GISAID's Role in Pandemic Response

A positive selection at binding site 501 in the B.1 lineage might have triggered the highly infectious sub-lineages of SARS-CoV-2

The descendants of the B lineage are the most predominant variants among the SARS-CoV-2 virus due to the incorporation of new mutations augmenting the infectivity of the virus. There is a substantial increase in the transition transversion bias, nucleotide diversity and purifying selection on the spike protein in the descendants of the B lineage of the SARS-CoV-2 virus on a temporal scale. A strong bias for C-to-U substitutions is found in the genes encoding spike protein in this lineage. The positive selection has operated on the spike gene of B lineages and its sub-lineages. The B.1 lineage has undergone positive selection on site 501 of the receptor binding domain ultimately reflected in a key substitution N501Y in its three descendant lineages namely B.1.1.7, B.1.351 and P.1. The intensity of purifying selection on the multiple sites of the spike gene has increased substantially in the sub-lineages of B.1 in a timescale. The binding site 501 on the spike protein in B lineage is found to coevolve with other amino acid sites. This study sheds light on the evolutionary trajectory of the B lineage into highly infectious descendants in the recent past under the influence of positive and purifying selection exerted by natural immunity and vaccination of the host.

De novo design of potential peptide analogs against the main protease of Omicron variant using in silico studies

SARS-CoV-2 and its variants are crossing the immunity barrier induced through vaccination. Recent Omicron sub-variants are highly transmissible and have a low mortality rate. Despite the low severity of Omicron variants, these new variants are known to cause acute post-infectious syndromes. Nowadays, novel strategies to develop new potential inhibitors for SARS-CoV-2 and other Omicron variants have gained prominence. For viral replication and survival the main protease of SARS-CoV-2 plays a vital role. Peptide-like inhibitors that mimic the substrate peptide have already proved to be effective in inhibiting the Mpro of SARS-CoV-2 variants. Our systematic canonical amino acid point mutation analysis on the native peptide has revealed various ways to improve the native peptide of the main protease. Multi mutation analysis has led us to identify and design potent peptide-analog inhibitors that act against the Mpro of the Omicron sub-variants. Our in-depth analysis of all-atom molecular dynamics studies has paved the way to characterize the atomistic behavior of Mpro in Omicron variants. Our goal is to develop potent peptide-analogs that could be therapeutically effective against Omicron and its sub-variants.

Wastewater tiling amplicon sequencing in sentinel sites reveals longitudinal dynamics of SARS-CoV-2 variants prevalence

The ongoing evolution of SARS-CoV-2 is a significant concern, especially with the decrease in clinical sequencing efforts, which impedes the ability of public health sectors to prepare for the emergence of new variants and potential COVID-19 outbreaks. Wastewater-based epidemiology (WBE) has been proposed as a surveillance program to detect and monitor the SARS-CoV-2 variants being transmitted in communities. However, research is limited in evaluating the effectiveness of wastewater collection at sentinel sites for monitoring disease prevalence and variant dynamics, especially in terms of inferring the epidemic patterns on a broader scale, such as at the state/province level. This study utilized a multiplexed tiling amplicon-based sequencing (ATOPlex) to track the longitudinal dynamics of variant of concern (VOC) in wastewater collected from municipalities in Queensland, Australia, spanning from 2020 to 2022. We demonstrated that wastewater epidemiology measured by ATOPlex exhibited a strong and consistent correlation with the number of daily confirmed cases. The VOC dynamics observed in wastewater closely aligned with the dynamic profile reported by clinical sequencing. Wastewater sequencing has the potential to provide early warning information for emerging variants. These findings suggest that WBE at sentinel sites, coupled with sensitive sequencing methods, provides a reliable and long-term disease surveillance strategy.

Prevalence of SARS-CoV-2 in domestic cats (Felis catus) during COVID-19 pandemic in Latvia

BACKGROUND

The causative agent of the COVID-19 pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is of zoonotic origin and has shown reverse zoonotic transmissibility.

OBJECTIVES

The aim of this cross-sectional study was to investigate the serological and molecular prevalence of SARS-CoV-2 infection in the domestic cat (Felis catus) population from Latvia in natural conditions and subsequently perform viral genome analysis.

METHODS

Oropharyngeal and rectal swabs and blood samples were collected from 273 domestic cats during the second wave of COVID-19 infection in Latvia. Molecular prevalence was determined by using reverse transcriptase-polymerase chain reaction (RT-PCR). Serum samples were analysed via double antigen enzyme-linked immunosorbent assay targeting the antibody against the nucleocapsid protein of SARS-CoV-2. Positive swab samples were analysed using whole viral genome sequencing and subsequent phylogenetic analysis of the whole genome sequencing data of the samples was performed.

RESULTS

The overall SARS-CoV-2 RT-PCR positivity and seroprevalence was 1.1% (3/273) and 2.6% (7/273), respectively. The SARS-CoV-2 genome sequences from three RT-PCR positive cats were assigned to the three common lineages (PANGOLIN lineage S.1.; B.1.177.60. and B.1.1.7.) circulating in Latvia during the particular period of time.

CONCLUSIONS

These findings indicate that feline infection with SARS-CoV-2 occurred during the second wave of the COVID-19 pandemic in Latvia, yet the overall prevalence was low. In addition, it seems like no special 'cat' pre-adaptations were necessary for successful infection of cats by the common lineages of SARS-CoV-2.

Evaluation of the Impact of Concentration and Extraction Methods on the Targeted Sequencing of Human Viruses from Wastewater

Sequencing human viruses in wastewater is challenging due to their low abundance compared to the total microbial background. This study compared the impact of four virus concentration/extraction methods (Innovaprep, Nanotrap, Promega, and Solids extraction) on probe-capture enrichment for human viruses followed by sequencing. Different concentration/extraction methods yielded distinct virus profiles. Innovaprep ultrafiltration (following solids removal) had the highest sequencing sensitivity and richness, resulting in the successful assembly of several near-complete human virus genomes. However, it was less sensitive in detecting SARS-CoV-2 by digital polymerase chain reaction (dPCR) compared to Promega and Nanotrap. Across all preparation methods, astroviruses and polyomaviruses were the most highly abundant human viruses, and SARS-CoV-2 was rare. These findings suggest that sequencing success can be increased using methods that reduce nontarget nucleic acids in the extract, though the absolute concentration of total extracted nucleic acid, as indicated by Qubit, and targeted viruses, as indicated by dPCR, may not be directly related to targeted sequencing performance. Further, using broadly targeted sequencing panels may capture viral diversity but risks losing signals for specific low-abundance viruses. Overall, this study highlights the importance of aligning wet lab and bioinformatic methods with specific goals when employing probe-capture enrichment for human virus sequencing from wastewater.

Nanomolar anti-SARS-CoV-2 Omicron activity of the host-directed TMPRSS2 inhibitor N-0385 and synergistic action with direct-acting antivirals

SARS-CoV-2 Omicron subvariants with increased transmissibility and immune evasion are spreading globally with alarming persistence. Whether the mutations and evolution of spike (S) Omicron subvariants alter the viral hijacking of human TMPRSS2 for viral entry remains to be elucidated. This is particularly important to investigate because of the large number and diversity of mutations of S Omicron subvariants reported since the emergence of BA.1. Here we report that human TMPRSS2 is a molecular determinant of viral entry for all the Omicron clinical isolates tested in human lung cells, including ancestral Omicron subvariants (BA.1, BA.2, BA.5), contemporary Omicron subvariants (BQ.1.1, XBB.1.5, EG.5.1) and currently circulating Omicron BA.2.86. First, we used a co-transfection assay to demonstrate the endoproteolytic cleavage by TMPRSS2 of spike Omicron subvariants. Second, we found that N-0385, a highly potent TMPRSS2 inhibitor, is a robust entry inhibitor of virus-like particles harbouring the S protein of Omicron subvariants. Third, we show that N-0385 exhibits nanomolar broad-spectrum antiviral activity against live Omicron subvariants in human Calu-3 lung cells and primary patient-derived bronchial epithelial cells. Interestingly, we found that N-0385 is 10-20 times more potent than the repositioned TMPRSS2 inhibitor, camostat, against BA.5, EG.5.1, and BA.2.86. We further found that N-0385 shows broad synergistic activity with clinically approved direct-acting antivirals (DAAs), i.e., remdesivir and nirmatrelvir, against Omicron subvariants, demonstrating the potential therapeutic benefits of a multi-targeted treatment based on N-0385 and DAAs.

