The next phase of SARS-CoV-2 surveillance: real-time molecular epidemiology

User experience with HIV molecular epidemiology in research, surveillance, and cluster detection and response: a needs assessment

OBJECTIVE

HIV molecular epidemiology (HIV ME) is a tool that aims to improve HIV research, surveillance, and cluster detection and response. HIV ME is a core pillar of the U.S. initiative to End the HIV Epidemic but faces some challenges and criticisms from stakeholders. We sought to assess user experience to identify the current needs for HIV ME.

METHODS

Users of HIV ME, including researchers and public health practitioners, were engaged via a structured survey. Needs were assessed via open-ended questions about HIV ME. Data were analyzed using reflexive thematic analysis; the concordance of results was assessed semi-quantitatively.

RESULTS

Of 90 possible HIV-ME end-users, 57 completed the survey (response rate = 63%), which included users engaged in research (n = 29) and public health (n = 28). Respondents identified current imperatives, challenges, and strategies to improve HIV ME. Imperatives included characterization of the virus, identification of HIV hotspots, and tailoring of HIV interventions. Challenges encompassed technological issues, ethical concerns, and implementation difficulties. Strategies to improve HIV ME involved improving data access and analysis, enhancing implementation guidance and resources, and fostering community engagement and support. Researchers and public health practitioners prioritized different imperatives, but similarly emphasized the ethical concerns with HIV ME.

CONCLUSION

The imperatives identified by users underscore the necessity of HIV ME, while the challenges highlight the hurdles to be overcome, including ethical concerns which emerged as a shared emphasis across user groups. The strategies outlined offer a roadmap for overcoming these challenges. These insights, drawn from user experience, present a valuable opportunity to inform the development of guidelines for the ethical application of HIV ME in research, surveillance, and cluster detection and response.

Differential Gene Expression and Transcriptomics Reveal High M-Gene Expression in JN.1 and KP.1/2 Omicron Sub-Variants of SARS-CoV-2: Implications for Developing More Sensitive Diagnostic Tests

SARS-CoV-2, a positive-strand RNA virus, utilizes both genomic replication and subgenomic mRNA transcription. Whole genome sequencing (WGS) from clinical samples can estimate viral gene expression levels. WGS was conducted on 529 SARS-CoV-2 positive clinical samples from Assam and northeastern India to track viral emergence and assess gene expression patterns. The results reveal differential expression across structural, non-structural, and accessory genes, with notable upregulation of the M gene, especially in the Omicron variant, followed by E and ORF6. The mean transcript per million (TPM) expression levels of the M gene were significantly higher in Omicron variants (175 611 ± 46 921), peaking in the KP.1/KP.2 sublineage (220 493 ± 34 917), compared to the Delta variant (129 717 ± 33 773). The relative fold change of M gene expression between Delta and Omicron 2024 subvariants showed a 1.6-fold change. Variant-wise gene expression analysis suggests a correlation between gene expression and viral mutation, impacting replication. As anticipated, the expression levels of genes surge with the increase in the virus mutation. The Chi-square trend for average substitution count versus average TPM of the M gene was highly significant (72.78., p < 0.0001). The M gene's high expression and low mutation rate make it an ideal target for designing a real-time RT-PCR kit assay. These findings highlight the need for continuous surveillance and understanding of viral gene expression dynamics for effective COVID-19 management. Further studies are necessary to elucidate the significance of these observations in viral pathogenesis and transmission dynamics.

A multicenter study on accuracy and reproducibility of nanopore sequencing-based genotyping of bacterial pathogens

Nanopore sequencing has shown the potential to democratize genomic pathogen surveillance due to its ease of use and low entry cost. However, recent genotyping studies showed discrepant results compared to gold-standard short-read sequencing. Furthermore, although essential for widespread application, the reproducibility of nanopore-only genotyping remains largely unresolved. In our multicenter performance study involving five laboratories, four public health-relevant bacterial species were sequenced with the latest R10.4.1 flow cells and V14 chemistry. Core genome MLST analysis of over 500 data sets revealed highly strain-specific typing errors in all species in each laboratory. Investigation of the methylation-related errors revealed consistent DNA motifs at error-prone sites across participants at read level. Depending on the frequency of incorrect target reads, this either leads to correct or incorrect typing, whereby only minimal frequency deviations can randomly determine the final result. PCR preamplification, recent basecalling model updates and an optimized polishing strategy notably diminished the non-reproducible typing. Our study highlights the potential for new errors to appear with each newly sequenced strain and lays the foundation for computational approaches to reduce such typing errors. In conclusion, our multicenter study shows the necessity for a new validation concept for nanopore sequencing-based, standardized bacterial typing, where single nucleotide accuracy is critical.

High-Throughput and Integrated CRISPR/Cas12a-Based Molecular Diagnosis Using a Deep Learning Enabled Microfluidic System

CRISPR/Cas-based molecular diagnosis demonstrates potent potential for sensitive and rapid pathogen detection, notably in SARS-CoV-2 diagnosis and mutation tracking. Yet, a major hurdle hindering widespread practical use is its restricted throughput, limited integration, and complex reagent preparation. Here, a system, microfluidic multiplate-based ultrahigh throughput analysis of SARS-CoV-2 variants of concern using CRISPR/Cas12a and nonextraction RT-LAMP (mutaSCAN), is proposed for rapid detection of SARS-CoV-2 and its variants with limited resource requirements. With the aid of the self-developed reagents and deep-learning enabled prototype device, our mutaSCAN system can detect SARS-CoV-2 in mock swab samples below 30 min as low as 250 copies/mL with the throughput up to 96 per round. Clinical specimens were tested with this system, the accuracy for routine and mutation testing (22 wildtype samples, 26 mutational samples) was 98% and 100%, respectively. No false-positive results were found for negative (n = 24) samples.

Glycan masking of NTD loops with a chimeric RBD of the spike protein as a vaccine design strategy against emerging SARS-CoV-2 Omicron variants

The N-terminal domain (NTD) of the SARS-CoV-2 S protein comprises five exposed protruding loops. Deletions, insertions, and substitutions within these NTD loops play a significant role in viral evolution and contribute to immune evasion. We reported previously that introducing the glycan masking mutation R158N/Y160T in the NTD loop led to increased titers of neutralizing antibodies against the SARS-CoV-2 Wuhan-Hu-01 strain, as well as the Alpha, Beta, and Delta variants. In this study, we conducted further investigations on 10 additional glycan-masking sites in the NTD loops. Our findings indicate that the introduction of glycan masking mutations, specifically N87/G89T, H146N/N148T, N185/K187T, and V213N/D215T significantly enhanced neutralizing antibody titers against the Delta variant. The combination of dual glycan-masking mutations R158N/Y160T+V213N/D215T and R158N/Y160T+G219N results in a shift toward the Omicron BA.1. Furthermore, the introduction of the Omicron receptor binding domain (RBD) alongside these two dual glycan masking mutations of Wuhan-Hu-1 and XBB.1 NTD sequences resulted in a noticeable shift in antigenic distances, aligning with the Omicron BA.4/5, BA.2.75.2, BQ.1.1, and XBB.1 subvariants on the antigenic map. This strategic combination, which involves the dual glycan masking mutations R158N/Y160T+V213N/D215T and R158N/Y160T+G219N in the NTD loops, along with the domain swap incorporating the Omicron RBD, emerges as a promising vaccine design strategy for the continuous development of next-generation SARS-CoV-2 vaccines.

Respiratory virus detection and sequencing from negative SARS-CoV-2 rapid antigen tests

Genomic epidemiology offers important insight into the transmission and evolution of respiratory viruses. We used metagenomic sequencing from negative SARS-CoV-2 antigen tests to identify a wide range of respiratory viruses and generate full genome sequences, offering a streamlined mechanism for broad respiratory virus genomic surveillance.

Early detection of highly transmissible viral variants using phylogenomics

As demonstrated by the SARS-CoV-2 pandemic, the emergence of novel viral strains with increased transmission rates poses a serious threat to global health. Statistical models of genome sequence evolution may provide a critical tool for early detection of these strains. Using a novel stochastic model that links transmission rates to the entire viral genome sequence, we study the utility of phylogenetic methods that use a phylogenetic tree relating viral samples versus count-based methods that use case counts of variants over time exclusively to detect increased transmission rates and identify candidate causative mutations. We find that phylogenies in particular can detect novel transmission-enhancing variants very soon after their origin and may facilitate the development of early detection systems for outbreak surveillance.

