Characterizing the D-Amino Acid Position in Peptide Epimers by Using Higher-Energy Collisional Dissociation Tandem Mass Spectrometry: A Case Study of Liraglutide.

D-amino acid-containing peptides (DAACPs) occur in biological and artificial environments. Since the importance of DAACPs has been recognized, various mass spectrometry-based analytical approaches have been developed. However, the capability of higher-energy collisional dissociation (HCD) fragmentation to characterize DAACP sites has not been evaluated. In this study, we compared the normalized spectra intensity under different conditions of HCD and used liraglutide along with its DAACPs as examples. Our results indicated that the difference in the intensity of y ions between DAACPs and all-L liraglutide could not only distinguish them but also localize the sites of D-amino acids in the DAACPs. Our data demonstrate the potential of using HCD for the site characterization of DAACPs, which may have great impact in biological studies and peptide drug development.

Identification of Xenobiotic Biotransformation Products Using Mass Spectrometry-Based Metabolomics Integrated with a Structural Elucidation Strategy by Assembling Fragment Signatures.

The identification of xenobiotic biotransformation products is crucial for delineating toxicity and carcinogenicity that might be caused by xenobiotic exposures and for establishing monitoring systems for public health. However, the lack of available reference standards and spectral data leads to the generation of multiple candidate structures during identification and reduces the confidence in identification. Here, a UHPLC-HRMS-based metabolomics strategy integrated with a metabolite structure elucidation approach, namely, FragAssembler, was proposed to reduce the number of false-positive structure candidates. biotransformation product candidates were filtered by mass defect filtering (MDF) and multiple-group comparison. FragAssembler assembled fragment signatures from the MS/MS spectra and generated the modified moieties corresponding to the identified biotransformation products. The feasibility of this approach was demonstrated by the three biotransformation products of di(2-ethylhexyl)phthalate (DEHP). Comprehensive identification was carried out, and 24 and 13 biotransformation products of two xenobiotics, DEHP and 4'-Methoxy-α-pyrrolidinopentiophenone (4-MeO-α-PVP), were annotated, respectively. The number of 4-MeO-α-PVP biotransformation product candidates in the FragAssembler calculation results was approximately 2.1 times lower than that generated by BioTransformer 3.0. Our study indicates that the proposed approach has great potential for efficiently and reliably identifying xenobiotic biotransformation products, which is attributed to the fact that FragAssembler eliminates false-positive reactions and chemical structures and distinguishes modified moieties on isomeric biotransformation products. The FragAssembler software and associated tutorial are freely available at https://cosbi.ee.ncku.edu.tw/FragAssembler/ and the source code can be found at https://github.com/YuanChihChen/FragAssembler.

Investigation of New Psychoactive Substances (NPS), Other Illicit Drugs, and Drug-Related Compounds in a Taiwanese Wastewater Sample Using High-Resolution Mass-Spectrometry-Based Targeted and Suspect Screening.

The proliferation of new psychoactive substances (NPSs) in recent years has posed a significant challenge to public health. Traditional monitoring methods have proven insufficient in tracking these constantly evolving substances, leading to the development of alternative approaches such as wastewater-based epidemiology (WBE). The present study aims to utilize high-resolution mass spectrometry (HRMS)-based targeted and suspect screening to profile NPS, other illicit drugs, and drug-related compounds in a Taiwanese wastewater sample. For the targeted analysis, 8 out 18 standards of illicit drugs have been identified. The suspect screening approach based on approximately 3600 substances in the SWGDRUG library can further identify 92 compounds, including opiate analgesics, synthetic cathinones, phenylalkylamines derivatives, phenethylamine derivatives, tryptamine derivatives, steroids, and ephedrine-related compounds. Additionally, the presence of 5-methoxy-2-aminoindane (MEAI) in the wastewater indicates that drug dealers have recently sold this potential NPS to evade drug regulations. This study firstly reports the HRMS-based comprehensive profile of NPS, other illicit drugs, and drug-related compounds in Taiwan, which could be applied as biomarkers for estimating the consumption of drugs.

Development of a lateral flow immunoassays-based method for the screening of ractopamine in foods and evaluation of the optimal strategy in combination of screening and confirmatory tests.

