Viral Diversity Research Articles

Molecular characterization of rotavirus indicates predominance of G9P[4] genotype among children with acute gastroenteritis: First report after vaccine introduction in Pakistan

AbstractGlobally, Group A rotavirus (RVA) is the leading cause of acute gastroenteritis in children under 5 years old, with Pakistan having the highest rates of RVA‐related morbidity and mortality. The current study aims to determine the genetic diversity of rotavirus and evaluate the impact of Rotarix‐vaccine introduction on disease epidemiology in Pakistan. A total of 4749 children, hospitalized with acute gastroenteritis between 2018 and 2020, were tested at four hospitals in Lahore and Karachi. Of the total, 19.3% (918/4749) cases were tested positive for RVA antigen, with the positivity rate varying annually (2018 = 22.7%, 2019 = 14.4%, 2020 = 20.9%). Among RVA‐positive children, 66.3% were under 1 year of age. Genotyping of 662 enzyme‐linked immuno sorbent assay‐positive samples revealed the predominant genotype as G9P[4] (21.4%), followed by G1P[8] (18.9%), G3P[8] (11.4%), G12P[6] (8.7%), G2P[4] (5.7%), G2P[6] (4.8%), and 10.8% had mixed genotypes. Among vaccinated children, genotypes G9P[4] and G12P[6] were more frequently detected, whereas a decline in G2P[4] was observed. Phylogenetic analysis confirmed the continued circulation of indigenous genotypes detected earlier in the country except G9 and P[6] strains. Our findings highlight the predominance of G9P[4] genotype after the vaccine introduction thus emphasizing continual surveillance to monitor the disease burden, viral diversity, and their impact on control of rotavirus gastroenteritis in children.

A Systematic Bioinformatics Approach for Mapping the Minimal Set of a Viral Peptidome

AbstractSequence changes in viral genomes generate protein sequence diversity that enables viruses to evade the host immune system, hindering the development of effective preventive and therapeutic interventions. The massive proliferation of sequence data provides unprecedented opportunities to study viral adaptation and evolution. An alignment‐free approach removes various restrictions posed by an alignment‐dependent approach for studying sequence diversity. The publicly available tool, UNIQmin, offers an alignment‐free approach for studying viral sequence diversity at any given rank of taxonomy lineage and is big data ready. The tool performs an exhaustive search to determine the minimal set of sequences required to capture the peptidome diversity within a given dataset. This compression is possible through the removal of identical sequences and unique sequences that do not contribute effectively to the peptidome diversity pool. Herein, we describe a detailed four‐part protocol utilizing UNIQmin to generate the minimal set for the purpose of viral diversity analyses, alignment‐free at any rank of the taxonomy lineage, using the recent global public health threat Monkeypox virus (MPX) sequence data as a case study. The protocol enables a systematic bioinformatics approach to study sequence diversity across taxonomic lineages, which is crucial for our future preparedness against viral epidemics. This is particularly important when data are abundant, freely available, and alignment is not an option. © 2024 Wiley Periodicals LLC.Basic Protocol 1: Tool installation and input file preparationBasic Protocol 2: Generation of a minimal set of sequences for a given datasetBasic Protocol 3: Comparative minimal set analysis across taxonomic lineage ranksBasic Protocol 4: Factors affecting the minimal set of sequences

Circulation of Non-Middle East Respiratory Syndrome (MERS) Coronaviruses in Imported Camels in Saudi Arabia.

