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Essay

Identification of Nutritional Ingredients and Medicinal Components of Hawk Tea and Insect Tea Using Widely Targeted Secondary Metabolomics

1
The Key Laboratory of Plant Resources Conservation and Germplasm Innovation in Mountainous Region (Ministry of Education), College of Life Sciences/Institute of Agro-Bioengineering, Guizhou University, Guiyang 550025, China
2
College of Tea Science, Institute of Plant Health & Medicine, Guizhou University, Guiyang 550025, China
*
Author to whom correspondence should be addressed.
Horticulturae 2023, 9(4), 457; https://doi.org/10.3390/horticulturae9040457
Submission received: 23 February 2023 / Revised: 26 March 2023 / Accepted: 31 March 2023 / Published: 2 April 2023
(This article belongs to the Section Medicinals, Herbs, and Specialty Crops)

Abstract

:
In this study, the metabolites in insect tea and hawk tea were analyzed by ultra-high performance liquid chromatography–triple quadrupole mass spectrometry. We found 49 metabolites in insect tea and hawk tea that can be used as key active components in traditional Chinese medicine, as well as 98 metabolites that can be used as active components of pharmaceutical preparations for the treatment of cancers, hypertension, cardiovascular diseases, etc. Comparative analysis found that insect tea and hawk tea had significant differences in their metabolic profiles. Insect tea contains more metabolites beneficial to human health than hawk tea; insect tea also has higher antioxidant activity in vitro than hawk tea. The results of this study will contribute to the development of new health foods using insect tea.

1. Introduction

China is the largest tea producer and consumer in the world, with a long history of tea production and a wide variety of teas [1]. Recently, “non-tea tea” has been the focus of widespread attention in this society owing to its unique quality characteristics and medicinal and health care functions. Hawk tea is made by drying the twigs and leaves of leopard skin camphor (Litsea coreana Levl.). As a non-tea tea, it has antioxidant, antibacterial, hypoglycemic and lipid-lowering, anti-inflammatory, and immunomodulatory effects [2]. Insect tea is a unique drink in China and an important part of Chinese tea culture. [3]. The most famous insect tea is Qianchong tea, which is native to the north and southeast of Guizhou province. It is dark brown in appearance and has round grains. Guizhou insect tea is a tea product made from special insects (Lepidopteran moth family rice borer, purple-spotted grain borer, gray straight borer, yellow-ringed bush borer, and weave moth family rice scorpion moth) that eat special plant leaves, such as leopard skin camphor and three Ye Hai tang (Malus sieboldii (Regel) Rehd.)), excrete feces, and are made through a series of processing processes [4]. Compared with ordinary tea, the components of insect tea have higher nutritional value and stronger antioxidant effects [5,6,7]. Insect tea contains amino acids, proteins, polyphenols, flavonoids, and other active ingredients; these components have health and medicinal functions. [8,9,10,11]. Animal experiments have shown that the antioxidant capacity of insect tea is higher than that of hawk tea [12]. Furthermore, the antioxidant activity of insect tea prevents HCl/ethanol oxidative stress-induced gastric mucosal injury in mice [13]. These polyphenols in insect tea also increase lipid peroxidation by reducing enzymatic activity in the body, resulting in antimutagenic and anticancer effects. In addition, studies have shown that insect tea has some effect on lowering blood sugar and blood pressure [14,15,16]. Feng [17] has also shown that insect tea can promote the apoptosis of TCA8113 human tongue squamous cell carcinoma cells [18]. Research by Suo [19] also found that insect tea has a strong effect against mouse buccal mucosal cancer. A study by Zhang [20] showed that insect tea has a positive effect on inhibiting the growth of MCF-7 human breast cancer cells.
In the last decade, metabolomics has made a breakthrough in the study of medicinal plants [7]. The total number of metabolites in the plant kingdom is approximately 200,000; however, most of them remain unidentified. [21,22,23]. Not only do these metabolites have critical functions in plant growth and development, but they also help plants to adapt to abiotic and biotic stresses [24,25,26] and serve as sources of important nutrients and medicines for humans [23]. These metabolites usually vary between different varieties of plants. Therefore, it is of interest to comprehensively compare and identify the metabolites in different species of plants. In recent years, insect tea has been found to have the health benefits of tea and the medicinal functions of Chinese medicine; its added value increases with storage time. However, the research on insect tea generally focuses on the types of insect tea and the production technology of insect tea beverages. [27,28]. A metabolomic method based on UHPLC-QqQ-MS was used in this study to enable the systematic identification and quantification of hawk tea (HT) and insect tea (IT) metabolites. In addition, the analysis of the key medicinal components in HT and IT is of great interest for the study, especially those that form the main active ingredients of traditional Chinese medicine (TCM) and the treatment of diseases. More importantly, metabolite content, metabolic pathway, and hierarchical clustering analysis in HT and IT were compared to identify different functional components associated with bioactivity and health benefits in tea and IT. These results provide new evidence that insect tea can improve human health.

2. Materials and Methods

2.1. Plant Materials

HT (HT1, HT2, and HT3 young leaves from three L. coreana var were picked) was made from the young leaves of leopard-skin camphor from Guizhou Province by frying, killing, greening, and drying. IT (IT1, IT2, IT3) IT and HT were refined, which involved preliminarily sieving by a 14-mesh sample sieve to remove impurities, re-screening with a 35-mesh sample sieve to remove dust, sterilizing by ultraviolet light for 15 min, and drying in an oven at 50 °C. These steps render the tea ready for use with constant weight. The HT was made from the young leaves of the camphor tree by frying and drying [29]. The materials were provided by the Guizhou Chishui Insect Tea Industry Base.

