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Article

Proteomics Analysis and Identification of Proteins Related to Isoprenoid Biosynthesis in Cinnamomum camphora (L.) Presl

by
Changsan Zhu
1,†,
Fan Zhang
2,†,
Silin Chen
2,
Kun Wang
1,
Ganju Xiang
2,
Xiaojing Liang
1,
Jiacheng An
1,
Kaixiang Li
1,* and
Li Liu
2,*
1
Guangxi Key Laboratory of Special Non-Wood Forest Cultivation and Utilization, Guangxi Engineering and Technology Research Center for Woody Spices, Forestry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530002, China
2
Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, Hubei Key Laboratory of Industrial Biotechnology, State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan 430062, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Forests 2022, 13(9), 1487; https://doi.org/10.3390/f13091487
Submission received: 19 July 2022 / Revised: 30 August 2022 / Accepted: 6 September 2022 / Published: 14 September 2022
(This article belongs to the Section Genetics and Molecular Biology)
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Abstract

:
Cinnamomum camphora is an evergreen tree that contains essential oils and the leaf is the main organ used to extract essential oils. Isoprenoid is a key component contributing to the essential oils of C. camphora. Still, the molecular mechanisms and regulatory pathways underlying isoprenoid biosynthesis remain to be explored. In our study, we found that the content of linalool was higher in 65-day-old leaves than that in 15-day-old leaves of linalool-type C. camphora. The leaf proteome of these two materials was then analyzed based on data-independent acquisition, respectively, and 11,503 proteins were identified, of which 11,076 were annotated. Analysis of differentially expressed proteins revealed that the expression levels of MCT, MDS, and AACT increased significantly in 65-day-old leaves. Further analysis of the protein interaction network indicated that 15 differentially expressed proteins related to isoprenoid biosynthesis were co-expressed, and also suggested that the transcription factor families of BES1, C3H, MYB, NF-YC, Nin-like, WRKY, ZF-HD, and bHLH may act as candidate regulators of leaf development in C. camphora. Our study verified that the process of isoprenoid biosynthesis in C. camphora is regulated by a complicated network consisting of conserved synthetases, and provides proteomic information for further investigation of isoprenoid metabolic.

1. Introduction

As a part of the Lauraceae family, Cinnamomum camphora (L.) Presl is a deciduous tree with important economic value [1], and its economic value primarily depends on the quality and quantity of its essential oil. With the abilities of antibacterial and antifungal, the essential oil of C. camphora has been wildly used in medicine and health [2,3]. According to a previous study, C. camphora essential oil can be extracted from the roots, stems, and leaves, and the extraction rate of essential oil from the leaves is the highest [1].
A previous study has verified that isoprenoids, also known as terpenoids, are the major components of C. camphora essential oil [4]. Based on the different main components of the essential oil, C. camphora can be divided into five chemotypes: isoborneol-type, camphor-type, cineole-type, borneol-type, and linalool-type [5]. As the main isoprenoid compound in linalool-type C. camphora, linalool is a kind of monoterpene and is responsible for the characteristic flavor. At present, linalool has been commercially used in food, consumer products, insect repellents, and insecticides [6] for its anti-inflammatory [7], antimicrobial [8], and antioxidant properties [9].
To date, terpenoids are all derived from dimethylallyl diphosphate (DMAPP) and isopentenyl diphosphate (IPP). In plants, mevalonate (MVA) and methylerythritol phosphate (MEP) are the two terpenoid precursor synthesis pathways [10]. The MEP pathway begins with the conversion of pyruvate and D-glyceraldehyde 3-phosphate (GAP) into 1-deoxy-D-xylulose 5-phosphate (DXP) which is catalyzed by DXP synthase (DXS). The DXP is converted to MEP by DXP reductoisomerase (DXR), which is subsequently reduced by 2-C-methyl-d-erythritol 4-phosphate cytidylyltransferase (MCT) to produce 4-(cytidine 5′-diphospho)-2-C-methyl-D-erythritol (CDP-ME). CDP-ME can be catalyzed to form 2-phospho-4-(cytidine 5′-diphospho)-2-C-methyl-D-erythritol (CDP-MEP) by 4-(cytidine 5′-diphospho)-2-C-methyl-D-erythritol kinase (CMK). 2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase (MDS) catalyzes the formation of 2-C-methyl-D-erythritol-2,4-cyclodiphosphate (MEcPP) directly from CDP-MEP. Under the catalysis of 4-hydroxy-3-methylbut-2-enyldiphosphate (HMBPP) synthase (HDS), MEcPP is converted to HMBPP, and then HMBPP can be catalyzed to produce both IPP and DMAPP by HMBPP reductase (HDR) [11]. The MVA pathway can produce IPP from acetyl-coenzyme A (CoA) via six consecutive steps catalyzed by acetyl-CoA C-acetyltransferase (AACT), 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) synthase (HMGS), HMG-CoA reductase (HMGR), mevalonic acid kinase (MK), phosphomevalonate kinase (PMK), and mevalonate-5-diphosphate decarboxylase (MPDC). IPP isomerase (IPPI) catalyzes IPP to produce DMAPP [12]. IPP and DMAPP can produce various isoprenoid precursors catalyzed by short-chain prenyltransferases: geranylfarnesyl diphosphate (GFPP), geranylgeranyl diphosphate (GGPP), farnesyl diphosphate (FPP), and geranyl diphosphate (GPP). Short-chain prenyltransferases include GFPP synthase (GFPPS), GGPP synthase (GGPPS), FPP synthase (FPPS), and GPP synthase (GPPS). GPP can further synthesize monoterpene, while GGPP can act as a precursor for the biosynthesis of carotenoids, tocopherols, phylloquinone, and diterpenes [10] (Supplement Figure S1).
Recently, some studies provided insights into isoprenoid biosynthesis in C. camphora based on sequencing technology. Eighty-three terpene synthase genes have been predicted and annotated in the chromosome-level genome sequence of C. camphora [13]. In addition to the investigation carried out on the genomic level, the analysis of genome-wide transcriptome also provides information about terpenoid biosynthesis in C. camphora [14]. Target identification analyses indicated that some microRNAs contributed to the regulation of terpenoid biosynthesis [15]. Moreover, the significant role that long non-coding RNAs played in terpenoid biosynthesis has been confirmed by using Strand-specific RNA sequencing [16]. At the protein level, the identification and functional characterization of trans-isopentenyl diphosphate synthases (TIDSs) revealed the potential roles of the CcTIDS family in terpenoids metabolic in C. camphora [17].
Data-independent acquisition (DIA) is a quantitative multiplexed proteomics technique that could compare hundreds of different samples while maintaining the accuracy obtainable and superb measurement precision [18]. At present, DIA has been widely used in plant proteomes, including crops [19,20], horticultural plants [21,22], and medicinal plants [23].
To illustrate the intrinsic differences in the isoprenoid biosynthesis pathway between different leaf ages of linalool-type C. camphora, the proteomic approach combined with metabolic analysis was performed in our study. We identified the candidate proteins that participated in isoprenoid biosynthesis and the potential transcription factor families that may play key roles in the leaf development of C. camphora. These results reinforce the notion that complicated regulatory networks are involved in the isoprenoid biosynthesis of plants.

