Characterizing SARS-CoV-2 Spike Sequences Based on Geographical Location.

Since 2020, the SARS-CoV-2 virus has infected billions of people and spread to 185 countries. The virus spreads by making new copies of its genome inside human cells and exploits the cells’ machinery to synthesise viral proteins it needs to infect further cells. Each time the virus copies its genetic material there’s a chance that the replication process introduces an error to the genetic sequence. Over time, these mutations accumulate which can give rise to new variants with different properties. These new variants, originating from a common ancestor, may spread faster or be able to evade immune systems that have learnt to recognise previous variants. To understand where new variants of SARS-CoV-2 come from and how related they are to each other, scientists build family trees called ‘phylogenetic trees’ based on similarities in the genetic sequences of different variants of the virus. Looking at these trees researchers can track how a variant spreads geographically, and also attempt to identify new worrying variants that might lead to a new wave of infections. The scale of the COVID-19 pandemic together with the global effort by clinicians and researchers to sequence SARS-CoV-2 genetic material means a library of over 13 million SARS-CoV-2 genomes now exists, making it the largest such collection for any organism. Although phylogenetic trees of viruses have been studied for a long time, exploring the SARS-CoV-2 library presents technical and practical challenges due to its sheer size. Sanderson has developed an open-source web tool called Taxonium that allows users to explore phylogenetic trees with millions of sequences. With help from collaborators at the University of California, Santa Cruz, Sanderson built a website called Cov2Tree, that uses the Taxonium platform to allow immediate access to an expansive tree of all publicly available SARS-CoV-2 sequences. Cov2Tree enables users to visualise all SARS-CoV-2 genomes in a birds-eye view akin to a ‘Google Earth for virus sequences’ where anyone can zoom in on a related family of viruses down to the level of individual sequences. This can be used to compare variants and follow geographic spread. Using Taxonium, scientists can explore how virus sequences are related to each other. They can also see the individual mutations that have occurred at each branch of the tree, and can search for sequences based on mutation, geographical location, or other factors. Interestingly, a trend appearing in the SARS-CoV-2 phylogenetic tree is the emergence of identical mutations at different branches of the tree without a common origin. These mutations may be a result of convergent evolution, a phenomenon that occurs when a mutation appears independently in different variants as it confers an advantage to the virus making such mutations more likely to persist. This means that scientists may be able to expect certain mutations to appear in more distantly related variants if they have appeared independently in several different variants already. Overall, Taxonium is an important tool for monitoring SARS-CoV-2 genomes, but it also has broader applications. The tool can be used to browse phylogenetic trees of other viruses and organisms. Furthermore, the Taxonium website offers a way to browse a tree of life, with images and links to Wikipedia. The SARS-CoV-2 library might be the largest now, but in the future even bigger datasets will likely be available, highlighting the importance of tools like Taxonium.

All biological products are required to demonstrate the absence of adventitious viruses (AVs), which may be inadvertently introduced at different steps involved in the manufacturing process. The currently recommended in vitro and in vivo virus detection assays have limitations for broad detection and are lengthy and laborious. Additionally, the use of animals is discouraged by the global 3 R's initiative for replacement, reduction, and refinement. High-throughput or next-generation sequencing (HTS/NGS) technologies can rapidly detect known and novel viruses in biological materials. There are, however, challenges for HTS detection of AVs due to differential abundance of viral sequences in public databases, which led to the creation of a non-redundant, Reference Viral Database (RVDB) containing all viral, viral-like, and viral-related sequences, with a reduced cellular sequence content. In this paper, we describe improvements in RVDB, which include the transition of RVDB production scripts from the original Python 2 to Python 3 codebase, updating the semantic pipeline to remove misannotated non-viral sequences and irrelevant viral sequences, use of taxonomy for the removal of phages, and inclusion of a quality-check step for SARS-CoV-2 genomes to exclude low-quality sequences. Additionally, RVDB website updates include search tools for exploring the database sequences and implementation of an automatic pipeline for providing annotation information to distinguish non-viral and viral sequences in the database. These updates for refining RVDB are expected to enhance HTS bioinformatics by reducing the computational time and increasing the accuracy for virus detection.IMPORTANCEHigh-throughput sequencing (HTS) has emerged as an advanced technology for demonstrating the safety of biological products. HTS can be used as an alternative adventitious virus detection method for replacing the currently recommended in vivo and PCR assays and supplementing or replacing the in vitro cell culture assays. However, HTS bioinformatics analysis for broad virus detection, including both known and novel viruses, depends on using a comprehensive and accurately annotated database. In this study, we have refined our original comprehensive Reference Virus Database (RVDB) for greater accuracy of virus detection with a reduced computational burden. Additionally, the production script for automating the generation of RVDB was updated to facilitate reliable database production and timely availability.

