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Why is PRRS virus so genetically diverse?

A better understanding of the natural history of PRRSV can provide insights that can potentially aid in mitigating the impact of the emergence of new viral variants.

By Igor Paploski, Cesar Corzo, Albert Rovira, Juan Sanhueza, Carles Vilalta and Kimberly VanderWaal, University of Minnesota Department of Veterinary Population Medicine; Declan Schroeder, University of Minnesota Department of Veterinary Population Medicine and University of Reading (United Kingdom) School of Biological Sciences; and Michael Murtaugh, In memoriam, University of Minnesota Department of Veterinary and Biomedical Sciences
Porcine reproductive and respiratory syndrome virus, the etiological agent of PRRS, is one of the most important endemic viruses affecting the swine industry in the United States1 and globally2. The economic impact of the disease in the United States alone was estimated at $664 million annually1.

PRRSV is divided into two major phylogenetic clades, PRRSV Type 1 (more prevalent in Europe) and Type 2 (more prevalent in North America)3. Genetic similarities between PRRSV isolates are often used as a tool to understand disease transmission and epidemiology4,5, and several strategies have been used for classifying isolates of PRRSV into epidemiologically meaningful groups. Restriction Fragment Length Polymorphism, commonly referred to as “RFLPs”, have been broadly adopted by the U.S. swine industry as a way to classify PRRSV isolates. However, shortcomings such as the unclear genetic relationship between RFLP types, the potential for two distantly related viruses to share the same RFLP type, and the instability of RFLP-typing when assessing isolates experimentally related to each other6 hinder interpretation of RFLP types.

In 2010, a classification system based on the phylogenetic relatedness of one portion of the PRRSV genome known as the open reading frame 5 (orf5) was proposed7,8. This classification system aggregates isolates into phylogenetic lineages based on the ancestral relationships and genetic distance among isolates. These lineages can be thought of as “ancestral families.” As compared to RFLPs, the relatedness among lineages are more intuitive and evolutionary trends across space and time can be tracked more easily. There are nine lineages known for PRRSV Type 2, each of which are approximately 11% different from one another in the average pairwise genetic distance7.

Despite control efforts involving improved biosecurity and different vaccination and exposure protocols, PRRSV continues to circulate and evolve. High levels of genetic and antigenic diversity are one of the foremost challenges in its control. Prior exposure to PRRS viruses results in varying protection against homologous and heterologous challenges, albeit the exact definition of what constitutes a homologous or heterologous challenge is often not clear, especially considering the genetic diversity existing within PRRSV Type 2.

Using more than 4,000 PRRSV orf5 sequences collected from 2009-17 from a single U.S. region curated by the University of Minnesota’s Morrison Swine Health Monitoring Project, we investigated how the occurrence of different lineages of PRRSV changed through time. We were able to document the sequential emergence of several PRRSV sub-lineages, including a sub-lineage containing most 1-7-4 viruses, which rapidly grew in prevalence to the point in which they were the most prevalent phylogenetic group occurring in the studied area at a given time. These emergence events appeared to occur every four or five years. Our group continues to analyze data to further understand factors related to these events.

The diversification and temporal dynamics of PRRSV observed in our dataset is consistent with the hypothesis that PRRSV long-term evolutionary patterns are at least partially modulated by immune-mediated selection. Veterinarians in farms might choose to expose their breeding herds and incoming gilts to different PRRS viruses (either from different vaccines or from wild viruses isolated on each farm). These practices combined with relatively high prevalence of immunity resulting from natural exposure likely create pig populations with high rates of PRRSV immunity, even if cross-protection is only partial. While high levels of herd immunity potentially diminish the odds or severity of future outbreaks due to “homologous” viruses, we hypothesize that partial immunity may also create selective pressure that might select for viruses that can “escape” or evade host immunity. As a virus evolves, immune responses generated against a past variant become less effective, resulting in a complex system where different PRRSV variants influence one another via the partial cross-immunity that they generate in the host population9,10. Theory predicts that due to frequency-dependent selection among co-circulating viral variants, rare genetic variants are expected to spread more widely in the host population but then subsequently decline as herd immunity rises.

