclization. Based on the state of the central C3 unit, flavonoids could be further grouped into flavone, flavonol, flavanone, chalcone, xanthone, and flavane [1]. These specialized metabolites are widely distributed in fruits, cereals, vegetables, and medicinal plants. Flavonoids usually display anti-inflammatory [2], anticancer [3], antihypertension [4], anti-coronary heart disease bioactivities [5]. Although more than seven thousand flavonoids have been characterized up to 2017 [6], the number of flavonoids is still expanding due to the versatile flavonoid metabolism in plants.
The structure elucidation for plant flavonoids was a fascinating work for natural product chemists. Nowadays, LC-MS/MS-based approach has been increasingly applied to characterize untapped secondary metabolites in plants, such as alkaloids [7]. Usually, the MS/MS spectra of flavonoids provide enough structural information due to their limited nucleus types and modified forms. Typical C-ring fragmentation patterns for flavonoids are summarized and illustrated in Fig. 1. Firstly, the cleavage of the central C3 unit through retro-Diels-Alder reaction in flavonoid produces several informative ions such as i,j A + and i,j B + . These fragment ions have been used as the diagnostic ions for flavonoid characterization. The substituents on ring A could be determined according to the diagnostic ions of i,j A + , and the substituents on ring B could be confirmed according to the fragments of i,j B + . Furthermore, the detailed fragmentation spectra for flavone, flavonol, flavanone, chalcone, xanthone and flavane vary from each other due to their different skeleton types and substitution patterns. Secondly, the loss of methyl, hydroxyl, carbonyl, and glucosyl are frequently detected in the fragmentation spectra of flavonoids. These clues also provide practical information for the substituents on the three skeleton rings. With the help of these guiding clues, forty flavonoids were identified according to their key fragments using ESI-IT-MS n [8]. Seven flavonoids were characterized in Scutellaria baicalensis based on their typical cleavage patterns [9]. Thirty flavonoid aglycones were identified from Cornus officinalis using ESI-QTOF-MS/MS [10].
Camptotheca acuminate, a native plant in China, is famous for its camptothecin-producing capability. Thirty-three alkaloids have been recently mined and characterized in our group through a UPLC-qTOF-HRMS based targeted metabolomics approach [7]. Hundreds of specialized metabolites have been detected in the flowers, fruits, stems, and leaves of this versatile plant. But a large amount of them remains uncharacterized. Numerous research efforts were poured on the isolation and characterization of alkaloids in C. acuminate due to their intriguing structure diversity and anticancer bioactivity. A metabolic map for indole alkaloids in C. acuminate has been constructed [7]. Interestingly, vigorous enzyme-mediated hydroxylation, methylation, and glycosylation modifications on the A, C or E ring of camptothecin analogs were observed in this plant. Therefore, we hypothesized that the indole alkaloid and flavonoid metabolic pathway in this plant might share common enzymatic catalysts, such as hydroxylase, glucosyltransferase, and O-methyltransferase. Some of these enzymes might be simultaneously responsible for the modification of camptothecin derivatives and flavonoids due to their substrate diversity. Therefore, identification and pathway elucidation of flavonoids in C. acuminate could also provide potential clues for uncovering the unknown steps in camptothecin biosynthesis. Only seven flavonoids were identified through HPLC-MS/MS analysis in C. acuminate up to now [11]. Flavonoid metabolism in C. acuminate remained an untapped area for years. Herein, purposefully mining and characterization of flavonoids and the genes probably involved in flavonoid metabolism were initiated with the help of our fundamental research. This study provides a comprehensive perspective on the versatile flavonoid metabolism in C. acuminate.

Plant material collection
Fresh flower, fruit, stem, and leaf samples were collected from the mature C. acuminate trees in Sichuan Agricultural University (Yaan campus), sealed, and stored at − 80 • C. The sampling interval was one week for flowers, two weeks for leaves and fruits, four weeks for stems.

Sample preparation and metabolite extraction
The frozen flower, fruit, stem, and leaf tissues were air-dried at 50 • C. Sample powder for each tissue was prepared through thoroughly grinding, and transferred into a conical flask, and soaked in n-hexane overnight. The n-hexane was removed through filtration, and the sample powder was dried, sealed, and stored. 500 μl of 80% methanol was added to re-suspend 0.1 g of sample powder and incubated at 30 • C for 10 min. The obtained extracts were centrifuged at 12,000 rpm for 5 min. The pipette was used to transfer the supernatants carefully. Then the obtained supernatants were filtrated by 0.22 μm filter in an Eppendorf tube through centrifugation. The final filtrate was used as the sample solution for subsequent LC-MS/MS analysis. An equal volume of the obtained filtrate from each sample was transferred into an Eppendorf tube and mixed by a vortex. The mixture was used as the QC sample, and the extraction solvent was designated as the blank sample.