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), can lead to hospitalisation, particularly in elderly, immunocompromised, and non-vaccinated or partially vaccinated individuals. Although vaccination provides protection, the duration of this protection wanes over time. Additional doses can restore immunity, but the influence of viral variants, specific sequences, and vaccine-induced immune responses on disease severity remains unclear. Moreover, the efficacy of therapeutic interventions during hospitalisation requires further investigation. The study aims to analyse the clinical course of COVID-19 in hospitalised patients, taking into account SARS-CoV-2 variants, viral sequences, and the impact of different vaccines. The primary outcome is all-cause in-hospital mortality, while secondary outcomes include admission to intensive care unit and length of stay, duration of hospitalisation, and the level of respiratory support required.MethodsThis ongoing multicentre study observes hospitalised adult patients with confirmed SARS-CoV-2 infection, utilising a combination of retrospective and prospective data collection. It aims to gather clinical and laboratory variables from around 35,000 patients, with potential for a larger sample size. Data analysis will involve biostatistical and machine-learning techniques. Selected patients will provide biological material. The study started on October 14, 2021 and is scheduled to end on October 13, 2026.DiscussionThe analysis of a large sample of retrospective and prospective data about the acute phase of SARS CoV-2 infection in hospitalised patients, viral variants and vaccination in several European and non-European countries will help us to better understand risk factors for disease severity and the interplay between SARS CoV-2 variants, immune responses and vaccine efficacy. The main strengths of this study are the large sample size, the long study duration covering different waves of COVID-19 and the collection of biological samples that allows future research.Trial registrationThe trial has been registered on ClinicalTrials.gov. The unique identifier assigned to this trial is NCT05463380.

Complete nucleotide sequence of a cell culture-adapted variant of hepatitis A virus: comparison with wild-type virus with restricted capacity for in vitro replication.

Computational fluid dynamics and genotyping to explore airborne transmission of respiratory viruses in hospitals.

The circulation and the genomic evolution of influenza A(H3N2) viruses during the 2021/2022 and 2022/2023 seasons were studied and associated with infection outcomes. Remnant influenza A-positive samples following standard-of-care testing from patients across the Johns Hopkins Health System (JHHS) were used for the study. Samples were randomly selected for whole viral genome sequencing. The sequence-based pEpitope model was used to estimate the predicted vaccine efficacy (pVE) for circulating H3N2 viruses. Clinical data were collected and associated with viral genomic data. A total of 121 683 respiratory specimens were tested for influenza at JHHS between 1 September 2021 and 31 December 2022. Among them, 6071 (4.99%) tested positive for influenza A. Of these, 805 samples were randomly selected for sequencing, with hemagglutinin (HA) segments characterized for 610 samples. Among the characterized samples, 581 were H3N2 (95.2%). Phylogenetic analysis of HA segments revealed the exclusive circulation of H3N2 viruses with HA segments of the 3C.2a1b.2a.2 clade. Analysis of a total of 445 complete H3N2 genomes revealed reassortments; 200 of 227 of the 2022/2023 season genomes (88.1%) were found to have reassorted with clade 3C.2a1b.1a. The pVE was estimated to be -42.53% for the 2021/2022 season and 30.27% for the 2022/2023 season. No differences in clinical presentations or admissions were observed between the 2 seasons. The increased numbers of cases and genomic diversity of influenza A(H3N2) during the 2022/2023 season were not associated with a change in disease severity compared to the previous influenza season.

Reference intervals from children are limited by access to healthy children and their limited blood volumes. In this study we set out to fill gaps in pediatric reference intervals for amino acids and steroid hormones using dried blood spots (DBS) from a cohort of the National Children's Study. Deidentified DBS annotated with age, birthweight, sex, and geographic location were obtained from 310 newborns aged 0-4 days and analyzed for 25 amino acids and 4 steroid hormones using LC-MS/MS. Nonparametric statistical approaches were used to generate the 2.5th-97.5th percentile distributions for newborns. Paired plasma/DBS specimens were used to mathematically transform DBS reference intervals to corresponding plasma intervals. 10 of 25 DBS amino acid distributions were dependent on sex. There was little correlation with age, birthweight, or geographic location over the first 4 days of life. In most cases, transformation of DBS distributions to plasma distributions faithfully reflected independent studies of newborn plasma amino acid distributions. In general newborn steroid distributions were negatively correlated with age and birthweight over the first 4 days of life. Data distributions for the 4 steroids were not found related to geographic location, but testosterone concentrations displayed sex dependence. Transformation of DBS distributions to plasma intervals did not faithfully replicate other neonate steroid reference intervals determined directly with plasma. These data demonstrate the feasibility and utility of deriving newborn reference intervals from large numbers of archived DBS samples such as those obtained from the National Children's Study biobank.

