Data acquisition and data mining techniques for metabolite identification using LC coupled to high-resolution MS

Application of Electro-Activated Dissociation Fragmentation Technique to Identifying Glucuronidation and Oxidative Metabolism Sites of Vepdegestrant by Liquid Chromatography-High Resolution Mass Spectrometry

Drug metabolite identification is an integrated part of drug metabolism and pharmacokinetics studies in drug discovery and development. Definitive identification of metabolic modification sides of test compounds such as screening metabolic soft spots and supporting metabolite synthesis are often required. Currently, liquid chromatography-high resolution mass spectrometry is the dominant analytical platform for metabolite identification. However, the interpretation of product ion spectra generated by commonly used collision-induced disassociation (CID) and higher-energy collisional dissociation (HCD) often fails to identify locations of metabolic modifications, especially glucuronidation. Recently, a ZenoTOF 7600 mass spectrometer equipped with electron-activated dissociation (EAD-HRMS) was introduced. The primary objective of this study was to apply EAD-HRMS to identify metabolism sites of vepdegestrant (ARV-471), a model compound that consists of multiple functional groups. ARV-471 was incubated in dog liver microsomes and 12 phase I metabolites and glucuronides were detected. EAD generated unique product ions via orthogonal fragmentation, which allowed for accurately determining the metabolism sites of ARV-471, including phenol glucuronidation, piperazine N-dealkylation, glutarimide hydrolysis, piperidine oxidation, and piperidine lactam formation. In contrast, CID and HCD spectral interpretation failed to identify modification sites of three O-glucuronides and three phase I metabolites. The results demonstrated that EAD has significant advantages over CID and HCD in definitive structural elucidation of glucuronides and phase I metabolites although the utility of EAD-HRMS in identifying various types of drug metabolites remains to be further evaluated. SIGNIFICANCE STATEMENT: Definitive identification of metabolic modification sites by liquid chromatography-high resolution mass spectrometry is highly needed in drug metabolism research, such as screening metabolic soft spots and supporting metabolite synthesis. However, commonly used collision-induced dissociation (CID) and higher-energy collisional dissociation (HCD) fragmentation techniques often fail to provide critical information for definitive structural elucidation. In this study, the electron-activated dissociation (EAD) was applied to identifying glucuronidation and oxidative metabolism sites of vepdegestrant, which generated significantly better results than CID and HCD.

A multi-module structure labelled molecular network orients the chemical profiles of traditional Chinese medicine prescriptions: Xiaoyao San, as an example

Ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) technology has emerged as a crucial tool for identifying components in traditional Chinese medicine (TCM). However, the characterization of the chemical profiles of TCM prescriptions (TCMPs) which often consist of multiple herbal medicines and contain diverse structural types, presents several challenges, such as component overlapping and time-consuming. In this study, a novel strategy known as the multi-module structure labelled molecular network (MSLMN), which integrates molecular networking, database annotation, and cluster analysis techniques, has been successfully proposed, which facilitates the identification of chemical constituents by leveraging a high-structural similarity ion list derived from the MSLMN. It has been effectively applied to analyze the chemical profile of Xiaoyao San (XYS), a classical TCMP. Through the MSLMN method, a total of 302 chemical constituents were identified, covering nine structural types in XYS. Furthermore, a validated and quantitative analytical method using UHPLC-QqQ-MS/MS technology was developed for 31 identified chemicals, encompassing all eight herbal medicines present in XYS, and the developed analytical approach was applied to investigate the content distribution across 40 different batches of commercially available XYS. In total, the proposed strategy has practical significance for improving the insight into the chemical profile of XYS and serves as a valuable approach for handling complex system data based on UHPLC-MS, particularly for TCMPs.

Stepwise Targeted Matching Strategy for Comprehensive Profiling of Xanthohumol Metabolites In Vivo and In Vitro Using UHPLC-Q-Exactive Orbitrap Mass Spectrometer

Xanthohumol (XN), a natural prenylated flavonoid extracted and isolated from the hop plant (Humulus lupulus), possesses diverse pharmacological activities. Although the metabolites of XN have been investigated in the previous study, a comprehensive metabolic profile has been insufficient in vivo or in vitro until now. The current study was aimed at systematically elucidating the metabolic pathways of XN after oral administration to rats. Herein, a UHPLC-Q-Exactive Orbitrap MS was adopted for the potential metabolites detection. A stepwise targeted matching strategy for the overall identification of XN metabolites was proposed. A metabolic net (53 metabolites included) on XN in vivo and in vitro, as well as the metabolic profile investigation, were designed, preferably characterizing XN metabolites in rat plasma, urine, liver, liver microsomes, and feces. On the basis of a stepwise targeted matching strategy, the net showed that major in vivo metabolic pathways of XN in rats include glucuronidation, sulfation, methylation, demethylation, hydrogenation, dehydrogenation, hydroxylation, and so on. The proposed metabolic pathways in this research will provide essential data for further pharmaceutical studies of prenylated flavonoids and lay the foundation for further toxicity and safety studies.

