GISAID Database Research Articles

Epidemiological and Genetic Characterization of Human Infection with Avian Influenza AI H5N6 Virus in Guangxi, China, 2021

Avian influenza (AI) H5N6 has replaced H5N1 as the predominant strain, and the increasing number of cases and complex recombination patterns pose significant threats to human health. The data were collected on human cases of AI H5N6 from the National Surveillance of Notifiable Infectious Disease Programme (NSNIDP) in Guangxi and used MEGA software to conduct phylogenetic analysis with published reference strains obtained from the GISAID database. Between January 1 and December 31, 2021, 11 cases of human AI H5N6 infection were reported in Guangxi. All HA genes belonged to clade 2.3.4.4, with only one virus belonging to 2.3.4.4h and the remaining viruses falling into 2.3.4.4b. Phylogenetic analysis of the genes was conducted, and some substitutions were detected in the HA gene, M1 protein, and NS1 protein. A close relationship between Guangxi viruses and AIVs of poultry origin has been observed. Given the contamination of live poultry markets and backyard poultry, AI H5N6 variants and genotypes will continuously emerge; therefore, enhancing surveillance is crucial for pandemic preparedness.

42 Clinical features and severity of COVID-19 with respiratory virus coinfections versus SARS-CoV-2 monoinfection in hospitalized children: A Canadian national surveillance study

Abstract Background The co-circulation of SARS-CoV-2 alongside other respiratory viruses has led to the risk of coinfections, potentially intensifying the severity of cases, especially in children. Objectives This study examined the epidemiology, clinical characteristics, and outcomes of SARS-CoV-2 respiratory virus coinfections in comparison to SARS-CoV-2 monoinfections in hospitalized children. Design/Methods A nationwide surveillance study was conducted to assess paediatric COVID-19-related hospitalizations across Canada from April 2020 to May 2022. Data were captured through two datasets covering ~90% of all Canadian tertiary-care paediatric beds: The Canadian Paediatric Surveillance Program and the Canadian Immunization Monitoring Program, ACTive. Coinfections were defined as the simultaneous detection of SARS-CoV-2 and ≥1 other respiratory virus. Severe infection was defined as intensive care, ventilatory, or hemodynamic support needs, organ systems complications, or death. Variables and outcomes were summarized and compared, and risk ratios were computed using Poisson regression, adjusting for age, gender, comorbid conditions, SARS-CoV-2 lineage, and vaccination status. Results Out of 1501 COVID-19-related hospitalizations, 163 (10.9%) had documented coinfections with 44/163 [27%] involving SARS-COV-2 plus ≥2 other respiratory viruses. The majority of SARS-CoV-2 monoinfections (1176/1501, 87.9%) and coinfections (139/163, 85.3%) belonged to the Omicron era (Figure A). RSV (66/163, 40.5%) and Enterovirus/rhinovirus (61/163, 37.4%) coinfections were the most common. Coinfection cases were significantly younger than monoinfection cases (median age 1.2 [IQR:0.3-3.3] vs 1.6 [IQR:0.3-7.0] years, p=0.04). Overall, severe disease was more common among cases with any coinfection (38.0%) than SARS-CoV-2 monoinfection (25.7%; adjusted risk ratio 1.45, 95% confidence interval 1.17-1.80) (Figure B). In particular, we observed that severe outcomes were significantly higher in SARS-CoV-2 coinfections compared to monoinfections during the Omicron era (Figure C-D). Overall, 26/61 (42.6%) Enterovirus/Rhinovirus and 20/66 (30.3%) RSV coinfections were associated with severe outcomes. Conclusion Children with documented coinfections had more severe respiratory disease compared to SARS-COV-2 monoinfections. However, children with severe COVID-19 may have been more likely tested for multiple viruses, leading to a risk of underestimation of coinfections among children with milder disease. Further work is needed to assess how different virus coinfections may affect children and which, if any, may be a predominant driver of disease severity. 1Severe disease was defined as intensive care, ventilatory, or hemodynamic support requirements, organ system complications, or death. 2Lineage was first assigned based on available genetic sequencing data. If missing, lineage was imputed based on the dominant circulating lineage at the provincial level according to the GISAID database.

The Global Trend of Drug Resistant Sites in Influenza A Virus Neuraminidase Protein from 2011 to 2020.

