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In this chapter, we describe a multi-purpose, reversed-phase liquid chromatography-high-resolution mass spectrometry (LC-HRMS) workflow for acquiring high-quality, non-targeted exposomics data utilizing data-dependent acquisition (DDA) combined with the use of toxicant inclusion lists for semi-targeted analysis. In addition, we describe expected retention times for >160 highly diverse xenobiotics in human plasma and serum samples. The method described is intended to serve as a generic LC-HRMS exposomics workflow for research and educational purposes. Moreover, it may be employed as a primer, allowing for further adaptations according to specialized research needs, e.g., by including reference and/or internal standards, by expanding to data-independent acquisition (DIA), or by modifying the list of compounds prioritized in fragmentation experiments (MS 2 )., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Mycotoxins are fungal toxins that may trigger adverse health effects in pregnant women and their unborn children. Yet, data is scarce on the dynamic exposure patterns of mycotoxins in pregnant women, especially in the United States. This study assessed mycotoxin exposure profiles in women (n = 50) from the Yale Pregnancy Outcome Prediction Study (YPOPS) cohort at four distinct time points. Multi-analyte human biomonitoring assays based on liquid chromatography tandem mass spectrometry (LC-MS/MS), were developed for human serum and plasma matrices. The serum method was applied, together with an established urine method, to quantify mycotoxin levels in longitudinally collected matched serum (n = 200) and spot urine (n = 200) samples throughout pregnancy. The serum samples were mostly contaminated by the potential carcinogen ochratoxin A (detection rate: 46 %; median: 0.09 ng/mL), the hepato- and nephrotoxic citrinin (detection rate: 32 %; median: 0.02 ng/mL) and two enniatins (EnnB; detection rate: 97 %; median: 0.01 ng/mL and EnnB 1 ; detection rate: 12 %; median: 0.003 ng/mL) which may act as immunotoxins. The most prevalent mycotoxins quantified in urine included deoxynivalenol (detection rate: 99 %; median: 23 ng/mL), alternariol monomethyl ether (detection rate: 69 %; median: 0.04 ng/mL), and zearalenone (detection rate: 63 %; median: 0.16 ng/mL). Seven other biomarkers of exposure including the highly estrogenic α-zearalenol and genotoxic Alternaria toxins, were also determined. Carcinogenic aflatoxins were not detected in any of the samples. Exposure assessment was based on the urinary data and performed by calculating probable daily intakes and comparing the human biomonitoring guidance value (HBM-GV) for deoxynivalenol. The results showed that the individuals exceeded the tolerable daily intake for deoxynivalenol and zearalenone on average at 28 % and 2 % over the different time points. Using the HBM-GV approach, the average exceedances for deoxynivalenol increased to 48 % indicating high exposure. For all the samples in which ochratoxin A was quantified, the estimated margin of exposure for neoplastic effects was below 10,000, indicating possible health concerns. Overall, this study showed that pregnant women were exposed to several regulated and emerging mycotoxins and that exposome-scale assessment should be a future priority in susceptible populations to better characterize xenobiotic exposure., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background and Objectives: Viral respiratory infections significantly affect young children, particularly extremely premature infants, resulting in high hospitalization rates and increased health-care burdens. Nasal epithelial cells, the primary defense against respiratory infections, are vital for understanding nasal immune responses and serve as a promising target for uncovering underlying molecular and cellular mechanisms., Methods: Using a trans-well pseudostratified nasal epithelial cell system, we examined age-dependent developmental differences and antiviral responses to influenza A and respiratory syncytial virus through systems biology approaches., Results: Our studies revealed differences in innate-receptor repertoires, distinct developmental pathways, and differentially connected antiviral network circuits between neonatal and adult nasal epithelial cells. Consensus network analysis identified unique and shared cellular-viral networks, emphasizing highly relevant virus-specific pathways, independent of viral replication kinetics., Conclusion: This research highlights the importance of nasal epithelial cells in innate antiviral immune responses and offers crucial insights that allow for a deeper understanding of age-related differences in nasal epithelial cell immunity following respiratory virus infections., (© 2024 The Author(s). Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.)

Natural toxins produced by Alternaria fungi include the mycotoxins alternariol, tenuazonic acid and altertoxins I and II. Several of these toxins have shown high toxicity even at low levels including genotoxic, mutagenic, and estrogenic effects. However, the metabolic effects of toxin exposure from Alternaria are understudied, especially in the liver as a key target. To gain insight into the impact of Alternaria toxin exposure on the liver metabolome, rats (n = 21) were exposed to either (1) a complex culture extract with defined toxin profiles from Alternaria alternata (50 mg/kg body weight), (2) the isolated, highly genotoxic altertoxin-II (ATX-II) (0.7 mg/kg of body weight) or (3) a solvent control. The complex mixture contained a spectrum of Alternaria toxins including a controlled dose of ATX-II, matching the concentration of the isolated ATX-II. Liver samples were collected after 24 h and analyzed via liquid chromatography-high-resolution mass spectrometry (LC-HRMS). Authentic reference standards (> 100) were used to identify endogenous metabolites and exogenous compounds from the administered exposures in tandem with SWATH-acquired MS/MS data which was used for non-targeted analysis/screening. Screening for metabolites produced by Alternaria revealed several compounds solely isolated in the liver of rats exposed to the complex culture, confirming results from a previously performed targeted biomonitoring study. This included the altersetin and altercrasin A that were tentatively identified. An untargeted metabolomics analysis found upregulation of acylcarnitines in rats receiving the complex Alternaria extract as well as downregulation of riboflavin in rats exposed to both ATX-II and the complex mixture. Taken together, this work provides a mechanistic view of Alternari toxin exposure and new suspect screening insights into hardly characterized Alternaria toxins., (© 2024. The Author(s).)

