A Portable and Reusable Database Infrastructure for Mass Spectrometry, and Its Associated Toolkit (The DIMSpec Project).

Nontargeted analysis (NTA) is a rapidly growing field of techniques that includes the identification of unknown chemical analytes in complex mixtures such as environmental, biological, and food matrices. The use of reference mass spectral databases is a key component of most NTA workflows, providing a high level of confidence for chemical identification when analytical standards are not available, yet effective interlaboratory sharing of research grade spectra remains challenging. The Database Infrastructure for Mass Spectrometry (DIMSpec) project focused on the creation of an open-source toolkit supporting storage and sharing of high-resolution mass spectra with attached sample and methodological metadata. As a demonstration of its utility, the DIMSpec toolkit was used to create a database of curated mass spectra for per- and polyfluoroalkyl substances (PFAS) generated from various sources. While the underlying toolkit is agnostic to analytical targets, this initial release (along with the database schema, mass spectral data, and database tools) should enable PFAS researchers to use these data for their own studies, including the identification of novel PFAS in the environment.

PFAS ghosts: how to identify, evaluate, and exorcise new and existing analytical interference.

With increasing public awareness of PFAS, and their presence in biological and environmental media across the globe, comes a matching increase in the number of PFAS monitoring studies. As more matrices and sample cohorts are examined, there are more opportunities for matrix interferents to appear as PFAS where there are none (i.e., "seeing ghosts"), impacting subsequent reports. Addressing these ghosts is vital for the research community, as proper analytical measurements are necessary for decision-makers to understand the presence, levels, and potential risks associated with PFAS and protect human and environmental health. To date, PFAS interference has been identified in several matrices (e.g., food, shellfish, blood, tissue); however, additional unidentified interferents are likely to be observed as PFAS research continues to expand. Therefore, the aim of this commentary is several fold: (1) to create and support a publicly available dataset of all currently known PFAS analytical interferents, (2) to allow for the expansion of that dataset as more sources of interference are identified, and (3) to advise the wider scientific community on how to both identify and eliminate current or new analytical interference in PFAS analyses.

Non-targeted analysis (NTA) and suspect screening analysis (SSA): a review of examining the chemical exposome.

Non-targeted analysis (NTA) and suspect screening analysis (SSA) are powerful techniques that rely on high-resolution mass spectrometry (HRMS) and computational tools to detect and identify unknown or suspected chemicals in the exposome. Fully understanding the chemical exposome requires characterization of both environmental media and human specimens. As such, we conducted a review to examine the use of different NTA and SSA methods in various exposure media and human samples, including the results and chemicals detected. The literature review was conducted by searching literature databases, such as PubMed and Web of Science, for keywords, such as "non-targeted analysis", "suspect screening analysis" and the exposure media. Sources of human exposure to environmental chemicals discussed in this review include water, air, soil/sediment, dust, and food and consumer products. The use of NTA for exposure discovery in human biospecimen is also reviewed. The chemical space that has been captured using NTA varies by media analyzed and analytical platform. In each media the chemicals that were frequently detected using NTA were: per- and polyfluoroalkyl substances (PFAS) and pharmaceuticals in water, pesticides and polyaromatic hydrocarbons (PAHs) in soil and sediment, volatile and semi-volatile organic compounds in air, flame retardants in dust, plasticizers in consumer products, and plasticizers, pesticides, and halogenated compounds in human samples. Some studies reviewed herein used both liquid chromatography (LC) and gas chromatography (GC) HRMS to increase the detected chemical space (16%); however, the majority (51%) only used LC-HRMS and fewer used GC-HRMS (32%). Finally, we identify knowledge and technology gaps that must be overcome to fully assess potential chemical exposures using NTA. Understanding the chemical space is essential to identifying and prioritizing gaps in our understanding of exposure sources and prior exposures. IMPACT STATEMENT: This review examines the results and chemicals detected by analyzing exposure media and human samples using high-resolution mass spectrometry based non-targeted analysis (NTA) and suspect screening analysis (SSA).

Attribute Analytics Performance Metrics from the MAM Consortium Interlaboratory Study.

The multi-attribute method (MAM) was conceived as a single assay to potentially replace multiple single-attribute assays that have long been used in process development and quality control (QC) for protein therapeutics. MAM is rooted in traditional peptide mapping methods; it leverages mass spectrometry (MS) detection for confident identification and quantitation of many types of protein attributes that may be targeted for monitoring. While MAM has been widely explored across the industry, it has yet to gain a strong foothold within QC laboratories as a replacement method for established orthogonal platforms. Members of the MAM consortium recently undertook an interlaboratory study to evaluate the industry-wide status of MAM. Here we present the results of this study as they pertain to the targeted attribute analytics component of MAM, including investigation into the sources of variability between laboratories and comparison of MAM data to orthogonal methods. These results are made available with an eye toward aiding the community in further optimizing the method to enable its more frequent use in the QC environment.