Hierarchical clustering analysis
To construct the accumulation patterns for identified flavonoids in C. acuminate, hierarchical clustering analysis was performed via MetaboAnalyst 5.0 according to the semi-quantified data. The metabolic map for flavonoids in C. acuminate was constructed based on their biosynthetic origins and chemical structures.

Co-expression analysis and gene candidate screening
To screen the untapped CYP450, UDP-glucosyltransferase and Omethyltransferase probably involved in flavonoid metabolism, weighted correlation network analysis was performed with the R package WGCNA based on our transcriptomic data matrix for C. acuminate plantlets, which was deposited at NCBI (BioProject No. PRJNA704189). The expression data was prefiltered based on the built-in threshold, and the co-expression network was constructed using a soft threshold power of 8 and the mergeCutHeight parameter of 0.25. Cytoscape 3.8.2 was used to visualize the obtained network. The hierarchical clustering heat map for the bait genes, the newly mined CYP450, UDP-glucosyltransferase and O-methyltransferase, was generated based on their FPKM values in our transcriptomic data matrix using MeV 4.9.
Seven metabolites were identified and classified as isoflavone analogs (IFE1-IFE7) according to their informative diagnostic ions ( Fig. 1) [14,15]. Their fragmentation pathways are illustrated in Fig. S7-S13. . One hydroxy on ring B was also determined based on this ion. Furthermore, the existence of a hydroxy on ring C was confirmed according to the observation of an ion at m/z 271.1670, formed through the cleavage of 18 Da in the initial cleavage step. It was identified as the critical bio-precursor for isoflavone biosynthesis according to its diagnostic ions and intermediate ions (Fig. S14). Furthermore, two metabolites were characterized as coumestan analogs (CN1-CN2) according to their diagnostic ions ( Fig. 1) [16]. Their fragmentation pathways are illustrated in Fig. S15-S16. The [M+H] + ion formula of CN1 (315.1107, Tr 11.10 min) was annotated as C 16 H 11 O 7 . The existence of one methoxy and carbonyl was verified according to the detection of a fragment at m/z 283.1098, formed through the cleavage of 32 Da (-OCH 3 ), and another one at m/z 287.1166, produced through the cleavage of 28 Da (-CO). CN1 was classified into pterocarpan analog based on two specific diagnostic ions at m/z 107.0853 ( 1, 4 A + -OCH 4 ) and 181.0752 ( 1, 4 B + ). In addition, the existence of one methoxy and one hydroxy on ring A, two hydroxy on ring B were further confirmed based on detecting two diagnostic fragments at m/z 91.0540 ( 0, 4 A + -OCH 4 ) and 153.0178 ( 2, 4 B + ). Herein, CN1 was characterized as wedelolactone. The [M+H] + ion formula of CN2 (367.2020, Tr 9.22 min) was annotated as C 21 H 19 O 6 . It was classified as a pterocarpan analog at first glance according to the observation of two fragments at m/z 221.1080 ( 2, 4 A + -CH 2 ) and 180.1026 ( 1, 4 A + -•C 2 H 3 ). One isopentenyl, one hydroxy, and one methoxy on ring A were also verified according to the observation of the fragments mentioned above. The specific cleavage of 18 Da (-H 2 O), 14 Da (-CH 2 ), 28 Da (-CO), 14 Da (-CH 2 ), 28 Da (-CO) were also detected in this metabolite. Thus, CN2 was characterized as glycyrol [16]. The structures of the identified flavone, isoflavone, and coumestan analogs (FE1-FE6, IFE1-IFE7, CN1-CN2) are illustrated in Fig. 2.

Mining and identification of flavanone analogs
Four metabolites were characterized as flavanone analogs (DFE1-DFE4) according to their informative diagnostic ions (Fig. 1) [19]. Their fragmentation pathways are illustrated in Fig. S33

Mining and identification of chalcone analogs
Four metabolites were identified and classified as chalcone analogs (CE1-CE4) according to the informative fragment ions [21]. Their fragmentation pathways are illustrated in Figs. S40-S43. Similar diagnostic ions with flavanone were sometimes observed in the fragmentation process of chalcone due to the C-ring cyclization rearrangement. Thus, DCE2 was identified as the hydroxy benzyl derivative of DCE1, angoluvarin. In addition, two biosynthetic precursors for chalcone, phenylalanine (CEP1) and 4-coumaric acid (CEP2) were also mined and identified according to their cleavage patterns (Figs. S46-S47) [22,23]. The structures of the identified chalcone analogs (CE1-CE4, DCE1-DCE2) are illustrated in Fig. 2.

