Method to Calculate the Retention Index in Hydrophilic Interaction Liquid Chromatography Using Normal Fatty Acid Derivatives as Calibrants

A novel endogenous retention-index for minimizing retention-time variations in metabolomic analysis with reversed-phase ultrahigh-performance liquid-chromatography and mass spectrometry

Consistent retention time (tR) of metabolites is vital for identification in metabolomic analysis with ultrahigh-performance liquid-chromatography (UPLC). To minimize inter-experimental tR variations from the reversed-phase UPLC-MS, we developed an endogenous retention-index (endoRI) using in-sample straight-chain acylcarnitines with different chain-length (LC, C0-C26) without additives. The endoRI-corrections reduced the tR variations caused by the combined changes of mobile phases, gradients, flow-rates, elution time, columns and temperature from up to 5.1 min-0.2 min for most metabolites in a model metabolome consisting of 91 metabolites and multiple biological matrices including human serum, plasma, fecal, urine, A549 cells and rabbit liver extracts. The endoRI-corrections also reduced the inter-batch and inter-platform tR variations from 1.5 min to 0.15 min for 95 % of detected features in the above biological samples. We further established a quantitative model between tR and LC for predicting tR values of acylcarnitines when absent in samples. This makes it possible to compare metabolites' tR from different tR databases and the UPLC-based metabolomic data from different batches.

BART: A transferable liquid chromatography retention time library for bile acids

Identification of unknown bile acids, especially the distinguishment between isomers, requires retention times of a large number of reference standards, which are often not commercially available. Meanwhile, published retention information cannot be directly transferred across labs due to the differences between liquid chromatography (LC) systems, such as different extra column volume and dwell volume. To improve this situation, a transferrable retention time library for bile acids named BART was developed. BART was composed of isocratic retention models of 272 bile acids and a software tool to predict their gradient retention times on various LC systems. The isocratic retention times of bile acids were acquired on a Waters BEH C18 column with mobile phases of acidic ammonium acetate buffer and acetonitrile, and fit to the quadratic solvent strength model (QSSM). Segmented linear gradient retention times were calculated with holdup time (t0), dwell time (tD) and actual gradient profile corrected using 21 bile acid calibration standards. In addition to the reference system where the isocratic retention times were acquired, this approach has been validated on four other LC-MS systems in four labs with two gradient methods. Average root mean square errors (RMSE) between predicted and experimental retention times were 0.052 and 0.054 min for the two gradients tested, which were 9-fold more accurate than referring to a static retention time library. The library is freely available at https://bafinder.github.io/.

A dataset of branched fatty acid esters of hydroxy fatty acids diversity in foods

Branched fatty acid esters of hydroxy fatty acids (FAHFAs) are a class of bioactive lipids that show therapeutic potential for diabetes, anti-cancer and inflammation. These FAHFAs can be obtained through dietary intake, potentially improving human health. However, there is currently inadequate knowledge regarding the presence and variety of FAHFAs in different foods. Herein, we profile FAHFAs from 12 typical food samples and 4 medicinal food samples with the aid of our previous established chemical isotope labeling-assisted liquid chromatography-mass spectrometry method and build a comprehensive dataset of FAHFA diversity. The dataset comprised a total of 1207 regioisomers belonging to 298 different families, with over 100 families being newly discovered for the first time. Therefore, our findings contribute valuable insights into the molecular diversity and presence of FAHFA in a range of foods. This dataset serves as a foundation for further exploration of the nutritional and medicinal functions of FAHFAs.

Analytical Strategy for Oxylipin Annotation by Combining Chemical Derivatization-Based Retention Index Algorithm and Feature Tandem Mass Spectrometric Fragmentation as a Biomarker Discovery Tool