The Analytical Strategy of “Ion Induction and Deduction Based on Net-Hubs” for the Comprehensive Characterization of Naringenin Metabolites In Vivo and In Vitro Using a UHPLC-Q-Exactive Orbitrap Mass Spectrometer

Naringenin (5,7,4′-trihydroxyflavanone), belonging to the flavanone subclass, is associated with beneficial effects such as anti-oxidation, anticancer, anti-inflammatory, and anti-diabetic effects. Drug metabolism plays an essential role in drug discovery and clinical safety. However, due to the interference of numerous endogenous substances in metabolic samples, the identification and efficient characterization of drug metabolites are difficult. Here, ultra-high-performance liquid chromatography (UHPLC) coupled with high-resolution mass spectrometry was used to obtain mass spectral information of plasma (processed by three methods), urine, feces, liver tissue, and liver microsome samples. Moreover, a novel analytical strategy named “ion induction and deduction” was proposed to systematically screen and identify naringenin metabolites in vivo and in vitro. The analysis strategy was accomplished by the establishment of multiple “net-hubs” and the induction and deduction of fragmentation behavior. Finally, 78 naringenin metabolites were detected and identified from samples of rat plasma, urine, feces, liver tissue, and liver microsomes, of which 67 were detected in vivo and 13 were detected in vitro. Naringenin primarily underwent glucuronidation, sulfation, oxidation, methylation, ring fission, and conversion into phenolic acid and their composite reactions. The current study provides significant help in extracting target information from complex samples and sets the foundation for other pharmacology and toxicology research.

A Discovery Biotransformation Strategy: Combining In Silico Tools with High-Resolution Mass Spectrometry and Software-Assisted Data Analysis for High-Throughput Metabolism

Understanding compound metabolism in early drug discovery aids medicinal chemistry in designing molecules with improved safety and ADME properties. While advancements in metabolite prediction brings increasedconfidence, structural decisions require experimental data. In vitro metabolism studies using liquid chromatography and high-resolution mass spectrometry (LC-MS) are generally resource intensive and performed on very few compounds, limiting the chemical space that can be examined.Here, we describe a novel metabolism strategy increasing compound throughput using residual in vitro clearance samples conducted at drug concentrations of 0.5 µM. Analysis by robust UHPLC separation and accurate-mass MS detection ensures major metabolites are identified from a single injection. In silico prediction (parent cLogD) tailors chromatographic conditions, with data-dependent MS/MS targeting predicted metabolites. Software-assisted data mining, structure elucidation and automatic reporting are used.Confidence in the globally-aligned workflow is demonstrated with sixteen marketed drugs. The approach is now implemented routinely across our laboratories. To date, the success rate for identification of at least one major metabolite is 85%. The utility of these data has been demonstrated across multiple projects, allowing earlier medicinal chemistry decisions to increase efficiency and impact of the design-make-test cycle; thus improving the translatability of early in vitro metabolism data.

A Novel Approach of SWATH-Based Metabolomics Analysis Using the Human Metabolome Database Spectral Library

Metabolomics is a potential approach to paving new avenues for clinical diagnosis, molecular medicine, and therapeutic drug monitoring and development. The conventional metabolomics analysis pipeline depends on the data-independent acquisition (DIA) technique. Although powerful, it still suffers from stochastic, non-reproducible ion selection across samples. Despite the presence of different metabolomics workbenches, metabolite identification remains a tedious and time-consuming task. Consequently, sequential windowed acquisition of all theoretical MS (SWATH) acquisition has attracted much attention to overcome this limitation. This article aims to develop a novel SWATH platform for data analysis with a generation of an accurate mass spectral library for metabolite identification using SWATH acquisition. The workflow was validated using inclusion/exclusion compound lists. The false-positive identification was 3.4% from the non-endogenous drugs with 96.6% specificity. The workflow has proven to overcome background noise despite the complexity of the SWATH sample. From the Human Metabolome Database (HMDB), 1282 compounds were tested in various biological samples to demonstrate the feasibility of the workflow. The current study identified 377 compounds in positive and 303 in negative modes with 392 unique non-redundant metabolites. Finally, a free software tool, SASA, was developed to analyze SWATH-acquired samples using the proposed pipeline.

Subcutaneous Catabolism of Peptide Therapeutics: Bioanalytical Approaches and ADME Considerations

Many peptide drugs such as insulin and glucagon-like peptide (GLP-1) analogues are successfully administered subcutaneously (SC). Following SC injection, peptides may undergo catabolism in the SC compartment before entering systemic circulation, which could compromise their bioavailability and in turn affect their efficacy.This review will discuss how both technology and strategy have evolved over the past years to further elucidate peptide SC catabolism.Modern bioanalytical technologies (particularly liquid chromatography-high-resolution mass spectrometry) and bioinformatics platforms for data mining has prompted the development of in silico, in vitro and in vivo tools for characterizing peptide SC catabolism to rapidly address proteolytic liabilities and, ultimately, guide the design of peptides with improved SC bioavailability.More predictive models able to recapitulate the interplay between SC catabolism and other factors driving SC absorption are highly desirable to improve in vitro/in vivo correlations.We envision the routine incorporation of in vitro and in vivo SC catabolism studies in ADME screening funnels to develop more effective peptide drugs for SC delivery.

Predictive Value of Preoperative Profiling of Serum Metabolites for Emergence Agitation After General Anesthesia in Adult Patients

Background: Emergence agitation (EA) in adult patients under general anesthesia leads to increased postoperative complications and heavy medical burden. Unfortunately, its pathogenesis has not been clarified until now. The purpose of the present study was to explore the relationship between preoperative serum metabolites and EA. Methods: We used an untargeted metabolic analysis method to investigate the different metabolomes in the serum of EA patients and non-EA patients undergoing elective surgical procedures after the induction of general anesthesia. A Richmond Agitation-Sedation Scale score ≥ +2 was diagnosed as EA during postoperative emergence. Non-EA patients were matched with EA patients according to general characteristics. Preoperative serum samples of the two groups were collected to investigate the association between serum metabolites and EA development. Results: The serum samples of 16 EA patients with 34 matched non-EA patients were obtained for metabolic analysis. After screening and alignment with databases, 31 altered metabolites were detected between the two groups. These metabolites were mainly involved in the metabolism of lipids, purines, and amino acids. Analyses of receiver-operating characteristic curves showed that the preoperative alterations of choline, cytidine, glycerophosphocholine, L-phenylalanine, oleamide, and inosine may be associated with adult EA. Conclusion: Multiple metabolic abnormalities (including those for lipids, purines, and amino acids) and other pathological processes (e.g., neurotransmitter imbalance and oxidative stress) may contribute to EA. Several altered metabolites in serum before surgery may have predictive value for EA diagnosis. This study might afford new metabolic clues for the understanding of EA pathogenesis.

