Dual derivatization strategy for the comprehensive quantification and double bond location characterization of fatty acids by ultra-high performance liquid chromatography-tandem mass spectrometry

Sample preparation for fatty acid analysis in biological samples with mass spectrometry-based strategies

Fatty acids (FAs) have attracted many interests for their pivotal roles in many biological processes. Imbalance of FAs is related to a variety of diseases, which makes the measurement of them important in biological samples. Over the past two decades, mass spectrometry (MS) has become an indispensable technique for the analysis of FAs owing to its high sensitivity and precision. Due to complex matrix effect of biological samples and inherent poor ionization efficiency of FAs in MS, sample preparation including extraction and chemical derivatization prior to analysis are often employed. Here, we describe an updated overview of FA extraction techniques, as well as representative derivatization methods utilized in different MS platforms including gas chromatography-MS, liquid chromatography-MS, and mass spectrometry imaging based on different chain lengths of FAs. Derivatization strategies for the identification of double bond location in unsaturated FAs are also summarized and highlighted. The advantages, disadvantages, and prospects of these methods are compared and discussed. This review provides the development and valuable information for sample pretreatment approaches and qualitative and quantitative analysis of interested FAs using different MS-based platforms in complex biological matrices. Finally, the challenges of FA analysis are summarized and the future perspectives are prospected.

Isoniazid derivatization strategy of carboxyl-containing metabolites for LC-MS/MS-based targeted metabolomics

Metabolomics is a biochemical analysis tool for identifying metabolic phenotypes and used to reveal the pathogenic mechanisms of disease and to inform drug-targeted therapies. Carboxyl-containing metabolites (CCMs) account for an important proportion of the metabolome, but because of the diversity of physical and chemical properties of CCMs in biological samples, traditional liquid chromatography-mass spectrometry (LC-MS) targeted metabolome analysis methods cannot achieve simultaneous quantification of multiple types of CCMs. Therefore, we proposed for the first time a targeted metabolomics strategy using isoniazid derivatization combined with LC-MS/MS to simultaneously quantify 39 CCMs of 5 different types (short-chain fatty acids, amino acids, bile acids, phenylalanine and tryptophan metabolic pathway acids) with large polarity differences associated with Alzheimer's disease (AD) and significantly improve the detection coverage and sensitivity. The yields of isoniazid derivative CCMs were high and could guarantee the accuracy of CCM quantification. The LODs of CCMs increased significantly (1.25-2000-fold) after derivatization. The method showed good selectivity, intra-day and inter-day accuracies and precisions, and repeatability. There was no significant effect on the determination of CCMs in terms of matrix effect and recovery. CCMs showed good stability. And CCMs showed good stability under short-term storage and freeze-thaw cycles. At the same time, the regulatory effects of Schisandrae chinensis Fructus and Ginseng Radix et Rhizoma (SG) herb pair on CCM metabolic disorders in feces, urine, serum, and the brain of AD rats were elucidated from the perspective of targeted metabolomics. In combination with pharmacodynamic evaluation and gut microbiota analysis, the mechanism of SG herb pair on AD rats was comprehensively understood. In summary, this innovative isoniazid derivatization combined with a targeted metabolomics method has great potential for trace biological lineage analysis.

Recent progress in the analysis of unsaturated fatty acids in biological samples by chemical derivatization-based chromatography-mass spectrometry methods

Unsaturated fatty acids (UFAs) are essential fatty acids that execute various biological functions in the human body. Therefore, the qualitative and quantitative analysis of UFAs in biological samples can help to clarify their roles in the occurrence and development of diseases, so to reveal the mechanisms of pathogenesis and potential drug intervention strategies. Chromatography-mass spectrometry is one of the most commonly used techniques for the analysis of UFAs in biological samples. However, due to factors such as the complex structural information of UFAs (the number and specific location of CC double bonds) and the low concentration of UFAs in biological samples, it is still difficult to conduct accurate qualitative and/or quantitative studies of UFAs in complex biological samples. In recent years, the integration and application of chemical derivatization and chromatography-mass spectrometry has been widely used in the detection of UFAs. Based on this overview, we reviewed recent developments and application progress for chemical derivatization-based chromatography-mass spectrometry methods for the qualitative and/or quantitative analysis of UFAs in biological samples over the past ten years. Potential trends for the design and improvement of novel derivatization reagents were proposed.