Traditionally, chemical exposure has been assessed by low-resolution mass spectrometry via targeted approaches due to the typically extremely low concentration of such compounds in biological samples. Nevertheless, untargeted approaches are now becoming a promising tool for a broader investigation of the exposome, covering additional compounds, their biotransformation products, and possible metabolic alterations (metabolomics). However, despite broad compound coverage, untargeted metabolomics still underperforms in ultratrace biomonitoring analysis. To overcome these analytical limitations, we present the development of the first combined targeted/untargeted LC-MS method, merging MRM-HR and SWATH experiments in one analytical run, making use of Zeno technology for improved sensitivity. Multiple reaction monitoring transitions were optimized for 135 highly diverse toxicants including mycotoxins, plasticizers, PFAS, personal care products ingredients, and industrial side products as well as potentially beneficial xenobiotics such as phytohormones. As a proof of concept, standard reference materials of human plasma (SRM 1950) and serum (SRM 1958) were analyzed with both Zeno MRM-HR + SWATH and SWATH-only methodologies. Results demonstrated a significant increase in sensitivity represented by the detection of lower concentration levels in spiked SRM materials (mean value: 2.2 and 3 times lower concentrations for SRMs 1950 and 1958, respectively). Overall, the detection frequency was increased by 68% (19 to 32 positive detections) in the MRM-HR + SWATH mode compared to the SWATH-only. This work presents a promising avenue for addressing the outstanding key challenge in the small-molecule omics field: finding a balance between high sensitivity and broad chemical coverage. It was demonstrated for exposomic applications but might be transferred to lipidomics and metabolomics workflows.

Humans are exposed to a cocktail of food-related and environmental contaminants, potentially contributing to the etiology of chronic diseases. Better characterizing the "exposome" is a challenging task and requires broad human biomonitoring (HBM). Veterinary drugs (VDs)/antibiotics, widely used and regulated in food and animal production, however, are typically not yet included in exposomics workflows. Therefore, in this work, a previously established multianalyte liquid chromatography-tandem mass spectrometry (LC-MS/MS) method covering >80 diverse xenobiotics was expanded by >40 VDs/antibiotics and pesticides. It was investigated if the generic workflow allowed for the successful integration of a high number of new analytes in a proof-of-principle study. The expanded method was successfully in-house validated and specificity, matrix effects, linearity, intra- and inter-day precision, accuracy, limits of quantification, and detection were evaluated. The optimized method demonstrated satisfactory recovery (81-120%) for most of the added analytes with acceptable RSDs (<20%) at three spiking levels. The majority of VDs/antibiotics and pesticides (69%) showed matrix effects within a range of 50-140%. Moreover, sensitivity was excellent with median LODs and LOQs of 0.10 ng/mL and 0.31 ng/mL, respectively. In total, the expanded method can be used to detect and quantify more than 120 highly diverse analytes in a single analytical run. To the best of the authors' knowledge, this work represents the first targeted biomonitoring method integrating VDs with various other classes of pollutants including plasticizers, PFAS, bisphenols, mycotoxins, and personal care products. It demonstrates the potential to expand targeted multianalyte methods towards additional groups of potentially toxic chemicals., (© 2024. The Author(s).)

