Orf virus (ORFV) is the etiological agent of Contagious Ecthyma (CE) disease that mainly affects sheep, goats, wild ruminants, and humans with a worldwide distribution. To date, only two strains from Argentinian sheep have been characterized at the molecular level and there is little information on ORFV strains circulating in Argentina. Here we describe and analyze five outbreaks of CE in goats in three geographic regions of the country: Northwest, Center, and Southwest. The phylogenetic analysis based on four molecular markers of ORFV (orf011 partial sequence and orf020, orf109, and orf127 complete sequence genes) revealed that there are different strains circulating in Argentina and pointed out the importance of knowing the health status of animals traded between farms.

Avian infectious laryngotracheitis (ILT) is a worldwide infectious disease that causes important economic losses in the poultry industry. Although it is known that ILT virus (ILTV) is present in Argentina, there is no information about the circulating strains. With the aim to characterize them, seven different genomic regions (thymidine kinase, glycoproteins D, G, B, C, and J, and infected cell polypeptide 4) were partially sequenced and compared between field samples. The gJ sequence resulted to be the most informative segment, it allowed the differentiation among field sample strains, and also, between wild and vaccine viruses. Specific changes in selected nucleotidic positions led to the definition of five distinct haplotypes. Tests for detection of clustering were run to test the null hypothesis that ILTV haplotypes were randomly distributed in time in Argentina and in space in the most densely populated poultry region of this country, Entre Rios. From this study, it was possible to identify a 46 km radius cluster in which higher proportions of haplotypes 4 and 5 were observed, next to a provincial route in Entre Rios and a significant decline of haplotype 5 between 2009 and 2011. Results here provide an update on the molecular epidemiology of ILT in Argentina, including data on specific genome segments that may be used for rapid characterization of the virus in the field. Ultimately, results will contribute to the surveillance of ILT in the country.

Deep sequencing of viral genomes is a powerful tool to study RNA virus complexity. However, the analysis of next-generation sequencing data might be challenging for researchers who have never approached the study of viral quasispecies by this methodology. In this work we present a suitable and affordable guide to explore the sub-consensus variability and to reconstruct viral quasispecies from Illumina sequencing data. The guide includes a complete analysis pipeline along with user-friendly descriptions of software and file formats. In addition, we assessed the feasibility of the workflow proposed by analyzing a set of foot-and-mouth disease viruses (FMDV) with different degrees of variability. This guide introduces the analysis of quasispecies of FMDV and other viruses through this kind of approach.

The COVID-19 pandemic has lately been driven by Omicron. This work aimed to study the dynamics of SARS-CoV-2 Omicron lineages during the third and fourth waves of COVID-19 in Argentina. Molecular surveillance was performed on 3431 samples from Argentina, between EW44/2021 and EW31/2022. Sequencing, phylogenetic and phylodynamic analyses were performed. A differential dynamic between the Omicron waves was found. The third wave was associated with lineage BA.1, characterized by a high number of cases, very fast displacement of Delta, doubling times of 3.3 days and a low level of lineage diversity and clustering. In contrast, the fourth wave was longer but associated with a lower number of cases, initially caused by BA.2, and later by BA.4/BA.5, with doubling times of about 10 days. Several BA.2 and BA.4/BA.5 sublineages and introductions were detected, although very few clusters with a constrained geographical distribution were observed, suggesting limited transmission chains. The differential dynamic could be due to waning immunity and an increase in population gatherings in the BA.1 wave, and a boosted population (for vaccination or recent prior immunity for BA.1 infection) in the wave caused by BA2/BA.4/BA.5, which may have limited the establishment of the new lineages.

Molecular knowledge of virus–antibody interactions is essential for the development of better vaccines and for a timely assessment of the spread and severity of epidemics. For foot-and-mouth disease virus (FMDV) research, in particular, computational methods for antigen–antibody (Ag–Ab) interaction, and cross-antigenicity characterization and prediction are critical to design engineered vaccines with robust, long-lasting, and wider response against different strains. We integrated existing structural modeling and prediction algorithms to study the surface properties of FMDV Ags and Abs and their interaction. First, we explored four modeling and two Ag–Ab docking methods and implemented a computational pipeline based on a reference Ag–Ab structure for FMDV of serotype C, to be used as a source protocol for the study of unknown interaction pairs of Ag–Ab. Next, we obtained the variable region sequence of two monoclonal IgM and IgG antibodies that recognize and neutralize antigenic site A (AgSA) epitopes from South America serotype A FMDV and developed two peptide ELISAs for their fine epitope mapping. Then, we applied the previous Ag–Ab molecular structure modeling and docking protocol further scored by functional peptide ELISA data. This work highlights a possible different behavior in the immune response of IgG and IgM Ab isotypes. The present method yielded reliable Ab models with differential paratopes and Ag interaction topologies in concordance with their isotype classes. Moreover, it demonstrates the applicability of computational prediction techniques to the interaction phenomena between the FMDV immunodominant AgSA and Abs, and points out their potential utility as a metric for virus-related, massive Ab repertoire analysis or as a starting point for recombinant vaccine design.