High resolution mass spectrometric quantitation of acrolein and etheno-DNA adducts in oral cells of smokers, e-cigarette users, and non-smokers
Guang Cheng, Jiehong Guo – Minnesota HHEAR Targeted Analysis Laboratory
Cigarette smoking and e-cigarette use are important sources of human exposure to toxicants and carcinogens. Acrolein, a widespread environmental pollutant considered “probably carcinogenic to humans” by the International Agency for Research on Cancer, is present in relatively high amounts in cigarette smoke and in lower amounts in e-cigarette vapor. Acrolein can react directly with DNA to form DNA adducts, which are critical intermediates in the induction of cancer and can serve as important biomarkers for the assessment of potential harm. Etheno-DNA adducts are promutagenic DNA lesions that can derive from exogenous chemicals as well as endogenous sources, including lipid peroxidation. We have developed a unique combined method for the quantitation of the acrolein-DNA adducts α-OH-Acr-dGuo and γ-OH-Acr-dGuo, and the etheno-DNA adducts 1,N6-etheno-dAdo (εdAdo) and 3,N4-etheno-dCyd (εdCyd) in oral cells of humans. The method uses state of the art liquid chromatography-nanoelelctrospray ionization-high resolution tandem mass spectrometry. We found significantly higher levels of α-OH-Acr-dGuo, γ-OH-Acr-dGuo, εdAdo and εdCyd in smokers than non-smokers and significantly higher levels of γ-OH-Acr-dGuo in e-cigarette users compared to non-users of any tobacco product. Our results demonstrate that oral mucosa cells are an excellent source of material for evaluating DNA adducts which can be used as biomarkers of carcinogen and toxicant exposure and molecular changes potentially related to cancer. The results in e-cigarette users are particularly important considering the extensive use of these products by younger people.
This work is published in Chemical Research in Toxicology. 2020; 33: 2197-2207.
This work will be published in Carcinogenesis (in press)
Targeted analysis of silicone wristbands for PFAS using LC-MS/MS
Ellen M. Cooper, Nick Herkert, Heather M. Stapleton, Sharon Zhang - Duke HHEAR Environmental Analysis Laboratory
Concern over human exposure to per-and polyfluoroalkyl substances (PFAS) has grown over the last decade with increased identification of communities with contaminated drinking water. While drinking water and food are widely acknowledged to be the most significant sources of human exposure to PFAS, exposure via inhalation and inadvertent ingestion of dust particles can also occur. Indoor air and dust have been shown to be contaminated with PFAS, including the persistent perfluoroalkyl acids (PFAAs), such as PFOA and PFOS. However, indoor environments often have higher levels of PFAA precursors, which are PFAS that can undergo transformation to produce persistent PFAAs. Examples of precursors include fluorotelomer alcohols (FTOHs) and polyfluoroalkyl phosphoric diesters (diPAPs). Building materials and consumer products, such as flooring materials, rugs and stain resistant upholstery are thought to be sources of these PFAS in indoor environments.
Silicone wristbands are a passive sampler that has been increasingly used over the past few years to assess and characterize exposure via inhalation, dermal exposure and inadvertent dust ingestion. Using wristbands, our research group has observed positive and significant correlations between levels of organic contaminants measured on wristbands, such as organophosphate esters (OPEs; flame retardants and plasticizers), triclosan, and parabens, with their urinary biomarkers of exposure.
Using resources available through the Human Health Analysis Resource (HHEAR) Development Core, the Duke Environmental Analysis Lab Hub developed a targeted method to quantify 18 PFAS that accumulate on silicone wristbands. A brief description of the method is shown below. This method was successfully applied to the analysis of wristbands worn by firefighters in Durham County, NC in 2020. Firefighters wore wristbands while they were on duty and while off-duty and differences in their exposure profiles were examined. PFAS were detected on all wristbands, and the most abundant PFAS detected were the precursors 6:2 diPAP and 8:2 diPAP. PFOA and PFOS were also commonly detected but at lower concentrations. When comparing on duty vs off-duty levels in wristbands, PFOS was found to be significantly higher while on duty and responding to a fire compared to off-duty. This suggests that firefighters have higher exposure to PFOS while working. In our study, firefighters did not use AFFF. This suggests that exposure may be from their gear, which can be contaminated with PFAS, or perhaps from other sources in the fire stations. These results suggest that wristbands can be used to monitor ambient exposure to PFAS. Further details on the method and this research study can be found in our publication (Levasseur et al. 2022).