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Early-life exposure to natural and synthetic chemicals can impact acute and chronic health conditions. Here, a suspect screening workflow anchored on high-resolution mass spectrometry was applied to elucidate xenobiotics in breast milk and matching stool samples collected from Nigerian mother-infant pairs (n = 11) at three time points. Potential correlations between xenobiotic exposure and the developing gut microbiome, as determined by 16S rRNA gene amplicon sequencing, were subsequently explored. Overall, 12,192 and 16,461 features were acquired in the breast milk and stool samples, respectively. Following quality control and suspect screening, 562 and 864 features remained, respectively, with 149 of these features present in both matrices. Taking advantage of 242 authentic reference standards measured for confirmatory purposes of food bio-actives and toxicants, 34 features in breast milk and 68 features in stool were identified and semi-quantified. Moreover, 51 and 78 features were annotated with spectral library matching, as well as 416 and 652 by in silico fragmentation tools in breast milk and stool, respectively. The analytical workflow proved its versatility to simultaneously determine a diverse panel of chemical classes including mycotoxins, endocrine-disrupting chemicals (EDCs), antibiotics, plasticizers, perfluorinated alkylated substances (PFAS), and pesticides, although it was originally optimized for polyphenols. Spearman rank correlation of the identified features revealed significant correlations between chemicals of the same classification such as polyphenols. One-way ANOVA and differential abundance analysis of the data obtained from stool samples revealed that molecules of plant-based origin elevated as complementary foods were introduced to the infants' diets. Annotated compounds in the stool, such as tricetin, positively correlated with the genus Blautia. Moreover, vulgaxanthin negatively correlated with Escherichia-Shigella. Despite the limited sample size, this exploratory study provides high-quality exposure data of matched biospecimens obtained from mother-infant pairs in sub-Saharan Africa and shows potential correlations between the chemical exposome and the gut microbiome., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Through investigating the combined impact of the environmental exposures experienced by an individual throughout their lifetime, exposome research provides opportunities to understand and mitigate negative health outcomes. While current exposome research is driven by epidemiological studies that identify associations between exposures and effects, new frameworks integrating more substantial population-level metadata, including electronic health and administrative records, will shed further light on characterizing environmental exposure risks. Molecular biology offers methods and concepts to study the biological and health impacts of exposomes in experimental and computational systems. Of particular importance is the growing use of omics readouts in epidemiological and clinical studies. This paper calls for the adoption of mechanistic molecular biology approaches in exposome research as an essential step in understanding the genotype and exposure interactions underlying human phenotypes. A series of recommendations are presented to make the necessary and appropriate steps to move from exposure association to causation, with a huge potential to inform precision medicine and population health. This includes establishing hypothesis-driven laboratory testing within the exposome field, supported by appropriate methods to read across from model systems research to human.

Untargeted metabolomics promises comprehensive characterization of small molecules in biological samples. However, the field is hampered by low annotation rates and abstract spectral data. Despite recent advances in computational metabolomics, manual annotations and manual confirmation of in-silico annotations remain important in the field. Here, exploratory data analysis methods for mass spectral data provide overviews, prioritization, and structural hypothesis starting points to researchers facing large quantities of spectral data. In this research, we propose a fluid means of dealing with mass spectral data using specXplore, an interactive Python dashboard providing interactive and complementary visualizations facilitating mass spectral similarity matrix exploration. Specifically, specXplore provides a two-dimensional t-distributed stochastic neighbor embedding embedding as a jumping board for local connectivity exploration using complementary interactive visualizations in the form of partial network drawings, similarity heatmaps, and fragmentation overview maps. SpecXplore makes use of state-of-the-art ms2deepscore pairwise spectral similarities as a quantitative backbone while allowing fast changes of threshold and connectivity limitation settings, providing flexibility in adjusting settings to suit the localized node environment being explored. We believe that specXplore can become an integral part of mass spectral data exploration efforts and assist users in the generation of structural hypotheses for compounds of interest.

The gut microbiome is associated with pathological neurophysiological evolvement in extremely premature infants suffering from brain injury. The exact underlying mechanism and its associated metabolic signatures in infants are not fully understood. To decipher metabolite profiles linked to neonatal brain injury, we investigate the fecal and plasma metabolome of samples obtained from a cohort of 51 extremely premature infants at several time points, using liquid chromatography (LC)-high-resolution mass spectrometry (MS)-based untargeted metabolomics and LC-MS/MS-based targeted analysis for investigating bile acids and amidated bile acid conjugates. The data are integrated with 16S rRNA gene amplicon gut microbiome profiles as well as patient cytokine, growth factor, and T cell profiles. We find an early onset of differentiation in neuroactive metabolites between infants with and without brain injury. We detect several bacterially derived bile acid amino acid conjugates in plasma and feces. These results provide insights into the early-life metabolome of extremely premature infants., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Exposure to polyphenols is relevant throughout critical windows of infant development, including the breastfeeding phase. However, the quantitative assessment of polyphenols in human breast milk has received limited attention so far, though polyphenols may positively influence infant health. Therefore, a targeted LC-MS/MS assay was developed to investigate 86 analytes representing different polyphenol classes in human breast milk. The sample preparation consisted of liquid extraction, salting out, freeze-out, and a dilution step. Overall, nearly 70% of the chemically diverse polyphenols fulfilled all strict validation criteria for full quantitative assessment. The remaining analytes did not fulfill all criteria at every concentration level, but can still provide useful semi-quantitative insights into nutritional and biomedical research questions. The limits of detection for all analyzed polyphenols were in the range of 0.0041-87 ng*mL -1 , with a median of 0.17 ng*mL -1 . Moreover, the mean recovery was determined to be 82% and the mean signal suppression and enhancement effect was 117%. The developed assay was applied in a proof-of-principle study to investigate polyphenols in breast milk samples provided by twelve Nigerian mothers at three distinct time points post-delivery. In total, 50 polyphenol analytes were detected with almost half being phenolic acids. Phase II metabolites, including genistein-7-β-D-glucuronide, genistein-7-sulfate, and daidzein-7-β-D-glucuronide, were also detected in several samples. In conclusion, the developed method was demonstrated to be fit-for-purpose to simultaneously (semi-) quantify a wide variety of polyphenols in breast milk. It also demonstrated that various polyphenols including their biotransformation products were present in breast milk and therefore likely transferred to infants where they might impact microbiome development and infant health., (© 2024. The Author(s).)