2. Materials and Methods

2.1. Plant Materials

After budding in February of 2018 (Guangxi Nanning, China), 15-day-old (15 d), 25-day-old (25 d), 35-day-old (35 d), 45-day-old (45 d), 55-day-old (55 d), and 65-day-old (65 d) leaves were collected from a three-year-old linalool-type Cinnamomum camphora. Fresh leaves were collected for linalool determination. As for protein extraction, the leaves of 15 d and 65 d were harvested and frozen in liquid nitrogen, then stored at −80 °C. Three independent sample replications were included.

2.2. Extraction of Essential Oil

The essential oil of linalool-type C. camphora was extracted using the CO2 supercritical extraction method [24]. Briefly, a 0.1 g sample was filled into a 5 mL extraction kettle for supercritical CO2 extraction with methanol used as an auxiliary extraction solvent. The conditions applied were 180 bar, 50 °C, the CO2 flow rate of 5.0 mL/min, and the methanol flow rate of 1.0 mL/min. The extracted liquid was collected and used to detect the content of the linalool by gas chromatography.

2.3. Gas Chromatography-Mass Spectrometry Analysis

The chromatographic conditions for quantitative analysis of linalool were set as follows: chromatographic column: elastic quartz capillary column BR-5ms (30 m × 0.25 mm × 0.25 μm), the carrier gas is nitrogen, temperature-programmed: 100–130 °C at 1.5 °C/min, 230 °C at 10 °C/min, sample inlet: 250 °C, vaporization chamber: 250 °C, split ratio: 1:50. Detector temperature: 280 °C, injection volume: 0.4 μL [25].

2.4. Protein Extraction and Digestion

The total proteins of leaves were extracted using the cold acetone method. Briefly, samples were ground in liquid nitrogen and the powder was then dissolved in a lysis buffer (7 M Urea, 2% SDS, 0.1% PMSF, 65 mM DTT), followed by centrifugation. The supernatant was incubated at −20 °C overnight with ice-cold acetone. The precipitations were then washed with acetone and redissolved in 8 M Urea by sonication. The protein content was determined by the BCA method [26]. The proteins were digested with trypsin (Promega, Madison, WI, USA) at a trypsin/protein ratio of 1:50 (w/w) at 37 °C for 16 h.

2.5. High pH Reverse Phase Separation

The peptides were separated on XBridge C18 column (4.6 mm × 250 mm, 5 μm) (Waters Corporation, Milford, MA, USA) with Ultimate 3,000 systems (ThermoFisher Scientific, Waltham, MA, USA). Buffer A consisted of 20 mM ammonium formate, adjusted to pH 10.0 with ammonia. Buffer B consisted of 0 mM ammonium format and 80% ACN, adjusted to pH 10.0. The peptides were dissolved in buffer A and 5%–45% buffer B for 40 min. The column maintained 1 mL/min at 30 °C. Six fractions were collected and dried in vacuum concentrators.

2.6. Nano-HPLC-MS/MS Analysis

The Orbitrap Fusion Lumos mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA) was used to analyze peptides, which were connected in series with EASY-nLC 1200 system. Solvent A was 0.1% formic acid aqueous solution, and solvent B was 0.1% formic acid ACN solution. The column Acclaim PepMap C18 (75 μm × 25 cm) flow rate was 200 nL/min. For each injection, 3 μL was loaded and separated with a 120 min gradient from 5% to 35% B.
The Orbitrap Lumos mass spectrometer was set to automatically switch between MS and MS/MS acquisition in data-dependent acquisition (DDA) mode for library generation, the parameters were as previously described [27]. The data-independent acquisition (DIA) mode for quantitative samples with 60 variable isolation windows overlapped at 1 m/z.

2.7. Data Analysis

Spectronaut X (Biognosys, Schlieren, Switzerland) was used to analyze the DDA data with the following settings: digestion enzyme: trypsin; fixed modification: carbamidomethyl; and variable modification: methionine oxidation. The false discovery rate (FDR) was set to 1% at the precursor threshold and protein threshold.
Spectronaut Pulsar (Biognosys, Schlieren, Switzerland) was used to analyze DIA data based on DDA data. The retention time prediction type was set to dynamic indexed retention time (iRT). Data filtered by 1% FDR. The decoy generation was configured as mutated in the feature identification. Quantification with all selected precursors passing through the filter. The number of major groups was calculated using the top 3 filtered peptides with an average passing 1% q-value cutoff. Proteins with q-value < 0.05 and fold change >1.2 (up) or <0.83 (down) were considered differentially expressed proteins (DEPs).

2.8. Bioinformatic Analysis

Functional annotations of proteins were obtained by searching against GO (Gene Ontology, http://geneontology.org/, accessed on 9 April 2020), KEGG (Kyoto Encyclopedia of Genes and Genomes, https://www.kegg.jp/, accessed on 9 April 2020), and COG (Cluster of Orthologous Groups of Proteins, https://www.ncbi.nlm.nih.gov/research/cog/webservices/, accessed on 9 April 2020) databases. The enrichment of DEPs was analyzed using the clusterProfiler package in RStudio (v2021.09.0+351, Boston, MA, USA), and q-value < 0.05 was considered significant. Furthermore, the PlantTFDB (Plant Transcription Factor database, http://planttfdb.gao-lab.org/, accessed on 9 April 2020) was used to predict the transcription factors and transcription factor families. All DEPs were then aligned to Cinnamomum miranthum (NCBI: txid337465) in NCBI with BLASTP for further analysis of the protein interactions. The protein co-expression and protein-protein interaction network of DEPs were predicted and constructed by String (http://string-db.org, accessed on 6 December 2021) and visualized by Cytoscape software (v3.9.0, Seattle, WA, USA).