Communicating Confidence of Per- and Polyfluoroalkyl Substance Identification via High-Resolution Mass Spectrometry.

Per- and polyfluoroalkyl substances (PFASs) are important environmental contaminants, yet relatively few analytical reference standards exist for this class. Nontarget analyses performed by means of high-resolution mass spectrometry (HRMS) are increasingly common for the discovery and identification of PFASs in environmental and biological samples. The certainty of PFAS identifications made via HRMS must be communicated through a reliable and harmonized approach. Here, we present a confidence scale along with identification criteria specific to suspect or nontarget analysis of PFASs by means of nontarget HRMS. Confidence levels range from level 1a-"Confirmed by Reference Standard," and level 1b-"Indistinguishable from Reference Standard," to level 5-"Exact Masses of Interest," which are identified by suspect screening or data filtering, two common forms of feature prioritization. This confidence scale is consistent with general criteria for communicating confidence in the identification of small organic molecules by HRMS (e.g., through a match to analytical reference standards, library MS/MS, and/or retention times) but incorporates the specific conventions and tools used in PFAS classification and analysis (e.g., detection of homologous series and specific ranges of mass defects). Our scale clarifies the level of certainty in PFAS identification and, in doing so, facilitates more efficient identification.

An Introduction to the Benchmarking and Publications for Non-Targeted Analysis Working Group.

Non-targeted analysis (NTA) encompasses a rapidly evolving set of mass spectrometry techniques aimed at characterizing the chemical composition of complex samples, identifying unknown compounds, and/or classifying samples, without prior knowledge regarding the chemical content of the samples. Recent advances in NTA are the result of improved and more accessible instrumentation for data generation and analysis tools for data evaluation and interpretation. As researchers continue to develop NTA approaches in various scientific fields, there is a growing need to identify, disseminate, and adopt community-wide method reporting guidelines. In 2018, NTA researchers formed the Benchmarking and Publications for Non-Targeted Analysis Working Group (BP4NTA) to address this need. Consisting of participants from around the world and representing fields ranging from environmental science and food chemistry to 'omics and toxicology, BP4NTA provides resources addressing a variety of challenges associated with NTA. Thus far, BP4NTA group members have aimed to establish a consensus on NTA-related terms and concepts and to create consistency in reporting practices by providing resources on a public Web site, including consensus definitions, reference content, and lists of available tools. Moving forward, BP4NTA will provide a setting for NTA researchers to continue discussing emerging challenges and contribute to additional harmonization efforts.

New Peak Detection Performance Metrics from the MAM Consortium Interlaboratory Study.

The Multi-Attribute Method (MAM) Consortium was initially formed as a venue to harmonize best practices, share experiences, and generate innovative methodologies to facilitate widespread integration of the MAM platform, which is an emerging ultra-high-performance liquid chromatography-mass spectrometry application. Successful implementation of MAM as a purity-indicating assay requires new peak detection (NPD) of potential process- and/or product-related impurities. The NPD interlaboratory study described herein was carried out by the MAM Consortium to report on the industry-wide performance of NPD using predigested samples of the NISTmAb Reference Material 8671. Results from 28 participating laboratories show that the NPD parameters being utilized across the industry are representative of high-resolution MS performance capabilities. Certain elements of NPD, including common sources of variability in the number of new peaks detected, that are critical to the performance of the purity function of MAM were identified in this study and are reported here as a means to further refine the methodology and accelerate adoption into manufacturer-specific protein therapeutic product life cycles.

Development of a Data Analysis Tool to Determine the Measurement Variability of Consensus Mass Spectra.

The success of nontargeted analysis often depends on libraries containing reference mass spectra of known chemical compounds; the mass spectra of unknown compounds are compared to these reference mass spectra, leading to a probable compound identity. Typical calculations include the mean measured values for each ion m/z and intensity with no estimation of the variability of the measurement. This study presents a novel tool for the calculation of the variability of a measured mass spectrum, including the various data parameters that can impact the measured variability. Using perfluorooctanoic acid (PFOA) as the model compound, the variability of measured data-dependent fragmentation mass spectra (ddMS2) was calculated within replicate measurements of a simple solution of PFOA and a complex mixture (house dust extract) containing PFOA. The variability of the measured ddMS2 for PFOA in the solution and house dust extract were similar, with standard deviations about the measured m/z value ranging from m/z 0.00003 to 0.00015 and the standard deviations about the measured relative intensity ranging from 0.0077 to 0.0211 relative intensity units. In addition, the selected parameters for the extraction of ddMS2 from a single analytical run varied between the sample types due to the increased presence of background ions in the house dust extract. Finally, the variability of the ddMS2 spectra for PFOA in both samples was used to calculate a more robust similarity factor, informing the confidence of the identification of unknown compounds.