A pre-column derivatization high-performance liquid chromatography method for simultaneous determination of short-chain and medium-chain fatty acids in a fecal sample

Short-chain and medium-chain fatty acids have plentiful biological functions, which play a crucial role in the diagnosis and therapy of many diseases. Herein, a new method for simultaneous quantifying 17 short-chain and medium-chain fatty acids with high-performance liquid chromatography coupled with an ultraviolet detector was developed and the pre-column derivatization by indole-3-acetic acid hydrazide was performed to improve the separation and detection. The conditions of the derivatization reaction were systematically investigated. Subsequently, the method was validated and the results showed a satisfactory linearity (linear regression coefficients > 0.9969), the limit of detection (4.0×10^-3 -1.9×10^-2 μmol/L), precision (0.9%-7.3% for intra-day and 2.0%-9.8% for inter-day), recovery (90.0%-109.1% with relative standard deviation <7.7%) and stability (0.1%-3.3% for standard solution and 0.2%-3.9% for fecal sample). Finally, the established method was successfully applied to quantify short-chain and medium-chain fatty acids in the feces of healthy control and diabetic rats. Eleven kinds of short-chain and medium-chain fatty acids were detected and six of them showed a significant difference between the control group and the model group.

Plasma fingerprint of free fatty acids and their correlations with the traditional cardiac biomarkers in patients with type 2 diabetes complicated by coronary heart disease

Type 2 diabetes mellitus (T2DM) is a well-established risk factor for cardiovascular disease, with at least 2–3 fold higher risk of cardiovascular diseases than non-diabetics. Free fatty acids (FFAs) are believed to play important roles in the occurrence of cardiovascular disease in people with T2DM. The aim of this study was to investigate the fingerprint of plasma FFAs and their correlations with the tradition risk factors of cardiovascular disease in T2DM patients complicated by coronary heart disease (CHD-T2DM). A total of 401 participants, including healthy control (HC, n = 143), T2DM patients (n = 134), and CHD-T2DM patients (n = 126) were enrolled in this study. Plasma levels of 36 FFAs with carbon chain length ranged from 3 to 22 were quantified by using reverse phase ultra-high performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS). Tradition risk factors of cardiovascular disease were tested in clinical laboratory, including homocysteine (HCY), creatine kinase (CK), high sensitivity C reactive protein (hsCRP), and N-terminal pro-brain natriuretic peptide (NT-proBNP) and so on. Almost all the FFAs with different carbon chain length and unsaturation were significantly upregulated in the T2DM-CHD groups, compared to the HC and T2DM groups. Both n-3 and n-6 polyunsaturated fatty acids (PUFA) were also found to be significantly upregulated in T2DM-CHD group compared to the T2DM group. However, no significantly differences of the n-6/n-3 PUFA ratio, arachidonic acid/eicosapentaenoic acid (AA/EPA) ratio, and arachidonic acid/docosahexaenoic acid (AA/DHA) ratio were observed between T2DM-CHD and T2DM groups. Plasma FFA levels were found to be positively correlated with HCY, CK, hsCRP, NT-proBNP and other tradition risk factors of CHD. Multivariate logistic regression analysis indicated that a dozens of FFAs were the independent risk factors of CHD after adjustment for confounding factors and other risk factors. Excessively high plasma levels of FFAs were demonstrated to be independent risk factors for CHD in patients with T2DM, despite of the differences in chain length, unsaturation, and double bond position.

Simultaneous quantification of eleven short-chain fatty acids by derivatization and solid phase microextraction - Gas chromatography tandem mass spectrometry

As metabolites of the gut microbiome, short-chain fatty acids (SCFAs) played an important role in the diagnosis of the metabolic diseases. Because of the high polarity, high volatility and complex matrix of biological samples, the highly sensitive, selective and accurate method to determine SCFAs remains a major challenge. Herein, a new method for simultaneous quantification of eleven SCFAs by derivatization combined with solid phase microextraction (SPME) and gas chromatography tandem mass spectrometry (GC-MS/MS) was developed. Isobutyl chloroformate coupled with isobutanol was used as the reaction reagent to derivatize SCFAs. The method validation data showed a satisfactory linearity with the linear regression coefficients (R) ranging from 0.9964 to 0.9996. The limit of detection (LOD) of all SCFAs ranges from 0.01 ng·mL^-1 to 0.72 ng·mL^-1 and the limit of quantification (LOQ) ranges from 0.04 ng·mL^-1 to 2.41 ng·mL^-1. The intra-day and inter-day precision (RSDs) ranged from 0.65% to 8.92% and 1.62% to 15.61%, respectively. The recovery ranged from 88.10% to 108.71%. Finally, the developed method was successfully used to determine SCFAs in mice fecal sample, and ten of the SCFAs were found in feces of mice, including formic acid.