3. Results

3.1. Linalool Content of Cinnamomum camphora Leaves at Different Stages

To investigate the change of isoprenoid biosynthesis in different leaf ages, we harvested the leaves of linalool-type Cinnamomum camphora (C. camphora) on the 15th, 25th, 35th, 45th, 55th, and 65th day after budding and extracted the essential oil from each stage (Figure 1a, Supplement Figure S2a). As expected, the main isoprenoid compound in linalool-type C. camphora was identified as linalool based on the comparison with the mass spectra of linalool oil. With the increase of leaf age, the contents of linalool were changed statistically and increased significantly over twofold in 65d compared with 15d (Figure 1b, Supplement Figure S2b). This result confirmed that isoprenoid biosynthesis is a continuous process in C. camphora, and its content will accumulate during leaf growth.

3.2. Quantitative Analysis and Functional Classification of Leaf Proteome

To elucidate the regulatory mechanisms of isoprenoid biosynthesis at different development stages in C. camphora, the total proteins were extracted from 15-day-old and 65-day-old leaves, respectively, for data-independent acquisition (DIA) analysis. A total of 60,938 precursors, 50,810 peptides, and 11,503 proteins were identified (Figure 1c), and over 83.08% were matched with at least two peptides (Figure 1d). All proteins were annotated by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and NCBI Eukaryotic Orthologous Groups (KOG) databases. In the GO database, 9653 proteins were annotated, and among the three categories (biological process, cellular component, and molecular function), most of the proteins were annotated in terms of biological processes (Supplement Figure S3a). As for KEGG pathway analysis, 5540 proteins were annotated, of which were mainly annotated in the category of metabolic (Supplement Figure S3b). Moreover, 9920 proteins were annotated into 25 functional classes in the KOG database (Supplement Figure S3c). Taken together, a total of 11,503 proteins were identified and 11,076 proteins were annotated based on the above three databases in our study (Supplement Figure S3d and Supplement Table S1). These results suggested that most proteins in the C. camphora leaf perform important metabolic functions.

3.3. Identification and Enrichment of Differentially Expressed Proteins

To explore the dynamic changes on the proteomic level during the leaf development, we considered proteins whose fold change >1.2 or <0.83 with a q-value <0.05 as differentially expressed proteins (DEPs). Based on this standard, 3186 DEPs were identified, of which 1245 proteins were up-regulated and 1941 proteins were down-regulated in 65d (Figure 2a, Table S2).
The GO enrichment analysis showed that most DEPs were enriched in 12 categories, including protein-chromophore linkage, photosynthesis, light-harvesting, photosynthesis, 3′-UTR-mediated mRNA destabilization, translation, photosynthetic-electron transport in photosystem II, cell redox homeostasis, glycolytic process, protein folding, ATP synthesis coupled proton transport, glycerol ether metabolic process, and chloroplast organization (Figure 2b). To KEGG enrichment analysis, a large proportion of DEPs was markedly enriched in the metabolic pathways (829 DEPs), followed by biosynthesis of secondary metabolites (Figure 2c). Further analysis of the metabolic pathways showed that 431 proteins were up-regulated and 398 proteins were down-regulated in 65d compared with 15d (Figure 2d). Taken together, these results suggested that many crucial biological processes such as metabolism, biosynthesis of secondary metabolites, and photosynthesis were significant changes at different development stages.

3.4. Proteins Related to Isoprenoid Biosynthesis

KEGG pathway enrichment analysis was performed among all DEPs to identify the proteins involved in isoprenoid biosynthesis. In the category of biosynthesis of secondary metabolites, 21 proteins were related to the isoprenoid biosynthesis pathway, of which 12 proteins were involved in methylerythritol phosphate and mevalonate. When compared to 15d, the expression levels of DXS, DXR, HDS, HDR, IPPI, FPPS, and VTE4 were considerably down-regulated in 65d. However, the expressions of MCT, MDS, AACT, GGPPS, VTE1, crtISO, PDS, AOG, NCED, ABA2, ZEP, wrbA, and alpha-terpineol synthase were significantly induced. Interestingly, in the MAS family, two DEPs were filtered, only one member was up-regulated, whereas the other was down-regulated in 65d (Figure 3 and Table S3). These results indicate that many proteins, such as MCT, MDS, ACCT, GGPPS, and alpha-terpineol synthase, may play pivotal roles in regulating the isoprenoid biosynthesis of C. camphora.

3.5. Analysis of Protein-Protein Interaction Network

The isoprenoid biosynthesis in plants is a sophisticated process adjusted by lots of regulators; hence, we predicted and constructed the co-expression network among the differentially expressed synthases. Among the 21 proteins related to isoprenoid biosynthesis, the DXR, IPPI, FPPS, VTE4, AACT, GGPPS, VTE1, crtISO, PDS, NCED, ABA2, ZEP, MCT, HDR, and HDS are likely involved in the same regulatory network. (Figure 4a). Notably, in the interaction network of proteome-wide DEPs, we found that 247 DEPs interacted with 11 transcription factors, including the families of BES1, C3H, FAR1, MYB, NF-YC, Nin-like, WRKY, Whirly, ZF-HD, and bHLH (Figure 4b). These results revealed that the complicated regulatory network of isoprenoid biosynthesis in C. camphora is adjusted by many conserved synthases, and also indicated that many transcription factors play important roles in regulating the growth and development of C. camphora. The function of the isoprenoid biosynthesis pathway is influenced both by the expression of isoprenoid synthases and the transcription factor regulation of leaf development.