Online pressurized liquid extraction enables directly chemical analysis of herbal medicines: A mini review

Extraction is responsible for transferring components from solid materials into solvent. Tedious extraction procedures are usually involved in liquid chromatography-based chemical analysis of herbal medicines (HMs), resulting in extensive consumptions of organic solvents, time, energy, and materials, as well as the significant chemical degradation risks for those labile compounds. Fortunately, an emerging online pressurized liquid extraction (OLE, also known as online liquid extraction) technique has been developed for the achievement of directly chemical analysis for solid matrices in recent years, and in a short period, this versatile technique has been widely applied for the chemical analysis of HMs. In the present mini-review, we aim to briefly summarize the principles, the instrumentation, along with the application progress of this robust and flexible extraction technique in the latest six years, and the emerging challenges and future prospects are discussed as well. Special attention is paid onto the hyphenation of the versatile OLE module with LC-MS instrument. The described information is expected to introduce a promising OLE approach and to provide the guidance for the achievement of directly chemical analysis of, but not limited to, HMs.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

Recent advances in identifying and utilizing metabolites of selected doping agents in human sports drug testing

Probing for evidence of the administration of prohibited therapeutics, drugs and/or drug candidates as well as the use of methods of doping in doping control samples is a central assignment of anti-doping laboratories. In order to accomplish the desired analytical sensitivity, retrospectivity, and comprehensiveness, a considerable portion of anti-doping research has been invested into studying metabolic biotransformation and elimination profiles of doping agents. As these doping agents include lower molecular mass drugs such as e.g. stimulants and anabolic androgenic steroids, some of which further necessitate the differentiation of their natural/endogenous or xenobiotic origin, but also higher molecular mass substances such as e.g. insulins, growth hormone, or siRNA/anti-sense oligonucleotides, a variety of different strategies towards the identification of employable and informative metabolites have been developed. In this review, approaches supporting the identification, characterization, and implementation of metabolites exemplified by means of selected doping agents into routine doping controls are presented, and challenges as well as solutions reported and published between 2010 and 2020 are discussed.

Insight into chemical basis of traditional Chinese medicine based on the state-of-the-art techniques of liquid chromatography-mass spectrometry

Traditional Chinese medicine (TCM) has been an indispensable source of drugs for curing various human diseases. However, the inherent chemical diversity and complexity of TCM restricted the safety and efficacy of its usage. Over the past few decades, the combination of liquid chromatography with mass spectrometry has contributed greatly to the TCM qualitative analysis. And novel approaches have been continuously introduced to improve the analytical performance, including both the data acquisition methods to generate a large and informative dataset, and the data post-processing tools to extract the structure-related MS information. Furthermore, the fast-developing computer techniques and big data analytics have markedly enriched the data processing tools, bringing benefits of high efficiency and accuracy. To provide an up-to-date review of the latest techniques on the TCM qualitative analysis, multiple data-independent acquisition methods and data-dependent acquisition methods (precursor ion list, dynamic exclusion, mass tag, precursor ion scan, neutral loss scan, and multiple reaction monitoring) and post-processing techniques (mass defect filtering, diagnostic ion filtering, neutral loss filtering, mass spectral trees similarity filter, molecular networking, statistical analysis, database matching, etc.) were summarized and categorized. Applications of each technique and integrated analytical strategies were highlighted, discussion and future perspectives were proposed as well.

"Force iteration molecular designing" strategy for the systematic characterization and discovery of new protostane triterpenoids from Alisma Rhizoma by UHPLC/LTQ-Orbitrap-MS

Comprehensive analysis and identification of chemical components are of great significance for evaluating the efficacy and safety of herbal medicines, as well as for drug exploitation and development. Here we developed a "force iteration molecular designing" strategy, by combing a database-based in-house software for a precursor ion list (PIL) and PIL-triggered collision-induced dissociation-MS² and high-energy C-trap dissociation-MS² (PIL-CID/MS²-HCD/MS²) on an LTQ-Orbitrap mass spectrometer, aiming for the systematic characterization and discovery of new protostane triterpenoids (PTs) from Alisma Rhizoma (AR). AR was a well-known herbal remedy widely used for diarrhea, but its systematic characterization and comparison between two botanical origins have not been reported. Firstly, in-house software was developed based on force iteration, to generate a PIL that contains 483 accurate precursor ions. Secondly, to facilitate the acquisition of rich fragments and diagnostic ions sufficient for the structural elucidation of different types of PTs, a hybrid data acquisition method, namely PIL-CID/MS²-HCD/MS², was generated. Thirdly, a total of 473 PTs were rapidly characterized from two botanical origins of AR according to an established four-step interpretation method, and the common constituents were 277 with ratio 70% (277/395) and 78% (277/355) in the rhizome of Alisma plantago-aquatica and A. orientale, respectively. Finally, two new PTs were isolated and unambiguously identified by NMR verifying the feasibility of this combined data acquisition strategy. This integrated strategy could improve the efficiency in the detection of new compounds in a single run and is practical to comprehensively characterize the complex components in herbal medicines.

