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Throughout the SARS-CoV-2 pandemic, several variants of concern (VOCs) have been identified, many of which share recurrent mutations in the spike glycoprotein's receptor-binding domain (RBD). This region coincides with known epitopes and can therefore have an impact on immune escape. Protracted infections in immunosuppressed patients have been hypothesized to lead to an enrichment of such mutations and therefore drive evolution towards VOCs. Here, we present the case of an immunosuppressed patient that developed distinct populations with immune escape mutations throughout the course of their infection. Notably, by investigating the co-occurrence of substitutions on individual sequencing reads in the RBD, we found quasispecies harboring mutations that confer resistance to known monoclonal antibodies (mAbs) such as S:E484K and S:E484A. These mutations were acquired without the patient being treated with mAbs nor convalescent sera and without them developing a detectable immune response to the virus. We also provide additional evidence for a viral reservoir based on intra-host phylogenetics, which led to a viral substrain that evolved elsewhere in the patient's body, colonizing their upper respiratory tract (URT). The presence of SARS-CoV-2 viral reservoirs can shed light on protracted infections interspersed with periods where the virus is undetectable, and potential explanations for long-COVID cases. [ABSTRACT FROM AUTHOR]

Background Universities returned to in-person learning in 2021 while SARS-CoV-2 spread remained high. At the time, it was not clear whether in-person learning would be a source of disease spread. Methods We combined surveillance testing, universal contact tracing, and viral genome sequencing to quantify introductions and identify likely on-campus spread. Results Ninety-one percent of viral genotypes occurred once, indicating no follow-on transmission. Less than 5% of introductions resulted in >3 cases, with 2 notable exceptions of 40 and 47 cases. Both partially overlapped with outbreaks defined by contact tracing. In both cases, viral genomics eliminated over half the epidemiologically linked cases but added an equivalent or greater number of individuals to the transmission cluster. Conclusions Public health interventions prevented within-university transmission for most SARS-CoV-2 introductions, with only 2 major outbreaks being identified January to May 2021. The genetically linked cases overlap with outbreaks identified by contact tracing; however, they persisted in the university population for fewer days and rounds of transmission than estimated via contact tracing. This underscores the effectiveness of test-trace-isolate strategies in controlling undetected spread of emerging respiratory infectious diseases. These approaches limit follow-on transmission in both outside-in and internal transmission conditions. [ABSTRACT FROM AUTHOR]

The avian influenza virus (AIV), traditionally confined to avian hosts, has recently been detected in various mammal species, raising significant concerns for both animal and public health, necessitating efficient and accurate methods for virus detection and characterization. This study presents a sequencing protocol combined with a comprehensive bioinformatics pipeline designed for the sequencing and analysis of AIV genomes. The presented streamlined approach encompasses whole genome PCR-amplification of the viral genome, enabling the genome characterization and detection of viral mutations with high precision. An amplicon-based MiniSeq sequencing workflow based on a set of PCR primers targeting all genome segments was developed. Three samples from H5 high pathogenic avian influenza (HPAI) outbreaks in Serbia were sequenced using the MiniSeq platform. The protocol involves optimized sample preparation, tailored specifically for AIV, library preparation and sequencing. This is complemented by a robust bioinformatics pipeline that includes quality control, read mapping, consensus genome generation, subtyping and pathotyping, as well as statistical sequencing data. The pipeline efficiently processes raw sequencing data, ensuring high-quality genome assemblies and accurate identification of viral strains. The protocol was used on AIV samples from various avian species, demonstrating its applicability and reliability. The results highlight the protocol’s capability to generate comprehensive genomic data, which is crucial for monitoring viral evolution and informing public health interventions. The described integrated approach offers a powerful tool for AIV surveillance and research, facilitating timely and informed decision-making in response to avian influenza outbreaks. This protocol can be readily adapted for use in various laboratory settings, contributing to global efforts in combating avian influenza and enhancing our understanding of its genomic landscape.

Long-range ribonucleic acid (RNA)–RNA interactions (RRI) are prevalent in positive-strand RNA viruses, including Beta-coronaviruses, and these take part in regulatory roles, including the regulation of sub-genomic RNA production rates. Crosslinking of interacting RNAs and short read-based deep sequencing of resulting RNA–RNA hybrids have shown that these long-range structures exist in severe acute respiratory syndrome coronavirus (SARS-CoV)-2 on both genomic and sub-genomic levels and in dynamic topologies. Furthermore, co-evolution of coronaviruses with their hosts is navigated by genetic variations made possible by its large genome, high recombination frequency and a high mutation rate. SARS-CoV-2's mutations are known to occur spontaneously during replication, and thousands of aggregate mutations have been reported since the emergence of the virus. Although many long-range RRIs have been experimentally identified using high-throughput methods for the wild-type SARS-CoV-2 strain, evolutionary trajectory of these RRIs across variants, impact of mutations on RRIs and interaction of SARS-CoV-2 RNAs with the host have been largely open questions in the field. In this review, we summarize recent computational tools and experimental methods that have been enabling the mapping of RRIs in viral genomes, with a specific focus on SARS-CoV-2. We also present available informatics resources to navigate the RRI maps and shed light on the impact of mutations on the RRI space in viral genomes. Investigating the evolution of long-range RNA interactions and that of virus–host interactions can contribute to the understanding of new and emerging variants as well as aid in developing improved RNA therapeutics critical for combating future outbreaks. [ABSTRACT FROM AUTHOR]

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New variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are continuing to spread globally, contributing to the persistence of the COVID-19 pandemic. Increasing resources have been focused on developing vaccines and therapeutics that target the Spike glycoprotein of SARS-CoV-2. Recent advances in microfluidics have the potential to recapitulate viral infection in the organ-specific platforms, known as organ-on-a-chip (OoC), in which binding of SARS-CoV-2 Spike protein to the angiotensin-converting enzyme 2 (ACE2) of the host cells occurs. As the COVID-19 pandemic lingers, there remains an unmet need to screen emerging mutations, to predict viral transmissibility and pathogenicity, and to assess the strength of neutralizing antibodies following vaccination or reinfection. Conventional detection of SARS-CoV-2 variants relies on two-dimensional (2-D) cell culture methods, whereas simulating the micro-environment requires three-dimensional (3-D) systems. To this end, analyzing SARS-CoV-2-mediated pathogenicity via microfluidic platforms minimizes the experimental cost, duration, and optimization needed for animal studies, and obviates the ethical concerns associated with the use of primates. In this context, this review highlights the state-of-the-art strategy to engineer the nano-liposomes that can be conjugated with SARS-CoV-2 Spike mutations or genomic sequences in the microfluidic platforms; thereby, allowing for screening the rising SARS-CoV-2 variants and predicting COVID-19-associated coagulation. Furthermore, introducing viral genomics to the patient-specific blood accelerates the discovery of therapeutic targets in the face of evolving viral variants, including B1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), c.37 (Lambda), and B.1.1.529 (Omicron). Thus, engineering nano-liposomes to encapsulate SARS-CoV-2 viral genomic sequences enables rapid detection of SARS-CoV-2 variants in the long COVID-19 era.