4. Discussion

Linalool is an important secondary metabolite in linalool-type Cinnamomum camphora [5]. In our study, the linalool content was significantly increased during leaf development stages (Supplement Figure S2). This result suggested that the linalool is continuously synthesized and accumulated during the development of the leaf, which is consistent with the previous study [28].
The content of linalool in 65-day-old leaves was significantly higher than that in 15-day-old leaves. To elucidate the molecular mechanisms in proteomics underlying the regulation of isoprenoid biosynthesis at different development stages in C. camphora, we performed proteomic analysis of 15d and 65d leaves and identified 11,503 proteins, of which 11,076 proteins were annotated. Among these proteins, most proteins functioned in metabolism (Supplement Figure S3). Further analysis of differentially expressed proteins revealed that the expressions of 1245 proteins were induced; meanwhile, 1941 proteins were inhibited in 65d (Figure 2a). Previous research has verified that translation, RNA processing and DNA organization, energy generation, transport, and metabolic processes play important roles in regulating the leaf growth of Arabidopsis thaliana [29]. In our study, significant changes were also found in the processes of photosynthesis and metabolism at different development stages (Figure 2b,c).
We detected some essential enzymes related to the biosynthesis of isoprenoids in C. camphora. Based on KEGG pathway enrichment analysis, in the category of biosynthesis of secondary metabolites, 21 proteins participated in the biosynthesis of isoprenoids, as catalytic enzymes were expressed differentially at different stages (Figure 3, Table S3). Notably, the expression of MCT, MDS, and AACT was significantly induced in the 65d. Consistent with our result, a previous study has also verified that the overexpression of MDS promoted the accumulation of linalool content in Osmanthus fragrans [30]. By combining the metabolic analysis with the proteomic approach, we hypothesized that the expression changes of isoprenoid-related synthases at the protein level might be a major cause for the significant accumulation of linalool that we detected in the 65d.
The protein-protein interaction network was then constructed to illustrate the internal connection among the isoprenoid-related synthases. We found that the DXR, IPPI, FPPS, VTE4, AACT, GGPPS, VTE1, crtISO, PDS, NCED, ABA2, ZEP, MCT, HDR, and HDS were involved in the co-expression network, suggesting that these synthases constitute a complicated network and play crucial regulatory roles in the biosynthesis of isoprenoid. (Figure 4a). Moreover, in the proteome-wide protein-protein interaction analysis, we noticed a network that consisted of several transcription factors and other DEPs. Transcription factors, including BES1, bHLH, C3H, FAR1, MYB, NF-YC, Nin-like, WRKY, Whirly, and ZF-HD occupied the core position of the network and formed a sophisticated network by linking with many other DEPs (Figure 4b). This finding suggested that these transcription factors may act as candidate regulators in the leaf development of C. camphora. Consistent with this result, many studies have confirmed the important roles that BES1 [31], C3H [32], MYB [33], NF-YC [34], Nin-like, WRKY [35], ZF-HD [36], and bHLH [37,38] families play in plant growth and development. In addition, the FAR1 [39], WRKY [40,41], Whirly [42], and ZF-HD [43] families have been described as regulators of leaf senescence in previous research. The study demonstrated that the bZIP transcription factor HY5 is a positive regulator of DXS and DXR expression [44]. Some studies proved that WRKY, bHLH, and bZIP regulate the biosynthesis of isoprenoids in response to stresses [45,46,47,48]. Together, these results revealed that all these changes allow plants to balance the biosynthesis of secondary metabolites and the developmental processes during the growth of plants.

5. Conclusions

Our findings identified the candidate proteins that participated in isoprenoid biosynthesis and the potential transcription factor families, which may play key roles in the leaf development of linalool-type Cinnamomum camphora by proteomic analysis. These results implicate that the process of isoprenoid biosynthesis in C. camphora is regulated by a complicated network consisting of many conserved synthetases and leaf development by transcription factors regulation. This study provides valuable proteomic information for further investigation of the regulatory mechanisms underlying the isoprenoid metabolism of plants.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f13091487/s1, Figure S1: The mevalonate (MVA) and methylerythritol phosphate (MEP) pathway; Figure S2: Metabolite analyses of Cinnamomum camphora leaves; Figure S3: Functional characterization of leaf proteome in Cinnamomum camphora; Table S1: Expression and annotation of all leaf proteins; Table S2: Expression and annotation of differentially expressed proteins; Table S3: Expression of proteins related to isoprenoid biosynthesis.