2.2. Sample Preparation and Extraction

The Metware Biotechnology Co., Ltd. (Wuhan, China) provided the methods to prepare and extract the samples as previously described [30,31].

2.3. Extraction of Dried Hawk Tea Leaves Metabolites

(1)
Samples frozen at −80 °C were thawed.
(2)
The sample was mixed and 50 mg was placed in a 2 mL centrifuge tube.
(3)
A total of 1.2 mL of an internal standard extract in 70% methanol was added. Scroll for 15 min.
(4)
Centrifuged for 3 min at 12,000 rpm at 4 °C. A microporous filter membrane (0.22 μm) was used to filter the supernatant, which was placed in a flask designed for use with tandem mass spectrometry combined with liquid chromatography (LC-MS/MS), and stored at −80 °C until use.

2.4. Extraction of Insect Tea Metabolites

(1)
The sample was removed from storage at −80 °C and thawed on ice.
(2)
After mixing, 20 (±1 mg) of the sample was placed in a 2 mL centrifuge tube.
(3)
An internal standard was added in a volume of 400 μL of 70% methanol and vortexed for 3 min.
(4)
The sample was then sonicated for 10 min in an ice water bath and incubated stationary for 30 min at −20 °C.
(5)
The sample was centrifuged for 10 min at 12,000 rpm at 4 °C and the supernatant was collected. A volume of 300 μL was added to a new centrifuge tube.
(6)
The sample was finally centrifuged for 3 min at 12,000 rpm at 4 °C and the supernatant was collected for analysis.

2.5. Ultra Performance Liquid Chromatography (UPLC) CONDITIONS

The sample extracts were analyzed using an ultra-performance liquid chromatography–electrospray ionization tandem mass spectro-metric (UPLC-ESI-MS/MS) system (SHIMADZU NexeraX2; Shimadzu, Kyoto, Japan) to analyze the sample extracts. The MS was an Applied Biosystems 4500 QTRAP® (Thermo Fisher Scientific, Waltham, MA, USA). The column was an Agilent SB-C18 (1.8 µm, 2.1 mm × 100 mm) (Agilent Technologies, Santa Clara, CA, USA). Both mobile phases contained 0.1% formic acid. Solvent A was composed of pure water, while solvent B was composed of acetonitrile. The UPLC utilized a gradient program with a low velocity of 0.35 mL per min and starting conditions of 95% A and 5% B. A linear gradient to 5% A, 95% B was programmed to take place within 9 min and then maintained for 1 min. A subsequent composition of 95% A, 5.0% B was adjusted within 1.1 min and maintained for 2.9 min. The column oven was set to 40 °C. A volume of 4 µL of sample was injected. The effluent was then connected to an ESI-triple quadrupole–linear ion trap (QTRAP)-MS.

2.6. ESI-Q TRAP-MS/MS

Linear Ion Trap (LIT) and triple quadrupole (QQQ) scans were acquired on a triple quadrupole–linear ion trap (QTRAP) mass spectrometer (AB4500 QTRAP® UPLC-MS/MS System; Sciex, Framingham, MA, USA) equipped with an ESI Turbo Ion-Spray interface and operated in positive and negative ion modes. It was controlled using Analyst 1.6.3 software (AB Sciex). The ESI source operation parameters included an ion source, turbo spray, source temperature of 550 °C, and ion spray voltage (IS) of 5500 V (positive ion mode)/−4500 V (negative ion mode); ion source gas I (GSI), gas II (GSII), and curtain gas (CUR) were set at 50, 60, and 25 psi, respectively. The collision-activated dissociation (CAD) was high. The instrument was tuned and the mass calibrated with 10 and 100 μmol/L of polypropylene glycol (PPG) solutions in the QQQ and LIT modes, respectively. QQQ scans were acquired as multiple reaction monitoring (MRM) experiments with collision gas (nitrogen) set to medium. Declustering potential (DP) and collision energy (CE) for individual MRM transitions were conducted with the additional optimization of DP and CE. A specific set of MRM transitions were monitored for each period based on the metabolites that eluted within this period.

2.7. Quantitative and Qualitative Determination of Metabolites

A self-built MetWare database (MWDB) provided by the Wuhan MetWare Biotechnology Co., Ltd. (Wuhan, China) was used to qualitatively analyze the metabolites. The metabolites from the primary and secondary MS data were annotated using the public metabolite database and MWDB as previously described [32]. To ensure the accuracy of the metabolite annotations, interference signals were first excluded, including the repetitive signals of fragment ions, the repeated signals of the K+, NH4+, and Na+ ions, and the isotope signal. The metabolite structure was analyzed in reference to the self-built MWDB and the mass spectroscopy public databases that exist, including KNAPSAcK (http://kanaya.naist.jp/KNApSAcK) (accessed on 9 November 2022), Human Metabolome Database (HMDB; http://www.hmdb.ca) (accessed on 11 November 2022), MassBank (http://www.massbank.jp) (accessed on 23 November 2022), METLIN (http://metlin.scripps.edu/index.php) (accessed on 3 December 2022), and MoTo DB (http://www.ab.wur.nl/moto) (accessed on 10 December 2022) [33]. The QQQ MS was utilized in the multiple reaction monitoring (MRM) mode to quantitatively analyze the metabolites as described by Hu [22].