Spatiotemporal transmission of SARS-CoV-2 lineages during 2020-2021 in Pernambuco-Brazil

SARS-CoV-2 virus emerged as a new threat to humans and spread around the world, leaving a large death toll. As of January 2023, Brazil is among the countries with the highest number of registered deaths. Nonpharmacological and pharmacological interventions have been heterogeneously implemented in the country, which, associated with large socioeconomic differences between the country regions, has led to distinct virus spread dynamics. Here, we investigate the spatiotemporal dispersion of SARS-CoV-2 lineages in the Pernambuco state (Northeast Brazil) throughout the distinct epidemiological scenarios that unfolded in the first 2 years of the pandemic. We generated a total of 1,389 new SARS-CoV-2 genomes from June 2020 to August 2021. This sampling captured the arrival, communitary transmission, and the circulation of the B1.1, B.1.1.28, and B.1.1.33 lineages; the emergence of the former variant of interest P.2; and the emergence and fast replacement of all previous variants by the more transmissible variant of concern P.1 (Gamma). Based on the incidence and lineage spread pattern, we observed an East-to-West to inner state pattern of transmission, which is in agreement with the transmission of more populous metropolitan areas to medium- and small-size country-side cities in the state. Such transmission patterns may be partially explained by the main routes of traffic across municipalities in the state. Our results highlight that the fine-grained intrastate analysis of lineages and incidence spread can provide actionable insights for planning future nonpharmacological intervention for air-borne transmissible human pathogens.IMPORTANCEDuring the COVID-19 pandemic, Brazil was one of the most affected countries, mainly due its continental-size, socioeconomic differences among regions, and heterogeneous implementation of intervention methods. In order to investigate SARS-CoV-2 dynamics in the state of Pernambuco, we conducted a spatiotemporal dispersion study, covering the period from June 2020 to August 2021, to comprehend the dynamics of viral transmission during the first 2 years of the pandemic. Throughout this study, we were able to track three significant epidemiological waves of transmission caused by B1.1, B.1.1.28, B.1.1.33, P.2, and P.1 lineages. These analyses provided valuable insights into the evolution of the epidemiological landscape, contributing to a deeper understanding of the dynamics of virus transmission during the early years of the pandemic in the state of Pernambuco.

ViralFlow v1.0-a computational workflow for streamlining viral genomic surveillance

ViralFlow v1.0 is a computational workflow developed for viral genomic surveillance. Several key changes turned ViralFlow into a general-purpose reference-based genome assembler for all viruses with an available reference genome. New virus-agnostic modules were implemented to further study nucleotide and amino acid mutations. ViralFlow v1.0 runs on a broad range of computational infrastructures, from laptop computers to high-performance computing (HPC) environments, and generates standard and well-formatted outputs suited for both public health reporting and scientific problem-solving. ViralFlow v1.0 is available at: https://viralflow.github.io/index-en.html.

Dynamic of SARS-CoV-2 variants circulation in Tunisian pediatric population, during successive waves, from March 2020 to September 2022

The emergence of SARS-CoV-2 variants has led to several cases among children. However, limited information is available from North African countries. This study describes the SARS-CoV-2 strains circulating in Tunisian pediatric population during successive waves. A total of 447 complete sequences were obtained from individuals aged from 13 days to 18 years, between March 2020 and September 2022: 369 sequences generated during this study and 78 ones, available in GISAID, previously obtained from Tunisian pediatric patients. These sequences were compared with 354 and 274 ones obtained from Tunisian adults and a global dataset, respectively. The variant circulation dynamics of predominant variants were investigated during the study period using maximum-likelihood phylogenetic analysis. Among the studied population, adolescents were the predominant age group, comprising 55.26% of cases. Twenty-three lineages were identified; seven of which were not previously reported in Tunisia. Phylogenetic analysis showed a close relationship between the sequences from Tunisian adults and children. The connections of sequences from other countries were variable according to variants: close relationships were observed for Alpha, B1.160 and Omicron variants, while independent Tunisian clusters were observed for Delta and B.1.177 lineages. These findings highlight the pivotal role of children in virus transmission and underscore the impact of vaccination on virus spread. Vaccination of children, with booster doses, may be considered for better management of future emergences.

Genetic diversity and evolutionary dynamics of the Omicron variant of SARS-CoV-2 in Morocco

Among the numerous variants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that have been reported worldwide, the emergence of the Omicron variant has drastically changed the landscape of the coronavirus disease (COVID-19) pandemic. Here, we analyzed the genetic diversity of Moroccan SARS-CoV-2 genomes with a focus on Omicron variant after one year of its detection in Morocco in order to understand its genomic dynamics, features and its potential introduction sources. From 937 Omicron genomes, we identified a total of 999 non-unique mutations distributed across 92 Omicron lineages, of which 13 were specific to the country. Our findings suggest multiple introductory sources of the Omicron variant to Morocco. In addition, we found that four Omicron clades are more infectious in comparison to other Omicron clades. Remarkably, a clade of Omicron is particularly more transmissible and has become the dominant variant worldwide. Moreover, our assessment of Receptor-Binding Domain (RBD) mutations showed that the Spike K444T and N460K mutations enabled a clade higher ability of immune vaccine escape. In conclusion, our analysis highlights the unique genetic diversity of the Omicron variant in Moroccan SARS-CoV-2 genomes, with multiple introductory sources and the emergence of highly transmissible clades. The distinctiveness of the Moroccan strains compared to global ones underscores the importance of ongoing surveillance and understanding of local genomic dynamics for effective response strategies in the evolving COVID-19 pandemic.

DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction

In the midst of an outbreak or sustained epidemic, reliable prediction of transmission risks and patterns of spread is critical to inform public health programs. Projections of transmission growth or decline among specific risk groups can aid in optimizing interventions, particularly when resources are limited. Phylogenetic trees have been widely used in the detection of transmission chains and high-risk populations. Moreover, tree topology and the incorporation of population parameters (phylodynamics) can be useful in reconstructing the evolutionary dynamics of an epidemic across space and time among individuals. We now demonstrate the utility of phylodynamic trees for transmission modeling and forecasting, developing a phylogeny-based deep learning system, referred to as DeepDynaForecast. Our approach leverages a primal-dual graph learning structure with shortcut multi-layer aggregation, which is suited for the early identification and prediction of transmission dynamics in emerging high-risk groups. We demonstrate the accuracy of DeepDynaForecast using simulated outbreak data and the utility of the learned model using empirical, large-scale data from the human immunodeficiency virus epidemic in Florida between 2012 and 2020. Our framework is available as open-source software (MIT license) at github.com/lab-smile/DeepDynaForcast.

Development of a reverse transcriptase digital droplet polymerase chain reaction-based approach for SARS-CoV-2 variant surveillance in wastewater

An urgent need for effective surveillance strategies arose due to the global emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although vaccines and antivirals are available, concerns persist about the evolution of new variants with potentially increased infectivity, transmissibility, and immune evasion. Therefore, variant monitoring is crucial for public health decision-making. Wastewater-based surveillance has proven to be an effective tool to monitor SARS-CoV-2 variants within populations. Specific SARS-CoV-2 variants are detected and quantified in wastewater in this study using a reverse transcriptase digital droplet polymerase chain reaction (RT-ddPCR) approach. The 11 designed assays were first validated in silico using a substantial dataset of high-quality SARS-CoV-2 genomes to ensure comprehensive variant coverage. The assessment of the sensitivity and specificity with reference material showed the capability of the developed assays to reliably identify target mutations while minimizing false positives and false negatives. The applicability of the assays was evaluated using wastewater samples from a wastewater treatment plant in Ghent, Belgium. The quantification of the specific mutations linked to the variants of concern present in these samples was calculated using these assays based on the detection of single mutations, which confirms their use for real-world variant surveillance. In conclusion, this study provides an adaptable protocol to monitor SARS-CoV-2 variants in wastewater with high sensitivity and specificity. Its potential for broader application in other viral surveillance contexts highlights its added value for rapid response to emerging infectious diseases. PRACTITIONER POINTS: Robust RT-ddPCR methodology for specific SARS-CoV-2 variants of concern detection in wastewater. Rigorous validation that demonstrates high sensitivity and specificity. Demonstration of real-world applicability using wastewater samples. Valuable tool for rapid response to emerging infectious diseases.