Comparison of different protein precipitation and solid-phase extraction protocols for the study of the catabolism of peptide drugs by LC-HRMS

LC-HRMS-based identification of the products of peptide catabolism is the key to drive the design of more stable compounds. Because the catabolite of a given peptide can be very different from the parent compound and from other catabolites in terms of physicochemical properties, it can be challenging to develop an analytical method that allows recovery and detection of the parent and all parent-related catabolites. The aim of this study was to investigate how the recovery and the matrix effect of peptidic drugs and their catabolites are affected by different protein precipitation (PP) and solid-phase extraction (SPE) protocols. To this purpose, four model peptides representative of different classes (somatostatin, GLP-2, human insulin and liraglutide) were digested with trypsin and chymotrypsin to simulate proteolytic catabolism. The resulting mixtures of the parent peptides and their proteolytic products covering a wide range of relative hydrophobicity (H_R ) and isoelectric points (pI) were spiked in human plasma and underwent different PP and SPE protocols. Recovery and matrix effect were measured for each peptide and its catabolites. PP with three volumes of ACN or EtOH yielded the highest overall recoveries (more than 50% for the four parent peptides and all their catabolites) among all the tested PP and SPE protocols. Mixed-mode anion exchange (MAX) was the only SPE sorbent among the five tested that allowed to extract all the peptides with recoveries more than 20%. Matrix effect was generally lower with SPE. Overall, it was observed that peptides with either high hydrophilicity (e.g., somatostatin catabolites) or hydrophobicity (GLP-2 and lipidated liraglutide catabolites) had a much narrower choice of PP solvent or SPE protocol. Simulation of catabolism using recombinant enzymes together with in silico calculation of the H_R and the pI of potential proteolysis products is recommended to select the optimal extraction conditions for the study of peptide catabolism.

Metabolomics Combined with Multivariate Statistical Analysis for Screening of Chemical Markers between Gentiana scabra and Gentiana rigescens

Gentianae Radix et Rhizome (Longdan in Chinese, GRR) in Chinese Pharmacopoeia is derived from the dried roots and rhizomes of Gentiana scabra and G. rigescens, that have long been used for heat-clearing and damp-drying in the medicinal history of China. However, the characterization of the chemical components of two species and the screening of chemical markers still remain unsolved. In current research, the identification and characterization of chemical components of two species was performed using ultra-high-performance liquid chromatography (UHPLC) coupled with linear ion trap-Orbitrap (LTQ-Orbitrap) mass spectrometry. Subsequently, the chemical markers of two species were screened based on metabolomics and multivariate statistical analysis. In total, 87 chemical constituents were characterized in G. scabra (65 chemical constituents) and G. rigescens (51 chemical constituents), with 29 common chemical constituents being discovered. Thereafter, 11 differential characteristic components which could differentiate the two species were designated with orthogonal partial least squares discriminant analysis (OPLS-DA) and random forest (RF) iterative modeling. Finally, seven characteristic components identified as (+)-syringaresinol, lutonarin, trifloroside, 4-O-β-d-glu-trifloroside, 4″-O-β-d-glucopyranosy1-6′-O-(4-O-β-d-glucaffeoyl)-linearroside, macrophylloside a and scabraside were selected as the chemical markers for the recognition of two Gentiana species. It was implied that the results could distinguish the GRR derived from different botanical sources, and also be beneficial in the rational clinical use of GRR.

Analytical performance of the various acquisition modes in Orbitrap MS and MS/MS

Quadrupole Orbitrap instruments (Q Orbitrap) permit high-resolution mass spectrometry-based full scan acquisitions and have a number of acquisition modes where the quadrupole isolates a particular mass range prior to a possible fragmentation and high-resolution mass spectrometry-based acquisition. Selecting the proper acquisition mode(s) is essential if trace analytes are to be quantified in complex matrix extracts. Depending on the particular requirements, such as sensitivity, selectivity of detection, linear dynamic range, and speed of analysis, different acquisition modes may have to be chosen. This is particularly important in the field of multi-residue analysis (eg, pesticides or veterinary drugs in food samples) where a large number of analytes within a complex matrix have to be detected and reliably quantified. Meeting the specific detection and quantification performance criteria for every targeted compound may be challenging. It is the aim of this paper to describe the strengths and the limitations of the currently available Q Orbitrap acquisition modes. In addition, the incorporation of targeted acquisitions between full scan experiments is discussed. This approach is intended to integrate compounds that require an additional degree of sensitivity or selectivity into multi-residue methods.

Biotransformation of Ilaprazole in Human Liver Microsomes and Human: Role of CYP3A4 in Ilaprazole Clearance and Drug-Drug Interaction

Ilaprazole is a new proton pump inhibitor and is currently marketed in China and South Korea for the treatment of gastric and duodenal ulcer. Ilaprazole has a favorable long half-life and minimal pharmacokinetic variability associated with CYP2C19 polymorphism. Sulfoxide oxidation of ilaprazole is catalyzed mainly by CYP3A4. Thus, it has been widely accepted that CYP3A4 plays a major role in the clearance of ilaprazole in humans. However, absorption, distribution, metabolism, and excretion data of radiolabeled ilaprazole in humans are not available. The primary goal of this study was to determine if sulfoxide oxidation is a major metabolic pathway of ilaprazole in humans. Metabolite profiles of ilaprazole, ilaprazole sulfide, and ilaprazole sulfone in human liver microsomes (HLMs) were characterized and quantitively analyzed by liquid chromatography (LC)/UV/high-resolution mass spectrometry (HRMS). Moreover, metabolites of ilaprazole in human urine and feces were detected and identified by LC-HRMS. The results revealed that sulfoxide reduction to ilaprazole sulfide rather than sulfoxide oxidation was the major biotransformation pathway in HLMs. Sulfoxide reduction also occurred in HLMs without NADPH or in deactivated HLMs. Ilaprazole sulfide and its multiple oxidative metabolites were major drug-related components in human urine and feces, where there were no ilaprazole sulfone and its metabolites. A small amount of the parent drug was found in feces. Thus, we propose that nonenzymatic sulfoxide reduction rather than CYP3A4-medidated sulfoxide oxidation is the major metabolic clearance pathway of ilaprazole in humans. Consequently, it is predicted that ilaprazole has no significant drug-drug interaction via CYP3A4 inhibition or induction by a coadministered drug.