Accurate oxylipin annotation is crucial for advancing our understanding of physiological processes in health and disease and identifying biomarkers. However, a full view of oxylipins for early diagnosis needs further attention due to the lack of proper analytical methods, which may be attributed to the wide dynamic range, poor sensitivity, extreme molecular complexity, and limited commercially available standards of oxylipins. Here, we devised a novel method by combining a chemical derivatization (CD)-based retention index (RI) algorithm and feature tandem mass spectrometric fragmentation annotation (CD-RI-LC-MS/MS) for identification and quantification of oxylipins. To this end, N,N-diethyl-1,3-diaminopropane (DEPA) was used for fast labeling of oxylipin (within 0.5 min at room temperature) to improve separation resolution and detection sensitivity. The RI algorithm was established to calibrate the retention time variances and assist the identification of oxylipins during liquid chromatography-tandem mass spectrometry (LC-MS) analysis. MS/MS analysis of in total 58 DEPA derivatives of authentic oxylipin standards was subsequently employed to obtain the tandem mass spectrometric feature fragmentation rules for further structure elucidation of the unknown regio-isomers. Finally, a method based upon CD-RI-LC-MS/MS was established for profiling oxylipins from Standard Reference Material (SRM) 1950 human plasma and nonalcoholic fatty liver disease (NAFLD) mouse liver tissue samples. A total of 87 and 96 potential oxylipins including 12 and 14 unreported oxylipins were detected and identified from human plasma and mouse liver tissues, respectively. The results showed that compared to the control group, in the liver samples of the NAFLD mouse, the content levels of prostaglandin (PG) E2, PGF2a, 8-hydroxy-eicosatrienoic acid (8-HETrE), and the newly discovered 2-hydroxy-octadecatrienoic acid (2-HOTrE) were remarkably increased, while the oxidation product of n-3 PUFA (p < 0.05) and all hydroperoxy oxylipins significantly decreased. On balance, this method contributes to future studies on oxylipin screening and application in other biological samples for facilitating the understanding of oxylipin roles in metabolic regulation of numerous diseases.

Mass Spectrometry Based on Chemical Derivatization Has Brought Novel Discoveries to Lipidomics: A Comprehensive Review

Lipids, as one of the most important organic compounds in organisms, are important components of cells and participate in energy storage and signal transduction of living organisms. As a rapidly rising field, lipidomics research involves the identification and quantification of multiple classes of lipid molecules, as well as the structure, function, dynamics, and interactions of lipids in living organisms. Due to its inherent high selectivity and high sensitivity, mass spectrometry (MS) is the "gold standard" analysis technique for small molecules in biological samples. The combination chemical derivatization with MS detection is a unique strategy that could improve MS ionization efficiency, facilitate structure identification and quantitative analysis. Herein, this review discusses derivatization-based MS strategies for lipidomic analysis over the past decade and focuses on all the reported lipid categories, including fatty acids and modified fatty acids, glycerolipids, glycerophospholipids, sterols and saccharolipids. The functional groups of lipids mainly involved in chemical derivatization include the C=C group, carboxyl group, hydroxyl group, amino group, carbonyl group. Furthermore, representative applications of these derivatization-based lipid profiling methods were summarized. Finally, challenges and countermeasures of lipid derivatization are mentioned and highlighted to guide future studies of derivatization-based MS strategy in lipidomics.

Novel Peak Shift Correction Method Based on the Retention Index for Peak Alignment in Untargeted Metabolomics

Peak alignment is a crucial step in liquid chromatography-mass spectrometry (LC-MS)-based large-scale untargeted metabolomics workflows, as it enables the integration of metabolite peaks across multiple samples, which is essential for accurate data interpretation. Slight differences or fluctuations in chromatographic separation conditions, however, can cause the chromatographic retention time (RT) shift between consecutive analyses, ultimately affecting the accuracy of peak alignment between samples. Here, we introduce a novel RT shift correction method based on the retention index (RI) and apply it to peak alignment. We synthesized a series of N-acyl glycine (C2-C23) homologues via the amidation reaction between glycine with normal saturated fatty acids (C2-C23) as calibrants able to respond proficiently in both mass spectrometric positive- and negative-ion modes. Using these calibrants, we established an N-acyl glycine RI system. This RI system is capable of covering a broad chromatographic space and addressing chromatographic RT shift caused by variations in flow rate, gradient elution, instrument systems, and LC separation columns. Moreover, based on the RI system, we developed a peak shift correction model to enhance peak alignment accuracy. Applying the model resulted in a significant improvement in the accuracy of peak alignment from 15.5 to 80.9% across long-term data spanning a period of 157 days. To facilitate practical application, we developed a Python-based program, which is freely available at https://github.com/WHU-Fenglab/RI-based-CPSC.

