Plant Targeted Metabolomics Service

What Is Plant Targeted Metabolomics

Plant metabolomics research utilizes computer science and experimental techniques to collect large amounts of data using high-tech equipment such as flow cytometry and mass spectrometry. It involves the analysis of various plant metabolites and their products. Targeted metabolomics allows for the extraction of information such as ion pairs and retention times for the target metabolites of interest. Metabolomic data from biological samples can be collected using MRM (Multiple Reaction Monitoring) mode to achieve absolute metabolite quantification. Additionally, by combining external standard quantification methods and standard curves of reference standards, absolute quantification of metabolites in samples can be achieved.

Plant targeted metabolomics research includes the analysis of metabolite products at different developmental stages, such as seeds, seedlings, young flowers, flower buds, and leaves. It aims to understand the synthesis and regulation mechanisms of metabolites, providing references for plant genetic breeding work. The study of signal transduction and regulatory mechanisms in plant cell synthesis metabolism helps to further discover and clone regulatory pathways and corresponding genes related to plant metabolism, enabling plant variety improvement and bio-synthetic engineering.

Plant Targeted Metabolomics Research Can Be Categorized Into The Following Areas:

Analysis of plant metabolites: Investigating the synthesis and regulation mechanisms of various types of plant metabolites (such as amino acids, fatty acids, glycosides, cell walls, etc.).

Study of key metabolic pathways in plant genetic breeding and nutritional quality improvement, exploring the molecular mechanisms of substance transformation regulation.

Utilizing experimental strategies such as storage, extraction, concentration, and purification to enhance the accuracy and efficiency of trace element and metabolite extraction in plants.

Using mass spectrometry analysis and computer science to study the signal transduction and regulatory mechanisms of metabolites, analyzing the correlation between plant cell metabolism and growth and development.

Developing novel experimental strategies and techniques in metabolomics to improve the efficiency of plant metabolomics research

List of Plant Targeted Metabolites Analysis Services

Technical Advantages:

• Advanced Platform: Utilization of the high-precision and high-resolution AB SCIEX QTRAP 6500+ mass spectrometer enables precise targeted identification.
• Self-built Database: Establishment of a standard database for eight plant hormones enables absolute qualitative and quantitative analysis, providing eight standard curves for these substances.
• Strict Quality Control: A dual quality control system of Standard QC and Sample QC, along with exogenous internal standards, ensures the stability and accuracy of the data.
• Accurate Qualitative Analysis: Each compound has at least two characteristic ion pairs, with one pair used for quantitative analysis and the remaining pairs aiding in qualitative analysis. Retention time verification ensures accurate qualitative results.
• Precise Quantitative Analysis: Triple quadrupole MRM mode, ESI ion source, and quantification using gold standards enable the accurate detection of relative substance levels.
• Wide Linear Range: 0.00671-1000 ng/mL with a correlation coefficient greater than 0.99, suitable for quantitative analysis of complex sample types.
• Manual Verification: Strict manual verification processes are implemented to ensure the accuracy and reliability of the methods.

Sample Requirements

Data Analysis Contents

Secondary Metabolites Profiled in Cannabis Inflorescences, Leaves, Stem Barks, and Roots for Medicinal Purposes

Journal: Scientific Reports

Published: 2020

Technology: Targeted metabolomics, LC-ESI-MS, HPLC-UV-MS, GC-MS, GC-FID

Abstract

The metabolic characteristics of inflorescence include terpenoids and flavonoids. According to research, however, extracts containing a large number of secondary metabolites may have better efficacy and fewer side effects than individually extracted compounds. Combinations of different secondary metabolites at different concentrations are believed to enhance therapeutic effects through a "synergistic effect." A recent study has shown that whole-plant extracts are more beneficial than pure CBD in treating inflammatory diseases in mice. Another preclinical study demonstrated that plant formulations are more effective than pure tetrahydrocannabinol in generating anti-tumor responses in vitro. The complexity of plants determines the depth and breadth of their historical uses, including separate applications of leaves, stem bark, and roots, while modern research has not fully explored their therapeutic potential.

Figure 1 | Synthetic pathways of terpenes, sterols, and flavonoids.

Methods

The purpose of this study was to conduct a comprehensive investigation utilizing the chemical characteristics of different parts of plants. The author employed the following analytical methods for comprehensive analysis:

Liquid chromatography-mass spectrometry (LC-MS) for analysis.

