Biology subjects

Warth, B.

Publications and source records attributed to Warth, B..

8 recordsLinked to original sources

bioRxiv2023

Insights into the early-life chemical exposome of Nigerian infants and potential correlations with the developing gut microbiome

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 were elevated when 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. Highlights- Suspect screening of exposure biomarkers in human breast milk and infant stool. - 542 features in breast milk and 864 in stool were identified or annotated. - Consumption of complementary foods influenced the chemical exposure of infants. - Correlations between xenobiotics in both biological matrices evaluated. - Dietary exposure correlated to the stool microbiome composition. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/566030v2_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@61ad1aorg.highwire.dtl.DTLVardef@ab99a5org.highwire.dtl.DTLVardef@1f44c17org.highwire.dtl.DTLVardef@1af8857_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2023

Tailored mass spectral data exploration using the specXplore interactive dashboard

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-SNE 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 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 in mass spectral data exploration efforts and assist users in the generation of structural hypotheses for compounds of interest. Technical TermsO_LIA network is a collection of connected features. In our case, a network consists of MS/MS spectral features connected provided their spectral similarity is high. Networks are represented using node-link-diagrams. C_LIO_LINode-link diagram -a term commonly used to refer to the graphical representation of a network via nodes and links (i.e. edges). In this paper, we use node-link diagram and network-view interchangeably. C_LIO_LIA node is a feature in a network that can be connected to other features via edges. An alternative term for node is vertex. C_LIO_LIAn edge is a connection between two nodes. Other terms for edges are links or vertices. C_LIO_LINetwork layout refers to the spatial arrangement of nodes and edges on an usually two dimensional plotting surface. Network layout is also sometimes referred to as embedding. This term is avoided in this paper to avoid confusion with embedding in the machine learning sense. C_LIO_LIGiven a network G(V, E), where V denotes its nodes and E its (weighted) edges, we define its topology as the relationships between individual (groups of) nodes and edges or the network as a whole, irrespective of the networks layout. C_LIO_LIMolecular Networking (MN) is an exploratory data analysis technique merging spectral similarity-based topological clustering and visualization as node-link diagrams. C_LIO_LIThe plain English words group/grouping are wherever appropriate to avoid jargon terms such as clustering (as in k-medoid or k-means clustering), embedding (as in projection of groups of features into a close-by lower dimensional space), or molecular families. The latter are groups of spectral data features clustered and visualized as network-views via traditional MN or feature based molecular networking (FBMN). Molecular families, usually represent smaller, disconnected networks that are part of a larger dataset. When we refer to this disconnected nature, we use the phrasing disjoint sub-network for emphasis. C_LI

bioinformatics↗

bioRxiv2022

Homologue Series Detection and Management in LC-MS data with homologueDiscoverer

SummaryUntargeted metabolomics data analysis is highly labor intensive and can be severely frustrated by both experimental noise and redundant features. Homologous polymer series are 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 which 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. AvailabilityhomologueDiscoverer is freely available at github https://github.com/kevinmildau/homologueDiscoverer. Contactkevin.mildau@univie.ac.at, christoph.bueschl@boku.ac.at, juergen.zanghellini@univie.ac.at

bioinformatics↗

bioRxiv2022

A broad, exposome-type evaluation of xenobiotic phase II biotransformation in human biofluids by LC-MS/MS

