Online Inquiry

Plant Metabolomics Service

  • Service Details
  • Case Study

What Is Plant Metabolomics

Plant metabolomics, as an important branch of metabolomics, focuses on studying plants. It involves the qualitative and quantitative analysis of all low-molecular-weight metabolites in a specific tissue or cell of a plant during a particular physiological stage. Plant metabolomics is based on community-level analysis, utilizes high-throughput detection and data processing techniques, and aims at information modeling and system integration. It explores the biochemical changes in organisms from a macroscopic perspective and helps monitor or evaluate gene functions.

As an emerging discipline, plant metabolomics follows the research approaches of genomics and proteomics. It involves comprehensive qualitative and quantitative analysis of all small-molecule metabolites in an organism, aiming to explore the relative relationship between metabolites and plant physiological changes and determine their physiological functions. Plant metabolomics is an integral part of systems biology. The analytical workflow can be divided into three main parts: sample preparation, sample analysis, and high-throughput data processing.

Research Content Of Plant Metabolomics

Plant Metabolomics includes not only primary metabolites essential for plant growth, development, and life activities, such as organic acids, amino acids, nucleotides, carbohydrates, and lipid molecules, but also secondary metabolites closely related to plant stress response, such as flavonoids, alkaloids, phenols, and terpenoids. Plant metabolomic analysis aims to qualitatively and quantitatively analyze as many metabolites as possible in plant samples. Achieving this goal requires the use of high-sensitivity detection techniques based on mass spectrometry.

Research on Plant Primary Metabolism Network: In recent years, plant metabolomics has also been applied to breeding research of major crops such as rice and maize, focusing on yield and quality traits. Precise quantification of agricultural traits has always been a challenging issue in conventional breeding processes and a major factor affecting breeding accuracy. Many researchers are attempting to use metabolites (or metabolic networks) to quantitatively characterize yield, quality, and other agricultural traits. The yield and quality of crops are theoretically directly related to the network of plant primary metabolic pathways, including photosynthesis, glycolysis, tricarboxylic acid cycle, respiration pathways, amino acid and fatty acid metabolism, among others. Relevant studies have shown (usually through population analysis of a set of recombinant inbred lines or near-isogenic lines) that the relationship between yield, quality, and compound content is not a simple linear correspondence (which is different from secondary metabolism studies), and different primary metabolite contents themselves belong to quantitative trait loci (QTLs).

Research on Plant Secondary Metabolism Network: Metabolomics plays a relatively direct role in the study of plant secondary metabolism networks because researchers are primarily concerned with changes in the content of compounds themselves (usually end products of metabolic pathways). Therefore, subsequent data correlation analysis steps generally do not need to consider the influence of factors such as coenzymes and growth environments on end product generation.

Metabolic Fluxomics Research: Metabolic fluxomics is the scientific study of the regularity of compound flow in all metabolic networks of a specific organism. It is a quantitative analysis method that uses a stoichiometric matrix model to represent the reactions within the cell under quasi-steady-state conditions. Another method of metabolic flux analysis is to track the transfer of stable isotopes in the metabolic network and perform corresponding model calculations to effectively quantify metabolic flux and its changes. Szecowka et al. used metabolomics platforms to analyze the enrichment of 40 primary metabolites in Arabidopsis rosette leaves over time under 13CO2 (substituted CO2) growth conditions, establishing a dynamic metabolic flux model of photosynthesis in rosette leaves. This deepened researchers' understanding of the regulation of photosynthetic metabolism and laid a solid foundation for improving the efficiency of plant photosynthesis through engineering modifications.

Coenzyme Factoromics Research: Among the variables in metabolic networks, coenzymes play a crucial role. Coenzymes refer to a class of small organic molecules that can transfer chemical groups from one enzyme to another, loosely bound to enzymes but essential for the activity of specific enzymes. Many vitamins (especially water-soluble B vitamins) and their derivatives, such as riboflavin, thiamine, and folate, belong to coenzymes. As essential chemicals for organisms, coenzymes should theoretically be synthesized and accumulated in various cells of plants.

Our Plant Metabolomics Service

Creative Proteomics has established a metabolomics research platform for primary and secondary metabolites in plants, starting from the integrative and dynamic nature of plant biological systems. Based on the experimental objectives, different sample processing strategies are adopted to efficiently extract primary and secondary metabolites from plants for omics analysis. This platform studies the dynamic changes of metabolic products, analyzes metabolic pathways, observes the accumulation process of active ingredients, and discovers the interconversion patterns among different components. It scientifically evaluates the quality of plant resources, thus laying the foundation for the development and utilization of plant resources.

Currently, more than 200,000 plant metabolites are known, whereas microbes have only 1,500 metabolites and animals have only 5,000 metabolites in comparison. Our company's UPHLC-QTOF-MS and UHPLC-QQQ-MS platforms provide tremendous assistance in addressing the scientific research challenges posed by the vast number of plant metabolites.