There is variability in viral load (VL) among individuals with untreated human immunodeficiency virus (HIV) infection, and this variability can be partly attributed to host genetics. HIV is known to develop escape mutations to evade host immune pressure, particularly from HLA alleles and, in some cases, counteracts the protective effect of host alleles. A recent genome-wide association study (GWAS) of HIV VL in individuals of African ancestry identified a locus on chromosome 1, near the protein-coding gene chromodomain helicase DNA-binding protein 1 like (CHD1L), that has a novel association with control of HIV replication. However, not all individuals carrying the protective alleles maintain low VL, and the region’s impact on viral evolution has not been investigated. To address this, we conducted a host-virus regional association analysis in 147 people living with HIV (PLWH) from South Africa with both human and viral genome data available. We observed significant associations between the CHD1L variants rs77029719 (G) (P = 1.6 × 10−2), rs7519713 (T) (P = 2.3 × 10−2), and rs59784663 (G) and 73004025 (T) (P = 1.4 × 10−2) with codon 248 of HIV reverse transcriptase (RT) and between CHD1L variant rs7519713 (T) and codon 18 (P = 3.2 × 10−2) and 147 (P = 3.9 × 10−2) of HIV gag. These associations are consistent with viral escape from CHD1L pressure. In addition, we observed significant associations between HLA B*81 (P = 1.5 × 10−5) and HLA C*18 (P = 7.0 × 10−4) with RT codon 4 and HLAB*58 with RT codon 196 (P = 9.0 × 10−4). This study reveals new evidence of host genetic variation impacting viral evolution in a population highly affected by HIV. IMPORTANCE It has been previously shown that genetic variants near CHD1L on chromosome 1 are associated with reduced HIV VL in African populations. However, the impact of these variants on viral diversity and how they restrict viral replication are unknown. We report on a regional association analysis in a South African population and show evidence of selective pressure by variants near CHD1L on HIV RT and gag. Our findings provide further insight into how genetic variability at this locus contributes to host control of HIV in a South African population. [ABSTRACT FROM AUTHOR]

Viruses are the most abundant biological entity on Earth, infect cellular organisms from all domains of life, and are central players in the global biosphere. Over the last century, the discovery and characterization of viruses have progressed steadily alongside much of modern biology. In terms of outright numbers of novel viruses discovered, however, the last few years have been by far the most transformative for the field. Advances in methods for identifying viral sequences in genomic and metagenomic datasets, coupled to the exponential growth of environmental sequencing, have greatly expanded the catalog of known viruses and fueled the tremendous growth of viral sequence databases. Development and implementation of new standards, along with careful study of the newly discovered viruses, have transformed and will continue to transform our understanding of microbial evolution, ecology, and biogeochemical cycles, leading to new biotechnological innovations across many diverse fields, including environmental, agricultural, and biomedical sciences.

Long-read, single-molecule DNA sequencing technologies have triggered a revolution in genomics by enabling the determination of large, reference-quality genomes in ways that overcome some of the limitations of short-read sequencing. However, the greater length and higher error rate of the reads generated on long-read platforms make the tools used for assembling short reads unsuitable for use in data assembly and motivate the development of new approaches. We present LoReTTA (Long Read Template-Targeted Assembler), a tool designed for performing de novo assembly of long reads generated from viral genomes on the PacBio platform. LoReTTA exploits a reference genome to guide the assembly process, an approach that has been successful with short reads. The tool was designed to deal with reads originating from viral genomes, which feature high genetic variability, possible multiple isoforms, and the dominant presence of additional organisms in clinical or environmental samples. LoReTTA was tested on a range of simulated and experimental datasets and outperformed established long-read assemblers in terms of assembly contiguity and accuracy. The software runs under the Linux operating system, is designed for easy adaptation to alternative systems, and features an automatic installation pipeline that takes care of the required dependencies. A command-line version and a user-friendly graphical interface version are available under a GPLv3 license at https://bioinformatics.cvr.ac.uk/software/ with the manual and a test dataset.

Long-read, single-molecule DNA sequencing technologies have triggered a revolution in genomics by enabling the determination of large, reference-quality genomes in ways that overcome some of the limitations of short-read sequencing. However, the greater length and higher error rate of the reads generated on long-read platforms make the tools used for assembling short reads unsuitable for use in data assembly and motivate the development of new approaches. We present LoReTTA (Long Read Template-Targeted Assembler), a tool designed for performing de novo assembly of long reads generated from viral genomes on the PacBio platform. LoReTTA exploits a reference genome to guide the assembly process, an approach that has been successful with short reads. The tool was designed to deal with reads originating from viral genomes, which feature high genetic variability, possible multiple isoforms, and the dominant presence of additional organisms in clinical or environmental samples. LoReTTA was tested on a range of simulated and experimental datasets and outperformed established long-read assemblers in terms of assembly contiguity and accuracy. The software runs under the Linux operating system, is designed for easy adaptation to alternative systems, and features an automatic installation pipeline that takes care of the required dependencies. A command-line version and a user-friendly graphical interface version are available under a GPLv3 license at https://bioinformatics.cvr.ac.uk/software/ with the manual and a test dataset.

Throughout the SARS-CoV-2 pandemic, several variants of concern (VOCs) have been identified, many of which share recurrent mutations in the spike glycoprotein’s receptor-binding domain (RBD). This region coincides with known epitopes and can therefore have an impact on immune escape. Protracted infections in immunosuppressed patients have been hypothesized to lead to an enrichment of such mutations and therefore drive evolution towards VOCs. Here, we present the case of an immunosuppressed patient that developed distinct populations with immune escape mutations throughout the course of their infection. Notably, by investigating the co-occurrence of substitutions on individual sequencing reads in the RBD, we found quasispecies harboring mutations that confer resistance to known monoclonal antibodies (mAbs) such as S:E484K and S:E484A. These mutations were acquired without the patient being treated with mAbs nor convalescent sera and without them developing a detectable immune response to the virus. We also provide additional evidence for a viral reservoir based on intra-host phylogenetics, which led to a viral substrain that evolved elsewhere in the patient’s body, colonizing their upper respiratory tract (URT). The presence of SARS-CoV-2 viral reservoirs can shed light on protracted infections interspersed with periods where the virus is undetectable, and potential explanations for long-COVID cases.

Abstract Background Sequencing viruses in many specimens is hindered by excessive background material from hosts, microbiota, and environmental organisms. Consequently, enrichment of target genomic material is necessary for practical high-throughput viral genome sequencing. Hybridization probes are widely used for enrichment in many fields, but their application to viral sequencing faces a major obstacle: it is difficult to design panels of probe oligo sequences that broadly target many viral taxa due to their rapid evolution, extensive diversity, and genetic hypervariability. To address this challenge, we created ProbeTools, a package of bioinformatic tools for generating effective viral capture panels, and for assessing coverage of target sequences by probe panel designs in silico. In this study, we validated ProbeTools by designing a panel of 3600 probes for subtyping the hypervariable haemagglutinin (HA) and neuraminidase (NA) genome segments of avian-origin influenza A viruses (AIVs). Using in silico assessment of AIV reference sequences and in vitro capture on egg-cultured viral isolates, we demonstrated effective performance by our custom AIV panel and ProbeTools’ suitability for challenging viral probe design applications. Results Based on ProbeTool’s in silico analysis, our panel provided broadly inclusive coverage of 14,772 HA and 11,967 NA reference sequences. For each reference sequence, we calculated the percentage of nucleotide positions covered by our panel in silico; 90% of HA and NA references sequences had at least 90.8 and 95.1% of their nucleotide positions covered respectively. We also observed effective in vitro capture on a representative collection of 23 egg-cultured AIVs that included isolates from wild birds, poultry, and humans and representatives from all HA and NA subtypes. Forty-two of forty-six HA and NA segments had over 98.3% of their nucleotide positions significantly enriched by our custom panel. These in vitro results were further used to validate ProbeTools’ in silico coverage assessment algorithm; 89.2% of in silico predictions were concordant with in vitro results. Conclusions ProbeTools generated an effective panel for subtyping AIVs that can be deployed for genomic surveillance, outbreak prevention, and pandemic preparedness. Effective probe design against hypervariable AIV targets also validated ProbeTools’ design and coverage assessment algorithms, demonstrating their suitability for other challenging viral capture applications.