Liquid chromatography with UV and mass spectrometry detection (LC-UV-MS) for analysis of flavonoid compounds.

Gas chromatography-mass spectrometry (GC-MS) for analysis of terpenoid compounds and steroids.

Results

Analysis and Validation Based on LC-ESI-MS

The LC-MS targeted metabolomics (accurate targeting) method was employed to detect the fragment ion mass-to-charge ratios (m/z) of each compound, as shown in Table 1.

Table 1 | Fragment ion mass-to-charge ratios (m/z) of each compound

The chromatograms of a 14-component mixed standard solution analyzed by LC-MS (accurate targeting) are shown in Figure 3a. The regression curves exhibit linearity, and the slopes and determination coefficients were calculated. All 14 compounds showed high correlation coefficients above 0.9998. The intercepts for each compound were set to zero. Validation analysis was conducted using analysis of variance, detection limit, quantification limit, repeatability, intra-day precision, relative deviation, measurement uncertainty, matrix effect, and extraction efficiency. No significant differences were observed in the extracted compounds, confirming the stability of the technique.

Figure 3 | Chromatograms of Monoterpenes, Sesquiterpenes, Flavonoids, Steroids, and Triterpenes

Detection and Method Validation of Monoterpenes and Sesquiterpenes

Identification and semi-quantification of terpenoid compounds without available reference standards were performed using GC-MS (targeted analysis) and GC-FID. Analysis involved comparing the mass spectra of target compounds obtained from available terpenoid compound standards and samples with data from the NIST mass spectral database embedded in the GC-MS system. If the retention index (LRI) and mass spectra confirmed the identity of the target compound, semi-quantification was performed by comparing the response areas of the target compound and closely eluting compounds with known concentrations, assuming a relative response factor for that compound.

Separation of monoterpenes and sesquiterpenes was achieved using the GC-MS (targeted analysis) platform, operating the mass spectrometer in selected ion monitoring (SIM) mode. The quantitative and qualitative ion lists for each compound are shown in Table 2:

Table 2 | Quantitative and Qualitative Ion Lists for Each Monoterpene and Sesquiterpene Compound

All 44 terpenoid compounds exhibited correlation coefficients higher than 0.9989. Evaluation was conducted through LOD (limit of detection), repeatability, inter-day precision, relative deviation, measurement uncertainty, and durability testing using twelve replicate samples. No significant differences were observed in terms of total yield of monoterpenes and sesquiterpenes.

Qualitative and Quantitative Analysis of Flavonoid Compounds Based on HPLC-UV-MS

HPLC-UV-MS was employed for the analysis of flavonoid compounds, and the fragment ion m/z of each compound was used for qualitative and quantitative determination of the seven identified flavonoids. Table 3 presents the fragment ion m/z values for the flavonoid compounds.

Table 3 | Fragment Ion m/z Values for Flavonoid Compounds

All seven compounds exhibited correlation coefficients greater than 0.9997. The accuracy of the acid hydrolysis determination of the seven flavonoid compounds, determined by recovery rate, was assessed. The recovery rates of hesperetin and apigenin were found to be 82% and 81%, respectively, consistent with previous studies. The repeatability of the method was verified by applying intra-day precision to twelve replicate leaf samples from flower clusters.

Analysis of Steroid and Triterpenoid Compounds

Quantification of triterpenoids and sterols was conducted using the GC-MS (targeted analysis) platform, with the mass spectrometer operating in the selected ion monitoring (SIM) mode. The quantification and qualification ions for each compound are presented in Table 4.

Table 4 | Quantification and Qualification Ions for Triterpenoid and Steroid Compounds

The correlation coefficients for all six compounds ranged from 0.9989 to 0.9999. The limits of detection (LOD) ranged from 0.17 to 0.26 µg/mL, while the limits of quantification (LOQ) ranged from 0.50 to 0.79 µg/mL. The repeatability, intra-day precision, and relative deviation measurements were validated for all compounds.

Distribution in Flower Clusters, Leaves, Stem Bark, and Roots

The content decreases from flower clusters to leaves, stem bark, and roots (Figure 4a), observed in all three chemovars. The stem bark contained quantified amounts of compounds at 0.005% and 0.008% compared to leaves and flower clusters, as shown in Figure 4b. The total content in the leaves ranged from 1.10% to 2.10%. This aligns with previous reports (1-2% and 1.40-1.75%). The flower clusters of all three chemovars exhibited a range of 15.77% to 20.37%, indicating a typical profile for modern medicinal chemovars.