Author Contributions

Conceptualization, methodology, investigation, writing original draft, and funding acquisition, C.Z.; conceptualization, methodology, data curation, writing original draft, validation, and visualization, F.Z.; investigation, resources, and methodology, S.C.; methodology and validation, K.W.; investigation and resources, G.X.; methodology, investigation, and data curation, X.L.; investigation, resources, and visualization, J.A.; conceptualization, methodology, investigation, resources, and supervision, K.L.; conceptualization, methodology, investigation, resources, supervision, writing review, and editing, L.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by Funds of Guangxi Key Laboratory of Special Non-wood Forest Cultivation and Utilization (no.19-B-04-01, JA-20-04-04, JA-20-04-07); Fundamental Research Funds for Guangxi Forestry Research Institute (no.201806, 202102); Guangxi Science and Technology Project (no.1517-06); Guangxi Special Expert Program.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Poudel, D.K.; Rokaya, A.; Ojha, P.K.; Timsina, S.; Satyal, R.; Dosoky, N.S.; Satyal, P.; Setzer, W.N. The Chemical Profiling of Essential Oils from Different Tissues of Cinnamomum camphora L. and Their Antimicrobial Activities. Molecules 2021, 26, 5132. [Google Scholar] [CrossRef]
  2. Wang, L.; Zhang, K.; Zhang, K.; Zhang, J.; Fu, J.; Li, J.; Wang, G.; Qiu, Z.; Wang, X.; Li, J. Antibacterial Activity of Cinnamomum camphora Essential Oil on Escherichia Coli During Planktonic Growth and Biofilm Formation. Front. Microbiol. 2020, 11, 561002. [Google Scholar] [CrossRef]
  3. Lv, C.; Hao, L.; Cui, X.; Yi, F.; Su, C. Study on the Composition and Physiological Activity of the Essential Oils and Extracts of Cinnamomum camphora Fruit. Chem. Biodivers. 2021, 18, e2100201. [Google Scholar] [CrossRef]
  4. Chen, C.; Zheng, Y.; Zhong, Y.; Wu, Y.; Li, Z.; Xu, L.-A.; Xu, M. Transcriptome Analysis and Identification of Genes Related to Terpenoid Biosynthesis in Cinnamomum camphora. BMC Genom. 2018, 19, 550. [Google Scholar] [CrossRef]
  5. Guo, X.; Cui, M.; Deng, M.; Liu, X.; Huang, X.; Zhang, X.; Luo, L. Molecular Differentiation of Five Cinnamomum camphora Chemotypes Using Desorption Atmospheric Pressure Chemical Ionization Mass Spectrometry of Raw Leaves. Sci. Rep. 2017, 7, 46579. [Google Scholar] [CrossRef]
  6. Tetali, S.D. Terpenes and Isoprenoids: A Wealth of Compounds for Global Use. Planta 2019, 249, 1–8. [Google Scholar] [CrossRef] [PubMed]
  7. Kim, M.-G.; Kim, S.-M.; Min, J.-H.; Kwon, O.-K.; Park, M.-H.; Park, J.-W.; Ahn, H.I.; Hwang, J.-Y.; Oh, S.-R.; Lee, J.-W.; et al. Anti-Inflammatory Effects of Linalool on Ovalbumin-Induced Pulmonary Inflammation. Int. Immunopharmacol. 2019, 74, 105706. [Google Scholar] [CrossRef] [PubMed]
  8. Guo, F.; Chen, Q.; Liang, Q.; Zhang, M.; Chen, W.; Chen, H.; Yun, Y.; Zhong, Q.; Chen, W. Antimicrobial Activity and Proposed Action Mechanism of Linalool Against Pseudomonas Fluorescens. Front. Microbiol. 2021, 12, 562094. [Google Scholar] [CrossRef] [PubMed]
  9. Elgendy, E.M.; Semeih, M.Y. Phyto—Monoterpene Linalool as Precursor to Synthesis Epoxides and Hydroperoxides as Anti Carcinogenic Agents via Thermal and Photo Chemical Oxidation Reactions. Arab. J. Chem. 2019, 12, 966–973. [Google Scholar] [CrossRef]
  10. Pu, X.; Dong, X.; Li, Q.; Chen, Z.; Liu, L. An Update on the Function and Regulation of Methylerythritol Phosphate and Mevalonate Pathways and Their Evolutionary Dynamics. J. Integr. Plant Biol. 2021, 63, 1211–1226. [Google Scholar] [CrossRef]
  11. Bongers, M.; Perez-Gil, J.; Hodson, M.P.; Schrübbers, L.; Wulff, T.; Sommer, M.O.; Nielsen, L.K.; Vickers, C.E. Adaptation of Hydroxymethylbutenyl Diphosphate Reductase Enables Volatile Isoprenoid Production. eLife 2020, 9, e48685. [Google Scholar] [CrossRef] [PubMed]
  12. Vranová, E.; Coman, D.; Gruissem, W. Network Analysis of the MVA and MEP Pathways for Isoprenoid Synthesis. Annu. Rev. Plant Biol. 2013, 64, 665–700. [Google Scholar] [CrossRef] [PubMed]
  13. Shen, T.; Qi, H.; Luan, X.; Xu, W.; Yu, F.; Zhong, Y.; Xu, M. The Chromosome-level Genome Sequence of the Camphor Tree Provides Insights into Lauraceae Evolution and Terpene Biosynthesis. Plant Biotechnol. J. 2021, 20, 244–246. [Google Scholar] [CrossRef] [PubMed]
  14. Hou, J.; Zhang, J.; Zhang, B.; Jin, X.; Zhang, H.; Jin, Z. Transcriptional Analysis of Metabolic Pathways and Regulatory Mechanisms of Essential Oil Biosynthesis in the Leaves of Cinnamomum camphora (L.) Presl. Front. Genet. 2020, 11, 598714. [Google Scholar] [CrossRef] [PubMed]
  15. Chen, C.; Zhong, Y.; Yu, F.; Xu, M. Deep Sequencing Identifies MiRNAs and Their Target Genes Involved in the Biosynthesis of Terpenoids in Cinnamomum camphora. Ind. Crops Prod. 2020, 145, 111853. [Google Scholar] [CrossRef]
  16. Ni, Z.; Han, X.; Chen, C.; Zhong, Y.; Xu, M.; Xu, L.; Yu, F. Integrating GC-MS and SsRNA-Seq Analysis to Identify Long Non-Coding RNAs Related to Terpenoid Biosynthesis in Cinnamomum camphora. Ind. Crops Prod. 2021, 171, 113875. [Google Scholar] [CrossRef]