Ractopamine has been authorized as a feed additive and permitted in animal husbandry. With the establishment of the regulation to limit the concentration of ractopamine, a rapid screening method for ractopamine is urgently needed. Additionally, how to combine the screening and confirmatory tests of ractopamine is also critical to maximizing the efficiency of testing. Here, we developed a lateral flow immunoassays-based method for the screening of ractopamine in foods and proposed a cost-benefit analysis approach to optimize cost allocation between screening and confirmatory tests. After verifying the analytical and clinical performances of the screening method, a mathematical model was established to calculate the screening and confirmatory test results with various parameter settings, such as cost allocation, false-negative tolerance, and total budget size. The developed immunoassay-based screening test could successfully distinguish gravy samples with ractopamine levels over and lower than maximum residue limits (MRL). The area under curve (AUC) value of receiver operating characteristic (ROC) curve is 0.99. For the cost-benefit analysis, mathematical simulation indicated that when the samples are allocated to screening and confirmatory tests at the optimized cost allocation, the number of confirmed positive samples can increase by 26 times compared to the scenarios entirely relying on confirmatory testing. While conventional wisdom considers that screening should be carried out at low false-negative rates, such as 0.1%, our results indicated that the cutoff value of a screening test with a 20% false-negative rate at MRL could capture the maximum number of confirmed positive samples at a limited budget. Our work indicated that the participation of the screening method in ractopamine analysis and optimized cost allocation between screening and confirmatory tests could enhance the efficiency in detecting the positive samples, which provides a rational basis for decision-making in food safety enforcement for public health.

Monitoring long-term chemical exposome by characterizing the hair metabolome using a high-resolution mass spectrometry-based suspect screening approach.

Hair has recently emerged as a biospecimen for characterizing the long-term chemical exposome in biomonitoring investigations spanning several months, as chemical compounds circulating in the bloodstream accumulate in hair. Although there has been interest in using human hair as a biospecimen for exposome studies, it has yet to be widely adopted compared to blood and urine. Here, we applied a high-resolution mass spectrometry (HRMS)-based suspect screening strategy to characterize the long-term chemical exposome in human hair. Hair samples were collected from 70 subjects and cut into 3 cm segments, which were then mixed to prepare pooled samples. The pooled hair samples underwent a sample preparation procedure, and the hair extracts were further analyzed using an HRMS-based suspect screening approach. An in-house chemical suspect list containing 1227 chemical entries from National Report on Human Exposure to Environmental Chemicals (Report) published by the U.S. CDC and the Exposome-Explorer 3.0 database developed by the WHO was subsequently used to screen and filter the suspect features against the HRMS dataset. Overall, we matched 587 suspect features in the HRMS dataset to 246 unique chemical formulas in the suspect list, and the structures of 167 chemicals were further identified through a fragmentation analysis. Among these, chemicals such as mono-2-ethylhexyl phthalate, methyl paraben, and 1-naphthol, which have been detected in the urine or blood for exposure assessment, were also identified in human hair. This suggests that hair reflects the accumulation of environmental compounds to which an individual is exposed. Exposure to exogenous chemicals may exert adverse effects on cognitive function, and we discovered 15 chemicals in human hair that may contribute to the pathogenesis of Alzheimer's disease. This finding suggests that human hair may be a promising biospecimen for monitoring long-term exposure to multiple environmental chemicals and perturbations in endogenous chemicals in biomonitoring investigations.

Untargeted metabolomics analysis assisted by signal selection for comprehensively identifying metabolites of new psychoactive substances: 4-MeO-α-PVP as an example.

New psychoactive substances (NPS) have been rapidly emerged as legal alternatives to controlled drugs, which raised severe public health issue. The detection and monitoring of its intake by complete metabolic profiling is an urgent and vital task. Untargeted metabolomics approach has been applied for several NPS metabolites studies. Although the number of such works is relatively limited but with a rapidly growing need. The present study aimed to propose a procedure that includes liquid chromatography high-resolution mass spectrometry (LC-HRMS) analysis and a signal selection software, MetaboFinder, programed as a web tool. The comprehensive metabolites profile of one kind of NPS, 4-methoxy-α-pyrrolidinovalerophenone (4-MeO-α-PVP), was studied by using this workflow. In this study, two different concentrations of 4-MeO-α-PVP along with as blank sample were incubated with human liver S9 fraction for the conversion to their metabolites and followed by LC-MS analysis. After retention time alignment and feature identification, 4640 features were obtained and submitted to statistical analysis for signal selection by using MetaboFinder. A total of 50 features were considered as 4-MeO-α-PVP metabolite candidates showing significant changes (p < 0.00001 and fold change >2) between the two investigated groups. Targeted LC-MS/MS analysis was conducted focusing on these significantly expressed features. Assisted by chemical formula determination according to high mass accuracy and in silico MS2 fragmentation prediction, 19 chemical structure identifications were achieved. Among which, 8 metabolites have been reported derived from 4-MeO-α-PVP in a previous literature while 11 novel 4-MeO-α-PVP metabolites were identified by using our strategy. Further in vivo animal experiment confirmed that 18 compounds were 4-MeO-α-PVP metabolites, which demonstrated the feasibility of our strategy for screening the 4-MeO-α-PVP metabolites. We anticipate that this procedure may support and facilitate traditional metabolism studies and potentially being applied for routine NPS metabolites screening.