Background Coronaviruses (CoVs) pose significant health risks to humans, with recent outbreaks like severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underscoring their zoonotic potential. Dromedary camels (Camelus dromedarius) have been implicated as intermediate hosts for MERS-CoV, prompting heightened surveillance efforts. This study aims to identify non-MERS-CoV CoVs in imported camels at the Jeddah seaport, Saudi Arabia, using molecular techniques. Methods Camel nasal swabs (n = 337) were collected from imported dromedary camels arriving at the Jeddah Islamic seaport from Sudan and Djibouti. Samples were tested for CoVs using real-time real-time reverse transcription polymerase chain reaction (RT-PCR) targeting the RNA-dependent RNA polymerase gene. Positive samples were confirmed by conventional RT-PCR and Sanger sequencing. Selected samples underwent RNA sequencing to identify viral genomes. The study underscores the importance of molecular surveillance in camels to mitigate zoonotic risks. Results Out of 337 camel samples tested, 28 (8.30%) were positive for CoVs, predominantly from camels imported from Djibouti, compared to Sudan (13.39% vs. 5.78%). Sequence analysis confirmed the presence of non-MERS CoVs, including camel alpha-coronavirus and human CoV-229E-related strains. These findings highlight potential viral diversity and transmission risks in imported camel populations. Conclusion This study identifies diverse CoVs circulating in imported dromedary camels at the Jeddah Islamic seaport, Saudi Arabia, underscoring their potential role in zoonotic transmission. Enhanced surveillance and collaborative efforts are essential to mitigate public health risks associated with novel coronavirus strains from camel populations.

Discarded diversity: Novel megaphages, auxiliary metabolic genes, and virally encoded CRISPR-Cas systems in landfills.

Viruses are the most abundant microbial entity on the planet, impacting microbial community structure and ecosystem services. Despite outnumbering Bacteria and Archaea by an order of magnitude, viruses have been comparatively underrepresented in reference databases. Metagenomic examinations have illustrated that viruses of Bacteria and Archaea have been specifically understudied in engineered environments. Here we employed metagenomic and computational biology methods to examine the diversity, host interactions, and genetic systems of viruses predicted from 27 samples taken from three municipal landfills across North America. We identified numerous viruses that are not represented in reference databases, including the third largest bacteriophage genome identified to date (~678 kbp), and note a cosmopolitan diversity of viruses in landfills that are distinct from viromes in other systems. Host-virus interactions were examined via host CRISPR spacer to viral protospacer mapping which captured hyper-targeted viral populations and six viral populations predicted to infect across multiple phyla. Virally-encoded auxiliary metabolic genes (AMGs) were identified with the potential to augment hosts' methane, sulfur, and contaminant degradation metabolisms, including AMGs not previously reported in literature. CRISPR arrays and CRISPR-Cas systems were identified from predicted viral genomes, including the two largest bacteriophage genomes to contain these genetic features. Some virally encoded Cas effector proteins appear distinct relative to previously reported Cas systems and are interesting targets for potential genome editing tools. Our observations indicate landfills, as heterogeneous contaminated sites with unique selective pressures, are key locations for diverse viruses and atypical virus-host dynamics.

Prediction of viral families and hosts of single-stranded RNA viruses based on K-Mer coding from phylogenetic gene sequences

There are billions of virus species worldwide, and viruses, the smallest parasitic entities, pose a serious threat. Therefore, fighting associated disorders requires an understanding of the genetic structure of viruses. Considering the wide diversity and rapid evolution of viruses, there is a critical need to quickly and accurately classify viral species and their potential hosts to better understand transmission dynamics, facilitating the development of targeted therapies. Recognizing this, this study has investigated the classes of RNA viruses based on their genomic sequences using Machine Learning (ML) and Deep Learning (DL) models. The PhyVirus dataset, consisting of pathogenic Single-stranded RNA viruses of Baltimore group four (+ssRNA) and five (-ssRNA) with different hosts and species, was analyzed. The dataset containing viral gene sequences was analyzed using the K-Mer coding technique, which is based on base words of various lengths. The study used classical ML algorithms (Random Forest, Gradient Boosting and Extra Trees) and the Fully Connected Deep Neural Network, a Deep Learning algorithm, to predict viral families and hosts. Detailed analyses were performed on the classifier performance in scenarios with different train-test ratios and different word lengths (k-values) for K-Mer. The observed results show that Fully Connected Deep Neural Network has a high success rate of 99.60 % in predicting virus families. In predicting virus hosts, the Extra Trees classifier achieved the highest success rate of 81.53 %. This study is considered to be the first classification study in the literature on this dataset, which has a very large family and host diversity consisting of gene sequences of Single-stranded RNA viruses. Our detailed investigations on how varying word lengths based on K-Mer coding in gene sequences affect the classification into viral families and hosts make this study particularly valuable. This study shows that ML and DL methods have the potential to produce valuable results in phylogenetic studies. In addition, the results and high-performance values show that these methods can be successfully used in regenerative applications of gene sequences or in studies such as the elimination of losses in gene sequences.