Influenza A virus (IAV) causes highly contagious respiratory disease worldwide, so prevention and control of IAV is extremely important. However, overuse of neuraminidase inhibitor (NAI) drugs leads to drug resistance. To explore the up-to-date geographical distribution and evolution of drug-resistant mutations (DRMs) in the NA protein of IAV, 81,492 near full-length NA sequences downloaded from NCBI and GISAID databases, including 34,481 H1N1 and 46,622 H3N2, were processed and analyzed. Our results showed the annual number of NA sequences from 2011 to 2019 continuously increased. Meanwhile, almost 85% of sequences were from developed countries in North America, Europe and Asia. Clustering analysis demonstrated H3N2 varied more than H1N1. Notably, H3N2 exhibited a higher frequency of DRMs than H1N1, with prevailing DRMs mainly located at non-active sites within the NA protein. Phylogenetic analyses showed NA harboring DRMs collected in the same year and from the same location clustered together, which may be related to the local economic level, clinical monitoring of DRMs and research level. Consequently, it is imperative to enhance global surveillance targeting drug resistance in IAV infections which can mitigate the transmission of drug-resistant strains. In summary, our research provides valuable insights for clinical medication while establishing a robust scientific basis for IAV prevention and treatment strategies to improve overall efficacy.

Evolution of Influenza A(H3N2) Viruses in Bhutan for Two Consecutive Years, 2022 and 2023.

Influenza A viruses pose a significant public health threat globally and are characterized by rapid evolution of the hemagglutinin (HA) gene causing seasonal epidemics. The aim of this study was to investigate the evolutionary dynamics of A(H3N2) circulating in Bhutan during 2022 and 2023. We analysed 166 whole-genome sequences of influenza A(H3N2) from Bhutan, obtained from the GISAID database. We employed a Bayesian Markov Chain Monte Carlo (MCMC) framework, with a curated global dataset of HA sequences from regions with significant migration links to Bhutan. Phylogenetic, temporal, and phylogeographic analyses were conducted to elucidate the evolutionary dynamics and spatial dissemination of the viruses. Our phylogenetic analysis identified the circulation of influenza A(H3N2) Clade 3C.2a1b.2a.2 in Bhutan during 2022 and 2023, with viruses further classified into three subclades: 2a.3 (39/166), 2a.3a.1 (58/166) and 2a.3b (69/166). The TMRCA estimates suggest that these viral lineages originated approximately 1.93 years prior to their detection. Phylogeographic analysis indicates introductions from the United States in 2022 and Australia in 2023. The mean evolutionary rate across all gene segments was calculated to be 4.42 × 10-3 substitutions per site per year (95% HPD: 3.19 × 10-3 to 5.84 × 10-3), with evidence of purifying selection and limited genetic diversity. Furthermore, reassortment events were rare, with an estimated rate of 0.045 events per lineage per year. Our findings show that primary forces shaping the local evolution of the influenza A(H3N2) in Bhutan are largely stochastic, with only sporadic instances of adaptive change, and thus underscore the importance of continuous surveillance to mitigate the impact of evolving strains.

Unmasking the Global Journey: Investigation of SARS-CoV-2 Variants of Interest Across Various Regions Through Whole-Genome and Phylogenetic Analysis

Background: The prolonged course of the Coronavirus Disease 2019 (COVID-19) pandemic and the virus's high mutation rate have sparked widespread interest in studying Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Research has shown that SARS-CoV-2 has evolved into numerous variants since its discovery. Objectives: This study aimed to investigate the differences in SARS-CoV-2 Variants of Interest (VOI) and Variants of Concern (VOC) from different geographical regions through phylogenetic analysis and mutational analysis. Methods: A total of 700 SARS-CoV-2 whole-genome sequences were retrieved from the GISAID database from January 1, 2021, to December 31, 2021. These sequences were aligned with the reference sequence (NC_045512) using Clustal Omega version 1.2.4. A phylogenetic tree was constructed using the IQ-TREE web server and visualized using ItoL. Results: The results revealed a fully resolved maximum likelihood tree with statistical support based on bootstrap values. The analysis demonstrated that Delta variant sequences clustered separately from other VOIs, VOCs, and outgroups. The shorter topology of the Delta variant showed that Africa branched away, similar to the Lambda and Gamma variants. Additionally, structural analysis identified three primarily uniform clusters in Europe, North America, and South America, which corresponded to the sister relationships observed in Clades 1, 2, and 7 topologies. These evolutionary trees were later linked to mutations in the spike, nucleocapsid, and nsp3 proteins, which displayed a high number of mutations. Conclusions: This study provides new insights into the evolving mutations of SARS-CoV-2 VOIs and VOCs across different regions of the world, contributing to our understanding of viral pathogenicity.

