A Comprehensive Review of Instrumentation and Applications in Post-Column and In-Source Derivatization for LC-MS

Liquid chromatography-mass spectrometry (LC-MS) has become an indispensable tool for elucidating molecular structures and quantifying diverse compounds within complex mixtures. Despite its versatility, it faces various challenges such as ion suppression, low sensitivity, analyte instability, and matrix effects, which are being overcome by different kinds of offline and online derivatization techniques to improve specificity and reduce potential interferences. In this context, considerable advancements have been made in reviewing and critically evaluating a wide range of developed methods and techniques; however, little attention has been given to post-column derivatization (PCD) in LC-MS. Therefore, this comprehensive review highlights state-of-the-art advancements in LC-MS with a specific focus on various types of chemical and physical PCD, and in-source derivatization. It also examines the latest instrumentation developments, highlights methods and influencing factors, and explores applications in food, proteomics, biology, pharmaceuticals, and environmental analysis from the past four decades. Besides, this review critically examines the role of PCD in LC-MS along with outlining its advantages and disadvantages. Furthermore, special emphasis is also made on prospects and insights for developing more versatile LC-PCD-MS techniques and in-source methodologies, to address ongoing challenges and aim to open new research avenues for analysts.

A sensitive post-column derivatization approach for enhancing hydroxyl metabolites detection

BACKGROUND

Chemical derivatization is a common technique in liquid chromatography-mass spectrometry (LC-MS) metabolomics used to improve the ionizability and chromatographic properties of metabolites in complex biological samples. This process facilitates better detection and separation of a wide array of compounds. The reagent 2-(4-boronobenzyl) isoquinolin-2-ium bromide (BBII), developed as a glucose labeling reagent for matrix-assisted laser desorption/ionization MS, enhances ionization for glucose and other hydroxyl metabolites. Its quaternary ammonium group increases ionization efficiency, and its rapid reaction time simplifies pretreatment procedures.

RESULTS

We developed a novel post-column derivatization (PCD) method using BBII to boost the detection sensitivity of hydroxyl metabolites in LC-MS. By optimizing this BBII PCD approach with 14 hydroxyl-containing compounds, we were able to detect previously undetectable metabolites such as glucose, ribose, and long-chain alcohols. Sensitivity enhancements for these metabolites ranged from 1.1 to 42.9-fold. Applying this method to metabolic profiling of hydroxyl metabolites in the DBTRG-05MG glioblastoma cell line, with and without treatment with the new drug MFB [1-(4-chlorobenzyl)-2-(5-methyl-2-furfurylideneamino)benzimidazole], revealed several hydroxyl metabolites with significantly reduced levels post-treatment.

SIGNIFICANCE AND NOVELTY

This study presents a new BBII PCD method that substantially improves the detection sensitivity of hydroxyl metabolites in LC-MS. This innovative approach is highly valuable for untargeted metabolomics studies in biological and clinical research, offering a robust tool for identifying metabolite changes and advancing our understanding of metabolic processes in disease and therapeutic contexts.

An economically viable stable isotope-enhanced multiple reaction monitoring method for total fatty acid analysis in a mouse model of non-alcoholic fatty liver disease

The complex pathological mechanisms of non-alcoholic fatty liver disease (NAFLD) are closely related to dysregulated lipid metabolism, and the therapeutic effects of the traditional Chinese medicine Zexie-Baizhu Decoction (AA) on NAFLD have been gaining increasing attention. However, research into altered lipid metabolism, especially fatty acids, in NAFLD and the intervention of AA faces technical challenges, especially in the precise quantitative analysis of fatty acids in biological samples. The high complexity of biological matrices, particularly after drug intervention, greatly increases the difficulty of detection. Therefore, this study innovatively developed a simple and economical stable isotope derivatization technique by synthesizing d6N,N-dimethylethylenediamine (d6-DMED) in the laboratory, establishing a simple and economical method for fatty acid quantification. This method employs a chemical reaction under low-temperature conditions to ensure the efficient synthesis of d6-DMED. Using ultra-high performance liquid chromatography-triple quadrupole mass spectrometry technique (UHPLC-MS/MS), combined with optimized chromatographic separation conditions and dynamic multiple reaction monitoring mode, the study established a highly sensitive detection method for 35 fatty acid derivatives. Methodological evaluation showed that the limits of quantification ranged from 0.002 to 0.060 μM, with high linearity of R² > 0.995. Additionally, the relative recovery rates were between 93.14% and 106.63%. To further demonstrate the feasibility of this method for fatty acid quantification, it was applied to measure fatty acids in multiple tissues in a mouse NAFLD model, as well as the effects of AA intervention on fatty acid metabolism. This rapid, simple, and cost-effective detection method not only enhances the understanding of NAFLD mechanisms but also provides a new strategy for evaluating the biological complex system after drug intervention.

