Nationwide bioaerosol metagenomic repository for environmental health research | LC26

Abstract
Air remains the least characterized major environmental compartment despite recent studies showing that over 85% of indoor air samples contain detectable respiratory pathogens. We developed the largest dedicated bioaerosol metagenomic dataset to date: over 1,000 air samples from more than 140 locations across the continental United States, collected from December 2023 through October 2024 across all four seasons. Using 3-micron fluoropore filters from high-volume environmental aerosol samplers, we developed standardized protocols optimized for Oxford Nanopore Technologies sequencing. DNA and RNA were extracted separately using ZymoBIOMICS kits. RNA was converted to cDNA, and both DNA and cDNA were prepared for sequencing on PromethION Flow Cells using the Rapid PCR Barcoding Kit. This approach enabled comprehensive metagenomic and metatranscriptomic characterization of airborne microbial communities. Sampling spanned indoor, outdoor, and transit environments, including special events such as the Boston Marathon and Mardi Gras. This repository represents an unprecedented scale for air microbiome research, capturing comprehensive geographic and temporal variation across the continental United States. The resulting dataset established the first nationwide baseline of airborne microbial communities generated using nanopore sequencing, revealing distinct seasonal and geographic signatures in microbial composition. All data has been made publicly accessible through the airmetagenomics.com dashboard, enabling interactive exploration of spatial and temporal patterns. Following the success of wastewater surveillance systems that provided one to four weeks of early warning before clinical case detection, this repository lays the foundation for analogous air-based environmental monitoring, empowering researchers to develop computational approaches that identify deviations with potential public health significance.

Biography
Kamil Khanipov, PhD, is an Assistant Professor in Pharmacology and Toxicology at The University of Texas Medical Branch and Associate Director of Artificial Intelligence Research at the Moody Brain Health Institute. His research applies nanopore sequencing to environmental metagenomics, including bioaerosol surveillance and air microbiome characterization at mass gatherings and in major metropolitan areas. He contributes to the Advanced Research Projects Agency for Health: Building Resilient Environments for Air and Total Health (ARPA-H:BREATHE) program, developing targets for real-time diagnostics. His emerging work integrates environmental determinants of health with digital brain twin modeling for neurodegenerative disease research.