How does untargeted environmental contaminant analysis improve exposure assessment?
Environmental chemical space is vast. Potentially toxic environmental contaminants occur typically in chemically diverse mixtures, with important contributions from compound classes such as pesticides, industrial byproducts, consumer chemicals, plastic additives, pharmaceuticals, and others. Any holistic assessment of human exposure to chemical stressors should ideally explore the diversity of toxicologically-important chemicals present in relevant environmental exposure media. Such assessment of the “external exposome” can be accomplished using high-resolution mass spectrometry (HRMS). Modern instruments, methods, and data processing routines have enabled comprehensive untargeted screening of environmental samples for chemical exposure assessment (Hollender et al., 2017). Integration of these approaches with epidemiological or laboratory assessment of health effects can lead to increased understanding of the links between chemical exposures and health outcomes.
How is untargeted analysis performed in environmental samples?
The environmental analysis lab hub within HHEAR relies primarily on liquid chromatography coupled to HRMS and tandem mass spectrometry for detecting and characterizing organic contaminants in environmental samples. This method is suitable for detection of polar and semi-polar organic compounds across a wide range of masses in a variety of sample types. Typically, samples are extracted and analyzed by LC-HRMS using a data-dependent MS/MS strategy to acquire high-coverage tandem mass spectra for relevant compounds in the sample. Data analysis is conducted using a combination of commercial and open-source, custom software designed to detect features, consolidate signals contributing to individual compounds, align compound signals across samples, and annotate tentative and confirmed structure identities using a combination of spectral library searching (> 30,000 compounds in library) and in silico computational mass spectrometry tools with associated measures of annotation confidence. For untargeted analysis of non-polar, semivolatile organic compounds in environmental samples, gas chromatography with HRMS detection is available, although data analysis and processing routines for this approach are still under development.
What contaminants can typically be detected and identified in untargeted analysis of environmental samples?
In principle, any organic compound that ionizes well under electrospray or APCI conditions in LC-HRMS can be detected in untargeted analysis of environmental samples. In practice, the limiting factor is often the availability of spectral reference data or computational mass spectrometry approaches for structure annotation of unknown chemical compounds. The HHEAR environmental analysis hub has had success in analysis of compounds such as pharmaceuticals, plastic additives, antioxidants, flame retardants, pesticides and other agrochemicals, polyfluorinated alkyl substances (PFAS), surfactants, biocides, endocrine disruptors, and transformation products of these in environmental samples. Note that the focus of the HHEAR environmental analysis hub’s untargeted approach is squarely on exogenous organic chemicals. We do not provide untargeted analysis of endogenous metabolites.
What types of environmental samples can be measured?
A variety of environmental sample types can be accepted by the environmental analysis lab hub for untargeted analysis. Examples of relevant sample types include drinking water, ambient surface- or groundwater, wastewater, sediment and soils, and indoor house dust. The complexity of sample types will influence the need for sample pre-treatment prior to analysis, and this may dictate the breadth of chemical space that can be covered by untargeted analysis approaches. Additional sample types may be accepted by the HHEAR environmental analysis hub, subject to consultation and assessment during the laboratory feasibility assessment.
What sample quality and quantity are necessary?
Sample quantity necessary for untargeted analysis of environmental samples is highly dependent on complexity of the samples, expected concentration of likely contaminants, and the objective of the study. An example can be given for water analysis: for characterizing parts-per-trillion level organic pollutants in finished drinking water, approximately 1 liter of sample would be required. However, for parts-per-billion level contaminants in raw or treated wastewater, only 1-10 mL of sample may be required. A significant consideration in accepting environmental samples for untargeted analysis will be sample collection, storage, and shipping methods. In general, it is best to avoid addition of preservatives to samples and to store and ship samples frozen (if practical) as quickly as possible after collection. In cases where shipment of large numbers of samples may be impractical (e.g. the example of 1 liter samples of drinking water above), the HHEAR environmental lab hub can provide protocols for processing/extracting samples prior to shipping them to the hub.
How does HHEAR ensure the quality of untargeted analysis of environmental samples?
The HHEAR environmental analysis hub applies a range of quality assurance/quality control (QA/QC) approaches to ensure high-fidelity data collection and processing. Examples of experimental approaches include isotopically-labeled standard amendment for benchmarking and internal calibration, analytical replication and QA mixture analysis in each batch. For data analysis, rigorous metrics have been developed to reduce artifacts in feature detection and consolidation, and all compound annotations are classified according to the scale set forth by Schymanski et al. (2014).
References
Hollender J, Schymanski EL, Singer HP, Ferguson PL. Nontarget screening with high resolution mass spectrometry in the environment: Ready to go? Environ. Sci. Tehcnol. 2017; 51(20):11505-11512.
Schymanski EL, Jeon J, Gulde R, et al. Identifying small molecules via high resolution mass spectrometry: Communicating confidence. Environ. Sci. Technol. 2014; 48(4):2097-2098.