Figure 4 | Distribution of Secondary Metabolites in Roots, Stem Bark, Leaves, and Flower Clusters

Monoterpene and sesquiterpene compounds in Flower Clusters, Leaves, Stem Bark, and Roots

Monoterpene and sesquiterpene compounds were not detected in stem bark or roots (Figure 4c). The total content of monoterpenes and sesquiterpenes in leaves ranged from 0.125% to 0.278%, and in flower clusters, the total content ranged from 1.283% to 2.141%, which is lower than reported for unfertilized flowers in previous studies. In Chemovar I and Chemovar II, the total content of sesquiterpenes in fan leaves was higher than the total content of monoterpenes, while in Chemovar III, they were comparable. This observation becomes even clearer when expressed as proportions: sesquiterpene compounds accounted for approximately 90% of the total terpene compounds in Chemovar I and II, and 53% in Chemovar III.

Flavonoid components in Flower Clusters, Leaves, Stem Bark, and Roots

A total of 26 flavonoid compounds were identified in the plant, including methylated and prenylated aglycones, or conjugated o-glycosides or c-glycosides of flavonols, isoflavones, flavones, and flavanones. The total flavonoid content was represented by the sum of these seven flavonoids after acid hydrolysis. Flavonoid compounds were not detected in roots and stem bark, while they were found in lower quantities in flower clusters and the highest levels in leaves (Figure 4e).

Sterol profile in Flower Clusters, Leaves, Stem Bark, and Roots

The total sterol content represented the sum of β-sitosterol, stigmasterol, and β-sitosterol in flower clusters, leaves, roots, and stem bark (Figure 4h). The proportions of the three sterols were consistent with previous studies on roots. β-sitosterol was the most abundant sterol in roots and stem bark of all chemovars, ranging from 0.04% to 0.06% (Figure 4i, j). The content of campesterol in roots and stem bark ranged from 0.01% to 0.02% and was not detected in leaves. The lowest concentration of stigmasterol was found in roots and stem bark at 0.01%, while the highest concentration was in leaves at 0.03%. The total sterol content in stem bark showed comparability across the three chemovars, while the total sterol content in root material differed significantly. β-sitosterol showed no significant differences in stem bark among the three.

Triterpene compounds control flower clusters, leaves, stem bark, and roots.

The total triterpene content is represented as the sum of β-amyrin, free triterpenols, and free triterpenes. It increases from flower clusters to leaves, stem bark, and roots (Figure 4k). The total triterpene content in the roots and stem bark of Chemovar III is significantly higher than that of Chemovar I and II. Free triterpenes are the most prominent triterpene compounds, concentrated in stem bark and roots (Figure 4l, m). The results show that the content of free triterpenes, free triterpenols, and β-amyrin in stem bark and roots of Chemovar III is significantly higher than in other chemovars. Free triterpenols or free triterpenes were not found in leaf samples. Instead, a higher content of β-amyrin was found in leaves compared to stem bark or roots.

Conclusion

This study is the first attempt to comprehensively analyze the secondary metabolite profiles of different parts of the plant using a targeted approach. The study analyzed 14 sesquiterpene compounds, 47 triterpene compounds (including 29 monoterpenes, 15 sesquiterpenes, and 3 triterpenes), 3 sterols, and 7 flavonoids in flower clusters, leaves, stem bark, and roots of three different varieties. By analyzing the secondary metabolites of terpenes, sterols, and flavonoids in different parts such as flower clusters, leaves, stem bark, and roots, it was found that monoterpenes, sesquiterpenes, and flavonoids are relatively abundant in flower clusters and leaves, while triterpenes and sterols are present in stem bark and roots. These bioactive compounds may serve as the basis for the traditional medicinal value of each plant. A comprehensive overview of bioactive compounds and in-depth studies of their synergistic effects establish the correlation between plant constituents and therapeutic effects, ultimately connecting traditional herbal medicine with modern science. This approach allows for the development of new drug candidates using the entire plant or its subsets. One of the future trends in the industry is to fully utilize the various parts by applying modern scientific methodologies to validate their traditional uses.