Soil metabolomics: Deciphering underground metabolic webs in terrestrial ecosystems

Soil metabolomics is an emerging approach for profiling diverse small molecule metabolites, i.e., metabolomes, in the soil. Soil metabolites, including fatty acids, amino acids, lipids, organic acids, sugars, and volatile organic compounds, often contain essential nutrients such as nitrogen, phosphorus, and sulfur and are directly linked to soil biogeochemical cycles driven by soil microorganisms. This paper presents an overview of methods for analyzing soil metabolites and the state-of-the-art of soil metabolomics in relation to soil nutrient cycling. We describe important applications of metabolomics in studying soil carbon cycling and sequestration, and the response of soil organic pools to changing environmental conditions. This includes using metabolomics to provide new insights into the close relationships between soil microbiome and metabolome, as well as responses of soil metabolome to plant and environmental stresses such as soil contamination. We also highlight the advantage of using soil metabolomics to study the biogeochemical cycles of elements and suggest that future research needs to better understand factors driving soil function and health.

Unravelling the brain metabolome: A review of liquid chromatography - mass spectrometry strategies for extracellular brain metabolomics

The analysis of the brain extracellular metabolome is of interest for numerous subdomains within neuroscience. Not only does it provide information about normal physiological functions, it is even more of interest for biomarker discovery and target discovery in disease. The extracellular analysis of the brain is particularly interesting as it provides information about the release of mediators in the brain extracellular fluid to look at cellular signaling and metabolic pathways through the release, diffusion and re-uptake of neurochemicals. In vivo samples are obtained through microdialysis, cerebral open-flow microperfusion or solid-phase microextraction. The analytes of potential interest are typically low in concentration and can have a wide range of physicochemical properties. Liquid chromatography coupled to mass spectrometry has proven its usefulness in brain metabolomics. It allows sensitive and specific analysis of low sample volumes, obtained through different approaches. Several strategies for the analysis of the extracellular fluid have been proposed. The most widely used approaches apply sample derivatization, specific stationary phases and/or hydrophilic interaction liquid chromatography. Miniaturization of these methods allows an even higher sensitivity. The development of chiral metabolomics is indispensable, as it allows to compare the enantiomeric ratio of compounds and provides even more challenges. Some limitations continue to exist for the previously developed methods and the development of new, more sensitive methods remains needed. This review provides an overview of the methods developed for sampling and liquid chromatography-mass spectrometry analysis of the extracellular metabolome.

A rapid and robust method for amino acid quantification using a simple N-hydroxysuccinimide ester derivatization and liquid chromatography-ion mobility-mass spectrometry

The vast majority of mass spectrometry (MS)-based metabolomics studies employ reversed-phase liquid chromatography (RPLC) to separate analytes prior to MS detection. Highly polar metabolites, such as amino acids (AAs), are poorly retained by RPLC, making quantitation of these key species challenging across the broad concentration ranges typically observed in biological specimens, such as cell extracts. To improve the detection and quantitation of AAs in microglial cell extracts, the implementation of a 4-dimethylaminobenzoylamido acetic acid N-hydroxysuccinimide ester (DBAA-NHS) derivatization agent was explored for its ability to improve both analyte retention and detection limits in RPLC-MS. In addition to the introduction of the DBAA-NHS labeling reagent, a uniformly (U) ¹³C-labeled yeast extract was also introduced during the sample preparation workflow as an internal standard (IS) to eliminate artifacts and to enable targeted quantitation of AAs, as well as untargeted amine submetabolome profiling. To improve method sensitivity and selectivity, multiplexed drift-tube ion mobility (IM) was integrated into the LC-MS workflow, facilitating the separation of isomeric metabolites, and improving the structural identification of unknown metabolites. Implementation of the U-¹³C-labeled yeast extract during the multiplexed LC-IM-MS analysis enabled the quantitation of 19 of the 20 common AAs, supporting a linear dynamic range spanning up to three orders of magnitude in concentration for microglial cell extracts, in addition to reducing the required cell count for reliable quantitation from 10 to 5 million cells per sample.