Influenza A virus (IAV) is a single-stranded, negative-sense RNA virus and a common cause of seasonal flu in humans. Its genome comprises eight RNA segments that facilitate reassortment, resulting in a great variety of IAV strains. To study these processes, the genetic code of each segment should be unraveled. Fortunately, new third-generation sequencing approaches allow for cost-efficient sequencing of IAV segments. Sequencing success depends on various factors, including proper sample storage and processing. Hence, this work focused on the effect of storage of oral fluids and swIAV sequencing. Oral fluids (n = 13) from 2017 were stored at −22 °C and later transferred to −80 °C. Other samples (n = 21) were immediately stored at −80 °C. A reverse transcription quantitative PCR (RT-qPCR) pre- and post-storage was conducted to assess IAV viral loads. Next, samples were subjected to two IAV long-read nanopore sequencing methods to evaluate success in this complex matrix. A significant storage-associated loss of swIAV loads was observed. Still, a total of 17 complete and 6 near-complete Polish swIAV genomes were obtained. Genotype T, (H1avN2, seven herds), P (H1N1pdm09, two herds), U (H1avN1, three herds), and A (H1avN1, 1 herd) were circulated on Polish farms. In conclusion, oral fluids can be used for long-read swIAV sequencing when considering appropriate storage and segment amplification protocols, which allows us to monitor swIAV in an animal-friendly and cost-efficient manner. [ABSTRACT FROM AUTHOR]

We investigated the evolution of SARS-CoV-2 spread in Calabria, Southern Italy, in 2022. A total of 272 RNA isolates from nasopharyngeal swabs of individuals infected with SARS-CoV-2 were sequenced by whole genome sequencing (N = 172) and/or Sanger sequencing (N = 100). Analysis of diffusion of Omicron variants in Calabria revealed the prevalence of 10 different sub-lineages (recombinant BA.1/BA.2, BA.1, BA.1.1, BA.2, BA.2.9, BA.2.10, BA.2.12.1, BA.4, BA.5, BE.1). We observed that Omicron spread in Calabria presented a similar trend as in Italy, with some notable exceptions: BA.1 disappeared in April in Calabria but not in the rest of Italy; recombinant BA.1/BA.2 showed higher frequency in Calabria (13%) than in the rest of Italy (0.02%); BA.2.9, BA.4 and BA.5 emerged in Calabria later than in other Italian regions. In addition, Calabria Omicron presented 16 non-canonical mutations in the S protein and 151 non-canonical mutations in non-structural proteins. Most non-canonical mutations in the S protein occurred mainly in BA.5 whereas non-canonical mutations in non-structural or accessory proteins (ORF1ab, ORF3a, ORF8 and N) were identified in BA.2 and BA.5 sub-lineages. In conclusion, the data reported here underscore the importance of monitoring the entire SARS-CoV-2 genome. [ABSTRACT FROM AUTHOR]

Curtobacterium is a genus of Gram-positive bacteria within the order Actinomycetales. Some Curtobacterium species (C. flaccumfaciens, C. plantarum) are harmful pathogens of agricultural crops such as soybean, dry beans, peas, sugar beet and beetroot, which occur throughout the world. Bacteriophages (bacterial viruses) are considered to be potential curative agents to control the spread of harmful bacteria. Temperate bacteriophages integrate their genomes into bacterial chromosomes (prophages), sometimes substantially influencing bacterial lifestyle and pathogenicity. About 200 publicly available genomes of Curtobacterium species, including environmental metagenomic sequences, were inspected for the presence of sequences of possible prophage origin using bioinformatic methods. The comparison of the search results with several ubiquitous bacterial groups showed the relatively low level of the presence of prophage traces in Curtobacterium genomes. Genomic and phylogenetic analyses were undertaken for the evaluation of the evolutionary and taxonomic positioning of predicted prophages. The analyses indicated the relatedness of Curtobacterium prophage-derived sequences with temperate actinophages of siphoviral morphology. In most cases, the predicted prophages can represent novel phage taxa not described previously. One of the predicted temperate phages was induced from the Curtobacterium genome. Bioinformatic analysis of the modelled proteins encoded in prophage-derived regions led to the discovery of some 100 putative glycopolymer-degrading enzymes that contained enzymatic domains with predicted cell-wall- and cell-envelope-degrading activity; these included glycosidases and peptidases. These proteins can be considered for the experimental design of new antibacterials against Curtobacterium phytopathogens. [ABSTRACT FROM AUTHOR]

Simple Summary: As COVID-19 shifts from pandemic to endemic, emerging variants may be more or less virulent. Predicting whether an emerging COVID-19 variant has of high risk of causing severe disease is needed to plan for potential burdens on hospital capacity and protecting vulnerable populations. However, it takes time to do laboratory and animal experiments to determine whether a new genetic variant might be more severe, and the results may not be representative of when the virus infects humans. By the time there is epidemiological data on the severity of disease associated with a new variant, it can be too late for designing an optimal public health response. There is a critical need for computer models that can predict severe disease risk from genetic sequence data, which can be obtained from just the first few infections in a potential incoming wave. Two key challenges make computer modeling difficult: (1) sequence changes are complex, and (2) using historical data to predict future disease requires accounting for the confounding effects of changing patient demographics, improving therapeutics, and increased vaccination. In this paper, we introduce a novel interpretable deep learning architecture to solve this problem, demonstrating that it can make robust predictions for emerging variants. Through the COVID-19 pandemic, SARS-CoV-2 has gained and lost multiple mutations in novel or unexpected combinations. Predicting how complex mutations affect COVID-19 disease severity is critical in planning public health responses as the virus continues to evolve. This paper presents a novel computational framework to complement conventional lineage classification and applies it to predict the severe disease potential of viral genetic variation. The transformer-based neural network model architecture has additional layers that provide sample embeddings and sequence-wide attention for interpretation and visualization. First, training a model to predict SARS-CoV-2 taxonomy validates the architecture's interpretability. Second, an interpretable predictive model of disease severity is trained on spike protein sequence and patient metadata from GISAID. Confounding effects of changing patient demographics, increasing vaccination rates, and improving treatment over time are addressed by including demographics and case date as independent input to the neural network model. The resulting model can be interpreted to identify potentially significant virus mutations and proves to be a robust predctive tool. Although trained on sequence data obtained entirely before the availability of empirical data for Omicron, the model can predict the Omicron's reduced risk of severe disease, in accord with epidemiological and experimental data. [ABSTRACT FROM AUTHOR]

Mutations in emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineages can interfere with laboratory methods used to generate viral genome sequences for public health surveillance. We identified 20 mutations that are widespread in variant of concern lineages and affect widely used sequencing protocols by the ARTIC network and Freed et al. Three of these mutations disrupted sequencing of P.1 lineage specimens during a recent outbreak in British Columbia, Canada. We provide laboratory validation of protocol modifications that restored sequencing performance. The study findings indicate that genomic sequencing protocols require immediate updating to address emerging mutations. This work also suggests that routine monitoring and protocol updates will be necessary as SARS-CoV-2 continues to evolve. The bioinformatic and laboratory approaches used here provide guidance for this kind of assay maintenance.