A nontargeted approach to determine the authenticity of Ginkgo biloba L. plant materials and dried leaf extracts by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and chemometrics.

The lack of stringent regulations regarding raw materials for herbal supplements used for medicinal purposes has been a constant challenge in the industry. Ginkgo biloba L. leaf extracts attract consumers because of the supposed positive effect on mental performance and memory. Supplements are produced using dried leaf materials and standardized leaf extracts such as EGb 761. Adulteration of Ginkgo biloba L. plants and extracts are becoming more and more common practice due to economically driven motivation from increasing demand in the market and the high cost of raw materials and production. Reinforcement in quality control (QC) to avoid adulterations is necessary to ensure the efficacy of the supplements. In this study, liquid chromatography-high-resolution mass spectrometry (LC-HRMS) was used with principal component analysis (PCA) as an unsupervised exploratory method to analyze, identify, and evaluate the adulterated Ginkgo biloba L. plant materials and dried leaf extracts using the PCA scores and loadings obtained and compound identification.

Evaluation of Method-Specific Extraction Variability for the Measurement of Fatty Acids in a Candidate Infant/Adult Nutritional Formula Reference Material.

To address community needs, the National Institute of Standards and Technology has developed a candidate Standard Reference Material (SRM) for infant/adult nutritional formula based on milk and whey protein concentrates with isolated soy protein called SRM 1869 Infant/Adult Nutritional Formula. One major component of this candidate SRM is the fatty acid content. In this study, multiple extraction techniques were evaluated to quantify the fatty acids in this new material. Extraction methods that were based on lipid extraction followed by transesterification resulted in lower mass fraction values for all fatty acids than the values measured by methods utilizing in situ transesterification followed by fatty acid methyl ester extraction (ISTE). An ISTE method, based on the identified optimal parameters, was used to determine the fatty acid content of the new infant/adult nutritional formula reference material.

Multianalyte profiling of per- and polyfluoroalkyl substances (PFASs) in liquid commercial products.

The chemical properties of poly- and perfluoroalkyl substances (PFASs) make them widespread for use in a number of industrial and commercial products to confer water and oil-repellency characteristics and to reduce surface tension e.g. in aqueous film-forming foams (AFFFs). Some PFASs, especially perfluoroctane sulfonate, and several perfluoroalkyl carboxylic acids, are known to cause significant human and environmental negative impact. Our knowledge on the content of PFASs in products remains scarce due to limited information available, thus impeding any precise assessment of human exposure and environmental release upon use. This study aimed at analyzing a wide variety of liquid products (n = 194) likely to contain PFASs, including impregnating agents, lubricants, cleansers, polishes, AFFFs and other industrial products. By means of LC- and GC-MS/MS analytical techniques, 24 PFASs (from 41 targeted PFASs) were detected and quantified in 55% of samples. PFAS quantification and profiling was found to be consumer product specific. PFASs were mostly detected in AFFF (90%) and impregnating agents (60%) with mainly ionic and neutral species, respectively. In particular, the fluorotelomer alcohols 6:2, 8:2 and 10:2 FTOHs were detected in 40-50% of impregnating agents. Further investigation by Fast Atom Bombardment Mass Spectrometry (FAB-MS) on a set of AFFF samples allowed the characterization of 8 different PFAS classes as major components in these formulations. Results demonstrated that numerous and diversified PFAS are currently used in specific commercial products, implying significant human exposure and environmental release that necessitate further research concerning their toxicological impact.

Trace Analysis of Surfactants in Corexit Oil Dispersant Formulations and Seawater.