Mining and identification of xanthone analogs
Four metabolites were identified and classified as xanthones analogs (XE1-XE4) according to their informative diagnostic ions (Fig. 1) [24]. 2 ) from the mother ion and the ion at m/z 310.1202 indicated the existence of di-tetrahydrofuran moiety. The di-tetrahydrofuran moiety, along with a hydroxy and methoxy on ring A, was confirmed based on two fragments at m/z 207.0799 ( 0,4 A + ) and 251.1063 ( 1,3 A + ). Finally, XE2 was identified as 5-hydroxy sterigmatocystin based on its detailed cleavage tree. The [M+H] + ion formula of XE3 (m/z 259.2046, Tr 14.60 min), 14 Da higher than XE1, was annotated as C 14 H 11 O 5 and defined as a methoxy derivative of XE1. One methoxy and hydroxy was verified on ring A according to the observation of a diagnostic fragment at m/z 123.1166 ( 0,4 A + ). Furthermore, a hydroxy on ring B was also confirmed based on detecting a diagnostic ion at m/z 137.0970 ( 0,4 B + ). Thus, XE3 was identified as 3-methyl gentisein. The [M+H] + ion formula of XE4 (277.2158, Tr 13.06 min), 32 Da higher than XE1, was annotated as C 13 H 9 O 7 . It was defined as a dihydroxy derivative of XE1 according to the observation of diagnostic ions at m/z 137.0603 ( 0,4 B + ), 109.0644 ( 0,3 B + ), 185.1319 ( 1,3 A + ), 157.1005 ( 1,4 A + ). XE4 was identified as a xanthone, 2,4-dihydroxy gentisein. In addition, three xanthone biosynthetic precursors XEP1-XEP3 were mined and identified according to their fragmentation spectra (Figs. S52-S54) [25]. The structures of the identified xanthone analogs (XE1-XE4) are illustrated in Fig. 2.

Mining and identification of flavane analogs
Ten metabolites were identified and classified as flavane analogs (FAE1, IFAE1, FAL1-FAL3, BF1-BF3, AN1-AN2) according to their informative diagnostic ions (Fig. 1)    loss of 18 Da (-H 2 O) was also detected in the first cleavage step. Thus, FAEP1 was determined as leucopelargonidin (Fig. S65) 163.0398 ( 0,4 B + ) and 151.0751 ( 0,2 A + ) formed. It indicated the existence of two hydroxy on ring A and one on ring B. Thus, the ion at m/z 271.1679 was characterized as an anthocyanin derivative. Finally, FAEP2 was characterized as the biosynthetic precursor for anthocyanin, 2-hydroxy leucopelargonidin (Fig. S66). The structures of the identified flavane analogs (FAE1, IFAE1, FAL1-3, BF1-3, AN1-2) are illustrated in Fig. 2. The fragmentation spectra for six flavonoid standards are also provided in Figs. S67-S72 and compared with the identified flavonoids in C. acuminate to verify the accuracy of our results.