Background: Sequencing viruses in many specimens is hindered by excessive background material from hosts, microbiota, and environmental organisms. Consequently, enrichment of target genomic material is necessary for practical high-throughput viral genome sequencing. Hybridization probes are widely used for enrichment in many fields, but their application to viral sequencing faces a major obstacle: it is difficult to design panels of probe oligo sequences that broadly target many viral taxa due to their rapid evolution, extensive diversity, and genetic hypervariability. To address this challenge, we created ProbeTools, a package of bioinformatic tools for generating effective viral capture panels, and for assessing coverage of target sequences by probe panel designs in silico. In this study, we validated ProbeTools by designing a panel of 3600 probes for subtyping the hypervariable haemagglutinin (HA) and neuraminidase (NA) genome segments of avian-origin influenza A viruses (AIVs). Using in silico assessment of AIV reference sequences and in vitro capture on egg-cultured viral isolates, we demonstrated effective performance by our custom AIV panel and ProbeTools' suitability for challenging viral probe design applications. Results: Based on ProbeTool's in silico analysis, our panel provided broadly inclusive coverage of 14,772 HA and 11,967 NA reference sequences. For each reference sequence, we calculated the percentage of nucleotide positions covered by our panel in silico; 90% of HA and NA references sequences had at least 90.8 and 95.1% of their nucleotide positions covered respectively. We also observed effective in vitro capture on a representative collection of 23 egg-cultured AIVs that included isolates from wild birds, poultry, and humans and representatives from all HA and NA subtypes. Forty-two of forty-six HA and NA segments had over 98.3% of their nucleotide positions significantly enriched by our custom panel. These in vitro results were further used to validate ProbeTools' in silico coverage assessment algorithm; 89.2% of in silico predictions were concordant with in vitro results. Conclusions: ProbeTools generated an effective panel for subtyping AIVs that can be deployed for genomic surveillance, outbreak prevention, and pandemic preparedness. Effective probe design against hypervariable AIV targets also validated ProbeTools' design and coverage assessment algorithms, demonstrating their suitability for other challenging viral capture applications. [ABSTRACT FROM AUTHOR]

Smear-ripened cheeses host complex microbial communities that play a crucial role in the ripening process. Although bacteriophages have been frequently isolated from dairy products, their diversity and ecological role in such this type of cheese remain underexplored. In order to fill this gap, the main objective of this study was to isolate and characterize bacteriophages from the rind of a smear-ripened cheese. Thus, viral particles extracted from the cheese rind were tested through a spot assay against a collection of bacteria isolated from the same cheese and identified by sequencing the full-length small subunit ribosomal RNA gene. In total, five virulent bacteriophages infecting Brevibacterium aurantiacum, Glutamicibacter arilaitensis, Leuconostoc falkenbergense and Psychrobacter aquimaris species were obtained. All exhibit a narrow host range, being only able to infect a few cheese-rind isolates within the same species. The complete genome of each phage was sequenced using both Nanopore and Illumina technologies, assembled and annotated. A sequence comparison with known phages revealed that four of them may represent at least new genera. The distribution of the five virulent phages into the dairy-plant environment was also investigated by PCR, and three potential reservoirs were identified. This work provides new knowledge on the cheese rind viral community and an overview of the distribution of phages within a cheese factory. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform the public health response. Millions of SARS-CoV-2 genome sequences have been deposited in global public repositories. The Canadian COVID-19 Genomics Network (CanCOGeN - VirusSeq), a consortium tasked with coordinating expanded sequencing of SARS-CoV-2 genomes across Canada early in the pandemic, created the Canadian VirusSeq Data Portal, with associated data pipelines and procedures, to support these efforts. The goal of VirusSeq was to allow open access to Canadian SARS-CoV-2 genomic sequences and enhanced, standardized contextual data that were unavailable in other repositories and that meet FAIR standards (Findable, Accessible, Interoperable and Reusable). In addition, the portal data submission pipeline contains data quality checking procedures and appropriate acknowledgement of data generators that encourages collaboration. From inception to execution, the portal was developed with a conscientious focus on strong data governance principles and practices. Extensive efforts ensured a commitment to Canadian privacy laws, data security standards, and organizational processes. This portal has been coupled with other resources, such as Viral AI, and was further leveraged by the Coronavirus Variants Rapid Response Network (CoVaRR-Net) to produce a suite of continually updated analytical tools and notebooks. Here we highlight this portal (https://virusseq-dataportal.ca/), including its contextual data not available elsewhere, and the Duotang (https://covarr-net.github.io/duotang/duotang.html), a web platform that presents key genomic epidemiology and modelling analyses on circulating and emerging SARS-CoV-2 variants in Canada. Duotang presents dynamic changes in variant composition of SARS-CoV-2 in Canada and by province, estimates variant growth, and displays complementary interactive visualizations, with a text overview of the current situation. The VirusSeq Data Portal and Duotang resources, alongside additional analyses and resources computed from the portal (COVID-MVP, CoVizu), are all open source and freely available. Together, they provide an updated picture of SARS-CoV-2 evolution to spur scientific discussions, inform public discourse, and support communication with and within public health authorities. They also serve as a framework for other jurisdictions interested in open, collaborative sequence data sharing and analyses.

Background: Viral sequencing of SARS-CoV-2 has been used for outbreak investigation, but there is limited evidence supporting routine use for infection prevention and control (IPC) within hospital settings. Methods: We conducted a prospective non-randomised trial of sequencing at 14 acute UK hospital trusts. Sites each had a 4-week baseline data collection period, followed by intervention periods comprising 8 weeks of ‘rapid’ (

In Poland, the first case of SARS-CoV-2 infection was confirmed in March 2020. Since then, many circulating virus lineages fueled rapid pandemic waves which inflicted a severe burden on the Polish healthcare system. Some of these lineages were associated with increased transmissibility and immune escape. Mutations in the viral spike protein, which is responsible for host cell recognition and serves as the primary target for neutralizing antibodies, are of particular importance. We investigated the molecular epidemiology of the SARS-CoV-2 clades circulating in Southern Poland from February 2021 to August 2021. The 921 whole-genome sequences were used for variant identification, spike mutation, and phylogenetic analyses. The Pango B.1.1.7 was the dominant variant (n = 730, 89.68%) from March 2021 to July 2021. In July 2021, the B.1.1.7 was displaced by the B.1.617.2 lineage with 66.66% in July 2021 and 92.3% in August 2021 frequencies, respectively. Moreover, our results were compared with the sequencing available on the GISAID platform for other regions of Poland, the Czech Republic, and Slovakia. The analysis showed that the dominant variant in the analyzed period was B.1.1.7 in all countries and Southern Poland (Silesia). Interestingly, B.1.1.7 was replaced by B.1.617.2 earlier in Southern Poland than in the rest of the country. Moreover, in the Czech Republic and Slovakia, AY lineages were predominant at that time, contrary to the Silesia region. [ABSTRACT FROM AUTHOR]