Rat Hair Metabolomics Analysis Reveals Perturbations of Unsaturated Fatty Acid Biosynthesis, Phenylalanine, and Arachidonic Acid Metabolism Pathways Are Associated with Amyloid-ß-Induced Cognitive Deficits.

Hair is a noninvasive valuable biospecimen for the long-term assessment of endogenous metabolic disturbance. Whether the hair is suitable for identifying biomarkers of the Alzheimer's disease (AD) process remains unknown. We aim to investigate the metabolism changes in hair after ß-amyloid (Aß1-42) exposure in rats using ultra-high-performance liquid chromatography-high-resolution mass spectrometry-based untargeted and targeted methods. Thirty-five days after Aß1-42 induction, rats displayed significant cognitive deficits, and forty metabolites were changed, of which twenty belonged to three perturbed pathways: (1) phenylalanine metabolism and phenylalanine, tyrosine, and tryptophan biosynthesis-L-phenylalanine, phenylpyruvate, ortho-hydroxyphenylacetic acid, and phenyllactic acid are up-regulated; (2) arachidonic acid (ARA) metabolism-leukotriene B4 (LTB4), arachidonyl carnitine, and 5(S)-HPETE are upregulation, but ARA, 14,15-DiHETrE, 5(S)-HETE, and PGB2 are opposite; and (3) unsaturated fatty acid biosynthesis- eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), FA 18:3 + 1O, and FA 18:3 + 2O are downregulated. Linoleic acid metabolism belonging to the biosynthesis of unsaturated fatty acid includes the upregulation of 8-hydroxy-9,10-epoxystearic acid, 13-oxoODE, and FA 18:2 + 4O, and downregulation of 9(S)-HPODE and dihomo-γ-linolenic acid. In addition, cortisone and dehydroepiandrosterone belonging to steroid hormone biosynthesis are upregulated. These three perturbed metabolic pathways also correlate with cognitive impairment after Aß1-42 stimulation. Furthermore, ARA, DHA, EPA, L-phenylalanine, and cortisone have been previously implicated in the cerebrospinal fluid of AD patients and show a similar changing trend in Aß1-42 rats' hair. These data suggest hair can be a useful biospecimen that well reflects the expression of non-polar molecules under Aß1-42 stimulation, and the five metabolites have the potential to serve as novel AD biomarkers.

Identifying Hair Biomarker Candidates for Alzheimer's Disease Using Three High Resolution Mass Spectrometry-Based Untargeted Metabolomics Strategies.

High-resolution mass spectrometry (HRMS)-based untargeted metabolomics strategies have emerged as an effective tool for discovering biomarkers of Alzheimer's disease (AD). There are various HRMS-based untargeted metabolomics strategies for biomarker discovery, including the data-dependent acquisition (DDA) method, the combination of full scan and target MS/MS, and the all ion fragmentation (AIF) method. Hair has emerged as a potential biospecimen for biomarker discovery in clinical research since it might reflect the circulating metabolic profiles over several months, while the analytical performances of the different data acquisition methods for hair biomarker discovery have been rarely investigated. Here, the analytical performances of three data acquisition methods in HRMS-based untargeted metabolomics for hair biomarker discovery were evaluated. The human hair samples from AD patients (N = 23) and cognitively normal individuals (N = 23) were used as an example. The most significant number of discriminatory features was acquired using the full scan (407), which is approximately 10-fold higher than that using the DDA strategy (41) and 11% higher than that using the AIF strategy (366). Only 66% of discriminatory chemicals discovered in the DDA strategy were discriminatory features in the full scan dataset. Moreover, compared to the deconvoluted MS/MS spectra with coeluted and background ions from the AIF method, the MS/MS spectrum obtained from the targeted MS/MS approach is cleaner and purer. Therefore, an untargeted metabolomics strategy combining the full scan with the targeted MS/MS method could obtain most discriminatory features along with a high quality MS/MS spectrum for discovering the AD biomarkers.

Connecting chemical exposome to human health using high-resolution mass spectrometry-based biomonitoring: Recent advances and future perspectives.