This work is published in Science of the Total Environment. 2022 Aug 15;834:155237.
Validated single urinary assay designed for exposomic multi-class biomarkers of common environmental exposures
Ravikumar Jagani, Divya Pulivarthi, Dhavalkumar Patel, Rosalind J. Wright, Robert O. Wright, Manish Arora, Mary S. Wolff, and Syam S. Andra – Mount Sinai HHEAR Network Targeted Lab Hub
Epidemiological studies often call for analytical methods that use a small biospecimen volume to quantify trace level exposures to environmental chemical mixtures. Currently, as many as 150 polar metabolites of environmental chemicals have been found in urine. Therefore, we developed a multi-class method for quantitation of biomarkers in urine. A single sample preparation followed by three LC injections was optimized in a proof-of-approach for a multi-class method. The assay was validated to quantify 50 biomarkers of exposure in urine, belonging to 7 chemical classes and 16 sub-classes. The classes represent metabolites of 12 personal care and consumer product chemicals (PCPs), 5 polycyclic aromatic hydrocarbons (PAHs), 5 organophosphate flame retardants (OPFRs), 18 pesticides, 5 volatile organic compounds (VOCs), 4 tobacco alkaloids, and 1 drug of abuse. Human urine (0.2 mL) was spiked with isotope-labeled internal standards, enzymatically deconjugated, extracted by solid-phase extraction, and analyzed using high-performance liquid chromatography-tandem mass spectrometry. The methanol eluate from the cleanup was split in half and the first half analyzed for PCPs, PAH, and OPFR on a Betasil C18 column; and pesticides and VOC on a Hypersil Gold AQ column. The second half was analyzed for tobacco smoke metabolites and a drug of abuse on a Synergi Polar RP column. Limits of detection ranged from 0.01 to 1.0 ng/mL of urine, with the majority ≤0.5 ng/mL (42/50). Analytical precision, estimated as relative standard deviation of intra- and inter-batch uncertainty, variabilities, was <20%. Extraction recoveries ranged from 83 to 109%. Results from the optimized multi-class method were qualified in formal international proficiency testing programs. Further method customization options were explored, and method expansion was demonstrated by inclusion of up to 101 analytes of endo- and exogenous chemicals. This exposome-scale assay is being used for population studies with savings of assay costs and biospecimens, providing both quantitative results and the discovery of unexpected exposures.
This work is published in Anal Bioanal Chem. 2022 Aug;414(19):5943-5966.
A liquid chromatography – tandem mass spectrometry method for the analysis of primary aromatic amines in human urine
Sridhar Chinthakindi and Kurunthachalam Kannan – Wadsworth HHEAR Targeted Analysis Laboratory
In this study, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed to determine 39 primary aromatic amines (AAs) along with nicotine and cotinine in human urine. Chromatographic separation of the 41 analytes was achieved on an Ultra biphenyl (100 mm x 2.1 mm, 5 µm) column. Mass spectrometry was operated in electrospray ionization positive ion multi-reaction monitoring (MRM) mode. The method exhibited excellent linear dynamic range (0.1-50 ng/mL) with correlation coefficients (r) >0.999 for all analytes. Urine samples (2 mL) were hydrolyzed using 10N NaOH at 95 0C for 15 h and target analytes were extracted using methyl-tert-butyl ether (MTBE). Addition of 15 µL of 0.25N HCl to the sample extracts improved the recoveries of several target analytes. The method was validated through the analysis of fortified quality control (QC) samples and a certified standard reference material (SRM). Relative recoveries (%) of target analytes fortified in QC samples were in the range of 75-114% for 37 of the 41 analytes while the other analytes exhibited lower recoveries (16-74%). The limits of detection (LOD) and limits of quantification (LOQ) of target analytes were in the range of 0.025-0.20 ng/mL and 0.1-1.0 ng/mL, respectively. Intra-day and inter-day precision of the method assessed through the analysis of fortified urine QC samples at three different concentrations were <11.7% and <15.9% (measured as RSD), respectively.