The diverse liver viromes of Australian geckos and skinks are dominated by hepaciviruses and picornaviruses and reflect host taxonomy and habitat

Abstract Lizards have diverse ecologies and evolutionary histories, and represent a promising group to explore how hosts shape virome structure and virus evolution. Yet, little is known about the viromes of these animals. In Australia, squamates (lizards and snakes) comprise the most diverse order of vertebrates, and Australia hosts the highest diversity of lizards globally, with the greatest breadth of habitat use. We used meta-transcriptomic sequencing to determine the virome of nine co-distributed, tropical lizard species from three taxonomic families in Australia and analyzed these data to identify host traits associated with viral abundance and diversity. We show that lizards carry a large diversity of viruses, identifying more than thirty novel, highly divergent vertebrate-associated viruses. These viruses were from nine viral families, including several that contain well known pathogens, such as the Flaviviridae, Picornaviridae, Bornaviridae, Iridoviridae, and Rhabdoviridae. Members of the Flaviviridae were particularly abundant across species sampled here, largely belonging to the genus Hepacivirus: fourteen novel hepaciviruses were identified, broadening the known diversity of this group and better defining its evolution by uncovering new reptilian clades. The evolutionary histories of the viruses studied here frequently aligned with the biogeographic and phylogenetic histories of the hosts, indicating that exogenous viruses may help infer host evolutionary history if sampling is strategic and sampling density high enough. Notably, analysis of alpha and beta diversity revealed that virome composition and richness in the animals sampled here was shaped by host taxonomy and habitat. In sum, we identified a diverse range of reptile viruses that broadly contributes to our understanding of virus-host ecology and evolution.

Discovery of novel RNA viruses through analysis of fungi-associated next-generation sequencing data

BackgroundLike all other species, fungi are susceptible to infection by viruses. The diversity of fungal viruses has been rapidly expanding in recent years due to the availability of advanced sequencing technologies. However, compared to other virome studies, the research on fungi-associated viruses remains limited.ResultsIn this study, we downloaded and analyzed over 200 public datasets from approximately 40 different Bioprojects to explore potential fungal-associated viral dark matter. A total of 12 novel viral sequences were identified, all of which are RNA viruses, with lengths ranging from 1,769 to 9,516 nucleotides. The amino acid sequence identity of all these viruses with any known virus is below 70%. Through phylogenetic analysis, these RNA viruses were classified into different orders or families, such as Mitoviridae, Benyviridae, Botourmiaviridae, Deltaflexiviridae, Mymonaviridae, Bunyavirales, and Partitiviridae. It is possible that these sequences represent new taxa at the level of family, genus, or species. Furthermore, a co-evolution analysis indicated that the evolutionary history of these viruses within their groups is largely driven by cross-species transmission events.ConclusionsThese findings are of significant importance for understanding the diversity, evolution, and relationships between genome structure and function of fungal viruses. However, further investigation is needed to study their interactions.

Identification and Genome Characterization of a Novel Nege-like Virus Isolated from Aphids (Aphis gossypii) in Yunnan Province.