2.8. Identification of the Key Active Ingredients in Hawk Tea and Insect Tea That Were Used in Traditional Chinese Medicines

A TCMSP database query was used to analyze all the metabolites in HT and IT that were isolated from the UHPLC-QqQ-MS [34]. An additional analysis was performed on the metabolites obtained to determine whether they were members of key active ingredients. The key parameters examined included the oral bioavailability (OB) ≥ 5% and the drug-likeness (DL) ≥ 0.14. If the metabolites met these standards, they were thought to be key active ingredients from TCM. The TCMSP database was also used to examine information on related diseases and targets of the metabolites identified.

2.9. Identification of the Active Pharmaceutical Ingredients for Seven Major Types of Disease Resistance in Hawk Tea and Insect Tea

The antitumor/cancer ingredients were identified by querying all the metabolites that were in the Anticancer Herbs Database of Systems Pharmacology, i.e., in the TCMSP analytical platform [34]. This platform is also known as the Cancer HSP and contains 2439 herbal medicines with activities against cancer, as well as 3575 ingredients with these properties. The metabolites obtained that were also contained in the Cancer HSP database were considered to be ingredients with potential against cancers and tumors. Efforts were also made to identify compounds that could act against cardiovascular disease, diabetes, atherosclerosis, hypertension, and thrombotic disease. These terms were entered in the menu for the TCMSP database under the disease name and the ingredients related to each type of disease resistance were downloaded. Finally, the active pharmaceutical ingredients from HT and IT were identified by a comparison of all the metabolites from the UHPLC-QqQ-MS analysis that matched the seven types of resistance to disease.

2.10. Principal Component Analysis

The data were scaled for unit variance and then used to conduct an unsupervised principal component analysis (PCA) using the statistics function prcomp within R (www.r-project.org) (accessed on 22 December 2022).

2.11. Hierarchical Cluster Analysis and Pearson Correlation Coefficients

The results of a hierarchical cluster analysis (HCA) conducted on the metabolites and samples were shown as heatmaps with dendrograms. In addition, Pearson correlation coefficients (PCC) between samples were calculated using the cor function in R and displayed as heatmaps. The R package Complex-Heatmap was used to perform both PCC and HCA. The metabolites were subjected to unit variance scaling for the HCA, which means that they were displayed as a color spectrum based on normalized signal intensities.

2.12. Differential Metabolite Analysis

Absolute log2FC (fold change) ≥ 1 and variable importance in the projection (VIP) ≥ 1 were used to select the metabolites that were significantly regulated between groups. The VIP values were extracted from the result of an orthogonal projection to latent structures discriminant analysis (OPLS-DA), which also contained permutation and score plots. The R package MetaboAnalystR was used to generate the analysis. The data were mean-centered and log transformed (log2) before the OPLS-DA was performed. Overfitting was avoided by performing a test of 200 permutations. Metabolites that were identified were annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) Compound database (http://www.kegg.jp/kegg/compound/) (accessed on 5 January 2023) and then mapped to the KEGG Pathway database (http://www.kegg.jp/kegg/pathway.html). (accessed on 7 January 2023) Significantly regulated metabolites that mapped to the pathways were then fed into the metabolite sets enrichment analysis (MSEA). The results of p-values following a hypergeometric test determined their significance.

2.13. Determination of In Vitro Antioxidant Activity

DPPH free radical scavenging activities of hawk tea and insect tea extracts were determined by Dadwal [35] and absorbance was recorded at 518 nm. The superoxide anion scavenging activity of the extract was determined using the method described by Jie [36] and the absorbance was recorded at 299 nm. The results used Vc as a reference and were shown by percentage suppression and semi-maximum suppression concentration (IC50). Potassium ferricyanide, as a strong oxidant and REDOX active metal, produced active metal ions such as superoxide ions in the biological system, which caused oxidative stress. The reducing capacity of the extract was determined by Gulcin [37] and the absorbance of the reaction mixture was determined at 700 nm. All experiments had 3 replicates.

3. Results and Discussion

3.1. Detection of Metabolites in HT and IT

To identify and more effectively understand the differences in metabolites between HT and IT, they were analyzed with an UHPLC-QqQ-MS. A total of 1056 metabolites were identified. This included 220 flavonoids, 162 lipids, 160 phenolic acids, 126 other metabolites, 84 organic acids, 82 amino acids, 82 alkaloids, 48 lignans and coumarins, 59 nucleotides and their derivatives, 22 terpenoids, and 11 tannins (Figure 1). The differential metabolites were screened using a volcano-shaped plot that was based on absolute Log2FC (fold change) ≥ 2 and VIP ≥ 1. The success of these techniques indicated that the method of widely targeting metabolomics based on UHPLC-QqQ-MS was an effective and powerful method to comprehensively identify plant metabolites. Nearly 1000 metabolites (953) were identified from IT. In addition, a similar number of metabolites (965) were identified from HT. The phenolic acids, flavonoids, and lipids were the primary contributors to the differences in the number of metabolites between HT and IT. Surprisingly, of the 1056 metabolites identified, 826 were found in both HT and IT; 103 and 91 metabolites were unique to HT and IT, respectively. These findings strongly suggested that the HT and IT metabolites were conserved and diverse. These metabolites are specific to HT and IT and are listed in Supplementary Table S1.