This work is published in Journal of Chromatography B. 2021; 180: 122888
A method for the analysis of 121 multi-class environmental chemicals in urine by high-performance liquid chromatography-tandem mass spectrometry
Hongkai Zhu, Sridhar Chinthakindi, and Kurunthachalam Kannan – Wadsworth HHEAR Targeted Analysis Laboratory
A method involving solid-phase extraction (SPE) coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) and capable of measuring 121 environmental chemicals comprising plasticizers (PMs; n=45), environmental phenols (EPs; n=45), and pesticides (n=31) through a single extraction of 500 uL urine was developed. Urine samples were incubated with 20 µL of β-glucuronidase/arylsulfatase (4000 units/mL urine) (from Helix pomatia) buffered at pH 5.5 for 2 h at 37oC for optimal deconjugation conditions. The SPE, with ABS Elut NEXUS® cartridges, was optimized to yield the best extraction efficiencies. For increased resolution and chromatographic separation, two methods involving Ultra AQ C18® and BetasilTM C18® columns were used. The MS/MS analyses were performed under both negative and positive ionization modes. The optimized method yielded excellent intra- and inter-day variabilities (relative standard deviation: 0.40–11%) and satisfactory recoveries (80–120%) for >95% of the analytes. The limits of detection were ≤ 0.1 for 101 analytes and between 0.1 and 1.0 ng/mL for 18 analytes. The optimized SPE LC-MS/MS method was validated through the analysis of standard reference materials and proficiency test urine samples and further applied in the analysis of 21 real urine samples to demonstrate simultaneous determination of 121 environmental chemicals in urine samples.
This work is published in Journal of Chromatography A. 2021; 1646: 462146
Analysis methods for conjugated metabolites
Timothy Fennell, Rodney Snyder and Colin Kay – North Carolina HHEAR Untargeted Analysis Laboratory
Many xenobiotics undergo multiple metabolic transformations including conjugation with glucuronic acid, sulfate, glycine, and glutathione with the excretion of mercapturic acids. Approaches for analysis of plasma and urine levels of chemicals involve the incubation with enzymes that cleave these conjugates and analyze the unconjugated form. While this approach is widely used in targeted analyses, incubation with e.g., β-glucuronidase can also enable other enzyme activity in the enzyme preparation and in the samples themselves to transform other molecules during the incubation. Many chemicals that are not readily analyzed by LC-MS are metabolized to conjugates that can be readily detected by LC-MS. High resolution LC-MS is used extensively for untargeted analysis, and typically uses MS and MS/MS fragmentation and retention time for characterization. We are adding conjugates e.g., glucuronides of exogenous compounds to our library. Advanced techniques for characterizing metabolites are being put in place following the addition of a Thermo Orbitrap IQ-X capable of MSn, to our core. We have implemented high resolution neutral loss experiments, and MSn to characterize features e.g., as a glucuronide with loss of 176 amu (MS2), and then with additional MS3 to characterize the remaining component of the molecule. The approach can be readily applied to find glucuronides, diglucuronides, and other conjugates during high resolution LC-MS, and to characterize unknowns that may result from exposure to exogenous chemicals.
Exploring untargeted metabolomics in seminal plasma to study reproductive health
Yuan Yuan Li – North Carolina HHEAR Untargeted Analysis Laboratory
Seminal plasma, the medium produced by several accessory sex glands of the male reproductive tract, contains many biochemical molecules related to the host metabolism – including fructose, putrescine, spermine, spermidine, proteins, extracellular vesicles, RNAs, and antioxidants – and plays an essential role in sperm development and functions related to male reproductive outcomes. Growing evidence indicated that exposure to environmentally relevant compounds, especially the environmental endocrine-disrupting chemicals, is related to male reproductive disorders (e.g., infertility, low testosterone, hypospadias, etc.). Many of these compounds are metabolized in our bodies and circulated in seminal plasma. Therefore, seminal plasma is an ideal non-invasive biospecimen to study the interaction between Exposome and male reproductive health. Semen samples were collected in a sterile plastic specimen cup after a 2–3-day abstinence period. Seminal plasma was extracted with methanol containing 500 ng/ml L-tryptophan-d5, and the metabolome was analyzed by the Vanquish UHPLC system coupled with a Q Exactive™ HF-X Hybrid Quadrupole-Orbitrap Mass Spectrometer (ThermoFisher Scientific, San Jose, CA).