Mycotoxins are toxic chemicals that adversely affect human health. Here, we assessed the influence of mycotoxin exposure on the longitudinal development of early life intestinal microbiota of Nigerian neonates and infants (NIs). Human biomonitoring assays based on liquid chromatography tandem mass spectrometry were applied to quantify mycotoxins in breast milk ( n = 68) consumed by the NIs, their stool ( n = 82), and urine samples ( n = 15), which were collected longitudinally from month 1-18 postdelivery. Microbial community composition was characterized by 16S rRNA gene amplicon sequencing of stool samples and was correlated to mycotoxin exposure patterns. Fumonisin B 1 (FB 1 ), FB 2 , and alternariol monomethyl ether (AME) were frequently quantified in stool samples between months 6 and 18. Aflatoxin M 1 (AFM 1 ), AME, and citrinin were quantified in breast milk samples at low concentrations. AFM 1 , FB 1 , and ochratoxin A were quantified in urine samples at relatively high concentrations. Klebsiella and Escherichia / Shigella were dominant in very early life stool samples (month 1), whereas Bifidobacterium was dominant between months 3 and 6. The total mycotoxin levels in stool were significantly associated with NIs' gut microbiome composition (PERMANOVA, p < 0.05). However, no significant correlation was observed between specific microbiota and the detection of certain mycotoxins. Albeit a small cohort, this study demonstrates that mycotoxins may influence early life gut microbiome composition.

While there are lighthouse examples of microbiome research in sub-Saharan Africa (SSA), a significant proportion of local researchers face several challenges. Here, we highlight prevailing issues limiting microbiome research in SSA and suggest potential technological, societal, and research-based solutions. We emphasize the need for considerable investment in infrastructures, training, and appropriate funding to democratize modern technologies with a view to providing useful data to improve human health., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Exposure to mycotoxins through the dietary route occurs on a daily basis while their deleterious effects are exhibited in the form of ailments, such as inflammation, cancer, and hormonal imbalance. The negative impact of mycotoxins can be attributed to their interaction with various biomolecules and their interference in metabolic pathways. The activity of biomolecules, such as enzymes/receptors, which engage the intricate mechanism of endogenous metabolism, is more susceptible to disruption by metabolites of high toxicity, which gives rise to adverse health effects. Metabolomics is a useful analytical approach that can assist in unraveling such information. It can simultaneously and comprehensively analyze a large number of endogenous and exogenous molecules present in biofluids and can, thus, reveal biologically relevant perturbations following mycotoxin exposure. Information provided by genome, transcriptome and proteome analyses, which have been utilized for the elucidation of biological mechanisms so far, are further complemented by the addition of metabolomics in the available bioanalytics toolbox. Metabolomics can offer insight into complex biological processes and their respective response to several (co-)exposures. This review focuses on the most extensively studied mycotoxins reported in literature and their respective impact on the metabolome upon exposure.

This study assessed the levels of environment and food-related exposures in urine of Austrian school children aged six to ten (n = 85) focusing on mycotoxins, phytoestrogens, and food processing by-products using two multi-analyte LC-MS/MS methods. Out of the 55 biomarkers of exposure reported in this study, 22 were quantified in the first void urine samples. Mycotoxins frequently quantified included zearalenone (detection rate 100%; median 0.11 ng/mL), deoxynivalenol (99%; 15 ng/mL), alternariol monomethyl ether (75%; 0.04 ng/mL), and ochratoxin A (19%; 0.03 ng/mL). Several phytoestrogens, including genistein, daidzein, and its metabolite equol, were detected in all samples at median concentrations of 22 ng/mL, 43 ng/mL, and 14 ng/mL, respectively. The food processing by-product 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), was detected in 4% of the samples (median 0.016 ng/mL). None of the investigated samples contained the tested phytotoxins that were rarely considered for human biomonitoring previously (pyrrolizidine alkaloids, tropane alkaloids, aristolochic acids). When relating estimated exposure to current health-based guidance values, 22% of the children exceeded the tolerable daily intake for deoxynivalenol, and the estimated MOE for OTA indicates possible health risks for some children. The results clearly demonstrate frequent low-level (co-)exposure and warrant further exposome-scale exposure assessments, especially in susceptible sub-populations and longitudinal settings., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Benedikt Warth reports financial support was provided by Austrian Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology. Benedikt Warth reports financial support was provided by Austrian Science Fund (FWF)., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The chemical exposome consists of environmental exposures experienced throughout a lifetime but to date analytical approaches to investigate the plethora of low-abundance chemicals remain very limited. Liquid chromatography high-resolution mass spectrometry (HRMS) is commonly applied in untargeted exposome-wide analyses of xenobiotics in biological samples; however, human biomonitoring approaches usually utilize targeted low-resolution triple quadrupole (QQQ) mass spectrometry tailored to a small number of chemicals. HRMS can cover a broader chemical space but the detection of molecules from low-level exposure amidst a background of highly-abundant endogenous molecules has proven to be difficult. In this study, a triple quadrupole (QQQ) and a high-resolution mass spectrometer (HRMS) with identical chromatography were utilized to determine the limits of quantitation (LOQ) of >100 xenobiotics and estrogenic hormones in pure solvent and human urine. Both instrumental platforms are currently applied in exposure assessment studies and were operated in their most frequently used acquisition mode (full scan for HRMS and multiple reaction monitoring for QQQ) to mimic typical applications. For HRMS analyses, the median LOQ was 0.9 and 1.2 ng/mL in solvent and urine, respectively, while for low-resolution QQQ measurements, the median LOQ was 0.1 and 0.2 ng/mL in solvent and urine, respectively. To evaluate the calculated LOQs in complex biological samples, spot urine samples from 24 Nigerian female volunteers were investigated. The higher LOQ values for HRMS resulted in less quantified low-abundance analytes and decreased the number of compounds detected below the LOQ. Even at chronic low-dose exposure, such compounds might be relevant for human health because of high individual toxicity or potential mixture effects. Nevertheless, HRMS enabled the additional screening for exposure to unexpected/unknown analytes, including emerging compounds and biotransformation products. Therefore, a synergy between high- and low-resolution mass spectrometry may currently be the best option to elucidate and quantify xenobiotics in comprehensive exposome-wide association studies (ExWAS)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Taurine-respiring gut bacteria produce H 2 S with ambivalent impact on host health. We report the isolation and ecophysiological characterization of a taurine-respiring mouse gut bacterium. Taurinivorans muris strain LT0009 represents a new widespread species that differs from the human gut sulfidogen Bilophila wadsworthia in its sulfur metabolism pathways and host distribution. T. muris specializes in taurine respiration in vivo, seemingly unaffected by mouse diet and genotype, but is dependent on other bacteria for release of taurine from bile acids. Colonization of T. muris in gnotobiotic mice increased deconjugation of taurine-conjugated bile acids and transcriptional activity of a sulfur metabolism gene-encoding prophage in other commensals, and slightly decreased the abundance of Salmonella enterica, which showed reduced expression of galactonate catabolism genes. Re-analysis of metagenome data from a previous study further suggested that T. muris can contribute to protection against pathogens by the commensal mouse gut microbiota. Together, we show the realized physiological niche of a key murine gut sulfidogen and its interactions with selected gut microbiota members., (© 2023. Springer Nature Limited.)

