Frontiers in Virology

Borealpox virus (BRPV; formerly Alaskapox) is an orthopoxvirus that has caused seven reported human infections in Alaska since 2015, including a fatal case in 2023. The natural reservoir of BRPV is unknown, although previous investigations have raised the possibility of wild small mammals transmitting the virus to humans, either through direct contact or via domestic cats and dogs. To understand which species may be involved in the maintenance and/or spillover of BRPV in Alaska, we trapped and sampled wild small mammals (including voles, shrews, and squirrels) in 2021 and 2024 near reported human case locations in Fairbanks and the Kenai Peninsula, respectively. We found evidence of previous exposure to orthopoxviruses in five species (including the House Mouse, Mus musculus) and detected BRPV DNA as well as viable virus in Northern Red-backed Voles (Clethrionomys rutilus). Further, screening of tissues from historical museum specimens revealed BRPV DNA in C. rutilus specimens collected in Denali National Park and Preserve in 1998 and 1999, 17 years before the first reported human case of BRPV. Phylogenomic analysis of all human and animal BRPV isolates strongly supports the hypothesis of local human infections through multiple spillover events. These findings suggest C. rutilus as a possible reservoir species for BRPV and indicate that BRPV has been present in Alaskan wild small-mammal populations for at least 25 years. Our study highlights the potential of museum collections to elucidate the temporal, spatial, and host ranges of emerging pathogens. Further museum- and field-based sampling will clarify the true geographic range of BRPV, which is closely related to Old World orthopoxviruses and may be circulating beyond North America.

Okra (bhendi) is a widely cultivated food crop in warm regions of the world, with India contributing approximately 60% of global production. However, okra cultivation in India is severely constrained by viral diseases, among which infections caused by the geminiviruses bhendi yellow vein mosaic virus (BYVMV) and okra enation leaf curl virus (OELCuV), in association with their satellites, represent major limitations to crop productivity. In recent years, the geminivirus-encoded C4 protein has emerged as a key pathogenicity determinant in this viral family, with functions that include suppression of multiple layers of plant antiviral defence and induction of disease symptoms. Here, we comparatively characterize the C4 proteins of BYVMV and OELCuV by determining their targeting signals and subcellular localization, and by assessing their ability to induce developmental abnormalities and suppress the cell-to-cell spread of RNA silencing. Our results reveal that the two C4 proteins display distinct subcellular localization patterns, yet both are capable of inducing developmental alterations, likely through different mechanisms, and of suppressing the intercellular spread of RNA silencing, possibly via interaction with a common host factor. Together, these findings suggest that C4 might be a critical virulence factor in okra-infecting geminiviruses and act as a symptom determinant. The C4 proteins encoded by BYVMV and OELCuV therefore emerge as promising targets for the development of antiviral management strategies in okra.

In this study the phenotypic consequences of naturally occurring single nucleotide polymorphisms (SNPs) in the MERS-CoV Spike protein were investigated. The impact of Spike mutations on virus entry and neutralisation of contemporary MERS-CoV strains is not currently well understood. Naturally occurring mutations were identified by aligning 584 MERS-CoV Spike sequences from either human clinical isolates collected between 2012 - 2024 or from viruses passaged in human cells. Fifteen SNPs of interest occurring in the NTD, RBD and adjacent to the S1/S2 cleavage site were selected for further characterisation based on their location in the Spike protein, frequency and identification in previous studies. A representative clade B, lineage 5 wildtype Spike sequence, which reflected those carried by MERS-CoV viruses circulating in the Middle East, was used in this study. The mutations of interest were introduced to the wildtype backbone to generate Spike variants. A lentiviral-based pseudotyping system was then used to investigate the impact of these Spike mutations on entry and neutralisation. I529T, E536K and L745F were shown to improve MERS-CoV entry. L411F, T424I, L506F, L745F and T746K were found to increase resistance to neutralisation by pooled patient sera. This study has identified novel naturally occurring Spike mutations that resulted in phenotypic differences in virus entry and neutralisation of contemporary MERS-CoV strains. Continued investigation of the phenotypic consequences of naturally occurring MERS-CoV Spike mutations is essential for assessing the risk to public health, especially given the pandemic potential of this virus. ImportanceThe main aim of this study was to investigate the impact of naturally occurring MERS-CoV Spike mutations on virus entry and neutralisation. The phenotypic consequences of mutations occurring in the Spike protein of contemporary MERS-CoV strains are not currently well understood. Improving our understanding is of particular importance due to MERS-CoV continuing to pose a public health risk, with frequent spillover events and mounting evidence of human-to-human transmission since the virus emerged in 2012. A major concern is that as MERS-CoV continues to evolve, it may become more infectious, resulting in increased transmission between humans. To add to this, surveillance is limited and there are currently no specific medical countermeasures available to treat MERS-CoV disease. The MERS-CoV Spike pseudotyping system developed in this study is a useful tool that could be used alongside surveillance systems to rapidly assess novel Spike mutations in functional assays. This MERS-CoV pseudotyping system could also be used to aid the development of medical countermeasures such as vaccines, antivirals and antibody therapies.

