Using a high-resolution mass spectrometry-based metabolomics strategy for comprehensively screening and identifying biomarkers of phthalate exposure: Method development and application

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.

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.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Advancing metabolic networks and mapping updated urinary metabolic fingerprints after exposure to typical carcinogenic heterocyclic aromatic amines

Heterocyclic aromatic amines (HAAs) were not only present in cooked foods and cigarette smoke, but also measured in airborne particles and diesel-exhaust particles. Typical HAAs have been reported to induce carcinogenicity and metabolic disturbances, but how these hazardous compounds interfere with metabolic networks by regulating metabolic pathways and fingerprinting signature metabolites as biomarkers remains ambiguous. We developed an advanced strategy that adopted chemical isotope labeling ultrahigh-performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry for urinary nontargeted metabolomics analysis to gain new insight into in vivo physiological responses stimulated by exposure to typical HAAs. Rats were orally administered with a single dose of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) or 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx) (1 and 10 mg/kg bw) and their D₃-isotopic compounds, respectively, and urine samples were then continuously collected within 36 h. Metabolomics data were acquired and processed by classical multivariate statistical analysis, while urinary metabolites were further identified and characterized according to mass spectrometric fragmentation rules, time- and dose-dependent profiles, and calibration of synthesized standards. We monitored 23 and 37 urinary metabolites as the biotransformation products of PhIP and MeIQx, respectively, and first identified demethylated metabolites of PhIP, tentatively named 2-amino-6-phenylimidazo[4,5-b]pyridine, and dihydroxylation products of classical HAAs as short-term biomarkers of exposure to further unravel the metabolic networks. In addition, our findings revealed that both HAAs significantly disturb histidine metabolism, arginine and proline metabolism, tryptophan metabolism, pyrimidine metabolism, tricarboxylic acid cycle, etc. Furthermore, we found that histamine, methionine, alanine, and 4-guanidinobutanoic acid could be considered potential characteristic biomarkers for the oncogenicity or carcinogenicity of both PhIP and MeIQx and screened their specific key pivotal metabolites. The current metabolomics approach is applicable in mapping updated urinary metabolic fingerprints and identifying potential specific biomarkers for HAAs-induced early tumorigenesis.

Environmental metal exposure, seminal plasma metabolome and semen quality: Evidence from Chinese reproductive-aged men

Environmental metal exposure has been associated with decreasing semen quality, but the effects of multiple metal exposure on seminal plasma metabolome remain obscure. In this study, semen and repeated urine samples from 551 volunteers were collected in Wuhan City. Heavy metals and trace elements were measured using inductively coupled plasma mass spectrometer, and seminal plasma metabolomes were acquired using liquid chromatography coupled with high-resolution mass spectrometry. Weighted gene co-expression network analysis showed more than half of the seminal plasma metals were associated with specific metabolite modules, whereas only a few urine metals presented weak associations, indicating that seminal plasma may be an ideal biological sample for male reproductive biomarker discovery and exposure risk assessment. Seminal plasma zinc (Zn) and selenium (Se) concentrations were significantly associated with 22 metabolites (e.g., glycerophospholipids, acyl-carnitines and amino acid derivatives). Among these metabolites, acyl-carnitines were positively associated with semen quality and sperm concentration. Moreover, acyl-carnitines were associated with both Zn and Se exposure, indicating the potential role of carnitine pathway in their toxicity mechanism. Our findings suggest that seminal plasma metabolome connects Zn and Se exposure and sperm concentrations in Chinese men of reproductive age.

Hair Metabolomics in Animal Studies and Clinical Settings

Metabolomics is a powerful tool used to understand comprehensive changes in the metabolic response and to study the phenotype of an organism by instrumental analysis. It most commonly involves mass spectrometry followed by data mining and metabolite assignment. For the last few decades, hair has been used as a valuable analytical sample to investigate retrospective xenobiotic exposure as it provides a wider window of detection than other biological samples such as saliva, plasma, and urine. Hair contains functional metabolomes such as amino acids and lipids. Moreover, segmental analysis of hair based on its growth rate can provide information on metabolic changes over time. Therefore, it has great potential as a metabolomics sample to monitor chronic diseases, including drug addiction or abnormal conditions. In the current review, the latest applications of hair metabolomics in animal studies and clinical settings are highlighted. For this purpose, we review and discuss the characteristics of hair as a metabolomics sample, the analytical techniques employed in hair metabolomics and the consequence of hair metabolome alterations in recent studies. Through this, the value of hair as an alternative biological sample in metabolomics is highlighted.