Polyphenols, prevalent in plants and fungi, are investigated intensively in nutritional and clinical settings because of their beneficial bioactive properties. Due to their complexity, analysis with untargeted approaches is favorable, which typically use high-resolution mass spectrometry (HRMS) rather than low-resolution mass spectrometry (LRMS). Here, the advantages of HRMS were evaluated by thoroughly testing untargeted techniques and available online resources. By applying data-dependent acquisition on real-life urine samples, 27 features were annotated with spectral libraries, 88 with in silico fragmentation, and 113 by MS 1 matching with PhytoHub, an online database containing >2000 polyphenols. Moreover, other exogenous and endogenous molecules were screened to measure chemical exposure and potential metabolic effects using the Exposome-Explorer database, further annotating 144 features. Additional polyphenol-related features were explored using various non-targeted analysis techniques including MassQL for glucuronide and sulfate neutral losses, and MetaboAnalyst for statistical analysis. As HRMS typically suffers a sensitivity loss compared to state-of-the-art LRMS used in targeted workflows, the gap between the two instrumental approaches was quantified in three spiked human matrices (urine, serum, plasma) as well as real-life urine samples. Both instruments showed feasible sensitivity, with median limits of detection in the spiked samples being 10-18 ng/mL for HRMS and 4.8-5.8 ng/mL for LRMS. The results demonstrate that, despite its intrinsic limitations, HRMS can readily be used for comprehensively investigating human polyphenol exposure. In the future, this work is expected to allow for linking human health effects with exposure patterns and toxicological mixture effects with other xenobiotics.

In 85 Austrian school children aged 6-10 years, two multi-analyte LC-MS/MS methods were used to study the concentrations of 33 chemical substances in urine, including per- and polyfluorinated alkylated substances (PFAS), bisphenols, parabens, benzophenones, triclosan, polycyclic aromatic hydrocarbon metabolites, and cotinine. Each of the children was exposed to 14-21 substances simultaneously. Correlations were found between compounds of the same and of divergent substance groups supporting the strong need to consider multiple exposures and mixture effects. Eight compounds, including perfluorohexanoic acid (PFHxA), perfluorononanoic acid (PFOA), methyl paraben (n-MeP), ethyl paraben (n-EtP), propyl paraben (n-PrP), benzophenone-1 (BP-1), 2-naphthol, and 3-hydroxyphenanthrene were detected in all urine samples. In the PFAS group the medians of detectable substances ranged between <0.0005 μg/l for perfluorononanoic acid (PFNA) and 0.004 μg/l for PFHxA. For other environmental contaminants investigated, a maximum urinary level of 893 μg/l was identified for n-MeP. The highest median value was 2.5 μg/l for 2-naphthol. Daily intakes were calculated for bisphenol A (BPA), triclosan (TCS), and four parabens. These values did not exceed the tolerable or acceptable daily intakes currently in force. Based on a recently proposed TDI for BPA, daily intakes of all children exceeded this value. A cumulative risk assessment was conducted for four parabens not showing exceedances of acceptable exposures. The results demonstrate simultaneous exposure to several different chemicals, with the majority showing impact on the endocrine system being of particular concern with respect to mixture effects. Further assessments with a stronger focus on mixtures are warranted. The results also highlight the need of policy actions as foreseen in the EU Chemicals Strategy for Sustainability., (Copyright © 2023 The Authors. Published by Elsevier GmbH.. All rights reserved.)