Pneumonia virus of mice (PVM), the mouse homolog to respiratory syncytial virus (RSV), is increasingly used as surrogate model to study pneumovirus pathogenesis in a more natural pathogen-host relation. Two major strains of PVM, strain 15 and J3666 are currently used in laboratories, with preferences for either one or the other based on the well-documented isolation history of strain 15 or the suggested higher virulence of strain J3666. Using conventional and long read sequencing, we found that the PVM strain J3666 represents two distinct virus populations, which are defined by sequence and structure of the G and SH genes encoding the putative attachment and small hydrophobic proteins, in addition to further nucleotide polymorphisms. Specifically, a nucleotide polymorphism at position 65 in the G gene results in either an upstream open reading frame (uORF) preceding the main ORF in frame, or an extension of the major G ORF by 18 codons. The impact of the different forms of the J3666-G genes on PVM was examined by generating recombinant PVMs differing exclusively in the distinctive 5 portion of the respective G gene. This revealed that the population expressing a G protein with an extended main G ORF was more virulent, whereas the presence of a uORF attenuated virulence. The virulence of PVM correlated with increased expression levels of G, whereas attenuation was rather associated with downregulated expression of G due to the presence of a uORF. Thus, modulation of G protein levels may be an important mechanism by which pneumoviruses modulate virulence. ImportanceThe pneumonia virus of mice strain J3666 is considered a more virulent and more suitable model for severe lower respiratory tract infections. The organization of the gene for the attachment protein G is reported to contain a small upstream open reading frame (uORF) preceding the main G ORF in frame. The translated G protein is predicted to comprise 396 amino acids. We report that this virus strain may be a mixture of two different populations, each with differing virulence. The more virulent population encodes a G protein of potentially 414 amino acids instead of a small uORF. This G gene organization is associated with an increased G protein expression. Importantly, this organization of the G gene is in line with that of several newly identified pneumoviruses, i.e., canine and swine pneumoviruses. These viruses may comprise a distinct group within the Pneumoviridae family.

BackgroundGenetic drift and host-associated adaptation in influenza A viruses threaten the long-term reliability of RT-qPCR-based diagnostics, particularly when nucleotide mismatches arise within primer and probe binding regions. Conventional assay evaluations often emphasize sequence conservation but rarely assess functional mismatch tolerance across divergent subtypes and hosts. MethodsWe performed an in silico evaluation of a matrix (M) gene-targeted RT-qPCR assay by aligning primer and probe binding regions against 22 H1N1 isolates and representative H3N2 and H5N1 reference strains, including recent zoonotic isolates from avian and bovine hosts. Nucleotide mismatches were identified, quantified, and mapped relative to assay components and oligonucleotide termini. Mismatch burden was summarized by subtype and assay region. ResultsH1N1 isolates exhibited complete conservation across primer and probe regions. In contrast, H3N2 and H5N1 strains demonstrated subtype-specific sequence variability, with a total of eleven mismatches identified across seven non-H1N1 isolates (mean mismatch per isolate = 2.43). Probe mismatches predominated (63.6%), occurring primarily at internal positions, while primer mismatches were infrequent and largely avoided 3' terminal nucleotides. Recent H5N1 isolates (2023-2024) shared conserved internal mismatches in the probe and forward primer, whereas a historical H5N1 isolate (2016) exhibited a distinct profile including a terminal probe mismatch. Despite this variability, mismatch patterns were consistent with preserved amplification potential. ConclusionThis study demonstrates that the evaluated influenza A M gene RT-qPCR assay exhibits inherent mismatch tolerance across human and zoonotic subtypes. By shifting diagnostic evaluation from strict sequence identity to functional resilience, our findings provide a framework for designing and maintaining robust molecular assays suitable for surveillance and pandemic preparedness amid ongoing viral evolution. Graphical AbstractIn silico evaluation of an influenza A matrix gene RT-qPCR assay demonstrates subtype-specific primer and probe mismatches across H3N2 and H5N1 strains, including recent zoonotic isolates. Despite observed variability, mismatches predominantly occur at internal positions and spare primer 3' termini, supporting inherent assay mismatch tolerance and suitability for surveillance applications. O_FIG O_LINKSMALLFIG WIDTH=150 HEIGHT=200 SRC="FIGDIR/small/707407v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@e48677org.highwire.dtl.DTLVardef@1380ddcorg.highwire.dtl.DTLVardef@11606f0org.highwire.dtl.DTLVardef@121b4ab_HPS_FORMAT_FIGEXP M_FIG C_FIG

