Molecular Basis of Antigenic Drift in Serotype O Foot-and-Mouth Disease Viruses (2013–2018) from Southeast Asia

Upadhyaya, Sasmita; Mahapatra, Mana; Mioulet, Valérie; Parida, Satya

doi:10.3390/v13091886

Cited by 9 publications

(6 citation statements)

References 46 publications

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“…FMD is endemic in several countries in Asia. The main serotypes of FMDV circulating in this region are O, A, and Asia 1 [ 12 , 13 ]. Numerous countries in Southeast Asia, including Cambodia, Lao PDR, Malaysia, Myanmar, Thailand, and Vietnam, are endemic to FMD [ 9 , 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Time-Series Analysis for the Number of Foot and Mouth Disease Outbreak Episodes in Cattle Farms in Thailand Using Data from 2010–2020

Punyapornwithaya

Mishra

Sansamur

et al. 2022

Viruses

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Thailand is one of the countries where foot and mouth disease outbreaks have resulted in considerable economic losses. Forecasting is an important warning technique that can allow authorities to establish an FMD surveillance and control program. This study aimed to model and forecast the monthly number of FMD outbreak episodes (n-FMD episodes) in Thailand using the time-series methods, including seasonal autoregressive integrated moving average (SARIMA), error trend seasonality (ETS), neural network autoregression (NNAR), and Trigonometric Exponential smoothing state–space model with Box–Cox transformation, ARMA errors, Trend and Seasonal components (TBATS), and hybrid methods. These methods were applied to monthly n-FMD episodes (n = 1209) from January 2010 to December 2020. Results showed that the n-FMD episodes had a stable trend from 2010 to 2020, but they appeared to increase from 2014 to 2020. The outbreak episodes followed a seasonal pattern, with a predominant peak occurring from September to November annually. The single-technique methods yielded the best-fitting time-series models, including SARIMA(1,0,1)(0,1,1)12, NNAR(3,1,2)12,ETS(A,N,A), and TBATS(1,{0,0},0.8,{<12,5>}. Moreover, SARIMA-NNAR and NNAR-TBATS were the hybrid models that performed the best on the validation datasets. The models that incorporate seasonality and a non-linear trend performed better than others. The forecasts highlighted the rising trend of n-FMD episodes in Thailand, which shares borders with several FMD endemic countries in which cross-border trading of cattle is found common. Thus, control strategies and effective measures to prevent FMD outbreaks should be strengthened not only in Thailand but also in neighboring countries.

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Section: Introductionmentioning

confidence: 99%

Time-Series Analysis for the Number of Foot and Mouth Disease Outbreak Episodes in Cattle Farms in Thailand Using Data from 2010–2020

Punyapornwithaya

Mishra

Sansamur

et al. 2022

Viruses

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“…Sporadic diversification is a preferred method of evolution for many positive and negative single-stranded RNA viruses, which usually exhibit purifying selection acting on their genome due to their small sizes [ 12 ]. Genetic drift and spontaneous mutations are reported to be responsible for the antigenic change in FMDV [ 17 , 52 ]. The sporadic diversifying evolution is calculated using the dN/dS ratio, which has a risk of overestimation due to non-fixed mutations in the population.…”

Section: Discussionmentioning

confidence: 99%

Evolutionary Dynamics of Foot and Mouth Disease Virus Serotype A and Its Endemic Sub-Lineage A/ASIA/Iran-05/SIS-13 in Pakistan

Naqvi

Bostan

Fukai

et al. 2022

Viruses

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Foot and mouth disease (FMD) causes severe economic losses to the livestock industry of endemic countries, including Pakistan. Pakistan is part of the endemic pool 3 for foot and mouth disease viruses (FMDV), characterized by co-circulating O, A, and Asia 1 serotypes, as designated by the world reference laboratory for FMD (WRL-FMD). FMDV serotype A lineage ASIA/Iran-05 is widespread in buffalos and cattle populations and was first reported in Pakistan in 2006. This lineage has a high turnover, with as many as 10 sub-lineages reported from Pakistan over the years. In this study, we reconstructed the evolutionary, demographic, and spatial history of serotype A and one of its sub-lineages, A/ASIA/Iran-05/SIS-13, prevalent in Pakistan. We sequenced nearly complete genomes of three isolates belonging to sub-lineage A/ASIA/Iran-05/SIS-13. We estimated recombination patterns and natural selection acting on the serotype A genomes. Source and transmission routes in Pakistan were inferred, and the clustering pattern of isolates of the SIS-13 sub-lineage were mapped on a tree. We hereby report nearly complete genome sequences of isolates belonging to sub-lineage A/ASIA/Iran-05/SIS-13, along with purported recombinant genomes, and highlight that complete coding sequences can better elucidate the endemic history and evolutionary pressures acting on long-term co-circulating FMDV strains.

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“…Viruses utilized in these papers came from 14 countries. These manuscripts were obtained from a search from google and PubMed databases using the search terms 'FMDV and r1 values' and 'FMDV and vaccine matching' yielding 4 manuscripts (18)(19)(20)(21). To be included, the study must have followed standard WHOA (22) methodology for generation of r1 values for serotype O viruses using virus neutralization tests (VNTs), as well as have associated viral sequence data.…”

Section: Data Preparationmentioning

confidence: 99%

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

Makau,

Arzt,

VanderWaal

2024

Preprint

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

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Molecular Basis of Antigenic Drift in Serotype O Foot-and-Mouth Disease Viruses (2013–2018) from Southeast Asia

Cited by 9 publications

References 46 publications

Time-Series Analysis for the Number of Foot and Mouth Disease Outbreak Episodes in Cattle Farms in Thailand Using Data from 2010–2020

Time-Series Analysis for the Number of Foot and Mouth Disease Outbreak Episodes in Cattle Farms in Thailand Using Data from 2010–2020

Evolutionary Dynamics of Foot and Mouth Disease Virus Serotype A and Its Endemic Sub-Lineage A/ASIA/Iran-05/SIS-13 in Pakistan

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

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