A targeted strategy to identify untargeted metabolites from in vitro to in vivo: Rapid and sensitive metabolites profiling of licorice in rats using ultra-high performance liquid chromatography coupled with triple quadrupole-linear ion trap mass spectrometry

It is challenging to conduct in vivo metabolic study for traditional Chinese medicines (TCMs) because of complex components, unpredictable metabolic pathways and low metabolite concentrations. Herein, we proposed a sensitive strategy to characterize TCM metabolites in vivo at an orally clinical dose using ultra-high performance liquid chromatography-triple quadrupole-linear ion trap mass spectrometry (UHPLC-QTRAP-MS). Firstly, the metabolism of individual compounds in rat liver microsomes was studied to obtain the metabolic pathways and fragmentation patterns. The untargeted metabolites in vitro were detected by multiple ion monitoring-enhanced product ion (EPI) and neutral loss-EPI scans. Subsequently, a sensitive multiple reaction monitoring-EPI method was developed according to the in vitro results and predicted metabolites to profile the in vivo metabolites. Licorice as a model herb was used to evaluate and validate our strategy. A clinical dose of licorice water extract was orally administered to rats, then a total of 45 metabolites in urine, 21 metabolites in feces and 35 metabolites in plasma were detected. Among them, 18 minor metabolites have not been reported previously and 6 minor metabolites were first detected in vivo. Several isomeric metabolites were well separated and differentiated in our strategy. These results suggested that this new strategy could be widely used for the detection and characterization of in vivo metabolites of TCMs.

An enhanced strategy integrating offline two-dimensional separation and step-wise precursor ion list-based raster-mass defect filter: Characterization of indole alkaloids in five botanical origins of Uncariae Ramulus Cum Unicis as an exemplary application

Comprehensive chemical profiling is of great significance for understanding the therapeutic material basis and quality control of herbal medicines, which is challenging due to its inherent chemical diversity and complexity, as well as wide concentration range. In this study, we introduced an enhanced strategy integrating offline two-dimensional (2D) separation and the step-wise precursor ion list-based raster-mass defect filter (step-wise PIL-based raster-MDF) scan by tandem LTQ-Orbitrap mass spectrometer. A comprehensive analysis of indole alkaloids in five botanical origins of Uncariae Ramulus Cum Unicis (Gou-Teng) was used as an exemplary application. A positively charged reversed phase (PR) × conventional RP LC system in different pH conditions was constructed with the orthogonality of 74%. A theoretical step-wise PIL among 310-950 Da with the step-size of 2 Da was developed to selectively trigger fragmentations and extend the coverage of potential indole alkaloids. Simultaneously, by defining parent mass width (PMW) of the step-wise PIL to ±55 mDa, a raster-MDF screening was achieved in the acquisition process. Additionally, subtype classification and structural elucidation were facilitated by a four-step interpretation strategy. As a result, a total of 1227 indole alkaloids were efficiently exposed and characterized from five botanical origins of Gou-Teng, which showed high chemical diversity. A systematic comparison among five species was first performed and only 66 indole alkaloids were common. For method validation, three new alkaloid N-oxides were isolated and unambiguously identified by NMR. The present study provides a novel data-dependent acquisition method with improved target coverage and high selectivity. The integrated strategy is practical to efficiently expose and comprehensively characterize complex components in herbal medicines.

Environmentally Friendly Procedure Based on Supercritical Fluid Chromatography and Tandem Mass Spectrometry Molecular Networking for the Discovery of Potent Antiviral Compounds from Euphorbia semiperfoliata

A supercritical fluid chromatography-based targeted purification procedure using tandem mass spectrometry and molecular networking was developed to analyze, annotate, and isolate secondary metabolites from complex plant extract mixture. This approach was applied for the targeted isolation of new antiviral diterpene esters from Euphorbia semiperfoliata whole plant extract. The analysis of bioactive fractions revealed that unknown diterpene esters, including jatrophane esters and phorbol esters, were present in the samples. The purification procedure using semipreparative supercritical fluid chromatography led to the isolation and identification of two new jatrophane esters (13 and 14) and one known (15) and three new 4-deoxyphorbol esters (16-18). The structure and absolute configuration of compound 16 were confirmed by X-ray crystallography. This compound was found to display antiviral activity against Chikungunya virus (EC₅₀ = 0.45 μM), while compound 15 proved to be a potent and selective inhibitor of HIV-1 replication in a recombinant virus assay (EC₅₀ = 13 nM). This study showed that a supercritical fluid chromatography-based protocol and molecular networking can facilitate and accelerate the discovery of bioactive small molecules by targeting molecules of interest, while minimizing the use of toxic solvents.

Post-acquisition data mining techniques for LC–MS/MS-acquired data in drug metabolite identification

Metabolite identification is a crucial part of the drug discovery process. LC–MS/MS-based metabolite identification has gained widespread use, but the data acquired by the LC–MS/MS instrument is complex, and thus the interpretation of data becomes troublesome. Fortunately, advancements in data mining techniques have simplified the process of data interpretation with improved mass accuracy and provide a potentially selective, sensitive, accurate and comprehensive way for metabolite identification. In this review, we have discussed the targeted (extracted ion chromatogram, mass defect filter, product ion filter, neutral loss filter and isotope pattern filter) and untargeted (control sample comparison, background subtraction and metabolomic approaches) post-acquisition data mining techniques, which facilitate the drug metabolite identification. We have also discussed the importance of integrated data mining strategy.