3.2. Identification of the Key Active Ingredients That Belong to TCMs in HT and IT

The high contents of bioactive flavonoids in HT and IT are the primary reason that they are currently considered as strong contributors to human health, owing to their use as excellent functional food sources [38,39]. However, the possibility that metabolites, in addition to flavonoids from these plants, could contribute to promoting human health remains to be elucidated. To determine whether there were additional metabolites that could contribute to human health, we queried the metabolites that had been identified in the TCMSP database to identify the key active ingredients from HT and IT that could promote human health. The results indicated that 170 (Supplementary Table S2) out of 1056 metabolites identified were found to be chemical components of TCMs. The parameters DL ≥ 0.14 and OB ≥ 5% were used as the criteria to screen the metabolites and help to identify the key active ingredients [34]. This approach was successful at identifying 49 out of the 170 metabolites (Supplementary Table S3). The 49 metabolites consisted of 17 flavonoids, 12 lipids, five terpenoids, three nucleotides and derivatives, three coumarins, three tannins, two phenolic acids, one saccharides and alcohols, one stilbene, four others, and one vitamin. Five compounds (stearidonic acid, methyl linoleate, ricinoleic acid, arachidonic acid, and erucic acid) and eight compounds (chrysin, 6-methoxy-2-(2-phenylethyl) chromone, capillarisin, myricetin, digallic acid, 8-hydroxypinoresinol, 3-epiursolic acid, and betulinic acid) were specifically located in HT and IT, respectively. These results suggested that many other classes of metabolites in HT and IT that were not flavonoids could also contribute to promoting improved health in humans. The lipids, flavonoids, coumarins, terpenoids, and tannins were the major compounds that contributed. These 49 metabolites included 34 that were found to have roles associated with 60 target proteins and were linked to 69 diseases [34]. These major diseases involved tumors, cancers, noninsulin-dependent diabetes mellitus, hypertension, cardiovascular diseases, asthma, Alzheimer’s, inflammation, nervous diseases, diabetes, and the condition of pregnancy. These results strongly suggested that these metabolites serve as major key active ingredients to improve human health in HT and IT. In addition, the remaining 15 metabolites lacked corresponding target proteins and diseases; however, it is notable that four have DL values > 0.65, which are extremely high. This is particularly true for two flavanones and one triterpene (DL ≥ 0.76). This implies that these metabolites could be highly significant in promoting health and could possibly be useful for developing new drugs. The four metabolites included eriodictyol-7-O-glucoside, planteose, 3-epiursolic acid, and isoschaftoside (Supplementary Table S3).

3.3. Identification of the Active Pharmaceutical Ingredients for Resistance to Major Diseases in HT and IT

Tumors and cancers, hypertension, cardiovascular disease, diabetes, thrombotic disease, and the condition of pregnancy are the current global major threats to human health. The active pharmaceutical ingredients in HT and IT that can be used against these major diseases were identified by querying the 1056 metabolites identified in the TCMSP database [34]. The 98 metabolites identified in HT and IT were classified [40]. The metabolites were not screened for OB ≥ 5% and DL ≥ 0.14; however, 98 that corresponded to at least one disease were identified in the HT and IT seeds (Table 1). These are the first metabolites identified in HT and IT that play a preventive role in these diseases. The 98 metabolites contained 20 phenolic acids, 16 flavonoids, 15 lipid, nine organic acids, nine lignans and coumarin, nine amino acids, seven nucleotides, three terpenoids, one alkaloid, four others, one saccharide and alcohol, two vitamins, and two stilbenes (Table 1). Of the metabolites identified, 98 co-existed in HT and IT (Table 1). In total, 83, 69, 6, 24, 17, 39, and 41 metabolites were associated with treatments for cancers and tumors, cardiovascular disease, diabetes, hypertension, thrombotic and pain diseases, and atherosclerosis, respectively (Table 1). In particular, some metabolites showed promise for the treatment of multiple diseases. One example is quercetin, which displayed resistance to five diseases. These findings indicated that these metabolites were the most important active metabolites from HT and IT that could serve to improve human health as pharmaceutical ingredients. In addition, these 98 metabolites included 33 that are also key active ingredients in TCM (Supplementary Tables S1 and S2). They included 13 flavonoids, three terpenoids, one phenolic acid, one nucleotides and derivatives, two quinones, one tannin, seven lipids, three lignans and coumarins, one stilbene, and one other. These findings suggested that HT and IT could serve as ideal food sources to prevent these types of diseases. In addition, this analysis demonstrated that these metabolites from HT and IT could be reliable key active ingredients to improve human health.

