Software Comparison for Nontargeted Analysis of PFAS in AFFF-Contaminated Soil

Nason, Sara L.; Koelmel, Jeremy P.; Zuverza‐Mena, Nubia; Stanley, Chelli; Tamez, Carlos; Bowden, John A.; Pollitt, Krystal J. Godri

doi:10.1021/jasms.0c00261

Cited by 36 publications

(48 citation statements)

References 18 publications

(47 reference statements)

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“…While it is clear FluoroMatch 2.0 can rapidly and comprehensively perform non-targeted PFAS analysis in an automated fashion, the question remains how confident the annotations provided are. Previous work has generally shown 100% agreement of score A and A− annotations with spiked standards, targeted analysis, and against other software platforms, with the exception of the inability to determine subtle differences including branched versus straight-chain isomers [30,34]. In the present sample, 74 species were assigned confident annotations (A) using class-based fragmentation patterns.…”

Section: Benchmarking Fluoromatch 20 Against Standards Traditional Non-targeted Approaches and Vendor Algorithmsmentioning

confidence: 74%

“…Furthermore, FluoroMatch 2.0 screens common PFAS fragments and incorporates MS/MS libraries predicted for all PFAS listed in the EPA database that are likely to form [M-H] − ions. This is in addition to the confident MS/MS rulebased annotation [34] derived from PFAS standards in the original FluoroMatch release [30]. All evidence is incorporated into a clear, yet thorough, scoring framework for ease of interpretation, which can be applied across multiple workflows by analytical chemists measuring PFAS.…”

Section: Introductionmentioning

confidence: 99%

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FluoroMatch 2.0—making automated and comprehensive non-targeted PFAS annotation a reality

et al. 2021

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Because of the pervasiveness, persistence, and toxicity of per-and polyfluoroalkyl substances (PFAS), there is growing concern over PFAS contamination, exposures, and health effects. The diversity of potential PFAS is astounding, with nearly 10,000 PFAS catalogued in databases to date (and growing). The ability to detect the thousands of known PFAS, and discover previously uncatalogued PFAS, is necessary to understand the scope of PFAS contamination and to identify appropriate remediation and regulatory solutions. Current non-targeted methods for PFAS analysis require manual curation and are time-consuming, prone to error, and not comprehensive. FluoroMatch Flow 2.0 is the first software to cover all steps of data processing for PFAS discovery in liquid chromatography-high-resolution tandem mass spectrometry samples. These steps include feature detection, feature blank filtering, exact mass matching to catalogued PFAS, mass defect filtering, homologous series detection, retention time pattern analysis, class-based MS/MS screening, fragment screening, and predicted MS/MS from SMILES structures. In addition, a comprehensive confidence level criterion is implemented to help users understand annotation certainty and integrate various layers of evidence to reduce overreporting. Applying the software to aqueous film forming foam analysis, we discovered over one thousand likely PFAS including previously unreported species. Furthermore, we were able to filter out 96% of features which were likely not PFAS. FluoroMatch Flow 2 increased coverage of likely PFAS by over tenfold compared to the previous release. This software will enable researchers to better characterize PFAS in the environment and in biological systems.

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Section: Benchmarking Fluoromatch 20 Against Standards Traditional Non-targeted Approaches and Vendor Algorithmsmentioning

confidence: 74%

Section: Introductionmentioning

confidence: 99%

FluoroMatch 2.0—making automated and comprehensive non-targeted PFAS annotation a reality

et al. 2021

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“…Dr. Nason: The primary contaminant at the study site is PFOS (perfluorooctane sulfonic acid), which we have found at up to 150 ppb in the soil, but many other PFAS are present as well. We have a publication out that focuses on analysis of soil from the site, where we identified over 70 total PFAS, but we also determined that that the PFAS levels at the site are highly variable (Nason et al, 2020). This variability limits the quality of our phytoremediation data, but in our 2020 field test, PFOS soil concentrations decreased in both hemp growth plots.…”

Section: An Ongoing Storymentioning

confidence: 96%

“…I met several other scientists via the taskforce, who I now have active collaborations with. So far, we have four publications related to PFAS (Koelmel et al, 2020, Koelmel et al, 2021Nason et al, 2020;Hagstrom et al, 2021) and two funded grant proposals, with more in progress! My work on this collaborative community project kick started all these additional activities.…”

Section: An Ongoing Storymentioning

confidence: 99%

A community based PFAS phytoremediation project at the former Loring Airforce Base

