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Free Fatty Acids

Covers 53 key free fatty acids (FFAs) across medium-, long-, and very-long-chain species.
53 calibration curves (r > 0.99) ensure accurate and reproducible FFA quantification.
Detects FFAs at ng/mL levels via GC–MS for high-sensitivity lipid profiling.
Comprehensive quality control ensures data accuracy, consistency, and reliability.

Introduction to Free Fatty Acid (FFA) Targeted Metabolomics

Free fatty acids (FFAs), also known as non-esterified fatty acids (NEFAs), are crucial intermediates in lipid metabolism, acting as essential energy sources, signaling molecules, and regulators of diverse biochemical pathways. They participate in key physiological processes including energy production, membrane formation, and metabolic regulation, maintaining cellular and organismal homeostasis across both animal and plant systems. In humans and animals, FFAs (NEFAs) play a central role in β-oxidation and lipid signaling, and their dysregulation is strongly associated with metabolic disorders including obesity, diabetes, and insulin resistance. In plants, FFAs serve as precursors for complex lipids and lipid-derived signaling molecules that mediate growth, stress responses, and energy storage. Comprehensive profiling of FFAs and NEFAs thus enables deeper insights into lipid metabolism and its role in health, development, and environmental adaptation across biological systems.
MetwareBio’s FFA-targeted metabolomics service provides absolute quantification of 53 core free fatty acids using an advanced GC-MS platform, with both internal and external standards ensuring high analytical accuracy. Powered by our proprietary database and cutting-edge technology, this service covers a comprehensive range of fatty acids, including medium-, long-, and very-long-chain straight-chain saturated fatty acids, as well as monounsaturated and polyunsaturated fatty acids, with carbon chain lengths ranging from C6 to C24.

Free Fatty Acid (FFA) Targeted Metabolomics Service technology workflow

 

Technology Superiority of GC-MS Free Fatty Acid Analysis

Comprehensive coverage
Targets 53 core free fatty acids, encompassing medium-, long-, and very-long-chain saturated, monounsaturated, and polyunsaturated fatty acids (C6–C24).
Absolute Quantitation
Internal-standard correction combined with external calibration—53 calibration curves with correlation coefficients (r) > 0.99 ensure precise quantification.
High Sensitivity
Agilent 8890-7000E GC–MS platform enables detection of free fatty acids at nanogram-per-milliliter (ng/mL) levels with exceptional reproducibility.
Rigorous Quality Control
Data reliability ensured through method blanks, solvent blanks, and mixed standards, guaranteeing robust and reproducible analytical performance.

Applications of Free Fatty Acid Quantification

Metabolic Health & Biomarker Discovery
Cancer Metabolism & Therapeutic Evaluation

Comprehensive FFA quantification reveals metabolic reprogramming in cancer, where enhanced fatty acid synthesis and oxidation support tumor growth and survival. Monitoring specific FFA patterns can uncover lipid-driven oncogenic pathways, immune–metabolic crosstalk, and treatment resistance mechanisms. These molecular signatures serve as actionable indicators for evaluating drug efficacy, metabolic targeting, and precision oncology development.

Pharmacology, Nutrition & Microbiome Research

Dynamic changes in FFA composition provide sensitive indicators of pharmacological and nutritional interventions. Quantitative FFA profiling supports studies on lipid-modulating drugs, dietary fatty acid utilization, and host–microbiome metabolic interactions. Integrated with PK/PD and time-course analysis, these data enable mechanism-of-action elucidation and translational insight into lipid-based therapeutic strategies.

Plant Lipid Metabolism & Stress Adaptation

In plants, FFAs are central intermediates in lipid biosynthesis, energy storage, and signaling. Their composition dynamically responds to abiotic and biotic stresses such as drought, salinity, temperature fluctuations, and pathogen attack. FFA profiling reveals adaptive metabolic shifts and informs the study of lipid remodeling, membrane stability, and stress tolerance. In oilseed and crop research, FFA profiles also correlate with oil content, composition, and quality traits, supporting breeding, germplasm evaluation, and metabolic engineering.

List of Free Fatty Acid Analytes

Index Abbr. Compound CAS No.
1 C6-0 hexanoic acid 142-62-1
2 C8-0 octanoic acid 124-07-2
3 C9-0 nonanoic acid 112-05-0
4 C10-0 decanoic acid 334-48-5
5 C11-1n1c cis-10-undecenoic acid 112-38-9
6 C11-0 undecanoic acid 112-37-8
7 C12-1n1c cis-11-dodecenoic acid 65423-25-8
8 C12-0 dodecanoic acid (lauric acid) 143-07-7
9 C13-1n1c cis-12-tridecenoic acid 6006-06-0
10 C13-0 tridecanoic acid 638-53-9
11 C14-1n5c cis-9-tetradecenoic acid (myristoleic acid) 544-64-9
12 C14-0 tetradecanoic acid (myristic acid) 544-63-8
13 C15-1n5c cis-10-pentadecenoic acid 84743-29-3
14 C15-0 pentadecanoic acid 1002-84-2
15 C16-1n7c cis-9-hexadecenoic acid (palmitoleic acid) 373-49-9
16 C16-1n7t trans-9-hexadecenoic acid (trans-palmitoleic acid) 10030-73-6
17 C16-0 hexadecanoic acid(palmitic acid) 57-10-3
18 C17-1n7c cis-10-heptadecanoic acid 29743-97-3
19 C17-1n7t trans-10-heptadecenoic acid 126761-43-1
20 C17-0 heptadecanoic acid(margaric acid) 506-12-7
21 C18-3n6c cis-6,9,12-octadecatrienoic acid(gamma-linolenic acid) 506-26-3
22 C18-2n6c cis-9,12-octadecadienoic acid(linoleic acid) 60-33-3
23 C18-1n9c cis-9-octadecenoic acid(oleic acid) 112-80-1
24 C18-2n6t trans-9,12-octadecadienoic acid(linoelaidic acid) 506-21-8
25 C18-3n3c cis-9,12,15-octadecatrienoic acid(alpha-linolenic acid) 463-40-1
... ...