Present and Future Non-Culture-Based Diagnostics: Stewardship Potentials and Considerations

The medical microbiologist plays a key role in the transition from culture-based to molecular test methods for diagnosis of infectious diseases. They must understand the scientific and technical bases underlying these tests along with their associated benefits and limitations and be able to educate administrators and patient providers on their proper use. Coordination of testing practices between clinical departments and the spectrum of public health and research laboratories is essential to optimize health care delivery.

Six dilemmas for stakeholders inherently affecting data sharing during a zoonotic (re-)emerging infectious disease outbreak response

BACKGROUND

Timely access to outbreak related data, particularly in the early events of a spillover, is important to support evidence based control measures in response to outbreaks of zoonotic Emerging Infectious Diseases (EID). Yet, this is impeded by several barriers that need to be understood to promote timely sharing of data. Using the MERS epidemic as a model for a zoonotic EID outbreak, this study sought to provide an in-depth understanding of data sharing practices.

METHODS

Semi-structured interviews with 25 experts were conducted, along with Focus Group Discussions with 15 additional experts. A root-cause analysis was performed to examine the causal relationships between barriers. Enablers were mapped to the root-cause analysis to understand their influence on the barriers. Finally, root causes were placed in context of core dilemmas identified from the qualitative analysis.

FINDINGS

Eight barriers to data sharing were identified, related to collaboration, technical preparedness, regulations, and (conflict of) interests, and placed in the context of six dilemmas inherent to the multi-stakeholder collaboration required for a zoonotic outbreak response. Fourteen identified enablers showed the willingness of stakeholders to overcome or circumvent these barriers, but also indicated the inherent trial and error nature of implementing such enablers.

INTERPRETATION

Addressing the barriers requires solutions that must consider the complexity and interconnectedness of the root causes underlying them, and should consider the distinct scopes and interests of the different stakeholders. Insights provided by this study can be used to encourage data sharing practices for future outbreaks FUNDING: Wellcome Trust and UK Aid; EU-H2020 Societal Challenges (grant agreement no. 643476), Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VI.Veni.201S.044).

Virus sequencing performance during the SARS-CoV-2 pandemic: a retrospective analysis of data from multiple rounds of external quality assessment in Austria

Introduction: A notable feature of the 2019 coronavirus disease (COVID-19) pandemic was the widespread use of whole genome sequencing (WGS) to monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Countries around the world relied on sequencing and other forms of variant detection to perform contact tracing and monitor changes in the virus genome, in the hopes that epidemic waves caused by variants would be detected and managed earlier. As sequencing was encouraged and rewarded by the government in Austria, but represented a new technicque for many laboratories, we designed an external quality assessment (EQA) scheme to monitor the accuracy of WGS and assist laboratories in validating their methods. Methods: We implemented SARS-CoV-2 WGS EQAs in Austria and report the results from 7 participants over 5 rounds from February 2021 until June 2023. The participants received sample material, sequenced genomes with routine methods, and provided the sequences as well as information about mutations and lineages. Participants were evaluated on the completeness and accuracy of the submitted sequence and the ability to analyze and interpret sequencing data. Results: The results indicate that performance was excellent with few exceptions, and these exceptions showed improvement over time. We extend our findings to infer that most publicly available sequences are accurate within ≤1 nucleotide, somewhat randomly distributed through the genome. Conclusion: WGS continues to be used for SARS-CoV-2 surveillance, and will likely be instrumental in future outbreak scenarios. We identified hurdles in building next-generation sequencing capacity in diagnostic laboratories. EQAs will help individual laboratories maintain high quality next-generation sequencing output, and strengthen variant monitoring and molecular epidemiology efforts.

Analysis of transcriptomics data from COVID-19 patients: a pilot research

During SARS-CoV-2 infection, the virus transforms the infected host cell into factories that produce new viral particles. As infection progresses, the infected cells undergo numerous changes in various pathways. One of these changes is the occurrence of a cytokine storm, which leads to severe symptoms. In this study, we examined the transcriptomic changes caused by COVID-19 by analyzing RNA-seq data obtained from COVID-19-positive patients as well as COVID-19-negative donors. RNA-seq data were collected for the purpose of identification of potential biomarkers associated with a different course of the disease. We analyzed the first datasets, consisting of 96 samples to validate our methods. The objective of this publication is to report the pilot results. To explore potential biomarkers related to disease severity, we conducted a differential expression analysis of human transcriptome, focusing on COVID-19 positivity and symptom severity. Given the large number of potential biomarkers we identified, we further performed pathway enrichment analysis with terms from Kyoto Encyclopedia of Genes and Genomics (KEGG) to obtain a more profound understanding of altered pathways. Our results indicate that pathways related to immune processes, response to infection, and multiple signaling pathways were affected. These findings align with several previous studies that also reported the influence of SARS-CoV-2 infection on these pathways.

The Omicron XBB.1 Variant and Its Descendants: Genomic Mutations, Rapid Dissemination and Notable Characteristics

The SARS-CoV-2 virus, which is a major threat to human health, has undergone many mutations during the replication process due to errors in the replication steps and modifications in the structure of viral proteins. The XBB variant was identified for the first time in Singapore in the fall of 2022. It was then detected in other countries, including the United States, Canada, and the United Kingdom. We study the impact of sequence changes on spike protein structure on the subvariants of XBB, with particular attention to the velocity of variant diffusion and virus activity with respect to its diffusion. We examine the structural and functional distinctions of the variants in three different conformations: (i) spike glycoprotein in complex with ACE2 (1-up state), (ii) spike glycoprotein (closed-1 state), and (iii) S protein (open-1 state). We also estimate the affinity binding between the spike protein and ACE2. The market binding affinity observed in specific variants raises questions about the efficacy of current vaccines in preparing the immune system for virus variant recognition. This work may be useful in devising strategies to manage the ongoing COVID-19 pandemic. To stay ahead of the virus evolution, further research and surveillance should be carried out to adjust public health measures accordingly.

A systematic approach to microbial forensics

The coronavirus disease 2019 pandemic accelerated developments in biotechnology that underpin infection science. These advances present an opportunity to refresh the microbial forensic toolkit. Integration of novel analytical techniques with established forensic methods will speed up acquisition of evidence and better support lines of enquiry. A critical part of any such investigation is demonstration of a robust causal relationship and attribution of responsibility for an incident. In the wider context of a formal investigation into agency, motivation and intent, the quick and efficient assembly of microbiological evidence sets the tone and tempo of the entire investigation. Integration of established and novel analytical techniques from infection science into a systematic approach to microbial forensics will therefore ensure that major perspectives are correctly used to frame and shape the evidence into a clear narrative, while recognizing that forensic hypothesis generation, testing and refinement comprise an iterative process. Development of multidisciplinary training exercises that use this approach will enable translation into practice and efficient implementation when the need arises.

Mobilisation and analyses of publicly available SARS-CoV-2 data for pandemic responses

The COVID-19 pandemic has seen large-scale pathogen genomic sequencing efforts, becoming part of the toolbox for surveillance and epidemic research. This resulted in an unprecedented level of data sharing to open repositories, which has actively supported the identification of SARS-CoV-2 structure, molecular interactions, mutations and variants, and facilitated vaccine development and drug reuse studies and design. The European COVID-19 Data Platform was launched to support this data sharing, and has resulted in the deposition of several million SARS-CoV-2 raw reads. In this paper we describe (1) open data sharing, (2) tools for submission, analysis, visualisation and data claiming (e.g. ORCiD), (3) the systematic analysis of these datasets, at scale via the SARS-CoV-2 Data Hubs as well as (4) lessons learnt. This paper describes a component of the Platform, the SARS-CoV-2 Data Hubs, which enable the extension and set up of infrastructure that we intend to use more widely in the future for pathogen surveillance and pandemic preparedness.

Many-core algorithms for high-dimensional gradients on phylogenetic trees

MOTIVATION

Advancements in high-throughput genomic sequencing are delivering genomic pathogen data at an unprecedented rate, positioning statistical phylogenetics as a critical tool to monitor infectious diseases globally. This rapid growth spurs the need for efficient inference techniques, such as Hamiltonian Monte Carlo (HMC) in a Bayesian framework, to estimate parameters of these phylogenetic models where the dimensions of the parameters increase with the number of sequences N. HMC requires repeated calculation of the gradient of the data log-likelihood with respect to (wrt) all branch-length-specific (BLS) parameters that traditionally takes O(N2) operations using the standard pruning algorithm. A recent study proposes an approach to calculate this gradient in O(N), enabling researchers to take advantage of gradient-based samplers such as HMC. The CPU implementation of this approach makes the calculation of the gradient computationally tractable for nucleotide-based models but falls short in performance for larger state-space size models, such as Markov-modulated and codon models. Here, we describe novel massively parallel algorithms to calculate the gradient of the log-likelihood wrt all BLS parameters that take advantage of graphics processing units (GPUs) and result in many fold higher speedups over previous CPU implementations.

