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Understanding Adverse Effects of Per- and Polyfluoroalkyl Substances on Nontarget Species

Sector: Hydrogen • Location: United States of America

Source: Grants.gov

Project
Archived

Background: Per- and polyfluoroalkyl substances (PFAS) have been released into the environment primarily through the use of aqueous film-forming foams that have been used to fight flammable liquid pool fires, but also through the ubiquitous use and disposal of a multitude of industrial and consumer-based products that contain PFAS. The film-forming foams are complex mixtures normally containing fl

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The project “Understanding Adverse Effects of Per- and Polyfluoroalkyl Substances on Nontarget Species” is an infrastructure initiative in the Hydrogen sector, located in United States of America. Taiyo aggregates data on it from Grants.gov.

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Description

Background: Per- and polyfluoroalkyl substances (PFAS) have been released into the environment primarily through the use of aqueous film-forming foams that have been used to fight flammable liquid pool fires, but also through the ubiquitous use and disposal of a multitude of industrial and consumer-based products that contain PFAS. The film-forming foams are complex mixtures normally containing fluorinated- and hydrogenated-surfactants that are used to extinguish fires involving highly flammable liquids. PFAS have become an important emerging concern worldwide, as these substances are found in biota, water and sediments and constitute potential hazards to environmental and human health. They are known to cause immunotoxicity and alter lipid metabolism, among other toxicological endpoints. To better understand the potential health hazards of PFAS and related compounds, molecular endpoints such as gene expression are being analyzed and incorporated into the Adverse Outcome Pathway (AOP) framework. Changes in gene expression, or transcriptomics, are a powerful measurement of chemical effects as it measures changes in thousands of genes at once. However, understanding how the molecular endpoints relate to apical toxicity and health hazard remains a challenge . Brief Description of Anticipated Work: Required Work Objectives: This project will determine changes in transcriptomes and behavior that can be linked to PFAS exposures from both field and laboratory experiments. The project will also address the impact of PFAS on biodiversity in the environment using molecular genetic approaches to identify species in water and sediment samples. The project is focused on determining health effects zebrafish and on metagenomic approaches to monitor changes in the abundance of different species in environmental samples. The ultimate goal of this effort is to develop methods that accelerate our understanding of the adverse effects of PFAS on aquatic species in order to inform risk assessment. Objective 1: RNA sequencing analysis of zebrafish embryo . We will receive fish samples from EL scientists and will perform RNAseq on the tissues of interest as discussed. Samples will be run on either HiSeq or NovaSeq Illumina platforms, depending on the number of samples and coverage needed. Bioinformatics analysis will be performed on the sequencing data in order to identify differentially expressed genes, enriched pathways, or other endpoints of interest. Objective 2: Analysis of omics and apical data from zebrafish. Apical effects of specific exposures on zebrafish will be analyzed in order to link molecular initiating events to apical endpoints of concern that might be affecting survival. These analyses will be used to develop AOPs for all the specific PFAS. Results from both objectives will be communicated to ERDC regularly in interim reports and transferred to the Public using conference presentations and the peer-reviewed literature. All methods and protocols will accompany the results and meet peer-review scrutiny for any interim reports. A successful application would likely include experience with performing RNAseq on Contaminants of Concerns (CoCs), development of AOPs, and successful publication record of these methods.

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High

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100%

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