Influenza A virus (IAV) is a single-stranded, negative-sense RNA virus and a common cause of seasonal flu in humans. Its genome comprises eight RNA segments that facilitate reassortment, resulting in a great variety of IAV strains. To study these processes, the genetic code of each segment should be unraveled. Fortunately, new third-generation sequencing approaches allow for cost-efficient sequencing of IAV segments. Sequencing success depends on various factors, including proper sample storage and processing. Hence, this work focused on the effect of storage of oral fluids and swIAV sequencing. Oral fluids (n = 13) from 2017 were stored at −22 °C and later transferred to −80 °C. Other samples (n = 21) were immediately stored at −80 °C. A reverse transcription quantitative PCR (RT-qPCR) pre- and post-storage was conducted to assess IAV viral loads. Next, samples were subjected to two IAV long-read nanopore sequencing methods to evaluate success in this complex matrix. A significant storage-associated loss of swIAV loads was observed. Still, a total of 17 complete and 6 near-complete Polish swIAV genomes were obtained. Genotype T, (H1avN2, seven herds), P (H1N1pdm09, two herds), U (H1avN1, three herds), and A (H1avN1, 1 herd) were circulated on Polish farms. In conclusion, oral fluids can be used for long-read swIAV sequencing when considering appropriate storage and segment amplification protocols, which allows us to monitor swIAV in an animal-friendly and cost-efficient manner.

Nitrogen is an essential component of major cellular macromolecules, such as DNA and proteins. Its bioavailability has a fundamental influence on the primary production of both terrestrial and oceanic ecosystems. Diverse marine microbes consume nitrogen, while only a limited taxon could replenish it, leaving nitrogen one of the most deficient nutrients in the ocean. A variety of microbes are involved in complex biogeochemical transformations of nitrogen compounds, and their ecological functions might be regulated by viruses in different manners. First and foremost, viruses drive marine nitrogen flow via host cell lysis, releasing abundant organic nitrogen into the surrounding environment. Secondly, viruses can also participate in the marine nitrogen cycle by expressing auxiliary metabolic genes (AMGs) to modulate host nitrogen metabolic pathways, such as nitrification, denitrification, anammox, and nitrogen transmembrane transport. Additionally, viruses also serve as a considerable reservoir of nitrogen element. The efficient turnover of viruses fundamentally promotes nitrogen flow in the oceans. In this review, we summarize viral contributions in the marine nitrogen cycling in different aspects and discuss challenges and issues based on recent discoveries of novel viruses involved in different processes of nitrogen biotransformation. [ABSTRACT FROM AUTHOR]

Nitrogen is an essential component of major cellular macromolecules, such as DNA and proteins. Its bioavailability has a fundamental influence on the primary production of both terrestrial and oceanic ecosystems. Diverse marine microbes consume nitrogen, while only a limited taxon could replenish it, leaving nitrogen one of the most deficient nutrients in the ocean. A variety of microbes are involved in complex biogeochemical transformations of nitrogen compounds, and their ecological functions might be regulated by viruses in different manners. First and foremost, viruses drive marine nitrogen flow via host cell lysis, releasing abundant organic nitrogen into the surrounding environment. Secondly, viruses can also participate in the marine nitrogen cycle by expressing auxiliary metabolic genes (AMGs) to modulate host nitrogen metabolic pathways, such as nitrification, denitrification, anammox, and nitrogen transmembrane transport. Additionally, viruses also serve as a considerable reservoir of nitrogen element. The efficient turnover of viruses fundamentally promotes nitrogen flow in the oceans. In this review, we summarize viral contributions in the marine nitrogen cycling in different aspects and discuss challenges and issues based on recent discoveries of novel viruses involved in different processes of nitrogen biotransformation.

ABSTRACT Next-generation sequencing has been essential to the global response to the COVID-19 pandemic. As of January 2022, nearly 7 million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences are available to researchers in public databases. Sequence databases are an abundant resource from which to extract biologically relevant and clinically actionable information. As the pandemic has gone on, SARS-CoV-2 has rapidly evolved, involving complex genomic changes that challenge current approaches to classifying SARS-CoV-2 variants. Deep sequence learning could be a potentially powerful way to build complex sequence-to-phenotype models. Unfortunately, while they can be predictive, deep learning typically produces “black box” models that cannot directly provide biological and clinical insight. Researchers should therefore consider implementing emerging methods for visualizing and interpreting deep sequence models. Finally, researchers should address important data limitations, including (i) global sequencing disparities, (ii) insufficient sequence metadata, and (iii) screening artifacts due to poor sequence quality control.

• Amplicon sequencing methods are widely used for SARS-CoV-2 genomics. • Amplicon sequencing is disrupted by mutations in emerging SARS-CoV-2 lineages. • Current protocols require immediate updates to address these mutations. • Routine updates to protocols will be necessary as SARS-CoV-2 continues to evolve. • We provide a bioinformatic and laboratory approach for updating sequencing protocols. Mutations in emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineages can interfere with laboratory methods used to generate viral genome sequences for public health surveillance. We identified 20 mutations that are widespread in variant of concern lineages and affect widely used sequencing protocols by the ARTIC network and Freed et al. Three of these mutations disrupted sequencing of P.1 lineage specimens during a recent outbreak in British Columbia, Canada. We provide laboratory validation of protocol modifications that restored sequencing performance. The study findings indicate that genomic sequencing protocols require immediate updating to address emerging mutations. This work also suggests that routine monitoring and protocol updates will be necessary as SARS-CoV-2 continues to evolve. The bioinformatic and laboratory approaches used here provide guidance for this kind of assay maintenance. [ABSTRACT FROM AUTHOR]

Many large national and transnational studies have been dedicated to the analysis of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) genome, most of which focused on missense and nonsense mutations. However, approximately 30 per cent of the SARS-CoV-2 variants are synonymous, therefore changing the target codon without affecting the corresponding protein sequence. By performing a large-scale analysis of sequencing data generated from almost 400,000 SARS-CoV-2 samples, we show that silent mutations increasing the similarity of viral codons to the human ones tend to fixate in the viral genome overtime. This indicates that SARS-CoV-2 codon usage is adapting to the human host, likely improving its effectiveness in using the human aminoacyl-tRNA set through the accumulation of deceitfully neutral silent mutations. One-Sentence Summary. Synonymous SARS-CoV-2 mutations related to the activity of different mutational processes may positively impact viral evolution by increasing its adaptation to the human codon usage. [ABSTRACT FROM AUTHOR]

Background: Understanding the genetic interplay between human hosts and infectious pathogens is crucial for how we interpret virulence factors. Here, we tested for associations between HIV and host genetics, and interactive genetic effects on viral load (VL) in HIV-positive antiretroviral treatment-naive clinical trial participants.Methods: HIV genomes were sequenced and the encoded amino acid (AA) variants were associated with VL, human single nucleotide polymorphisms (SNPs), and imputed HLA alleles using generalized linear models with Bonferroni correction.Results: Human (388 501 SNPs) and HIV (3010 variants) genetic data were available for 2122 persons. Four HIV variants were associated with VL (P < 1.66 × 10-5). Twelve HIV variants were associated with a range of 1-512 human SNPs (P < 4.28 × 10-11). We found 46 associations between HLA alleles and HIV variants (P < 1.29 × 10-7). HIV variants and immunotypes when analyzed separately were associated with lower VL, whereas the opposite was true when analyzed in concert. Epitope binding predictions supported our observations.Conclusions: Our results show the importance of immunotype specificity on viral antigenic determinants, and the identified genetic interplay emphasizes that viral and human genetics should be studied in the context of each other.Clinical Trials Registration: NCT00867048. [ABSTRACT FROM AUTHOR]