3.4. Profiles of Differential Metabolites in HT and IT

To effectively understand the differences in metabolites between HT and IT, we utilized UPLC-MS/MS-based metabolite profiling of HT and IT that was widely targeted (Figure 2A). Two principal components were revealed in the two-dimensional (2-D) principal component analysis (PCA) scatter plots (Figure 2C). The total variation could be explained by PC1 (79.43%) and PC2 (6.48%) (the first two principle components). Samples that originated from the three biological replicates clustered to the same side along PC1 and could be clearly differentiated from each other. A hierarchical cluster analysis (HCA) produced a heatmap that displayed the patterns of accumulation of all the metabolites that were identified among the two samples (Figure 2B). They clustered hierarchically into two primary branches, including a yellow bar and a red bar, which displayed the obvious variation in the total metabolites between the two groups. The red bar indicated IT, while the yellow bar indicated HT. The three replicates also clustered, indicating that each variety was highly repeatable. The HCA analysis was consistent with the results of the PCA analysis. It also revealed obvious differences between the metabolites from HT and IT. The metabolites of IT exhibited a greater number of changes than those of HT. Therefore, the combination of HCA and PCA analyses suggested that the metabolic profiles of these two plants were obviously distinct.
The comparison between HT and IT produced VIP values of the OPLS-DA model ≥ 1 and the |log2(foldchange)| ≥1. There were 687 differential metabolites that were identified in at least one pairwise comparison, consisting of 132 flavonoids, 109 phenolic acids, 102 lipids, 56 organic acids, 52 amino acids and their derivatives, 54 alkaloids, 35 nucleotides and their derivatives, 33 lignans and coumarins, 15 terpenoids, eight tannic acids, and 91 other metabolites (Figure 2D). The K-means method could be used to classify all 687 differential metabolites into two categories (Figure 3). In these two categories, species specificity was determined. The contents of these metabolites differed significantly between HT and IT. The results of the HCA and PCA analyses reinforced the degree of these differences.

3.5. Characterization of the Differential Metabolites in HT and IT

To identify bioactive markers in HT and IT, we compared HT and IT and identified a total of 687 significantly different metabolites (Fold Change ≥ 2 and Fold Change ≤ 0.5 and VIP ≥ 1). Among these identified differential metabolites, 493 metabolites coexisted in HT and IT (Supplementary Table S4). Among these 687 metabolites, 260 metabolites were significantly higher in IT than HT, indicating that these metabolites are potential biological activity markers of IT. In total, these 260 metabolites included 46 flavonoids, 11 terpenoids, 35 phenolic acids, 13 amino acids and derivatives, 14 organic acids, 12 nucleotides and derivatives, 15 alkaloids, 70 lipids, 16 types of lignans and coumarins, 11 kinds of sugars and alcohols, four types of vitamins, three types of stilbene, and 10 other types of metabolites. The 427 types of metabolites in HT that were significantly higher than those in IT included 86 flavonoids, 74 phenolic acids, four terpenoids, 39 amino acids and derivatives, 42 organic acids, 23 nucleotides and derivatives, 39 alkaloids, 32 Lipids, 17 lignans and coumarins, 41 sugars and alcohols, eight vitamins, three stilbene, and 11 other metabolites. Notably, 91 of the 687 metabolites were specifically present in IT (16 flavonoids, five nucleotides and derivatives, 12 phenolic acids, seven lignans and coumarins, eight terpenoids, two quinones, eight alkaloids, 22 lipids, two organic acids, and one sugar) and 103 species specifically present in HT (12 flavonoids, 28 phenolic acids, one terpenoid, seven alkaloids, one tannin, 10 organic acids, and one sugar and alcohol). In addition, the analysis that utilized KEGG enrichment revealed that there were 687 differential metabolites. A total of 228 were assigned to 95 pathways after annotation. The top 20 metabolic pathways that were the most frequently enriched are shown in Figure 4A. The KEGG-enriched pathways that were significant included “flavonoid biosynthesis” (ko00941), “flavonoids and flavonol biosynthesis” (ko00944), and “stilbene, diarylheptane and gingerol biosynthesis” (ko00945); differentially enriched pathways had p < 0.05. The KEGG differential abundance score shows that most of the metabolites in fructose and mannose metabolism were upregulated in IT, while the metabolites in sulfur metabolism were upregulated and downregulated in equal numbers in IT; other pathways were upregulated in IT tea. The number of downregulated metabolites was higher than the number of upregulated metabolites. However, as beverages, amino acids and catechins have some impact on the changes in the taste of the two [41]. There are 18 amino acids in the two differential metabolites, including serine and glutamic acid, among others. These amino acids are significantly reduced in IT, while amino acids in IT are the source of umami in tea; this means that compared with HT, Insect Tea has lower umami in the taste. Among the catechins, epicatechin, catechin, gallocatechin, and epigallocatechin significantly differed between the two. The catechin metabolites were significantly reduced in the insect tea; the catechin metabolites were one of the sources of bitterness and astringency. Bitter and astringent tastes in harmony with various other flavors can enrich and improve the flavor of food. The reduction in amino acids and catechin metabolites will lead to a decrease in the flavor of IT (Figure 4B).
Most of the differential metabolites were found to be included in the key active components of TCM and were the main active pharmaceutical components of disease resistance (Table 1). Of the total metabolites, 26 were found to be key active components of TCM and the main active components of drugs for disease resistance (Supplementary Table S5), indicating that these metabolites are the main compounds of the key active components of TCM. These 26 metabolites are composed of 11 flavonoids (epicatechin, catechin, quercetin, hesperetin, gallocatechin, epigallocatechin, epiafzelechin, isorhamnetin, kaempferol-7-O, one phenolic acid (digallic acid), and one terpenoid (betulinic acid), tannins (procyanidin B1 and procyanidin B2), and others (capillarisin). A total of 15 of them were reduced or even disappeared in IT (Figure 5); 11 metabolites increased in IT (Figure 6) and it is even worth noting that six (betulinic acid, 8-hydroxypinoresinol, digallic acid, myricetin, chrysin and capillarisin) are only found in IT, enabling them to be used as a bioactive marker of IT. Betulinic acid, myricetin, and chrysin have been proven to have some curative effects on the treatment of tumors and cancer [42,43], which indicates that the health care effects of IT are stronger than that of HT. The HT is superior and only five types of lipid compounds (stearidonic acid, methyl linoleate, ricinoleic acid, arachidonic acid, and erucic acid) disappear in the IT. The reason for the difference could be that insects do not need to take fat from food; however, it can be converted and synthesized from protein and carbohydrates, while new compounds may be generated simultaneously (91 specific compounds of insect tea), Thus, insect tea may contain more active pharmaceutical substances than raw materials [44]. This suggests that a broadly targeted metabolomic approach based on comparative metabolomics is a bioactive marker for identifying different metabolites.