CATNAP (Compile, Analyze and Tally NAb Panels) is a new web server at Los Alamos HIV Database, created to respond to the newest advances in HIV neutralizing antibody research. It is a comprehensive platform focusing on neutralizing antibody potencies in conjunction with viral sequences. CATNAP integrates neutralization and sequence data from published studies, and allows users to analyze that data for each HIV Envelope protein sequence position and each antibody. The tool has multiple data retrieval and analysis options. As input, the user can pick specific antibodies and viruses, choose a panel from a published study, or supply their own data. The output superimposes neutralization panel data, virus epidemiological data, and viral protein sequence alignments on one page, and provides further information and analyses. The user can highlight alignment positions, or select antibody contact residues and view position-specific information from the HIV databases. The tool calculates tallies of amino acids and N-linked glycosylation motifs, counts of antibody-sensitive and -resistant viruses in conjunction with each amino acid or N-glycosylation motif, and performs Fisher's exact test to detect potential positive or negative amino acid associations for the selected antibody. Website name: CATNAP (Compile, Analyze and Tally NAb Panels). Website address:http://hiv.lanl.gov/catnap.

BackgroundDuring the 2016/17 influenza season, influenza B/VIC lineage variant viruses emerged with two (K162N163) or three (K162N163D164) amino acid (aa) deletions in the haemagglutinin (HA) protein. There are currently five antigenically distinct HA proteins expressed by co-circulating influenza B viruses: B/YAM, B/VIC V1A (no deletion), B/VIC V1A-2DEL (2 aa deletion) and two antigenically distinguishable groups of B/VIC V1A-3DEL (3 aa deletion). The prevalence of these viruses differs across geographical regions, making it critical to have a sensitive, rapid diagnostic assay that detects and distinguishes these influenza B variant viruses during surveillance.AimOur objective was to develop a real-time RT-PCR (rRT-PCR) assay for detection and discrimination of influenza B/VIC lineage variant viruses.MethodsWe designed a diagnostic assay with one pair of conserved primers and three probes specific to each genetic group. We used propagated influenza B/VIC variant viruses and clinical specimens to assess assay performance.ResultsThis rRT-PCR assay detects and distinguishes the influenza B/VIC V1A, B/VIC V1A-2DEL, and B/VIC V1A-3DEL variant viruses, with no cross-reactivity. This assay can be run as a multiplex reaction, allowing for increased testing efficiency and reduced cost.ConclusionCoupling this assay with the Centers for Disease Control and Prevention’s Human Influenza Virus Real-Time RT-PCR Diagnostic Panel Influenza B Lineage Genotyping Kit results in rapid detection and characterisation of circulating influenza B viruses. Detailed surveillance information on these distinct influenza B variant viruses will provide insight into their prevalence and geographical distribution and could aid in vaccine recommendations.

Viruses represent the most abundant life forms on the planet. Recent experimental and computational improvements have led to a dramatic increase in the number of viral genome sequences identified primarily from metagenomic samples. As a result of the expanding catalog of metagenomic viral sequences, there exists a need for a comprehensive computational platform integrating all these sequences with associated metadata and analytical tools. Here we present IMG/VR (https://img.jgi.doe.gov/vr/), the largest publicly available database of 3908 isolate reference DNA viruses with 264 413 computationally identified viral contigs from >6000 ecologically diverse metagenomic samples. Approximately half of the viral contigs are grouped into genetically distinct quasi-species clusters. Microbial hosts are predicted for 20 000 viral sequences, revealing nine microbial phyla previously unreported to be infected by viruses. Viral sequences can be queried using a variety of associated metadata, including habitat type and geographic location of the samples, or taxonomic classification according to hallmark viral genes. IMG/VR has a user-friendly interface that allows users to interrogate all integrated data and interact by comparing with external sequences, thus serving as an essential resource in the viral genomics community.

A potyvirus isolated from Pinellia ternata in China was characterised and shown to be related to Soybean mosaic virus (SMV). The virus was pathogenic on P. ternata and some soybean cultivars, whereas the local soybean SMV isolate HH5 did not infect P. ternata. Western blot experiments demonstrated a serological relationship between the virus from Pinellia, SMV and Watermelon mosaic virus (WMV). The complete nucleotide sequences of the Pinellia virus (isolate P-1, 9735 nt) and of the Chinese soybean SMV isolates HH5 (9585 nt) and HZ (9588 nt) were determined. A 1733 nt sequence at the 3'-terminus of a second isolate from Pinellia (isolate P-2) was also determined. The predicted polyprotein of isolate P-1 has 83% amino acid (aa) identity with those of published SMV sequences. In many parts of the genome, aa identity was about 90% but it was much lower in the P1 protein region (24-29%), where it more closely resembled Dasheen mosaic virus (62%). The partial sequence of isolate P-2 had 91% nt identity to P-1 and both isolates resembled a recent sequence in the public databases (AF469171) wrongly named Zantedeschia mosaic virus. The two complete SMV soybean sequences had 93-95% nt identity with those of the previously sequenced isolates and >97% amino acid identity. Phylogenetic analysis and comparisons of coat proteins suggest that the Pinellia, WMV and SMV potyviruses should probably be treated as strains of the same species.