Nason

Stanley

PeterPaul³

et al. 2021

iScience

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The Loring Airforce Base (AFB) in Aroostook County, Maine, USA was active from 1947 through 1994. Like many military sites, it has a substantial history of pollution from a wide variety of toxins. Currently, some of the AFB land belongs to the Micmac Nation, an Indigenous tribe, who are very concerned about the contamination on the land. Starting in 2019, a group of community activists, research scientists, and tribal members came together to test methods for cleaning the land. This backstory features perspectives from six project participants. BEGINNINGSWhat are the goals of this project? How did you decide what to investigate?Dr. Sara L. Nason (Connecticut Agricultural Experiment Station): The overall goal of our work is to improve the quality of the land on the former Loring AFB, which now belongs to the Aroostook band of the Micmac Nation. Specifically, we are testing the use of fiber hemp plants for phytoremediation of per-and polyfluoroalkyl substances (PFAS). PFAS are a class of emerging contaminants that are highly toxic at low concentrations and are frequently found on former military bases owing to their use in firefighting foams (Hagstrom et al., 2021). They are often called ''forever chemicals,'' as they are highly resistant to degradation. Part of the land acquired by the Micmac people was formerly used as a firefighting testing area. The US Airforce has detected concerning levels of PFAS in groundwater at this site, but did not conduct any remediation (Baker, 2018). There are limited technologies available for removing PFAS Currently, some of the Loring Airforce Base (AFB) land belongs to the Micmac Nation, an Indigenous tribe, who are very concerned about the contamination on the land. Starting in 2019, a group of community activists, research scientists, and tribal members came together to test methods for cleaning the land. This backstory features perspectives from six project participants.

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“…So far, NTS has been developed mostly in the fields of drinking water monitoring, food and soil analysis, forensics and metabolomics [e.g., 1 – 5 ], with human health or economic interests as the major underlying motivation. Yet, for the analysis of trace compounds in ambient or indoor air, only very limited NTS-related research has been done (e.g., the discovery of the greenhouse gas [ 6 , 7 ]), despite the need for a better understanding of the composition of the air.…”

Section: Introductionmentioning

confidence: 99%

Automated fragment formula annotation for electron ionisation, high resolution mass spectrometry: application to atmospheric measurements of halocarbons

Guillevic

Vollmer

et al. 2021

J Cheminform

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Background Non-target screening consists in searching a sample for all present substances, suspected or unknown, with very little prior knowledge about the sample. This approach has been introduced more than a decade ago in the field of water analysis, together with dedicated compound identification tools, but is still very scarce for indoor and atmospheric trace gas measurements, despite the clear need for a better understanding of the atmospheric trace gas composition. For a systematic detection of emerging trace gases in the atmosphere, a new and powerful analytical method is gas chromatography (GC) of preconcentrated samples, followed by electron ionisation, high resolution mass spectrometry (EI-HRMS). In this work, we present data analysis tools to enable automated fragment formula annotation for unknown compounds measured by GC-EI-HRMS. Results Based on co-eluting mass/charge fragments, we developed an innovative data analysis method to reliably reconstruct the chemical formulae of the fragments, using efficient combinatorics and graph theory. The method does not require the presence of the molecular ion, which is absent in $$\sim$$ ∼ 40% of EI spectra. Our method has been trained and validated on >50 halocarbons and hydrocarbons, with 3–20 atoms and molar masses of 30–330 g mol$$^{-1}$$ - 1 , measured with a mass resolution of approx. 3500. For >90% of the compounds, more than 90% of the annotated fragment formulae are correct. Cases of wrong identification can be attributed to the scarcity of detected fragments per compound or the lack of isotopic constraint (no minor isotopocule detected). Conclusions Our method enables to reconstruct most probable chemical formulae independently from spectral databases. Therefore, it demonstrates the suitability of EI-HRMS data for non-target analysis and paves the way for the identification of substances for which no EI mass spectrum is registered in databases. We illustrate the performances of our method for atmospheric trace gases and suggest that it may be well suited for many other types of samples. The L-GPL licenced Python code is released under the name ALPINAC for ALgorithmic Process for Identification of Non-targeted Atmospheric Compounds.

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Software Comparison for Nontargeted Analysis of PFAS in AFFF-Contaminated Soil

Cited by 36 publications

References 18 publications

FluoroMatch 2.0—making automated and comprehensive non-targeted PFAS annotation a reality

FluoroMatch 2.0—making automated and comprehensive non-targeted PFAS annotation a reality

A community based PFAS phytoremediation project at the former Loring Airforce Base

Automated fragment formula annotation for electron ionisation, high resolution mass spectrometry: application to atmospheric measurements of halocarbons

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