After data preprocessing and quality control procedures, we obtained 15,648 signals from seminal plasma. Over 100 exogenous metabolites, including environmentally relevant metabolites (phthalates, mercapturic acids, tobacco-related metabolite, phenols, and benzene metabolites), ingested food components (hippuric acid and derivatives, benzaldehyde/benzoic acid metabolites, purine derivatives, tryptophan-indole metabolite, and pyridine carboxylic acids), drugs and medications (acetaminophen, ibuprofen metabolite, naproxen), and metabolites relevant to microbiome-xenobiotic interaction (dipeptide, sugar amide, tyrosine metabolite), were identified and annotated from the seminal plasma samples, through matching against the NC HHEAR hub in-house experimental standard library. Mercapturic acids, including (R,S)-N-Acetyl-S-(2-hydroxy-3-buten-1-yl)-L-cysteine and N-Acetyl-S-(2-hydroxy-3-propionamide)-L-cysteine, were found to be significantly higher (p<0.1) in the low quality sperm (LQS) than the normal quality sperm (NSQ). We observed clear differentiation of metabolic profiles in the unsupervised multivariate principle analysis (PCA) regarding different sperm quality (LQS vs. NQS) and different birth outcomes (not-live birth vs. live birth). Pathway enrichment analysis indicated that fatty acid biosynthesis and metabolism, vitamin A metabolism, and histidine metabolism were associated with the differentiation of sperm quality; while pathways involving vitamin A metabolism, C21-steroid hormone biosynthesis and metabolism, arachidonic acid metabolism, and Omega-3 fatty acid metabolism were distinguished regarding the birth outcomes.
Taken together, this pilot suggests that seminal plasma metabolomics can be used to study the exposome and reproductive birth outcomes. Future studies aim to expand our analyses to validate these findings.
Exposome analysis of stool samples from vegans and omnivores
Blake Rushing – North Carolina HHEAR Untargeted Analysis Laboratory
Pooled stool samples from vegans and omnivores, divided into aqueous and lyophilized fractions, were provided by NIST.
Sample preparation for lyophilized stool fractions
20 mg samples from each pooled reference material were weighed out and placed into MagNA lyser tubes containing ceramic beads. Additional MagNA lyser tubes with beads containing no stool sample were prepared for blank samples. Samples were extracted by the addition of 1 mL of a 50% acetonitrile solution, and then homogenized using an Omni Bead Ruptor (5 meters/sec, two 30 sec cycles, 15 sec dwell time in between cycles). Samples were then centrifuged at 4oC for 15 min at 16000 rcf. 800 uL of the supernatant from each sample was transferred to new tubes and then re-centrifuged at 4oC for 10 min at 16000 rcf. A total pool was made by combining equal volumes from each diet and then dispensing into 50 uL aliquots. All samples were dried by Speedvac, reconstituted in 100 uL of a 5% methanol solution, and 5 uL was injected for LC-MS analysis.
Sample preparation for aqueous stool fractions
Aliquots of 50 uL from both vegan and omnivorous diets were placed into individual tubes. Blanks were prepared by creating 50 uL aliquots of LC-MS water. Samples were extracted by the addition of 400 uL of a 50% acetonitrile solution, vortexing for 5 min at 5000 rpm, and centrifuging at 4oC for 10 min at 16000 rcf. For each sample, 100 uL of the supernatant was transferred to new tubes. Total pool samples were made by combining an additional 70 uL of each supernatant into one mixture, which was distributed into 100 uL aliquots. All samples were dried by speedvac, reconstituted in 200 uL of a 5% methanol solution, and 5 uL was injected for LC-MS analysis.
Compound Identification and Annotation
Biospecimens and blanks were analyzed by UHPLC-HRMS. Data preprocessing including peak picking, alignment, and peak deconvolution was performed by Progenesis QI (version 2.1, Water Corporation). Background removal was performed by removing signals with a higher average intensity in the method blanks as compared to their corresponding reference materials. Peak lists from biospecimens were searched against the in-house library of environmental compound reference standards in Progenesis QI to identify environmental compounds in each matrix. Reference standard compounds were matched to experimental peaks by exact mass (MS), fragmentation pattern (MS/MS), and retention time (RT). An MS match was defined as < 3 ppm, an MS/MS match was defined as a similarity score > 30, and an RT match was defined as within ± 0.5 minutes of the reference standard’s elution time. An ontology system was used to denote the evidence basis for assigning compounds to peaks. This ontology system was comprised of three levels: OL1, OL2a, and OL2b. An OL1 match is defined as a match by MS, MS/MS, and RT. An OL2a match is defined as a match by MS and RT. An OL2b match is defined by a match by MS and MS/MS. MetaboAnalyst 5.0 was used to determine significantly altered pathways between vegan and omnivore samples.
