Untargeted metabolomics in urine to investigate smoking exposure

Background: Although thousands of different chemicals have been identified in cigarette smoke, the characterization of urinary metabolites derived from those compounds is still not completely achieved. The aim of this work was to perform an untargeted metabolomic experiment on a pilot cross-sectional study conducted on subjects with different smoking habits. Methods: Urine samples were collected from 67 adults; including 38 non-smokers, 7 electronic cigarette smokers, and 22 traditional tobacco smokers. Samples were analyzed by liquid chromatography/time-of flight mass spectrometer operating in data dependent mode. Data were processed using the R-packages IPO and XCMS to perform feature detection, retention time correction and alignment. The ANOVA test was used to detect significant features among groups. The software BEAMS (University of Birmingham) was implemented for grouping adducts and isotopes, and to perform a first annotation. Annotation was completed by comparing fragmentation patterns with on-line databases as Metlin, and using the software MS-FINDER. Results: One hundred and seventeen features, out of 3613, were statistically different among groups. We estimated that they correspond to about 80 metabolites, of which we were able to putatively annotate about half. The identification of the mercapturic acids of acrolein, 1,3-butadiene, and crotonaldeide, chemicals known to be present in tobacco smoke, supports the validity of the proposed approach. With a lower level of confidence, we annotated the glucuronide conjugated of 3-hydroxycotinine and the sulfate conjugate of methoxyphenol; finally, with the lowest degree of confidence, several other sulfate conjugates of small molecules were annotated. Short discussion/conclusions: The proposed approach seems to be useful for the investigation of exposure to toxicants in humans

A workflow for data integration, analysis, and metabolite annotation for untargeted metabolomics

Metabolomics is the youngest of the \u201comics\u201d disciplines and it is regarded as a promising approach to understand the metabolic changes that can occur in particular conditions and to identify new biomarkers. We present here a workflow for data integration, analysis, and metabolite annotation to be applied to untargeted metabolomic experiments. Data acquired with LC-MS/MS, operating in data dependent mode, are processed using the R-packages IPO and XCMS to perform feature detection, retention time correction and alignment. The data-table obtained is elaborated and submitted to statistical analysis using the on-line software MetaboAnalyst. Multivariate analysis, in particular principal component and partial least squares discriminant analysis are performed for data visualization. Univariate analysis, in particular T-test for pairwise and ANOVA for multi-groups comparison, are performed to detect significant features among groups. The software BEAMS, developed by the University of Birmingham, is then implemented for grouping adducts and isotopes, and to perform a first annotation. Metabolite annotation is finally completed by comparing the fragmentation pattern obtained from each parent ion corresponding to a significant feature with data stored in on-line databases as Metlin, and with the help of the software MS-FINDER, which performs in-silico fragmentation. We applied this workflow to an untargeted metabolomic experiment performed on 67 urine samples obtained from adult subjects with different smoking habits: non-smokers, electronic cigarette smokers, and traditional tobacco smokers. 117 features, out of 3613, were statistically different among groups. We estimated that they correspond to about 80 metabolites. We were able to putatively annotate compound classes of most of the significant metabolites (level 3 according to the \u201cProposed minimum reporting standards\u201d; Sumner et al., 2007) and to putatively annotate some of them (level 2). Among them, the glucuronide conjugated of 3-hydroxycotinine supports the validity of the proposed approach

Investigation of urine metabolites related to tobacco smoke chemicals using an untargeted metabolomic approach

Although thousands of different chemicals have been identified in cigarette smoke, the characterization of urinary metabolites derived from those compounds is still not completely achieved. The aim of this work was to perform an untargeted metabolomic experiment on a pilot cross-sectional study conducted on subjects with different smoking habits. Urine samples were collected from 67 adults; including 38 non-smokers, 7 electronic cigarette smokers, and 22 traditional tobacco smokers. Samples were analyzed by liquid chromatography/time-of flight mass spectrometer operating in data dependent mode. Data were processed using the R-packages IPO and XCMS to perform feature detection, retention time correction and alignment. The ANOVA test was used to detect significant features among groups. The software BEAMS (University of Birmingham) was implemented for grouping adducts and isotopes, and to perform a first annotation. Annotation was completed by comparing fragmentation patterns with on-line databases as Metlin, and using the software MS-FINDER. One hundred and seventeen features, out of 3613, were statistically different among groups. We estimated that they correspond to about 80 metabolites, for which we were able to putatively annotate about half. Among these, the identification of the glucuronide conjugated of 3-hydroxycotinine supports the validity of the proposed approach. Furthermore, several metabolites, mostly as sulfate conjugates, derived from chemicals known to be present in tobacco smoke, were annotated, among which the metabolite of methoxyphenol, acrolein, 1,3-butadiene, and crotonaldeide

Un approccio metabolomico non mirato per indagare l'esposizione a sostanze tossiche nel fumo di sigaretta