RESULTS

We benchmark these GPU algorithms on three computing systems using three evolutionary inference examples exploring complete genomes from 997 dengue viruses, 62 carnivore mitochondria and 49 yeasts, and observe a >128-fold speedup over the CPU implementation for codon-based models and >8-fold speedup for nucleotide-based models. As a practical demonstration, we also estimate the timing of the first introduction of West Nile virus into the continental Unites States under a codon model with a relaxed molecular clock from 104 full viral genomes, an inference task previously intractable.

AVAILABILITY AND IMPLEMENTATION

We provide an implementation of our GPU algorithms in BEAGLE v4.0.0 (https://github.com/beagle-dev/beagle-lib), an open-source library for statistical phylogenetics that enables parallel calculations on multi-core CPUs and GPUs. We employ a BEAGLE-implementation using the Bayesian phylogenetics framework BEAST (https://github.com/beast-dev/beast-mcmc).

Interaction of toll-like receptors and ACE-2 with different variants of SARS-CoV-2: A computational analysis

Introduction

Computational studies were performed to investigate the unknown status of endosomal and cell surface receptors in SARS-CoV-2 infection. The interactions between Toll-like receptors (TLRs)- 4/7/8/9 or ACE2 receptor and different SARS-CoV-2 variants were investigated.

Methods

The RNA motifs for TLR7, TLR8 and a CpG motif for TLR9 were analyzed in different variants. Molecular docking and molecular dynamics (MD) simulations were performed to investigate receptor-ligand interactions.

Results

The number of motifs recognized by TLR7/8/9 in the Alpha, Delta and Iranian variants was lower than in the wild type (WT). Docking analysis revealed that the Alpha, Delta and some Iranian spike variants had a higher affinity for ACE2 and TLR4 than the WT, which may account for their higher transmission rate. The MD simulation also showed differences in stability and structure size between the variants and the WT, indicating potential variations in viral load.

Conclusion

It appears that Alpha and some Iranian isolates are the variants of concern due to their higher transmissibility and rapid spread. The Delta mutant is also a variant of concern, not only because of its closer interaction with ACE2, but also with TLR4. Our results emphasize the importance of ACE2 and TLR4, rather than endosomal TLRs, in mediating the effects of different viral mutations and suggest their potential therapeutic applications.

Molecular biology of SARS-CoV-2 and techniques of diagnosis and surveillance

The World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19), a disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a global pandemic in March 2020. Reverse transcription-polymerase chain reaction (RT-PCR) is the reference technique for molecular diagnosis of SARS-CoV-2 infection. The SARS-CoV-2 virus is constantly mutating, and more transmissible variants have emerged, making genomic surveillance a crucial tool for investigating virus transmission dynamics, detecting novel genetic variants, and assessing mutation impact. The S gene, which encodes the spike protein, is frequently mutated, and it plays an important role in transmissibility. Spike protein mutations affect infectivity and vaccine effectiveness. SARS-CoV-2 variants are tracked using whole genome sequencing (WGS) and S-gene analysis. WGS, Sanger sequencing, and many S-gene-targeted RT-PCR methods have been developed. WGS and Sanger sequencing are standard methods for detecting mutations and can be used to identify known and unknown mutations. Melting curve analysis, endpoint genotyping assay, and S-gene target failure are used in the RT-PCR-based method for the rapid detection of specific mutations in SARS-CoV-2 variants. Therefore, these assays are suitable for high-throughput screening. The combinatorial use of RT-PCR-based assays, Sanger sequencing, and WGS enables rapid and accurate tracking of SARS-CoV-2 variants. In this review, we described RT-PCR-based detection and surveillance techniques for SARS-CoV-2.

Comparative genotyping of SARS-CoV-2 among Egyptian patients: near-full length genomic sequences versus selected spike and nucleocapsid regions

Several tools have been developed for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genotyping based on either whole genome or spike sequencing. We aimed to highlight the molecular epidemiological landscape of SARS-CoV-2 in Egypt since the start of the pandemic, to describe discrepancies between the 3 typing tools: Global Initiative on Sharing Avian Influenza Data (GISAID), Nextclade, and Phylogenetic Assignment of Named Global Outbreak Lineages (PANGOLIN) and to assess the fitness of spike and nucleocapsid regions for lineage assignment compared to the whole genome. A total of 3935 sequences isolated from Egypt (March 2020-2023) were retrieved from the GISAID database. A subset of data (n = 1212) with high coverage whole genome was used for tool discrimination and agreement analyses. Among 1212 sequences, the highest discriminatory power was 0.895 for PANGOLIN, followed by GISAID (0.872) and Nextclade (0.866). There was a statistically significant difference (p = 0.0418) between lineages assigned via spike (30%) and nucleocapsid (46%) compared to their whole genome-assigned lineages. The first 3 pandemic waves were dominated by B.1, followed by C.36 and then C.36.3, while the fourth to sixth waves were dominated by the B.1.617.2, BA, and BA.5.2 lineages, respectively. Current shift in lineage typing to recombinant forms. The 3 typing tools showed comparable discrimination among SARS-CoV-2 lineages. The nucleocapsid region could be used for lineage assignment.

Vulnerability of pangolin SARS-CoV-2 lineage assignment to adversarial attack

Pangolin is the most popular tool for SARS-CoV-2 lineage assignment. During COVID-19, healthcare professionals and policymakers required accurate and timely lineage assignment of SARS-CoV-2 genomes for pandemic response. Therefore, tools such as Pangolin use a machine learning model, pangoLEARN, for fast and accurate lineage assignment. Unfortunately, machine learning models are susceptible to adversarial attacks, in which minute changes to the inputs cause substantial changes in the model prediction. We present an attack that uses the pangoLEARN architecture to find perturbations that change the lineage assignment, often with only 2-3 base pair changes. The attacks we carried out show that pangolin is vulnerable to adversarial attack, with success rates between 0.98 and 1 for sequences from non-VoC lineages when pangoLEARN is used for lineage assignment. The attacks we carried out are almost never successful against VoC lineages because pangolin uses Usher and Scorpio - the non-machine-learning alternative methods for VoC lineage assignment. A malicious agent could use the proposed attack to fake or mask outbreaks or circulating lineages. Developers of software in the field of microbial genomics should be aware of the vulnerabilities of machine learning based models and mitigate such risks.

Quartz Crystal Microbalance Platform for SARS-CoV-2 Immuno-Diagnostics

Rapid and accurate serological analysis of SARS-CoV-2 antibodies is important for assessing immune protection from vaccination or infection of individuals and for projecting virus spread within a population. The quartz crystal microbalance (QCM) is a label-free flow-based sensor platform that offers an opportunity to detect the binding of a fluid-phase ligand to an immobilized target molecule in real time. A QCM-based assay was developed for the detection of SARS-CoV-2 antibody binding and evaluated for assay reproducibility. The assay was cross-compared to the Roche electrochemiluminescence assay (ECLIA) Elecsys® Anti-SARS-CoV-2 serology test kit and YHLO's chemiluminescence immunoassay (CLIA). The day-to-day reproducibility of the assay had a correlation of r2 = 0.99, p < 0.001. The assay linearity was r2 = 0.96, p < 0.001, for dilution in both serum and buffer. In the cross-comparison analysis of 119 human serum samples, 59 were positive in the Roche, 52 in the YHLO, and 48 in the QCM immunoassay. Despite differences in the detection method and antigen used for antibody capture, there was good coherence between the assays, 80-100% for positive and 96-100% for negative test results. In summation, the QCM-based SARS-CoV-2 IgG immunoassay showed high reproducibility and linearity, along with good coherence with the ELISA-based assays. Still, factors including antibody titer and antigen-binding affinity may differentially affect the various assays' responses.