Forecasting the spread of COVID-19 based on policy, vaccination, and Omicron data

The COVID-19 pandemic caused by the novel SARS-COV-2 virus poses a great risk to the world. During the COVID-19 pandemic, observing and forecasting several important indicators of the epidemic (like new confirmed cases, new cases in intensive care unit, and new deaths for each day) helped prepare the appropriate response (e.g., creating additional intensive care unit beds, and implementing strict interventions). Various predictive models and predictor variables have been used to forecast these indicators. However, the impact of prediction models and predictor variables on forecasting performance has not been systematically well analyzed. Here, we compared the forecasting performance using a linear mixed model in terms of prediction models (mathematical, statistical, and AI/machine learning models) and predictor variables (vaccination rate, stringency index, and Omicron variant rate) for seven selected countries with the highest vaccination rates. We decided on our best models based on the Bayesian Information Criterion (BIC) and analyzed the significance of each predictor. Simple models were preferred. The selection of the best prediction models and the use of Omicron variant rate were considered essential in improving prediction accuracies. For the test data period before Omicron variant emergence, the selection of the best models was the most significant factor in improving prediction accuracy. For the test period after Omicron emergence, Omicron variant rate use was considered essential in deciding forecasting accuracy. For prediction models, ARIMA, lightGBM, and TSGLM generally performed well in both test periods. Linear mixed models with country as a random effect has proven that the choice of prediction models and the use of Omicron data was significant in determining forecasting accuracies for the highly vaccinated countries. Relatively simple models, fit with either prediction model or Omicron data, produced best results in enhancing forecasting accuracies with test data.

Global pattern and determinant for interaction of seasonal influenza viruses

BACKGROUND

The prevalence of different types/subtypes varies across seasons and countries for seasonal influenza viruses, indicating underlying interactions between types/subtypes. The global interaction patterns and determinants for seasonal influenza types/subtypes need to be explored.

METHODS

Influenza epidemiological surveillance data, as well as multidimensional data that include population-related, environment-related, and virus-related factors from 55 countries worldwide were used to explore type/subtype interactions based on Spearman correlation coefficient. The machine learning method Extreme Gradient Boosting (XGBoost) and interpretable framework SHapley Additive exPlanation (SHAP) were utilized to quantify contributing factors and their effects on interactions among influenza types/subtypes. Additionally, causal relationships between types/subtypes were also explored based on Convergent Cross-mapping (CCM).

RESULTS

A consistent globally negative correlation exists between influenza A/H3N2 and A/H1N1. Meanwhile, interactions between influenza A (A/H3N2, A/H1N1) and B show significant differences across countries, primarily influenced by population-related factors. Influenza A has a stronger driving force than influenza B, and A/H3N2 has a stronger driving force than A/H1N1.

CONCLUSION

The research elucidated the globally complex and heterogeneous interaction patterns among influenza type/subtypes, identifying key factors shaping their interactions. This sheds light on better seasonal influenza prediction and model construction, informing targeted prevention strategies and ultimately reducing the global burden of seasonal influenza.

COVID-19 outbreak and genomic investigation in an inpatient behavioral health unit

Background

Inpatient behavioral health units (BHUs) had unique challenges in implementing interventions to mitigate coronavirus disease 2019 (COVID-19) transmission, in part due to socialization in BHU settings. The objective of this study was to identify the transmission routes and the efficacy of the mitigation strategies employed during a COVID-19 outbreak in an inpatient BHU during the Omicron surge from December 2021 to January 2022.

Methods

An outbreak investigation was performed after identifying 2 COVID-19-positive BHU inpatients on December 16 and 20, 2021. Mitigation measures involved weekly point prevalence testing for all inpatients, healthcare workers (HCWs), and staff, followed by infection prevention mitigation measures and molecular surveillance. Whole-genome sequencing on a subset of COVID-19-positive individuals was performed to identify the outbreak source. Finally, an outbreak control sustainability plan was formulated for future BHU outbreak resurgences.

Results

We identified 35 HCWs and 8 inpatients who tested positive in the BHU between December 16, 2021, and January 17, 2022. We generated severe acute respiratory coronavirus virus 2 (SARS-CoV-2) genomes from 15 HCWs and all inpatients. Phylogenetic analyses revealed 3 distinct but genetically related clusters: (1) an HCW and inpatient outbreak likely initiated by staff, (2) an HCW and inpatient outbreak likely initiated by an inpatient visitor, and (3) an HCW-only cluster initiated by staff.

Conclusions

Distinct transmission clusters are consistent with multiple, independent SARS-CoV-2 introductions with further inpatient transmission occurring in communal settings. The implemented outbreak control plan comprised of enhanced personal protective equipment requirements, limited socialization, and molecular surveillance likely minimized disruptions to patient care as a model for future pandemics.

INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance

BACKGROUND

Implementation of clinical metagenomics and pathogen genomic surveillance can be particularly challenging due to the lack of bioinformatics tools and/or expertise. In order to face this challenge, we have previously developed INSaFLU, a free web-based bioinformatics platform for virus next-generation sequencing data analysis. Here, we considerably expanded its genomic surveillance component and developed a new module (TELEVIR) for metagenomic virus identification.

RESULTS

The routine genomic surveillance component was strengthened with new workflows and functionalities, including (i) a reference-based genome assembly pipeline for Oxford Nanopore technologies (ONT) data; (ii) automated SARS-CoV-2 lineage classification; (iii) Nextclade analysis; (iv) Nextstrain phylogeographic and temporal analysis (SARS-CoV-2, human and avian influenza, monkeypox, respiratory syncytial virus (RSV A/B), as well as a "generic" build for other viruses); and (v) algn2pheno for screening mutations of interest. Both INSaFLU pipelines for reference-based consensus generation (Illumina and ONT) were benchmarked against commonly used command line bioinformatics workflows for SARS-CoV-2, and an INSaFLU snakemake version was released. In parallel, a new module (TELEVIR) for virus detection was developed, after extensive benchmarking of state-of-the-art metagenomics software and following up-to-date recommendations and practices in the field. TELEVIR allows running complex workflows, covering several combinations of steps (e.g., with/without viral enrichment or host depletion), classification software (e.g., Kaiju, Kraken2, Centrifuge, FastViromeExplorer), and databases (RefSeq viral genome, Virosaurus, etc.), while culminating in user- and diagnosis-oriented reports. Finally, to potentiate real-time virus detection during ONT runs, we developed findONTime, a tool aimed at reducing costs and the time between sample reception and diagnosis.

CONCLUSIONS

The accessibility, versatility, and functionality of INSaFLU-TELEVIR are expected to supply public and animal health laboratories and researchers with a user-oriented and pan-viral bioinformatics framework that promotes a strengthened and timely viral metagenomic detection and routine genomics surveillance. INSaFLU-TELEVIR is compatible with Illumina, Ion Torrent, and ONT data and is freely available at https://insaflu.insa.pt/ (online tool) and https://github.com/INSaFLU (code).

Molecular Insights into the Variability in Infection and Immune Evasion Capabilities of SARS-CoV-2 Variants: A Sequence and Structural Investigation of the RBD Domain

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continuously emerge, an increasing number of mutations are accumulating in the Spike protein receptor-binding domain (RBD) region. Through sequence analysis of various Variants of Concern (VOC), we identified that they predominantly fall within the ο lineage although recent variants introduce any novel mutations in the RBD. Molecular dynamics simulations were employed to compute the binding free energy of these variants with human Angiotensin-converting enzyme 2 (ACE2). Structurally, the binding interface of the ο RBD displays a strong positive charge, complementing the negatively charged binding interface of ACE2, resulting in a significant enhancement in the electrostatic potential energy for the ο variants. Although the increased potential energy is partially offset by the rise in polar solvation free energy, enhanced electrostatic potential contributes to the long-range recognition between the ο variant's RBD and ACE2. We also conducted simulations of glycosylated ACE2-RBD proteins. The newly emerged ο (JN.1) variant has added a glycosylation site at N-354@RBD, which significantly weakened its binding affinity with ACE2. Further, our interaction studies with three monoclonal antibodies across multiple SARS-CoV-2 strains revealed a diminished neutralization efficacy against the ο variants, primarily attributed to the electrostatic repulsion between the antibodies and RBD interface. Considering the characteristics of the ο variant and the trajectory of emerging strains, we propose that newly developed antibodies against SARS-CoV-2 RBD should have surfaces rich in negative potential and, postbinding, exhibit strong van der Waals interactions. These findings provide invaluable guidance for the formulation of future therapeutic strategies.

