Metabolomics FAQ

• • Identification Methods of Sugars in Glycosides

  Glycosides are compounds consisting of a sugar moiety and a non-carbohydrate moiety (commonly an aromatic or aliphatic compound). Identifying the sugar component is a critical step in elucidating the structure and function of glycosides. The following methods are commonly employed for the identification of sugars in glycosides: 1. Chromatographic Methods High-performance liquid chromatography (HPLC) and gas chromatography (GC) are frequently used techniques. These methods enable the separation and ........

• • What Is Metabolomics, How Does It Differ From Proteomics, and What’s Its Future Outlook

  Metabolomics is a discipline that studies the spectrum of metabolites in organisms under specific physiological or pathological conditions. Metabolites are small molecules involved in metabolic pathways, including various amino acids, nucleic acids, carbohydrates, and fatty acids. They are direct products of cellular activities, thus providing us with detailed information about the physiological and functional state of cells. By analyzing the types and quantities of metabolites within organisms, metab......

• • How to Screen Differential Metabolites for Experimental Validation in Untargeted Metabolomics

  To screen differential metabolites in non-targeted metabolomics, the following methods can be employed: 1. Statistical Analysis: (1) t-test or ANOVA: Used for comparisons between two groups or among multiple groups, respectively. (2) Multivariate Analysis: Techniques such as Principal Component Analysis (PCA) or Partial Least Squares Discriminant Analysis (PLS-DA) can be used to identify key metabolites that differentiate between groups. 2. Setting Thresholds: (1) Based on the effect size of the exper......

• • Can OPLS-DA Be Used If R² Is 0.93 but the Permutation Test Slope Is Negative

  In OPLS-DA, the R² value quantifies the proportion of variance in the data that is explained by the model. An R² value of 0.93 indicates that the model accounts for 93% of the data variability, which is generally considered high and suggests strong explanatory power. During a permutation test, a plot is typically used to illustrate the relationship between model performance metrics (such as R² or Q²) and the permutation order. In this context, a negative slope may suggest that as the permutations increase..

• • How Can the Optimal Column Loading Be Determined for Polysaccharide Purification Using DEAE-52 Anion Exchange Chromatography?

  DEAE-52 is a weak anion exchange resin widely used for the purification of biomacromolecules such as polysaccharides and proteins. During polysaccharide purification using a DEAE-52 column, the sample loading amount plays a critical role in determining the separation resolution and overall process efficiency.   The optimal column loading of polysaccharides is primarily influenced by the following factors:   1. Resin Exchange Capacity This refers to the maximum number of ions the resin can bind, typica......

• • What Are the Effective Strategies for Hydrolyzing Sucrose into Monosaccharides?

  Sucrose is a disaccharide composed of one glucose unit and one fructose unit linked via a glycosidic bond. It can be hydrolyzed into its constituent monosaccharides through two primary approaches:   Enzymatic Hydrolysis This method commonly employs invertase (also known as sucrase) to catalyze the cleavage of the glycosidic bond in sucrose, yielding glucose and fructose. The reaction is typically conducted under defined temperature and pH conditions, and the extent of hydrolysis can be monitored using......

• • OPLS-DA Fails to Classify in Clinical Metabolomics, but Can Linear Regression Help with Different P and FC

  In clinical metabolomics studies, orthogonal partial least squares discriminant analysis (OPLS-DA) is commonly employed to distinguish between disease and control groups. However, in some cases, these groups may not be clearly separable, even when statistical analyses indicate significant differences in p-values and fold change (FC) values. Several factors could contribute to this issue. The following are recommendations for addressing this challenge: Re-Evaluating the OPLS-DA Model 1. Adjusting Model .....

• • What Are the Common Ethanol-Based Methods for Crude Polysaccharide Extraction?

  Ethanol-based extraction of crude polysaccharides primarily relies on the solubility differences between polysaccharides and other soluble components in the extraction medium. When the ethanol concentration reaches a specific threshold, polysaccharides precipitate out of solution, whereas other soluble substances—such as non-polar compounds and small molecular weight substances—remain dissolved. Two commonly employed ethanol precipitation strategies for crude polysaccharide extraction are outlined bel......

• • How to Perform Normalization and Peak Alignment Using XCMS for Metabolomics Data Preprocessing

  When performing metabolomics data preprocessing with XCMS, normalization and peak alignment are critical steps. Normalization eliminates technical variation between samples, allowing for comparison and analysis of metabolite peak intensities across different samples. Peak alignment addresses the drift and shift of metabolite peaks across samples, ensuring consistent peak positions for the same metabolite in different samples. The general steps are as follows: 1. First, use XCMS to extract peaks from raw....

• • Steps for Visualizing Lipidomics Data Analysis

  Here are the steps for several common visualization methods: Principal Component Analysis (PCA) Plot Creation 1. Data Preparation Obtain the standardized dataset from your statistical analysis, ensuring the data format is suitable for PCA analysis. 2. Plotting with Python Import necessary libraries like pandas for data reading, scikit-learn for PCA analysis, and matplotlib or seaborn for plotting. Read the dataset into a DataFrame, setting lipid types as rows and samples as columns. Perform PCA analysis....