Identification of Protonated Sulfone and Aromatic Carboxylic Acid Functionalities in Organic Molecules by Using Ion-Molecule Reactions Followed by Collisionally Activated Dissociation in a Linear Quadrupole Ion Trap Mass Spectrometer

Gas-phase reactivity of protonated model compounds with different functional groups toward trimethoxymethylsilane (TMMS) was studied to explore the utility of this reagent in mass spectrometric identification of specific functionalities for potentially rapid characterization of drug metabolites. Only protonated analytes with a carboxylic acid, a sulfone, or a sulfonamide functionality formed diagnostic adducts that had lost a methanol molecule upon reactions with TMMS. Collisionally activated dissociation (CAD) of these methanol-eliminated adduct ions (MS³ experiments) produced characteristic fragment ions of m/z 75, 105, and 123 for sulfones, while an additional methanol elimination was observed for carboxylic acids and sulfonamides. CAD of latter products (MS⁴ experiments) resulted in elimination of diagnostic neutral molecules CO₂ (44 Da) and C₂H₆O₂Si (90 Da) for aromatic carboxylic acids. Both aliphatic carboxylic acids and sulfonamides yield several fragment ions in these MS⁴ experiments that are different from those observed for sulfones or aromatic carboxylic acids. Potential energy surfaces were calculated (at the M06-2X/6-311++G(d,p) level of theory) to explore the mechanisms of various reactions. In summary, sulfones and aromatic carboxylic acids can be differentiated from each other and also from sulfonamides and aliphatic carboxylic acids based on reactions with TMMS and one or two CAD experiments. Aliphatic carboxylic acids and sulfonamides could not be differentiated from each other.

A relative quantitative positive/negative ion switching method for untargeted lipidomics via high resolution LC-MS/MS from any biological source

INTRODUCTION

Advances in high-resolution mass spectrometry have created renewed interest for studying global lipid biochemistry in disease and biological systems.

OBJECTIVES

Here, we present an untargeted 30 min. LC-MS/MS platform that utilizes positive/negative polarity switching to perform unbiased data dependent acquisitions (DDA) via higher energy collisional dissociation (HCD) fragmentation to profile more than 1000-1500 lipid ions mainly from methyl-tert-butyl ether (MTBE) or chloroform:methanol extractions.

METHODS

The platform uses C18 reversed-phase chromatography coupled to a hybrid QExactive Plus/HF Orbitrap mass spectrometer and the entire procedure takes ~10 h from lipid extraction to identification/quantification for a data set containing 12 samples (~4 h for a single sample). Lipids are identified by both accurate precursor ion mass and fragmentation features and quantified using Lipid-Search and Elements software.

RESULTS

Using this approach, we are able to profile intact lipid ions from up to 18 different main lipid classes and 66 subclasses. We show several studies from different biological sources, including cultured cancer cells, resected tissues from mice such as lung and breast tumors and biological fluids such as plasma and urine.

CONCLUSIONS

Using mouse embryonic fibroblasts, we showed that TSC2-/- KD significantly abrogates lipid biosynthesis and that rapamycin can rescue triglyceride (TG) lipids and we show that SREBP-/- shuts down lipid biosynthesis significantly via mTORC1 signaling pathways. We show that in mouse EGFR driven lung tumors, a large number of TGs and phosphatidylmethanol (PMe) lipids are elevated while some phospholipids (PLs) show some of the largest decrease in lipid levels from ~ 2000 identified lipid ions. In addition, we identified more than 1500 unique lipid species from human blood plasma.

Trends in the application of high-resolution mass spectrometry for human biomonitoring: An analytical primer to studying the environmental chemical space of the human exposome

Global profiling of xenobiotics in human matrices in an untargeted mode is gaining attention for studying the environmental chemical space of the human exposome. Defined as the study of a comprehensive inclusion of environmental influences and associated biological responses, human exposome science is currently evolving out of the metabolomics science. In analogy to the latter, the development and applications of high resolution mass spectrometry (HRMS) has shown potential and promise to greatly expand our ability to capture the broad spectrum of environmental chemicals in exposome studies. HRMS can perform both untargeted and targeted analysis because of its capability of full- and/or tandem-mass spectrum acquisition at high mass accuracy with good sensitivity. The collected data from target, suspect and non-target screening can be used not only for the identification of environmental chemical contaminants in human matrices prospectively but also retrospectively. This review covers recent trends and advances in this field. We focus on advances and applications of HRMS in human biomonitoring studies, and data acquisition and mining. The acquired insights provide stepping stones to improve understanding of the human exposome by applying HRMS, and the challenges and prospects for future research.

2016 White Paper on recent issues in bioanalysis: focus on biomarker assay validation (BAV) (Part 1 - small molecules, peptides and small molecule biomarkers by LCMS)

The 2016 10^th Workshop on Recent Issues in Bioanalysis (10^th WRIB) took place in Orlando, Florida with participation of close to 700 professionals from pharmaceutical/biopharmaceutical companies, biotechnology companies, contract research organizations, and regulatory agencies worldwide. WRIB was once again a 5-day, weeklong event - A Full Immersion Week of Bioanalysis including Biomarkers and Immunogenicity. As usual, it was specifically designed to facilitate sharing, reviewing, discussing and agreeing on approaches to address the most current issues of interest including both small and large molecule analysis involving LCMS, hybrid LBA/LCMS, and LBA approaches, with the focus on biomarkers and immunogenicity. This 2016 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop, and is aimed to provide the bioanalytical community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. This white paper is published in 3 parts due to length. This part (Part 1) discusses the recommendations for small molecules, peptides and small molecule biomarkers by LCMS. Part 2 (Hybrid LBA/LCMS and regulatory inputs from major global health authorities) and Part 3 (large molecule bioanalysis using LBA, biomarkers and immunogenicity) will be published in the Bioanalysis journal, issue 23.