There have been several attempts to develop machine learning (ML) models to identify human infecting viruses from their genomic sequences, with varying degrees of success. Direct comparison between models is problematic, because these models are typically trained and evaluated on different datasets with alter-native data splitting schemes, features, and model performance metrics. In this paper we present a standardized dataset of mammal infecting and non-infecting viral pathogens, refined from the previous work of Mollentze et al. to include the latest literature evidence, roughly doubling the number of curated host-virus records available to the community, and new host target labels, primate and mammal. The new host labels were included for several reasons, including previous reports that classification performance is better at broader taxonomic ranks and the idea that there may be more data for primate infection that might serve as a suitable proxy for zoonotic potential and avoidance of false positives for human infection due to absence of evidence. On this dataset, we report the performance of eight machine learning models for predicting mammal-infecting viruses from their genomic sequences. We find that randomly assigning cases in our improved dataset to training/testing sets, when compared to the original assignments into training/testing in Mollentze et al., increases the overall average ROC AUC of prediction of human infection from 0.663 {+/-} 0.070 to 0.784 {+/-} 0.013, consistent with the reduction in phylogenetic distance between train and test sets (relative entropy change from 3.00 to 0.08). The broadest host category of mammal infection can be predicted most reliably at 0.850 {+/-} 0.020. We share our improved dataset and code to enable standardized comparisons of machine learning methods to predict human host infections. Overall, we have presented preliminary evidence that classification of virus host infection is more tractable at higher taxonomic ranks, that unsurprisingly reducing the phylogenetic distance between training and test sets can improve predictive performance, that peptide kmer features appear to be harmful to out of sample model performance, and we are left with the question of whether models for virus host prediction can reasonably be expected to perform well in out of sample scenarios given the likelihood that viruses do not share a common ancestor. Consistent with this concern, when the data is resampled such that there is no overlap between viral families in training and test sets (relative entropy > 24), models perform no bet-ter than random chance at prediction of human infection regardless of whether kmers are included (ROC AUC 0.50 {+/-} 0.08) or not (ROC AUC 0.50 {+/-} 0.04). Author SummaryDetermining whether a virus can infect a human or other animal based on its genetic information is useful for assessing the threat level of circulating and newly emerging viruses. Previous studies in this domain have had access to limited datasets, and in this work we nearly double the amount of manually labelled host data for viral infection, so that others may build on it and improve it further. We use machine learning models to rank the likelihood of human and mammal infection for viruses in this improved dataset. Results are consistent with the determination of host infection being more tractable for broader categories of hosts, like mammals, than for specific species, like humans. This may suggest that the prospects are good for improved future models that first screen viruses based on their likelihood of infecting mammals, and then in a second stage for likelihood of human infection. The most challenging scenarios were for predictions of viruses that were not similar to viruses in the training data, and the question remains whether we can expect reasonable generalization of predictive models to completely new viruses given that, at the time of writing, viruses do not appear to share a common ancestor.

Avian influenza virus (AIV) epidemiology is well-documented in temperate regions but remains poorly understood in isolated ecosystems like tropical oceanic islands. On these islands, seabirds nest in dense interspecific colonies where the role of different species as reservoirs and dispersers of AIV may vary greatly. Here, we examine the role of noddies (Anous spp.) as potential reservoirs for low pathogenic AIV and evaluate their potential as sentinel species for highly pathogenic AIV introduction on tropical oceanic islands. We analyzed blood samples from 11 seabird species across eight islands in the southwestern Indian Ocean (2015-2020). Noddies exhibited high, stable seroprevalence (30-45%), comparable to reservoir host species in temperate regions. The detection of two N7-positive noddies, sampled the same year on two distinct islands, provided direct molecular evidence that AIV actively circulates on these island colonies. While most other species showed low exposure, Bridled Terns (Onychoprion anaethetus) had exceptionally high seroprevalence (80%), though their reservoir status requires further investigation due to limited sampling. Given noddies consistent exposure and regional distribution, we recommend prioritizing islands with large noddy populations for AIV surveillance. Continued investigation of viral dynamics within and among islands is now called for to elucidate the ecological drivers of AIV maintenance and transmission.