SARS-CoV-2 genomics and impact on clinical care for COVID-19

The emergence and worldwide spread of SARS-CoV-2 during the COVID-19 pandemic necessitated the adaptation and rapid deployment of viral WGS and analysis techniques that had been previously applied on a more limited basis to other viral pathogens, such as HIV and influenza viruses. The need for WGS was driven in part by the low mutation rate of SARS-CoV-2, which necessitated measuring variation along the entire genome sequence to effectively differentiate lineages and characterize viral evolution. Several WGS approaches designed to maximize throughput and accuracy were quickly adopted by surveillance labs around the world. These broad-based SARS-CoV-2 genomic sequencing efforts revealed ongoing evolution of the virus, highlighted by the successive emergence of new viral variants throughout the course of the pandemic. These genomic insights were instrumental in characterizing the effects of viral mutations on transmissibility, immune escape and viral tropism, which in turn helped guide public health policy, the use of monoclonal antibody therapeutics and vaccine development strategies. As the use of direct-acting antivirals for the treatment of COVID-19 became more widespread, the potential for emergence of antiviral resistance has driven ongoing efforts to delineate resistance mutations and to monitor global sequence databases for their emergence. Given the critical role of viral genomics in the international effort to combat the COVID-19 pandemic, coordinated efforts should be made to expand global genomic surveillance capacity and infrastructure towards the anticipation and prevention of future pandemics.

Lineage replacement and evolution captured by 3 years of the United Kingdom Coronavirus (COVID-19) Infection Survey

The Office for National Statistics Coronavirus (COVID-19) Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors, although this was also accompanied by a gradual fall in average viral burdens from June 2021 to March 2023. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non-SGTF over time. Evolution was characterized by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens.

An overview of avian influenza surveillance strategies and modes

The global epidemic of avian influenza has imposed a substantial disease burden, inciting substantial societal panic and economic losses. The high variability and associated uncertainty of the influenza virus present significant challenges in its prevention and control. As a pivotal strategy for the mitigation of avian influenza, the surveillance network has shown considerable growth at both global and regional levels. This includes the expansion of surveillance coverage, continuous refinement of monitoring content and scope, and rapid enhancement of monitoring quality. Although the ultimate goal of avian influenza surveillance remains uniform, strategies and models vary, reflecting regional or national differences in surveillance system frameworks and their implementation. This review collates and examines the features and experiences of global, regional, and national avian influenza surveillance efforts. Furthermore, it delves into the surveillance system modalities in light of the "One Health" concept, which includes the establishment and enhancement of interdisciplinary and cross-sectoral coordination and cooperation among medical, veterinary, and public health institutions, and the sharing of surveillance information for timely alerts.

From De Novo Design to Redesign: Harnessing Computational Protein Design for Understanding SARS-CoV-2 Molecular Mechanisms and Developing Therapeutics

The continuous emergence of novel SARS-CoV-2 variants and subvariants serves as compelling evidence that COVID-19 is an ongoing concern. The swift, well-coordinated response to the pandemic highlights how technological advancements can accelerate the detection, monitoring, and treatment of the disease. Robust surveillance systems have been established to understand the clinical characteristics of new variants, although the unpredictable nature of these variants presents significant challenges. Some variants have shown resistance to current treatments, but innovative technologies like computational protein design (CPD) offer promising solutions and versatile therapeutics against SARS-CoV-2. Advances in computing power, coupled with open-source platforms like AlphaFold and RFdiffusion (employing deep neural network and diffusion generative models), among many others, have accelerated the design of protein therapeutics with precise structures and intended functions. CPD has played a pivotal role in developing peptide inhibitors, mini proteins, protein mimics, decoy receptors, nanobodies, monoclonal antibodies, identifying drug-resistance mutations, and even redesigning native SARS-CoV-2 proteins. Pending regulatory approval, these designed therapies hold the potential for a lasting impact on human health and sustainability. As SARS-CoV-2 continues to evolve, use of such technologies enables the ongoing development of alternative strategies, thus equipping us for the "New Normal".

Designing peptides predicted to bind to the omicron variant better than ACE2 via computational protein design and molecular dynamics

Brought about by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease (COVID-19) pandemic has resulted in large numbers of worldwide deaths and cases. Several SARS-CoV-2 variants have evolved, and Omicron (B.1.1.529) was one of the important variants of concern. It gets inside human cells by using its S1 subunit's receptor-binding domain (SARS-CoV-2-RBD) to bind to Angiotensin-converting enzyme 2 receptor's peptidase domain (ACE2-PD). Using peptides to inhibit binding interactions (BIs) between ACE2-PD and SARS-CoV-2-RBD is one of promising COVID-19 therapies. Employing computational protein design (CPD) as well as molecular dynamics (MD), this study used ACE2-PD's α1 helix to generate novel 25-mer peptide binders (SPB25) of Omicron RBD that have predicted binding affinities (ΔGbind (MM‑GBSA)) better than ACE2 by increasing favorable BIs between SPB25 and the conserved residues of RBD. Results from MD and the MM-GBSA method identified two best designed peptides (SPB25T7L/K11A and SPB25T7L/K11L with ΔGbind (MM‑GBSA) of -92.4 ± 0.4 and -95.7 ± 0.5 kcal/mol, respectively) that have better ΔGbind (MM‑GBSA) to Omicron RBD than ACE2 (-87.9 ± 0.5 kcal/mol) and SPB25 (-71.6 ± 0.5 kcal/mol). Additionally, they were predicted to have slightly higher stabilities, based on their percent helicities in water, than SBP1 (the experimentally proven inhibitor of SARS-CoV-2-RBD). Our two best designed SPB25s are promising candidates as omicron variant inhibitors.

Genomic Epidemiology and Lineage Dynamics of SARS-CoV-2 in Bulgaria: Insights from a Three-Year Pandemic Analysis

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has brought about significant challenges worldwide. In this study, we present a comprehensive analysis of the genomic epidemiology and lineage dynamics of SARS-CoV-2 in Bulgaria over a three-year period. Through extensive genomic sequencing and data analysis, we investigated the evolution of the virus, the emergence of variants of concern (VOCs), and their impact on the country's pandemic trajectory. We also assessed the relationship between viral diversity and COVID-19 morbidity and mortality in Bulgaria. Our findings shed light on the temporal and spatial distribution of SARS-CoV-2 lineages and provide crucial insights into the dynamics of the pandemic in the country. The interplay between international travel and viral transmission plays a significant role in the emergence and dissemination of different SARS-CoV-2 variants. The observed proportions of exportation to various continents provide insights into the potential pathways through which these lineages spread globally. Understanding the genomic epidemiology of SARS-CoV-2 in Bulgaria is essential for formulating targeted public health strategies, enhancing vaccination efforts, and effectively managing future outbreaks.

Genomic classification and antimicrobial resistance profiling of Streptococcus pneumoniae and Haemophilus influenza isolates associated with paediatric otitis media and upper respiratory infection

Acute otitis media (AOM) is the most common childhood bacterial infectious disease requiring antimicrobial therapy. Most cases of AOM are caused by translocation of Streptococcus pneumoniae or Haemophilus influenzae from the nasopharynx to the middle ear during an upper respiratory tract infection (URI). Ongoing genomic surveillance of these pathogens is important for vaccine design and tracking of emerging variants, as well as for monitoring patterns of antibiotic resistance to inform treatment strategies and stewardship.In this work, we examined the ability of a genomics-based workflow to determine microbiological and clinically relevant information from cultured bacterial isolates obtained from patients with AOM or an URI. We performed whole genome sequencing (WGS) and analysis of 148 bacterial isolates cultured from the nasopharynx (N = 124, 94 AOM and 30 URI) and ear (N = 24, all AOM) of 101 children aged 6-35 months presenting with AOM or an URI. We then performed WGS-based sequence typing and antimicrobial resistance profiling of each strain and compared results to those obtained from traditional microbiological phenotyping.WGS of clinical isolates resulted in 71 S. pneumoniae genomes and 76 H. influenzae genomes. Multilocus sequencing typing (MSLT) identified 33 sequence types for S. pneumoniae and 19 predicted serotypes including the most frequent serotypes 35B and 3. Genome analysis predicted 30% of S. pneumoniae isolates to have complete or intermediate penicillin resistance. AMR predictions for S. pneumoniae isolates had strong agreement with clinical susceptibility testing results for beta-lactam and non beta-lactam antibiotics, with a mean sensitivity of 93% (86-100%) and a mean specificity of 98% (94-100%). MLST identified 29 H. influenzae sequence types. Genome analysis identified beta-lactamase genes in 30% of H. influenzae strains, which was 100% in agreement with clinical beta-lactamase testing. We also identified a divergent highly antibiotic-resistant strain of S. pneumoniae, and found its closest sequenced strains, also isolated from nasopharyngeal samples from over 15 years ago.Ultimately, our work provides the groundwork for clinical WGS-based workflows to aid in detection and analysis of H. influenzae and S. pneumoniae isolates.