First detection of influenza A virus subtypes H1N1 and H3N8 in the Antarctic region: King George Island, 2023.

Influenza A virus is characterized by a segmented single-stranded RNA genome. Such organization of the virus genome determines the possibility of reassortment, which can lead to the emergence of new virus variants. The main natural reservoir of most influenza A virus subtypes are wild waterfowl. Seasonal migrations gather waterfowl from all major migration routes to nesting areas near the northern and southern polar circles. This makes intercontinental spread of influenza A viruses possible. Objective ‒ to conduct molecular genetic monitoring and study the phylogenetic relationships of influenza A virus variants circulating in Antarctica in 2023. We studied 84 samples of biological material obtained from birds and marine mammals in April‒May 2023 in coastal areas of Antarctica. For 3 samples, sequencing was performed on the Miseq, Illumina platform and phylogenetic analysis of the obtained nucleotide sequences of the influenza A virus genomes was performed. The circulation of avian influenza virus in the Antarctic region was confirmed. Heterogeneity of the pool of circulating variants of the influenza A virus (H3N8, H1N1) was revealed. Full-length genomes of the avian influenza virus were sequenced and posted in the GISAID database (EPI_ISL_19032103, 19174530, 19174467). The study of the genetic diversity of influenza A viruses circulating in the polar regions of the Earth and the identification of the conditions for the emergence of new genetic variants is a relevant task for the development of measures to prevent biological threats.

Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders.

The coronavirus disease of 2019 (COVID-19) pandemic is characterized by sequential emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, lineages, and sublineages, outcompeting previously circulating ones because of, among other factors, increased transmissibility and immune escape. We propose DeepAutoCoV, an unsupervised deep learning anomaly detection system to predict future dominant lineages (FDLs). We define FDLs as viral (sub)lineages that will constitute more than 10% of all the viral sequences added to the GISAID database on a given week. DeepAutoCoV is trained and validated by assembling global and country-specific data sets from over 16 million Spike protein sequences sampled over a period of about 4 years. DeepAutoCoV successfully flags FDLs at very low frequencies (0.01% - 3%), with median lead times of 4-17 weeks, and predicts FDLs ~5 and ~25 times better than a baseline approach For example, the B.1.617.2 vaccine reference strain was flagged as FDL when its frequency was only 0.01%, more than a year before it was considered for an updated COVID-19 vaccine. Furthermore, DeepAutoCoV outputs interpretable results by pinpointing specific mutations potentially linked to increased fitness, and may provide significant insights for the optimization of public health pre-emptive intervention strategies.

Evolutionary trajectory and characteristics of Mpox virus in 2023 based on a large-scale genomic surveillance in Shenzhen, China

The global epidemic of Mpox virus (MPXV) continues, and a local outbreak has occurred in Shenzhen city since June 2023. Herein, the evolutionary trajectory and characteristics of MPXV in 2023 were analyzed using 92 MPXV sequences from the Shenzhen outbreak and the available genomes from GISAID and GenBank databases. Phylogenetic tracing of the 92 MPXVs suggests that MPXVs in Shenzhen may have multiple sources of importation, and two main transmission chains have been established. The combination of phylogenetic relationships, epidemiological features, and mutation characteristics supports the emergence of a new lineage C.1.1. Together with the B.1 lineage diverging from the A.1 lineage, C.1.1 lineage diverging from the C.1 lineage may serve as another significant evolutionary events of MPXV. Moreover, increasing apolipoprotein B mRNA-editing catalytic polypeptide-like 3 (APOBEC3) related mutations, higher rate of missense mutations, and less mutations in the non-coding regions have been shown during MPXV evolution. Host regulation proteins of MPXV have accumulated considerable amino acid mutations since the B.1 lineage, and a lineage-defining APOBEC3-related mutation that disrupts the N2L gene encoding a viral innate immune modulator has been identified in the C.1.1 lineage. In summary, our study provides compelling evidence for the ongoing evolution of MPXV with specific features.