High-resolution mass spectrometry in toxicology: current status and future perspectives

This paper reviews high-resolution mass spectrometry (HRMS) approaches using time-of-flight or Orbitrap techniques for research and application in various toxicology fields, particularly in clinical toxicology and forensic toxicology published since 2013 and referenced in PubMed. In the introduction, an overview on applications of HRMS in various toxicology fields is given with reference to current review articles. Papers concerning HRMS in metabolism, screening, and quantification of pharmaceuticals, drugs of abuse, and toxins in human body samples are critically reviewed. Finally, a discussion on advantages as well as limitations and future perspectives of these methods is included.

Metabolism and bioactivation of the tricyclic antidepressant amitriptyline in human liver microsomes and human urine

Aim: Amitriptyline is a widely used tricyclic antidepressant, but the metabolic studies were conducted almost 20 years ago using high-performance liquid chromatography coupled with ultraviolet detector or radiolabeled methods. Results: First, multiple ion monitoring (MIM)- enhanced product ion (EPI) scan was used to obtain the diagnostic ions or neutral losses in human liver microsome incubations with amitriptyline. Subsequently, predicted multiple reaction monitoring (MRM)-EPI scan was used to identify the metabolites in human urine with the diagnostic ions or neutral losses. Finally, product ion filtering and neutral loss filtering were used as the data mining tools to screen metabolites. Consequently, a total of 28 metabolites were identified in human urine after an oral administration using LC–MS/MS. Conclusion: An integrated workflow using LC–MS/MS was developed to comprehensively profile the metabolites of amitriptyline in human urine, in which five N-acetyl-l-cysteine conjugates were characterized as tentative biomarkers for idiosyncratic toxicity.

Discovery of nutritional biomarkers: future directions based on omics technologies

Understanding the interactions between food and human biology is of utmost importance to facilitate the development of more efficient nutritional interventions that might improve our wellness status and future health outcomes by reducing risk factors for non-transmittable chronic diseases, such as cardiovascular diseases, cancer, obesity and metabolic syndrome. Dissection of the molecular mechanisms that mediate the physiological effects of diets and bioactive compounds is one of the main goals of current nutritional investigation and the food industry as might lead to the discovery of novel biomarkers. It is widely recognized that the availability of robust nutritional biomarkers represents a bottleneck that delays the innovation process of the food industry. In this regard, omics sciences have opened up new avenues of research and opportunities in nutrition. Advances in mass spectrometry, nuclear magnetic resonance, next generation sequencing and microarray technologies allow massive genome, gene expression, proteomic and metabolomic profiling, obtaining a global and in-depth analysis of physiological/pathological scenarios. For this reason, omics platforms are most suitable for the discovery and characterization of novel nutritional markers that will define the nutritional status of both individuals and populations in the near future, and to identify the nutritional bioactive compounds responsible for the health outcomes.

In vivo drug metabolite identification in preclinical ADME studies by means of UPLC/TWIMS/high resolution-QTOF MS(E) and control comparison: cost and benefit of vehicle-dosed control samples

1. Liquid chromatography (LC)-high resolution mass spectrometry (HRMS) techniques proved to be well suited for the identification of predicted and unexpected drug metabolites in complex biological matrices. 2. To efficiently discriminate between drug-related and endogenous matrix compounds, however, sophisticated postacquisition data mining tools, such as control comparison techniques are needed. For preclinical absorption, distribution, metabolism and excretion (ADME) studies that usually lack a placebo-dosed control group, the question arises how high-quality control data can be yielded using only a minimum number of control animals. 3. In the present study, the combination of LC-traveling wave ion mobility separation (TWIMS)-HRMS(E) and multivariate data analysis was used to study the polymer patterns of the frequently used formulation constituents polyethylene glycol 400 and polysorbate 80 in rat plasma and urine after oral and intravenous administration, respectively. 4. Complex peak patterns of both constituents were identified underlining the general importance of a vehicle-dosed control group in ADME studies for control comparison. Furthermore, the detailed analysis of administration route, blood sampling time and gender influences on both vehicle peak pattern as well as endogenous matrix background revealed that high-quality control data is obtained when (i) control animals receive an intravenous dose of the vehicle, (ii) the blood sampling time point is the same for analyte and control sample and (iii) analyte and control samples of the same gender are compared.

High-Efficiency Recognition and Identification of Disulfide Bonded Peptides in Rat Neuropeptidome Using Targeted Electron Transfer Dissociation Tandem Mass Spectrometry

The main goal of the present study is to develop a method to recognize and identify endogenous intrachain disulfide bonded peptide, which are rarely sequenced in current peptidomics studies. In order to achieve highly efficient detection of these peptides in a neuropeptidome analysis, we alkylated the peptides, mined the raw mass spectrometry data, and then recognized the candidates of untreated disulfide bonded peptides from unalkylated peptide extracts. After removing more than 90% features, targeted electron transfer dissociation fragmentation was performed for detecting and fragmenting disulfide bonded peptides, and even most of them were present in low abundance in the original sample. Diverse endogenous disulfide bonded peptides were then detected and sequenced, opening up new perspectives for comprehensively understanding the response of a neuropeptidome.