Deer tick virus (DTV), or lineage II Powassan virus, is an emergent tick-borne encephalitis virus in North America. Survivors frequently sustain neurologic sequelae. Nationally reported cases have been increasing. DTV is thought to be maintained in nature by multiple modes including horizontal transmission (from viremic host to tick), cofeeding transmission (between ticks feeding nearby) and by transovarial transmission (female to progeny). Analysis of the relative importance of each mode has been hindered by low enzootic transmission. In 2021, Marthas Vineyard, Massachusetts experienced an epizootic that allowed us to probe the modes of transmission on the island. We detected virus in 7.8% of questing deer tick nymphs (161 of 2063) and in 0.3% of lone star nymphs (2 of 678). Infected ticks had a highly focal distribution; 56% of infected ticks derived from only 4 of 71 collection sites. Tick mitochondrial genome sequencing demonstrated that infected ticks were not more likely to be siblings than negative ticks and, therefore, were unlikely to have inherited the infection. Whole viral genome sequencing revealed the presence of 3 genotypes, 58% were type1, 0.6% type2, and 13.7% type3. Tick host bloodmeal identification analyses determined that nymphs infected with type1 were significantly associated with having fed on shrews (50 of 94 type1 ticks, odds ratio=2.3, p<0.001). This is consistent with shrews serving as a reservoir. Ticks infected with type3, however, had no host associations, consistent with infection acquired by cofeeding. It may be that local DTV genetic variation is shaped by transmission modes or host associations. ImportanceDeer tick virus (DTV; Powassan lineage II) is a tick-borne encephalitis virus that causes a rare zoonosis in North America. Cases have been increasingly reported within the last decade. Is the recent risk trend due to increased transmission? How this virus is perpetuated in nature is not well understood. We took advantage of a natural epizootic on Marthas Vineyard to probe how the ticks there had become infected. Using a combination of viral whole genome sequencing and bloodmeal remnant identification in ticks, we find that the mode of transmission varied by viral genotype. One genotype is associated with ticks that had fed on shrews, and another did not depend on a specific reservoir host. Host associations may drive genetic diversity of deer tick virus and thus local host population dynamics may influence zoonotic risk.

Porcine reproductive and respiratory syndrome (PRRS) is a globally distributed disease caused by Betaarterivirus europensis (PRRSV-1) and Betaarterivirus americense (PRRSV-2). Its clinical presentation ranges from subclinical infection to severe disease, depending on viral evolution and the emergence of novel variants. The aim of this study was to characterize the genetic diversity and identify recombination events in the ORF7 (nucleocapsid, N) gene of ten PRRSV-2 strains circulating in pig farms in Lima, Peru. Bioinformatic analyses were performed using DNAMAN v10.0, MEGA 6, BepiPred-2.0, DnaSP v6, and RDP v4.101. Phylogenetic analysis revealed two well-defined lineages: eight strains clustered within lineage 1A (NADC34-like), and two within lineage 5A (VR2332-like), demonstrating the co-circulation of genetically distinct variants in the region. Comparative sequence analysis identified significant amino acid substitutions in eight strains (15, 16, 17, 20, 21, 22, 23, and 24), with strain 24 being the most divergent, accumulating multiple substitutions, including T81I, R109S, I115F, R116S, and A119K within the C-terminal region encompassing antigenic domains I-V. B-cell epitope prediction using BepiPred-2.0 identified six epitope patterns (A-F) comprising nine potential B-cell epitope regions (positions 5-19, 33-72, 33-73, 84-85, 87-98, 84-98, 87-97, 84, and 119). Patterns B, E, and F exhibited four to five predicted epitope sites and corresponded to strains 21, 22, 23, and 24. Recombination analysis using RDP v4.101 detected a statistically robust recombination event in strain 18_montana2020-R (lineage 5A), with strain 24_montana2020-WT (lineage 1A) identified as the putative major parent (100% similarity) and the vaccine-like VR2332 strain (lineage 5A) as the minor parent (99.3% similarity). Secondary evidence of the same recombination event was observed in strain 19_montana2020-R. Genetic diversity analysis of the ORF7 gene identified 50 polymorphic nucleotide sites and 52 mutations. Overall, these findings demonstrate substantial genetic variability in the ORF7 gene of PRRSV-2 circulating in Lima, Peru, characterized by lineage co-circulation and inter-lineage recombination. Continuous molecular surveillance is warranted to monitor viral evolution, assess potential antigenic implications, and support effective PRRS control strategies in the Peruvian swine industry.