Chemical derivatization strategy for mass spectrometry-based lipidomics

Lipids, serving as the structural components of cellular membranes, energy storage, and signaling molecules, play the essential and multiple roles in biological functions of mammals. Mass spectrometry (MS) is widely accepted as the first choice for lipid analysis, offering good performance in sensitivity, accuracy, and structural characterization. However, the untargeted qualitative profiling and absolute quantitation of lipids are still challenged by great structural diversity and high structural similarity. In recent decade, chemical derivatization mainly targeting carboxyl group and carbon-carbon double bond of lipids have been developed for lipidomic analysis with diverse advantages: (i) offering more characteristic structural information; (ii) improving the analytical performance, including chromatographic separation and MS sensitivity; (iii) providing one-to-one chemical isotope labeling internal standards based on the isotope derivatization regent in quantitative analysis. Moreover, the chemical derivatization strategy has shown great potential in combination with ion mobility mass spectrometry and ambient mass spectrometry. Herein, we summarized the current states and advances in chemical derivatization-assisted MS techniques for lipidomic analysis, and their strengths and challenges are also given. In summary, the chemical derivatization-based lipidomic approach has become a promising and reliable technique for the analysis of lipidome in complex biological samples.

Quaterization Derivatization with Bis(Pyridine) Iodine Tetrafluoroboride: High-Sensitivity Mass Spectrometric Analysis of Unsaturated Fatty Acids in Human Thyroid Tissues

Accurate quantification of disease-related unsaturated fatty acids (UFAs) in biomedical samples plays an important role in clinical diagnosis. Here, we reported a quaterization derivatization-stable isotope labeling strategy for accurate quantitative analysis of UFAs by high-performance liquid chromatography-mass spectrometry. [d₀]/[d₁₀]-Bis(pyridine) iodine tetrafluoroboride ([d₀]/[d₁₀]-IPy₂BF₄) was employed as the carbon-carbon double bond derivatization reagent with high efficiency and high specificity, to introduce a charge tag on UFAs and avoid the interference of saturated fatty acids. After labeling, the detection sensitivity was significantly enhanced by up to three orders of magnitude compared to intact UFAs. The standard curves showed good linearity (R² > 0.999) over a wide concentration range. This strategy was successfully applied to determine the content of 12 UFAs in human thyroid carcinoma and para-carcinoma tissues. A significant difference was found in the content of several UFAs between these two kinds of tissues (p < 0.05). These results indicated that the proposed strategy may be valuable for the discovery of abnormal UFA content in early clinical diagnosis.

Chloramine-T-Enabled Mass Spectrometric Analysis of C═C Isomers of Unsaturated Fatty Acids and Phosphatidylcholines in Human Thyroids

Specific locations of carbon-carbon double bonds (C═C) in lipids often play an essential role in biological processes, and there has been a booming development in C═C composition analysis by mass spectrometry. However, a universal derivatization and fragmentation pattern for the annotation of C═C positions in lipids is still challenging and attractive. To expand this field in lipidomics, a flexible and convenient N-tosylaziridination method was developed, with high derivatization efficiency, sensitivity, and specificity. The derivatization was very fast (15 s), and C═C numbers as well as locations could be pinpointed specifically in tandem mass spectra. By qualitative and quantitative studies of paratumor and tumor thyroid tissues of human beings, the total content of unsaturated fatty acids was suggested to be increased in tumor tissues, and good correlations in and between lysophosphatidylcholines and phosphatidylcholines were revealed by Spearman analysis. Further studies of C═C isomers showed that n-6/n-3 ratios were closely associated with human thyroid tumorigenesis, and high ratios of n-6/n-3 isomers seemed to suffer a high risk of carcinogenesis. Other isomers were not very representative; however, C═C in n-9/n-7 could also be significant for oncology research. Generally, it is supposed that both total amounts and C═C isomer ratios were related to cancer, and N-tosylaziridine derivatization could provide an alternative strategy for the C═C isomer study of disease models.

