Untargeted metabolomics enables the unbiased detection of dynamic changes in most small molecule metabolites within an organism in response to external stimuli. By leveraging Liquid Chromatography-Mass Spectrometry (LC-MS), researchers can gain comprehensive insights into biological systems influenced by environmental, genetic ortherapeutic variations.
At Novogene, our comprehensive untargeted metabolomics services offer the latest state-of-the-art LC-MS technologies together with cutting-edge bioinformatics analyses to deliver high-quality metabolomic data to support your research.
Applications:
Untargeted metabolomics plays a vital role in agricultural, clinical, and medical research by offering insights into plant and soil metabolite profiles, stress responses, and environmental interactions, while also facilitating the in-depth study of metabolic changes related to diseases, drug responses, and personalized medicine.
- Stress Resistance Research
- Crop Improvement & Breeding
- Plant Growth, Soil Health & Microbial Interactions
- Food Science Research
- Biomarker Screening
- Pathological Mechanisms
Advantages and Features of Novogene's Untargeted Metabolomics Services
- Ultra-high Resolution and Sensitivity: Powered by the Q Exactive HF-X mass spectrometry platform, Novogene delivers exceptional data quality for precise and reliable results.
- High Quality Database: A high-quality secondary spectral database including in-house standard database(15,000+ standards) and in-house secondary spectrum library, ensuring comprehensive and high-quality search results.
- Rigorous Quality Control: QC indicator for monitoring all aspects of experimentation from sample preparation to data collection.
Sample Requirements for Biomedical Metabolomics Sample
| Sample Type | Sample | Recommended Sample | Biological Replicate |
| Liquid | Plasma, Serum, Hemolymph, Whole Blood, Milk, Egg White | 100 μL | Human≥30, Animal≥8, Plant≥3 |
| Cerebrospinal Fluid, Interstitial Fluid, Uterine Fluid, Pancreatic Juice, Bile, Pleural Effusion, Follicular Fluid, Postmortem Fluid, Tissue Fluid, Culture Medium (liquid), Culture Supernatant, Tears, Aqueous Humor, Digestive Juices,Bone Marrow (liquid) | 100 μL | ||
| Seminal Plasma, Amniotic Fluid, Prostatic Fluid, Rumen Fluid, Respiratory Condensate, Gastric Lavage Fluid, Broncho-alveolar Lavage Fluid (BALF), Urine, Sweat, Saliva, Sputum | 500 μL | ||
| Tissue | Animal Tissues, Placenta, Blood Clot, Mycelium, Nematode, Zebrafish (whole fish), Bone Marrow (solid), Nail | 100 mg | |
| Whole Insect Body, Wings (of insects), Pupa, Eggs, Large Fungi (mushroom types), Large Algae (red algae), Large Amount of Mycelium/Mycelial Balls, Cartilage, Bone (solid) | 500 mg | ||
| Zebrafish Organs, Insect Organs, Whole Microinsect Body (e.g., Drosophila) | 20 units | ||
| Solid | Feces, Intestinal Contents, Lyophilized Fecal Powder | 200 mg | |
| Milk Powder, Microbial Fermentation Product (solid), Culture Medium (solid), Earwax, Lyophilized Tissue Powder,Feed, Egg Yolk, Lyophilized Plant Powder, Lyophilized Egg Powder | 100 mg | ||
| Honey, Nasal Mucus, Sputum | 100 mg | ||
| Sludge, Soil | 600 mg | ||
| Cell | Adherent Cells, Animal Cell Lines | 1*10^7 cells | |
| E. Coli, Yeast Cells | 1×10^10 cells | ||
| Small Amount of Fungal Mycelial Balls/Mycelium, Unicellular Algae (Cyanobacteria), Large Quantities of BacterialHyphae (sediment), Mucilaginous Protoplasmic Clusters (hyphae) | 100 mg | ||
| Organelle | Lysosomes, Mitochondria, Endoplasmic Reticulum | 4×10^7 cells | |
| Exosomes, Extracellular Vesicles | 2×10^9Particles | ||
| Special Sample | Skin Tape or Patch | 2 pieces | |
| Test Strips | 2 pieces | ||
| Swab | 1 piece |
Notes:
1. Not applicable for GC-MS.
2. The amounts shown in the table are for a single round of metabolite extraction. If the sample volume is sufficient, it is recommended to provide enough for two rounds of extraction. This way, if the first extraction does not yield ideal results, it can help avoid the delay caused by having to re-submit samples.