Ion-Pairing Chromatography and Amine Derivatization Provide Complementary Approaches for the Targeted LC-MS Analysis of the Polar Metabolome

Liquid chromatography coupled to mass spectrometry is a key metabolomics/metabonomics technology. Reversed-phase liquid chromatography (RPLC) is very widely used as a separation step, but typically has poor retention of highly polar metabolites. Here, we evaluated the combination of two alternative methods for improving retention of polar metabolites based on 6-aminoquinoloyl-N-hydroxysuccinidimyl carbamate derivatization for amine groups, and ion-pairing chromatography (IPC) using tributylamine as an ion-pairing agent to retain acids. We compared both of these methods to RPLC and also to each other, for targeted analysis using a triple-quadrupole mass spectrometer, applied to a library of ca. 500 polar metabolites. IPC and derivatization were complementary in terms of their coverage: combined, they improved the proportion of metabolites with good retention to 91%, compared to just 39% for RPLC alone. The combined method was assessed by analyzing a set of liver extracts from aged male and female mice that had been treated with the polyphenol compound ampelopsin. Not only were a number of significantly changed metabolites detected, but also it could be shown that there was a clear interaction between ampelopsin treatment and sex, in that the direction of metabolite change was opposite for males and females.

Progress and Challenges in Quantifying Carbonyl-Metabolomic Phenomes with LC-MS/MS

Carbonyl-containing metabolites widely exist in biological samples and have important physiological functions. Thus, accurate and sensitive quantitative analysis of carbonyl-containing metabolites is crucial to provide insight into metabolic pathways as well as disease mechanisms. Although reversed phase liquid chromatography electrospray ionization mass spectrometry (RPLC-ESI-MS) is widely used due to the powerful separation capability of RPLC and high specificity and sensitivity of MS, but it is often challenging to directly analyze carbonyl-containing metabolites using RPLC-ESI-MS due to the poor ionization efficiency of neutral carbonyl groups in ESI. Modification of carbonyl-containing metabolites by a chemical derivatization strategy can overcome the obstacle of sensitivity; however, it is insufficient to achieve accurate quantification due to instrument drift and matrix effects. The emergence of stable isotope-coded derivatization (ICD) provides a good solution to the problems encountered above. Thus, LC-MS methods that utilize ICD have been applied in metabolomics including quantitative targeted analysis and untargeted profiling analysis. In addition, ICD makes multiplex or multichannel submetabolome analysis possible, which not only reduces instrument running time but also avoids the variation of MS response. In this review, representative derivatization reagents and typical applications in absolute quantification and submetabolome profiling are discussed to highlight the superiority of the ICD strategy for detection of carbonyl-containing metabolites.

An Integrated Strategy for Rapid Discovery and Identification of Quality Markers in Gardenia Fructus Using an Omics Discrimination-Grey Correlation-Biological Verification Method

Background: Gardenia Fructus (GF), a traditional Chinese medicine of Gardenia Ellis in Rubiaceae family, has the potential to clear heat and purge fire and has been widely used to treat multiple infection-related diseases. However, the quality markers (Q-Markers) of GF have not been revealed comprehensively.

Methods: In this experiment, the transgenic zebrafish lines, Tg (l-fabp:EGFP) and Tg (lyz:EGFP), were used to evaluate two main kinds of traditional efficacies of GF, hepatoprotective and anti-inflammatory effects. All the GF samples from different production areas were tested their anti-liver injury and anti-inflammantory activities. High-performance liquid chromatography-quadrupole time-of-flight mass spectrometry method (HPLC-Q-TOF/MS) was employed for herbal metabonomic analysis of GF samples. Gray correlation analysis (GCA) was utilized to screen out the components closely associated with the activities. Finally, the zebrafish model was applied to verify the bioactivity of the crucial components to determine the Q-Markers of GF.

Results: The zebrafish models were established by inducing with hydrogen peroxide or copper sulfate and applied to quickly evaluate the hepatoprotective effect and inflammation of GF samples. 27 potentially active components for liver protection and 21 potentially active components with anti-inflammatory properties were identified by herbal metabolomic analysis based on HPLC-Q-TOF/MS. The GCA result showed that five of the 27 components were highly correlated with liver protection, 15 of the 21 components were highly correlated with anti-inflammatory activity. Among them, geniposide and crocin-1 were confirmed their bioactivities on zebrafish experiment to be responsible for the protective effects of GF against liver injury, and genipin-1-β-D-gentiobioside, quinic acid, gardenoside, d-glucuronic acid, l-malic acid, mannitol, rutin, and chlorogenic acid were confirmed to be responsible for the anti-inflammatory effects. Finally, according to the screening principles of Q-Markers, genipin-1-β-D-gentiobioside, geniposide, and gardenoside were preliminarily identified to be the Q-Markers of GF.