Xenobiotics are chemicals foreign to a specific organism that humans are exposed to on a daily basis through their food, drugs and the environment. These molecules are frequently metabolized to increase polarity and subsequent excretion. During sample preparation, deconjugation of phase II metabolites is a critical step to capture the total exposure to chemicals in liquid chromatography mass spectrometry assays (LC-MS). Knowledge on deconjugation efficiencies of different enzymes and the extend of conjugation in human biofluids has primarily been investigated for single compounds or individual chemical classes. In this study, the performance of three {beta}-glucuronidase and arylsulfatase mixtures from H. pomatia, from recombinant sources (BGS), and from Escherichia coli combined with recombinant arylsulfatase (ASPC) was compared and the efficiency of phase II deconjugation was monitored in breast milk, urine and plasma. An innovative LC-MS/MS biomonitoring method encompassing more than 80 highly diverse xenobiotics (e.g., plasticizers, industrial chemicals, mycotoxins, phytoestrogens, pesticides) was utilized for the comprehensive investigation of phase II conjugation in experiments investigating levels in breast milk and urine obtained from breastfeeding women. Overall, it was confirmed that H. pomatia is the most efficient enzyme in hydrolyzing different classes of xenobiotics for future exposome-scale biomonitoring studies. The recombinant BGS formulation, however, provided better results for breast milk samples, primarily due to lower background contamination, a major issue when employing the typically applied crude H. pomatia extracts. A deeper understanding of the global xenobiotic conjugation patterns will be essential for capturing environmental and food-related exposures within the exposome framework more comprehensively. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/500202v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@4fbe48org.highwire.dtl.DTLVardef@15588edorg.highwire.dtl.DTLVardef@90b394org.highwire.dtl.DTLVardef@1fde3e5_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2020

Longitudinal assessment of mycotoxin co-exposures in exclusively breastfed infants

ABSTRACTEarly-life development of infants may be critically affected by man-made or natural contaminants including mycotoxins. However, data on the occurrence of food contaminants in breast milk is scarce and prohibits a comprehensive exposure and risk assessment for mothers and their infants.Here, we present a longitudinal exposure assessment over the first 211 days of a single newborn girl (study A) by measuring multiple mycotoxins in milk. Eighty-seven consecutive breast milk samples were obtained from the newborn’s mother living in Austria and following a regular mixed diet. Mycotoxins were analyzed by utilizing a highly sensitive LC-MS/MS approach covering 29 mycotoxins and key metabolites. In addition to this longitudinal study, three mothers provided breast milk samples each on five consecutive days, for a preliminary comparison of inter-day and inter-individual variation in exposures (study B). Study A revealed that mycotoxin occurrence in breast milk was limited to the emerging mycotoxins alternariol monomethyl ether (AME), beauvericin (BEA), enniatins (A, A1, B, B1) and to ochratoxin A (OTA), which is regulated in commercial infant food. These mycotoxins were, if present, mostly detected at very low concentrations (<10 ng/L), except AME which exceeded this concentration on two distinct days by a factor of 3x and 5x. Overall, longitudinal results indicated chronic low-dose exposure to the detected mycotoxins. Other regulated mycotoxins including the carcinogenic aflatoxins or the estrogenic zearalenone and their biotransformation products were absent in all tested samples. Study B confirmed the results of study A, with minimal inter-day and inter-individual variation. In addition, a preliminary correlation of OTA levels occurring in breast milk and matched urine samples was found (r=0.64, p=0.034) in study B. Based on the data set obtained in study A, exposure of the infant was estimated. Exposure estimates of individual mycotoxins were on average below 1 ng/kg body weight per day.Our preliminary findings suggest that recommended maximum daily intake levels might not be exceeded in the Austrian population. However, exposure is likely to be higher in populations with lower food safety standards. In the light of co-occurrence of several emerging mycotoxins in breast milk, future studies should address low-dose mixture effects. This also includes other environmental contaminants which may be present in this bio-fluid and should involve an exposome-scale risk assessment. All these efforts must be intended to minimize exposure of mothers and infants in a window of high susceptibility.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pharmacology and toxicology↗

bioRxiv2018

Palbociclib and fulvestrant act in synergy to modulate central carbon metabolism in breast cancer cells

