Background per- and polyfluoroalkyl substances (PFAS) in laboratory fish diet: Implications for zebrafish toxicological studies

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.

Studying mixture effects on uptake and tissue distribution of PFAS in zebrafish (Danio rerio) using physiologically based kinetic (PBK) modelling

Per- and polyfluoroalkyl substances (PFAS) are ubiquitously distributed in the aquatic environment. They include persistent, mobile, bioaccumulative, and toxic chemicals and it is therefore critical to increase our understanding on their adsorption, distribution, metabolism, excretion (ADME). The current study focused on uptake of seven emerging PFAS in zebrafish (Danio rerio) and their potential maternal transfer. In addition, we aimed at increasing our understanding on mixture effects on ADME by developing a physiologically based kinetic (PBK) model capable of handling co-exposure scenarios of any number of chemicals. All studied chemicals were taken up in the fish to varying degrees, whereas only perfluorononanoate (PFNA) and perfluorooctanoate (PFOA) were quantified in all analysed tissues. Perfluorooctane sulfonamide (FOSA) was measured at concerningly high concentrations in the brain (Cmax over 15 μg/g) but also in the liver and ovaries. All studied PFAS were maternally transferred to the eggs, with FOSA and 6:2 perfluorooctane sulfonate (6,2 FTSA) showing significant (p < 0.02) signs of elimination from the embryos during the first 6 days of development, while perfluorobutane sulfonate (PFBS), PFNA, and perfluorohexane sulfonate (PFHxS) were not eliminated in embryos during this time-frame. The mixture PBK model resulted in >85 % of predictions within a 10-fold error and 60 % of predictions within a 3-fold error. At studied levels of PFAS exposure, competitive binding was not a critical factor for PFAS kinetics. Gill surface pH influenced uptake for some carboxylates but not the sulfonates. The developed PBK model provides an important tool in understanding kinetics under complex mixture scenarios and this use of New Approach Methodologies (NAMs) is critical in future risk assessment of chemicals and early warning systems.