Negeviruses are insect-specific enveloped RNA viruses that exhibit a wide geographic distribution. A novel nege-like virus, tentatively named Aphis gossypii nege-like virus (AGNLV, GenBank: OR880429.1), was isolated from aphids (Aphis gossypii) in Lijiang City, Yunnan, China. AGNLV has a genome sequence of 9258 nt (excluding the polyA tail) encoding three open reading frames (ORFs). ORF1 (7149 nt) encodes a viral methyltransferase, a viral RNA helicase, and an RNA-dependent RNA polymerase. ORF2 (1422 nt) encodes a DiSB-ORF2_chro domain and ORF3 encodes an SP24 domain. The genome sequence of AGNLV shares the highest nucleotide identity of 60.0% and 59.5% with Wuhan house centipede virus 1 (WHCV1) and Astegopteryx formosana nege-like virus (AFNLV), respectively. Phylogenetic analysis based on the RNA-dependent RNA polymerase shows that AGNLV is clustered with other negeviruses and nege-like viruses discovered in aphids, forming a distinct "unclassified clade". Interestingly, AGNLV only encodes three ORFs, whereas AFNLV and WHCV1 have four ORFs. Structure and transmembrane domain predictions show the presence of eight alpha helices and five transmembrane helices in the AGNLV ORF3. Translational enhancement of the AGNLV 5' UTR was similar to that of the 5' UTR of plant viruses. Our findings provide evidence of the diversity and structure of nege-like viruses and are the first record of such a virus from a member of the genus Aphis.

Whole-Genome Sequencing and Genetic Diversity of Human Respiratory Syncytial Virus in Patients with Influenza-like Illness in Sicily (Italy) from 2017 to 2023.

Monitoring the genetic variability of human respiratory syncytial virus (hRSV) is of paramount importance, especially for the potential implication of key antigenic mutations on the emergence of immune escape variants. Thus, to describe the genetic diversity and evolutionary dynamics of hRSV circulating in Sicily (Italy), a total of 153 hRSV whole-genome sequences collected from 770 hRSV-positive subjects between 2017 and 2023, before the introduction of expanded immunization programs into the population, were investigated. The phylogenetic analyses indicated that the genotypes GA.2.3.5 (ON1) for hRSV-A and GB.5.0.5a (BA9) for hRSV-B co-circulated in our region. Amino acid (AA) substitutions in the surface and internal proteins were evaluated, including the F protein antigenic sites, as the major targets of immunoprophylactic monoclonal antibodies and vaccines. Overall, the proportion of AA changes ranged between 1.5% and 22.6% among hRSV-A, whereas hRSV-B varied in the range 0.8-16.9%; the latter was more polymorphic than hRSV-A within the key antigenic sites. No AA substitutions were found at site III of both subgroups. Although several non-synonymous mutations were found, none of the polymorphisms known to potentially affect the efficacy of current preventive measures were documented. These findings provide new insights into the global hRSV molecular epidemiology and highlight the importance of defining a baseline genomic picture to monitor for future changes that might be induced by the selective pressures of immunological preventive measures, which will soon become widely available.

Diversity, evolution, and emergence of fish viruses.

The production of aquatic animals has more than doubled over the last 50 years and is anticipated to continually increase. While fish are recognized as a valuable and sustainable source of nutrition, particularly in the context of human population growth and climate change, the rapid expansion of aquaculture coincides with the emergence of highly pathogenic viruses that often spread globally through aquacultural practices. Here, we provide an overview of the fish virome and its relevance for disease emergence, with a focus on the insights gained through metagenomic sequencing, noting potential areas for future study. In particular, we describe the diversity and evolution of fish viruses, for which the majority have no known disease associations, and demonstrate how viruses emerge in fish populations, most notably at an expanding domestic-wild interface. We also show how wild fish are a powerful and tractable model system to study virus ecology and evolution more broadly and can be used to identify the major factors that shape vertebrate viromes. Central to this is a process of virus-host co-divergence that proceeds over many millions of years, combined with ongoing cross-species virus transmission.