3.6. In Vitro Antioxidant Activity

In this study, hawk tea and insect tea were used to detect the free radical scavenging activity. The results showed that the IC50 value of insect tea was lower than that of hawk tea in the detection of DPPH free radical, which showed a stronger antioxidant potential for DPPH free radical (Figure 7A). The antioxidant activity of insect tea extract was higher than that of hawk tea in the detection of superoxide anion method (Figure 7B). In the detection of potassium ferricyanide, the antioxidant activity of insect tea extract was significantly higher than that of hawk tea (Figure 7C). Our results effectively proved that insect tea had higher antioxidant activity in vitro than hawk tea, which was consistent with the fact that insect tea contained more phenols and flavonoids.

4. Conclusions

We conducted UHPLC-QqQ-MS-based widely targeted metabolomics in this study. A total of 1056 metabolites were identified in hawk tea and insect tea. In total, 103 and 91 metabolites were unique to hawk tea and insect tea, respectively. The phenolic acids, flavonoids, and lipids were the primary contributors to the differences in the number of metabolites between hawk tea and insect tea. We identified 49 metabolites as key active ingredients that belong to TCMs in hawk tea and insect tea, and 98 metabolites that prevent cancer and tumors, hypertension, cardiovascular disease, diabetes, and other diseases. These metabolites from hawk tea and insect tea may be reliable key active ingredients for improving human health. We combined HCA and PCA analysis, which suggested that hawk tea and insect tea have distinct metabolite profiles. Betulinic acid, 8-hydroxypolyaminophenol, dienoic acid, myricetin, chrysin, and capillarin are only found in insect tea, enabling them to be used as a bioactive marker of insect tea. What is valuable is that insect tea contains flavonoids (myricetin and chrysin) and terpenes (betulinic acid) that are superior medicinal active ingredients and can be further verified by cytological experiments. Our findings provide new insights into the characterization of metabolites of insect tea. In addition, the metabolites identified from insect tea have broad application prospects in the fields of food and medicine, which are worthy of further study.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae9040457/s1. Supplementary Table S1: the differences in metabolites between HT and IT; Supplementary Table S2: 170 out of 1056 metabolites identified were found to be chemical components of TCMs; Supplementary Table S3: 49 out of the 170 metabolites were specifically located in HT and IT; Supplementary Table S4: 493 metabolites coexisted in HT and IT; Supplementary Table S5: 26 metabolites were found to be key active components of TCM and the main active components of drugs for disease resistance.

