The plant-environment interaction metabolome allows the analysis of small molecules or metabolites that are involved in dynamic biochemical interactions between plants and their surroundings. It encompasses the complex network of metabolic reactions and responses that occur when plants interact with a variety of environmental factors, such as soil conditions, temperature, light, moisture, biotic stressors (e.g., pests and pathogens) and abiotic stressors (e.g., drought) or nutrient availability).
Essentially, the metabolome of a plant's interactions with its environment is a snapshot of the chemical communication and adaptive processes that occur in a plant in response to its surroundings. It encompasses a wide range of metabolites, including primary metabolites (e.g., sugars, amino acids) and secondary metabolites (e.g., phytochemicals, terpenoids, and phenolic compounds), all of which play an important role in mediating the plant's response to environmental signals.
Metabolomic technologies can provide insights into how plants perceive and respond to their environment, enabling you to study the biochemical mechanisms behind plant growth, stress tolerance, defense responses, and adaptation strategies. By analyzing changes in the metabolome of plants interacting with their environment, we can better understand how plants thrive, survive and interact with their ecosystems.
Beneath the Earth's surface lies a thriving ecosystem teeming with microorganisms crucial for plant health and growth. Soil is not just a matrix; it's an intricate network where plants engage in metabolic dialogues with microorganisms. Our cutting-edge mass spectrometry-based techniques, including liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS), are the keys to deciphering these hidden interactions. We unveil the secrets of nutrient cycling, disease suppression, and plant growth promotion.
When pests and pathogens threaten plant health, nature's biochemical defenses come to the forefront. Plants employ a range of metabolic strategies to fend off these adversaries. Our sophisticated instrumentation, such as the Thermo Scientific Q Exactive Plus LC-MS/MS and the Agilent 7890B GC-MS, provides a window into this biochemical battlefield. Here, we explore the world of defensive compounds, including alkaloids, terpenoids, and phenolic compounds, and understand how plants adapt their metabolic pathways in response to biotic stressors.
Plant-mycorrhizal fungi symbiosis exemplifies the intricate dance of cooperation in nature. Plants provide mycorrhizal fungi with carbon compounds, while fungi enhance the plant's nutrient uptake, especially phosphorus. To unravel the metabolic intricacies of this mutually beneficial relationship, we turn to advanced instrumentation, including the Waters Xevo G2-XS QTof LC-MS and the Shimadzu GCMS-TQ8050.
Liquid Chromatography-Mass Spectrometry (LC-MS): LC-MS enables the comprehensive profiling of metabolites in plant samples. It aids in the detection and quantification of compounds, including secondary metabolites, nutrients, and harmful substances, offering insights into how plants adapt metabolically to changing environmental conditions.
Gas Chromatography-Mass Spectrometry (GC-MS): GC-MS specializes in the analysis of volatile compounds, making it valuable for studying plant responses to specific environmental factors. It is particularly useful for investigating the release of volatile organic compounds by plants under stress.
Case. Metabolomics Analysis of Portuguese Common Bean Accessions Grown in Contrasting Environments
Background
This study aimed to investigate the metabolomics diversity of Portuguese common bean accessions grown in two different environments and identify specific metabolites that could be associated with heat tolerance in these beans.
Samples
The study involved 107 underexploited Portuguese common bean accessions, which were cultivated in two contrasting environments: Cabrela (traditional) and Cordoba (heat-stress).
Technological Methods
Metabolite Identification: Metabolites were identified primarily using negative ionization mode, which offers improved sensitivity and lower detection limits. Online databases were used for annotation, and compounds were selected based on VIP scores (Variable Importance in Projection) higher than 0.8.
Annotation Challenges: The annotation of compounds was hindered by limited diversity in available online libraries and the quality of mass spectrometry (MS) and MS/MS fragmentation spectra. This was due to the historical underrepresentation of legume metabolomics research.
Superclasses Classification: The annotated compounds were categorized into seven different superclasses, including phenylpropanoids and polyketides, organic oxygen compounds, benzenoids, lipids, nucleosides, nucleotides, organic acids, and derivatives.
Results:
Classification of metabolites into different superclasses.
Score plot obtained by principal component analysis (PCA), showing common bean accessions, cropped in contrasting environments.
Reference