AlphaFold2 Reveals Structural Patterns of Seasonal Haplotype Diversification in SARS-CoV-2 Nucleocapsid Protein Variants.

The COVID-19 pandemic saw the emergence of various Variants of Concern (VOCs) that took the world by storm, often replacing the ones that preceded them. The characteristic mutant constellations of these VOCs increased viral transmissibility and infectivity. Their origin and evolution remain puzzling. With the help of data mining efforts and the GISAID database, a chronology of 22 haplotypes described viral evolution up until 23 July 2023. Since the three-dimensional atomic structures of proteins corresponding to the identified haplotypes are not available, ab initio methods were here utilized. Regions of intrinsic disorder proved to be important for viral evolution, as evidenced by the targeted change to the nucleocapsid (N) protein at the sequence, structure, and biochemical levels. The linker region of the N-protein, which binds to the RNA genome and self-oligomerizes for efficient genome packaging, was greatly impacted by mutations throughout the pandemic, followed by changes in structure and intrinsic disorder. Remarkably, VOC constellations acted co-operatively to balance the more extreme effects of individual haplotypes. Our strategy of mapping the dynamic evolutionary landscape of genetically linked mutations to the N-protein structure demonstrates the utility of ab initio modeling and deep learning tools for therapeutic intervention.

Comparative Atlas of SARS-CoV-2 Substitution Mutations: A Focus on Iranian Strains Amidst Global Trends.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new emerging coronavirus that caused coronavirus disease 2019 (COVID-19). Whole-genome tracking of SARS-CoV-2 enhanced our understanding of the mechanism of the disease, control, and prevention of COVID-19. we analyzed 3368 SARS-CoV-2 protein sequences from Iran and compared them with 15.6 million global sequences in the GISAID database, using the Wuhan-Hu-1 strain as a reference. Our investigation revealed that NSP12-P323L, ORF9c-G50N, NSP14-I42V, membrane-A63T, Q19E, and NSP3-G489S were found to be the most frequent mutations among Iranian SARS-CoV-2 sequences. Furthermore, it was observed that more than 94% of the SARS-CoV-2 genome, including NSP7, NSP8, NSP9, NSP10, NSP11, and ORF8, had no mutations when compared to the Wuhan-Hu-1 strain. Finally, our data indicated that the ORF3a-T24I, NSP3-G489S, NSP5-P132H, NSP14-I42V, envelope-T9I, nucleocapsid-D3L, membrane-Q19E, and membrane-A63T mutations might be responsible factors for the surge in the SARS-CoV-2 Omicron variant wave in Iran. real-time genomic surveillance is crucial for detecting new SARS-CoV-2 variants, updating diagnostic tools, designing vaccines, and understanding adaptation to new environments.

Unlocking the puzzle: non-defining mutations in SARS-CoV-2 proteome may affect vaccine effectiveness.

SARS-CoV-2 variants are defined by specific genome-wide mutations compared to the Wuhan genome. However, non-clade-defining mutations may also impact protein structure and function, potentially leading to reduced vaccine effectiveness. Our objective is to identify mutations across the entire viral genome rather than focus on individual mutations that may be associated with vaccine failure and to examine the physicochemical properties of the resulting amino acid changes. Whole-genome consensus sequences of SARS-CoV-2 from COVID-19 patients were retrieved from the GISAID database. Analysis focused on Dataset_1 (7,154 genomes from Italy) and Dataset_2 (8,819 sequences from Spain). Bioinformatic tools identified amino acid changes resulting from codon mutations with frequencies of 10% or higher, and sequences were organized into sets based on identical amino acid combinations. Non-defining mutations in SARS-CoV-2 genomes belonging to clades 21 L (Omicron), 22B/22E (Omicron), 22F/23A (Omicron) and 21J (Delta) were associated with vaccine failure. Four sets of sequences from Dataset_1 were significantly linked to low vaccine coverage: one from clade 21L with mutations L3201F (ORF1a), A27- (S) and G30- (N); two sets shared by clades 22B and 22E with changes A27- (S), I68- (S), R346T (S) and G30- (N); and one set shared by clades 22F and 23A containing changes A27- (S), F486P (S) and G30- (N). Booster doses showed a slight improvement in protection against Omicron clades. Regarding 21J (Delta) two sets of sequences from Dataset_2 exhibited the combination of non-clade mutations P2046L (ORF1a), P2287S (ORF1a), L829I (ORF1b), T95I (S), Y145H (S), R158- (S) and Q9L (N), that was associated with vaccine failure. Vaccine coverage associations appear to be influenced by the mutations harbored by marketed vaccines. An analysis of the physicochemical properties of amino acid revealed that primarily hydrophobic and polar amino acid substitutions occurred. Our results suggest that non-defining mutations across the proteome of SARS-CoV-2 variants could affect the extent of protection of the COVID-19 vaccine. In addition, alteration of the physicochemical characteristics of viral amino acids could potentially disrupt protein structure or function or both.