  17. Yang, Z.; Xie, C.; Zhan, T.; Li, L.; Liu, S.; Huang, Y.; An, W.; Zheng, X.; Huang, S. Genome-Wide Identification and Functional Characterization of the Trans-Isopentenyl Diphosphate Synthases Gene Family in Cinnamomum camphora. Front. Plant Sci. 2021, 12, 708697. [Google Scholar] [CrossRef]
  18. Pappireddi, N.; Martin, L.; Wühr, M. A Review on Quantitative Multiplexed Proteomics. ChemBioChem 2019, 20, 1210–1224. [Google Scholar] [CrossRef]
  19. Wang, Y.; Sang, Z.; Xu, S.; Xu, Q.; Zeng, X.; Jabu, D.; Yuan, H. Comparative Proteomics Analysis of Tibetan Hull-Less Barley under Osmotic Stress via Data-Independent Acquisition Mass Spectrometry. GigaScience 2020, 9, giaa019. [Google Scholar] [CrossRef]
  20. Xie, X.; Yan, Y.; Liu, T.; Chen, J.; Huang, M.; Wang, L.; Chen, M.; Li, X. Data-Independent Acquisition Proteomic Analysis of Biochemical Factors in Rice Seedlings Following Treatment with Chitosan Oligosaccharides. Pestic. Biochem. Physiol. 2020, 170, 104681. [Google Scholar] [CrossRef]
  21. Cai, Y.-F.; Zhang, L.; Peng, L.-C.; Li, S.-F.; Song, J.; Xie, W.-J.; Wang, J.-H. Key Proteins and Metabolic Pathways Involved in 24-Epibrasionlide Improving Drought Tolerance of Rhododendron Delavayi Franch. Horticulturae 2021, 7, 501. [Google Scholar] [CrossRef]
  22. Riebel, M.; Fronk, P.; Distler, U.; Tenzer, S.; Decker, H. Proteomic Profiling of German Dornfelder Grape Berries Using Data-Independent Acquisition. Plant Physiol. Biochem. 2017, 118, 64–70. [Google Scholar] [CrossRef] [PubMed]
  23. Chen, M.; Yan, T.; Ji, L.; Dong, Y.; Sidoli, S.; Yuan, Z.; Cai, C.; Chen, J.; Tang, Y.; Shen, Q.; et al. Comprehensive Map of the Artemisia Annua Proteome and Quantification of Differential Protein Expression in Chemotypes Producing High versus Low Content of Artemisinin. Proteomics 2020, 20, 1900310. [Google Scholar] [CrossRef] [PubMed]
  24. Suleiman, W.B. In Vitro Estimation of Superfluid Critical Extracts of Some Plants for Their Antimicrobial Potential, Phytochemistry, and GC–MS Analyses. Ann. Clin. Microbiol. Antimicrob. 2020, 19, 29. [Google Scholar] [CrossRef] [PubMed]
  25. Korpinen, R.I.; Välimaa, A.-L.; Liimatainen, J.; Kunnas, S. Essential Oils and Supercritical CO2 Extracts of Arctic Angelica (Angelica archangelica L.), Marsh Labrador Tea (Rhododendron tomentosum) and Common Tansy (Tanacetum vulgare)—Chemical Compositions and Antimicrobial Activities. Molecules 2021, 26, 7121. [Google Scholar] [CrossRef] [PubMed]
  26. Smith, P.K.; Krohn, R.I.; Hermanson, G.T.; Mallia, A.K.; Gartner, F.H.; Provenzano, M.D.; Fujimoto, E.K.; Goeke, N.M.; Olson, B.J.; Klenk, D.C. Measurement of Protein Using Bicinchoninic Acid. Anal. Biochem. 1985, 150, 76–85. [Google Scholar] [CrossRef]
  27. Yang, Y.; Dong, A.; Zenda, T.; Liu, S.; Liu, X.; Wang, Y.; Li, J.; Duan, H. DIA (Data Independent Acquisition) Proteomic Based Study on Maize Filling-Kernel Stage Drought Stress-Responsive Proteins and Metabolic Pathways. Biotechnol. Biotechnol. Equip. 2020, 34, 1198–1214. [Google Scholar] [CrossRef]
  28. Zhang, T.; Yang, H.; Wen, S.; Qiu, F.; Liu, X. Effects of Harvest Season and Storage Time on the Essential Oil of the Linalool Chemotype of Cinnamomum camphora. J. Essent. Oil Bear. Plants 2019, 22, 1379–1385. [Google Scholar] [CrossRef]
  29. Mergner, J. Proteomic and Transcriptomic Profiling of Aerial Organ Development in Arabidopsis. Sci. Data 2020, 7, 334. [Google Scholar] [CrossRef]
  30. Han, Y.; Wang, H.; Wang, X.; Li, K.; Dong, M.; Li, Y.; Zhu, Q.; Shang, F. Mechanism of Floral Scent Production in Osmanthus fragrans and the Production and Regulation of Its Key Floral Constituents, β-Ionone and Linalool. Hortic Res. 2019, 6, 106. [Google Scholar] [CrossRef] [Green Version]
  31. Saito, M.; Kondo, Y.; Fukuda, H. BES1 and BZR1 Redundantly Promote Phloem and Xylem Differentiation. Plant Cell Physiol. 2018, 59, 590–600. [Google Scholar] [CrossRef] [PubMed]
  32. Kim, D.W.; Jeon, S.J.; Hwang, S.M.; Hong, J.C.; Bahk, J.D. The C 3 H-Type Zinc Finger Protein GDS1/C3H42 Is a Nuclear-Speckle-Localized Protein That Is Essential for Normal Growth and Development in Arabidopsis. Plant Sci. 2016, 250, 141–153. [Google Scholar] [CrossRef] [PubMed]
  33. Hou, H.; Zhang, C.; Hou, X. Cloning and Functional Analysis of BcMYB101 Gene Involved in Leaf Development in Pak Choi (Brassica rapa ssp. Chinensis). Int. J. Mol. Sci. 2020, 21, 2750. [Google Scholar] [CrossRef]
  34. Palmeros-Suárez, P.A.; Massange-Sánchez, J.A.; Martínez-Gallardo, N.A.; Montero-Vargas, J.M.; Gómez-Leyva, J.F.; Délano-Frier, J.P. The Overexpression of an Amaranthus Hypochondriacus NF-YC Gene Modifies Growth and Confers Water Deficit Stress Resistance in Arabidopsis. Plant Sci. 2015, 240, 25–40. [Google Scholar] [CrossRef]
  35. Chen, J.; Nolan, T.; Ye, H.; Zhang, M.; Tong, H.; Xin, P.; Chu, J.; Chu, C.; Li, Z.; Yin, Y. Arabidopsis WRKY46, WRKY54 and WRKY70 Transcription Factors Are Involved in Brassinosteroid-Regulated Plant Growth and Drought Response. Plant Cell 2017, 29, 1425–1439. [Google Scholar] [CrossRef] [PubMed]
  36. Hong, S.-Y.; Kim, O.-K.; Kim, S.-G.; Yang, M.-S.; Park, C.-M. Nuclear Import and DNA Binding of the ZHD5 Transcription Factor Is Modulated by a Competitive Peptide Inhibitor in Arabidopsis. J. Biol. Chem. 2011, 286, 1659–1668. [Google Scholar] [CrossRef]