Main Research Technology

TechniquePlant Untargeted MetabolomicsPlant Targeted MetabolomicsWidely Targeted Metabolomics
ObjectiveMetabolite detection at an omics levelDetection of individual or a class of known substancesHigh-throughput qualitative and quantitative detection of metabolites
AdvantagesHigh throughput, multiple detection signalsAccurate identification of metabolites, high sensitivity, absolute quantification to obtain metabolite concentrations in the sampleHigh throughput, batch identification of substances with accuracy, high sensitivity for detecting low-abundance metabolites, custom-built databases to discover new metabolites, good reproducibility
DisadvantagesComplex metabolite identification process, low sensitivity for detecting low-abundance substances, reliance on public databases making it difficult to discover new substances, semi-quantitative resultsLow throughput, need to purchase standard substances, high costs for method development, validation, and researchComplex sample preparation, complex detection process, need for custom-built databases
PlatformsNMR, GC-MS, LC-MS, etc.HPLC, GC, GC-MS, LC-MS, etc.LC-QQQ/MS, etc.

Sample Requirements

Sample TypeRecommended Sample Quantity (per sample)
Fresh plant tissue≥ 1 g
Freeze-dried plant tissue≥ 200 mg

Workflow Of Our Plant Metabolomics Service

Workflow Of Our Plant Metabolomics Service

Data Analysis Contents

Basic Data AnalysisAdvanced Data Analysis
Data preprocessing
PCA analysis
PLS-DA analysis
OPLS-DA analysis
Differential compound screening
Differential compound identification
Metabolic pathway analysis
Metabolic network analysis
Multi-omics data correlation analysis (for studies with multiple omics data)

A sister group contrast using untargeted global metabolomic analysis delineates the biochemical regulation underlying desiccation tolerance in Sporobolus stapfianus.

Journal: Plant Cell
Published: 2011


In the study of plant stress resistance, research on drought resistance is an important direction. In addition to studying genes and proteins related to drought resistance, exploring the mechanisms of drought resistance from the perspective of plant metabolism is an interesting and relatively less studied area.

The author used two herbaceous plants, Sporobolus stapfianus and Sporobolus pyramidalis, which exhibit contrasting drought resistance phenotypes. These two plants belong to the same genus, Sporobolus. S. pyramidalis is sensitive to drought, while S. stapfianus exhibits strong drought resistance. What are the reasons for such significant differences in drought resistance between these two closely related herbaceous plants?


Metabolomics research has shown that even in a normal non-drought environment (prior to drought), there are significant differences in leaf metabolomes between the two plant species (Figure 1).

There are 36 metabolites with higher concentrations in S. stapfianus, while 34 metabolites have significantly higher concentrations in S. pyramidalis compared to S. stapfianus. These significantly different metabolites between the two species mainly belong to two categories: amino acid metabolism and energy metabolism. Many metabolites involved in glycolysis, tricarboxylic acid cycle, and starch synthesis-related metabolites are found at higher concentrations in the drought-sensitive S. pyramidalis compared to the drought-tolerant S. stapfianus. It is possible that the drought-tolerant S. stapfianus maintains a relatively lower basal metabolic level, which may be one of its strategies for drought resistance.

Figure 1Figure 1

Comparing the changes in leaf metabolomes of S. pyramidalis and S. stapfianus relative to their non-drought state, it was found that the metabolites in S. pyramidalis exhibited minor alterations. Only a few metabolites, such as proline, fructose, and glucose, showed increased concentrations (Figure 2), indicating that S. pyramidalis attempted limited osmotic adjustment to prevent water loss. In contrast, S. stapfianus underwent significant metabolic adjustments during the early stages of drought response. Numerous amino acids (including proline) and sugars (monosaccharides, disaccharides, sugar alcohols, etc.) significantly increased, indicating that compared to S. pyramidalis, S. stapfianus exhibits a wider range of osmotic adjustment and stronger water retention capabilities. The rapid increase in amino acids is attributed to the high levels of asparagine (Asn) stored in S. stapfianus under non-drought conditions. After reaching an RWC (relative water content) of less than 40%, S. stapfianus relies mainly on adjustments in nitrogen metabolism and oxidative stress response to cope with water loss. Specifically, the oxidative stress response is enhanced by the synthesis of glutathione (GSH) (Figure 3).

Figure 2Figure 2

Figure 3Figure 3


This study compared drought resistance in closely related grass species S. stapfianus and S. pyramidalis. S. stapfianus exhibited lower energy metabolism metabolites and higher osmotic regulators, delaying water loss. Upon drought onset, S. stapfianus rapidly produced regulators and antioxidants to protect cells, while S. pyramidalis showed weak responses, damaging cells. S. stapfianus combined prepared metabolism and rapid response to delay desiccation. As drought progressed, S. stapfianus stored nitrogen metabolites and reinforced oxidative stress response. Increased γ-glutamyl amino acids indicated enhanced glutathione cycling. Nitrogen metabolites relieved ammonia toxicity. Novel phthalate accumulation in drought stress was found.


  1. Tiago F. Jorge, Ana T. Mata and Carla. António Mass spectrometry as a quantitative tool in plant metabolomics. Quantitative mass spectrometry. 2016
* For Research Use Only. Not for use in diagnostic procedures.
Our customer service representatives are available 24 hours a day, 7 days a week. Inquiry

Online Inquiry

Please submit a detailed description of your project. We will provide you with a customized project plan to meet your research requests. You can also send emails directly to for inquiries.

* Email
* Service & Products of Interest
Services Required and Project Description
* Verification Code
Verification Code