Early human life is considered a critical window of susceptibility to external exposures. Infants are exposed to a multitude of environmental factors, collectively referred to as the exposome. The chemical exposome can be summarized as the sum of all xenobiotics that humans are exposed to throughout a lifetime. We review different exposure classes and routes that impact fetal and infant metabolism and the potential toxicological role of mixture effects. We also discuss the progress in human biomonitoring and present possiblemodels for studying maternal-fetal transfer. Data gaps on prenatal and infant exposure to xenobiotic mixtures are identified and include natural biotoxins, in addition to commonly reported synthetic toxicants, to obtain a more holistic assessment of the chemical exposome. We highlight the lack of large-scale studies covering a broad range of xenobiotics. Several recommendations to advance our understanding of the early-life chemical exposome and the subsequent impact on health outcomes are proposed.

Summary: Untargeted metabolomics data analysis is highly labour intensive and can be severely frustrated by both experimental noise and redundant features. Homologous polymer series is a particular case of features that can either represent large numbers of noise features or alternatively represent features of interest with large peak redundancy. Here, we present homologueDiscoverer, an R package that allows for the targeted and untargeted detection of homologue series as well as their evaluation and management using interactive plots and simple local database functionalities., Availability and Implementation: homologueDiscoverer is freely available at GitHub https://github.com/kevinmildau/homologueDiscoverer., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press.)

The totality of environmental exposures and lifestyle factors, commonly referred to as the exposome, is poorly understood. Measuring the myriad of chemicals that humans are exposed to is immensely challenging, and identifying disrupted metabolic pathways is even more complex. Here, we present a novel technological approach for the comprehensive, rapid, and integrated analysis of the endogenous human metabolome and the chemical exposome. By combining reverse-phase and hydrophilic interaction liquid chromatography (HILIC) and fast polarity-switching, molecules with highly diverse chemical structures can be analyzed in 15 min with a single analytical run as both column's effluents are combined before analysis. Standard reference materials and authentic standards were evaluated to critically benchmark performance. Highly sensitive median limits of detection (LODs) with 0.04 μM for >140 quantitatively assessed endogenous metabolites and 0.08 ng/mL for the >100 model xenobiotics and human estrogens in solvent were obtained. In matrix, the median LOD values were higher with 0.7 ng/mL (urine) and 0.5 ng/mL (plasma) for exogenous chemicals. To prove the dual-column approach's applicability, real-life urine samples from sub-Saharan Africa (high-exposure scenario) and Europe (low-exposure scenario) were assessed in a targeted and nontargeted manner. Our liquid chromatography high-resolution mass spectrometry (LC-HRMS) approach demonstrates the feasibility of quantitatively and simultaneously assessing the endogenous metabolome and the chemical exposome for the high-throughput measurement of environmental drivers of diseases., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

The gut microbiome of neonates, infants, and toddlers (NITs) is very dynamic, and only begins to stabilize towards the third year of life. Within this period, exposure to xenobiotics may perturb the gut environment, thereby driving or contributing to microbial dysbiosis, which may negatively impact health into adulthood. Despite exposure of NITs globally, but especially in Africa, to copious amounts and types of xenobiotics - such as mycotoxins, pesticide residues, and heavy metals - little is known about their influence on the early-life microbiome or their effects on acute or long-term health. Within the African context, the influence of fermented foods, herbal mixtures, and the delivery environment on the early-life microbiome are often neglected, despite being potentially important factors that influence the microbiome. Consequently, data on in-depth understanding of the microbiome-exposome interactions is lacking in African cohorts. Collecting and evaluating such data is important because exposome-induced gut dysbiosis could potentially favor disease progression., Competing Interests: Declaration of interests There are no interests to declare., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Mycotoxins produced by Alternaria spp. act genotoxic in cell-based studies, but data on their toxicity in vivo is scarce and urgently required for risk assessment. Thus, male Sprague-Dawley rats received single doses of a complex Alternaria toxin extract (CE; 50 mg/kg bw), altertoxin II (ATX-II; 0.21 mg/kg bw) or vehicle by gavage, one of the most genotoxic metabolites in vitro and were sacrificed after 3 or 24 h, respectively. Using SDS-PAGE/Western Blot, a significant increase of histone 2a.X phosphorylation and depletion of the native protein was observed for rats that were exposed to ATX-II for 24 h. Applying RT-PCR array technology we identified genes of interest for qRT-PCR testing, which in turn confirmed an induction of Rnf8 transcription in the colon of rats treated with ATX-II for 3 h and CE for 24 h. A decrease of Cdkn1a transcription was observed in rats exposed to ATX-II for 24 h, possibly indicating tissue repair after chemical injury. In contrast to the observed response in the colon, no markers for genotoxicity were induced in the liver of treated animals. We hereby provide the first report of ATX-II as a genotoxicant in vivo . Deviating results for similar concentrations of ATX-II in a natural Alternaria toxin mixture argue for substantial mixture effects., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Aichinger, Pahlke, Puntscher, Groestlinger, Grabher, Braun, Tillmann, Plasenzotti, Del Favero, Warth, Höger and Marko.)