SARS-CoV-2 Genomic Epidemiology Dashboards: A Review of Functionality and Technological Frameworks for the Public Health Response.

During the coronavirus disease 2019 (COVID-19) pandemic, the number and types of dashboards produced increased to convey complex information using digestible visualizations. The pandemic saw a notable increase in genomic surveillance data, which genomic epidemiology dashboards presented in an easily interpretable manner. These dashboards have the potential to increase the transparency between the scientists producing pathogen genomic data and policymakers, public health stakeholders, and the public. This scoping review discusses the data presented, functional and visual features, and the computational architecture of six publicly available SARS-CoV-2 genomic epidemiology dashboards. We found three main types of genomic epidemiology dashboards: phylogenetic, genomic surveillance, and mutational. We found that data were sourced from different databases, such as GISAID, GenBank, and specific country databases, and these dashboards were produced for specific geographic locations. The key performance indicators and visualization used were specific to the type of genomic epidemiology dashboard. The computational architecture of the dashboards was created according to the needs of the end user. The genomic surveillance of pathogens is set to become a more common tool used to track ongoing and future outbreaks, and genomic epidemiology dashboards are powerful and adaptable resources that can be used in the public health response.

Unveiling the emergence of SARS-CoV-2 JN.1 sub-variant: Insights from the first cases at Charles Nicolle Hospital, Tunisia.

The JN.1 sub-variant is a new variant of the SARS-CoV-2 Omicron strain, derived from the BA.2.86 sub-variant. It was first detected in late 2023 and has quickly spread to many countries, becoming the most prevalent variant in some regions. JN.1 exhibits a unique mutation (L455S) in the spike protein compared to the BA.2.86 lineage, which may affect its transmissibility and immune evasion capabilities. JN.1 has been designated as a "variant of interest" by the World Health Organization due to its rapidly increasing spread and is being closely monitored for its impact on the COVID-19 pandemic. This study describes the emergence of SARS-CoV-2 JN.1 sub-variant in Tunisia, and reports its mutation profiles.Nasopharyngeal samples collected over a four-month period (October 2023 to January 2024) were subjected to RNA extraction and real-time RT-PCR confirmation of SARS-CoV-2 infection. The whole-genome sequencing was performed by an iSeq 100 sequencer and COVIDSeq kit reagents (Illumina, USA).Mutation analysis, using the NextClade platform and GISAID database, revealed the presence of JN.1 in 15 out of 80 positive cases (18.75%) during the study period.The emergence of JN.1 highlights the ongoing evolution of SARS-CoV-2 and the need for continued surveillance and research to better understand the characteristics and impact of emerging variants.

Dispersal history of SARS-CoV-2 variants Alpha, Delta, and Omicron (BA.1) in Spain.

Different factors influence the spread of SARS-CoV-2, from the inherent transmission capabilities of the different variants to the control measurements put in place. Here we studied the introduction of the Alpha, Delta, and Omicron-BA.1 variants of concern (VOCs) into Spain. For this, we collected genomic data from the GISAID database and combined it with connectivity data from different countries with Spain to perform a phylodynamic Bayesian analysis of the introductions. Our findings reveal that the introductions of these VOCs predominantly originated from France, especially in the case of Alpha. As travel restrictions were eased during the Delta and Omicron-BA.1 waves, the number of introductions from distinct countries increased, with the United Kingdom and Germany becoming significant sources of the virus. The largest number of introductions detected corresponded to the Delta wave, which was associated with fewer restrictions and the summer period, when Spain receives a considerable number of tourists. This research underscores the importance of monitoring international travel patterns and implementing targeted public health measures to manage the spread of SARS-CoV-2.