The NS3 helicases from the Flaviviridae family of viruses exhibit nucleotide-hydrolysis-dependent, nucleic-acid-unwinding activity. The RNA unwinding activity for NS3 helicases from the Orthoflavivirus genus has not been fully explored and contrasts with NS3 helicase from Hepatitis C virus (HCV) of the Hepacivirus genus, which has thus far served as the prototypical model enzyme from this family of viruses. To begin to understand the functional differences between flavivirus NS3 helicases, we first developed an expression and purification system for full-length untagged NS3 protein from West Nile virus (WNV) and Zika virus (ZIKV). Both enzymes exhibit RNA-stimulated ATPase activity and are dependent on the nucleoside triphosphatase active site of the enzyme. Unlike HCV NS3, orthoflavivirus NS3s do not efficiently pre-assemble on a 3-ssRNA-tailed dsRNA substrate in the absence of ATP-Mg which is a prerequisite for formation of a productive HCV NS3-RNA complex that can exhibit a rapid burst of RNA unwinding. Instead, to observe RNA unwinding by WNV and ZIKV NS3s, low Mg-ATP concentrations are required at a time coincident when NS3 encounters the RNA substrate. In addition, we find that orthoflavivirus NS3s require translocation beyond the displaced strand to completely unwind a dsRNA substrate. Last, we find that orthoflavivirus NS5 stimulates the ability of NS3 to unwind dsRNA. These results suggest that functional differences exist between the flavivirus NS3 helicases and illuminate that orthoflavivirus NS3s require a functional interaction with the NS5 protein for coordination of its activity, as it is believed these two proteins constitute the viral replicase.

SARS-CoV-2 mutations play a key role in viral evolution, in immune escape, and potentially in disease severity. However, the clinical impact of most mutations remains poorly understood, particularly across different variants. A historical observational study was conducted using SARS-CoV-2 whole-genome sequencing data linked to clinical metadata from 175,503 COVID-19 cases in Israel. The dataset was stratified into four variant-specific periods: B.1.1.7, B.1.617.2, BA.1, and BA.2. Logistic regression models were applied separately within each period to assess the association between individual mutations and the need for hospitalization, adjusting for age, gender, and time since vaccination. False discovery rate correction was used to account for multiple testing. A total of 18 SARS-CoV-2 mutations were significantly associated with COVID-19 severity, of which eight remained statistically significant after false discovery rate correction. Among these, two were associated with increased risk and six with reduced risk. Most were non-synonymous mutations located in functionally relevant regions such as the spike protein and non-structural proteins. This study provides a variant-stratified assessment of SARS-CoV-2 mutations associated with clinical severity, revealing both known and novel associations. The findings highlight the importance of integrating genomic and clinical data in public health surveillance and may inform future outbreak preparedness by identifying mutations with potential clinical impact.

Citrus is one of the most important crops cultivated worldwide, representing a strategic source of agricultural income for many countries, including Spain, the main producer within the European Union. The protection of this highly valuable industry against an increasing global movement of pests and pathogens requires effective regulatory measures, including control of plant propagation material, phytosanitary surveillance and risk assessment, which are based not only on knowledge of the established threats but also on potential emerging threats affecting citrus that may circulate unnoticed in the production system. In this work, with the aim of generating knowledge on potential emerging viruses in Spanish citrus orchards, high-throughput sequencing (HTS) analysis has been applied to monitor the sanitary status of several growing areas of one of the main citrus producer regions in Spain, the Valencian Community. The results of this study have revealed a much more complex citrus virome than previously reported, including citrus yellow vein clearing virus (CYVCV), a non-regulated but harmful citrus virus, as well as the T3 genotype of citrus tristeza virus (CTV) and citrus virus A (CiVA), not detected to date in Spain. Moreover, our results indicate the existence of other unknown components of the citrus virome. HTS detection of CYVCV, CTV T3 and CiVA and their presence in Spanish orchards has been confirmed by RT-PCR and Sanger sequencing. These findings have relevant implications in the development of control and regulatory measures against three important viral diseases, tristeza, impietratura and yellow vein clearing diseases, and demonstrate the added value of HTS-based surveillance to discover emerging components of the citrus virome.