Host obesity impacts genetic variation in influenza A viral populations.

Obesity is well established as a risk factor for many noncommunicable diseases; however, its consequences for infectious disease are poorly understood. Here, we investigated the impact of host obesity on influenza A virus (IAV) genetic variation using a diet-induced obesity ferret model and the A/Hong Kong/1073/1999 (H9N2) strain. Using a co-caging study design, we investigated the maintenance, generation, and transmission of intrahost IAV genetic variation by sequencing viral genomic RNA obtained from nasal wash samples over multiple days of infection. We found evidence for an enhanced role of positive selection acting on de novo mutations in obese hosts that led to nonsynonymous changes that rose to high frequency. In addition, we identified numerous cases of mutations throughout the genome that were specific to obese hosts and that were preserved during transmission between hosts. Despite detection of obese-specific variants, the overall viral genetic diversity did not differ significantly between obese and lean hosts. This is likely due to the high supply rate of de novo variation and common evolutionary adaptations to the ferret host regardless of obesity status, which we show are mediated by variation in the hemagglutinin and polymerase genes (PB2 and PB1). We also identified defective viral genomes (DVGs) that were found uniquely in either obese or lean hosts, but the overall DVG diversity and dynamics did not differ between the two groups. Our study suggests that obesity may result in a unique selective environment impacting intrahost IAV evolution, highlighting the need for additional genetic and functional studies to confirm these effects.IMPORTANCEObesity is a chronic health condition characterized by excess adiposity leading to a systemic increase in inflammation and dysregulation of metabolic hormones and immune cell populations. Influenza A virus (IAV) is a highly infectious pathogen responsible for seasonal and pandemic influenza. Host risk factors, including compromised immunity and pre-existing health conditions, can contribute to increased infection susceptibility and disease severity. During viral replication in a host, the negative-sense single-stranded RNA genome of IAV accumulates genetic diversity that may have important consequences for viral evolution and transmission. Our study provides the first insight into the consequences of host obesity on viral genetic diversity and adaptation, suggesting that host factors associated with obesity alter the selective environment experienced by a viral population, thereby impacting the spectrum of genetic variation.

Comparing full variation profile analysis with the conventional consensus method in SARS-CoV-2 phylogeny.

This study proposes a novel approach to studying severe acute respiratory syndrome coronavirus 2 virus mutations through sequencing data comparison. Traditional consensus-based methods, which focus on the most common nucleotide at each position, might overlook or obscure the presence of low-frequency variants. Our method, in contrast, retains all sequenced nucleotides at each position, forming a genomic matrix. Utilizing simulated short reads from genomes with specified mutations, we contrasted our genomic matrix approach with the consensus sequence method. Our matrix methodology, across multiple simulated datasets, accurately reflected the known mutations with an average accuracy improvement of 20% over the consensus method. In real-world tests using data from GISAID and NCBI-SRA, our approach demonstrated an increase in reliability by reducing the error margin by approximately 15%. The genomic matrix approach offers a more accurate representation of the viral genomic diversity, thereby providing superior insights into virus evolution and epidemiology.

Biomarkers associated with vaccine-associated enhanced respiratory disease following influenza A virus infection in swine

