Evidence for SARS-CoV-2 Delta and Omicron co-infections and recombination

Enhancing the epidemiological surveillance of SARS-CoV-2 using Sanger sequencing to identify circulating variants and recombinants

Since the emergence of SARS-CoV-2 in December 2019, more than 12,000 mutations in the virus have been identified. These could cause changes in viral characteristics and directly impact global public health. The emergence of variants is a great concern due to the chance of increased transmissibility and infectivity. Sequencing for surveillance and monitoring circulating strains is extremely necessary as the early identification of new variants allows public health agencies to make faster and more effective decisions to contain the spread of the virus. In the present study, we identified circulating variants in samples collected in Belo Horizonte, Brazil, and detected a recombinant lineage using the Sanger method. The identification of lineages was done through gene amplification of SARS-CoV-2 by Reverse Transcription-Polymerase Chain Reaction (RT-PCR). By using these specific fragments, we were able to differentiate one variant of interest and five circulating variants of concern. We were also able to detect recombinants. Randomly selected samples were sequenced by either Sanger or Next Generation Sequencing (NGS). Our findings validate the effectiveness of Sanger sequencing as a powerful tool for monitoring variants. It is easy to perform and allows the analysis of a larger number of samples in countries that cannot afford NGS.

Towards Understanding and Identification of Human Viral Co-Infections

Viral co-infections, in which a host is infected with multiple viruses simultaneously, are common in the human population. Human viral co-infections can lead to complex interactions between the viruses and the host immune system, affecting the clinical outcome and posing challenges for treatment. Understanding the types, mechanisms, impacts, and identification methods of human viral co-infections is crucial for the prevention and control of viral diseases. In this review, we first introduce the significance of studying human viral co-infections and summarize the current research progress and gaps in this field. We then classify human viral co-infections into four types based on the pathogenic properties and species of the viruses involved. Next, we discuss the molecular mechanisms of viral co-infections, focusing on virus-virus interactions, host immune responses, and clinical manifestations. We also summarize the experimental and computational methods for the identification of viral co-infections, emphasizing the latest advances in high-throughput sequencing and bioinformatics approaches. Finally, we highlight the challenges and future directions in human viral co-infection research, aiming to provide new insights and strategies for the prevention, control, diagnosis, and treatment of viral diseases. This review provides a comprehensive overview of the current knowledge and future perspectives on human viral co-infections and underscores the need for interdisciplinary collaboration to address this complex and important topic.

Data-driven recombination detection in viral genomes

Recombination is a key molecular mechanism for the evolution and adaptation of viruses. The first recombinant SARS-CoV-2 genomes were recognized in 2021; as of today, more than ninety SARS-CoV-2 lineages are designated as recombinant. In the wake of the COVID-19 pandemic, several methods for detecting recombination in SARS-CoV-2 have been proposed; however, none could faithfully confirm manual analyses by experts in the field. We hereby present RecombinHunt, an original data-driven method for the identification of recombinant genomes, capable of recognizing recombinant SARS-CoV-2 genomes (or lineages) with one or two breakpoints with high accuracy and within reduced turn-around times. ReconbinHunt shows high specificity and sensitivity, compares favorably with other state-of-the-art methods, and faithfully confirms manual analyses by experts. RecombinHunt identifies recombinant viral genomes from the recent monkeypox epidemic in high concordance with manually curated analyses by experts, suggesting that our approach is robust and can be applied to any epidemic/pandemic virus.

A panel of multivalent nanobodies broadly neutralizing Omicron subvariants and recombinant

The emerging Omicron subvariants have a remarkable ability to spread and escape nearly all current monoclonal antibody (mAb) treatments. Although the virulence of SARS-CoV-2 has now diminished, it remains a significant threat to public health due to its high transmissibility and susceptibility to mutation. Therefore, it is urgent to develop broad-acting and potent therapeutics targeting current and emerging Omicron variants. Here, we identified a panel of Omicron BA.1 spike receptor-binding domain (RBD)-targeted nanobodies (Nbs) from a naive alpaca VHH library. This panel of Nbs exhibited high binding affinity to the spike RBD of wild-type, Alpha B.1.1.7, Beta B.1.351, Delta plus, Omicron BA.1, and BA.2. Through multivalent Nb construction, we obtained a subpanel of ultrapotent neutralizing Nbs against Omicron BA.1, BA.2, BF.7 and even emerging XBB.1.5, and XBB.1.16 pseudoviruses. Protein structure prediction and docking analysis showed that Nb trimer 2F2E5 targets two independent RBD epitopes, thus minimizing viral escape. Taken together, we obtained a panel of broad and ultrapotent neutralizing Nbs against Omicron BA.1, Omicron BA.2, BF.7, XBB.1.5, and XBB.1.16. These multivalent Nbs hold great promise for the treatment against SARS-CoV-2 infection and could possess a superwide neutralizing breadth against novel omicron mutants or recombinants.