Zoos may serve as sentinel sites for zoonotic vector-borne diseases. West Nile virus (WNV) and Usutu virus (USUV) are closely related orthoflaviviruses transmitted between Culex mosquitoes and a bird reservoir. Both viruses can also infect mammals, including humans, where they may cause symptoms and, more rarely, hospitalization and death. However, serological cross-reactivity between WNV and USUV complicates their differential diagnosis. Here, we aimed to reconstruct the dynamics of emergence of WNV in a zoo located in a newly affected area in Europe, using ELISA and Virus Neutralization Test (VNT) serological analysis of 1707 animal sera collected between 2015 and 2024. Combining this data in a model accounting for cross-reactivity with USUV, we estimated yearly forces of infection (FOI) by both viruses, and thus found that WNV likely circulated in the area one year prior to the first cases reported to the passive surveillance system. Our results also showed that, in the zoo, mammals and reptiles had a lower risk of infection than birds (relative risk of 0.14 [0.05; 0.28]), and that the exposure of birds to water (aquatic lifestyle or proximity to stagnant water) affected the risk. Finally, we estimated diagnosis parameters, including the sensitivity of the VNT (80.4% [76.5%; 84.3%]), the expected VNT titer value, and the level of serological cross-reactivity between viruses during the VNT. To conclude, our modelling framework allowed to disentangle the co-circulation of two closely related viruses, a crucial point in ensuring the reliable sentinel surveillance of these vector-borne zoonotic pathogens.

Incidence of norovirus has strong seasonality in temperate and continental climates. Many studies have examined its association with climate variables, but evidence remains disparate. We address this gap by performing a systematic review to summarise and interpret the strength and directionality of associations between climate variables and norovirus incidence. Embase, Scopus, Web of Science and PubMed databases were screened for peer-reviewed studies on 2nd of December 2024. Articles were included if they described any climate or meteorological variable, in a categorical or numerical format, relative to a measurement of norovirus incidence risk in a human population, or prevalence or survivability outside the human host. Bias was assessed using a modified Critical Appraisal Skills Programme checklist. If dispersion of the effect in a human population was provided, the mean size was calculated using inverse variance weighting. The effect size outside the host was summarised as D-values, representing the time required to achieve a 90% reduction in the detected amount of virus. A total 139 studies were included. Predictors of risk were ambient and water temperature, relative and absolute humidity, anomalies of ambient temperature and precipitation, atmospheric and vapour pressure. High heterogeneity in direction and size of effects was observed due to regional differences in the factors driving norovirus seasonality and differences in outcome and exposure definitions. Our review suggests that the sensitivity of norovirus to individual climate variables is region and time specific, reflecting geographical differences in the relative importance of norovirus transmission via environmental pathways versus human-to-human contact. Plain Language SummaryNorovirus, a gastrointestinal virus, has a higher number of cases during specific months of the year. Regions with similar types of climate appear to have similar time periods when the increase in the number of infections occurs, which has been linked to norovirus case numbers being correlated to individual climate variables, such as temperature or rainfall. To understand how these associations compare globally and what are their potential explanations, we screened four major scientific databases, namely Embase, Scopus, Web of Science and PubMed. After the selection process, a total 139 peer-reviewed studies were included in this study. We found that ambient and water temperature, relative and absolute humidity, anomalies of ambient temperature and precipitation, atmospheric and vapour pressure were predictors of an increase in norovirus cases. However, the strength and direction of the relationships differed from region to region. A potential explanation is that geographies also differ in how important individual routes are for the transmission of norovirus, specifically via the environment as opposed to direct human-to-human contact, whereas climate is likely to have a greater influence on the former. Key pointsO_LIThe strength and direction of associations between climate variables and norovirus incidence varies by region and time period C_LIO_LIThe strength of associations vary across the transmission routes of norovirus, e.g., environmental versus human-to-human contact C_LIO_LIClimate variables impact norovirus survival and dissemination outside the host, which may inform models of environmental virus transmission C_LI

Porcine Reproductive and Respiratory Syndrome Virus 2 (PRRSV-2) represents a major threat to the global swine industry. The epidemiological dynamics of PRRSV-2 are characterized by the recurrent annual emergence of dozens of variants. Long-distance spread of PRRSV-2 is largely driven by animal shipments. Spatiotemporal dynamics of PRRSV-2 in the USA have been explored; however, how fast variants spread to new regions after their emergence remains unclear, and this information could improve preparedness. To address this, we analyzed 14,835 sequences, retrieved from the Morrison Swine Health Monitoring Project (MSHMP), representing 156 variants sampled from 2015 to 2024, covering the five major swine-producing regions in the USA: the Upper Midwest (UM), Lower Midwest (LM), Atlantic Seaboard (AS), Northeast (NE), and Great Plains (GP). Time to spread was assessed using the time-to-dispersal event analysis and waiting time analyses. Genetic diversity was measured using Hill numbers. The UM had the highest variant richness (n=123), followed by the LM (n=47), AS (n=35), NE (n=45), and GP (n=38). Of the 62 variants that initially emerged in the UM, 17 later spread to other regions. The UM also received the highest number of variant introductions (n=24), followed by LM (n=14), NE (n=14), AS (n=4), and GP (n=7), highlighting regional differences in connectivity and risk. Our results suggest faster dispersal corridors among interior regions (e.g., GP to UM and LM to UM, [~]1.2-2.0 years) and slower for coast to interior pathways (AS to interior, [~]2-3 years). These findings may help anticipate the risk of PRRSV-2 variant introduction and provide more accurate dispersal time estimates, which are useful for improving epidemiological models and disease preparedness.

