Federal grant · project grant (b)
Employing Biofilters to Detect Human Pathogens in Mid-atlantic Us Waters - Project Summary Throughout the United States, Human Populations in Coastal Zones Have Been Steadily Increasing. Additionally, Humans Partake in Many Aquatic Recreational Activities and Consume Significant Amounts of Seafood Either Farmed or Harvested From Coastal Waters. All of These Activities Increase the Diversity, Dispersal, and Transmission Potential of Human Pathogens. Unfortunately, Knowledge of the Environmental Epidemiology of Human Pathogens in Coastal Waters Is Limited. Tools Capable of Generating High-resolution Information Are Needed to Determine the Sources, Connectivity, and Spatial Distribution of These Organisms in Coastal Environments. This Project Proposes the Design, Optimization, and Utilization of a Set of In-solution Sequence Capture Arrays to Conduct Targeted Enrichment of Viral and Bacterial Human Pathogens to Determine Their Diversity, Distribution, Dispersal, and Connectivity in Coastal Waterways. Both Capture Arrays Will Utilize Existing Genomic Resources to Create the Arrays, Which Will Include a Mixture of Shared and Unique Loci. Using a Variety of Conserved and Variable Loci From These Pathogens Allows Us to Capture Genomic Regions Useful for Comparative Studies Across Taxa (shared Loci) and for Population Genomic Studies (unique Loci) Within Taxa. the Efficiency, Sensitivity, and Specificity of the Designed Capture Arrays Will Be Assessed by Testing These Arrays on Samples From Biofilters, Which Will Be Market-sized Oysters Deployed Downstream From Wastewater Treatment Facilities. the Data Generated From This Project Will Be Used to Conduct Preliminary Environmental Molecular Epidemiological Studies on These Parasite Taxa Across Spatial and Temporal Scales. This Information Is Critical for Public Health Officials to Make Informed Decisions About the Health and Safety of Humans Using, Living Near, and Consuming Food Resources From Coastal Waters.
Committed
$105,225
Paid out
$93.2K
89%
Committed, not yet paid
$12.0K
11%
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