Systematic detection of co-infection and intra-host recombination in more than 2 million global SARS-CoV-2 samples

Systematic monitoring of SARS-CoV-2 co-infections between different lineages and assessing the risk of intra-host recombinant emergence are crucial for forecasting viral evolution. Here we present a comprehensive analysis of more than 2 million SARS-CoV-2 raw read datasets submitted to the European COVID-19 Data Portal to identify co-infections and intra-host recombination. Co-infection was observed in 0.35% of the investigated cases. Two independent procedures were implemented to detect intra-host recombination. We show that sensitivity is predominantly determined by the density of lineage-defining mutations along the genome, thus we used an expanded list of mutually exclusive defining mutations of specific variant combinations to increase statistical power. We call attention to multiple challenges rendering recombinant detection difficult and provide guidelines for the reduction of false positives arising from chimeric sequences produced during PCR amplification. Additionally, we identify three recombination hotspots of Delta - Omicron BA.1 intra-host recombinants.

Competitive fitness and homologous recombination of SARS-CoV-2 variants of concern

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to emerge and cocirculate in humans and wild animals. The factors driving the emergence and replacement of novel variants and recombinants remain incompletely understood. Herein, we comprehensively characterized the competitive fitness of SARS-CoV-2 wild type (WT) and three variants of concern (VOCs), Alpha, Beta and Delta, by coinfection and serial passaging assays in different susceptible cells. Deep sequencing analyses revealed cell-specific competitive fitness: the Beta variant showed enhanced replication fitness during serial passage in Caco-2 cells, whereas the WT and Alpha variant showed elevated fitness in Vero E6 cells. Interestingly, a high level of neutralizing antibody sped up competition and completely reshaped the fitness advantages of different variants. More importantly, single clone purification identified a significant proportion of homologous recombinants that emerged during the passage history, and immune pressure reduced the frequency of recombination. Interestingly, a recombination hot region located between nucleotide sites 22,995 and 28,866 of the viral genomes could be identified in most of the detected recombinants. Our study not only profiled the variable competitive fitness of SARS-CoV-2 under different conditions, but also provided direct experimental evidence of homologous recombination between SARS-CoV-2 viruses, as well as a model for investigating SARS-CoV-2 recombination.

SARS-CoV-2 Co-Infections and Recombinations Identified by Long-Read Single-Molecule Real-Time Sequencing

Co-infection with at least 2 strains of virus is the prerequisite for recombination, one of the means of genetic diversification. Little is known about the prevalence of these events in SARS-CoV-2, partly because it is difficult to detect them. We used long-read PacBio single-molecule real-time (SMRT) sequencing technology to sequence whole genomes and targeted regions for haplotyping. We identified 17 co-infections with SARS-CoV-2 strains belonging to different clades in 6829 samples sequenced between January and October, 2022 (prevalence 0.25%). There were 3 Delta/Omicron co-infections and 14 Omicron/Omicron co-infections (4 cases of 21K/21L, 1 case of 21L/22A, 2 cases of 21L/22B, 4 cases of 22A/22B, 2 cases of 22B/22C and 1 case of 22B/22E). Four of these patients (24%) also harbored recombinant minor haplotypes, including one with a recombinant virus that was selected in the viral quasispecies over the course of his chronic infection. While co-infections remain rare among SARS-CoV-2-infected individuals, long-read SMRT sequencing is a useful tool for detecting them as well as recombinant events, providing the basis for assessing their clinical impact, and a precise indicator of epidemic evolution. IMPORTANCE SARS-CoV-2 variants have been responsible for the successive waves of infection over the 3 years of pandemic. While co-infection followed by recombination is one driver of virus evolution, there have been few reports of co-infections, mainly between Delta and Omicron variants or between the first 2 Omicron variants 21K_BA.1 and 21L_BA.2. The 17 co-infections we detected during 2022 included cases with the recent clades of Omicron 22A, 22B, 22C, and 22E; 24% harbored recombinant variants. This study shows that long-read SMRT sequencing is well suited to SARS-CoV-2 genomic surveillance.