Novel strains of hepatitis E virus identified from humans and other animal species: is hepatitis E a zoonosis?

Human T-cell leukemia virus type I (HTLV-I) has been associated with adult T-cell leukemia/lymphoma and the chronic neurologic disorder tropical spastic paraparesis/HTLV-I-associated myelopathy (TSP/HAM). To study the genetic structure of the virus associated with TSP/HAM, we have obtained and sequenced a partial genomic clone from an HTLV-I-positive cell line established from cerebrospinal fluid (CSF) of a Jamaican patient with TSP/HAM. This clone consisted of a 4.3-kb viral sequence containing the 5' long terminal repeat (LTR), gag, and N-terminal portion of the pol gene, with an overall 1.3% sequence variation resulting from mostly nucleotide substitutions, as compared to the prototype HTLV-I ATK-1. The gag and pol regions showed only 1.4% and 1.2% nucleotide variations, respectively. However, the U3 region of the LTR showed the highest sequence variation (3.6%), where several changes appear to be common among certain TSP/HAM isolates. Several of these changes reside within the 21-bp boundaries and the Tax-responsive element. It would be important to determine if the observed changes are sufficient to cause neurologic disorders similar to the murine leukemia virus system or simply reflect the divergent pool of HTLV-I from different geographic locations. At this time, we cannot rule out the possibility that the observed changes have either direct or indirect significance for the HTLV-I pathogenesis in TSP/HAM.

With the exponential increase in protein sequence data, there is an urgency to acquire a knowledge of function of the millions of sequences, using automated methods with high reliability. Conventional methods for annotating a protein sequence transfer the function of a homologous sequence with known functions based on evolutionary information. Here, we present a newer way of classifying amino acids based on chemical measures and demonstrate that, when integrated with mask BLAST, the chemical properties identified outperform current classifications of amino acids as well as evolutionary measures in function detection.

Fog forecasting and fog nowcasting events are challenging issues especially when the fog phenomenon appears in the vicinity of airports because the reduced visibility associated with fog represent a high risk for air traffic events. Bucharest Henri Coandă International Airport (OTP, 44.57°N, 26.1°E, 95 m above sea level) is the largest airport in Romania and is located about 16 km north of Bucharest, the capital and most developed city of Romania. Its surroundings are comprised partly of residential and natural protected areas, and partly have agricultural use. Due to its geographic position, the airport is an important air traffic hub on the routes between western and eastern world destinations. In terms of numbers of flights, during the observation period analyzed here, the air traffic at OTP was significantly lowered during the spring of 2020 due to COVID-19 pandemic but soon after the restrictions were lifted and due to redirection of the flights over Ukraine after 2022, the air traffic is significantly increased in present. Data and analyses reported here cover a period of 2 decades from the beginning of 2003 to the end of 2023. Meteorological data, including fog events, relative humidity, wind speed and direction, were measured by the weather station of Romanian Air Traffic Services Administration ROMATSA R.A. Data about boundary layer and solar radiation was extracted from the public available database from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5. Present study reports the analysis of the evolution of the frequency of fog events and the relationships between fog events and speed and direction of the wind, and between fog events and the relative humidity. The correlations between the boundary layer height, solar radiation and the fog events were also investigated. Bivariate polar plots revealed fog appears with higher frequency (about 32%) during cold season, from October to March, and during early morning hours. Overview of the entire data set shows in some years mono-modal distributions of the fog frequency of occurrence with respect to the local time with peaks during the night and in the early morning hours and mono-modal flat distributions in other years. We observed the fog events are correlated with dominant wind directions of east-nord-east (ENE) and west-south-west (WSW). Statistical analysis of the data also showed a prevalence of the radiation fog over the advection fog. Acknowledgement: AV was supported by the University of Bucharest, PhD research grant. AV acknowledges the partial funding from the NO Grants 2014-2021, under Project contract no. 31/2020, EEA-RO-NO-2019-0423 project. Data regarding boundary layer and solar radiation was extracted from the public available database from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5. We thank ROMATSA R.A. for access to the database.