 

Contact for a full list.

Project Workflow for FFA Targeted Metabolomics

Sample Requirement for Free Fatty Acid Analysis

Sample Class Sample Type Sample Description Recommended sample size Minimum sample size
Plant Samples Tissue Stem, Shoot, Node, Leaf, Root, Flower, Pollen, Cotyledon, Seed 300 mg 200 mg
Liquid I Root exudates, Alcohol 2 ml /
Liquid II Fermentation liquid, Tissue fluid, Extract solution, Juice, Plant oil 200 µl 50 µl
Human/Animal samples Liquid I Plasma, Serum, Hemolymph, Whole Blood, Milk, Egg White 100 µl 50 µl
Liquid II Cerebrospinal Fluid (CSF), Interstitial fluid (TIF), Urine, Pancreatic Juice, Bile, Peritoneal Effusion, Lenticular Fluid, Rostral-tail Fluid, Tissue Fluid, Culture Medium (liquid), Sputum Supernatant, Tears, Aqueous humor, Digestive Juices, Bone Marrow (liquid) 100 µl 50µl
Liquid III Seminal Plasma, Amniotic Fluid, Prostatic Fluid, Rumen Fluid, Respiratory Condensate, Gastric lavage fluid, Bronchoalveolar Lavage Fluid (BALF), Urine, Sweat, Saliva, Sputum 500 µl 50 µl
Tissue I Small Animal Tissues, Placenta, Blood clot, Nematode, Zebrafish (whole fish), Bone Marrow (solid), Nail 100 mg 20 mg
Tissue II Large Animal Tissues, Whole Insect body, Wings (of insects), Pupae, Eggs, Cartilage, Bone (solid) 500 mg 20 mg
Tissue III Zebrafish Organs, Insect Organs, Whole micro-insect body (e.g., Drosophila) 20 units /
Others Solid I Feces, Intestinal Contents, Lyophilized Fecal Powder 200 mg 20 mg
Solid II Milk Powder, Microbial Fermentation Product (solid), Culture Medium (solid), Medium, Lyophilized Tissue Powder, Feed, Egg yolk, Lyophilized Egg Powder 100 mg 20 mg
Solid III Honey, Nasal Mucus, Sputum 2 g 500 mg
Solid IV Sludge, Soil 600 mg 300 mg
Cell I Adherent Cells, Animal Cell Lines 2×10^7 cells 1×10^7 cells
Cell II E.Coli, Yeast Cells 1×10^10 cells 5×10^8 cells
Cell III Small Amount of Fungal Mycelial, Bacterial/Mycelial, Unicellular Algae (Cyanobacteria), Large quantities of Bacterial Hyphae (sediment), Mucilaginous Leptopelagic Cluster (hyphae), 100 mg /
Organelle I Lysosomes, Mitochondria, Endoplasmic Reticulum 4×10^7 cells 1×10^7 cells
Organelle II Exosomes, Extracellular Vesicles 2×10^9 particles 1×10^8 particles
Special Sample I Skin Tape or Patch 2 pieces 1 piece
Special Sample II Test Strips 2 pieces 1 piece
Special Sample III Swab 1 piece 1 piece

Case Study of GC-MS Free Fatty Acid Profiling

(Supported by MetwareBio’s free fatty acid analysis)

Article:  Carbohydrate Repartitioning in the Rice Starch Branching Enzyme IIb Mutant Stimulates Higher Resistant Starch Content and Lower Seed Weight Revealed by Multiomics Analysis


Abstract:

The starch branching enzyme IIb mutant (be2b) in rice significantly increases the resistant starch (RS) content and leads to reduced seed weight. However, the underlying metabolic mechanisms remain unclear. Proteomic analysis indicated that upregulation of starch synthase IIa (SSIIa) and SSIIIa and downregulation of BEI and SSI were possibly responsible for the decreased short amylopectin chains (DP 6-15) and increased longer chains (DP > 16) of be2b starch. The upregulation of granule-bound starch synthase led to increased amylose content (AC). These changes in the amylopectin structure and AC accounted for the increased RS content. α-Amylase 2A showed the strongest upregulation (up to 8.45-fold), indicating that the loss of BEIIb activity enhanced starch degradation. Upregulation of glycolysis-related proteins stimulated carbohydrate repartitioning through glycerate-3-phosphate and promoted the accumulation of tricarboxylic acid cycle intermediates, amino acids, and fatty acids. The unexpected carbohydrate partitioning and enhanced starch degradation resulted in the reduced seed weight in the be2b mutant.

Possible metabolic pathway of fatty acids in the be2b endosperm (Chen et al., 2022)

 

Reference

Chen Y, Luo L, Xu F, Xu X, Bao J. Carbohydrate Repartitioning in the Rice Starch Branching Enzyme IIb Mutant Stimulates Higher Resistant Starch Content and Lower Seed Weight Revealed by Multiomics Analysis. J Agric Food Chem. 2022;70(31):9802-9816. doi:10.1021/acs.jafc.2c03737

 

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