Multi-mycotoxin Analysis of Finished Grain and Nut Products Using Ultrahigh-Performance Liquid Chromatography and Positive Electrospray Ionization-Quadrupole Orbital Ion Trap High-Resolution Mass Spectrometry

Ultrahigh-performance liquid chromatography using positive electrospray ionization and quadrupole orbital ion trap high-resolution mass spectrometry was evaluated for analyzing mycotoxins in finished cereal and nut products. Optimizing the orbital ion trap mass analyzer in full-scan mode using mycotoxin-fortified matrix extracts gave mass accuracies, δM, of < ± 2.0 ppm at 70,000 full width at half maximum (FWHM) mass resolution (RFWHM). The limits of quantitation were matrix- and mycotoxin-dependent, ranging from 0.02 to 11.6 μg/kg. Mean recoveries and standard deviations for mycotoxins from acetonitrile/water extraction at their relevant fortification levels were 91 ± 10, 94 ± 10, 98 ± 12, 91 ± 13, 99 ± 15, and 93 ± 17% for corn, rice, wheat, almond, peanut, and pistachio, respectively. Nineteen mycotoxins with concentrations ranging from 0.3 (aflatoxin B1 in peanut and almond) to 1175 μg/kg (fumonisin B1 in corn flour) were found in 35 of the 70 commercial grain and nut samples surveyed. Mycotoxins could be identified at δM < ± 5 ppm by identifying the precursor and product ions in full-scan MS and data-dependent MS/MS modes. This method demonstrates a new analytical approach for monitoring mycotoxins in finished grain and nut products.

Assessment of tandem mass spectrometry and high-resolution mass spectrometry for the analysis of bupivacaine in plasma

Triple quadrupole mass spectrometers coupled with high performance liquid chromatography are workhorses in quantitative bioanalyses. They provide substantial benefits including reproducibility, sensitivity and selectivity for trace analysis. Selected reaction monitoring allows targeted assay development but datasets generated contain very limited information. Data mining and analysis of nontargeted high-resolution mass spectrometry profiles of biological samples offer the opportunity to perform more exhaustive assessments, including quantitative and qualitative analysis. The objectives of this study were to test method precision and accuracy, to statistically compare bupivacaine drug concentration in real study samples and to verify if high-resolution and accurate mass data collected in scan mode can actually permit retrospective data analysis, more specifically, extract metabolite related information. The precision and accuracy data presented using both instruments provided equivalent results. Overall, the accuracy ranged from 106.2 to 113.2% and the precision observed was from 1.0 to 3.7%. Statistical comparisons using a linear regression between both methods revealed a coefficient of determination (R(2)) of 0.9996 and a slope of 1.02, demonstrating a very strong correlation between the two methods. Individual sample comparison showed differences from -4.5 to 1.6%, well within the accepted analytical error. Moreover, post-acquisition extracted ion chromatograms at m/z 233.1648 ± 5 ppm (M - 56) and m/z 305.2224 ± 5 ppm (M + 16) revealed the presence of desbutyl-bupivacaine and three distinct hydroxylated bupivacaine metabolites. Post-acquisition analysis allowed us to produce semi-quantitative evaluations of the concentration-time profiles for bupicavaine metabolites.

Metabonomics and drug development

Metabolites as an end product of metabolism possess a wealth of information about altered metabolic control and homeostasis that is dependent on numerous variables including age, sex, and environment. Studying significant changes in the metabolite patterns has been recognized as a tool to understand crucial aspects in drug development like drug efficacy and toxicity. The inclusion of metabonomics into the OMICS study platform brings us closer to define the phenotype and allows us to look at alternatives to improve the diagnosis of diseases. Advancements in the analytical strategies and statistical tools used to study metabonomics allow us to prevent drug failures at early stages of drug development and reduce financial losses during expensive phase II and III clinical trials. This chapter introduces metabonomics along with the instruments used in the study; in addition relevant examples of the usage of metabonomics in the drug development process are discussed along with an emphasis on future directions and the challenges it faces.

Rethinking Mass Spectrometry-Based Small Molecule Identification Strategies in Metabolomics

The CASMI 2013 (Critical Assessment of Small Molecule Identification 2013, http://casmi-contest.org/) contest was held to systematically evaluate strategies used for mass spectrometry-based identification of small molecules. The results of the contest highlight that, because of the extensive efforts made towards the construction of databases and search tools, database-assisted small molecule identification can now automatically annotate some metabolite signals found in the metabolome data. In this commentary, the current state of metabolite annotation is compared with that of transcriptomics and proteomics. The comparison suggested that certain limitations in the metabolite annotation process need to be addressed, such as (i) the completeness of the database, (ii) the conversion between raw data and structure, (iii) the one-to-one correspondence between measured data and correct search results, and (iv) the false discovery rate in database search results.

An integrated approach for detection and characterization of the trace impurities in levofloxacin using liquid chromatography-tandem mass spectrometry

RATIONALE

Impurity analysis plays an important role to guarantee the quality and safety of pharmaceuticals. However, identification of impurities remains challenging, especially for those unknown or at trace levels. We present an integrated approach to detect and characterize the trace impurities in drugs.

METHODS

Based on liquid chromatography-tandem mass spectrometry (LC-MS/MS), an approach integrating automatic impurity screening method using multiple mass defect filters (MMDFs) and background subtraction (BS) was developed. This approach was used to acquire the structural and semi-quantitative information in a single sample run, and even to discover the impurity signals submerged by background and drug ions. This approach was illustrated by the comprehensive impurity analysis of levofloxacin.

RESULTS

This approach was sensitive to detect impurities at the level of 0.02% with respect to levofloxacin concentration. Nineteen impurities were detected, fourteen of which were structurally characterized and eight impurities were reported for the first time. Impurity profiles of levofloxacin drug substances and degradation samples were obtained reliably. A plausible degradation pathway of levofloxacin was proposed including descarboxyl reaction under acid, piperazinyl ring cleavage degradation under light, and N-oxidation under oxidative condition.

CONCLUSIONS

The generic approach integrating LC-MS/MS and an automatic impurity screening method was developed for the detection, characterization and monitoring of impurities, especially those unknown or at trace levels. This approach was demonstrated to be rapid, sensitive and automatic for impurity profiling of drugs.