  37. Jang, S.; Cho, J.-Y.; Do, G.-R.; Kang, Y.; Li, H.-Y.; Song, J.; Kim, H.-Y.; Kim, B.-G.; Hsing, Y.-I. Modulation of Rice Leaf Angle and Grain Size by Expressing OsBCL1 and OsBCL2 under the Control of OsBUL1 Promoter. Int. J. Mol. Sci. 2021, 22, 7792. [Google Scholar] [CrossRef]
  38. Seo, H.; Kim, S.-H.; Lee, B.-D.; Lim, J.-H.; Lee, S.-J.; An, G.; Paek, N.-C. The Rice Basic Helix–Loop–Helix 79 (OsbHLH079) Determines Leaf Angle and Grain Shape. Int. J. Mol. Sci. 2020, 21, 2090. [Google Scholar] [CrossRef]
  39. Xie, Y.; Ma, M.; Liu, Y.; Wang, B.; Wei, H.; Kong, D.; Wang, H. Arabidopsis FHY3 and FAR1 Function in Age Gating of Leaf Senescence. Front. Plant Sci. 2021, 12, 770060. [Google Scholar] [CrossRef]
  40. Gu, L.; Dou, L.; Guo, Y.; Wang, H.; Li, L.; Wang, C.; Ma, L.; Wei, H.; Yu, S. The WRKY Transcription Factor GhWRKY27 Coordinates the Senescence Regulatory Pathway in Upland Cotton (Gossypium hirsutum L.). BMC Plant Biol. 2019, 19, 116. [Google Scholar] [CrossRef] [Green Version]
  41. Huang, R.; Liu, D.; Huang, M.; Ma, J.; Li, Z.; Li, M.; Sui, S. CpWRKY71, a WRKY Transcription Factor Gene of Wintersweet (Chimonanthus praecox), Promotes Flowering and Leaf Senescence in Arabidopsis. Int. J. Mol. Sci. 2019, 20, 5325. [Google Scholar] [CrossRef] [PubMed]
  42. Janack, B.; Sosoi, P.; Krupinska, K.; Humbeck, K. Knockdown of WHIRLY1 Affects Drought Stress-Induced Leaf Senescence and Histone Modifications of the Senescence-Associated Gene HvS40. Plants 2016, 5, 37. [Google Scholar] [CrossRef] [PubMed]
  43. Wu, L.; Li, M.; Tian, L.; Wang, S.; Wu, L.; Ku, L.; Zhang, J.; Song, X.; Liu, H.; Chen, Y. Global Transcriptome Analysis of the Maize (Zea mays L.) Inbred Line 08LF during Leaf Senescence Initiated by Pollination-Prevention. PLoS ONE 2017, 12, e0185838. [Google Scholar] [CrossRef]
  44. Chenge-Espinosa, M.; Cordoba, E.; Romero-Guido, C.; Toledo-Ortiz, G.; León, P. Shedding Light on the Methylerythritol Phosphate (MEP)-Pathway: Long Hypocotyl 5 (HY5)/Phytochrome-Interacting Factors (PIFs) Transcription Factors Modulating Key Limiting Steps. Plant J. 2018, 96, 828–841. [Google Scholar] [CrossRef] [PubMed]
  45. Schluttenhofer, C.; Yuan, L. Regulation of Specialized Metabolism by WRKY Transcription Factors. Plant Physiol. 2015, 167, 295–306. [Google Scholar] [CrossRef] [PubMed]
  46. Fu, J.; Liu, Q.; Wang, C.; Liang, J.; Liu, L.; Wang, Q. ZmWRKY79 Positively Regulates Maize Phytoalexin Biosynthetic Gene Expression and Is Involved in Stress Response. J. Exp. Bot. 2018, 69, 497–510. [Google Scholar] [CrossRef]
  47. Okada, A.; Okada, K.; Miyamoto, K.; Koga, J.; Shibuya, N.; Nojiri, H.; Yamane, H. OsTGAP1, a bZIP Transcription Factor, Coordinately Regulates the Inductive Production of Diterpenoid Phytoalexins in Rice. J. Biol. Chem. 2009, 284, 26510–26518. [Google Scholar] [CrossRef]
  48. Yamamura, C.; Mizutani, E.; Okada, K.; Nakagawa, H.; Fukushima, S.; Tanaka, A.; Maeda, S.; Kamakura, T.; Yamane, H.; Takatsuji, H.; et al. Diterpenoid Phytoalexin Factor, a bHLH Transcription Factor, Plays a Central Role in the Biosynthesis of Diterpenoid Phytoalexins in Rice. Plant J. 2015, 84, 1100–1113. [Google Scholar] [CrossRef]
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Figure 1. Metabolite and proteome analyses of Cinnamomum camphora leaves. (a) Phenotypes of 15-day-old and 65-day-old leaves. (b) Analysis of linalool contents. Values are the means ± SD (n = 3). The significant difference was analyzed by the t-test (* p-value < 0.05). (c) Protein identification. According to the filtering standard of q-value < 0.01. (d) Analysis of peptide distribution.
Figure 1. Metabolite and proteome analyses of Cinnamomum camphora leaves. (a) Phenotypes of 15-day-old and 65-day-old leaves. (b) Analysis of linalool contents. Values are the means ± SD (n = 3). The significant difference was analyzed by the t-test (* p-value < 0.05). (c) Protein identification. According to the filtering standard of q-value < 0.01. (d) Analysis of peptide distribution.
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Figure 2. Analysis of differentially expressed proteins at different development stages. (a) Volcano plot of DEPs between 15d and 65d. Red: up-regulated proteins in the 65d (q-value < 0.05, FC > 1.2). Blue: down-regulated proteins in the 65d (q-value < 0.05, FC < 0.83). (b) GO enrichment analysis of DEPs. (c) KEGG pathway enrichment analysis of DEPs. (d) Expression profiles of DEPs in the metabolic pathway. Red: up-regulated proteins in the 65d. Purple: down-regulated proteins in the 65d.
Figure 2. Analysis of differentially expressed proteins at different development stages. (a) Volcano plot of DEPs between 15d and 65d. Red: up-regulated proteins in the 65d (q-value < 0.05, FC > 1.2). Blue: down-regulated proteins in the 65d (q-value < 0.05, FC < 0.83). (b) GO enrichment analysis of DEPs. (c) KEGG pathway enrichment analysis of DEPs. (d) Expression profiles of DEPs in the metabolic pathway. Red: up-regulated proteins in the 65d. Purple: down-regulated proteins in the 65d.