Author Contributions

Guided the present research, L.L; performed sample preparation, Q.S., X.Y. and H.C.; performed the experiments and analyzed the metabolites data, Q.S. and X.Y.; wrote the draft and revised the manuscript, Q.S. and H.T.; checked the manuscript, L.L.; All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Natural Science Foundation of China (3226180451) and Guizhou Province Science and Technology Planning Project (Qiankehe Support [2021] General 111); Guizhou University introduces talent research projects [2021]5.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Classification of secondary metabolites in HT and IT. HT: hawk tea; IT: insect tea.
Figure 1. Classification of secondary metabolites in HT and IT. HT: hawk tea; IT: insect tea.
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Figure 2. Analysis of secondary metabolomics of hawk tea and insect tea. Pictures of the phenotypes from hawk tea (HT) and insect tea (IT) were taken under the same condition. (A) Heatmap of secondary metabolites in the two samples from the HT and the IT groups (B). Two-dimensional PCA scatter plots of secondary metabolites (C). Differential metabolite clustering heatmap (D).
Figure 2. Analysis of secondary metabolomics of hawk tea and insect tea. Pictures of the phenotypes from hawk tea (HT) and insect tea (IT) were taken under the same condition. (A) Heatmap of secondary metabolites in the two samples from the HT and the IT groups (B). Two-dimensional PCA scatter plots of secondary metabolites (C). Differential metabolite clustering heatmap (D).
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Figure 3. K-means clustering groups of the profile of expression of the differential metabolites of HT and IT. The x axis represents the different samples, while the y axis represents the standardized content per metabolite.
Figure 3. K-means clustering groups of the profile of expression of the differential metabolites of HT and IT. The x axis represents the different samples, while the y axis represents the standardized content per metabolite.
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Figure 4. Differential abundance score map of the KEGG enrichment map of differential metabolites. (A) KEGG enrichment map of differential metabolites. The abscissa represent the corresponding rich factor of each pathway. The ordinate represents the pathway name, while the color of dot reflects the p-value. Dots that are redder indicate more significant enrichment. The size of the dots represents the number of enriched differential metabolites. (B) Differential abundance score map. (The horizontal axis represents the differential abundance (DA) score, while the vertical axis represents the differential pathway name. The overall amount of change in all the metabolites in the metabolic pathway is reflected by the DA score. A score of 1 indicates that the trend of expression of all the metabolites identified in this pathway is upregulated, while −1 indicates that the trend of expression of all the metabolites identified in this pathway is downregulated. The line segment describes two parameters for the pathway. Its length represents the absolute value of the DA score, while the size of dots at the endpoints represents the number of differential metabolites. The dots that are distributed on the left side of the central axis and have a longer line segment are more likely to indicate the downregulation of the overall expression of the pathway. The dots that are distributed on the right side of the central axis and have a longer line segment indicate that the overall expression of the pathway is more likely is to be upregulated. Larger dots indicate that the number of metabolites is greater. The color of the line segment and dot reflects the size of the p-value. Dots that are closer to red have a smaller p-value, while those that are closer to purple have a larger p-value).
Figure 4. Differential abundance score map of the KEGG enrichment map of differential metabolites. (A) KEGG enrichment map of differential metabolites. The abscissa represent the corresponding rich factor of each pathway. The ordinate represents the pathway name, while the color of dot reflects the p-value. Dots that are redder indicate more significant enrichment. The size of the dots represents the number of enriched differential metabolites. (B) Differential abundance score map. (The horizontal axis represents the differential abundance (DA) score, while the vertical axis represents the differential pathway name. The overall amount of change in all the metabolites in the metabolic pathway is reflected by the DA score. A score of 1 indicates that the trend of expression of all the metabolites identified in this pathway is upregulated, while −1 indicates that the trend of expression of all the metabolites identified in this pathway is downregulated. The line segment describes two parameters for the pathway. Its length represents the absolute value of the DA score, while the size of dots at the endpoints represents the number of differential metabolites. The dots that are distributed on the left side of the central axis and have a longer line segment are more likely to indicate the downregulation of the overall expression of the pathway. The dots that are distributed on the right side of the central axis and have a longer line segment indicate that the overall expression of the pathway is more likely is to be upregulated. Larger dots indicate that the number of metabolites is greater. The color of the line segment and dot reflects the size of the p-value. Dots that are closer to red have a smaller p-value, while those that are closer to purple have a larger p-value).
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Figure 5. Among the 26 metabolites that promote health, HT (red) is higher than IT (blue). Standard deviations represent the mean content of each HT and IT from three biological replicates.
Figure 5. Among the 26 metabolites that promote health, HT (red) is higher than IT (blue). Standard deviations represent the mean content of each HT and IT from three biological replicates.
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Figure 6. Among the 26 metabolites that promote health, IT (blue) is higher than HT (red). Standard deviations represent the mean content of each HT and IT from three biological replicates.