Conclusion: This study established an effective research strategy of “Omics Discrimination-Grey Correlation-Biological Verification,” which enabled the rapid identification of key pharmacological components of GF. These markers have provided a scientific basis for constructing a modern quality evaluation system for GF.

Quantitative analysis of the relationship of derivatization reagents and detection sensitivity of electrospray ionization-triple quadrupole tandem mass spectrometry: Hydrazines as prototypes

Chemical derivatization-assisted electrospray ionization-triple quadrupole mass spectrometry (ESI-QqQ-MS) has become an efficient tool for the quantification of low-molecular-weight molecules. Many studies found that the derivatives of the same analytes derivatized by different derivatization reagents with the same reaction group had different detection sensitivity, even under the same conditions of electrospray ionization-mass spectrometry (ESI-MS). This phenomenon was suggested to be caused by the different modifying groups in the derivatization reagents. However, there is still a lack of systematic study on how modifying groups in the derivatization reagents affect the detection sensitivity of their corresponding derivatives of analytes, especially theoretical investigations. In this study, we employed a quantitative structure-activity relationship (QSAR) modeling approach to explore the relationship between modifying group structures and the detection sensitivity of derivatization reagents and their derivatives during ESI-MS detection. A total of 110 derivatization reagents of the hydrazine family and their hexanal derivatives (substituted hydrazones) were selected as the prototypes to construct QSAR models. The established models suggested that several molecular descriptors, related to hydrophobicity, electronegativity, and molecular shape, were related to the detection sensitivity of hexanal derivatives induced by different modifying groups in the derivatization reagents. Besides, we found that the detection sensitivity of compounds detected in selected ion mode (SIM) showed a positive correlation with that obtained in multiple reaction monitoring mode (MRM), and the ionization efficiency was the key factor on the detection sensitivity in both modes.

Derivatization procedures and their analytical performances for HPLC determination in bioanalysis

Derivatization, or chemical structure modification, is often used in bioanalysis performed by liquid chromatography technique in order to enhance detectability or to improve the chromatographic performance for the target analytes. The derivatization process is discussed according to the analytical procedure used to achieve the reaction between the reagent and the target compounds (containing hydroxyl, thiol, amino, carbonyl and carboxyl as the main functional groups involved in derivatization). Important procedures for derivatization used in bioanalysis are in situ or based on extraction processes (liquid-liquid, solid-phase and related techniques) applied to the biomatrix. In the review, chiral, isotope-labeling, hydrophobicity-tailored and post-column derivatizations are also included, based on representative publications in the literature during the last two decades. Examples of derivatization reagents and brief reaction conditions are included, together with some bioanalytical applications and performances (chromatographic conditions, detection limit, stability and sample biomatrix).

Discovery and identification of antithrombotic chemical markers in Gardenia Fructus by herbal metabolomics and zebrafish model

ETHNOPHARMACOLOGICAL RELEVANCE

Gardenia Fructus (GF), a traditional Chinese medicine for clearing heat and purging fire, has been reported to use to treat thrombotic related diseases, but the antithrombotic components are not clear.

AIM OF THE STUDY

To develop efficient research methods for discovering some representative antithrombotic compounds of GF.

MATERIALS AND METHODS

AB line zebrafish induced by arachidonic acid (AA) was used as a fast and trace-sample-required valuation model for antithrombptic effect of GF samples. Among nine samples of GF from different production areas, two samples with the largest difference in bioactivity were selected for downstream analysis. High-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF/MS) was applied to detect compounds in the GF samples. And herbal metabolomics and grey correlation analysis (GCA) were used to identify crucial compounds with potential antithrombotic activity. Then the bioactivity of those important compounds was verified on the zebrafish model. Network pharmacology was used to explore the protein targets and signaling pathways of these compounds.

RESULTS

Among the GF samples, S1 (Huoshan City, Anhui Province), and S6 (Jichun City, Hubei Province), significantly differed in thrombus inhibiting bioactivity. HPLC-Q-TOF/MS identified a total of 614 compounds in each GF sample. 19 compounds were selected as important potential variables from metabolomics data by orthogonal partial least squares discriminant analysis (OPLS-DA). And 10 compounds among them were further found to be positively correlated with the antithrombotic bioactivity of GF by GCA. Finally, 3 compounds in them, geniposide, citric acid, and quinic acid, were confirmed as representative antithrombotic chemical markers of GF. Using network pharmacology analysis, some key protein targets, such as proto-oncogene tyrosine-protein kinase Src (SRC) and cyclin-dependent kinase 2 (CDK2), and some signaling pathways were found to supply powerful evidence about antithrombotic mechanisms of three compounds and GF.