Genomic epidemiology of SARS-CoV-2 in Senegal in 2020-2021.

In Senegal, molecular diagnosis was widely used for the detection and management of COVID-19 patients. However, genomic surveillance was very limited in the public sector. This study aimed to share the experience of a Senegalese public sector laboratory in response to the COVID-19 pandemic, and to describe the distribution of variants circulating in 2020 and 2021. From July 2020 to December 2021, SARS-CoV-2 qRT-PCR was performed on nasopharyngeal samples from travelers and symptomatic patients at the Bacteriology and Virology Laboratory (LBV) of the Aristide le Dantec University Teaching Hospital. Samples with a cycle threshold (Ct) ≤ 30 were selected for whole-genome sequencing (WGS) using the Nanopore technology. In-house scripts were developed to study the spatial and temporal distribution of SARS-CoV-2 variants in Senegal, using our sequences and those retrieved from the GISAID database. Of 8,207 patients or travelers screened for SARS-CoV-2, 970 (11.8%) were positive and 386 had a Ct ≤ 30. WGS was performed on 133 samples. Concomitantly with high-quality sequences deposited in the GISAID database covering nine cities in Senegal in 2020 and 2021 (n = 1,539), we observed a high circulation of the 20A (B.1, B.1.416 and B.1.620) and 20B (B.1.1.420) lineages in 2020, while most of the samples belonged to Delta variants (AY34 and AY.34.1, 22%) in 2021. Despite its late involvement, COVID-19 diagnosis was routinely performed in LBV, but genomic characterization remained challenging. The genomic diversity of SARS-CoV-2 strains in Senegal reflected that observed worldwide during the first waves of the pandemic.

Dispersal history of SARS-CoV-2 in Galicia, Spain.

The dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission are influenced by a variety of factors, including social restrictions and the emergence of distinct variants. In this study, we delve into the origins and dissemination of the Alpha, Delta, and Omicron-BA.1 variants of concern in Galicia, northwest Spain. For this, we leveraged genomic data collected by the EPICOVIGAL Consortium and from the GISAID database, along with mobility information from other Spanish regions and foreign countries. Our analysis indicates that initial introductions during the Alpha phase were predominantly from other Spanish regions and France. However, as the pandemic progressed, introductions from Portugal and the United States became increasingly significant. The number of detected introductions varied from 96 and 101 for Alpha and Delta to 39 for Omicron-BA.1. Most of these introductions left a low number of descendants (<10), suggesting a limited impact on the evolution of the pandemic in Galicia. Notably, Galicia's major coastal cities emerged as critical hubs for viral transmission, highlighting their role in sustaining and spreading the virus. This research emphasizes the critical role of regional connectivity in the spread of SARS-CoV-2 and offers essential insights for enhancing public health strategies and surveillance measures.

Evolution of H6N6 viruses in China between 2014 and 2019 involves multiple reassortment events

ABSTRACT H6N6 avian influenza viruses (AIVs) have been widely detected in wild birds, poultry, and even mammals. Recently, H6N6 viruses were reported to be involved in the generation of H5 and H7 subtype viruses. To investigate the emergence, evolutionary pattern, and potential for an epidemic of H6N6 viruses, the complete genomes of 198 H6N6 viruses were analyzed, including 168 H6N6 viruses deposited in the NCBI and GISAID databases from inception to January 2019 and 30 isolates collected from China between November 2014 and January 2019. Using phylogenetic analysis, the 198 strains of H6N6 viruses were identified as 98 genotypes. Molecular clock analysis indicated that the evolution of H6N6 viruses in China was constant and not interrupted by selective pressure. Notably, the laboratory isolates reassorted with six subtype viruses: H6N2, H5N6, H7N9, H5N2, H4N2, and H6N8, resulting in nine novel H6N6 reassortment events. These results suggested that H6N6 viruses can act as an intermediary in the evolution of H5N6, H6N6, and H7N9 viruses. Animal experiments demonstrated that the 10 representative H6N6 viruses showed low pathogenicity in chickens and were capable of infecting mice without prior adaptation. Our findings suggest that H6N6 viruses play an important role in the evolution of AIVs, and it is necessary to continuously monitor and evaluate the potential epidemic of the H6N6 subtype viruses.