Figure 6. Among the 26 metabolites that promote health, IT (blue) is higher than HT (red). Standard deviations represent the mean content of each HT and IT from three biological replicates.
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Figure 7. In vitro antioxidant activity. (A) DPPH method was used to determine the antioxidant activity. (B) Superoxide anion method was used to determine the antioxidant activity. (C) Potassium ferricyanide method was used to determine the antioxidant activity. The x axis represents the concentration of hawk tea and insect tea (mg/mL).
Figure 7. In vitro antioxidant activity. (A) DPPH method was used to determine the antioxidant activity. (B) Superoxide anion method was used to determine the antioxidant activity. (C) Potassium ferricyanide method was used to determine the antioxidant activity. The x axis represents the concentration of hawk tea and insect tea (mg/mL).
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Table 1. A list of 98 metabolites identified in HT and IT with potential roles in disease resistance.
Table 1. A list of 98 metabolites identified in HT and IT with potential roles in disease resistance.
ClassAnticancer
Ingredients
Antidiabetic
Ingredients
Anticardiovascular
Ingredients
Antihypertensive
Ingredients
Anti-AtheroscleroticingredientsAntithrombotic
Ingredients
Antipain
Ingredients
Phenolic
acids(20)
Salicylic acid Salicylic acid Salicylic acid
Protocatechuald-
ehyde
Isovanillin Isovanillin Isovanillin
4-Methoxycinn-
amaldehyde
4-Methoxycinn-
namaldehyde
4-Methoxycinn-
amaldehyde
p-Coumaric acid p-Coumaric acid p-Coumaric acid
Terephthalic acid Terephthalic acidTerephthalic acid
2-Hydroxy-3-
phenylpropanoic acid
2-Hydroxy-3-
phenylpropanoic acid
2-Hydroxy-3-
phenylpropanoic acid
Vanillic acid Vanillic acid
3-Hydroxy-4-
methoxybenzoic acid
3-Hydroxy-4-
methoxybenzoic acid
3-Hydroxy-4-
methoxybenzoic acid
4-Methoxycinna-mic acid 2-Methoxycinna-
mic acid
4-Methoxycinn-
amic acid
2-Methoxycinna-mic acid 2-Methoxycinna-
mic acid
2-Methoxycinna-
mic acid
Caffeic acid Caffeic acidCaffeic acidCaffeic acid
4-O-Methylgallic acid 4-O-Methylgallic acid 4-O-Methylgallic acid
Dimethyl phthalate Dimethyl phthalate
Methyl caffeate Methyl caffeate Methyl caffeate
Syringic acidSyringic acid
Ferulic acid
methyl ester
Ferulic acid
methyl ester
Sinapinaldehyde Sinapinaldehyde Sinapinaldehyde
Digallic acid Digallic acid
Rosmarinic acid Rosmarinic acidRosmarinic acid
Flavnoids (16) Chalcone
Chrysin Chrysin
Epiafzelechin Epiafzelechin Epiafzelechin
Epicatechin Epicatechin
Catechin Catechin Catechin
Chrysoeriol Chrysoeriol Chrysoeriol
Quercetin QuercetinQuercetinQuercetinQuercetin
Hesperetin Hesperetin
Gallocatechin Gallocatechin
Epigallocatechin Epigallocatechin Epigallocatechin
Isorhamnetin Isorhamnetin Isorhamnetin
Myricetin Myricetin
Kaempferol-7-O-rhamnoside
Catechin gallate
Quercetin-3-O-
glucuronide
Quercetin-
3-O-
glucuronide
Quercetin-3-O-
glucuronide
Isorhamnetin-3-O-neohesperidoside
Terpenoids (3)Ursolic acid Ursolic acid
Betulinic acid
CycloartenolCycloartenol
Lipids (15) Tridecanoic acid
Myristic acid Myristic acid Myristic acid
Pentadecanoic acid Pentadecanoic acid Pentadecanoic acid
Palmitoleic acid Palmitoleic acid Palmitoleic acid
Palmitic acid Palmitic acid Palmitic acid
Methyl palmitateMethyl palmitate
Stearidonic acid Stearidonic acid Stearidonic acid
Elaidic acid Elaidic acid Elaidic acid
Stearic acid Stearic acid Stearic acid
Methyl linolenate Methyl linolenate Methyl linolenate
Methyl linoleate Methyl linoleate Methyl linoleate
Phytol
Ricinoleic acid Ricinoleic acid Ricinoleic acid
Arachidonic acid Arachidonic acid Arachidonic acid
Erucic acid Erucic acid Erucic acid
Lignans and (9)
coumarins
Coumarin Coumarin CoumarinCoumarin
4-Hydroxycou-
marin
4-Hydroxycou-
marin
4-Hydroxycou-
marin
4-Hydroxycoumarin
Umbelliferone Umbelliferone UmbelliferoneUmbelliferone
EsculetinEsculetinEsculetin
Isofraxidin Isofraxidin IsofraxidinIsofraxidin
Isolariciresinol Isolariciresinol Isolariciresinol
8-Hydroxypinor-
esinol
8-Hydroxypinor-
esinol
8-Hydroxypinor-esinol8-Hydroxypinor-
esinol
Olivil
Syringaresinol SyringaresinolSyringaresinol
Organic acids (11) 3-Hydroxy-butyric acid3-Hydroxybutyric acid 3-Hydroxybutyric acid
Malonic acid
2-Furoic acid
Succinic acid
2-Hydroxyphen-
ylacetic acid
2-Hydroxyphen-
ylacetic acid
2-Hydroxyphen-
ylacetic acid
Phenylpyruvic acid Phenylpyruvic acid Phenylpyruvic acidPhenylpyruvic acid
Shikimic acid Shikimic acid
Isocitric acid Isocitric acid Isocitric acid
Citric acid Citric acid Citric acid
Quinic acid Quinic acid
Amino
acids (9)
L-Serine L-Serine
L-Proline
L-Valine L-Valine L-Valine
L-AsparagineL-Aspara-
gine
L-Asparagine
L-Lysine
L-Glutamic acid L-Glutamic acid L-Glutamic acid
L-Histidine L-Histidine
L-Arginine L-Arginine
L-Tryptophan L-Tryptophan L-Tryptophan
Nucleotides (7) Uracil
Adenine Adenine
Hypoxanthine Hypoxanthine
Guanine Guanine
Thymidine Thymidine
Uridine
Uridine 5’-
monophosphate
Tannins (2)Procyanidin B2 Procyanidin B2
Procyanidin B1 Procyanidin B1 Procyanidin B1
Alkaloids (1)Indole-3-
carboxylic acid
Stilbene (2)Resveratrol Resveratrol
Pterostilbene Pterostilbene Pterostilbene
Saccharide and
alcohol (1)
D-sorbitol D-sorbitol
Vitamin (2)Nicotinamide Nicotinamide Nicotinamide
Pyridoxine PyridoxinePyridoxinePyridoxine
Others (4)5-Hydroxyme-
thylfurfural
5-Hydroxyme-
thylfurfural
5-Hydroxyme-
thylfurfural
Butylideneph-
thalide
Sarisan
Capillarisin Capillarisin Capillarisin
Total numbers8356924173941
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Sheng, Q.; Yao, X.; Chen, H.; Tang, H.; Lu, L. Identification of Nutritional Ingredients and Medicinal Components of Hawk Tea and Insect Tea Using Widely Targeted Secondary Metabolomics. Horticulturae 2023, 9, 457. https://doi.org/10.3390/horticulturae9040457

AMA Style

Sheng Q, Yao X, Chen H, Tang H, Lu L. Identification of Nutritional Ingredients and Medicinal Components of Hawk Tea and Insect Tea Using Widely Targeted Secondary Metabolomics. Horticulturae. 2023; 9(4):457. https://doi.org/10.3390/horticulturae9040457

Chicago/Turabian Style

Sheng, Qi, Xinzhuan Yao, Hufang Chen, Hu Tang, and Litang Lu. 2023. "Identification of Nutritional Ingredients and Medicinal Components of Hawk Tea and Insect Tea Using Widely Targeted Secondary Metabolomics" Horticulturae 9, no. 4: 457. https://doi.org/10.3390/horticulturae9040457

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