CONCLUSIONS

This research have succeeded to discover and identify three representative antithrombotic compounds of GF using an efficient integrated research strategy we established, an Omics Discriminant-Grey Correlation-Biological Activity strategy. The antithrombotic chemical makers we found could also contribute to provided more accurate index components for comprehensive quality control of GF.

Metabolomics in pharmacology - a delve into the novel field of pharmacometabolomics

Introduction: Pharmacometabolomics is an emerging science pursuing the application of precision medicine. Combining both genetic and environmental factors, the so-called pharmacometabolomic approach guides patient selection and stratification in clinical trials and optimizes personalized drug dosage, improving efficacy and safety.Areas covered: This review illustrates the progressive introduction of pharmacometabolomics as an innovative solution for enhancing the discovery of novel drugs and improving research and development (R&D) productivity of the pharmaceutical industry. An extended analysis on published pharmacometabolomics studies both in animal models and humans includes results obtained in several areas such as hepatology, gastroenterology, nephrology, neuropsychiatry, oncology, drug addiction, embryonic cells, neonatology, and microbiomics.Expert opinion: a tailored, individualized therapy based on the optimization of pharmacokinetics and pharmacodynamics, the improvement of drug efficacy, and the abolition of drug toxicity and adverse drug reactions is a key issue in precision medicine. Genetics alone has become insufficient for deciphring intra- and inter-individual variations in drug-response, since they originate both from genetic and environmental factors, including human microbiota composition. The association between pharmacogenomics and pharmacometabolomics may be considered the new strategy for an in-deep knowledge on changes and alterations in human and microbial metabolic pathways due to the action of a drug.

LC–MS/MS method for quantification of 3,4-dihydroxyphenylglycol, a norepinephrine metabolite in plasma and brain regions

Aim: To evaluate suitability of the LC–MS/MS method to quantify 3,4-dihydroxyphenylglycol (DHPG) that is used as a biomarker for monoamine oxidase (MAO) inhibition. Methods: DHPG was extracted using alumina basic cartridges and quantified on a triple quadrupole mass spectrometer using negative electrospray ionization, without the use of derivatization reagents. Results: Modulation of DHPG levels was observed following administration of selective and nonselective MAO inhibitors and results were in correlation with historical MAO inhibition potential of compounds. Conclusion: The proposed method is sensitive enough to measure plasma DHPG levels and DHPG can be used as a biomarker to assess MAO inhibition potential of new therapeutic agents.

Spatio-temporal profiling of abscisic acid, indoleacetic acid and jasmonic acid in single rice seed during seed germination

Abscisic acid (ABA), indoleacetic acid (IAA) and jasmonic acid (JA) are plant hormones that were reported to play indispensable roles during seed germination. However, the interactions between these plant hormones during rice seed germination have still not been explored clearly. A sensitive method for determination of these plant hormones would be beneficial for the exploration of such interactions. Herein, we present a liquid chromatography coupled with mass spectrometry (LC-MS) method for the quantification of ABA, IAA and JA in a single tissue of rice seed to investigate the spatio-temporal distribution of these plant hormones during rice seed germination. To this end, an in silico strategy was developed in order to select a derivatization reagent with an ideal sensitivity of MS detection. This strategy was confirmed with experimental studies on three reagents N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide (EDC), N,N-dimethylethylenediamine (DMED), and N-(acridin-9-yl)-2-bromoacetamide (AYBA) and their formic acid derivatives. Our results from the in silico and LC-MS experiments show that AYBA is a good derivatization reagent for ABA, IAA and JA due to its reasonable ionization efficiency in electrospray ionization mass spectrometry (ESI-MS) and excellent hydrophobicity. Finally, a sensitive LC-MS method upon AYBA was established for the determination of ABA, IAA and JA in germinated seeds. Good linearities for ABA, IAA, and JA were obtained with correlation coefficients greater than 0.99. The limits of detection (LODs) were in the range of 0.14-0.16 pg mL^-1. The method exhibits good precisions with RSD 1.5%-13.8% (intra-day) and 1.2%-7.3% (inter-day) and acceptable recoveries (88.6%-102.9%, n = 6). Finally, the method was successfully employed in the spatio-temporal profiling of ABA, IAA and JA in a single tissue of rice seed during rice seed germination.