3. Appropriate for Untargeted Metabolomics, Untargeted Plus Metabolomics, TM Widely-Targeted Metabolomics, Quantitative Lipidomics, Energy Metabolism, Amino Acids, Tryptophan, and Short-Chain Fatty Acids studies.
Sample Requirements for Plant Metabolomics Sample
| Sample Type | Sample | Recommended Sample | Biological Replicate |
| Tissue | Root, Stem, Leaf, Fruit, Flower, Bud, Node, Callus | 600 mg | Human≥30, Animal≥8, Plant≥3 |
| Fruit Peel, Seed Coat | 600 mg | ||
| Anther, Filament, Pollen, Style, Stigma, Embryo | 1.2 g | ||
| Liquid | Root Exudate | 10 ml | |
| Juice, Wine, Fermentation Broth | 5 ml | ||
| Oils, Essential Oils, Honey, Nectar, Paste | 500 μl | ||
| Herb Extract, Herb Decoction, Plant Tissue Fluid | 500 μl | ||
| Cell | Cultured Plant Cell | 1×10^7 cells | |
| Algae | 300 mg | ||
| Solid | Lyophilized Plant Powder | 200 mg | |
| Sludge, Soil | 600 mg |
Notes:
1. Not applicable for GC-MS.
2. For extracted metabolites, please advise on the recommended quantity for the extraction process.
3. Suitable for Untargeted Metabolomics, Widely-Targeted Metabolomics, Quantitative Lipidomics, Flavonoids, Carotenoid, Anthocyanin, Energy Metabolism, Amino Acids, Short-Chain Fatty Acids Metabolomics for Plants.
4. Recommended sampling approach:
– Collect samples from 3 or more individuals for each biological replicate.
– Ensure a minimum of 3 biological replicates per sample group.
– Example: Combine leaves from 3 individual plants as one replicate; repeat for 2 more replicates (involving 6 additional individual plants) to achieve
3 biological replicates for one experimental group (e.g., Control).
– Repeat the process with 9 individual plants for the second experimental group (e.g., Treatment).
Project Workflow
Metabolomics research experimental procedures encompass sample collection and pre-processing, metabolite extraction, LC-MS data acquisition, metabolite annotation and identification through database searching, and bioinformatic analysis. These steps enable researchers to gain holistic insights into the metabolic state of a system.
At Novogene, we uphold the highest standards of precision and quality control at every step of the experimental process, ensuring consistent, reliable and high-quality data for your research.
Metabolite Classification Pie Chart
Visualization of the proportion of different metabolite categories based on their respective numbers.
PCA analysis of total samples
Convert a group of variables that may have correlation into a group of linear uncorrelated variables through orthogonal transformation
PLS-DA plot
Uses partial least squares regression to establish the relationship model between the relative quantitative value of metabolites and the sample category to realize the prediction of the sample category.
Volcano plot of differential metabolites
Volcano plot of differential metabolites
Lollipop chart of different metabolites
Show the up and down-regulation of the metabolites and the substances with large difference multiple changes.
Box plot of differential metabolite
Display the measurement statistics of the central trend and the measurement statistics of the dispersion.
Differential metabolite violin map
The distribution pattern of the same metabolite across different groups.
K-Means analysis of differential metabolites
The variation trend of metabolites across different groups.
Correlation analysis of different metabolites
The consistency of variation trends between pairs of metabolites, where red indicates a positive correlation and blue indicates a negative correlation.
Chord diagram of differential metabolites
Reflects the correlation and association between pairs of differential metabolites.
Z-score analysis
The relative abundance levels across different groups.
Cluster analysis of differential metabolites
Metabolites with similar or identical metabolic patterns are clustered together to infer their functions.
KEGG enrichment bubble diagram
The hypergeometric test algorithm is used to analyze the relevant metabolic pathways associated with differential metabolites between two groups.
KEGG enrichment pathway diagram
GSEA analysis
ROC curve Analysis of differential metabolite
Use the Area Under the Curve (AUC) to evaluate the sensitivity and specificity of metabolite detection.
