PRRSV-2 variant classification: a dynamic nomenclature for enhanced monitoring and surveillance

mSphere, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 23, 2025

ABSTRACT Existing genetic classification systems for porcine reproductive and respiratory syndrome virus type 2 (PRRSV-2), such as restriction fragment length polymorphisms sub-lineages, are unreliable indicators of close relatedness or lack sufficient resolution epidemiological monitoring routinely conducted by veterinarians. Here, we outline a fine-scale system PRRSV-2 variants in the United States. Based on >25,000 U.S. open reading frame 5 (ORF5) sequences, sub-lineages were divided into using clustering algorithm. Through classifying new sequences every 3 months systematically identifying across 8 years, demonstrated that prospective implementation variant produced robust, reproducible results time can dynamically accommodate diversity arising from evolution. From 2015 to 2023, 118 identified, with ~48 active per year, which 26 common (detected >50 times). Mean within-variant distance was 2.4% (max: 4.8%). The mean closest related 4.9%. A updated webtool ( https://stemma.shinyapps.io/PRRSLoom-variants/ ) developed is publicly available end users assign newly generated ID. This relies onward; further efforts required extend this older international sequences. Finally, demonstrate how better discriminate between previous strains farm, determine possible sources introductions farm/system, track emerging regionally. Adoption will enhance monitoring, research, communication, improve industry responses variants. IMPORTANCE development represent significant advancement occurrence swine industry. applied criteria identification national-scale sequence data, addresses shortcomings existing methods offering higher adaptability capture provides stable method variants, facilitated freely regularly use veterinarians diagnostic labs. Although currently based ORF5 be expanded include other countries, paving way standardized global system. By enabling accurate improved discrimination significantly enhances ability monitor, respond outbreaks, ultimately supporting management control strategies

Language: Английский

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Phylogenetic-based methods for fine-scale classification of PRRSV-2 ORF5 sequences: a comparison of their robustness and reproducibility

Frontiers in Virology, Journal Year: 2024, Volume and Issue: 4

Published: Aug. 13, 2024

Disease management and epidemiological investigations of porcine reproductive respiratory syndrome virus-type 2 (PRRSV-2) often rely on grouping together highly related sequences. In the USA, last five years have seen a major shift within swine industry when classifying PRRSV-2, beginning to move away from RFLP (restriction fragment length polymorphisms)-typing adopting use phylogenetic lineage-based classification. However, lineages sub-lineages are large genetically diverse, making them insufficient for identifying new emerging variants. Thus, lineage system, dynamic fine-scale classification scheme is needed provide better resolution relatedness PRRSV-2 viruses inform disease monitoring efforts facilitate research communication surrounding circulating PRRSV viruses. Here, we compare systems variants (i.e., genetic clusters closely ORF5 sequences at finer scales than sub-lineage) using database 28,730 2010 2021, representing >55% U.S. pig population. total, compared 140 approaches that differed in their tree-building method, criteria, thresholds defining trees. Three resulted variant classifications were reproducible robust even input data or phylogenies changed. For these approaches, average distance among belonging same was 2.1–2.5%, divergence between 2.5–2.7%. Machine learning algorithms trained assign an existing with >95% accuracy, which shows newly generated can be assigned without repeating clustering analyses. Finally, identified 73 sequence-clusters (dated <1 year apart close relatedness) associated circulation events single farms. The percent farm ID change 6.5–8.7% our approaches. contrast, ~43% had variation RFLP-type, further demonstrating how proposed system addresses shortcomings RFLP-typing. Through this work lays foundation would more reliably group field decision-making management.

Language: Английский

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Repeat offenders: PRRSV-2 clinical re-breaks from a whole genome perspective

Veterinary Microbiology, Journal Year: 2025, Volume and Issue: 302, P. 110411 - 110411

Published: Jan. 29, 2025

Language: Английский

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Immunological drivers of zoonotic virus emergence, evolution, and endemicity

Immunity, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

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Phylogenetic-based methods for fine-scale classification of PRRSV-2 ORF5 sequences: a comparison of their robustness and reproducibility