The effects of amino acid substitution of spike protein and genomic recombination on the evolution of SARS-CoV-2

Over three years' pandemic of 2019 novel coronavirus disease (COVID-19), multiple variants and novel subvariants have emerged successively, outcompeted earlier variants and become predominant. The sequential emergence of variants reflects the evolutionary process of mutation-selection-adaption of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Amino acid substitution/insertion/deletion in the spike protein causes altered viral antigenicity, transmissibility, and pathogenicity of SARS-CoV-2. Early in the pandemic, D614G mutation conferred virus with advantages over previous variants and increased transmissibility, and it also laid a conservative background for subsequent substantial mutations. The role of genomic recombination in the evolution of SARS-CoV-2 raised increasing concern with the occurrence of novel recombinants such as Deltacron, XBB.1.5, XBB.1.9.1, and XBB.1.16 in the late phase of pandemic. Co-circulation of different variants and co-infection in immunocompromised patients accelerate the emergence of recombinants. Surveillance for SARS-CoV-2 genomic variations, particularly spike protein mutation and recombination, is essential to identify ongoing changes in the viral genome and antigenic epitopes and thus leads to the development of new vaccine strategies and interventions.

Wastewater surveillance uncovers regional diversity and dynamics of SARS-CoV-2 variants across nine states in the USA

Wastewater-based epidemiology (WBE) is a non-invasive and cost-effective approach for monitoring the spread of a pathogen within a community. WBE has been adopted as one of the methods to monitor the spread and population dynamics of the SARS-CoV-2 virus, but significant challenges remain in the bioinformatic analysis of WBE-derived data. Here, we have developed a new distance metric, CoVdist, and an associated analysis tool that facilitates the application of ordination analysis to WBE data and the identification of viral population changes based on nucleotide variants. We applied these new approaches to a large-scale dataset from 18 cities in nine states of the USA using wastewater collected from July 2021 to June 2022. We found that the trends in the shift between the Delta and Omicron SARS-CoV-2 lineages were largely consistent with what was seen in clinical data, but that wastewater analysis offered the added benefit of revealing significant differences in viral population dynamics at the state, city, and even neighborhood scales. We also were able to observe the early spread of variants of concern and the presence of recombinant lineages during the transitions between variants, both of which are challenging to analyze based on clinically-derived viral genomes. The methods outlined here will be beneficial for future applications of WBE to monitor SARS-CoV-2, particularly as clinical monitoring becomes less prevalent. Additionally, these approaches are generalizable, allowing them to be applied for the monitoring and analysis of future viral outbreaks.

Effect of Transmission and Vaccination on Time to Dominance of Emerging Viral Strains: A Simulation-Based Study

We studied the effect of transmissibility and vaccination on the time required for an emerging strain of an existing virus to dominate in the infected population using a simulation-based experiment. The emergent strain is assumed to be completely resistant to the available vaccine. A stochastic version of a modified SIR model for emerging viral strains was developed to simulate surveillance data for infections. The proportion of emergent viral strain infections among the infected was modeled using a logistic curve and the time to dominance (TTD) was recorded for each simulation. A factorial experiment was implemented to compare the TTD values for different transmissibility coefficients, vaccination rates, and initial vaccination coverage. We discovered a non-linear relationship between TTD and the relative transmissibility of the emergent strain for populations with low vaccination coverage. Furthermore, higher vaccination coverage and high vaccination rates in the population yielded significantly lower TTD values. Vaccinating susceptible individuals against the current strain increases the susceptible pool of the emergent virus, which leads to the emergent strain spreading faster and requiring less time to dominate the infected population.

