Prevalence and Genomic Sequence Analysis of Domestic Cat Hepadnavirus in the United States

Hepadnaviruses are partially double-stranded DNA viruses that infect a variety of species. The prototypical virus in this family is the human hepatitis B virus, which chronically infects approximately 400 million people worldwide and is a risk factor for progressive liver disease and liver cancer. The first hepadnavirus isolated from carnivores was a domestic cat hepadnavirus (DCH), initially identified in Australia and subsequently detected in cats in Europe and Asia. As with all characterized hepadnaviruses so far, DCH infection has been associated with hepatic disease in its host. Prevalence of this infection in the United States has not been explored broadly. Thus, we utilized conventional and quantitative PCR to screen several populations of domestic cats to estimate DCH prevalence in the United States. We detected DCH DNA in 1 out of 496 animals (0.2%) in the U.S. cohort. In contrast, we detected circulating DCH DNA in 7 positive animals from a cohort of 67 domestic cats from Australia (10.4%), consistent with previous studies. The complete consensus genome of the U.S. DCH isolate was sequenced by Sanger sequencing with overlapping PCR products. An in-frame deletion of 157 bp was identified in the N-terminus of the core open reading frame. The deletion begins at the direct repeat 1 sequence (i.e., the 5′ end of the expected double-stranded linear DNA form), consistent with covalently closed circular DNA resultant from illegitimate recombination described in other hepadnaviruses. Comparative genome sequence analysis indicated that the closest described relatives of the U.S. DCH isolate are those previously isolated in Italy. Motif analysis supports DCH using NTCP as an entry receptor, similar to human HBV. Our work indicates that chronic DCH prevalence in the U.S. is likely low compared to other countries

Facilitating a more efficient commercial review process for pediatric drugs and biologics

Over the past two decades, the biopharmaceutical industry has seen unprecedented expansion and innovation in concert with significant technological advancements. While the industry has experienced marked growth, the regulatory system in the United States still operates at a capacity much lower than the influx of new drug and biologic candidates. As a result, it has become standard for months or even years of waiting for commercial approval by the U.S. Food and Drug Administration. These regulatory delays have generated a system that stifles growth and innovation due to the exorbitant costs associated with awaiting approval from the nation’s sole regulatory agency. The recent re-emergence of diseases that impact pediatric demographics represents one particularly acute reason for developing a regulatory system that facilitates a more efficient commercial review process. Herein, we present a range of initiatives that could represent early steps toward alleviating the delays in approving life-saving therapeutics

Data_Sheet_1_Apathogenic proxies for transmission dynamics of a fatal virus.pdf

Identifying drivers of transmission—especially of emerging pathogens—is a formidable challenge for proactive disease management efforts. While close social interactions can be associated with microbial sharing between individuals, and thereby imply dynamics important for transmission, such associations can be obscured by the influences of factors such as shared diets or environments. Directly-transmitted viral agents, specifically those that are rapidly evolving such as many RNA viruses, can allow for high-resolution inference of transmission, and therefore hold promise for elucidating not only which individuals transmit to each other, but also drivers of those transmission events. Here, we tested a novel approach in the Florida panther, which is affected by several directly-transmitted feline retroviruses. We first inferred the transmission network for an apathogenic, directly-transmitted retrovirus, feline immunodeficiency virus (FIV), and then used exponential random graph models to determine drivers structuring this network. We then evaluated the utility of these drivers in predicting transmission of the analogously transmitted, pathogenic agent, feline leukemia virus (FeLV), and compared FIV-based predictions of outbreak dynamics against empirical FeLV outbreak data. FIV transmission was primarily driven by panther age class and distances between panther home range centroids. FIV-based modeling predicted FeLV dynamics similarly to common modeling approaches, but with evidence that FIV-based predictions captured the spatial structuring of the observed FeLV outbreak. While FIV-based predictions of FeLV transmission performed only marginally better than standard approaches, our results highlight the value of proactively identifying drivers of transmission—even based on analogously-transmitted, apathogenic agents—in order to predict transmission of emerging infectious agents. The identification of underlying drivers of transmission, such as through our workflow here, therefore holds promise for improving predictions of pathogen transmission in novel host populations, and could provide new strategies for proactive pathogen management in human and animal systems.</p