Infants are sensitive to negative effects caused by food contaminants such as mycotoxins. To date, analytical methods assessing mycotoxin mixture exposure in infant stool are absent. Herein, we present a novel multi-mycotoxin LC-MS/MS assay capable of detecting 30+ analytes including the regulated mycotoxin classes (aflatoxins, trichothecenes, ochratoxins, zearalenone, citrinin), emerging Alternaria and Fusarium toxins, and several key metabolites. Sample preparation consisted of a 'dilute, filter, and shoot' approach. The method was in-house validated and demonstrated that 25 analytes fulfilled all required criteria despite the high diversity of chemical structures included. Extraction recoveries for most of the analytes were in the range of 65-114% with standard deviations below 30% and limits of detection between 0.03 and 11.3 ng/g dry weight. To prove the methods' applicability, 22 human stool samples from premature Austrian infants (n = 12) and 12-month-old Nigerian infants (n = 10) were analyzed. The majority of the Nigerian samples were contaminated with alternariol monomethyl ether (8/10) and fumonisin B 1 (8/10), while fumonisin B 2 and citrinin were quantified in some samples. No mycotoxins were detected in any of the Austrian samples. The method can be used for sensitive human biomonitoring (HBM) purposes and to support exposure and, potentially, risk assessment of mycotoxins. Moreover, it allows for investigating potential associations between toxicant exposure and the infants' developing gut microbiome., (© 2021. The Author(s).)

Establishing a method for human biomonitoring (HBM) of polyphenols enables the assessment of internal concentrations of these food bio-actives and the correlation with potential health effects such as antioxidant or anti-inflammatory properties. Thus, a targeted LC-MS/MS method for quantifying up to 90 analytes, representing the main polyphenol classes including flavanones, isoflavones, stilbenes, and phenolic acids, was developed for human urine, serum, and plasma. The method was established for low sample volumes and with a cost and time efficient sample preparation protocol for high-throughput, which is critical for its application in large cohort and exposome-wide association studies. On average, the sample preparation yielded extraction efficiencies of 98% for urine, 98% for serum, and 87% for plasma. Limits of detection were between 0.11 ng mL -1 and 300 ng mL -1 for urine, 0.12 ng mL -1 and 190 ng mL -1 for serum, and 0.12 ng mL -1 and 340 ng mL -1 for plasma, excluding one analyte. In-house validation revealed that 66, 49, and 64 analytes for urine, serum, and plasma, respectively, fulfilled all stringent requirements, that are usually utilized for tailored single analyte methods, at all evaluated concentration levels. After validation, this method was applied in a proof-of-principle study that detected 39 polyphenols in urine. Changes in the concentrations of the analytes after the ingestion of a high polyphenol smoothie was examined over 24 h. The study further confirmed that the majority of polyphenols detected were phenolic acids, and phase II conjugated metabolites were more abundant than their respective non-conjugated forms., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Motivation: Chromatographic peak picking is among the first steps in data processing workflows of raw LC-HRMS datasets in untargeted metabolomics applications. Its performance is crucial for the holistic detection of all metabolic features as well as their relative quantification for statistical analysis and metabolite identification. Random noise, non-baseline separated compounds and unspecific background signals complicate this task., Results: A machine-learning-based approach entitled PeakBot was developed for detecting chromatographic peaks in LC-HRMS profile-mode data. It first detects all local signal maxima in a chromatogram, which are then extracted as super-sampled standardized areas (retention-time versus m/z). These are subsequently inspected by a custom-trained convolutional neural network that forms the basis of PeakBot's architecture. The model reports if the respective local maximum is the apex of a chromatographic peak or not as well as its peak center and bounding box. In training and independent validation datasets used for development, PeakBot achieved a high performance with respect to discriminating between chromatographic peaks and background signals (accuracy of 0.99). For training the machine-learning model a minimum of 100 reference features are needed to learn their characteristics to achieve high-quality peak-picking results for detecting such chromatographic peaks in an untargeted fashion. PeakBot is implemented in python (3.8) and uses the TensorFlow (2.5.0) package for machine-learning related tasks. It has been tested on Linux and Windows OSs., Availability and Implementation: The package is available free of charge for non-commercial use (CC BY-NC-SA). It is available at https://github.com/christophuv/PeakBot., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press.)

Exposure to synthetic and natural chemicals is a major environmental risk factor in the etiology of many chronic diseases. Investigating complex co-exposures is necessary for a holistic assessment in exposome-wide association studies. In this work, a sensitive liquid chromatography-tandem mass spectrometry approach was developed and validated. The assay enables the analysis of more than 80 highly-diverse xenobiotics in urine, serum/plasma, and breast milk; with detection limits generally in the pg-ng mL -1 range. In plasma of extremely-premature infants, 27 xenobiotics are identified; including contamination with plasticizers, perfluorinated alkylated substances and parabens. In breast milk samples collected longitudinally over the first 211 days post-partum, 29 analytes are detected, including pyrrolizidine- and tropane alkaloids which have not been identified in this matrix before. A preliminary estimation of daily toxicant intake via breast milk is conducted. In conclusion, we observe significant early-life co-exposure to multiple toxicants, and demonstrate the method's applicability for large-scale exposomics-type cohort studies., (© 2022. The Author(s).)