We investigated the evolution of SARS-CoV-2 spread in Calabria, Southern Italy, in 2022. A total of 272 RNA isolates from nasopharyngeal swabs of individuals infected with SARS-CoV-2 were sequenced by whole genome sequencing (N = 172) and/or Sanger sequencing (N = 100). Analysis of diffusion of Omicron variants in Calabria revealed the prevalence of 10 different sub-lineages (recombinant BA.1/BA.2, BA.1, BA.1.1, BA.2, BA.2.9, BA.2.10, BA.2.12.1, BA.4, BA.5, BE.1). We observed that Omicron spread in Calabria presented a similar trend as in Italy, with some notable exceptions: BA.1 disappeared in April in Calabria but not in the rest of Italy; recombinant BA.1/BA.2 showed higher frequency in Calabria (13%) than in the rest of Italy (0.02%); BA.2.9, BA.4 and BA.5 emerged in Calabria later than in other Italian regions. In addition, Calabria Omicron presented 16 non-canonical mutations in the S protein and 151 non-canonical mutations in non-structural proteins. Most non-canonical mutations in the S protein occurred mainly in BA.5 whereas non-canonical mutations in non-structural or accessory proteins (ORF1ab, ORF3a, ORF8 and N) were identified in BA.2 and BA.5 sub-lineages. In conclusion, the data reported here underscore the importance of monitoring the entire SARS-CoV-2 genome.

Curtobacterium is a genus of Gram-positive bacteria within the order Actinomycetales. Some Curtobacterium species (C. flaccumfaciens, C. plantarum) are harmful pathogens of agricultural crops such as soybean, dry beans, peas, sugar beet and beetroot, which occur throughout the world. Bacteriophages (bacterial viruses) are considered to be potential curative agents to control the spread of harmful bacteria. Temperate bacteriophages integrate their genomes into bacterial chromosomes (prophages), sometimes substantially influencing bacterial lifestyle and pathogenicity. About 200 publicly available genomes of Curtobacterium species, including environmental metagenomic sequences, were inspected for the presence of sequences of possible prophage origin using bioinformatic methods. The comparison of the search results with several ubiquitous bacterial groups showed the relatively low level of the presence of prophage traces in Curtobacterium genomes. Genomic and phylogenetic analyses were undertaken for the evaluation of the evolutionary and taxonomic positioning of predicted prophages. The analyses indicated the relatedness of Curtobacterium prophage-derived sequences with temperate actinophages of siphoviral morphology. In most cases, the predicted prophages can represent novel phage taxa not described previously. One of the predicted temperate phages was induced from the Curtobacterium genome. Bioinformatic analysis of the modelled proteins encoded in prophage-derived regions led to the discovery of some 100 putative glycopolymer-degrading enzymes that contained enzymatic domains with predicted cell-wall- and cell-envelope-degrading activity; these included glycosidases and peptidases. These proteins can be considered for the experimental design of new antibacterials against Curtobacterium phytopathogens.

ABSTRACT The emergence of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genetic variants that may alter viral fitness highlights the urgency of widespread next-generation sequencing (NGS) surveillance. To profile genetic variants of the entire SARS-CoV-2 genome, we developed and clinically validated a hybridization capture SARS-CoV-2 NGS assay, integrating novel methods for panel design using double-stranded DNA (dsDNA) biotin-labeled probes, and built accompanying software. This test is the first hybrid capture-based NGS assay given Food and Drug Administration (FDA) emergency use authorization for detection of the SARS-CoV-2 virus. The positive and negative percent agreement (PPA and NPA, respectively) were defined in comparison to the results for an orthogonal real-time reverse transcription polymerase chain reaction (RT-PCR) assay (PPA and NPA, 96.7 and 100%, respectively). The limit of detection was established to be 800 copies/ml with an average fold enrichment of 46,791. Furthermore, utilizing the research-use-only analysis to profile the variants, we identified 55 novel mutations, including 11 in the functionally important spike protein. Finally, we profiled the full nasopharyngeal microbiome using metagenomics and found overrepresentation of 7 taxa and evidence of macrolide resistance in SARS-CoV-2-positive patients. This hybrid capture NGS assay, coupled with optimized software, is a powerful approach to detect and comprehensively map SARS-CoV-2 genetic variants for tracking viral evolution and guiding vaccine updates. IMPORTANCE This is the first FDA emergency-use-authorized hybridization capture-based next-generation sequencing (NGS) assay to detect the SARS-CoV-2 genome. Viral metagenomics and the novel hybrid capture NGS-based assay, along with its research-use-only analysis, can provide important genetic insights into SARS-CoV-2 and other emerging pathogens and improve surveillance and early detection, potentially preventing or mitigating new outbreaks. Better understanding of the continuously evolving SARS-CoV-2 viral genome and the impact of genetic variants may provide individual risk stratification, precision therapeutic options, improved molecular diagnostics, and population-based therapeutic solutions.

The COVID-19 pandemic has seen an unprecedented response from the sequencing community. Leveraging the sequence data from more than 140,000 SARS-CoV-2 genomes, we study mutation rates and selective pressures affecting the virus. Understanding the processes and effects of mutation and selection has profound implications for the study of viral evolution, for vaccine design, and for the tracking of viral spread. We highlight and address some common genome sequence analysis pitfalls that can lead to inaccurate inference of mutation rates and selection, such as ignoring skews in the genetic code, not accounting for recurrent mutations, and assuming evolutionary equilibrium. We find that two particular mutation rates, G →U and C →U, are similarly elevated and considerably higher than all other mutation rates, causing the majority of mutations in the SARS-CoV-2 genome, and are possibly the result of APOBEC and ROS activity. These mutations also tend to occur many times at the same genome positions along the global SARS-CoV-2 phylogeny (i.e. they are very homoplasic). We observe an effect of genomic context on mutation rates, but the effect of the context is overall limited. Although previous studies have suggested selection acting to decrease U content at synonymous sites, we bring forward evidence suggesting the opposite. [ABSTRACT FROM AUTHOR]

ABSTRACTDespite the advanced PCR-based assays available, a fraction of the pediatric respiratory infections remain unexplained every epidemic season, and there is a perception that novel viruses might be present in these specimens. We systematically collected samples from a prospective cohort of pediatric patients with respiratory infections, that returned negative results by validated molecular RT–PCR assays, and studied them with a target-independent, high-throughput sequencing-based approach. We also included a matched cohort of children with no symptoms of respiratory infection, as a contrast study population. More than fifty percent of the specimens from the group of patients with unexplained respiratory infections were resolved. However, the higher rate of detection was not due to the presence of novel viruses, but to the identification of well-known viral respiratory pathogens. Our results show that already known viral pathogens are responsible for the majority of cases that remain unexplained after the epidemic season. High-throughput sequencing approaches that use pathogen-specific probes are easier to standardize because they ensure reproducible library enrichment and sequencing. In consequence, these techniques might be desirable from a regulatory standpoint for diagnostic laboratories seeking to benefit from the many advantages of these sequencing technologies.