This has important implications in identifying patterns of emergence and re-emergence of genetic variants of PRRSV that have negative impacts on the swine industry. Although the data analyzed here come from a single U.S. region, the general pattern of emergence and turnover of different lineages over time reflect an evolutionary phenomenon that should also occur in other U.S. regions. A better understanding of the natural history of PRRSV can provide insights that can potentially aid in mitigating the impact of the emergence of new viral variants as well as serving as a basis for further work exploring the evolution of PRRSV and the effect this has on disease control, management and impact on the industry. To that end, constant surveillance on PRRSV occurrence is crucial. Further studies utilizing whole genome sequencing and exploring the extent of cross-immunity between heterologous PRRS viruses could shed light on immunological response against PRRSV and aid in developing strategies that might be able to diminish disease impact.

References

  1. Holtkamp DJ, Kliebenstein JB, Neumann EJ, Zimmerman JJ, Rotto HF, Yoder TK, et al. Assessment of the economic impact of porcine reproductive and respiratory syndrome virus on United States pork producers. J Swine Heal Prod [Internet]. 2013;21(2):72-84.
  2. VanderWaal K, Perez A, Torremorrell M, Morrison RM, Craft M. Role of animal movement and indirect contact among farms in transmission of porcine epidemic diarrhea virus. Epidemics [Internet]. 2018 Sep;24:67-75.
  3. Stadejek T, Stankevicius A, Murtaugh MP, Oleksiewicz MB. Molecular evolution of PRRSV in Europe: Current state of play. Vet Microbiol [Internet]. 2013;165(1-2):21-8.
  4. Wesley RD, Mengeling WL, Lager KM, Clouser DF, Landgraf JG, Frey ML. Differentiation of a porcine reproductive and respiratory syndrome virus vaccine strain from North American field strains by restriction fragment length polymorphism analysis of ORF 5. J Vet Diagn Invest [Internet]. 1998 Apr;10(2):140-4.
  5. Kapur V, Elam MR, Pawlovich TM, Murtaugh MP. Genetic variation in porcine reproductive and respiratory syndrome virus isolates in the midwestern United States. J Gen Virol [Internet]. 1996 Jun 1;77(6):1271-6.
  6. Cha S-H, Chang C-C, Yoon K-J. Instability of the restriction fragment length polymorphism pattern of open reading frame 5 of porcine reproductive and respiratory syndrome virus during sequential pig-to-pig passages. J Clin Microbiol [Internet]. 2004 Oct;42(10):4462-7.
  7. Shi M, Lam TT-Y, Hon C-C, Murtaugh MP, Davies PR, Hui RK-H, et al. Phylogeny-Based Evolutionary, Demographical, and Geographical Dissection of North American Type 2 Porcine Reproductive and Respiratory Syndrome Viruses. J Virol [Internet]. 2010 Sep 1;84(17):8700-11. 
  8. Shi M, Lam TT-Y, Hon C-C, Hui RK-H, Faaberg KS, Wennblom T, et al. Molecular epidemiology of PRRSV: A phylogenetic perspective. Virus Res [Internet]. 2010 Dec;154(1-2):7-17.
  9. Gupta S, Ferguson N, Anderson R. Chaos, persistence, and evolution of strain structure in antigenically diverse infectious agents. Science [Internet]. 1998 May 8;280(5365):912-5. 
  10. Kucharski AJ, Andreasen V, Gog JR. Capturing the dynamics of pathogens with many strains. J Math Biol [Internet]. 2016;72(1-2):1-24.
 
Sources: Igor Paploski, Cesar Corzo, Albert Rovira, Juan Sanhueza, Carles Vilalta, Kimberly VanderWaal, Declan Schroeder and Michael Murtaugh, who are solely responsible for the information provided, and wholly own the information. Informa Business Media and all its subsidiaries are not responsible for any of the content contained in this information asset.
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