A comprehensive analysis of SARS-CoV-2 missense mutations indicates that all possible amino acid replacements in the viral proteins occurred within the first two-and-a-half years of the pandemic

The surveillance of COVID-19 pandemic has led to the determination of millions of genome sequences of the SARS-CoV-2 virus, with the accumulation of a wealth of information never collected before for an infectious disease. Exploring the information retrieved from the GISAID database reporting at that time >13 million genome sequences, we classified the 141,639 unique missense mutations detected in the first two-and-a-half years (up to October 2022) of the pandemic. Notably, our analysis indicates that 98.2 % of all possible conservative amino acid replacements occurred. Even non-conservative mutations were highly represented (73.9 %). For a significant number of residues (3 %), all possible replacements with the other nineteen amino acids have been observed. These observations strongly indicate that, in this time interval, the virus explored all possible alternatives in terms of missense mutations for all sites of its polypeptide chain and that those that are not observed severely affect SARS-CoV-2 integrity. The implications of the present findings go well beyond the structural biology of SARS-CoV-2 as the huge amount of information here collected and classified may be valuable for the elucidation of the sequence-structure-function relationships in proteins.

The RdRp genotyping of SARS-CoV-2 isolated from patients with different clinical spectrum of COVID-19

BackgroundThe evolution of SARS-CoV-2 has been observed from the very beginning of the fight against COVID-19, some mutations are indicators of potentially dangerous variants of the virus. However, there is no clear association between the genetic variants of SARS-CoV-2 and the severity of COVID-19. We aimed to analyze the genetic variability of RdRp in correlation with different courses of COVID-19.ResultsThe prospective study included 77 samples of SARS-CoV-2 isolated from outpatients (1st degree of severity) and hospitalized patients (2nd, 3rd and 4th degree of severity). The retrospective analyses included 15,898,266 cases of SARS-CoV-2 genome sequences deposited in the GISAID repository. Single-nucleotide variants were identified based on the four sequenced amplified fragments of SARS-CoV-2. The analysis of the results was performed using appropriate statistical methods, with p < 0.05, considered statistically significant. Additionally, logistic regression analysis was performed to predict the strongest determinants of the observed relationships. The number of mutations was positively correlated with the severity of the COVID-19, and older male patients. We detected four mutations that significantly increased the risk of hospitalization of COVID-19 patients (14676C > T, 14697C > T, 15096 T > C, and 15279C > T), while the 15240C > T mutation was common among strains isolated from outpatients. The selected mutations were searched worldwide in the GISAID database, their presence was correlated with the severity of COVID-19.ConclusionIdentified mutations have the potential to be used to assess the increased risk of hospitalization in COVID-19 positive patients. Experimental studies and extensive epidemiological data are needed to investigate the association between individual mutations and the severity of COVID-19.

Global and genetic diversity of SARS-CoV-2 in wastewater

The analysis of SARS-CoV-2 in wastewater has enabled us to better understand the spread and evolution of the virus worldwide. To deepen our understanding of its epidemiological and genomic characteristics, we analyzed 10,147 SARS-CoV-2 sequences from 5 continents and 21 countries that were deposited in the GISAID database up until January 31, 2023. Our results revealed over 100 independent lineages of the virus circulating in water samples from March 2020 to January 2023, including variants of interest and concern. We observed four clearly defined periods of global distribution of these variants over time, with one variant being replaced by another. Interestingly, we found that SARS-CoV-2 water-borne sequences from different countries had a close phylogenetic relationship. Additionally, 40 SARS-CoV-2 water-borne sequences from Europe and the USA did not show any phylogenetic relationship with SARS-CoV-2 human sequences. We also identified a significant number of non-synonymous mutations, some of which were detected in previously reported cryptic lineages. Among the countries analyzed, France and the USA showed the highest degree of sequence diversity, while Austria reported the highest number of genomes (6,296). Our study provides valuable information about the epidemiological and genomic diversity of SARS-CoV-2 in wastewater, which can be employed to support public health initiatives and preparedness.