Non-targeted identification and semi-quantitation of emerging per- and polyfluoroalkyl substances (PFAS) in US rainwater.

High-resolution mass spectrometry was used to screen for emerging per- and polyfluorinated alkyl substances (PFAS) in precipitation samples collected in summer 2019 at seven sites in the United States. We previously quantified the concentration of ten PFAS in the rainwater samples using the method of isotopic dilution (Pike et al., 2021). Nine of these targeted analytes belonged to the U.S. Environmental Protection Agency Regional Screening Level list, herein referred to as EPA-monitored analytes. In this new work, we identify emerging PFAS compounds by liquid chromatography quadrupole time-of-flight mass spectrometry. Several emerging PFAS were detected across all samples, with the most prevalent compounds being C3-C8 hydrogen-substituted perfluorocarboxylic acids (H-PFCAs) and fluorotelomer carboxylic acids (FTCAs). Concentrations of emerging PFAS were in the 10-1000 ng L-1 range (approximately 1-2 orders of magnitude greater than EPA-monitored PFAS) at all sites except Wooster, OH, where concentrations were even higher, with a maximum estimated ΣPFAS of 16 400 ng L-1. The elevated levels of emerging PFAS in the Wooster samples were predominantly even and odd chain-length H-PFCAs and FTCAs comprised of complex mixtures of branched isomers. This unique composition did not match any known manufactured PFAS formulation reported to date, but it could represent thermally transformed by-products emitted by a local point source. Overall, the results indicate that PFAS outside of the standard analyte lists make up a significant and previously unappreciated fraction of contaminants in rainwater collected within the central U.S.-and potentially world-wide-especially in proximity to localized point sources.

MetaNetwork Enhances Biological Insights from Quantitative Proteomics Differences by Combining Clustering and Enrichment Analyses.

Interpreting proteomics data remains challenging due to the large number of proteins that are quantified by modern mass spectrometry methods. Weighted gene correlation network analysis (WGCNA) can identify groups of biologically related proteins using only protein intensity values by constructing protein correlation networks. However, WGCNA is not widespread in proteomic analyses due to challenges in implementing workflows. To facilitate the adoption of WGCNA by the proteomics field, we created MetaNetwork, an open-source, R-based application to perform sophisticated WGCNA workflows with no coding skill requirements for the end user. We demonstrate MetaNetwork's utility by employing it to identify groups of proteins associated with prostate cancer from a proteomic analysis of tumor and adjacent normal tissue samples. We found a decrease in cytoskeleton-related protein expression, a known hallmark of prostate tumors. We further identified changes in module eigenproteins indicative of dysregulation in protein translation and trafficking pathways. These results demonstrate the value of using MetaNetwork to improve the biological interpretation of quantitative proteomics experiments with 15 or more samples.

Correlation Analysis of Perfluoroalkyl Substances in Regional U.S. Precipitation Events.

Per- and polyfluoroalkyl substances (PFAS) are transported in the atmosphere, leading to both wet and dry deposition to the surface. The concentrations of 15 PFAS were measured at six locations in the Ohio-Indiana region of the U.S. during the summer of 2019 and compared to samples collected at a distant site in NW Wyoming. ΣPFAS concentrations ranged from 50-850 ng L-1, with trifluoroacetic acid (TFA) being the dominant compound (~90%). Concentrations of perfluorooctanoic acid (PFOA) and perfluorosulfonic acid (PFOS) were similar to amounts observed over the past 20 years, indicating persistence in the atmosphere despite regulatory action, and the newer species HFPO-DA (GenX) was also widely detected in rainwater. ANOVA modeling and correlation matrices were used to determine association of PFAS concentrations, location, and functional group and chain length. Statistically significant differences (p < 0.05) in PFAS profiles across sites separated by 10-100 km indicate that local point sources strongly contribute to wet deposition. This work introduces correlation plots for PFAS that allow rapid visual comparison of multi-analyte and multi-site data sets.