The 2024 dengue epidemic in Brazil-the largest arboviral emergency in the country's history-exposed critical gaps in the reliability of molecular diagnostics across its national public health laboratory network. Quality control (QC) of RT-qPCR assays performed by geographically dispersed Central Public Health Laboratories (LACENs) is essential to ensure the accuracy of epidemiological surveillance and clinical management. We conducted a multicenter QC evaluation of 3,192 complete RT-qPCR runs (19,152 datapoints) for dengue virus serotypes 1-4 (DENV1-4), Zika virus (ZIKV), and Chikungunya virus (CHIKV) across 15 LACENs over one epidemic year. An automated R-based bioinformatic pipeline applied hierarchical clustering (AGNES and DIANA), principal component analysis (PCA), linear and quadratic discriminant analysis (LDA/QDA), Shewhart and XmR control charts, process capability analysis, ANOVA, Baker's gamma permutation testing, and PVClust bootstrap clustering to positive-control cycle threshold (CT) value datasets. Median CT values for DENV4 positive controls ranged from 26.3 to 30.5 across laboratories, representing an approximately 16-fold difference in measured RNA quantity. PCA explained 54.1%-100% of total variance on PC1 across viral targets. Baker's gamma permutation tests confirmed significant concordance between AGNES and DIANA hierarchies across all six viral targets. LDA achieved 37.7% and QDA 49.1% cross-validated accuracy in laboratory-of-origin classification. PVClust bootstrap clustering identified DENV2+DENV4 (approximately unbiased probability, AU = 90) as the most analytically coherent serotype pair. ANOVA confirmed significant operator effects on ZIKV CT values (F = 8.799, df = 23), with regression coefficients for specific operators reaching beta; = +4.01 cycles-equivalent to an approximately 16-fold inferred difference in RNA quantity. Extreme outlier CT values signaled data integrity failures requiring immediate corrective action. The integrated multivariate QC framework substantially outperformed univariate Westgard-rule monitoring. Operator-specific CT deviations of up to four cycles carry direct consequences for clinical classification of borderline specimens. The automated R-based pipeline is operationally feasible in low-resource public health networks and provides a replicable model for arboviral diagnostic QC governance during epidemic emergencies.

The North American deermouse Peromyscus leucopus is reservoir for several zoonotic agents, including bacterial, protozoan, and viral. It is remarkable for indiscernible or limited fitness consequences of these infections, a trait known as infection tolerance. But experimental infections have largely been of pathogens that P. leucopus naturally harbors. We asked whether infection tolerance extended to an agent, like SARS-CoV-2 virus, it had presumably not encountered before. Following protocols for experiments with mice and hamsters, we infected 8 female and 8 male P. leucopus of heterogeneous stock and compared responses of these animals on days 3 or 6 to those of 14 controls inoculated with virus-free medium. Serologic and virologic confirmation of infection was obtained for all exposed deermice. Moderate inflammation in lungs was histologically evident in infected animals, but no histological changes were noted in brains, even when viral RNA was present. Fourteen (88%) animals displayed no or only mild sickness; two had more severe illness. Genome-wide RNA-seq revealed an interferon-stimulated response on day 3 superceded mainly by a cell-mediated response by day 6. In brains transcription of the interferon-stimulated genes Isg15 and Mx2 positively correlated with viral RNA levels. The findings confirmed susceptibility of this species of Peromyscus to SARS-CoV-2 virus. For most infected outbred animals the immune response was swift and effective in controlling the pathogen and without evidence of excessive inflammation. Whatever is the basis for P. leucopus trait of infection tolerance, it extended to at least one pathogen that for it would be novel. ImportancePeromyscus leucopus is North American rodent that is reservoir for several agents of human disease, while exhibiting minimal illness, a phenotype termed infection tolerance. Whether this trait is pathogen-specific or represents a broader strategy has remained uncertain. By experimentally infecting P. leucopus with SARS-CoV-2 virus, which it is unlikely to have encountered, we investigated whether infection tolerance extends to a novel virus. Despite disseminated infection and lung pathology, most animals showed only mild or no disease. Expression analyses revealed early interferon-stimulated responses followed by cell-mediated responses with only limited production of inflammatory mediators interferon-gamma and nitric oxide synthase 2. Compared with results with a mouse model of infection, deermice displayed higher baseline expression of antiviral genes and quicker resolution of interferon responses. These findings suggest that infection tolerance is a strategy that limits immunopathology generally while resisting microbes, which has implications for understanding reservoir competence and host resilience.