Abstract Background With sequencing technologies becoming cheaper and easier to use, more groups are able to obtain whole genome sequences of viruses of public health and scientific importance. Submission of genomic data to NCBI GenBank is a requirement prior to publication and plays a critical role in making scientific data publicly available. GenBank currently has automatic prokaryotic and eukaryotic genome annotation pipelines but has no viral annotation pipeline beyond influenza virus. Annotation and submission of viral genome sequence is a non-trivial task, especially for groups that do not routinely interact with GenBank for data submissions. Results We present Viral Annotation Pipeline and iDentification (VAPiD), a portable and lightweight command-line tool for annotation and GenBank deposition of viral genomes. VAPiD supports annotation of nearly all unsegmented viral genomes. The pipeline has been validated on human immunodeficiency virus, human parainfluenza virus 1–4, human metapneumovirus, human coronaviruses (229E/OC43/NL63/HKU1/SARS/MERS), human enteroviruses/rhinoviruses, measles virus, mumps virus, Hepatitis A-E Virus, Chikungunya virus, dengue virus, and West Nile virus, as well the human polyomaviruses BK/JC/MCV, human adenoviruses, and human papillomaviruses. The program can handle individual or batch submissions of different viruses to GenBank and correctly annotates multiple viruses, including those that contain ribosomal slippage or RNA editing without prior knowledge of the virus to be annotated. VAPiD is programmed in Python and is compatible with Windows, Linux, and Mac OS systems. Conclusions We have created a portable, lightweight, user-friendly, internet-enabled, open-source, command-line genome annotation and submission package to facilitate virus genome submissions to NCBI GenBank. Instructions for downloading and installing VAPiD can be found at https://github.com/rcs333/VAPiD.

Smear-ripened cheeses host complex microbial communities that play a crucial role in the ripening process. Although bacteriophages have been frequently isolated from dairy products, their diversity and ecological role in such this type of cheese remain underexplored. In order to fill this gap, the main objective of this study was to isolate and characterize bacteriophages from the rind of a smear-ripened cheese. Thus, viral particles extracted from the cheese rind were tested through a spot assay against a collection of bacteria isolated from the same cheese and identified by sequencing the full-length small subunit ribosomal RNA gene. In total, five virulent bacteriophages infecting Brevibacterium aurantiacum, Glutamicibacter arilaitensis, Leuconostoc falkenbergense and Psychrobacter aquimaris species were obtained. All exhibit a narrow host range, being only able to infect a few cheese-rind isolates within the same species. The complete genome of each phage was sequenced using both Nanopore and Illumina technologies, assembled and annotated. A sequence comparison with known phages revealed that four of them may represent at least new genera. The distribution of the five virulent phages into the dairy-plant environment was also investigated by PCR, and three potential reservoirs were identified. This work provides new knowledge on the cheese rind viral community and an overview of the distribution of phages within a cheese factory.

In Poland, the first case of SARS-CoV-2 infection was confirmed in March 2020. Since then, many circulating virus lineages fueled rapid pandemic waves which inflicted a severe burden on the Polish healthcare system. Some of these lineages were associated with increased transmissibility and immune escape. Mutations in the viral spike protein, which is responsible for host cell recognition and serves as the primary target for neutralizing antibodies, are of particular importance. We investigated the molecular epidemiology of the SARS-CoV-2 clades circulating in Southern Poland from February 2021 to August 2021. The 921 whole-genome sequences were used for variant identification, spike mutation, and phylogenetic analyses. The Pango B.1.1.7 was the dominant variant (n = 730, 89.68%) from March 2021 to July 2021. In July 2021, the B.1.1.7 was displaced by the B.1.617.2 lineage with 66.66% in July 2021 and 92.3% in August 2021 frequencies, respectively. Moreover, our results were compared with the sequencing available on the GISAID platform for other regions of Poland, the Czech Republic, and Slovakia. The analysis showed that the dominant variant in the analyzed period was B.1.1.7 in all countries and Southern Poland (Silesia). Interestingly, B.1.1.7 was replaced by B.1.617.2 earlier in Southern Poland than in the rest of the country. Moreover, in the Czech Republic and Slovakia, AY lineages were predominant at that time, contrary to the Silesia region.

Inferring algorithmic structure in data is essential for discovering causal generative models. In this research, we present a quantum computing framework using the circuit model, for estimating algorithmic information metrics. The canonical computation model of the Turing machine is restricted in time and space resources, to make the target metrics computable under realistic assumptions. The universal prior distribution for the automata is obtained as a quantum superposition, which is further conditioned to estimate the metrics. Specific cases are explored where the quantum implementation offers polynomial advantage, in contrast to the exhaustive enumeration needed in the corresponding classical case. The unstructured output data and the computational irreducibility of Turing machines make this algorithm impossible to approximate using heuristics. Thus, exploring the space of program-output relations is one of the most promising problems for demonstrating quantum supremacy using Grover search that cannot be dequantized. Experimental use cases for quantum acceleration are developed for self-replicating programs and algorithmic complexity of short strings. With quantum computing hardware rapidly attaining technological maturity, we discuss how this framework will have significant advantage for various genomics applications in meta-biology, phylogenetic tree analysis, protein-protein interaction mapping and synthetic biology. This is the first time experimental algorithmic information theory is implemented using quantum computation. Our implementation on the Qiskit quantum programming platform is copy-left and is publicly available on GitHub. [ABSTRACT FROM AUTHOR]

In February 2020, the municipality of Vo’, a small town near Padua (Italy) was quarantined due to the first coronavirus disease 19 (COVID-19)-related death detected in Italy. To investigate the viral prevalence and clinical features, the entire population was swab tested in two sequential surveys. Here we report the analysis of 87 viral genomes, which revealed that the unique ancestor haplotype introduced in Vo’ belongs to lineage B, carrying the mutations G11083T and G26144T. The viral sequences allowed us to investigate the viral evolution while being transmitted within and across households and the effectiveness of the non-pharmaceutical interventions implemented in Vo’. We report, for the first time, evidence that novel viral haplotypes can naturally arise intra-host within an interval as short as two weeks, in approximately 30% of the infected individuals, regardless of symptom severity or immune system deficiencies. Moreover, both phylogenetic and minimum spanning network analyses converge on the hypothesis that the viral sequences evolved from a unique common ancestor haplotype that was carried by an index case. The lockdown extinguished both the viral spread and the emergence of new variants.

This report details the outcome of the 13(th) Meeting of the Genomic Standards Consortium. The three-day conference was held at the Kingkey Palace Hotel, Shenzhen, China, on March 5-7, 2012, and was hosted by the Beijing Genomics Institute. The meeting, titled From Genomes to Interactions to Communities to Models, highlighted the role of data standards associated with genomic, metagenomic, and amplicon sequence data and the contextual information associated with the sample. To this end the meeting focused on genomic projects for animals, plants, fungi, and viruses; metagenomic studies in host-microbe interactions; and the dynamics of microbial communities. In addition, the meeting hosted a Genomic Observatories Network session, a Genomic Standards Consortium biodiversity working group session, and a Microbiology of the Built Environment session sponsored by the Alfred P. Sloan Foundation.