Applying an instrument-agnostizing methodology for the standardization of pesticide quantitation using different liquid chromatography-mass spectrometry platforms: A case study

Liquid chromatography coupled to mass spectrometry (LC-MS) is a powerful technique commonly used for pesticide residue analysis in agri-food matrices. Despite the fact it has several advantages, one of the main problems is the transferability of the data from one analytical equipment to another for identification and quantitation purposes. In this study, instrument-agnostizing methodology was used to set standard retention scores (SRSs), which was utilized as a parameter for the identification of 74 targeted compounds when different instruments are used. The SRS variation was lower than 5% for most of the compounds included in this study, which is much lower than those obtained when retention times were compared, correcting the elution shift between LC instruments. Additionally, this methodology was also tested for quantitation purposes, and normalized areas were used as analytical responses, allowing for the determination of the concentrations of the targeted compounds in samples injected in one equipment using the analytical responses of standards from another one. The applicability of this approach was tested at two concentrations, 0.06 and 0.15 mg/kg, and less than 10 out of 74 compounds were quantified with an error higher than 40% at 0.06 mg/kg and 0.15 mg/kg, showing that this methodology could be useful to minimize differences between LC-MS systems.

Simultaneous Analysis of the Metabolome and Lipidome Using Polarity Partition Two-Dimensional Liquid Chromatography-Mass Spectrometry

Comprehensive metabolic profiling is a considerable challenge for systems biology since the metabolites in biological samples have significant polarity differences. A heart-cutting two-dimensional liquid chromatography-mass spectrometry (2D-LC-MS) method-based polarity partition was established to analyze both the metabolome and lipidome in a single run. Based on the polarity partition strategy, metabolites with high polarity were retained and separated by one-dimensional hydrophilic chromatography, while low- and medium-polarity lipids were collected into a sample loop and injected into two-dimensional reversed-phase chromatography for separation. A simple online dilution strategy realized the online coupling of the 2D-LC-MS, which effectively solved band broadening and peak distortion caused by solvent incompatibility. Moreover, a dual gradient elution procedure was introduced to further broaden the coverage of low-polarity lipids. The metabolites' log P values, which this 2D-LC-MS method could analyze, ranged from -8.79 to 26.86. The feasibility of the 2D-LC-MS system was demonstrated by simultaneous analysis of the metabolome and lipidome in rat plasma related to depression. A total of 319 metabolites were determined within 40 min, including organic acids, nucleosides, carbohydrate derivatives, amino acids, lipids, and other organic compounds. Finally, 44 depression-related differential metabolites were screened. Compared with conventional LC-MS-based methods, the 2D-LC method covered over 99% of features obtained by two conventional methods. In addition, the selectivity and resolution of the hydrophilic metabolites were improved, and the matrix effects of the hydrophobic metabolites were reduced in the developed method. The results indicated that the established 2D-LC system is a powerful tool for comprehensive metabolomics studies.

Metabolomics and complementary techniques to investigate the plant phytochemical cosmos

Covering: up to 2021Plants and their associated microbial communities are known to produce millions of metabolites, a majority of which are still not characterized and are speculated to possess novel bioactive properties. In addition to their role in plant physiology, these metabolites are also relevant as existing and next-generation medicine candidates. Elucidation of the plant metabolite diversity is thus valuable for the successful exploitation of natural resources for humankind. Herein, we present a comprehensive review on recent metabolomics approaches to illuminate molecular networks in plants, including chemical isolation and enzymatic production as well as the modern metabolomics approaches such as stable isotope labeling, ultrahigh-resolution mass spectrometry, metabolome imaging (spatial metabolomics), single-cell analysis, cheminformatics, and computational mass spectrometry. Mass spectrometry-based strategies to characterize plant metabolomes through metabolite identification and annotation are described in detail. We also highlight the use of phytochemical genomics to mine genes associated with specialized metabolites' biosynthesis. Understanding the metabolic diversity through biotechnological advances is fundamental to elucidate the functions of the plant-derived specialized metabolome.

