Modeling suggests gene editing combined with vaccination could eliminate a persistent disease in livestock

Recent breakthroughs in gene-editing technologies that can render individual animals fully resistant to infections may offer unprecedented opportunities for controlling future epidemics in farm animals. Yet, their potential for reducing disease spread is poorly understood as the necessary theoretical framework for estimating epidemiological effects arising from gene-editing applications is currently lacking. Here, we develop semistochastic modeling approaches to investigate how the adoption of gene editing may affect infectious disease prevalence in farmed animal populations and the prospects and time scale for disease elimination. We apply our models to the porcine reproductive and respiratory syndrome (PRRS), one of the most persistent global livestock diseases to date. Whereas extensive control efforts have shown limited success, recent production of gene-edited pigs that are fully resistant to the PRRS virus have raised expectations for eliminating this deadly disease. Our models predict that disease elimination on a national scale would be difficult to achieve if gene editing was used as the only disease control. However, from a purely epidemiological perspective, disease elimination may be achievable within 3 to 6 y, if gene editing were complemented with widespread and sufficiently effective vaccination. Besides strategic distribution of genetically resistant animals, several other key determinants underpinning the epidemiological impact of gene editing were identified.

Novel genomic technologies such as gene editing offer promising opportunities to tackle some of the most pressing global challenges humanity faces today. They provide new prospects to solving emerging threats such as the global COVID-19 pandemic (1) as well as to long-standing global health issues such as the HIV/AIDS crisis (2) or malnutrition (3, 4), with minimal side effects. Besides the medical field, food production stands to gain most from widespread use of genome editing technologies. Currently 11% of the human population suffers malnourishment (5), and this is expected to increase with the projected growth of the human population to 10.9 billion by 2100 (42%) (6). Meeting the 60% increase of agricultural production needed to provide sustainable and nutritious diets will likely require transformative innovations to existing production methods (7). While genome-editing technologies have been applied widely in plant breeding to simultaneously improve production and resilience to diverse stressors (see ref. 8 for examples), their application in the livestock sector is still in its infancy, primarily due to technical limitations associated with the gene-editing process itself and the safe and fast dissemination of edits, as well as ethical and societal concerns (9). Nevertheless, breakthroughs in genetic modification of farm animals through genome editing start to emerge with drastic improvements in efficiency traits (10, 11), animal welfare (12), and disease resistance (13, 14). Improving disease resistance in livestock seems particularly pertinent, as infectious diseases affect the entire food production chain and its economic viability (15).The recent scientific breakthroughs in genome editing raise expectations for radical shifts in infectious disease control in livestock (14). Although many countries currently lack specific regulations covering the application of genome-edited animals in the food chain, this technology currently falls under genetically modified organism legislation in countries that have such processes. Reflecting this, we are seeing the rapid development of gene-editing regulations worldwide [see the Global Gene Editing Regulation Tracker (16) for an up-to-date status of gene-editing regulations per country]. Specifically, some countries have identified that some genome-editing strategies are exempt from regulatory approval. This is reflected in the recent announcement in Japan that a genome-edited seabream does not need to be regulated as no gene has been introduced into the genome (17, 18). These developments make it realistic that application of gene editing to help control infectious disease is likely in the near future. This prospect evokes pressing questions concerning the theoretical and practical feasibility of tackling diseases for which conventional control methods have failed. It is currently not known how to best implement gene-editing-induced disease resistance to achieve noticeable reduction in disease prevalence and possibly even eliminate the disease on a national scale, and on what time scale such ambitious goals could be achieved.These questions are impossible to address in an entirely hypothetical context since epidemiological characteristics affecting the spread of the disease in question and the dynamics of the dispersal of resistant animals within the population play important roles in the success of the scheme. In this study, we focus on a particular disease, porcine reproductive and respiratory syndrome (PRRS), for the development of a mathematical modeling framework to investigate the feasibility of the application of gene editing to achieve disease elimination. PRRS represents one of the most important infectious disease problems for the pig industry worldwide, with economic losses estimated at $2.5 billion per annum in the United States and Europe alone (19, 20). Despite extensive global control efforts, the disease continues to persist in national commercial pig populations, largely due to high genetic heterogeneity of the PRRS virus, PRRSV (21), and the associated limited effectiveness of all PRRS vaccines (22, 23) and limited reliability of diagnostic tests (24, 25). There is considerable natural genetic variation in pigs’ responses to PRRSV infection, but evidence to date suggests that no pig strain is naturally fully resistant to it (26). However, recent advances in gene editing of porcine macrophages, in which a simple disruption of the CD163 gene confers complete resistance to infection with PRRSV, may revolutionize future PRRS control (27–29).To exploit the full potential of gene editing for PRRS control, we here develop a theoretical proof-of-concept model to address a number of crucial research questions. To what extent can gene editing help reduce PRRS prevalence in national commercial pig populations? Is it possible to eliminate this disease through gene editing by creating a disease-resistant subpopulation adequately dispersed within the national susceptible population? If so, what proportion of pigs would have to be PRRSV-resistant and how would these animals need to be distributed across herds?It is unlikely that gene editing will fully replace existing control methods, such as widespread vaccination. Hence, we also use our model to investigate the epidemiological effects of gene editing and vaccination combined. Finally, we investigate how fast the required proportion of resistant animals could be introduced in a national commercial pig population, if gene editing was strictly limited to breeding programs and resistance alleles propagate to commercial pigs using current industry practices with their diverse technical limitations. This last question becomes particularly important for an RNA virus with a high evolutionary rate such as PRRSV, since escape mutants of the virus might limit the shelf-life of gene editing and vaccines in terms of effectiveness (14, 30).We address these questions with two linked simulation models: 1) an epidemiological model to simulate the effects of different disease control schemes on PRRS prevalence in a national commercial pig population and 2) a gene flow model to simulate the propagation of PRRSV resistance alleles from breeding programs that routinely carry out gene editing for PRRS resistance into the commercial population. The epidemiological model provides insight into the numbers and distribution of genetically resistant pigs required to eliminate PRRS under a range of realistic scenarios. The allele propagation model subsequently provides estimates for the time required to realistically produce this required number of genetically resistant pigs.Our proof-of-concept model provides quantitative estimates for how gene editing may reduce infectious disease prevalence in farm animals and the required time frame and criteria for eliminating a disease on a national level.