Parallel deployment of passive and composite samplers for surveillance and variant profiling of SARS-CoV-2 in sewage

Wastewater-based epidemiology during the COVID-19 pandemic has proven useful for public health decision-making but is often hampered by sampling methodology constraints, particularly at the building- or neighborhood-level. Time-weighted composite samples are commonly used; however, autosamplers are expensive and can be affected by intermittent flows in sub-sewershed contexts. In this study, we compared time-weighted composite, grab, and passive sampling via Moore swabs, at four locations across a college campus to understand the utility of passive sampling. After optimizing the methods for sample handling and processing for viral RNA extraction, we quantified SARS-CoV-2 N1 and N2, as well as a fecal strength indicator, PMMoV, by ddRT-PCR and applied tiled amplicon sequencing of the SARS-CoV-2 genome. Passive samples compared favorably with composite samples in our study area: for samples collected concurrently, 42 % of the samples agreed between Moore swab and composite samples and 58 % of the samples were positive for SARS-CoV-2 using Moore swabs while composite samples were below the limit of detection. Variant profiles from Moore swabs showed a shift from variant BA.1 to BA.2, consistent with in-person saliva samples. These data have implications for the broader implementation of sewage surveillance without advanced sampling technologies and for the utilization of passive sampling approaches for other emerging pathogens.

PF-D-Trimer, a protective SARS-CoV-2 subunit vaccine: immunogenicity and application

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has had and continues to have a significant impact on global public health. One of the characteristics of SARS-CoV-2 is a surface homotrimeric spike protein, which is primarily responsible for the host immune response upon infection. Here we present the preclinical studies of a broadly protective SARS-CoV-2 subunit vaccine developed from our trimer domain platform using the Delta spike protein, from antigen design through purification, vaccine evaluation and manufacturability. The pre-fusion trimerized Delta spike protein, PF-D-Trimer, was highly expressed in Chinese hamster ovary (CHO) cells, purified by a rapid one-step anti-Trimer Domain monoclonal antibody immunoaffinity process and prepared as a vaccine formulation with an adjuvant. Immunogenicity studies have shown that this vaccine candidate induces robust immune responses in mouse, rat and Syrian hamster models. It also protects K18-hACE2 transgenic mice in a homologous viral challenge. Neutralizing antibodies induced by this vaccine show cross-reactivity against the ancestral WA1, Delta and several Omicrons, including BA.5.2. The formulated PF-D Trimer is stable for up to six months without refrigeration. The Trimer Domain platform was proven to be a key technology in the rapid production of PF-D-Trimer vaccine and may be crucial to accelerate the development and accessibility of updated versions of SARS-CoV-2 vaccines.

Molecular Evolution of SARS-CoV-2 during the COVID-19 Pandemic

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) produced diverse molecular variants during its recent expansion in humans that caused different transmissibility and severity of the associated disease as well as resistance to monoclonal antibodies and polyclonal sera, among other treatments. In order to understand the causes and consequences of the observed SARS-CoV-2 molecular diversity, a variety of recent studies investigated the molecular evolution of this virus during its expansion in humans. In general, this virus evolves with a moderate rate of evolution, in the order of 10-3-10-4 substitutions per site and per year, which presents continuous fluctuations over time. Despite its origin being frequently associated with recombination events between related coronaviruses, little evidence of recombination was detected, and it was mostly located in the spike coding region. Molecular adaptation is heterogeneous among SARS-CoV-2 genes. Although most of the genes evolved under purifying selection, several genes showed genetic signatures of diversifying selection, including a number of positively selected sites that affect proteins relevant for the virus replication. Here, we review current knowledge about the molecular evolution of SARS-CoV-2 in humans, including the emergence and establishment of variants of concern. We also clarify relationships between the nomenclatures of SARS-CoV-2 lineages. We conclude that the molecular evolution of this virus should be monitored over time for predicting relevant phenotypic consequences and designing future efficient treatments.

Using Haplotype-Based Artificial Intelligence to Evaluate SARS-CoV-2 Novel Variants and Mutations

Importance

Earlier detection of emerging novel SARS-COV-2 variants is important for public health surveillance of potential viral threats and for earlier prevention research. Artificial intelligence may facilitate early detection of SARS-CoV2 emerging novel variants based on variant-specific mutation haplotypes and, in turn, be associated with enhanced implementation of risk-stratified public health prevention strategies.

Objective

To develop a haplotype-based artificial intelligence (HAI) model for identifying novel variants, including mixture variants (MVs) of known variants and new variants with novel mutations.

Design, Setting, and Participants

This cross-sectional study used serially observed viral genomic sequences globally (prior to March 14, 2022) to train and validate the HAI model and used it to identify variants arising from a prospective set of viruses from March 15 to May 18, 2022.