Lessons learned: overcoming common challenges in reconstructing the SARS-CoV-2 genome from short-read sequencing data via CoVpipe2

Background

Accurate genome sequences form the basis for genomic surveillance programs, the added value of which was impressively demonstrated during the COVID-19 pandemic by tracing transmission chains, discovering new viral lineages and mutations, and assessing them for infectiousness and resistance to available treatments. Amplicon strategies employing Illumina sequencing have become widely established for variant detection and reference-based reconstruction of SARS-CoV-2 genomes, and are routine bioinformatics tasks. Yet, specific challenges arise when analyzing amplicon data, for example, when crucial and even lineage-determining mutations occur near primer sites.

Methods

We present CoVpipe2, a bioinformatics workflow developed at the Public Health Institute of Germany to reconstruct SARS-CoV-2 genomes based on short-read sequencing data accurately. The decisive factor here is the reliable, accurate, and rapid reconstruction of genomes, considering the specifics of the used sequencing protocol. Besides fundamental tasks like quality control, mapping, variant calling, and consensus generation, we also implemented additional features to ease the detection of mixed samples and recombinants.

Results

We highlight common pitfalls in primer clipping, detecting heterozygote variants, and dealing with low-coverage regions and deletions. We introduce CoVpipe2 to address the above challenges and have compared and successfully validated the pipeline against selected publicly available benchmark datasets. CoVpipe2 features high usability, reproducibility, and a modular design that specifically addresses the characteristics of short-read amplicon protocols but can also be used for whole-genome short-read sequencing data.

Conclusions

CoVpipe2 has seen multiple improvement cycles and is continuously maintained alongside frequently updated primer schemes and new developments in the scientific community. Our pipeline is easy to set up and use and can serve as a blueprint for other pathogens in the future due to its flexibility and modularity, providing a long-term perspective for continuous support. CoVpipe2 is written in Nextflow and is freely accessible from \href{https://github.com/rki-mf1/CoVpipe2}{github.com/rki-mf1/CoVpipe2} under the GPL3 license.

A Comparative Analysis of Innate Immune Responses and the Structural Characterization of Spike from SARS-CoV-2 Gamma Variants and Subvariants

The SARS-CoV-2 P.1 variant, responsible for an outbreak in Manaus, Brazil, is distinguished by 12 amino acid differences in the S protein, potentially increasing its ACE-2 affinity and immune evasion capability. We investigated the innate immune response of this variant compared to the original B.1 strain, particularly concerning cytokine production. Blood samples from three severe COVID-19 patients were analyzed post-infection with both strains. Results showed no significant difference in cytokine production of mononuclear cells and neutrophils for either variant. While B.1 had higher cytopathogenicity, neither showed viral replication in mononuclear cells. Structural analyses of the S protein highlighted physicochemical variations, which might be linked to the differences in infectivity between the strains. Our studies point to the increased infectivity of P.1 could stem from altered immunogenicity and receptor-binding affinity.

Locations and structures of influenza A virus packaging-associated signals and other functional elements via an in silico pipeline for predicting constrained features in RNA viruses

Influenza A virus contains regions of its segmented genome associated with ability to package the segments into virions, but many such regions are poorly characterised. We provide detailed predictions of the key locations within these packaging-associated regions, and their structures, by applying a recently-improved pipeline for delineating constrained regions in RNA viruses and applying structural prediction algorithms. We find and characterise other known constrained regions within influenza A genomes, including the region associated with the PA-X frameshift, regions associated with alternative splicing, and constraint around the initiation motif for a truncated PB1 protein, PB1-N92, associated with avian viruses. We further predict the presence of constrained regions that have not previously been described. The extra characterisation our work provides allows investigation of these key regions for drug target potential, and points towards determinants of packaging compatibility between segments.

Single-center Outcomes After Liver Transplantation With SARS-CoV-2-Positive Donors: An Argument for Increased Utilization

Background

The COVID-19 pandemic has led to an increase in SARS-CoV-2-test positive potential organ donors. The benefits of life-saving liver transplantation (LT) must be balanced against the potential risk of donor-derived viral transmission. Although emerging evidence suggests that the use of COVID-19-positive donor organs may be safe, granular series thoroughly evaluating safety are still needed. Results of 29 consecutive LTs from COVID-19-positive donors at a single center are presented here.

Methods

A retrospective cohort study of LT recipients between April 2020 and December 2022 was conducted. Differences between recipients of COVID-19-positive (n = 29 total; 25 index, 4 redo) and COVID-19-negative (n = 472 total; 454 index, 18 redo) deceased donor liver grafts were compared.

Results

COVID-19-positive donors were significantly younger (P = 0.04) and had lower kidney donor profile indices (P = 0.04) than COVID-19-negative donors. Recipients of COVID-19-positive donor grafts were older (P = 0.04) but otherwise similar to recipients of negative donors. Donor SARS-CoV-2 infection status was not associated with a overall survival of recipients (hazard ratio, 1.11; 95% confidence interval, 0.24-5.04; P = 0.89). There were 3 deaths among recipients of liver grafts from COVID-19-positive donors. No death seemed virally mediated because there was no qualitative association with peri-LT antispike antibody titers, post-LT prophylaxis, or SARS-CoV-2 variants.

Conclusions

The utilization of liver grafts from COVID-19-positive donors was not associated with a decreased overall survival of recipients. There was no suggestion of viral transmission from donor to recipient. The results from this large single-center study suggest that COVID-19-positive donors may be used safely to expand the deceased donor pool.

Activity and inhibition of the SARS-CoV-2 Omicron nsp13 R392C variant using RNA duplex unwinding assays

SARS-CoV-2 nsp13 helicase is an essential enzyme for viral replication and a promising target for antiviral drug development. This study compares the double-stranded RNA (dsRNA) unwinding activity of nsp13 and the Omicron nsp13R392C variant, which is predominant in currently circulating lineages. Using in vitro gel- and fluorescence-based assays, we found that both nsp13 and nsp13R392C have dsRNA unwinding activity with equivalent kinetics. Furthermore, the R392C mutation had no effect on the efficiency of the nsp13-specific helicase inhibitor SSYA10-001. We additionally confirmed the activity of several other helicase inhibitors against nsp13, including punicalagin that inhibited dsRNA unwinding at nanomolar concentrations. Overall, this study reveals the utility of using dsRNA unwinding assays to screen small molecules for antiviral activity against nsp13 and the Omicron nsp13R392C variant. Continual monitoring of newly emergent variants will be essential for considering resistance profiles of lead compounds as they are advanced towards next-generation therapeutic development.

The SARS-CoV-2 neutralizing antibody response to SD1 and its evasion by BA.2.86

Under pressure from neutralising antibodies induced by vaccination or infection the SARS-CoV-2 spike gene has become a hotspot for evolutionary change, leading to the failure of all mAbs developed for clinical use. Most potent antibodies bind to the receptor binding domain which has become heavily mutated. Here we study responses to a conserved epitope in sub-domain-1 (SD1) of spike which have become more prominent because of mutational escape from antibodies directed to the receptor binding domain. Some SD1 reactive mAbs show potent and broad neutralization of SARS-CoV-2 variants. We structurally map the dominant SD1 epitope and provide a mechanism of action by blocking interaction with ACE2. Mutations in SD1 have not been sustained to date, but one, E554K, leads to escape from mAbs. This mutation has now emerged in several sublineages including BA.2.86, reflecting selection pressure on the virus exerted by the increasing prominence of the anti-SD1 response.

Genetic Diversity of Avian Influenza Viruses Detected in Waterbirds in Northeast Italy Using Two Different Sampling Strategies

Avian influenza viruses (AIVs), which circulate endemically in wild aquatic birds, pose a significant threat to poultry and raise concerns for their zoonotic potential. From August 2021 to April 2022, a multi-site cross-sectional study involving active AIV epidemiological monitoring was conducted in wetlands of the Emilia-Romagna region, northern Italy, adjacent to densely populated poultry areas. A total of 129 cloacal swab samples (CSs) and 407 avian faecal droppings samples (FDs) were collected, with 7 CSs (5.4%) and 4 FDs (1%) testing positive for the AIV matrix gene through rRT-PCR. A COI-barcoding protocol was applied to recognize the species of origin of AIV-positive FDs. Multiple low-pathogenic AIV subtypes were identified, and five of these were isolated, including an H5N3, an H1N1, and three H9N2 in wild ducks. Following whole-genome sequencing, phylogenetic analyses of the hereby obtained strains showed close genetic relationships with AIVs detected in countries along the Black Sea/Mediterranean migratory flyway. Notably, none of the analyzed gene segments were genetically related to HPAI H5N1 viruses of clade 2.3.4.4b isolated from Italian poultry during the concurrent 2021-2022 epidemic. Overall, the detected AIV genetic diversity emphasizes the necessity for ongoing monitoring in wild hosts using diverse sampling strategies and whole-genome sequencing.