After the April 2010 explosion on the Deepwater Horizon oil rig, and subsequent release of millions of barrels of oil, two Corexit oil dispersant formulations were used in unprecedented quantities both on the surface and sub-surface of the Gulf of Mexico. Although the dispersant formulations contain four classes of surfactants, current studies to date focus on the anionic surfactant, bis-(2-ethylhexyl) sulfosuccinate (DOSS). Factors affecting the integrity of environmental and laboratory samples for Corexit analysis have not been systematically investigated. For this reason, a quantitative analytical method was developed for the detection of all four classes of surfactants, as well as the hydrolysis products of DOSS, the enantiomeric mixture of α- and ß-ethylhexyl sulfosuccinate (α-/ß-EHSS). The analytical method was then used to evaluate which practices for sample collection, storage, and analysis resulted in high quality data. Large volume, direct injection of seawater followed by liquid chromatography tandem mass spectrometry (LC-MS/MS) minimized analytical artifacts, analysis time, and both chemical and solid waste. Concentrations of DOSS in the seawater samples ranged from 71 - 13,000 ng/L, while the nonionic surfactants including Span 80, Tween 80, Tween 85 were detected infrequently (26% of samples) at concentrations from 840 - 9100 ng/L. The enantiomers α-/ß-EHSS were detected in seawater, at concentrations from 200 - 1,900 ng/L, and in both Corexit dispersant formulations, indicating α-/ß-EHSS were applied to the oil spill and may be not unambiguous indicator of DOSS degradation. Best practices are provided to ensure sample integrity and data quality for environmental monitoring studies and laboratory that require the detection and quantification of Corexit-based surfactants in seawater.

Evaluation of the impact of peak description on the quantitative capabilities of comprehensive two-dimensional liquid chromatography.

Comprehensive, two-dimensional liquid chromatography (LC × LC) is a powerful technique for the separation of complex mixtures. Most studies using LC × LC are focused on qualitative efforts, such as increasing peak capacity. The present study examined the use of LC × LC-UV/vis for the separation and quantitation of polycyclic aromatic hydrocarbons (PAHs). More specifically, this study evaluated the impact of different peak integration approaches on the quantitative performance of the LC × LC method. For well-resolved three-dimensional peaks, parameters such as baseline definition, peak base shape, and peak width determination did not have a significant impact on accuracy and precision. For less-resolved peaks, a dropped baseline and the summation of all slices in the peak improved the accuracy and precision of the integration methods. The computational approaches to three-dimensional peak integration are provided, including fully descriptive, select slice, and summed heights integration methods, each with its own strengths and weaknesses. Overall, the integration methods presented quantify each of the PAHs within acceptable precision and accuracy ranges and have comparable performance to that of single dimension liquid chromatography.

Extraction of fullerenes from environmental matrices as affected by solvent characteristics and analyte concentration.

Fullerenes possess unique chemical properties that make the isolation of these compounds from heterogeneous environmental matrices difficult. For example, previous reports indicate that toluene-based extraction techniques vary in their ability to extract C60, especially from highly carbonaceous solid matrices. Here, we examined the effects of (i) solvent type (toluene alone versus an 80:20 v/v mixture of toluene and 1-methylnaphthalene) and (ii) analyte concentration on the extraction efficiency of an isotopically labeled surrogate compound, (13)C60. The toluene/1-methylnaphthalene mixture increased fullerene extraction efficiency from carbon lampblack by a factor of five, but was not significantly different from 100% toluene when applied to wood stove soot or montmorillonite. Recovery of the (13)C60 surrogate declined with decreasing analyte concentration. The usefulness of isotopically labeled surrogate is demonstrated and the study provides a quantitative assessment regarding the dependence of fullerene extraction efficiencies on the geochemical characteristics of solid matrices.

Identification of novel fluorochemicals in aqueous film-forming foams used by the US military.

Aqueous film-forming foams (AFFFs) are a vital tool to fight large hydrocarbon fires and can be used by public, commercial, and military firefighting organizations. In order to possess these superior firefighting capabilities, AFFFs contain fluorochemical surfactants, of which many of the chemical identities are listed as proprietary. Large-scale controlled (e.g., training activities) and uncontrolled releases of AFFF have resulted in contamination of groundwater. Information on the composition of AFFF formulations is needed to fully define the extent of groundwater contamination, and the first step is to fully define the fluorochemical composition of AFFFs used by the US military. Fast atom bombardment mass spectrometry (FAB-MS) and high resolution quadrupole-time-of-flight mass spectrometry (QTOF-MS) were combined to elucidate chemical formulas for the fluorochemicals in AFFF mixtures, and, along with patent-based information, structures were assigned. Sample collection and analysis was focused on AFFFs that have been designated as certified for US military use. Ten different fluorochemical classes were identified in the seven military-certified AFFF formulations and include anionic, cationic, and zwitterionic surfactants with perfluoroalkyl chain lengths ranging from 4 to 12. The environmental implications are discussed, and research needs are identified.