Location: Foreign Arthropod Borne Animal Disease Research
2022 Annual Report
Objectives
OBJECTIVE 1: Identify factors associated with Flavivirus infections, pathogenesis, and maintenance in vectors and animal hosts to inform prevention and mitigation strategies.
• Identify factors associated with JEV maintenance in relevant insect vectors.
• Characterize susceptibility, pathogenesis, and clinical disease of JEV in swine.
• Characterize vector-virus-host interactions associated with JEV transmission.
Sub-objective 1.A. Evaluate the ability of an emerging JEV genotype to infect and replicate in North American domestic swine and mosquito vectors.
Sub-objective 1.B. Investigate potential roles of North American feral swine and biting midges in JEV transmission.
Approach
Japanese encephalitis virus (JEV) is a zoonotic arthropod-borne pathogen native to Asia and the Pacific Rim, where it is a significant cause of reproductive and neonatal loss in swine and severe encephalitis and death in humans. JEV is transmitted to vertebrate hosts by infected mosquito vectors and has demonstrated an ability to emerge in new geographic regions that contain competent vectors and susceptible hosts. JEV does not currently circulate in the United States (U.S.); however, the risk of its introduction has been assessed as high (Oliveira et al. 2020). Significant research gaps exist regarding U.S. vulnerability following an introduction of JEV, including the range of native vectors and hosts capable of sustaining transmission and whether U.S. mosquitoes and livestock are vulnerable to emerging genotypes of JEV. This project will address these gaps by evaluating the ability of an emerging JEV genotype to infect and replicate in domestic swine and mosquitoes and by investigating the potential roles of previously uncharacterized wildlife hosts and insect vectors in JEV transmission. These studies will use in vitro and in vivo infection models to investigate the effects of wild-type JE viruses on insect vectors and mammalian hosts (Objective 1). Additionally, next generation sequencing and genomic analyses will be used to study vector-virus-host interactions to determine effects that hosts and vectors have on virus populations. The knowledge gained will be used to inform risk assessments and predictive models and help identify target points to guide diagnostic development, surveillance programs, and control strategies. Together, these measures will help strengthen the U.S. disease prevention and response framework for rapidly stopping foreign animal disease incursions to protect the health and profitability of U.S. livestock.
Progress Report
This report is for the new project, 3022-32000-025-000D, entitled “Japanese Encephalitis Virus Prevention and Mitigation Strategies”, which began in January 2022. This project was preceded by project 3022-32000-023-000D. For information on that expired project, please see the final report for 3022-32000-023-000D.
In the partial year this project has been active, progress has been made on its single objective. Nine new collaborations were formed with six institutions to directly support or complement the project objective, including six collaborations with U.S. universities, one with a commercial partner, and two with international partners. New personnel were hired, filling critical science vacancies for the Research Leader (Supervisory Microbiologist) and Clinical Veterinary Medical Officer, as well as several important support staff vacancies. New Biosafety Level 2 (BSL-2) research spaces were identified, and the applicable regulatory permits and approvals were successfully acquired to initiate research in these spaces. Three new scientific staff members completed the rigorous training required to perform work in the Biosafety Level 3 (BSL-3) spaces at Kansas State University, Manhattan, Kansas, where much of this project’s research is currently conducted. As prerequisites to beginning research on the new project, new standard operating procedures (SOP) have been developed, and new protocols have been submitted to, and approved by, the Kansas State University Institutional Biosafety Committee and Institutional Animal Care and Use Committee.
Accomplishments
1. If you cannot beat them, eat them. Insects as animal and human food is coming closer to reality each year. Insects are a high-quality protein source that are much easier and cheaper to raise than traditional farm animals. ARS researchers at Manhattan, Kansas, and Kansas State University collaborators have been building giant suction traps to harvest insects to be used as animal feed from backyard farms and large-scale commercial livestock operations. These traps are economical to produce and made from parts found in a junkyard or a local hardware store. This innovation won the 2021 prize in the ARS high-risk, high-reward research funding competition, ARSX, and was evaluated on chicken farms. The trap was able to collect kilograms of house flies which, once disinfected, can be fed back to the chickens. These massive suction traps will reduce the use of insecticides and improve animal health by removing nuisance and biting insects while also producing a protein source for animals. But greater interest is in the sampled insects which can be used for pathogen surveillance. A small sample of collected insects are processed to survey for pathogens in the surrounding area. Early detection of circulating pathogens is an early warning system prior to the onset of clinical cases or an outbreak in the farmed animals.
2. PICTUREE: Predicting Insect Contact and Transmission Using histoRical Entomological and Environmental data. PICTUREE is an outbreak forecasting tool developed by ARS researchers at Manhattan, Kansas, and Kansas State University. The tool helps planners with decision support to optimize provisioning and alignment of resources based on estimated risk for arthropod-transmitted pathogens. Current practices for vector-borne diseases are reactionary and retroactive for human health protection, but PICTUREE will provide a proactive and adaptive approach to preventing pathogens from becoming a health threat. The tool uses case data, rainfall, temperature, elevation, ecoregions, and disease vector life history stage models to predict when and where there is elevated risk of mosquito transmitted pathogens. The model makes forecasts using network-based computational models, ensemble Kalman filters, particle filters, and deep neural networks. These methods are combined to make an ensemble risk assessment. The predictions were used by the Department of Defense to determine when and where to start and stop mosquito surveillance, which saved them hundreds of thousands of dollars.
3. Molecular tools for identifying cryptic disease vector species. Cryptic species, or physically similar looking insects of different species, are a real problem when managing insect populations below a disease transmission threshold. When the insect species look similar, it is difficult to determine how many of the disease vector species are transmitting pathogens in the wild. ARS researchers at Manhattan, Kansas, and Texas A&M University in College Station, Texas, developed molecular tools to differentiate vector and non-vector species. A consequence of these studies was that the traditional three species of the vector complex was elevated to five species, one of which was the discovery of a previously undescribed species. These new methods to identify the geographic range and identify of collected insects allows for more accurate models of species distributions and better explains the patterns of disease outbreaks throughout the central United States.
Review Publications
Humphreys Jr, J.M., Young, K.M., Cohnstaedt, L.W., Haney, K., Peters, D.C. 2021. Vector surveillance, host species richness, and demographic factors as neuroinvasive West Nile Disease risk factors. Viruses and Bacteriophages. 13:5. https://doi.org/10.3390/v13050934.
Ferdousi, T., Cohnstaedt, L.W., Scoglio, C. 2021. A windowed correlation based feature selection method to improve time series prediction of dengue fever cases. IEEE Access. 9:141210-141222. https://doi.org/10.1109/ACCESS.2021.3120309.
