Applications of Bayesian Phylodynamic Methods in a Recent U.S. Porcine Reproductive and Respiratory Syndrome Virus Outbreak

Abstract

Classical phylogenetic methods such as neighbor-joining or maximum likelihood trees, provide limited inferences about the evolution of important pathogens and ignore important evolutionary parameters and uncertainties, which in turn limits decision making related to surveillance, control, and prevention resources. Bayesian phylodynamic models have recently been used to test research hypotheses related to evolution of infectious agents. However, few studies have attempted to model the evolutionary dynamics of porcine reproductive and respiratory syndrome virus (PRRSV) and, to the authors' knowledge, no attempt has been made to use large volumes of routinely collected data, sometimes referred to as big data, in the context of animal disease surveillance. The objective of this study was to explore and discuss the applications of Bayesian phylodynamic methods for modeling the evolution and spread of a notable 1-7-4 RFLP-type PRRSV between 2014 and 2015. A convenience sample of 288 ORF5 sequences was collected from 5 swine production systems in the United States between September 2003 and March 2015. Using coalescence and discrete trait phylodynamic models, we were able to infer population growth and demographic history of the virus, identified the most likely ancestral system (root state posterior probability = 0.95) and revealed significant dispersal routes (Bayes factor > 6) of viral exchange among systems. Results indicate that currently circulating viruses are evolving rapidly, and show a higher level of relative genetic diversity over time, when compared to earlier relatives. Biological soundness of model results is supported by the finding that sow farms were responsible for PRRSV spread within the systems. Such results cannot be obtained by traditional phylogenetic methods, and therefore, our results provide a methodological framework for molecular epidemiological modeling of new PRRSV outbreaks and demonstrate the prospects of phylodynamic models to inform decision-making processes for routine surveillance and, ultimately, to support prevention and control of food animal disease at local and regional scales.

Keywords: Bayesian phylodynamics; ORF5 gene; PRRSV; RFLP type 1-7-4; molecular surveillance.

Figure 1

PRRSV RFLP 1-7-4 cluster filtering. (A) Maximum likelihood tree of complete PRRSV sequence dataset (N = 6774) with the 1-7-4 cluster expanded. (B) The ML tree of extracted sequences containing the 1-7-4 cluster. Two nearest neighbor 1-7-4 RFLP types (green dots) were collected in August 2012 and March 2007. Two red dots indicated a 1-7-4 type isolated in January 2004 and a 1-4-4 type isolated in October 2006. The figure was generated from File S1.

Figure 2

Bayesian Skyline plots (BSP) illustrating temporal changes in the relative genetic diversity of Porcine Reproductive and Respiratory Syndrome Virus RFLP type 1-7-4 isolated between September 2003 and March 2015 in the United States estimated from the ORF5 gene sequences. Line plots summarize estimates of the effective population size (N_eT), a measure of genetic diversity, for ORF5 gene segment; the shaded regions correspond to the 95% HPD (Upper, Red; Median, Blue; Lower, Green).

Figure 3

Maximum clade credibility (MCC) phylogenies of ORF5 gene of Porcine Reproductive and Respiratory Syndrome Virus RFLP type 1-7-4 cluster in the United States. The color of the branches represents the most probable system type of their descendent nodes. The color-coding corresponds to the upper left figure, which represents the regional system root state posterior probability (RSPP) distributions. The figure was generated from File S6.

Figure 4

Bayes factor (BF) test for significant non-zero rates in ORF5 gene of Porcine Reproductive and Respiratory Syndrome Virus RFLP type 1-7-4 cluster in the United States. Only rates supported by a BF greater than six are indicated. The color of lines correspond to the probability of the inferred transmission rates. Blue and red line gradients indicate relatively weak to strong support, respectively. Site locations for the five systems (A–E) were anonymous and therefore latitude and longitude locations were placed in Alaska.

Figure 5

Maximum clade credibility (MCC) phylogenies of ORF5 gene of Porcine Reproductive and Respiratory Syndrome Virus RFLP type 1-7-4 cluster in the United States. The color of the branches represents the most probable farm type of their descendent nodes. The color-coding corresponds to the upper left figure, which represents the production type root state posterior probability (RSPP) distributions. Black branches in the tree indicate posterior probability < 0.60. The figure was generated from File S7.