Molecular epidemiology of SARS-CoV-2 variants in circulation in the state of Maranhão, Brazil

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a coronavirus belonging to the beta CoV genus, responsible for SARS in humans, which became known as COVID-19. The emergence of variants of this virus is related to the presence of cases of reinfection, reduced vaccine effectiveness and greater transmission of the virus. Objective: In this study, we evaluated the molecular epidemiology of SARS-CoV-2 lineages circulating in the state of Maranhão. This is a cross-sectional and retrospective epidemiological study of genomic surveillance of SARS-CoV-2. The study comprised of 338 genomes sequenced by the Next Generation Sequencing technique on Illumina's Miseq equipment, submitted to Global Initiative on Sharing Avian Influenza Data, 190 (56.2%) are from samples of female and 148 (43.8%) from male patients. Sequencing performed covered samples of patients aged between 1 and 108 years, with emphasis on the age groups from 30 to 39 years with 15.0% of sequenced genomes and 20 to 29 years with 12.4%. As for the distribution of sequenced genomes by health macro-regions, 285 (84.3%) are from cities in the northern macro-region. We evidenced the circulation of 29 lineages and sub-lineages, four of which belonging to the Delta variant (AY.43, AY.99.1, AY.99.2 and AY.101 responsible for 4.5% of the genomes) and the others belonging to the Omicron variant, with emphasis on: BA.1 and sub-lineages (42.8%); BA.4, BA.5 and sub-lineages (5.3% and 41.1%); the sub-lineages DL.1 and BQ.1 (5% and 2%). A strong genomic surveillance system allows the study of the natural history of the disease, when there is a resurgence of SARS-CoV-2 cases.

Genome analysis of SARS-CoV-2 isolates from a population reveals the rapid selective sweep of a haplotype carrying many pre-existing and new mutations

To understand the mechanism underlying the evolution of SARS-CoV-2 in a population, we sequenced 92 viral genomes from Assam, India. Analysis of these and database sequences revealed a complete selective sweep of a haplotype in Assam carrying 13 pre-existing variants, including a high leap in frequency of a variant on ORF8, which is involved in immune evasion. A comparative study between sequences of same lineage and similar time frames in and outside Assam showed that 10 of the 13 pre-existing variants had a frequency ranging from 96 to 99%, and the remaining 3 had a low frequency outside Assam. Using a phylogenetic approach to infer sequential occurrences of variants we found that the variant Phe120del on ORF8, which had a low frequency (1.75%) outside Assam, is at the base of the phylogenetic tree of variants and became totally fixed (100%) in Assam population. Based on this observation, we inferred that the variant on ORF8 had a selective advantage, so it carried the haplotype to reach the100% frequency. The haplotype also carried 32 pre-existing variants at a frequency from 1.00 to 80.00% outside Assam. Those of these variants that are more closely linked to the S-protein locus, which often carries advantageous mutations and is tightly linked to the ORF8 locus, retained higher frequencies, while the less tightly linked variants showed lower frequencies, likely due to recombination among co- circulating variants in Assam. The ratios of non-synonymous substitutions to synonymous substitutions suggested that some genes such as those coding for the S-protein and non-structural proteins underwent positive selection while others were subject to purifying selection during their evolution in Assam. Furthermore, we observed negative correlation of the Ct value of qRT-PCR of the patients with abundant ORF6 transcripts, suggesting that ORF6 can be used as a marker for estimating viral titer. In conclusion, our in-depth analysis of SARS-CoV-2 genomes in a regional population reveals the mechanism and dynamics of viral evolution.

Comparison of Four Active SARS-CoV-2 Surveillance Strategies in Representative Population Sample Points: Two-Factor Factorial Randomized Controlled Trial

BACKGROUND

The COVID-19 pandemic is characterized by rapid increases in infection burden owing to the emergence of new variants with higher transmissibility and immune escape. To date, monitoring the COVID-19 pandemic has mainly relied on passive surveillance, yielding biased epidemiological measures owing to the disproportionate number of undetected asymptomatic cases. Active surveillance could provide accurate estimates of the true prevalence to forecast the evolution of the pandemic, enabling evidence-based decision-making.

OBJECTIVE

This study compared 4 different approaches of active SARS-CoV-2 surveillance focusing on feasibility and epidemiological outcomes.

METHODS

A 2-factor factorial randomized controlled trial was conducted in 2020 in a German district with 700,000 inhabitants. The epidemiological outcome comprised SARS-CoV-2 prevalence and its precision. The 4 study arms combined 2 factors: individuals versus households and direct testing versus testing conditioned on symptom prescreening. Individuals aged ≥7 years were eligible. Altogether, 27,908 addresses from 51 municipalities were randomly allocated to the arms and 15 consecutive recruitment weekdays. Data collection and logistics were highly digitized, and a website in 5 languages enabled low-barrier registration and tracking of results. Gargle sample collection kits were sent by post. Participants collected a gargle sample at home and mailed it to the laboratory. Samples were analyzed with reverse transcription loop-mediated isothermal amplification (RT-LAMP); positive and weak results were confirmed with real-time reverse transcription-polymerase chain reaction (RT-PCR).

RESULTS

Recruitment was conducted between November 18 and December 11, 2020. The response rates in the 4 arms varied between 34.31% (2340/6821) and 41.17% (2043/4962). The prescreening classified 16.61% (1207/7266) of the patients as COVID-19 symptomatic. Altogether, 4232 persons without prescreening and 7623 participating in the prescreening provided 5351 gargle samples, of which 5319 (99.4%) could be analyzed. This yielded 17 confirmed SARS-CoV-2 infections and a combined prevalence of 0.36% (95% CI 0.14%-0.59%) in the arms without prescreening and 0.05% (95% CI 0.00%-0.108%) in the arms with prescreening (initial contacts only). Specifically, we found a prevalence of 0.31% (95% CI 0.06%-0.58%) for individuals and 0.35% (95% CI 0.09%-0.61%) for households, and lower estimates with prescreening (0.07%, 95% CI 0.0%-0.15% for individuals and 0.02%, 95% CI 0.0%-0.06% for households). Asymptomatic infections occurred in 27% (3/11) of the positive cases with symptom data. The 2 arms without prescreening performed the best regarding effectiveness and accuracy.

CONCLUSIONS

This study showed that postal mailing of gargle sample kits and returning home-based self-collected liquid gargle samples followed by high-sensitivity RT-LAMP analysis is a feasible way to conduct active SARS-CoV-2 population surveillance without burdening routine diagnostic testing. Efforts to improve participation rates and integration into the public health system may increase the potential to monitor the course of the pandemic.

TRIAL REGISTRATION

Deutsches Register Klinischer Studien (DRKS) DRKS00023271; https://tinyurl.com/3xenz68a.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s13063-021-05619-5.

Phylogenies increase power to detect highly transmissible viral genome variants

As demonstrated by the SARS-CoV-2 pandemic, the emergence of novel viral strains with increased transmission rates poses a significant threat to global health. Viral genome sequences, combined with statistical models of sequence evolution, may provide a critical tool for early detection of these strains. Using a novel statistical model that links transmission rates to the entire viral genome sequence, we study the power of phylogenetic methods-using a phylogenetic tree relating viral samples-and count-based methods-using case-counts of variants over time-to detect increased transmission rates, and to identify causative mutations. We find that phylogenies in particular can detect novel variants very soon after their origin, and may facilitate the development of early detection systems for outbreak surveillance.