Interaction between host G3BP and viral nucleocapsid protein regulates SARS-CoV-2 replication and pathogenicity

G3BP1/2 are paralogous proteins that promote stress granule formation in response to cellular stresses, including viral infection. The nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inhibits stress granule assembly and interacts with G3BP1/2 via an ITFG motif, including residue F17, in the N protein. Prior studies examining the impact of the G3PB1-N interaction on SARS-CoV-2 replication have produced inconsistent findings, and the role of this interaction in pathogenesis is unknown. Here, we use structural and biochemical analyses to define the residues required for G3BP1-N interaction and structure-guided mutagenesis to selectively disrupt this interaction. We find that N-F17A mutation causes highly specific loss of interaction with G3BP1/2. SARS-CoV-2 N-F17A fails to inhibit stress granule assembly in cells, has decreased viral replication, and causes decreased pathology in vivo. Further mechanistic studies indicate that the N-F17-mediated G3BP1-N interaction promotes infection by limiting sequestration of viral genomic RNA (gRNA) into stress granules.

Epidemiology of the 2022 Mpox Outbreak in the US Veterans Health Administration

BACKGROUND

In May 2022, mpox cases were reported in nonendemic countries, including the United States. We examined mpox infections in the Veterans Health Administration (VHA).

METHODS

Mpox diagnostic and whole genome sequencing (WGS) results, demographics, risk factors, hospitalizations, exposures, deaths, and pharmacy and immunization data were obtained from VHA data sources (23 May 2022-31 May 2023).

RESULTS

Of 1144 Veterans tested, 251 (21.9%) were presumptive positive for nonvariola orthopoxvirus (NVO) or confirmed positive for NVO and Monkeypox virus (MPXV). Incidence rate was 7.5 per 100 000 Veterans in care, with the highest rate observed in Veterans aged 25-34 years (13.83 cases per 100 000). Higher odds of NVO or NVO/MPXV positivity was associated with male sex; non-Hispanic Black race/ethnicity; syphilis or human immunodeficiency virus (HIV) positivity; or genital/rectal sample site, whereas older age and vaccination with JYNNEOS or vaccinia (smallpox) had lower odds. Among 209 with confirmatory testing, 90.4% reported intimate contact and/or an epidemiological link, 84.5% were men who have sex with men (MSM), 24.2% received tecovirimat, and 8.1% were hospitalized with 1 death. Eighty-six sequenced samples had evaluable WGS results. All were clade IIb, representing 10 different lineages from 20 states and the District of Columbia.

CONCLUSIONS

Mpox affected younger, MSM, non-Hispanic Black, and HIV/syphilis-positive men among US Veterans. Viral diversity was noted across geographic regions. At-risk Veterans would benefit from vaccination and risk reduction strategies for mpox and other sexually transmitted infections.

Whole-Genome Sequencing and Mutation Analyses of SARS-CoV-2 Isolates from Indonesia

The SARS-CoV-2 infection that caused the COVID-19 pandemic has become a significant public health concern. New variants with distinct mutations have emerged, potentially impacting its infectivity, immune evasion capacity, and vaccine response. A whole-genome sequencing study of 292 SARS-CoV-2 isolates collected from selected regions of Indonesia between January and October 2021 was performed to identify the distribution of SARS-CoV-2 variants and common mutations in Indonesia. During January-April 2021, Indonesian lineages B.1.466.2 and B.1.470 dominated, but from May 2021, Delta's AY.23 lineage outcompeted them. An analysis of 7515 published sequences from January 2021 to June 2022 revealed a decline in Delta in November 2021, followed by the emergence of Omicron variants in December 2021. We identified C241T (5'UTR), P314L (NSP12b), F106F (NSP3), and D614G (Spike) mutations in all sequences. The other common substitutions included P681R (76.4%) and T478K (60%) in Spike, D377Y in Nucleocapsid (61%), and I82T in Membrane (60%) proteins. Breakthrough infection and prolonged viral shedding cases were associated with Delta variants carrying the Spike T19R, G142D, L452R, T478K, D614G, P681R, D950N, and V1264L mutations. The dynamic of SARS-CoV-2 variants in Indonesia highlights the importance of continuous genomic surveillance in monitoring and identifying potential strains leading to disease outbreaks.

Amplidiff: an optimized amplicon sequencing approach to estimating lineage abundances in viral metagenomes

BACKGROUND

Metagenomic profiling algorithms commonly rely on genomic differences between lineages, strains, or species to infer the relative abundances of sequences present in a sample. This observation plays an important role in the analysis of diverse microbial communities, where targeted sequencing of 16S and 18S rRNA, both well-known hypervariable genomic regions, have led to insights into microbial diversity and the discovery of novel organisms. However, the variable nature of discriminatory regions can also act as a double-edged sword, as the sought-after variability can make it difficult to design primers for their amplification through PCR. Moreover, the most variable regions are not necessarily the most informative regions for the purpose of differentiation; one should focus on regions that maximize the number of lineages that can be distinguished.

RESULTS

Here we present AmpliDiff, a computational tool that simultaneously finds highly discriminatory genomic regions in viral genomes of a single species, as well as primers allowing for the amplification of these regions. We show that regions and primers found by AmpliDiff can be used to accurately estimate relative abundances of SARS-CoV-2 lineages, for example in wastewater sequencing data. We obtain errors that are comparable with using whole genome information to estimate relative abundances. Furthermore, our results show that AmpliDiff is robust against incomplete input data and that primers designed by AmpliDiff also bind to genomes sampled months after the primers were selected.

CONCLUSIONS

With AmpliDiff we provide an effective, cost-efficient alternative to whole genome sequencing for estimating lineage abundances in viral metagenomes.

Next-generation treatments: Immunotherapy and advanced therapies for COVID-19

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in 2019 following prior outbreaks of coronaviruses like SARS and MERS in recent decades, underscoring their high potential of infectivity in humans. Insights from previous outbreaks of SARS and MERS have played a significant role in developing effective strategies to mitigate the global impact of SARS-CoV-2. As of January 7, 2024, there have been 774,075,242 confirmed cases of COVID-19 worldwide. To date, 13.59 billion vaccine doses have been administered, and there have been 7,012,986 documented fatalities (https://www.who.int/) Despite significant progress in addressing the COVID-19 pandemic, the rapid evolution of SARS-CoV-2 challenges human defenses, presenting ongoing global challenges. The emergence of new SARS-CoV-2 lineages, shaped by mutation and recombination processes, has led to successive waves of infections. This scenario reveals the need for next-generation vaccines as a crucial requirement for ensuring ongoing protection against SARS-CoV-2. This demand calls for formulations that trigger a robust adaptive immune response without leading the acute inflammation linked with the infection. Key mutations detected in the Spike protein, a critical target for neutralizing antibodies and vaccine design -specifically within the Receptor Binding Domain region of Omicron variant lineages (B.1.1.529), currently dominant worldwide, have intensified concerns due to their association with immunity evasion from prior vaccinations and infections. As the world deals with this evolving threat, the narrative extends to the realm of emerging variants, each displaying new mutations with implications that remain largely misunderstood. Notably, the JN.1 Omicron lineage is gaining global prevalence, and early findings suggest it stands among the immune-evading variants, a characteristic attributed to its mutation L455S. Moreover, the detrimental consequences of the novel emergence of SARS-CoV-2 lineages bear a particularly critical impact on immunocompromised individuals and older adults. Immunocompromised individuals face challenges such as suboptimal responses to COVID-19 vaccines, rendering them more susceptible to severe disease. Similarly, older adults have an increased risk of severe disease and the presence of comorbid conditions, find themselves at a heightened vulnerability to develop COVID-19 disease. Thus, recognizing these intricate factors is crucial for effectively tailoring public health strategies to protect these vulnerable populations. In this context, this review aims to describe, analyze, and discuss the current progress of the next-generation treatments encompassing immunotherapeutic approaches and advanced therapies emerging as complements that will offer solutions to counter the disadvantages of the existing options. Preliminary outcomes show that these strategies target the virus and address the immunomodulatory responses associated with COVID-19. Furthermore, the capacity to promote tissue repair has been demonstrated, which can be particularly noteworthy for immunocompromised individuals who stand as vulnerable actors in the global landscape of coronavirus infections. The emerging next-generation treatments possess broader potential, offering protection against a wide range of variants and enhancing the ability to counter the impact of the constant evolution of the virus. Furthermore, advanced therapies are projected as potential treatment alternatives for managing Chronic Post-COVID-19 syndromeand addressing its associated long-term complications.

tANCHOR-cell-based assay for monitoring of SARS-CoV-2 neutralizing antibodies rapidly adaptive to various receptor-binding domains

Conventional neutralizing enzyme-linked immunosorbent assay (ELISA) systems for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mimic the protein-protein interaction between angiotensin-converting enzyme 2 (ACE2) and the receptor-binding domain (RBD). However, an easy and rapidly adaptative ELISA-based system for testing neutralizing antibodies against upcoming SARS-CoV-2 variants is urgently needed. In this study, we closed this gap by developing a tANCHOR-cell-based RBD neutralization assay that avoids time-consuming protein expression and purification followed by coating on ELISA plates. This cell-based assay can be rapidly adopted to monitor neutralizing antibodies (NAbs) against upcoming SARS-CoV-2 variants. We show that the results obtained with the tANCHOR-cell-based assay system strongly correlate with commercially available surrogate assays for testing NAbs. Moreover, this technique can directly measure binding between cell-surface-exposed RBDs and soluble ACE2. With this technique, the degree of antibody escape elicited by emerging SARS-CoV-2 variants in current vaccination regimens can be determined rapidly and reliably.