Absolute Quantification of Acylcarnitines Using Integrated Tmt-PP Derivatization-Based LC-MS/MS and Quantitative Analysis of Multi-Components by a Single Marker Strategy

Acylcarnitines (ACs) play important roles in the fatty acid β-oxidation and are considered as diagnostic markers for many diseases. Accurate determination of ACs remains challenging due to their low abundance, high structure diversity, and limited availability of standard compounds. In this study, microwave-assisted Tmt-PP (p-[3,5-(dimethylamino)-2,4,6-triazine] benzene-1-sulfonyl piperazine) derivatization was utilized to facilitate the liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) determination of ACs. The result indicated that Tmt-PP labeling enables the prediction of the retention time and MS response of ACs and enhances their MS response up to 4 times. The introduction of the microwave during the derivatization procedure greatly improved the reaction efficiency, demonstrated by the shortened reaction time from 90 to 1 min. Furthermore, we applied a strategy named quantitative analysis of multi-components by a single marker (QAMS) for the assay of 26 ACs with only 5 AC standards, solving the standard availability issue to a large extent. The established workflow was applied to discover dysregulated ACs in xenograft colon cancer mice, and the quantification results were highly comparable with traditional methods where there were the corresponding standards for each AC. Our study demonstrated that chemical derivatization-based LC-MS/MS integrated with the QAMS strategy is robust for the identification and quantification of ACs and has great potential in targeted metabolomics study.

Current Challenges and Recent Developments in Mass Spectrometry-Based Metabolomics

High-resolution mass spectrometry (MS) has advanced the study of metabolism in living systems by allowing many metabolites to be measured in a single experiment. Although improvements in mass detector sensitivity have facilitated the detection of greater numbers of analytes, compound identification strategies, feature reduction software, and data sharing have not kept up with the influx of MS data. Here, we discuss the ongoing challenges with MS-based metabolomics, including de novo metabolite identification from mass spectra, differentiation of metabolites from environmental contamination, chromatographic separation of isomers, and incomplete MS databases. Because of their popularity and sensitive detection of small molecules, this review focuses on the challenges of liquid chromatography-mass spectrometry-based methods. We then highlight important instrumentational, experimental, and computational tools that have been created to address these challenges and how they have enabled the advancement of metabolomics research.

A mathematical method for calibrating the signal drift in liquid chromatography - mass spectrometry analysis

Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has become the most versatile analytical tool for profiling small-molecule compounds and increasingly been applied in many fields. Nevertheless, LC-MS based quantification still face some challenges, such as signal drift in LC-MS, which may affect the validity of the obtained data and lead to misinterpretation of biological results. Here, we established a calibration method known as "RIM" to compensate the signal drift of LC-MS. To this end, a mixture of d₄-2-dimethylaminoethylamine (d₄-DMED)-coded normal fatty acids (C5-C23) was used as calibrants to construct RIM calibration. With the addition of calibrants, not only the MS signal drift, but also the mass accuracy and LC retention time can be calibrated, thereby improving the reliability of quantitative data. The effectiveness of RIM was carefully validated using a human serum extract spiked with 34 standards and then RIM was applied for rat brain untargeted metabolome research. In addition, to expand the functionality and flexibility of RIM for data handling, we generated a MATLAB-based RIM program, which implements the above concepts and allows automatic data process. Taken together, the proposed RIM method has potential application in large-scale quantitative study of complex samples.

Towards a More Reliable Identification of Isomeric Metabolites Using Pattern Guided Retention Validation

Reliable analyte identification is critical in metabolomics experiments to ensure proper interpretation of data. Due to chemical similarity of metabolites (as isobars and isomers) identification by mass spectrometry or chromatography alone can be difficult. Here we show that isomeric compounds are quite common in the metabolic space as given in common metabolite databases. Further, we show that retention information can shift dramatically between different experiments decreasing the value of external or even in-house compound databases. As a consequence the retention information in compound databases should be updated regularly, to allow a reliable identification. To do so we present a feasible and budget conscious method to guarantee updates of retention information on a regular basis using well designed compound mixtures. For this we combine compounds in "Ident-Mixes", showing a way to distinctly identify chemically similar compounds through combinatorics and principle of exclusion. We illustrate the feasibility of this approach by comparing Gas chromatography (GC)-columns with identical properties from three different vendors and by creating a compound database from measuring these mixtures by Liquid chromatography-mass spectrometry (LC-MS). The results show the high influence of used materials on retention behavior and the ability of our approach to generate high quality identifications in a short time.

