This study was conducted to optimize a targeted plant proteomics approach from signature peptide selection and liquid chromatography with tandem mass spectrometry (LC-MS/MS) analytical method development and optimization to sample preparation method optimization. Three typical protein extraction and precipitation methods, including trichloroacetic acid (TCA)/ acetone method, phenol method, and TCA/acetone/phenol method, and two digestion methods, including trypsin digestion and LysC/trypsin digestion, were evaluated for selected proteins related to the impact of engineered nanomaterials (ENMs) on wheat (Triticum aestivum) plant growth. In addition, we compared two plant tissue homogenization methods: grinding freeze-dried tissue and fresh tissue into a fine powder using a mortar and pestle aided with liquid nitrogen. Wheat plants were grown under a 16 h photoperiod (light intensity 150 μmol•m −2 •s −1 ) for 4 weeks at 22 °C with a relative humidity of 60% and were watered daily to maintain a 70−90% water content in the soil. Processed samples were analyzed with an optimized LC-MS/MS method. The concentration of selected signature peptides for the wheat proteins of interest indicated that the phenol extraction method using fresh plant tissue, coupled with trypsin digestion, was the best sample preparation method for the targeted proteomics study. Overall, the optimized approach yielded the highest total peptide concentration (68,831 ng/g, 2.4 times the lowest concentration) as well as higher signature peptide concentrations for most peptides (19 out of 28). In addition, three of the signature peptides could only be detected using the optimized approach. This study provides a workflow for optimizing targeted proteomics studies.

Per-and polyfluoroalkyl substances (PFAS) have received increased scrutiny from environmental and public health protection agencies, with focus placed on phased-out "legacy" PFAS such as perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA). However, recent studies highlight the need to also evaluate the risks of replacement and breakdown products such as perfluorobutanesulfonic acid (PFBS) and hexafluoropropylene oxide dimer acid (HFPO-DA). Thus, the objective was to evaluate the ecological risks of legacy and newer PFAS, using monitoring and predictive models. Here, PFBS, PFOA, PFOS, and other PFAS were detected in samples collected downstream from 16 Southern and Central California wastewater treatment plants (WWTPs). PFBS, PFOA, and PFOS were sometimes detected at concentrations above experimentally determined lowest observed effect concentrations. Additionally, ChemFate, a fate and transport model, was used to estimate daily loads to the upstream WWTPs. Population size and urban land use were the best predictors of PFAS loads to WWTPs. The sum of influent loads of selected PFAS was estimated to be 61,000 ± 40,000 kg/year for California. Additionally, the sum of PFAS totaled annually in evaluated regions correlated well with the overall pollution burden. Here, the practicality of using predictive models in conjunction with field sampling to predict PFAS inputs and their ecological risks to the environment was demonstrated.