Main Outcomes and Measures

Viral sequences, collection dates, and locations were subjected to statistical learning analysis to estimate variant-specific core mutations and haplotype frequencies, which were then used to construct an HAI model to identify novel variants.

Results

Through training on more than 5 million viral sequences, an HAI model was built, and its identification performance was validated on an independent validation set of more than 5 million viruses. Its identification performance was assessed on a prospective set of 344 901 viruses. In addition to achieving an accuracy of 92.8% (95% CI within 0.1%), the HAI model identified 4 Omicron MVs (Omicron-Alpha, Omicron-Delta, Omicron-Epsilon, and Omicron-Zeta), 2 Delta MVs (Delta-Kappa and Delta-Zeta), and 1 Alpha-Epsilon MV, among which Omicron-Epsilon MVs were most frequent (609/657 MVs [92.7%]). Furthermore, the HAI model found that 1699 Omicron viruses had unidentifiable variants given that these variants acquired novel mutations. Lastly, 524 variant-unassigned and variant-unidentifiable viruses carried 16 novel mutations, 8 of which were increasing in prevalence percentages as of May 2022.

Conclusions and Relevance

In this cross-sectional study, an HAI model found SARS-COV-2 viruses with MV or novel mutations in the global population, which may require closer examination and monitoring. These results suggest that HAI may complement phylogenic variant assignment, providing additional insights into emerging novel variants in the population.

The Delta and Omicron Variants of SARS-CoV-2: What We Know So Far

The world has not yet completely overcome the fear of the havoc brought by SARS-CoV-2. The virus has undergone several mutations since its initial appearance in China in December 2019. Several variations (i.e., B.1.616.1 (Kappa variant), B.1.617.2 (Delta variant), B.1.617.3, and BA.2.75 (Omicron variant)) have emerged throughout the pandemic, altering the virus's capacity to spread, risk profile, and even symptoms. Humanity faces a serious threat as long as the virus keeps adapting and changing its fundamental function to evade the immune system. The Delta variant has two escape alterations, E484Q and L452R, as well as other mutations; the most notable of these is P681R, which is expected to boost infectivity, whereas the Omicron has about 60 mutations with certain deletions and insertions. The Delta variant is 40-60% more contagious in comparison to the Alpha variant. Additionally, the AY.1 lineage, also known as the "Delta plus" variant, surfaced as a result of a mutation in the Delta variant, which was one of the causes of the life-threatening second wave of coronavirus disease 2019 (COVID-19). Nevertheless, the recent Omicron variants represent a reminder that the COVID-19 epidemic is far from ending. The wave has sparked a fervor of investigation on why the variant initially appeared to propagate so much more rapidly than the other three variants of concerns (VOCs), whether it is more threatening in those other ways, and how its type of mutations, which induce minor changes in its proteins, can wreck trouble. This review sheds light on the pathogenicity, mutations, treatments, and impact on the vaccine efficacy of the Delta and Omicron variants of SARS-CoV-2.

SARS-CoV-2 Variants of Concern and Variations within Their Genome Architecture: Does Nucleotide Distribution and Mutation Rate Alter the Functionality and Evolution of the Virus?

SARS-CoV-2 virus pathogenicity and transmissibility are correlated with the mutations acquired over time, giving rise to variants of concern (VOCs). Mutations can significantly influence the genetic make-up of the virus. Herein, we analyzed the SARS-CoV-2 genomes and sub-genomic nucleotide composition in relation to the mutation rate. Nucleotide percentage distributions of 1397 in-house-sequenced SARS-CoV-2 genomes were enumerated, and comparative analyses (i) within the VOCs and of (ii) recovered and mortality patients were performed. Fisher's test was carried out to highlight the significant mutations, followed by RNA secondary structure prediction and protein modeling for their functional impacts. Subsequently, a uniform dinucleotide composition of AT and GC was found across study cohorts. Notably, the N gene was observed to have a high GC percentage coupled with a relatively higher mutation rate. Functional analysis demonstrated the N gene mutations, C29144T and G29332T, to induce structural changes at the RNA level. Protein secondary structure prediction with N gene missense mutations revealed a differential composition of alpha helices, beta sheets, and coils, whereas the tertiary structure displayed no significant changes. Additionally, the N gene CTD region displayed no mutations. The analysis highlighted the importance of N protein in viral evolution with CTD as a possible target for antiviral drugs.