Introduzione: Nel fumo di sigaretta siano state identificate migliaia di diverse sostanze chimiche pericolose; ci\uf2 nonostante la caratterizzazione dei metaboliti urinari di queste sostanze a seguito di esposizione nell'uomo \ue8 stata effettuata sono parzialmente. Obiettivo: Lo studio si propone di applicare un approccio metabolomico non mirato all'analisi di campioni di urina di soggetti con diversa abitudine al fumo, allo scopo di identificare i metaboliti derivanti da sostanze tossiche associati. Metodi: Sono stati raccolti campioni estemporanei di urina da 67 soggetti suddivisi in tre gruppi sulla base della loro abitudine al fumo: 38 soggetti erano non fumatori, 7 erano fumatori di sigaretta elettronica e 22 erano fumatori di tabacco. I campioni sono stati analizzati utilizzando la cromatografia liquida accoppiata ad uno spettrometro di massa con tempo di volo, raccogliendo i segnali degli ioni negativi. I dati sono stati processati utilizzando i pacchetti R IPA e MXCMS per correggere i tempi di ritenzione ed effettuare l'allineamento tra i cromatogrammi. Il test ANOVA \ue8 stato utilizzato per identificare gli elementi caratteristici che distinguono tra loro i gruppi. Il software BEAMS, sviluppato dall'universit\ue0 di Birmingham, \ue8 stato applicato per raggruppare gli addotti e gli isotopi riferiti ad una stessa sostanza ed effettuare una prima annotazione dei picchi. L'annotazione \ue8 stata completata confrontando gli spettri di frammentazione ottenuti da standard puri e con il database Metlin, usando il software MS-FINDER Risultati: Nei cromatogrammi ottenuti sono stati identificati complessivamente 3613 segnali, di cui 117 sono risultati diversi nei gruppi studiati. Questi segnali sono stati attribuiti a circa 80 diversi metaboliti, dei quali siamo riusciti ad annotarne putativamente circa la met\ue0. L\u2019identificazione, con un grado di confidenza pari a 1, degli acidi mercapturici dell\u2019acroleina, del 1,3-butadiene, e della crotonaldeide, sostanze risaputamene presenti nel fumo di tabacco, supportano la validit\ue0 dell\u2019approccio adottato (il grado di confidenza 1 si attribuisce alle molecole identificate con certezza per confronto con lo standard puro). Con un grado di confidenza minore (pari a 2) sono state identificati: il coniugato glucuronide della 3-idrossicotinina e il coniugato solfato del metossifenolo. Infine, con un grado di confidenza 3, sono state identificate numerose altre piccole molecole, escrete come coniugati solfati. Conclusione: L\u2019approccio proposto sembra utile per indagare l\u2019esposizione a miscele di sostanze tossiche nell\u2019uomo. Dato che l\u2019esposizione a miscele di sostanze chimiche, piuttosto che a singoli composti, \ue8 una caratteristica peculiare di molti ambienti di lavoro, si reputa che questo approccio apra interessanti prospettive per la medicina del lavoro

State of nature 2019

State of Nature 2019 presents an overview of how the country’s wildlife is faring, looking back over nearly 50 years of monitoring to see how nature has changed in the UK, its Crown Dependencies and Overseas Territories. As well as this long-term view, we focus on what has happened in the last decade, and so whether things are getting better or worse for nature. In addition, we have assessed the pressures that are acting on nature, and the responses being made, collectively, to counter these pressures

Current practices in lc-ms untargeted metabolomics: a scoping review on the use of pooled quality control samples

Untargeted metabolomics is an analytical approach with numerous applications serving as an effective metabolic phenotyping platform to characterize small molecules within a biological system. Data quality can be challenging to evaluate and demonstrate in metabolomics experiments. This has driven the use of pooled quality control (QC) samples for monitoring and, if necessary, correcting for analytical variance introduced during sample preparation and data acquisition stages. Described herein is a scoping literature review detailing the use of pooled QC samples in published untargeted liquid chromatography-mass spectrometry (LC-MS) based metabolomics studies. A literature query was performed, the list of papers was filtered, and suitable articles were randomly sampled. In total, 109 papers were each reviewed by at least five reviewers, answering predefined questions surrounding the use of pooled quality control samples. The results of the review indicate that use of pooled QC samples has been relatively widely adopted by the metabolomics community and that it is used at a similar frequency across biological taxa and sample types in both small- and large-scale studies. However, while many studies generated and analyzed pooled QC samples, relatively few reported the use of pooled QC samples to improve data quality. This demonstrates a clear opportunity for the field to more frequently utilize pooled QC samples for quality reporting, feature filtering, analytical drift correction, and metabolite annotation. Additionally, our survey approach enabled us to assess the ambiguity in the reporting of the methods used to describe the generation and use of pooled QC samples. This analysis indicates that many details of the QC framework are missing or unclear, limiting the reader's ability to determine which QC steps have been taken. Collectively, these results capture the current state of pooled QC sample usage and highlight existing strengths and deficiencies as they are applied in untargeted LC-MS metabolomics

Phase Behavior of Aqueous Na-K-Mg-Ca-CI-NO3 Mixtures: Isopiestic Measurements and Thermodynamic Modeling

A comprehensive model has been established for calculating thermodynamic properties of multicomponent aqueous systems containing the Na{sup +}, K{sup +}, Mg{sup 2+}, Ca{sup 2+}, Cl{sup -}, and NO{sub 3}{sup -} ions. The thermodynamic framework is based on a previously developed model for mixed-solvent electrolyte solutions. The framework has been designed to reproduce the properties of salt solutions at temperatures ranging from the freezing point to 300 C and concentrations ranging from infinite dilution to the fused salt limit. The model has been parameterized using a combination of an extensive literature database and new isopiestic measurements for thirteen salt mixtures at 140 C. The measurements have been performed using Oak Ridge National Laboratory's (ORNL) previously designed gravimetric isopiestic apparatus, which makes it possible to detect solid phase precipitation. Water activities are reported for mixtures with a fixed ratio of salts as a function of the total apparent salt mole fraction. The isopiestic measurements reported here simultaneously reflect two fundamental properties of the system, i.e., the activity of water as a function of solution concentration and the occurrence of solid-liquid transitions. The thermodynamic model accurately reproduces the new isopiestic data as well as literature data for binary, ternary and higher-order subsystems. Because of its high accuracy in calculating vapor-liquid and solid-liquid equilibria, the model is suitable for studying deliquescence behavior of multicomponent salt systems