Metabolic pathway mapping of flavonoids and untapped biosynthetic gene discovery
To screen the discrimination flavonoids in C. acuminate, the ion abundance of the fifty-eight identified flavonoid metabolites in the flower, fruit, stem, and leaf samples was extracted from the raw dataset matrix and submitted to MetaboAnalyst 5.0 for multivariate analysis and enrichment analysis. PCA analysis in Fig. 3A indicated that fruit groups were not separated from the stem group. Better separation between the four groups were obtained based on the PLS-DA analysis and illustrated in Fig. 3B. Five discrimination flavonoids, including CE3, FOL1, FOL3, FOL12, FOL15 (VIP>2), were obtained (Fig. 3C). Interestingly, four of them were classified into flavonol analogs. Furthermore, CE3 and FOL3 could be designated as the marker metabolites for flowers, FOL15 for leaves, FOL1 and FOL12 for stems in C. acuminate based on their enrichment patterns. To unveil the flavonoid metabolism in C. acuminate, a metabolic map for all the identified flavonoids was constructed and depicted in Fig. 4 based on their biogenetic originations, chemical structures, and enrichment pattern in different tissues. Undoubtedly, this ancient tree species could be designated as a versatile flavonoid manufacturer. Numerous untapped CYP450, glucosyltransferase, and O-methyltransferase probably involved in flavonoid metabolism could be mined in the gene reservoir of C. acuminate, based on our metabolic pathway for flavonoids.
Firstly, the genes involved in the biosynthesis of chalcone, the common precursor for flavonoids, were purposefully mined according to their conserved domains. Five phenylalanine ammonia-lyase, two cinnamate 4-hydroxylase, five chalcone synthase, one chalcone isomerase, thirteen 4-coumarate coenzyme A ligase, were obtained from the generated genomic dataset. The identities and coverages were calculated through sequence alignment with the characterized ones from other plants and listed in Table 1. The distribution pattern for these bait genes was generated according to our co-expression analysis results. Although the twenty-six bait genes mentioned above were broadcast in eleven different clusters, seven of them, including CaPAL-Cac_g020956, CaC4H-Cac_g002001, CaC4H-Cac_g025455, Ca4CL-Cac_g024972, Ca4CL-Cac_g021728, Ca4CL-Cac_g031657, and CaCHS-Cac_g017730, which were responsible for the upstream biosynthetic pathway for flavonoids, were concentratedly distributed in cluster turquoise. And the unique CaCHI-Cac_g004852, along with CaCHS-Cac_g010309, appeared in cluster tan. The mining of the CYP450, OMT, and UGT candidate genes probably involved in the biosynthetic modification of flavonoids was initiated and focused on the turquoise cluster.
CaCHS-Cac_g017730, were extracted from the co-expression matrix of the turquoise cluster. The co-expressed network was constructed with Cytoscape 3.8.2 and depicted in Fig. 5. Interestingly, only nineteen of the twenty-five UGT candidates, eight of the nine OMT candidates, twenty-four of the thirty-five CYP450 candidates were synchronously correlated with the four kinds of genes involved in flavonoid biosynthesis. Thus, the full amino acid sequence of these candidates was further extracted from the genomic and transcriptomic dataset and used to perform sequence alignment analysis with the characterized ones. Encouragingly, two of the obtained OMT candidates, Cac_g006777 and Cac_g032399, shared 66.67% and 52.19% identities with flavone-8-Omethyltransferase in Ocimum basilicum (AGQ21571.1) [27] and flavonoid 3 ′ -O-methyltransferase in Chrysosplenium americanum (AAA86982.1) [28], respectively. Two of the obtained CYP450 candidates, Cac_g004916 and Cac_g032229, were classified as CYP71D and CYP81 family, respectively, according to their conserved domains and catalytic residues. They shared 57.14% and 41.04% identities with the flavonoid 6-hydroxylase in Glycine max (AGB55868.1) [29] and isoflavone 2 ′ -hydroxylase in Glycyrrhiza echinate (AB001379.1) [30], respectively. Four UGT candidates, Cac_g031815, Cac_g016165, Cac_g014741, and Cac_g014740, were screened from the obtained UGT candidates according to their conserved domains and catalytic residues. They shared 56.33%, 54.72%, 57.23 and 56.21% identities with the flavonol 3-O-glucosyltransferase (BAR88078.1) in Glycine max [31], flavonol 5-O-glucosyltransferase (AF171902.1) in Paeonia lactiflora [32], flavonoid 7-O-glucosyltransferases (AAS94329.1) in Beta vulgaris [33], respectively. The identities and coverages for these newly fished CYP450s, OMTs, UGTs, are listed in Table 1. Sequence alignment analysis with the characterized ones is provided in Figs. S73-S79 . The expression levels for the newly fished CYP450s, OMTs, UGTs, along with the bait genes, are visualized in Fig. 6based on our transcriptomic data for C. acuminate plantlets after different elicitor treatments. Encouragingly, most of our targeted genes cluster together in the heat map. Five of the seven bait genes distributed in cluster turquoise, and six of the eight newly fished genes, were significantly upregulated after MeJa treatment. The expression level of CYP71-Cac_g004916 was significantly upregulated after AgNO 3 treatment. Minor upregulation was observed for the targeted genes distributed in cluster turquoise after PEG and Fig. 6. The hierarchical clustering heat map for the bait genes and the newly fished CYP450, OMT, UGT candidate genes involved in flavonoid biosynthesis. The genes distributed in cluster turquoise are marked with black circle.