Abstract Background Human herpesvirus-6A and -6B (HHV-6) are betaherpesviruses that reach > 90% seroprevalence in the adult population. Unique among human herpesviruses, HHV-6 can integrate into the subtelomeric regions of human chromosomes; when this occurs in germ line cells it causes a condition called inherited chromosomally integrated HHV-6 (iciHHV-6). Only two complete genomes are available for replicating HHV-6B, leading to numerous conflicting annotations and little known about the global genomic diversity of this ubiquitous virus. Results Using a custom capture panel for HHV-6B, we report complete genomes from 61 isolates of HHV-6B from active infections (20 from Japan, 35 from New York state, and 6 from Uganda), and 64 strains of iciHHV-6B (mostly from North America). HHV-6B sequence clustered by geography and illustrated extensive recombination. Multiple iciHHV-6B sequences from unrelated individuals across the United States were found to be completely identical, consistent with a founder effect. Several iciHHV-6B strains clustered with strains from recent active pediatric infection. Combining our genomic analysis with the first RNA-Seq and shotgun proteomics studies of HHV-6B, we completely reannotated the HHV-6B genome, altering annotations for more than 10% of existing genes, with multiple instances of novel splicing and genes that hitherto had gone unannotated. Conclusion Our results are consistent with a model of intermittent de novo integration of HHV-6B into host germline cells during active infection with a large contribution of founder effect in iciHHV-6B. Our data provide a significant advance in the genomic annotation of HHV-6B, which will contribute to the detection, diversity, and control of this virus.

Viral disease poses a major barrier to sustainable aquaculture, with outbreaks causing large economic losses and growing concerns for fish welfare. Genomic epidemiology can support disease control by providing rapid inferences on viral evolution and disease transmission. In this study, genomic epidemiology was used to investigate salmonid alphavirus (SAV), the causative agent of pancreas disease (PD) in Atlantic salmon. Our aim was to reconstruct SAV subtype-2 (SAV2) diversity and transmission dynamics in recent Norwegian aquaculture, including the origin of SAV2 in regions where this subtype is not tolerated under current legislation. Using nanopore sequencing, we captured ~90% of the SAV2 genome for n = 68 field isolates from 10 aquaculture production regions sampled between 2018 and 2020. Using time-calibrated phylogenetics, we infer that, following its introduction to Norway around 2010, SAV2 split into two clades (SAV2a and 2b) around 2013. While co-present at the same sites near the boundary of Møre og Romsdal and Trøndelag, SAV2a and 2b were generally detected in non-overlapping locations at more Southern and Northern latitudes, respectively. We provide evidence for recent SAV2 transmission over large distances, revealing a strong connection between Møre og Romsdal and SAV2 detected in 2019/20 in Rogaland. We also demonstrate separate introductions of SAV2a and 2b outside the SAV2 zone in Sognefjorden (Vestland), connected to samples from Møre og Romsdal and Trøndelag, respectively, and a likely 100 km Northward transmission of SAV2b within Trøndelag. Finally, we recovered genomes of SAV2a and SAV3 co-infecting single fish in Rogaland, involving novel SAV3 lineages that diverged from previously characterized strains >25 years ago. Overall, this study demonstrates useful applications of genomic epidemiology for tracking viral disease spread in aquaculture.

Background Powassan virus (POWV) is an emerging cause of severe encephalitis; very little is known about human pathogenicity due to challenges in diagnosis and viral RNA recovery. We present 3 patients with fatal encephalitis due to POWV lineage II (deer tick virus). Methods We obtained 27 unique samples, including from brain biopsy and autopsy, and used metagenomic sequencing, quantitative reverse transcriptase polymerase chain reaction, and a newly developed CRISPR-based diagnostic assay to perform the first detailed characterization of POWV compartmentalization and genomics between and within human subjects. Results In all 3 patients, imaging and histopathology findings were notable for profound cerebellar involvement. All patients were initially diagnosed with POWV by metagenomic sequencing, and 2 of the 3 had negative clinical testing by serology. We detected POWV RNA in 13 clinical samples; levels were highest in the cerebellum, and there was very little involvement of peripheral tissue. We assembled complete POWV genomes from 8 samples, providing unique information about the strains of POWV lineage II (deer tick virus) that infect humans. Conclusions We demonstrate the utility of molecular assays for detecting POWV infection, including in seronegative patients, and nominate viral genomic features that may relate to human infection and neuropathogenicity. The cerebellum was identified as a key target POWV in fatal infection, by radiological and histopathological findings as well as molecular testing. [ABSTRACT FROM AUTHOR]

Enhancers play indispensable roles in cell proliferation and survival through spatiotemporally regulating gene transcription. Active enhancers and superenhancers often produce noncoding enhancer RNAs (eRNAs) that precisely control RNA polymerase II activity. Kaposi's sarcoma-associated herpesvirus (KSHV) is a human oncogenic gamma-2 herpesvirus that causes Kaposi's sarcoma and primary effusion lymphoma (PEL). It is well characterized that KSHV utilizes host epigenetic machineries to control the switch between two lifecycles, latency and lytic replication. However, how KSHV impacts host epigenome at different stages of viral lifecycle is not well understood. Using global run-on sequencing (GRO-seq) and chromatin-immunoprecipitation sequencing (ChIP-seq), we profiled the dynamics of host transcriptional regulatory elements during latency and lytic replication of KSHV-infected PEL cells. This revealed that a number of critical host genes for KSHV latency, including MYC proto-oncogene, were under the control of superenhancers whose activities were globally repressed upon viral reactivation. The eRNA-expressing MYC superenhancers were located downstream of the MYC gene in KSHV-infected PELs and played a key role in MYC expression. RNAi-mediated depletion or dCas9- KRAB CRISPR inhibition of eRNA expression significantly reduced MYC mRNA level in PELs, as did the treatment of an epigenomic drug that globally blocks superenhancer function. Finally, while cellular IRF4 acted upon eRNA expression and superenhancer function for MYC expression during latency, KSHV viral IRF4 repressed cellular IRF4 expression, decreasing MYC expression and thereby, facilitating lytic replication. These results indicate that KSHV acts as an epigenomic driver that modifies host epigenomic status upon reactivation by effectively regulating host enhancer function. [ABSTRACT FROM AUTHOR]

The virosphere is largely unexplored and the majority of viruses are yet to be represented in public sequence databases. Bats are rich reservoirs of viruses, including several zoonoses. In this study, high throughput sequencing (HTS) of viral RNA extracted from swabs of four body sites per bat per timepoint is used to characterize the virome through a longitudinal study of a captive colony of fruit nectar bats, species Eonycteris spelaea in Singapore. Through unbiased shotgun and target enrichment sequencing, we identify both known and previously unknown viruses of zoonotic relevance and define the population persistence and temporal patterns of viruses from families that have the capacity to jump the species barrier. To our knowledge, this is the first study that combines probe-based viral enrichment with HTS to create a viral profile from multiple swab sites on individual bats and their cohort. This work demonstrates temporal patterns of the lesser dawn bat virome, including several novel viruses. Given the known risk for bat–human zoonoses, a more complete understanding of the viral dynamics in South-eastern Asian bats has significant implications for disease prevention and control. The findings of this study will be of interest to U.S. Department of Defense personnel stationed in the Asia-Pacific region and regional public health laboratories engaged in emerging infectious disease surveillance efforts. [ABSTRACT FROM AUTHOR]