Compared with the rapid advances in genomics leading to broad understanding of human disease, the linkage between chemical exposome and diseases is still under investigation. High-resolution mass spectrometry (HRMS) is expected to accelerate the process via relatively accurate and precise biomonitoring of human exposome. This review covers recent advancements in biomonitoring of exposed environmental chemicals (chemical exposome) using HRMS described in the 124 articles that resulted from a systematic literature search on Medline and Web of Science databases. The analytical strategic aspects, including the selection of specimens, sample preparation, instrumentation, untargeted versus targeted analysis, and workflows for MS-based biomonitoring to explore the environmental chemical space of human exposome, are deliberated. Applications of HRMS in human exposome investigation are presented by biomonitoring (1) exposed chemical compounds and their biotransformation products; (2) DNA/protein adducts; and (3) endogenous compound perturbations. Challenges and future perspectives are also discussed.

Post-Deconvolution MS/MS Spectra Extraction with Data-Independent Acquisition for Comprehensive Profiling of Urinary Glucuronide-Conjugated Metabolome.

Conjugation reactions are of critical significance in human metabolism. Identification of these conjugated metabolites is still challenging. Here, we propose a strategy, post-deconvolution MS/MS spectra extraction with data-independent acquisition (PDMS2E-DIA), to comprehensively profile the glucuronide-conjugated metabolome. PDMS2E-DIA enables the identification of conjugated and unconjugated metabolite pairs through neutral loss filtering combined with a significant change in abundance after the deconjugation reaction. Purified DIA MS/MS spectra were constructed by extracting MS/MS fragments shared between spectra derived from conjugated and unconjugated metabolites. The feasibility of this approach was first demonstrated by the identification of two glucuronide-conjugated metabolite standards spiked in urine samples. For human urine samples, 479 features were structurally annotated as potential glucuronide-conjugated metabolites, resulting in the identification of 211 metabolites. Fragment peaks derived from interferents were found to be removed by PDMS2E-DIA, which increased about 6 times the number of identified urine metabolites compared with those calculated from raw DIA deconvoluted MS/MS spectra. This approach was found to have great potential for identifying glucuronide-conjugated metabolites, as well as other kinds of chemical conjugations.

Extraction strategies for tackling complete hair metabolome using LC-HRMS-based analysis.

Over recent years, metabolomics has been featured as the state-of-the-art technology that successfully opens the paths to understanding biological mechanisms and facilitating biomarker discovery. However, the inherent dynamic and sensitive nature of the metabolome have been challenging the accuracy of capturing the timepoints of interest while using biofluids such as urine and blood. Hair has thus emerged as a valuable analytical specimen for the long-term and retrospective determinations. Unfortunately, notwithstanding the apparent interest on global hair metabolomics, very few studies have engaged in the optimisation of the extraction strategy. In this study, we systemically investigated the extraction procedures for hair metabolome using a single factor experimental design. Three pH values (acidic, neutral, and basic) in aqueous solution, six extraction solvents (methanol, acetonitrile, acetone, phosphate-buffered saline, deionised water, and dichloromethane), different compositions of selected solvent mixtures and their sequential extraction, and a series of extraction times (15, 45, 60, 120, 240, and 480 min) were evaluated. The ideal condition for hair extraction is ultrasonic-assisted extraction with methanol:phosphate-buffered saline 50:50 (v/v) under +55 °C for 240 min. This strategy may secure the true composition of the metabolome, maximise the signal abundance, and guarantee a high coverage of wide-range metabolites in a straightforward approach. The optimised extraction strategy was then coupled with structure annotation tools for hair metabolome profiling. After a single RPLC-HRMS run, hair metabolite identification was achieved as the annotations of 171 probable structures and 853 tentative structures as well as the assignments of 414 unequivocal molecular formulae. In conclusion, we established an efficient extraction strategy for untargeted hair metabolomics, which the method is deliverable to any analytical laboratories and the sample can be directly profiled by means of a conventional RPLC-HRMS gradient.

New coumarins and anti-inflammatory constituents from the fruits of Cnidium monnieri.

The fruit of Cnidium monnieri is commercially used as healthcare products for the improvement of impotence and skin diseases. Three new coumarins, 3'-O-methylmurraol (1), rel-(1'S,2'S)-1'-O-methylphlojodicarpin (2), and (1'S,2'S)-1'-O-methylvaginol (3), have been isolated from the fruits of C. monnieri, together with 14 known compounds (4-17). The structures of these new compounds were determined through spectroscopic and MS analyses. Compounds 1, 4-12, and 14-17 exhibited inhibition (IC50 ≤ 7.31 µg/mL) of superoxide anion generation by human neutrophils in response to formyl-l-methionyl-l-leucyl-l-phenylalanine/cytochalasin B (fMLP/CB). Compounds 7, 9-11, 15, and 17 inhibited fMLP/CB-induced elastase release with IC50 values ≤7.83 µg/mL. This investigation reveals that bioactive isolates (especially 6, 7, 14, and 17) could be further developed as potential candidates for the treatment or prevention of various inflammatory diseases.