Results from the SARS-CoV-2 wastewater-based surveillance system in Denmark, July 2021 to June 2022

The microbiological analysis of wastewater samples is increasingly used for the surveillance of SARS-CoV-2 globally. We described the setup process of the national SARS-CoV-2 wastewater-based surveillance system in Denmark, presented its main results during the first year of activities, from July 2021 to June 2022, and discussed their operational significance. The Danish SARS-CoV-2 wastewater-based surveillance system was designed to cover 85 % of the population in Denmark and it entailed taking three weekly samples from 230 sites. Samples were RT-qPCR tested for SARS-CoV-2 RNA, targeting the genetic markers N1, N2 and RdRp, and for two faecal indicators, Pepper Mild Mottle Virus and crAssphage. We calculated the weekly SARS-CoV-2 RNA concentration in the wastewater from each sampling site and monitored it in view of the results from individual testing, at the national and regional levels. We attempted to use wastewater results to identify potential local outbreaks, and we sequenced positive wastewater samples using Nanopore sequencing to monitor the circulation of viral variants in Denmark. The system reached its full implementation by October 2021 and covered up to 86.4 % of the Danish population. The system allowed for monitoring of the national and regional trends of SARS-CoV-2 infections in Denmark. However, the system contribution to the identification of potential local outbreaks was limited by the extensive information available from clinical testing. The sequencing of wastewater samples identified relevant variants of concern, in line with results from sequencing of human samples. Amidst the COVID-19 pandemic, Denmark implemented a nationwide SARS-CoV-2 wastewater-based surveillance system that integrated routine surveillance from individual testing. Today, while testing for COVID-19 at the community level has been discontinued, the system is on the frontline to monitor the occurrence and spread of SARS-CoV-2 in Denmark.

Unravelling the link between SARS-CoV-2 mutation frequencies, patient comorbidities, and structural dynamics

Genomic surveillance is crucial for tracking emergence and spread of novel variants of pathogens, such as SARS-CoV-2, to inform public health interventions and to enforce control measures. However, in some settings especially in low- and middle- income counties, where sequencing platforms are limited, only certain patients get to be selected for sequencing surveillance. Here, we show that patients with multiple comorbidities potentially harbour SARS-CoV-2 with higher mutation rates and thus deserve more attention for genomic surveillance. The relationship between the patient comorbidities, and type of amino acid mutations was assessed. Correlation analysis showed that there was a significant tendency for mutations to occur within the ORF1a region for patients with higher number of comorbidities. Frequency analysis of the amino acid substitution within ORF1a showed that nsp3 P822L of the PLpro protease was one of the highest occurring mutations. Using molecular dynamics, we simulated that the P822L mutation in PLpro represents a system with lower Root Mean Square Deviation (RMSD) fluctuations, and consistent Radius of gyration (Rg), Solvent Accessible Surface Area (SASA) values-indicate a much stabler protein than the wildtype. The outcome of this study will help determine the relationship between the clinical status of a patient and the mutations of the infecting SARS-CoV-2 virus.

SARS-CoV-2 evolution during prolonged infection in immunocompromised patients

Prolonged infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in immunocompromised patients provides an opportunity for viral evolution, potentially leading to the generation of new pathogenic variants. To investigate the pathways of viral evolution, we carried out a study on five patients experiencing prolonged SARS-CoV-2 infection (quantitative polymerase chain reaction-positive for 79-203 days) who were immunocompromised due to treatment for lymphoma or solid organ transplantation. For each timepoint analyzed, we generated at least two independent viral genome sequences to assess the heterogeneity and control for sequencing error. Four of the five patients likely had prolonged infection; the fifth apparently experienced a reinfection. The rates of accumulation of substitutions in the viral genome per day were higher in hospitalized patients with prolonged infection than those estimated for the community background. The spike coding region accumulated a significantly greater number of unique mutations than other viral coding regions, and the mutation density was higher. Two patients were treated with monoclonal antibodies (bebtelovimab and sotrovimab); by the next sampled timepoint, each virus population showed substitutions associated with monoclonal antibody resistance as the dominant forms (spike K444N and spike E340D). All patients received remdesivir, but remdesivir-resistant substitutions were not detected. These data thus help elucidate the trends of emergence, evolution, and selection of mutational variants within long-term infected immunocompromised individuals.

IMPORTANCE

SARS-CoV-2 is responsible for a global pandemic, driven in part by the emergence of new viral variants. Where do these new variants come from? One model is that long-term viral persistence in infected individuals allows for viral evolution in response to host pressures, resulting in viruses more likely to replicate efficiently in humans. In this study, we characterize replication in several hospitalized and long-term infected individuals, documenting efficient pathways of viral evolution.

Viral genome sequencing to decipher in-hospital SARS-CoV-2 transmission events

The SARS-CoV-2 pandemic has highlighted the need to better define in-hospital transmissions, a need that extends to all other common infectious diseases encountered in clinical settings. To evaluate how whole viral genome sequencing can contribute to deciphering nosocomial SARS-CoV-2 transmission 926 SARS-CoV-2 viral genomes from 622 staff members and patients were collected between February 2020 and January 2021 at a university hospital in Munich, Germany, and analysed along with the place of work, duration of hospital stay, and ward transfers. Bioinformatically defined transmission clusters inferred from viral genome sequencing were compared to those inferred from interview-based contact tracing. An additional dataset collected at the same time at another university hospital in the same city was used to account for multiple independent introductions. Clustering analysis of 619 viral genomes generated 19 clusters ranging from 3 to 31 individuals. Sequencing-based transmission clusters showed little overlap with those based on contact tracing data. The viral genomes were significantly more closely related to each other than comparable genomes collected simultaneously at other hospitals in the same city (n = 829), suggesting nosocomial transmission. Longitudinal sampling from individual patients suggested possible cross-infection events during the hospital stay in 19.2% of individuals (14 of 73 individuals). Clustering analysis of SARS-CoV-2 whole genome sequences can reveal cryptic transmission events missed by classical, interview-based contact tracing, helping to decipher in-hospital transmissions. These results, in line with other studies, advocate for viral genome sequencing as a pathogen transmission surveillance tool in hospitals.

VIPERA: Viral Intra-Patient Evolution Reporting and Analysis

Viral mutations within patients nurture the adaptive potential of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during chronic infections, which are a potential source of variants of concern. However, there is no integrated framework for the evolutionary analysis of intra-patient SARS-CoV-2 serial samples. Herein, we describe Viral Intra-Patient Evolution Reporting and Analysis (VIPERA), a new software that integrates the evaluation of the intra-patient ancestry of SARS-CoV-2 sequences with the analysis of evolutionary trajectories of serial sequences from the same viral infection. We have validated it using positive and negative control datasets and have successfully applied it to a new case, which revealed population dynamics and evidence of adaptive evolution. VIPERA is available under a free software license at https://github.com/PathoGenOmics-Lab/VIPERA.

Why is the Omicron main protease of SARS-CoV-2 less stable than its wild-type counterpart? A crystallographic, biophysical, and theoretical study of the free enzyme and its complex with inhibitor 13b-K

During the continuing evolution of SARS-CoV-2, the Omicron variant of concern emerged in the second half of 2021 and has been dominant since November that year. Along with its sublineages, it has maintained a prominent role ever since. The Nsp5 main protease (Mpro) of the Omicron virus is characterized by a single dominant mutation, P132H. Here we determined the X-ray crystal structures of the P132H mutant (or O-Mpro) as free enzyme and in complex with the Mpro inhibitor, the alpha-ketoamide 13b-K, and we conducted enzymology, biophysical as well as theoretical studies to characterize the O-Mpro. We found that O-Mpro has a similar overall structure and binding with 13b-K; however, it displays lower enzymatic activity and lower thermal stability compared to the WT-Mpro (with "WT" referring to the original Wuhan-1 strain). Intriguingly, the imidazole ring of His132 and the carboxylate plane of Glu240 are in a stacked configuration in the X-ray structures determined here. The empirical folding free energy calculations suggest that the O-Mpro dimer is destabilized relative to the WT-Mpro due to the less favorable van der Waals interactions and backbone conformation in the individual protomers. The all-atom continuous constant pH molecular dynamics (MD) simulations reveal that His132 and Glu240 display coupled titration. At pH 7, His132 is predominantly neutral and in a stacked configuration with respect to Glu240 which is charged. In order to examine whether the Omicron mutation eases the emergence of further Mpro mutations, we also determined crystal structures of the relatively frequent P132H+T169S double mutant but found little evidence for a correlation between the two sites.