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 15, 2024

Abstract Disease management and epidemiological investigations of porcine reproductive respiratory syndrome virus-type 2 (PRRSV-2) often rely on grouping together highly related sequences. In the USA, last five years have seen a major paradigm shift within swine industry when classifying PRRSV-2, beginning to move away from RFLP (restriction fragment length polymorphisms)-typing adopting use phylogenetic lineage-based classification. However, lineages sub-lineages are large genetically diverse, rapid mutation rate PRRSV coupled with global prevalence disease has made it challenging identify new emerging variants. Thus, lineage system, dynamic fine-scale classification scheme is needed provide better resolution relatedness PRRSV-2 viruses inform monitoring efforts facilitate research communication surrounding circulating viruses. Here, we compare potential systems for variants (i.e., genetic clusters closely ORF5 sequences at finer scales than sub-lineage) using database 28,730 2010 2021, representing >55% U.S. pig population. total, compared 140 approaches that differed in their tree-building method, criteria, thresholds defining trees TreeCluster . Three produced epidemiologically meaningful ≥5 per cluster), resulted reproducible robust outputs even input data or phylogenies were changed. three best performing approaches, average distance amongst belonging same variant was 2.1 – 2.5%, divergence between 2.5-2.7%. Machine learning algorithms also trained assign an existing >95% accuracy, which shows newly generated could be assigned without repeating clustering analyses. Finally, identified 73 sequence-clusters (dated <1 year apart close relatedness) associated circulation events single farms. The percent farm ID change 6.5-8.7% our approaches. contrast, ∼43% had variation RFLP-type, further demonstrating how proposed system addresses shortcomings RFLP-typing. Through identifying this work lays foundation would more reliably group field improved clarity decision-making management.

Language: Английский

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Machine learning approaches for estimating cross-neutralization potential among FMD serotype O viruses

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 24, 2024

Abstract In this study, we aimed to develop an algorithm that uses sequence data estimate cross-neutralization between serotype O foot-and-mouth disease viruses (FMDV) based on r1 values, while identifying key genomic sites associated with high or low values. The ability potential among co-circulating FMDVs in silico is significant for vaccine developers, animal health agencies making herd immunization decisions, and preparedness. Using published virus neutralization titer (VNT) assays VP1 sequences from GenBank, applied machine learning algorithms (BORUTA random forest) predict cross-reaction serum/vaccine-virus pairs 73 distinct FMDV strains. Model optimization involved tenfold cross-validation sub-sampling address imbalance improve performance. predictors included amino acid distances, site-wise polymorphisms, differences N-glycosylation sites. dataset comprised 108 observations (serum-virus pairs) Observations were dichotomized using a 0.3 threshold, yielding putative non-cross-neutralizing (< values) cross-neutralizing groups (≥ values). best model had training accuracy, sensitivity, specificity of 0.96 (95% CI: 0.88-0.99), 0.93, 0.96, respectively, accuracy 0.94 0.71-1.00), sensitivity 1.00, positive, negative predictive values 0.60 one testing AUC, specificity, all approaching 1.00 second dataset. Additionally, positions 48, 100, 135, 150, 151 the region alongside distance found be important cross-neutralization. Our study highlights value genetic/genomic informing strategies management understanding immune-mediated competition amongst related endemic strains field. We also showcase leveraging routinely generated applying parsimonious expedite decision-making selection candidates application vaccines controlling FMD, particularly O. A similar approach can other serotypes.

Language: Английский

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Linear epitopes of PRRSV-1 envelope proteins ectodomains are not correlated with broad neutralization

Porcine Health Management, Journal Year: 2024, Volume and Issue: 10(1)

Published: Oct. 21, 2024

Abstract Background Neutralizing antibodies against PRRSV are capable of conferring protection viral reinfection, but they tend to be strain specific and usually have poor cross-reactivity. Nonetheless, it has been described that there individuals efficiently neutralizing viruses different origin, so is expected conserved epitopes relevant for broad neutralization. However, although immunodominant regions in envelope proteins, their role neutralization unknown. The main objective this study was determine whether the linear existing ectodomains proteins play a cross-neutralization. Results A pepscan analysis carried out using synthetic peptides PRRSV-hyperimmune sera results obtained confirm existence antigenic GP2, GP3, GP4 GP5 relatively among isolates. these immunogenicity since only recognized by limited number sera. Furthermore, no differences were found between reactivity with cross-neutralization capacity heterologous activity, which indicate not development broadly reactive antibodies. Subsequently, some selected used competition assays virus binding cell receptors seroneutralization inhibition incubation hyperimmune Firstly, interfere infectivity identified assays, case one isolate, points possible strain-dependent inhibition. assay that, under conditions our study, none inhibiting Conclusions analyzed do major induction antibodies, could probably depend on conformational neutralizing.

Language: Английский

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