Influenza A virus (IAV) is a major pathogen in the swine industry. Whole-inactivated virus (WIV) vaccines in swine are highly effective against homologous viruses but provide limited protection to antigenically divergent viruses and may lead to vaccine-associated enhanced respiratory disease (VAERD) after heterologous infection. Although VAERD is reproducible in laboratory studies, clinical diagnosis is challenging, as it would require both knowledge of prior vaccine history and evidence of severe disease by assessment of pathologic lesions at necropsy following infection with a heterologous virus. The objective of this study was to identify potential biomarkers for VAERD for antemortem clinical diagnosis. Naïve pigs were split into two groups, and one group was vaccinated with IAV WIV vaccine. All pigs were then challenged with a heterologous virus to induce VAERD in the vaccinated group and necropsied at 5 days post infection (dpi). Blood was collected on 0, 1, 3, and 5 dpi, and assessed by hematology, plasma chemistry, acute phase proteins, and citrullinated H3 histone (CitH3) assays. Additionally, cytokine and CitH3 levels were assessed in bronchoalveolar lavage fluid (BALF) collected at necropsy. Compared to nonvaccinated challenged pigs, blood collected from vaccinated and challenged (V/C) pigs with VAERD had elevated white blood cells and neutrophils, elevated C-reactive protein and haptoglobin acute phase proteins, and elevated CitH3. In BALF, the proinflammatory cytokine IL-8 and CitH3 were elevated in V/C pigs. In conclusion, a profile of elevated white blood cells and neutrophils, elevated C-reactive protein and haptoglobin, and elevated CitH3 may be relevant for a clinical antemortem IAV VAERD diagnosis.

VAMPirus: A versatile amplicon processing and analysis program for studying viruses.

Amplicon sequencing is an effective and increasingly applied method for studying viral communities in the environment. Here, we present vAMPirus, a user-friendly, comprehensive, and versatile DNA and RNA virus amplicon sequence analysis program, designed to support investigators in exploring virus amplicon sequencing data and running informed, reproducible analyses. vAMPirus intakes raw virus amplicon libraries and, by default, performs nucleotide- and amino acid-based analyses to produce results such as sequence abundance information, taxonomic classifications, phylogenies and community diversity metrics. The vAMPirus analytical framework leverages 16 different opensource tools and provides optional approaches that can increase the ratio of biological signal-to-noise and thereby reveal patterns that would have otherwise been masked. Here, we validate the vAMPirus analytical framework and illustrate its implementation as a general virus amplicon sequencing workflow by recapitulating findings from two previously published double-stranded DNA virus datasets. As a case study, we also apply the program to explore the diversity and distribution of a coral reef-associated RNA virus. vAMPirus is streamlined within Nextflow, offering straightforward scalability, standardization and communication of virus lineage-specific analyses. The vAMPirus framework is designed to be adaptable; community-driven analytical standards will continue to be incorporated as the field advances. vAMPirus supports researchers in revealing patterns of virus diversity and population dynamics in nature, while promoting study reproducibility and comparability.

Low-level viremia episodes appear to affect the provirus composition of the circulating cellular HIV reservoir during antiretroviral therapy.

Low-level viremia (LLV) ranging from 50 to 1,000 copies/ml is common in most HIV-1-infected patients receiving antiretroviral therapy (ART). However, the source of LLV and the impact of LLV on the HIV-1 reservoir during ART remain uncertain. We hypothesized that LLV may arise from the HIV reservoir and its occurrence affect the composition of the reservoir after LLV episodes. Accordingly, we investigated the genetic linkage of sequences obtained from plasma at LLV and pre-ART time points and from peripheral blood mononuclear cells (PBMCs) at pre-ART, pre-LLV, LLV, and post-LLV time points. We found that LLV sequences were populated with a predominant viral quasispecies that accounted for 67.29%∼100% of all sequences. Two episodes of LLV in subject 1, spaced 6 months apart, appeared to have originated from the stochastic reactivation of latently HIV-1-infected cells. Moreover, 3.77% of pre-ART plasma sequences were identical to 67.29% of LLV-3 plasma sequences in subject 1, suggesting that LLV may have arisen from a subset of cells that were infected before ART was initiated. No direct evidence of sequence linkage was found between LLV viruses and circulating cellular reservoirs in all subjects. The reservoir size, diversity, and divergence of the PBMC DNA did not differ significantly between the pre- and post-LLV sampling points (P > 0.05), but the composition of viral reservoir quasispecies shifted markedly before and after LLV episodes. Indeed, subjects with LLV had a higher total PBMC DNA level, greater viral diversity, a lower proportion of variants with identical sequences detected at two or more time points, and a shorter variant duration during ART compared with subjects without LLV. Overall, our findings suggested that LLV viruses may stem from an unidentified source other than circulating cellular reservoirs. LLV episodes may introduce great complexity into the HIV reservoir, which brings challenges to the development of treatment strategies.