Disappearance of Imported Cases of Omicron Lineage BA.2.40 in West Kalimantan, Indonesia

Background

The World Health Organization has declared Omicron as the fifth variant of concern with more than 50 mutations, particularly in the spike protein. Given increased viral infectivity due to mutations, worldwide genomic surveillance and detection of severe acute respiratory syndrome 2 (SARS-CoV-2) is essential. The present study aimed to track Omicron lineage BA.2.40 in West Kalimantan, Indonesia.

Methods

In May-August 2022, nasopharyngeal swab samples (n=3,642) were collected from international travelers to West Kalimantan (active surveillance), and patients hospitalized due to SARS-CoV-2 infection (baseline surveillance). The samples were tested for Omicron lineages based on ORF1ab, N, and HV69-70del genes, followed by whole-genome sequencing. The sequences were then identified using two genomic databases, aligned against the reference genome (Wuhan/Hu-1/2019), and then compared with BA.2.40 lineage detected across the world. Phylogenetic analysis between the samples and other SARS-CoV-2 isolates was performed using molecular evolutionary genetics analysis software.

Results

Based on the genomic databases, 10 isolates were identified as BA.2.40. All samples tested positive for the ORF1ab and N genes, but negative for the HV69-70del gene, which is a marker to detect the Omicron variant. Phylogenetic analysis showed the isolates were closely related to an isolate from Malaysia, an area dominated by BA.2.40.

Conclusion

Omicron lineage BA.2.40 has no HV69-70 deletion in the spike protein, a marker used to screen for the Omicron variant. BA.2.40 showed a high similarity to an isolate from Malaysia and was detected only during certain periods, indicating the effect of internationally imported cases.

Resurgence of human respiratory syncytial virus during COVID-19 pandemic in Southern Brazil

Respiratory Syncytial Virus (RSV) is an important cause of respiratory infection in humans. Severe cases are common in children ≤2 years old, immunocompromised individuals, and the elderly. In 2020, RSV infection reduced in Rio Grande do Sul (RS), southern Brazil; however, in 2021 resurgence of RSV was observed. This study analyzed epidemiological and genetic features of RSV infection cases reported in 2021 in RS. Nasopharyngeal samples collected from individuals with respiratory infection negative for SARS-CoV-2, Influenza A and B viruses were assessed for the presence of RSV by real time RT-qPCR. RSV-A and RSV-B genomic sequencing and phylogenetic reconstructions were performed for genotyping and clade characterization. Among 21,035 respiratory samples analyzed, 2,947 were positive for RSV, 947 of which were hospitalized patients. Positive cases were detected year-round, with the highest number in June-July (winter). Children <1 year comprised 56.28% (n = 533) of the hospitalized patients infected with RSV, whereas 14.46% (n = 137) were individuals >60 years. Of a total of 361 deaths, 14.68% (n = 53) were RSV positive, mostly patients >60 years old (73.58%, n = 39). Chronic kidney disease, cardiopathy, Down syndrome and neurological diseases were associated with RSV infection. RSV-A was identified in 58.5% (n = 117/200) of the patients, and RSV-B in 41.5% (n = 83/200). Of 95 RSV genomes recovered from SARI cases, 66 were RSV-A GA.2.3.5 genotype, while 29 were RSV-B GB.5.0.5a genotype. This study provides epidemiological and molecular data on RSV cases in RS during the COVID-19 pandemic and highlights that investigation of different respiratory viruses is essential for decision-making and disease prevention and control measures.

Defining Incidental Versus Non-incidental COVID-19 Hospitalizations

Background Rates of COVID-19 hospitalization are an important measure of the health system burden of severe COVID-19 disease and have been closely followed throughout the pandemic. The highly transmittable, but often less severe, Omicron COVID-19 variant has led to an increase in hospitalizations with incidental COVID-19 diagnoses where COVID-19 is not the primary reason for admission. There is a strong public health need for a measure that is implementable at low cost with standard electronic health record (EHR) datasets that can separate these incidental hospitalizations from non-incidental hospitalizations where COVID-19 is the primary cause or an important contributor. Two crude metrics are in common use. The first uses in-hospital administration of dexamethasone as a marker of non-incidental COVID-19 hospitalizations. The second, used by the United States (US) CDC, relies on a limited set of COVID-19-related diagnoses (i.e., respiratory failure, pneumonia). Both measures likely undercount non-incidental COVID-19 hospitalizations. We therefore developed an improved EHR-based measure that is better able to capture the full range of COVID-19 hospitalizations. Methods We conducted a retrospective study of ED visit data from a national emergency medicine group from April 2020 to August 2023. We assessed the CDC approach, the dexamethasone-based measure, and alternative approaches that rely on co-diagnoses likely to be related to COVID-19, to determine the proportion of non-incidental COVID-19 hospitalizations. Results Of the 153,325 patients diagnosed with COVID-19 at 112 general EDs in 17 US states, and admitted or transferred, our preferred measure classified 108,243 (70.6%) as non-incidental, compared to 71,066 (46.3%) using the dexamethasone measure and 77,399 (50.5%) using the CDC measure. Conclusions Identifying non-incidental COVID-19 hospitalizations using ED administration of dexamethasone or the CDC measure provides substantially lower estimates than our preferred measure.

Exploration of low-frequency allelic variants of SARS-CoV-2 genomes reveals coinfections in Mexico occurred during periods of VOCs turnover

A total of 14 973 alleles in 29 661 sequenced samples collected between March 2021 and January 2023 by the Mexican Consortium for Genomic Surveillance (CoViGen-Mex) and collaborators were used to construct a thorough map of mutations of the Mexican SARS-CoV-2 genomic landscape containing Intra-Patient Minor Allelic Variants (IPMAVs), which are low-frequency alleles not ordinarily present in a genomic consensus sequence. This additional information proved critical in identifying putative coinfecting variants included alongside the most common variants, B.1.1.222, B.1.1.519, and variants of concern (VOCs) Alpha, Gamma, Delta, and Omicron. A total of 379 coinfection events were recorded in the dataset (a rate of 1.28 %), resulting in the first such catalogue in Mexico. The most common putative coinfections occurred during the spread of Delta or after the introduction of Omicron BA.2 and its descendants. Coinfections occurred constantly during periods of variant turnover when more than one variant shared the same niche and high infection rate was observed, which was dependent on the local variants and time. Coinfections might occur at a higher frequency than customarily reported, but they are often ignored as only the consensus sequence is reported for lineage identification.

Omicron and Delta variant prevalence detection and identification during the fourth COVID-19 wave in Mexico using wastewater-based epidemiology

Objectives

To identify the SARS-CoV-2 variants Delta and Omicron during the fourth wave of the COVID-19 pandemic in Mexico using samples taken from 19 locations in 18 out of the 32 states.

Methods

The genetic material concentration was done with PEG/NaCl precipitation, SARS-CoV-2 presence was confirmed by reverse transcriptase-quantitative polymerase chain reaction assay, the variant detection was carried out using a commercial mutation detection panel kit, and variant/mutation confirmation was done by amplicon sequencing of receptor-binding domain target region. The study used 41 samples.

Results

The Delta variant was confirmed in two samples during August 2021 (Querétaro and CDMX) and in three samples during November 2021 (Aguascalientes, Ciudad Juárez campuses, and Nuevo Leon). In December 2021, another sample with the Delta variant was confirmed in Nuevo Leon. Between January to March 2022 only the presence of Omicron was confirmed, (variant BA.1). Additionally, in this period six samples were identified with the status "Variant Not Determined".

Conclusion

To our knowledge, this study is one of the first to identify Omicron and Delta variants with polymerase chain reaction in Mexico and Latin America and its distribution across the country with 56% Mexican states making it a viable alternative for variant detection without conducting a large quantity of sequencing of clinical tests.

