Tracking and curating putative SARS-CoV-2 recombinants with RIVET

Higher frequency of interstate over international transmission chains of SARS-CoV-2 virus at the Rio Grande do Sul - Brazil state borders

Brazil's COVID-19 response has faced challenges due to the continuous emergence of variants of concern (VOCs), emphasizing the need for ongoing genomic surveillance and retrospective analyses of past epidemic waves to reassess and fine tune containment protocols. Rio Grande do Sul (RS), Brazil's southernmost state, has international borders and trades with Argentina and Uruguay, along with significant domestic connections within Brazil. The identification of source and sink transmission chains at national and international scales can identify main hubs and pathways to target future interventions. In this study we investigated the RS state role in the national and international SARS-CoV-2 transmission chains, which has not been fully explored. Nasopharyngeal samples from various municipalities in RS were collected between June 2020 and July 2022. SARS-CoV-2 whole genome amplification and sequencing were performed using high-throughput Illumina sequencing. Bioinformatics analysis encompassed the development of scripts and tools to perform subsampling taking into account epidemiological information to reduce sequencing disparities bias among the regions/countries, genome assembly, and large-scale alignment and phylogenetic reconstruction. We sequenced a total of 1,480 SARS-CoV-2 genomes from RS, covering all major regions. Sequences predominantly represented Gamma (April-June 2021) and Omicron (January-July 2022) lineages. Phylogenetic analysis revealed a regional pattern for transmission dynamics, particularly with Southeast Brazil for Gamma, and a range of inter-regional connections for Delta and Omicron within the country. On the other hand, international and cross-border transmission with Argentina and Uruguay was rather limited. We evaluated the three VOCs circulation over two years in RS using a new subsampling strategy based on the number of cases in each state during the circulation of each VOC. In summary, the retrospective analysis of genomic surveillance data demonstrated that virus transmission was less intense between country borders than within the country. These findings suggest that while non-pharmacological interventions were effective to mitigate transmission across international RS land borders, they were insufficient to contain transmission at the domestic level.

Comprehensive detection and dissection of interlineage recombination events in the SARS-CoV-2 pandemic

The global prevalence of the XBB lineage presents a formidable challenge posed by the recombinant SARS-CoV-2 virus. The understanding of SARS-CoV-2's recombination preference assumes utmost significance in predicting future recombinant variants and adequately preparing for subsequent pandemics. Thus, an urgent need arises to establish a comprehensive landscape concerning SARS-CoV-2 recombinants worldwide and elucidate their evolutionary mechanisms. However, the initial step, involving the detection of potential recombinants from a vast pool of over 10 million sequences, presents a significant obstacle. In this study, we present CovRecomb, a lightweight methodology specifically designed to effectively identify and dissect interlineage SARS-CoV-2 recombinants. Leveraging CovRecomb, we successfully detected 135,567 putative recombinants across the entirety of 14.5 million accessed SARS-CoV-2 genomes. These putative recombinants could be classified into 1451 distinct recombination events, of which 206 demonstrated transmission spanning multiple countries, continents, or globally. Hotspot regions were identified in six specific areas, with prominence observed in the latter halves of the N-terminal domain and receptor-binding domain within the spike (S) gene. Epidemiological investigations revealed extensive recombination events occurring among different SARS-CoV-2 (sub)lineages, independent of lineage prevalence frequencies.

Subsequent Waves of Convergent Evolution in SARS-CoV-2 Genes and Proteins

Beginning in 2022, following widespread infection and vaccination among the global population, the SARS-CoV-2 virus mainly evolved to evade immunity derived from vaccines and past infections. This review covers the convergent evolution of structural, nonstructural, and accessory proteins in SARS-CoV-2, with a specific look at common mutations found in long-lasting infections that hint at the virus potentially reverting to an enteric sarbecovirus type.

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity, which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic 'novel' lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1 % frequency, results were more reliable above a 5 % threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of error or bias in wastewater sequencing analysis and to appreciate the commonalities and differences across methods.

A framework for automated scalable designation of viral pathogen lineages from genomic data

Pathogen lineage nomenclature systems are a key component of effective communication and collaboration for researchers and public health workers. Since February 2021, the Pango dynamic lineage nomenclature for SARS-CoV-2 has been sustained by crowdsourced lineage proposals as new isolates were sequenced. This approach is vulnerable to time-critical delays as well as regional and personal bias. Here we developed a simple heuristic approach for dividing phylogenetic trees into lineages, including the prioritization of key mutations or genes. Our implementation is efficient on extremely large phylogenetic trees consisting of millions of sequences and produces similar results to existing manually curated lineage designations when applied to SARS-CoV-2 and other viruses including chikungunya virus, Venezuelan equine encephalitis virus complex and Zika virus. This method offers a simple, automated and consistent approach to pathogen nomenclature that can assist researchers in developing and maintaining phylogeny-based classifications in the face of ever-increasing genomic datasets.

RCoV19: A One-stop Hub for SARS-CoV-2 Genome Data Integration, Variant Monitoring, and Risk Pre-warning

The Resource for Coronavirus 2019 (RCoV19) is an open-access information resource dedicated to providing valuable data on the genomes, mutations, and variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this updated implementation of RCoV19, we have made significant improvements and advancements over the previous version. Firstly, we have implemented a highly refined genome data curation model. This model now features an automated integration pipeline and optimized curation rules, enabling efficient daily updates of data in RCoV19. Secondly, we have developed a global and regional lineage evolution monitoring platform, alongside an outbreak risk pre-warning system. These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns, enabling better preparedness and response strategies. Thirdly, we have developed a powerful interactive mutation spectrum comparison module. This module allows users to compare and analyze mutation patterns, assisting in the detection of potential new lineages. Furthermore, we have incorporated a comprehensive knowledgebase on mutation effects. This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations. In summary, RCoV19 serves as a vital scientific resource, providing access to valuable data, relevant information, and technical support in the global fight against COVID-19. The complete contents of RCoV19 are available to the public at https://ngdc.cncb.ac.cn/ncov/.