Palbociclib, is a selective inhibitor of cyclin-dependent kinases 4 and 6 and used as a first-line treatment for patients with estrogen receptor positive breast cancer. It has been shown that patients have improved progression-free survival when treated in combination with fulvestrant, an estrogen receptor antagonist. However, the mechanisms for this survival advantage are not known. We sought to analyze metabolic and transcriptomic changes in MCF-7 adenocarcinoma breast cancer cells following single and combined treatments to determine if selective metabolic pathways are targeted during combination therapy. Our results showed that individually, the drugs caused metabolic disruption to the same metabolic pathways, however fulvestrant additionally attenuated the pentose phosphate pathway and the production of important coenzymes. A comprehensive effect was observed when the drugs were applied together, confirming the combinatory therapy's synergism in the cell model. This study highlights the power of merging high-dimensional datasets to unravel mechanisms involved in cancer metabolism and therapy.\n\nHighlights{circ} First study employing multi-omics to investigate combined therapy on breast cancer cells\n{circ}Fulvestrant attenuates the pentose phosphate pathway and coenzyme production\n{circ}Synergism of palbociclib and fulvestrant was confirmed in vitro\n{circ}Altered key pathways have been identified\n\n\neTOC BlurbJohnson et al. applied an innovative multi-omics approach to decipher metabolic pathways affected by single versus combination dosing of palbociclib and fulvestrant in estrogen receptor positive breast cancer. Key metabolites and genes were correlated within metabolic pathways and shown to be involved in the drugs' synergism.

biochemistry↗

bioRxiv2017

Dietary xenoestrogens significantly alter cellular metabolism induced by palbociclib/letrozole combination cancer therapy

HighlightsO_LISynergism of combined palbociclib/letrozole chemotherapy was examined by global metabolomics\nC_LIO_LICombination therapy led to more pronounced effects on the MCF-7 metabolome than single agents\nC_LIO_LIDietary phyto- and mycoestrogens significantly affected the metabolic and anti-oncogenic response of the drugs\nC_LIO_LIImplications of these bio-active chemicals on therapeutic success in breast cancer patients appear plausible\nC_LI\n\nIn BriefWarth et al. used innovative global metabolomics and pathway prediction technology to describe the metabolic effects of the combined palbociclib/letrozole breast cancer therapy. Moreover, the role of dietary xenoestrogens on this treatment was examined by metabolite data, proliferation experiments, and functional assays.\n\nSummaryRecently, the palbociclib/letrozole combination therapy was granted accelerated FDA approval for the treatment of estrogen receptor (ER) positive breast cancer. Since the underlying metabolic effects of these drugs are yet unknown, we investigated their synergism at the metabolome level in MCF-7 cells. As xenoestrogens interact with the ER, we additionally aimed at deciphering the impact of the phytoestrogen genistein, and the estrogenic mycotoxin zearalenone on this treatment. A global metabolomics approach was applied to unravel metabolite and pathway modifications. The results clearly showed that the combined effects of palbociclib and letrozole on cellular metabolism were far more pronounced than that of each agent alone and potently influenced by xenoestrogens. This behavior was confirmed in proliferation experiments and functional assays. Specifically, amino acids and central carbon metabolites were attenuated while higher abundances were observed for fatty acids and most nucleic acid related metabolites. Interestingly, exposure to model xenoestrogens appeared to partially counteract these effects.

cancer biology↗

bioRxiv2017

Exposing the Exposome with Global Metabolomics andCognitive Computing

Concurrent exposure to a wide variety of xenobiotics and their combined toxic effects can play a pivotal role in health and disease, yet are largely unexplored. Investigating the totality of these exposures, i.e. the exposome, and their specific biological effects constitutes a new paradigm for environmental health but still lacks high-throughput, user-friendly technology. We demonstrate the utility of mass spectrometry-based global exposure metabolomics combined with tailored database queries and cognitive computing for comprehensive exposure assessment and the straightforward elucidation of biological effects. The METLIN Exposome database has been redesigned to help identify environmental toxicants, food contaminants and supplements, drugs, and antibiotics as well as their biotransformation products, through its expansion with over 700,000 chemical structures to now include more than 950,000 unique small molecules. More importantly, we demonstrate how the XCMS/METLIN platform now allows for the readout of the biological effect of a toxicant through metabolomic-derived pathway analysis and further, cognitive computing provides a means of assessing the role of a potential toxicant. The presented workflow addresses many of the outstanding methodological challenges current exposome research is facing and will serve to gain a deeper understanding of the impact of environmental exposures and combinatory toxic effects on human health.

epidemiology↗