Using early detection data to estimate the date of emergence of an epidemic outbreak

While the first infection of an emerging disease is often unknown, information on early cases can be used to date it. In the context of the COVID-19 pandemic, previous studies have estimated dates of emergence (e.g., first human SARS-CoV-2 infection, emergence of the Alpha SARS-CoV-2 variant) using mainly genomic data. Another dating attempt used a stochastic population dynamics approach and the date of the first reported case. Here, we extend this approach to use a larger set of early reported cases to estimate the delay from first infection to the Nth case. We first validate our framework by running our model on simulated data. We then apply our model using data on Alpha variant infections in the UK, dating the first Alpha infection at (median) August 21, 2020 (95% interpercentile range across retained simulations (IPR): July 23-September 5, 2020). Next, we apply our model to data on COVID-19 cases with symptom onset before mid-January 2020. We date the first SARS-CoV-2 infection in Wuhan at (median) November 28, 2019 (95% IPR: November 2-December 9, 2019). Our results fall within ranges previously estimated by studies relying on genomic data. Our population dynamics-based modelling framework is generic and flexible, and thus can be applied to estimate the starting time of outbreaks in contexts other than COVID-19.

Multiple Lines of Evidence Support 199 SARS-CoV-2 Positively Selected Amino Acid Sites

SARS-CoV-2 amino acid variants that contribute to an increased transmissibility or to host immune system escape are likely to increase in frequency due to positive selection and may be identified using different methods, such as codeML, FEL, FUBAR, and MEME. Nevertheless, when using different methods, the results do not always agree. The sampling scheme used in different studies may partially explain the differences that are found, but there is also the possibility that some of the identified positively selected amino acid sites are false positives. This is especially important in the context of very large-scale projects where hundreds of analyses have been performed for the same protein-coding gene. To account for these issues, in this work, we have identified positively selected amino acid sites in SARS-CoV-2 and 15 other coronavirus species, using both codeML and FUBAR, and compared the location of such sites in the different species. Moreover, we also compared our results to those that are available in the COV2Var database and the frequency of the 10 most frequent variants and predicted protein location to identify those sites that are supported by multiple lines of evidence. Amino acid changes observed at these sites should always be of concern. The information reported for SARS-CoV-2 can also be used to identify variants of concern in other coronaviruses.

SARS-CoV-2 ORF7a Mutation Found in BF.5 and BF.7 Sublineages Impacts Its Functions

A feature of the SARS-CoV-2 Omicron subvariants BF.5 and BF.7 that recently circulated mainly in China and Japan was the high prevalence of the ORF7a: H47Y mutation, in which the 47th residue of ORF7a has been mutated from a histidine (H) to a tyrosine (Y). Here, we evaluated the effect of this mutation on the three main functions ascribed to the SARS-CoV-2 ORF7a protein. Our findings show that H47Y mutation impairs the ability of SARS-CoV-2 ORF7a to antagonize the type I interferon (IFN-I) response and to downregulate major histocompatibility complex I (MHC-I) cell surface levels, but had no effect in its anti-SERINC5 function. Overall, our results suggest that the H47Y mutation of ORF7a affects important functions of this protein, resulting in changes in virus pathogenesis.

COVID-19 reinfections in Mexico City: implications for public health

Background

Since its appearance, COVID-19 has immensely impacted our society. Public health measures, from the initial lockdowns to vaccination campaigns, have mitigated the crisis. However, SARS-CoV-2's persistence and evolving variants continue to pose global threats, increasing the risk of reinfections. Despite vaccination progress, understanding reinfections remains crucial for informed public health responses.

Methods

We collected available data on clinical and genomic information for SARS-CoV-2 samples from patients treated in Mexico City from 2020 epidemiological week 10 to 2023 epidemiological week 06 encompassing the whole public health emergency's period. To identify clinical data we utilized the SISVER (Respiratory Disease Epidemiological Surveillance System) database for SARS-CoV-2 patients who received medical attention in Mexico City. For genomic surveillance we analyzed genomic data previously uploaded to GISAID generated by Mexican institutions. We used these data sources to generate descriptors of case number, hospitalization, death and reinfection rates, and viral variant prevalence throughout the pandemic period.

Findings

The fraction of reinfected individuals in the COVID-19 infected population steadily increased as the pandemic progressed in Mexico City. Most reinfections occurred during the fifth wave (40%). This wave was characterized by the coexistence of multiple variants exceeding 80% prevalence; whereas all other waves showed a unique characteristic dominant variant (prevalence >95%). Shifts in symptom patient care type and severity were observed, 2.53% transitioned from hospitalized to ambulatory care type during reinfection and 0.597% showed the opposite behavior; also 7.23% showed a reduction in severity of symptoms and 6.05% displayed an increase in severity. Unvaccinated individuals accounted for the highest percentage of reinfections (41.6%), followed by vaccinated individuals (31.9%). Most reinfections occurred after the fourth wave, dominated by the Omicron variant; and after the vaccination campaign was already underway.

Interpretation

Our analysis suggests reduced infection severity in reinfections, evident through shifts in symptom severity and care patterns. Unvaccinated individuals accounted for most reinfections. While our study centers on Mexico City, its findings may hold implications for broader regions, contributing insights into reinfection dynamics.

Virological characteristics of the SARS-CoV-2 BA.2.86 variant

In late 2023, several SARS-CoV-2 XBB descendants, notably EG.5.1, were predominant worldwide. However, a distinct SARS-CoV-2 lineage, the BA.2.86 variant, also emerged. BA.2.86 is phylogenetically distinct from other Omicron sublineages, accumulating over 30 amino acid mutations in its spike protein. Here, we examined the virological characteristics of the BA.2.86 variant. Our epidemic dynamics modeling suggested that the relative reproduction number of BA.2.86 is significantly higher than that of EG.5.1. Additionally, four clinically available antivirals were effective against BA.2.86. Although the fusogenicity of BA.2.86 spike is similar to that of the parental BA.2 spike, the intrinsic pathogenicity of BA.2.86 in hamsters was significantly lower than that of BA.2. Since the growth kinetics of BA.2.86 are significantly lower than those of BA.2 both in vitro and in vivo, the attenuated pathogenicity of BA.2.86 is likely due to its decreased replication capacity. These findings uncover the features of BA.2.86, providing insights for control and treatment.

Nationwide quality assurance of high-throughput diagnostic molecular testing during the SARS-CoV-2 pandemic: role of the Belgian National Reference Centre

Since the onset of the coronavirus disease (COVID-19) pandemic in Belgium, UZ/KU Leuven has played a crucial role as the National Reference Centre (NRC) for respiratory pathogens, to be the first Belgian laboratory to develop and implement laboratory developed diagnostic assays for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and later to assess the quality of commercial kits. To meet the growing demand for decentralised testing, both clinical laboratories and government-supported high-throughput platforms were gradually deployed across Belgium. Consequently, the role of the NRC transitioned from a specialised testing laboratory to strengthening capacity and coordinating quality assurance. Here, we outline the measures taken by the NRC, the national public health institute Sciensano and the executing clinical laboratories to ensure effective quality management of molecular testing throughout the initial two years of the pandemic (March 2020 to March 2022).

Stable Isotope Analysis Reveals Common Teal (Anas crecca) Molting Sites in Western Siberia: Implications for Avian Influenza Virus Spread

The wetlands of southwestern Siberia (SWS) are a crossroads of bird migration routes, bringing avian influenza (AIV) strains that were previously isolated in different regions of the continent to Siberia. It is known that Anseriformes that breed in SWS migrate for the winter to central Hindustan or further west, while their migration routes to southeast Asia (SEA) remain unconfirmed. Here, we mapped the molting sites of the migrating Common Teals (Anas crecca) via analyzing stable hydrogen isotope content in feathers of hunters' prey and supplemented the analysis with the genetic structure of viruses isolated from teals in the same region. Post-breeding molt of autumn teals most likely occurred within the study region, whereas probable pre-breeding molting grounds of spring teals were in the south of Hindustan. This link was supported by viral phylogenetic analysis, which showed a close relationship between SWS isolates and viruses from south and southeast Asia. Most viral segments have the highest genetic similarity and the closest phylogenetic relationships with viruses from teal wintering areas in southeast Asian countries, including India and Korea. We assume that the winter molt of SWS breeding teals on the Hindustan coast suggests contacts with the local avifauna, including species migrating along the coast to SEA. Perhaps this is one of the vectors of AIV transmission within Eurasia.