Ebola virus is a single-stranded negative-sense RNA virus that can cause severe hemorrhagic fevers in humans. Ebola virus, along with other members of the filoviridae family, produce virions with a characteristic filamentous morphology. VP40 is the Ebola virus matrix protein, which is responsible for curving the host PM into filamentous buds. VP40 forms cytosolic homodimers via interactions in its N-terminal domain, while interactions in its C-terminal domain drive oligomerization into the 2D-crystalline matrix layer. While VP40 is expressed in the host cytosol and assembles on the inner leaflet of the plasma membrane (PM), trafficking between the cytosol and PM is not direct. Here, we characterize a series of VP40 mutants targeted to the molecular determinants of Ebola VP40 assembly and trafficking using confocal microscopy with genetically-encoded fluorescent tags. Using this approach, we characterize the subcellular distribution of these mutants, showing novel phenotypes for each. Mutants related to trafficking show aggregation dependent on membrane binding, suggesting a possible mode of VP40 trafficking.

Small ruminants (sheep and goats) are one of the few mammals in which an exogenous retrovirus (XRV) and closely related endogenous retroviral elements (ERV) coexist within the same host genome. The betaretroviruses Jaagsiekte sheep retrovirus (JSRV) and enzootic nasal tumor virus (ENTV) cause pulmonary and nasal adenocarcinomas, respectively, and share extensive sequence similarity with their endogenous counterparts. Consequently, molecular surveillance must rely on assays that can unequivocally distinguish true exogenous infection from ERV-derived templates; failure to do so compromises diagnosis, phylogenetic inference, and epidemiological conclusions. We retrieved all complete JSRV, ENTV-1/2, and related ERV genomes deposited in public repositories and performed a comprehensive alignment. Only a limited number of genomic segments were capable of distinguishing exogenous from endogenous sequences. We refer to these as discriminating regions (DRs). Phylogenies built using DRs revealed that several entries annotated as XRV are, in fact, ERV-derived or chimeric artefacts generated by short-amplicon reconstruction. A systematic literature review of over 100 articles identified 286 distinct primers and probes used for the XRV amplification. In-silico mapping of each oligonucleotide onto the full alignment showed that only 28 % reliably differentiate XRV from ERV. We experimentally validated the predictive power of this approach for 17 primer/probe sets, confirming that non-discriminating assays produce false-positive signals from endogenous templates. The misannotation of ERV sequences as exogenous viruses has resulting in the population of databases with dubious entries, fostering erroneous hypotheses such as vector-borne transmission of JSRV and ENTV. To address this issue, we propose a concise set of criteria for assay design, validation, and database annotation emphasizing DR targeting, specificity testing against endogenous templates, and transparent reporting. Although this framework was developed for small ruminants, it is readily applicable to any host-virus system in which exogenous viruses coexist with endogenous viral elements. This will strengthen viral surveillance, phylogenetics, and the One Health initiatives.

BackgroundHeartland virus (HRTV) is an emerging tick-borne virus capable of causing severe illness and death. The burden of disease is likely underestimated due to limited seroprevalence studies, lack of commercially available diagnostic tests, and an overlapping clinical syndrome with more commonly diagnosed bacterial diseases such as spotted fever group rickettsiosis or ehrlichiosis. MethodsActive surveillance for Heartland virus disease was conducted at a large academic center from March to September 2024. Enrolled subjects included those who had testing sent for Ehrlichia polymerase chain reaction (PCR) along with fever and 2 of the 3 criteria: leukopenia, thrombocytopenia, and/or elevated liver function tests. Specimens with detectable RNA underwent whole genome sequencing and analysis. FindingsOver 800 specimens were received with 53 individuals meeting enrollment criteria. Among these 53, two (3.8%) had detectable HRTV RNA in whole blood during the time of Ehrlichia PCR testing. The two cases had disparate clinical manifestations: one with mild disease which was identified in an outpatient setting, while a second case required intensive care unit-level support. Heartland virus genome sequences from the two cases were more similar to viruses from other states than they were to one another. InterpretationDespite only two prior reported cases of Heartland virus disease in North Carolina, we identified two individuals with acute HRTV viremia. Further surveillance for HRTV disease is necessary to understand the burden of disease and to facilitate further studies of virus pathogenesis and host responses. FundingFunding for the study was provided by a Creativity Hub Award to Dr. Boyce from the UNC Office of the Vice Chancellor for Research. Dr. Zychowskis effort was supported by the T32 NIAD grant AI070114.