In-Depth Annotation Strategy of Saturated Hydroxy Fatty Acids Based on Their Chromatographic Retention Behaviors and MS Fragmentation Patterns

Hydroxy fatty acids are a class of bioactive compounds in a variety of organisms. The identification of hydroxy fatty acids in biological samples has still been a challenge because of their low abundance, high structural similarity, and limited availability of authentic hydroxy fatty acid standards. Here, we present a strategy for the annotation of saturated monohydroxyl fatty acids (OH-FAs) based on the integration of chromatographic retention rules and MS² fragmentation patterns. Thirty-nine authentic OH-FA standards were used to investigate their retention behavior on a reversed-phase stationary phase (C18) of liquid chromatography, and we found that their retention simultaneously follows two kinds of "carbon number rules". Using the "carbon number rules", the retention index (RI) of all OH-FAs that contain carbon numbers from 8 to 18 (C_8-18) can be predicted. Additionally, by studying the MS² fragmentation of OH-FAs under collision-induced dissociation, we found that the intensity ratio (IR) of the characteristic fragment ions ([M + H]⁺-63 and [M + H]⁺-45) is closely related to the position of the hydroxyl group on the OH-FA structure, which is helpful to further identify and confirm the OH-FA isomers. As a result, 97 of 107 potential OH-FAs detected in honey, human serum, and rice seedling by chemical isotope labeling-assisted liquid chromatography-mass spectrometry were annotated upon the RI matching and IR confirming. Furthermore, in order to simplify the annotation process of OH-FAs, we constructed an OH-FA library to facilitate the annotation of OH-FAs. Overall, this study provides a new and promising tool for the in-depth annotation of OH-FA isomers.

Novel computational approaches to retention modeling in dual hydrophilic interactions/reversed phase chromatography

The mixed-mode chromatographic behavior was estimated for imidazoline and serotonin receptor ligands, and their related compounds on dual hydrophilic/reversed phase stationary phase. The Box-Cox transformation was used to obtain the most suitable mathematical equations which describe the mixed-mode retention. Optimal equations were found for the optimization parameter (λ): λ = -1, λ = -0.5, λ = 0, λ = 0.5, and λ = 1. The proposed equations show satisfactory characteristics compared to standard multimodal and quadratic approaches. For a wide range of volume fractions of the mobile phase modifier, crossing between hydrophilic and reversed phase interactions (the turning point) was defined in terms of the minimal retention and the minimum value of the volume fraction of the aqueous eluent in the mobile phase. The cubic spline interpolation was used as a reference method for estimation of the turning point. It was found out that the newly proposed equations can be used as alternative mathematical forms for the description of the dual retention mechanism and for the evaluation of the turning point. Three new experimental descriptors of the mixed-mode retention were proposed. Two descriptors quantitatively characterize hydrophilic (log k_H) and reversed phase (log k_R) interactions, while the third one (log k_A) refers to the average retention for the whole HILIC/RP range. It was established that the main factors which control dual nature of the mixed-mode retention are lipophilicity, dipol-dipol, van der Waals and hydrogen bonding interactions. It was concluded that the newly proposed estimations of the retention data reliably characterize the mixed-mode chromatographic behavior.

Creating a Reliable Mass Spectral-Retention Time Library for All Ion Fragmentation-Based Metabolomics

Accurate metabolite identification remains one of the primary challenges in a metabolomics study. A reliable chemical spectral library increases the confidence in annotation, and the availability of raw and annotated data in public databases facilitates the transfer of Liquid chromatography coupled to mass spectrometry (LC-MS) methods across laboratories. Here, we illustrate how the combination of MS2 spectra, accurate mass, and retention time can improve the confidence of annotation and provide techniques to create a reliable library for all ion fragmentation (AIF) data with a focus on the characterization of the retention time. The resulting spectral library incorporates information on adducts and in-source fragmentation in AIF data, while noise peaks are effectively minimized through multiple deconvolution processes. We also report the development of the Mass Spectral LIbrary MAnager (MS-LIMA) tool to accelerate library sharing and transfer across laboratories. This library construction strategy improves the confidence in annotation for AIF data in LC-MS-based metabolomics and will facilitate the sharing of retention time and mass spectral data in the metabolomics community.