Identification of SARS-CoV-2 variants in indoor dust

Environmental surveillance of pathogens underlying infectious disease is critical to ensure public health. Recent efforts to track SARS-CoV-2 have utilized wastewater sampling to infer community trends in viral abundance and variant composition. Indoor dust has also been used for building-level inferences, though to date no sequencing data providing variant-scale resolution have been reported from dust samples, and strategies to monitor circulating variants in dust are needed to help inform public health decisions. In this study, we demonstrate that SARS-CoV-2 lineages can be detected and sequenced from indoor bulk dust samples. We collected 93 vacuum bags from April 2021 to March 2022 from buildings on The Ohio State University's (OSU) Columbus campus, and the dust was used to develop and apply an amplicon-based whole-genome sequencing protocol to identify the variants present and estimate their relative abundances. Three variants of concern were detected in the dust: Alpha, Delta, and Omicron. Alpha was found in our earliest sample in April 2021 with an estimated frequency of 100%. Delta was the primary variant present from October of 2021 to January 2022, with an average estimated frequency of 91% (±1.3%). Omicron became the primary variant in January 2022 and was the dominant strain in circulation through March with an estimated frequency of 87% (±3.2%). The detection of these variants on OSU's campus correlates with the circulation of these variants in the surrounding population (Delta p<0.0001 and Omicron p = 0.02). Overall, these results support the hypothesis that dust can be used to track COVID-19 variants in buildings.

Virological characteristics of the SARS-CoV-2 Omicron XBB.1.5 variant

Circulation of SARS-CoV-2 Omicron XBB has resulted in the emergence of XBB.1.5, a new Variant of Interest. Our phylogenetic analysis suggests that XBB.1.5 evolved from XBB.1 by acquiring the S486P spike (S) mutation, subsequent to the acquisition of a nonsense mutation in ORF8. Neutralization assays showed similar abilities of immune escape between XBB.1.5 and XBB.1. We determine the structural basis for the interaction between human ACE2 and the S protein of XBB.1.5, showing similar overall structures between the S proteins of XBB.1 and XBB.1.5. We provide the intrinsic pathogenicity of XBB.1 and XBB.1.5 in hamsters. Importantly, we find that the ORF8 nonsense mutation of XBB.1.5 resulted in impairment of MHC suppression. In vivo experiments using recombinant viruses reveal that the XBB.1.5 mutations are involved with reduced virulence of XBB.1.5. Together, our study identifies the two viral functions defined the difference between XBB.1 and XBB.1.5.

Helix-based screening with structure prediction using artificial intelligence has potential for the rapid development of peptide inhibitors targeting class I viral fusion

The rapid development of drugs against emerging and re-emerging viruses is required to prevent future pandemics. However, inhibitors usually take a long time to optimize. Here, to improve the optimization step, we used two heptad repeats (HR) in the spike protein (S protein) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a model and established a screening system for peptide-based inhibitors containing an α-helix region (SPICA). SPICA can be used to identify critical amino acid regions and evaluate the inhibitory effects of peptides as decoys. We further employed an artificial intelligence structure-prediction system (AlphaFold2) for the rapid analysis of structure-activity relationships. Here, we identified that critical amino acid regions, DVDLGD (amino acids 1163-1168 in the S protein), IQKEIDRLNE (1179-1188), and NLNESLIDL (1192-1200), played a pivotal role in SARS-CoV-2 fusion. Peptides containing these critical amino acid regions efficiently blocked viral replication. We also demonstrated that AlphaFold2 could successfully predict structures similar to the reported crystal and cryo-electron microscopy structures of the post-fusion form of the SARS-CoV-2 S protein. Notably, the predicted structures of the HR1 region and the peptide-based fusion inhibitors corresponded well with the antiviral effects of each fusion inhibitor. Thus, the combination of SPICA and AlphaFold2 is a powerful tool to design viral fusion inhibitors using only the amino-acid sequence of the fusion protein.

Analysis of SARS-CoV-2 genome evolutionary patterns

The spread of SARS-CoV-2 virus accompanied by public availability of abundant sequence data provides a window for the determination of viral evolutionary patterns. In this study, SARS-CoV-2 genome sequences were collected from seven countries in the period January 2020-December 2022. The sequences were classified into three phases, namely, pre-vaccination, post-vaccination, and recent period. Comparison was performed between these phases based on parameters like mutation rates, selection pressure (dN/dS ratio), and transition to transversion ratios (Ti/Tv). Similar comparisons were performed among SARS-CoV-2 variants. Statistical significance was tested using Graphpad unpaired t-test. The analysis showed an increase in the percent genomic mutation rates post-vaccination and in recent periods across all countries from the pre-vaccination sequences. Mutation rates were highest in NSP3, S, N, and NSP12b before and increased further after vaccination. NSP4 showed the largest change in mutation rates after vaccination. The dN/dS ratios showed purifying selection that shifted toward neutral selection after vaccination. N, ORF8, ORF3a, and ORF10 were under highest positive selection before vaccination. Shift toward neutral selection was driven by E, NSP3, and ORF7a in the after vaccination set. In recent sequences, the largest dN/dS change was observed in E, NSP1, and NSP13. The Ti/Tv ratios decreased with time. C→U and G→U were the most frequent transitions and transversions. However, U→G was the most frequent transversion in recent period. The Omicron variant had the highest genomic mutation rates, while Delta showed the highest dN/dS ratio. Protein-wise dN/dS ratio was also seen to vary across the different variants.IMPORTANCETo the best of our knowledge, there exists no other large-scale study of the genomic and protein-wise mutation patterns during the time course of evolution in different countries. Analyzing the SARS-CoV-2 evolutionary patterns in view of the varying spatial, temporal, and biological signals is important for diagnostics, therapeutics, and pharmacovigilance of SARS-CoV-2.

Synchrony of Bird Migration with Global Dispersal of Avian Influenza Reveals Exposed Bird Orders

Highly pathogenic avian influenza virus (HPAIV) A H5, particularly clade 2.3.4.4, has caused worldwide outbreaks in domestic poultry, occasional spillover to humans, and increasing deaths of diverse species of wild birds since 2014. Wild bird migration is currently acknowledged as an important ecological process contributing to the global dispersal of HPAIV H5. However, this mechanism has not been quantified using bird movement data from different species, and the timing and location of exposure of different species is unclear. We sought to explore these questions through phylodynamic analyses based on empirical data of bird movement tracking and virus genome sequences of clade 2.3.4.4 and 2.3.2.1. First, we demonstrate that seasonal bird migration can explain salient features of the global dispersal of clade 2.3.4.4. Second, we detect synchrony between the seasonality of bird annual cycle phases and virus lineage movements. We reveal the differing exposed bird orders at geographical origins and destinations of HPAIV H5 clade 2.3.4.4 lineage movements, including relatively under-discussed orders. Our study provides a phylodynamic framework that links the bird movement ecology and genomic epidemiology of avian influenza; it highlights the importance of integrating bird behavior and life history in avian influenza studies.

Comparative Review of the State of the Art in Research on the Porcine Epidemic Diarrhea Virus and SARS-CoV-2, Scope of Knowledge between Coronaviruses

This review presents comparative information corresponding to the progress in knowledge of some aspects of infection by the porcine epidemic diarrhea virus (PEDV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) coronaviruses. PEDV is an alphacoronavirus of great economic importance due to the million-dollar losses it generates in the pig industry. PEDV has many similarities to the SARS-CoV-2 betacoronavirus that causes COVID-19 disease. This review presents possible scenarios for SARS-CoV-2 based on the collected literature on PEDV and the tools or strategies currently developed for SARS-CoV-2 that would be useful in PEDV research. The speed of the study of SARS-CoV-2 and the generation of strategies to control the pandemic was possible due to the knowledge derived from infections caused by other human coronaviruses such as severe acute respiratory syndrome (SARS) and middle east respiratory syndrome (MERS). Therefore, from the information obtained from several coronaviruses, the current and future behavior of SARS-CoV-2 could be inferred and, with the large amount of information on the virus that causes COVID-19, the study of PEDV could be improved and probably that of new emerging and re-emerging coronaviruses.

Key Challenges for Respiratory Virus Surveillance while Transitioning out of Acute Phase of COVID-19 Pandemic

To support the ongoing management of viral respiratory diseases while transitioning out of the acute phase of the COVID-19 pandemic, many countries are moving toward an integrated model of surveillance for SARS-CoV-2, influenza virus, and other respiratory pathogens. Although many surveillance approaches catalyzed by the COVID-19 pandemic provide novel epidemiologic insight, continuing them as implemented during the pandemic is unlikely to be feasible for nonemergency surveillance, and many have already been scaled back. Furthermore, given anticipated cocirculation of SARS-CoV-2 and influenza virus, surveillance activities in place before the pandemic require review and adjustment to ensure their ongoing value for public health. In this report, we highlight key challenges for the development of integrated models of surveillance. We discuss the relative strengths and limitations of different surveillance practices and studies as well as their contribution to epidemiologic assessment, forecasting, and public health decision-making.