Computational Metabolomics: A Framework for the Million Metabolome

Abstract

“Sola dosis facit venenum.” These words of Paracelsus, “the dose makes the poison”, can lead to a cavalier attitude concerning potential toxicities of the vast array of low abundance environmental chemicals to which humans are exposed. Exposome research teaches that 80–85% of human disease is linked to environmental exposures. The human exposome is estimated to include >400,000 environmental chemicals, most of which are uncharacterized with regard to human health. In fact, mass spectrometry measures >200,000 m/z features (ions) in microliter volumes derived from human samples; most are unidentified. This crystallizes a grand challenge for chemical research in toxicology: to develop reliable and affordable analytical methods to understand health impacts of the extensive human chemical experience. To this end, there appears to be no choice but to abandon the limitations of measuring one chemical at a time. The present review looks at progress in computational metabolomics to provide probability based annotation linking ions to known chemicals and serve as a foundation for unambiguous designation of unidentified ions for toxicologic study. We review methods to characterize ions in terms of accurate mass m/z, chromatographic retention time, correlation of adduct, isotopic and fragment forms, association with metabolic pathways and measurement of collision-induced dissociation products, collision cross section, and chirality. Such information can support a largely unambiguous system for documenting unidentified ions in environmental surveillance and human biomonitoring. Assembly of this data would provide a resource to characterize and understand health risks of the array of low-abundance chemicals to which humans are exposed.

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

“…In untargeted or hybrid metabolomics approaches, such as those used in this study, a blank correction is inappropriate, especially when measuring low intensity features representing ubiquitous environmental exposures. This is compensated for through the use of advanced bioinformatics methods, quality controls, isotopic standards, and a high-resolution metabolomics platform in tandem (3, 68). Thus, noise is dramatically reduced in the final feature tables used in the analyses here without the explicit and overly conservative removal of signals.…”

Putrescine as indicator of manganese neurotoxicity: Dose-response study in human SH-SY5Y cells

“…2; details concerning m/z , RT, adduct and identification score of Schymanski et al (2014) are provided in Table 1, and more extensive details are provided in Supplemental Table 1. Additional confidence in identification of poly-amine metabolites is provided by significant correlations of metabolic precursors and products within known metabolic pathways (see (Uppal et al, 2016)).…”

“…To help overcome the false discovery due to multiple comparisons, the experiments were designed with nine independent biological replicates for each of the six experimental conditions of Mn concentration. Metabolic extracts were prepared as described previously (Go et al, 2014, 2015a; Soltow et al, 2013; Uppal et al, 2013, 2016, 2017). Briefly, after the 5-h treatment, cells were washed with phosphate-buffered saline and 200 μL of 1:2 HPLC grade water: acetonitrile solution containing a mixture of stable isotopic standards (Go et al, 2015a; Soltow et al, 2013) was added to each plate to precipitate proteins and extract metabolites (Go et al, 2014).…”

Trends in the application of high-resolution mass spectrometry for human biomonitoring: An analytical primer to studying the environmental chemical space of the human exposome

“…Hence, the exposome concept is gaining support for inclusion in epidemiological studies (Vineis et al, 2016, DeBord et al, 2016, Lopez de Maturana et al, 2016, Andra et al, 2016). However, the chemical space of the human exposome is estimated to have >400,000 environmental chemicals with >200,000 molecular features or ions that are yet to be characterized in human matrices analyzed with HRMS (Uppal et al, 2016). This space is known as the ‘ dark matter of the exposome ’.…”

“…To tackle this issue, the Clinical Biomarkers Laboratory at Emory University is applying high-resolution metabolomics to analyze over 20,000 biological specimens using rigorous standard operating procedures (Go et al, 2015) and has obtained more than 100,000 molecular features for which accurate mass, retention time, and ion intensity information were collected. Development of such a reference database will enable retrospective analysis of human exposures and help interpret the human exposome (Uppal et al, 2016, Grondin et al, 2016). The use of high-resolution metabolomics to study the human exposome in multiple ways is outlined by Jones (Jones, 2016).…”