Exposure to food and environmental contaminants is a global environmental health issue. In this study, innovative LC-MS/MS approaches were applied to investigate mycotoxin co-exposure in mother-infant pairs (n = 23) by analyzing matched plate-ready food, breast milk and urine samples of mothers and their exclusively breastfed infants. The study revealed frequent co-occurrence of two to five mycotoxins. Regulated (e.g. aflatoxins, deoxynivalenol and ochratoxin A) and emerging mycotoxins (e.g. alternariol monomethyl ether and beauvericin) were frequently detected (3 %-89 % and 45 %-100 %), in at least one specimen. In addition, a moderate association of ochratoxin A in milk to urine of mothers (r = 0.47; p = 0.003) and infants (r = 0.52; p = 0.019) but no other significant correlations were found. Average concentration levels in food mostly did not exceed European maximum residue limits, and intake estimates demonstrated exposure below tolerable daily intake values. Infants were exposed to significantly lower toxin levels compared to their mothers, indicating the protective effect of breastfeeding. However, the transfer into milk and urine and the resulting chronic low-dose exposure warrant further monitoring. In the future, occurrence of mycotoxin-mixtures, and their combined toxicological effects need to be comprehensively considered and implemented in risk management strategies. These should aim to minimize early-life exposure in critical developmental stages., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Environmental exposure to xenoestrogens, i.e., chemicals that imitate the hormone 17β-estradiol, has the potential to influence hormone homeostasis and action. Detailed knowledge of xenobiotic biotransformation processes in cell models is key when transferring knowledge learned from in vitro models to in vivo relevance. This study elucidated the metabolism of two naturally-occurring phyto- and mycoestrogens; namely genistein and zearalenone, in an estrogen receptor positive breast cancer cell line (MCF-7) with the aid of stable isotope-assisted metabolomics and the bioinformatic tool MetExtract II. Metabolism was studied in a time course experiment after 2 h, 6 h and 24 h incubation. Twelve and six biotransformation products of zearalenone and genistein were detected, respectively, clearly demonstrating the abundant xenobiotic biotransformation capability of the cells. Zearalenone underwent extensive phase-I metabolism resulting in α-zearalenol (α-ZEL), a molecule known to possess a significantly higher estrogenicity, and several phase-II metabolites (sulfo- and glycoconjugates) of the native compound and the major phase I metabolite α-ZEL. Moreover, potential adducts of zearalenone with a vitamin and several hydroxylated metabolites were annotated. Genistein metabolism resulted in sulfation, combined sulfation and hydroxylation, acetylation, glucuronidation and unexpectedly adduct formation with pentose- and hexose sugars. Kinetics of metabolite formation and subsequent excretion into the extracellular medium revealed a time-dependent increase in most biotransformation products. The untargeted elucidation of biotransformation products formed during cell culture experiments enables an improved and more meaningful interpretation of toxicological assays and has the potential to identify unexpected or unknown metabolites., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

A multi-specimen, multi-mycotoxin approach involving ultra-sensitive LC-MS/MS analysis of breast milk, complementary food and urine was applied to examine mycotoxin co-exposure in 65 infants, aged 1-18 months, in Ogun state, Nigeria. Aflatoxin M 1 was detected in breast milk (4/22 (18%)), while six other classes of mycotoxins were quantified; including dihydrocitrinone (6/22 (27%); range: 14.0-59.7 ng/L) and sterigmatocystin (1/22 (5%); 1.2 ng/L) detected for the first time. Seven distinct classes of mycotoxins including aflatoxins (9/42 (21%); range: 1.0-16.2 µg/kg) and fumonisins (12/42 (29%); range: 7.9-194 µg/kg) contaminated complementary food. Mycotoxins covering seven distinct classes with diverse structures and modes of action were detected in 64/65 (99%) of the urine samples, demonstrating ubiquitous exposure. Two aflatoxin metabolites (AFM 1 and AFQ 1 ) and FB 1 were detected in 6/65 (9%), 44/65 (68%) and 17/65 (26%) of urine samples, respectively. Mixtures of mycotoxin classes were common, including 22/22 (100%), 14/42 (33%) and 56/65 (86%) samples having 2-6, 2-4, or 2-6 mycotoxins present, for breast milk, complementary food and urine, respectively. Aflatoxin and/or fumonisin was detected in 4/22 (18%), 12/42 (29%) and 46/65 (71%) for breast milk, complimentary foods and urine, respectively. Furthermore, the detection frequency, median concentrations and occurrence of mixtures were typically greater in urine of non-exclusively breastfed compared to exclusively breastfed infants. The study provides novel insights into mycotoxin co-exposures in early-life. Albeit a small sample set, it highlights transition to higher levels of infant mycotoxin exposure as complementary foods are introduced, providing impetus to mitigate during this critical early-life period and encourage breastfeeding., (Copyright © 2021. Published by Elsevier Ltd.)