Nitrifying microorganisms linked to biotransformation of perfluoroalkyl sulfonamido precursors from legacy aqueous film forming foams

Bridger J. Ruyle; Lara Schultes; Denise M. Akob; Cassandra Rashan Harris; Michelle M. Lorah; Simon Vojta; Jitka Becanova; Shelly McCann; Heidi M. Pickard; Ann Pearson; Rainer Lohmann; Chad D. Vecitis; Elsie M. Sunderland

doi:10.1021/acs.est.2c07178

USGS · 70242902

Nitrifying microorganisms linked to biotransformation of perfluoroalkyl sulfonamido precursors from legacy aqueous film forming foams

Bridger J. Ruyle·Lara Schultes·Denise M. Akob·Cassandra Rashan Harris·Michelle M. Lorah·Simon Vojta·Jitka Becanova·Shelly McCann·Heidi M. Pickard·Ann Pearson·Rainer Lohmann·Chad D. Vecitis·Elsie M. Sunderland

View original source ↗Export metadata ↓

Abstract

Drinking water supplies across the United States have been contaminated by firefighting and fire-training activities that use aqueous film-forming foams (AFFF) containing per- and polyfluoroalkyl substances (PFAS). Much of the AFFF is manufactured using electrochemical fluorination by 3M. Precursors with six perfluorinated carbons (C6) and non-fluorinated amine substituents make up approximately one-third of the PFAS in 3M AFFF. C6 precursors can be transformed through nitrification (microbial oxidation) of amine moieties into perfluorohexane sulfonate (PFHxS), a compound of regulatory concern. Here, we report biotransformation of the most abundant C6 sulfonamido precursors in 3M AFFF with available commercial standards (FHxSA, PFHxSAm, and PFHxSAmS) in microcosms representative of the groundwater/surface water boundary. Results show rapid (<1 day) biosorption to living cells by precursors but slow biotransformation into PFHxS (1–100 pM day –1 ). The transformation pathway includes one or two nitrification steps and is supported by the detection of key intermediates using high-resolution mass spectrometry. Increasing nitrate concentrations and total abundance of nitrifying taxa occur in parallel with precursor biotransformation. Together, these data provide multiple lines of evidence supporting microbially limited biotransformation of C6 sulfonamido precursors involving ammonia-oxidizing archaea ( Nitrososphaeria ) and nitrite-oxidizing bacteria ( Nitrospina ). Further elucidation of interrelationships between precursor biotransformation and nitrogen cycling in ecosystems would help inform site remediation efforts.

Explore related subjects

Environmental Science and Technology Article

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Bridger J. Ruyle, Lara Schultes, Denise M. Akob, Cassandra Rashan Harris, Michelle M. Lorah, Simon Vojta, Jitka Becanova, Shelly McCann, Heidi M. Pickard, Ann Pearson, Rainer Lohmann, Chad D. Vecitis, Elsie M. Sunderland. 2023-03-27. Nitrifying microorganisms linked to biotransformation of perfluoroalkyl sulfonamido precursors from legacy aqueous film forming foams. https://doi.org/10.1021/acs.est.2c07178

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

Digging into soil: Effects of soil texture on RT-QuIC performance for environmental prion surveillance.

Chronic wasting disease (CWD) is a fatal neurodegenerative disease caused by infectious prions affecting wild and captive cervids. Transmission occurs directly between hosts or indirectly through contact with prion-contaminated environments. Soils, particularly those rich in clay, are hypothesized to enhance prion stability, retention, and bioavailability. Accurate detection of prions is therefore important for understanding environmental transmission risks. Real-time quaking-induced conversion (RT-QuIC) is a sensitive assay used to detect PrP CWD in tissue, excreta, and environmental materials. However, RT-QuIC performance across soil textures has not been evaluated. This study assessed RT-QuIC sensitivity and specificity using laboratory-prepared soils spiked with CWD-positive brain homogenate or water controls under a standardized extraction method. Conditional on the extraction method used, results suggest that RT-QuIC performance depends on soil texture, and thus, an optimal time-to-threshold (TTT) cutoff required to balance sensitivity and specificity will also vary with soil texture. RT-QuIC exhibited higher sensitivity and moderate specificity in soils with low clay (<20%) and moderate to high silt content, whereas high-clay soils (>20%) with low to moderate silt content (2%–60%) reduced both sensitivity and specificity, and required shorter TTT cutoffs. These findings highlight the importance of accounting for soil texture in environmental CWD surveillance.

Environmental Science and Technology↗

USGS2026

Remote sensing enables basin-scale inventories of coal mine methane

Underground coal mines are important global sources of methane, but emission estimates are uncertain. We show that emission estimates for individual mines from aircraft remote-sensing surveys in the United States agree within 40% with direct measurements used for national emission reporting (IPCC Tier 3 estimate). Such direct measurements are unavailable in most countries, which rely on estimated emission factors (EFs) applied to coal-production rates. We find that EFs from IPCC Tier 1 and the Model for Calculating Coal Mine Methane (MC2M) methods overestimate U.S. emissions 3-fold due to incorrect dependence on mine depth. An IPCC Tier 2 method using measured basin-specific mine gas content agrees with direct emission measurements but does not account for gob well emissions and requires gas content data that are generally unavailable. We show that aircraft remote sensing for a small sample of mines can successfully estimate basin-specific EFs for ventilation shafts and gob wells, enabling estimates of basin- and national-scale emissions. We discuss how the method can be applied with satellite remote sensing to quantify coal emissions worldwide.

Alabama, Colorado, Kentucky, New Mexico, Ohio, Pen↗

USGS2026

Fifteen years of WRTDS for advancing water-quality science: A critical review of methodological developments and global applications

Contamination by nutrients, major ions, and metals poses a major threat to global water sustainability. Understanding how these pollutants vary across time and space requires long-term monitoring and robust statistical approaches. Traditional methods, however, often struggle to account for streamflow variability, seasonality, and nonlinear responses. Introduced in 2010, the Weighted Regressions on Time, Discharge, and Season (WRTDS) method offers a flexible, data-driven framework that generates both observed and flow-normalized estimates of concentration and load. Over the past 15 years, WRTDS has become a state-of-the-art tool for water-quality science and management, with applications spanning a wide range of hydrologic, climatic, and policy contexts─including major watersheds across North America, Europe, Asia, Australia, and the Arctic. In this review of WRTDS, we document the method’s major advancements, examine its expanding geographic and thematic applications, and summarize its relevance to water-quality management programs and policies worldwide. We also discuss its performance relative to other regression and machine-learning approaches. Finally, we identify key priorities for future development to support the continued evolution of WRTDS as a trusted and practical tool for scientists and managers working to protect and sustain water resources.

Environmental Science and Technology↗