Pathway analysis revealed perturbations in multiple microbiome-associated pathways including tryptophan, tyrosine, and butanoate metabolism. Both aqueous and lyophilized fractions showed highly similar results. Multiple environmental classes could be identified at the OL1 or OL2a level and included tobacco-related metabolites, parabens, phthalates, pesticides, cannabinoids, and microbiome-metabolites.
Cloud resource ADAP-KDB for compound identification and annotation
Xiuxia Du – North Carolina HHEAR Untargeted Analysis Laboratory
Informatics capabilities have been developed for identification and annotation of signals from untargeted LC-MS/MS experiments. These capabilities have been incorporated into the online resource ADAP-KDB at https://www.adap.cloud, including the following: (1) Automated matching of experimental signals against the Sumner-Lab in-house physical standards reference library, HHEAR common core, HHEAR multi-class panel compounds, and public compound libraries – the latter include HMDB, EPA ToxCast, LipidBlast, and DrugBank. (2) Automated assignment of ontology levels that provide evidence for compound identifications and annotations as defined in Table 1. (3) Data visualization to allow analytical chemists to visually examine match quality between query MS/MS spectra against library MS/MS spectra. (4) Using a user-friendly format to export the library matching and ontology assignment results from ADAP-KDB. This export format contains color-coded sections for experimental signals, library matching results with ontology levels, and library compound information. This organization of the compound identification and annotation results makes it easy for analytical chemists and biologists to review the results.
Table 1: Definition of the ontology levels to convey evidence of compound identification and annotation.
|OL_1||experimental signal and in-house library compound have similar exact masses, retention times, and MS/MS spectra within predefined tolerances|
|OL_2a||experimental signal and in-house library compound have similar exact masses and retention times|
|OL_2b||experimental signal and in-house library compound have similar exact masses and MS/MS spectra|
|PD_a||experimental signal and public library compound have similar exact masses and MS/MS spectra|
|PD_b||experimental signal and predicted compound have similar exact masses and MS/MS spectra|
|PD_c||experimental signal and public compound have similar exact masses and isotopic distributions|
|PD_d||experimental signal and public library compound have similar exact masses only|
Building an in-house dietary exposome physical standard library (DEPSL) for expanding the annotations and identifications on the NC HHEAR Lab Hub untargeted platform
Yuan-Yuan Li, Blake Rushing, Xiuxia Du, Timothy Fennell, Colin D. Kay, Susan Sumner – North Carolina HHEAR Untargeted Analysis Laboratory
A systematic literature review was conducted to select compounds that are most relevant to a plant-origin diet and included in the construction of the Dietary Exposome Standards library. Reference standards were purchased and used to build a targeted UPLC-MS(n) (SCIEX QTRAP 6500+ scheduled MRM) assay to screen over 5,000 human biospecimens (e.g., serum, plasma, urine) following 11 controlled nutrition intervention studies (e.g., placebo and controlled feeding studies) to confirm the existence of these metabolites in human biospecimens following food consumption. Compounds that were quantified in biospecimens included phytoestrogens, aromatic ketones, benzoic acids, elegiac acids, flavonoids, caffeoylquinic acids, catecholamines, coumarins, hippuric acid, hydroxytoluenes, phenylamines, stilbenes, urolithins, valerolactons, and xanthonoids. The identified compounds were then analyzed using a UPLC-Q-Exactive HFx-MS untargeted metabolomics platform to aid in the identification of unknown signals derived from the diet. Chromatographic and HRMS data were acquired on a Vanquish UHPLC system coupled to a Q ExactiveTM HF-X Hybrid Quadrupole-Orbitrap Mass Spectrometer (Thermo Fisher) using conditions according to published untargeted metabolomics methods. Progenesis QI (version 2.1, Waters Corporation) was used for peak picking, data extraction (RT, MS, and MS/MS), and construction of searchable library files. Next urine and plasma reference materials were received from the Child Health Exposure Analysis Resource (CHEAR) consortium and extracted using the following methods. Untargeted metabolomics data was acquired using the instrument and method parameters described above. Peaks were matched to compounds in the Dietary Exposome Library by retention time (RT), exact mass (MS), and/or MS/MS fragmentation pattern. The majority of compounds (124 of 167) included in Library were detected in urine and/or plasma by the HRMS untargeted platform. Urine samples contained more detectable metabolites compared to the plasma samples.