David J. Duffy | Geology Reports

USGS2025

Shotgun sequencing of airborne eDNA achieves rapid assessment of whole biomes, population genetics and genomic variation

Biodiversity and its associated genetic diversity are being lost at an unprecedented rate. Simultaneously, the distributions of flora, fauna, fungi, microbes and pathogens are rapidly changing. Novel technology can help to capture and record genetic diversity before it is lost and to measure population shifts and pathogen distributions. Here we report the rapid application of shotgun long-read environmental DNA (eDNA) analysis for non-invasive biodiversity, genetic diversity and pathogen assessments from air. We also compared air eDNA with water and soil eDNA. Coupling long-read sequencing with established cloud-based biodiversity pipelines enabled a 2-day turnaround from airborne sample collection to completed analysis by a single investigator. To determine the full utility of airborne eDNA, we also conducted a local bioinformatic analysis and deep short-read shotgun sequencing. From outdoor air eDNA alone, comprehensive genetic analysis was performed, including population genetics (phylogenetic placement) of a charismatic mammal (bobcat, Lynx rufus ) and a venomous spider (golden silk orb weaver, Trichonephila clavipes ), and haplotyping humans ( Homo sapiens ) from natural complex community settings, such as subtropical forests and temperate locations. The rich datasets also enabled deeper analysis of specific species and genomic regions of interest, including viral variant calling, human variant analysis and antimicrobial resistance gene surveillance from airborne DNA. Our results highlight the speed, versatility and specificity of pan-biodiversity monitoring via non-invasive eDNA sampling using current benchtop/portable and cloud-based approaches. Furthermore, they reveal the future feasibility of scaling down (equipment and temporally) these approaches for near real-time analysis. Together these approaches can enable rapid simultaneous detection of all life and its genetic diversity from air, water and sediment samples for unbiased non-targeted information-rich genomics-empowered (1) biodiversity monitoring, (2) population genetics, (3) pathogen and disease-vector genomic surveillance, (4) allergen and narcotic surveillance, (5) antimicrobial resistance surveillance and (6) bioprospecting.

Nature Ecology & Evolution↗

USGS2023

Green turtle fibropapillomatosis: Tumor morphology and growth rate in a rehabilitation setting

Fibropapillomatosis (FP) is a neoplastic disease most often found in green turtles ( Chelonia mydas ). Afflicted turtles are burdened with potentially debilitating tumors concentrated externally on the soft tissues, plastron, and eyes and internally on the lungs, kidneys, and the heart. Clinical signs occur at various levels, ranging from mild disease to severe debilitation. Tumors can both progress and regress in affected turtles, with outcomes ranging from death due to the disease to complete regression. Since its official description in the scientific literature in 1938, tumor growth rates have been rarely documented. In addition, FP tumors come in two very different morphologies; yet, to our knowledge, there have been no quantified differences in growth rates between tumor types. FP tumors are often rugose in texture, with a polypoid to papillomatous morphology, and may or may not be pedunculated. In other cases, tumors are smooth, with a skin-like surface texture and little to no papillose structures. In our study, we assessed growth-rate differences between rugose and smooth tumor morphologies in a rehabilitation setting. We measured average biweekly tumor growth over time in green turtles undergoing rehabilitation at the University of Florida Whitney Laboratory Sea Turtle Hospital in St. Augustine, Florida, and compared growth between rugose and smooth tumors. Our results demonstrate that both rugose and smooth tumors follow a similar active growth progression pattern, but rugose tumors grew at significantly faster rates ( p = 0.013) than smooth ones. We also documented regression across several examined tumors, ranging from −0.19% up to −10.8% average biweekly negative growth. Our study offers a first-ever assessment of differential growth between tumor morphologies and an additional diagnostic feature that may lead to a more comprehensive understanding and treatment of the disease. We support the importance of tumor morphological categorization (rugose versus smooth) being documented in future FP hospital- and field-based health assessments.

Veterinary Sciences↗