Investigating the Genetic Diversity of Hepatitis Delta Virus in Hepatocellular Carcinoma (HCC): Impact on Viral Evolution and Oncogenesis in HCC.

Hepatitis delta virus (HDV), an RNA virus with two forms of the delta antigen (HDAg), relies on hepatitis B virus (HBV) for envelope proteins essential for hepatocyte entry. Hepatocellular carcinoma (HCC) ranks third in global cancer deaths, yet HDV's involvement remains uncertain. Among 300 HBV-associated HCC serum samples from Taiwan's National Health Research Institutes, 2.7% (8/300) tested anti-HDV positive, with 62.7% (5/8) of these also HDV RNA positive. Genotyping revealed HDV-2 in one sample, HDV-4 in two, and two samples showed mixed HDV-2/HDV-4 infection with RNA recombination. A mixed-genotype infection revealed novel mutations at the polyadenylation signal, coinciding with the ochre termination codon for the L-HDAg. To delve deeper into the possible oncogenic properties of HDV-2, the predominant genotype in Taiwan, which was previously thought to be less associated with severe disease outcomes, an HDV-2 cDNA clone was isolated from HCC for study. It demonstrated a replication level reaching up to 74% of that observed for a widely used HDV-1 strain in transfected cultured cells. Surprisingly, both forms of HDV-2 HDAg promoted cell migration and invasion, affecting the rearrangement of actin cytoskeleton and the expression of epithelial-mesenchymal transition markers. In summary, this study underscores the prevalence of HDV-2, HDV-4, and their mixed infections in HCC, highlighting the genetic diversity in HCC as well as the potential role of both forms of the HDAg in HCC oncogenesis.

Old Foe, New Host: Epidemiology, Genetic Diversity, and Pathogenic Characterization of Maize Streak Virus in Rice Fields from Burkina Faso

Rice is of critical significance regarding food security worldwide, including in Africa. Only two viruses impacting rice production in Africa have been deeply investigated for decades: the rice yellow mottle virus ( Solemoviridae) and the rice stripe necrosis virus ( Benyviridae). Using viral metagenomics, we aimed at broadening knowledge on interacting communities associated with plants in rice landscapes and exploring the diversity and epidemiological status of viruses circulating in rice fields from Burkina Faso. We performed an epidemiological survey in this country between 2016 and 2019 involving 57 small farmers’ rice fields under two production systems: rainfed lowlands and irrigated areas. More than 2,700 rice samples were collected without regard to disease symptoms following a regular scheme. Wild and cultivated Poaceae (maize and sugarcane) growing in nearby rice fields were also collected. Unexpectedly, metagenomics detected maize streak virus (MSV) ( Geminiviridae) in analyzed rice samples. Further molecular analyses using rolling circle amplification-polymerase chain reaction showed that MSV was widely distributed and highly prevalent in both rainfed lowlands and irrigated rice areas. MSV-A and MSV-G strains were identified. MSV-G, exclusively identified thus far in wild grasses, was the most prevalent strain, whereas MSV-A, known to cause severe symptoms in maize, was sporadically identified. Using infectious clones in experimental conditions, we confirmed the pathogenicity of both MSV strains in rice. Thus, in addition to contributing to the epidemiological surveillance of rice production in Africa, our results illuminate new epidemiological and pathogenic aspects of one of the most studied plant viruses with significant economic consequences in Africa. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Dynamics of emergence and genetic diversity of dengue virus in Reunion Island from 2012 to 2022.