Molecular and Clinical Epidemiology of SARS-CoV-2 Infection among Vaccinated and Unvaccinated Individuals in a Large Healthcare Organization from New Jersey

New Jersey was among the first states impacted by the COVID-19 pandemic, with one of the highest overall death rates in the nation. Nevertheless, relatively few reports have been published focusing specifically on New Jersey. Here we report on molecular, clinical, and epidemiologic observations, from the largest healthcare network in the state, in a cohort of vaccinated and unvaccinated individuals with laboratory-confirmed SARS-CoV-2 infection. We conducted molecular surveillance of SARS-CoV-2-positive nasopharyngeal swabs collected in nine hospitals from December 2020 through June 2022, using both whole genome sequencing (WGS) and a real-time RT-PCR screening assay targeting spike protein mutations found in variants of concern (VOCs) within our region. De-identified clinical data were obtained retrospectively, including demographics, COVID-19 vaccination status, ICU admission, ventilator support, mortality, and medical history. Statistical analyses were performed to identify associations between SARS-CoV-2 variants, vaccination status, clinical outcomes, and medical risk factors. A total of 5007 SARS-CoV-2-positive nasopharyngeal swabs were successfully screened and/or sequenced. Variant screening identified three predominant VOCs, including Alpha (n = 714), Delta (n = 1877), and Omicron (n = 1802). Omicron isolates were further sub-typed as BA.1 (n = 899), BA.2 (n = 853), or BA.4/BA.5 (n = 50); the remaining 614 isolates were classified as "Other". Approximately 31.5% (1577/5007) of the samples were associated with vaccine breakthrough infections, which increased in frequency following the emergence of Delta and Omicron. Severe clinical outcomes included ICU admission (336/5007 = 6.7%), ventilator support (236/5007 = 4.7%), and mortality (430/5007 = 8.6%), with increasing age being the most significant contributor to each (p < 0.001). Unvaccinated individuals accounted for 79.7% (268/336) of ICU admissions, 78.3% (185/236) of ventilator cases, and 74.4% (320/430) of deaths. Highly significant (p < 0.001) increases in mortality were observed in individuals with cardiovascular disease, hypertension, cancer, diabetes, and hyperlipidemia, but not with obesity, thyroid disease, or respiratory disease. Significant differences (p < 0.001) in clinical outcomes were also noted between SARS-CoV-2 variants, including Delta, Omicron BA.1, and Omicron BA.2. Vaccination was associated with significantly improved clinical outcomes in our study, despite an increase in breakthrough infections associated with waning immunity, greater antigenic variability, or both. Underlying comorbidities contributed significantly to mortality in both vaccinated and unvaccinated individuals, with increasing risk based on the total number of comorbidities. Real-time RT-PCR-based screening facilitated timely identification of predominant variants using a minimal number of spike protein mutations, with faster turnaround time and reduced cost compared to WGS. Continued evolution of SARS-CoV-2 variants will likely require ongoing surveillance for new VOCs, with real-time assessment of clinical impact.

Deep mutagenesis scanning using whole trimeric SARS-CoV-2 spike highlights the importance of NTD-RBD interactions in determining spike phenotype

New variants of SARS-CoV-2 are continually emerging with mutations in spike associated with increased transmissibility and immune escape. Phenotypic maps can inform the prediction of concerning mutations from genomic surveillance, however most of these maps currently derive from studies using monomeric RBD, while spike is trimeric, and contains additional domains. These maps may fail to reflect interdomain interactions in the prediction of phenotypes. To try to improve on this, we developed a platform for deep mutational scanning using whole trimeric spike. We confirmed a previously reported epistatic effect within the RBD affecting ACE2 binding, that highlights the importance of updating the base spike sequence for future mutational scanning studies. Using post vaccine sera, we found that the immune response of vaccinated individuals was highly focused on one or two epitopes in the RBD and that single point mutations at these positions can account for most of the immune escape mediated by the Omicron BA.1 RBD. However, unexpectedly we found that the BA.1 RBD alone does not account for the high level of antigenic escape by BA.1 spike. We show that the BA.1 NTD amplifies the immune evasion of its associated RBD. BA.1 NTD reduces neutralistion by RBD directed monoclonal antibodies, and impacts ACE2 interaction. NTD variation is thus an important mechanism of immune evasion by SARS-CoV-2. Such effects are not seen when pre-stabilized spike proteins are used, suggesting the interdomain effects require protein mobility to express their phenotype.

SARS-CoV-2 protein structure and sequence mutations: Evolutionary analysis and effects on virus variants

The structure and sequence of proteins strongly influence their biological functions. New models and algorithms can help researchers in understanding how the evolution of sequences and structures is related to changes in functions. Recently, studies of SARS-CoV-2 Spike (S) protein structures have been performed to predict binding receptors and infection activity in COVID-19, hence the scientific interest in the effects of virus mutations due to sequence, structure and vaccination arises. However, there is the need for models and tools to study the links between the evolution of S protein sequence, structure and functions, and virus transmissibility and the effects of vaccination. As studies on S protein have been generated a large amount of relevant information, we propose in this work to use Protein Contact Networks (PCNs) to relate protein structures with biological properties by means of network topology properties. Topological properties are used to compare the structural changes with sequence changes. We find that both node centrality and community extraction analysis can be used to relate protein stability and functionality with sequence mutations. Starting from this we compare structural evolution to sequence changes and study mutations from a temporal perspective focusing on virus variants. Finally by applying our model to the Omicron variant we report a timeline correlation between Omicron and the vaccination campaign.

Polarimetric imaging for the detection of synthetic models of SARS-CoV-2: A proof of concept

Objective

To conduct a proof-of-concept study of the detection of two synthetic models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polarimetric imaging.

Approach

Two SARS-CoV-2 models were prepared as engineered lentiviruses pseudotyped with the G protein of the vesicular stomatitis virus, and with the characteristic Spike protein of SARS-CoV-2. Samples were prepared in two biofluids (saline solution and artificial saliva), in four concentrations, and deposited as 5-µL droplets on a supporting plate. The angles of maximal degree of linear polarization (DLP) of light diffusely scattered from dry residues were determined using Mueller polarimetry from87 samples at 405 nm and 514 nm. A polarimetric camera was used for imaging several samples under 380-420 nm illumination at angles similar to those of maximal DLP. Per-pixel image analysis included quantification and combination of polarization feature descriptors in 475 samples.

Main results

The angles (from sample surface) of maximal DLP were 3° for 405 nm and 6° for 514 nm. Similar viral particles that differed only in the characteristic spike protein of the SARS-CoV-2, their corresponding negative controls, fluids, and the sample holder were discerned at 10-degree and 15-degree configurations.

Significance

Polarimetric imaging in the visible spectrum may help improve fast, non-contact detection and identification of viral particles, and/or other microbes such as tuberculosis, in multiple dry fluid samples simultaneously, particularly when combined with other imaging modalities. Further analysis including realistic concentrations of real SARS-CoV-2 viral particles in relevant human fluids is required. Polarimetric imaging under visible light may contribute to a fast, cost-effective screening of SARS-CoV-2 and other pathogens when combined with other imaging modalities.

Universal whole-genome Oxford nanopore sequencing of SARS-CoV-2 using tiled amplicons

We developed a comprehensive multiplexed set of primers adapted for the Oxford Nanopore Rapid Barcoding library kit that allows universal SARS-CoV-2 genome sequencing. This primer set is designed to set up any variants of the primers pool for whole-genome sequencing of SARS-CoV-2 using single- or double-tiled amplicons from 1.2 to 4.8 kb with the Oxford Nanopore. This multiplexed set of primers is also applicable for tasks like targeted SARS-CoV-2 genome sequencing. We proposed here an optimized protocol to synthesize cDNA using Maxima H Minus Reverse Transcriptase with a set of SARS-CoV-2 specific primers, which has high yields of cDNA template for RNA and is capable of long-length cDNA synthesis from a wide range of RNA amounts and quality. The proposed protocol allows whole-genome sequencing of the SARS-CoV-2 virus with tiled amplicons up to 4.8 kb on low-titer virus samples and even where RNA degradation has occurred. This protocol reduces the time and cost from RNA to genome sequence compared to the Midnight multiplex PCR method for SARS-CoV-2 genome sequencing using the Oxford Nanopore.

The Lambda Variant in Argentina: Analyzing the Evolution and Spread of SARS-CoV-2 Lineage C.37

The second wave of COVID-19 occurred in South America in early 2021 and was mainly driven by Gamma and Lambda variants. In this study, we aimed to describe the emergence and local genomic diversity of the SARS-CoV-2 Lambda variant in Argentina, from its initial entry into the country until its detection ceased. Molecular surveillance was conducted on 9356 samples from Argentina between October 2020 and April 2022, and sequencing, phylogenetic, and phylogeographic analyses were performed. Our findings revealed that the Lambda variant was first detected in Argentina in January 2021 and steadily increased in frequency until it peaked in April 2021, with continued detection throughout the year. Phylodynamic analyses showed that at least 18 introductions of the Lambda variant into the country occurred, with nine of them having evidence of onward local transmission. The spatial--temporal reconstruction showed that Argentine clades were associated with Lambda sequences from Latin America and suggested an initial diversification in the Metropolitan Area of Buenos Aires before spreading to other regions in Argentina. Genetic analyses of genome sequences allowed us to describe the mutational patterns of the Argentine Lambda sequences and detect the emergence of rare mutations in an immunocompromised patient. Our study highlights the importance of genomic surveillance in identifying the introduction and geographical distribution of the SARS-CoV-2 Lambda variant, as well as in monitoring the emergence of mutations that could be involved in the evolutionary leaps that characterize variants of concern.

