Plant Metabolome Bioinformatics Analysis

To survive and reproduce, organisms need to adapt their morphological and physiological characteristics to different environmental conditions. These eco-physiological adjustments can be identified and quantified using metabolomics techniques. Plant metabolomics studies all small molecule metabolic components in plant cells. With the continuous development of high-throughput and high-resolution metabolic detection technologies, bioinformatics plays an increasingly important role in plant metabolomics research.

Lifeasible has a state-of-the-art technology platform for mass spectrometry analysis and has been engaged in plant metabolomics research for over a decade. We can combine multiple bioinformatics technologies and statistical methods to efficiently analyze high throughput metabolic data to reveal the underlying genetic signature of plant metabolites.

What We Offer

The main techniques used in plant metabolomics research include nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography-mass spectrometry (LC/MS), and gas chromatography-mass spectrometry (GC/MS). The bioanalytical process for plant metabolomic data includes data pre-processing, statistical analysis, and database search and comparison.

• Data Pre-processing

Depending on the purpose of the study, the type of data, and the statistical analysis method, we will choose the appropriate pre-processing methods, mainly noise reduction, baseline correction, normalization, and data normalization.

• Univariate Analysis

Metabolomics analysis begins with a significance test for differences in the data to determine whether random fluctuations cause variation in the data. We commonly use t-tests and U-tests to compare whether differences between two data sets are significant. Variance (ANOVA) analysis is required when analyzing the statistical significance of differences between data from multiple sample metabolomes. Overall randomness can be verified by the D-method, W-method, or chi-squared test, and chi-squareness can be tested by the Barlett or Levene method.

• Multivariate Analysis

Multivariate analysis can be divided into a supervised method and an unsupervised method.

1. Unsupervised methods directly categorize the raw data to discover the overall characteristics of the data and the intrinsic relationships between the variables, including principal component analysis (PCA), hierarchical cluster analysis (HCA), and self-organizing maps (SOMs).
2. The supervised methods include partial least squares (PLS), linear discrimination analysis (LDA), support vector machine (SVM), and artificial neural networks (ANN).
3. Database Search and Comparison

The analysis of metabolomic data cannot be done without various databases. Commonly used metabolomics databases include reference spectral databases such as MassBank, METLIN, and NIST; metabolic pathway databases such as KEGG, PlantCyc, and MetaCye; and compound information databases such as PubChem, ChemSpider. The metabolomic data were compared with these databases and integrated to obtain the metabolic networks of the plants to be analyzed.

Plant Species Covered by Our Services

Applications

• Widely used in research areas such as plant physiological changes and metabolic regulatory networks.
• To study the overall changes and differences in metabolites under different genotypes and environmental conditions.
• To study gene function, elucidate metabolic pathways and their regulatory mechanisms, and explore various plant biological phenomena.

Why Choose Lifeasible

We provide the technical means to leap from the study of a single metabolite or a few metabolites to the simultaneous study of a large number of metabolites as a whole or at a certain level, breaking the limitations of a narrow level of analysis and insufficient data information. In addition, we can combine genomics, proteomics, transcriptomics, and metabolomics to provide a comprehensive analysis of gene, protein expression, and metabolite changes, allowing for the construction of a more comprehensive biological information network on plant metabolites.

How to Place an Order

Lifeasible has been dedicated to providing our clients with plant metabolome bioinformatics analysis services for many years. Please feel free to contact us with your questions, needs, or collaboration.