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Figure 3. Identification of candidate proteins related to the isoprenoid biosynthesis pathway. The pathway shows the subset of metabolites and enzymes that constitute the process of isoprenoid biosynthesis. Red: up-regulated proteins in the 65d. Green: down-regulated proteins in the 65d. Yellow: in the MAS family, only one member was up-regulated, whereas the other was down-regulated in 65d. AACT, Acetyl-CoA C-acetyltransferase; IPPI, isopentenyl diphosphate isomerase; FPPS, farnesyl diphosphate synthase; DXS, 1-deoxy-D-xylulose 5-phosphate synthase; DXR, 1-deoxy-D-xylulose 5-phosphate reductoisomerase; MCT, 2-C-methyl-D-erythritol 4-phosphate cytidylyltransferase; MDS, 2-Cmethyl-D-erythritol 2,4-cyclodiphosphate synthase; HDS, 4-hydroxy-3-methylbut-2-enyldiphosphate synthase; HDR, 4-hydroxy-3-methylbut-2-enlyldiphosphate reductase; MAS, momilactone-A synthase; VTE1, tocopherol cyclase; VTE4, γ-tocopherol methyltransferase; wrbA, NADPH dehydrogenase; PDS, 15-cis-phytoene desaturase; crtISO, prolycopene isomerase; ZEP, zeaxanthin epoxidase; NCED, 9-cis-epoxycarotenoid dioxygenase; ABA2, xanthoxin dehydrogenase; AOG, abscisate beta-glucosyltransferase. GAP, D-glyceraldehyde 3-phosphate; DXP, 1-deoxy-D-xylulose 5-phosphate; MEP, methylerythritol phosphate; CDP-ME, 4-(cytidine 5′-diphospho)-2-C-methyl-D-erythritol; CDP-MEP, 2-phospho-4-(cytidine 5′-diphospho)-2-C-methyl-D-erythritol; MEcPP, 2-C-methyl-D-erythritol-2,4-cyclodiphosphate; HMBPP, 4-hydroxy-3-methylbut-2-enyldiphosphate; DMAPP, dimethylallyl diphosphate; GPP, geranyl diphosphate; Acetyl-CoA, acetyl-coenzyme A; Aceto-acetyl-CoA, Aceto-acetyl-coenzyme A; IPP, isopentenyl diphosphate; FPP, farnesyl diphosphate; GFPP, geranylfarnesyl diphosphate; GGPP, geranylgeranyl diphosphate.
Figure 3. Identification of candidate proteins related to the isoprenoid biosynthesis pathway. The pathway shows the subset of metabolites and enzymes that constitute the process of isoprenoid biosynthesis. Red: up-regulated proteins in the 65d. Green: down-regulated proteins in the 65d. Yellow: in the MAS family, only one member was up-regulated, whereas the other was down-regulated in 65d. AACT, Acetyl-CoA C-acetyltransferase; IPPI, isopentenyl diphosphate isomerase; FPPS, farnesyl diphosphate synthase; DXS, 1-deoxy-D-xylulose 5-phosphate synthase; DXR, 1-deoxy-D-xylulose 5-phosphate reductoisomerase; MCT, 2-C-methyl-D-erythritol 4-phosphate cytidylyltransferase; MDS, 2-Cmethyl-D-erythritol 2,4-cyclodiphosphate synthase; HDS, 4-hydroxy-3-methylbut-2-enyldiphosphate synthase; HDR, 4-hydroxy-3-methylbut-2-enlyldiphosphate reductase; MAS, momilactone-A synthase; VTE1, tocopherol cyclase; VTE4, γ-tocopherol methyltransferase; wrbA, NADPH dehydrogenase; PDS, 15-cis-phytoene desaturase; crtISO, prolycopene isomerase; ZEP, zeaxanthin epoxidase; NCED, 9-cis-epoxycarotenoid dioxygenase; ABA2, xanthoxin dehydrogenase; AOG, abscisate beta-glucosyltransferase. GAP, D-glyceraldehyde 3-phosphate; DXP, 1-deoxy-D-xylulose 5-phosphate; MEP, methylerythritol phosphate; CDP-ME, 4-(cytidine 5′-diphospho)-2-C-methyl-D-erythritol; CDP-MEP, 2-phospho-4-(cytidine 5′-diphospho)-2-C-methyl-D-erythritol; MEcPP, 2-C-methyl-D-erythritol-2,4-cyclodiphosphate; HMBPP, 4-hydroxy-3-methylbut-2-enyldiphosphate; DMAPP, dimethylallyl diphosphate; GPP, geranyl diphosphate; Acetyl-CoA, acetyl-coenzyme A; Aceto-acetyl-CoA, Aceto-acetyl-coenzyme A; IPP, isopentenyl diphosphate; FPP, farnesyl diphosphate; GFPP, geranylfarnesyl diphosphate; GGPP, geranylgeranyl diphosphate.
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Figure 4. Analysis of protein-protein interaction network. (a) Protein-protein co-expression network of differentially expressed candidate synthases related to isoprenoid synthesis. (b) Protein-protein interaction network of differentially expressed transcription factors. Circles represent differentially expressed transcription factors, and triangles represent other differentially expressed proteins.
Figure 4. Analysis of protein-protein interaction network. (a) Protein-protein co-expression network of differentially expressed candidate synthases related to isoprenoid synthesis. (b) Protein-protein interaction network of differentially expressed transcription factors. Circles represent differentially expressed transcription factors, and triangles represent other differentially expressed proteins.
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Zhu, C.; Zhang, F.; Chen, S.; Wang, K.; Xiang, G.; Liang, X.; An, J.; Li, K.; Liu, L. Proteomics Analysis and Identification of Proteins Related to Isoprenoid Biosynthesis in Cinnamomum camphora (L.) Presl. Forests 2022, 13, 1487. https://doi.org/10.3390/f13091487

AMA Style

Zhu C, Zhang F, Chen S, Wang K, Xiang G, Liang X, An J, Li K, Liu L. Proteomics Analysis and Identification of Proteins Related to Isoprenoid Biosynthesis in Cinnamomum camphora (L.) Presl. Forests. 2022; 13(9):1487. https://doi.org/10.3390/f13091487

Chicago/Turabian Style

Zhu, Changsan, Fan Zhang, Silin Chen, Kun Wang, Ganju Xiang, Xiaojing Liang, Jiacheng An, Kaixiang Li, and Li Liu. 2022. "Proteomics Analysis and Identification of Proteins Related to Isoprenoid Biosynthesis in Cinnamomum camphora (L.) Presl" Forests 13, no. 9: 1487. https://doi.org/10.3390/f13091487

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