Extensive ITR expansion of the 2022 Mpox virus genome through gene duplication and gene loss

Poxviruses are known to evolve slower than RNA viruses with only 1-2 mutations/genome/year. Rather than single mutations, rearrangements such as gene gain and loss, which have been discussed as a possible driver for host adaption, were described in poxviruses. In 2022 and 2023 the world is being challenged by the largest global outbreak so far of Mpox virus, and the virus seems to have established itself in the human community for an extended period of time. Here, we report five Mpox virus genomes from Germany with extensive gene duplication and loss, leading to the expansion of the ITR regions from 6400 to up to 24,600 bp. We describe duplications of up to 18,200 bp to the opposed genome end, and deletions at the site of insertion of up to 16,900 bp. Deletions and duplications of genes with functions of supposed immune modulation, virulence and host adaption as B19R, B21R, B22R and D10L are described. In summary, we highlight the need for monitoring rearrangements of the Mpox virus genome rather than for monitoring single mutations only.

SARS-CoV-2 viral variants can rapidly be identified for clinical decision making and population surveillance using a high-throughput digital droplet PCR assay

Epidemiologic surveillance of circulating SARS-CoV-2 variants is essential to assess impact on clinical outcomes and vaccine efficacy. Whole genome sequencing (WGS), the gold-standard to identify variants, requires significant infrastructure and expertise. We developed a digital droplet polymerase chain reaction (ddPCR) assay that can rapidly identify circulating variants of concern/interest (VOC/VOI) using variant-specific mutation combinations in the Spike gene. To validate the assay, 800 saliva samples known to be SARS-CoV-2 positive by RT-PCR were used. During the study (July 2020-March 2022) the assay was easily adaptable to identify not only existing circulating VAC/VOI, but all new variants as they evolved. The assay can discriminate nine variants (Alpha, Beta, Gamma, Delta, Eta, Epsilon, Lambda, Mu, and Omicron) and sub-lineages (Delta 417N, Omicron BA.1, BA.2). Sequence analyses confirmed variant type for 124/124 samples tested. This ddPCR assay is an inexpensive, sensitive, high-throughput assay that can easily be adapted as new variants are identified.

The Swiss Pathogen Surveillance Platform - towards a nation-wide One Health data exchange platform for bacterial, viral and fungal genomics and associated metadata

The Swiss Pathogen Surveillance Platform (SPSP) is a shared secure surveillance platform between human and veterinary medicine, to also include environmental and foodborne isolates. It enables rapid and detailed transmission monitoring and outbreak surveillance of pathogens using whole genome sequencing data and associated metadata. It features controlled data access, complex dynamic queries, dedicated dashboards and automated data sharing with international repositories, providing actionable results for public health and the vision to improve societal well-being and health.

SARS-CoV-2 Variants by Whole-Genome Sequencing in a University Hospital in Bangkok: First to Third COVID-19 Waves

BACKGROUND

Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants emerged globally during the recent coronavirus disease (COVID-19) pandemic. From April 2020 to April 2021, Thailand experienced three COVID-19 waves, and each wave was driven by different variants. Therefore, we aimed to analyze the genetic diversity of circulating SARS-CoV-2 using whole-genome sequencing analysis.

METHODS

A total of 33 SARS-CoV-2 positive samples from three consecutive COVID-19 waves were collected and sequenced by whole-genome sequencing, of which, 8, 10, and 15 samples were derived from the first, second, and third waves, respectively. The genetic diversity of variants in each wave and the correlation between mutations and disease severity were explored.

RESULTS

During the first wave, A.6, B, B.1, and B.1.375 were found to be predominant. The occurrence of mutations in these lineages was associated with low asymptomatic and mild symptoms, providing no transmission advantage and resulting in extinction after a few months of circulation. B.1.36.16, the predominant lineage of the second wave, caused more symptomatic COVID-19 cases and contained a small number of key mutations. This variant was replaced by the VOC alpha variant, which later became dominant in the third wave. We found that B.1.1.7 lineage-specific mutations were crucial for increasing transmissibility and infectivity, but not likely associated with disease severity. There were six additional mutations found only in severe COVID-19 patients, which might have altered the virus phenotype with an inclination toward more highly pathogenic SARS-CoV-2.

CONCLUSION

The findings of this study highlighted the importance of whole-genome analysis in tracking newly emerging variants, exploring the genetic determinants essential for transmissibility, infectivity, and pathogenicity, and helping better understand the evolutionary process in the adaptation of viruses in humans.

Comparison of SARS-CoV-2 whole genome sequencing using tiled amplicon enrichment and bait hybridization

The severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) pandemic has led to extensive virological monitoring by whole genome sequencing (WGS). Investigating the advantages and limitations of different protocols is key when conducting population-level WGS. SARS-CoV-2 positive samples with Ct values of 14-30 were run using three different protocols: the Twist Bioscience SARS‑CoV‑2 protocol with bait hybridization enrichment sequenced with Illumina, and two tiled amplicon enrichment protocols, ARTIC V3 and Midnight, sequenced with Illumina and Oxford Nanopore Technologies, respectively. Twist resulted in better coverage uniformity and coverage of the entire genome, but has several drawbacks: high human contamination, laborious workflow, high cost, and variation between batches. The ARTIC and Midnight protocol produced an even coverage across samples, and almost all reads were mapped to the SARS-CoV-2 reference. ARTIC and Midnight represent robust, cost-effective, and highly scalable methods that are appropriate in a clinical environment. Lineage designations were uniform across methods, representing the dominant lineages in Sweden during the period of collection. This study provides insights into methodological differences in SARS‑CoV‑2 sequencing and guidance in selecting suitable methods for various purposes.

RT-RPA-Cas12a-based assay facilitates the discrimination of SARS-CoV-2 variants of concern

Timely and accurate detection of SARS-CoV-2 variants of concern (VOCs) is urgently needed for pandemic surveillance and control. Great efforts have been made from a mass of scientists in increasing the detection sensitivity and operability, and reducing the turn-around time and cost. Here, we report a nucleic acid testing-based method aiming to detect and discriminate SARS-CoV-2 mutations by combining RT-RPA and CRISPR-Cas12a detecting assays (RRCd). With a detection limit of 10 copies RNA/reaction, RRCd was validated in 194 clinical samples, showing 89% positive predictive agreement and 100% negative predictive agreement, respectively. Critically, using specific crRNAs, representatives of single nucleotide polymorphisms and small deletions in SARS-CoV-2 VOCs including N501Y, T478K and ΔH69-V70 were discriminated by RRCd, demonstrating 100% specificity in clinical samples with C _t < 33. The method completes within 65 min and could offer visible results without using any electrical devices, which probably facilitate point-of-care testing of SARS-CoV-2 variants and other epidemic viruses.

High-throughput screening of spike variants uncovers the key residues that alter the affinity and antigenicity of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has elicited a worldwide pandemic since late 2019. There has been ~675 million confirmed coronavirus disease 2019 (COVID-19) cases, leading to more than 6.8 million deaths as of March 1, 2023. Five SARS-CoV-2 variants of concern (VOCs) were tracked as they emerged and were subsequently characterized. However, it is still difficult to predict the next dominant variant due to the rapid evolution of its spike (S) glycoprotein, which affects the binding activity between cellular receptor angiotensin-converting enzyme 2 (ACE2) and blocks the presenting epitope from humoral monoclonal antibody (mAb) recognition. Here, we established a robust mammalian cell-surface-display platform to study the interactions of S-ACE2 and S-mAb on a large scale. A lentivirus library of S variants was generated via in silico chip synthesis followed by site-directed saturation mutagenesis, after which the enriched candidates were acquired through single-cell fluorescence sorting and analyzed by third-generation DNA sequencing technologies. The mutational landscape provides a blueprint for understanding the key residues of the S protein binding affinity to ACE2 and mAb evasion. It was found that S205F, Y453F, Q493A, Q493M, Q498H, Q498Y, N501F, and N501T showed a 3-12-fold increase in infectivity, of which Y453F, Q493A, and Q498Y exhibited at least a 10-fold resistance to mAbs REGN10933, LY-CoV555, and REGN10987, respectively. These methods for mammalian cells may assist in the precise control of SARS-CoV-2 in the future.