Dengue is a major public health concern in Reunion Island, marked by recurrent epidemics, including successive outbreaks of dengue virus serotypes 1 and 2 (DENV1 and DENV2) with over 70,000 cases confirmed since 2017. In this study, we used Oxford Nanopore NGS technology for sequencing virologically-confirmed samples and clinical isolates collected between 2012 and 2022 to investigate the molecular epidemiology and evolution of DENV in Reunion Island. Here, we generated and analyzed a total of 499 DENV1, 360 DENV2, and 18 DENV3 sequences. By phylogenetic analysis, we show that different genotypes and variants of DENV have circulated in the past decade that likely originated from Seychelles, Mayotte and Southeast Asia and highly affected areas in Asia and Africa. DENV sequences from Reunion Island exhibit a high genetic diversity which suggests regular introductions of new viral lineages from various Indian Ocean islands. The insights from our phylogenetic analysis may inform local health authorities about the endemicity of DENV variants circulating in Reunion Island and may improve dengue management and surveillance. This work emphasizes the importance of strong local coordination and collaboration to inform public health stakeholders in Reunion Island, neighboring areas, and mainland France.

A mathematical model for HIV dynamics with multiple infections: implications for immune escape.

Multiple infections enable the recombination of different strains, which may contribute to viral diversity. How multiple infections affect the competition dynamics between the two types of strains, the wild and the immune escape mutant, remains poorly understood. This study develops a novel mathematical model that includes the two strains, two modes of viral infection, and multiple infections. For the representative double-infection case, the reproductive numbers are derived and global stabilities of equilibria are obtained via the Lyapunov direct method and theory of limiting systems. Numerical simulations indicate similar viral dynamics regardless of multiplicities of infections though the competition between the two strains would be the fiercest in the case of quadruple infections. Through sensitivity analysis, we evaluate the effect of parameters on the set-point viral loads in the presence and absence of multiple infections. The model with multiple infections predict that there exists a threshold for cytotoxic T lymphocytes (CTLs) to minimize the overall viral load. Weak or strong CTLs immune response can result in high overall viral load. If the strength of CTLs maintains at an intermediate level, the fitness cost of the mutant is likely to have a significant impact on the evolutionary dynamics of mutant viruses. We further investigate how multiple infections alter the viral dynamics during the combination antiretroviral therapy (cART). The results show that viral loads may be underestimated during cART if multiple-infection is not taken into account.

Target enrichment metaviromics enables comprehensive surveillance of coronaviruses in environmental and animal samples

The COVID-19 pandemic has underscored the importance of understanding the role of animals in the transmission of coronaviruses (CoVs) and their impact on human health. A One Health approach, integrating human, animal, and environmental health, is essential for effective CoVs control. Next-generation sequencing has played a pivotal role in identifying and monitoring the evolution of novel CoVs strains, like SARS-CoV-2. However, viral occurrence and diversity studies in environmental and animal samples are challenging because of the complexity of viral communities and low abundance of viruses in these samples.Target enrichment sequencing (TES) has emerged as a valuable tool for investigating viral families in challenging samples. This approach involves the specific capture and enrichment of viral genomes using sequence-specific probes, thereby enhancing the efficiency of detection and characterization.In this study, we aimed to develop and validate a TES panel to study CoVs in various complex environmental and animal derived samples. The results demonstrated the panel's effectiveness in capturing and sequencing a wide diversity of CoVs providing valuable insights into their abundance and host diversity in urban wastewater, farm animal corpses lixiviates and bat guano samples. In sewage samples, CoVs were detected solely when TES was employed while in guano samples, sequencing of CoVs species was achieved in 2 out of 4 samples showing an almost three-logarithmic increase in the number of reads obtained in comparison with the untargeted approach. For animal lixiviates, only the TES application enabled the acquisition of CoVs reads. The information obtained can significantly contribute to early detection, surveillance, and control measures for CoVs, including viral discovery and potential spillover events. Additionally, this sequencing panel shows potential for studying other significant viral families and monitoring viral diversity in different animal populations.