ABSTRACT
A globally implemented unified classification for human respiratory syncytial virus (HRSV) below the subgroup level remains elusive. Here, we formulate the global consensus of HRSV classification based on the challenges and limitations of our previous proposals and the future of genomic surveillance. From a high-quality dataset of 1,480 HRSV-A and 1,385 HRSV-B genomes submitted to NCBI and GISAID up to March 2023, we categorized HRSV-A/B sequences into lineages based on phylogenetic clades and amino acid markers. We defined 24 lineages within HRSV-A and 16 within HRSV-B, providing guidelines for prospective lineages definition. Our classification demonstrated robustness in its applicability to both complete and partial genomes. In addition, it allowed the observation of notable lineage replacements and the identification of lineages exclusively detected since the COVID-19 pandemic. We envision that this unified HRSV classification proposal will strengthen and facilitate HRSV molecular epidemiology on a global scale.
Subject(s)
COVID-19 , Respiratory Syncytial Virus InfectionsABSTRACT
We report the genomic analysis of a highly divergent SARS-CoV-2 sample obtained in October 2022 from an HIV+ patient with presumably long-term COVID-19 infection. Phylogenetic analysis indicates that the sample is characterized by a gain of 89 mutations since divergence from its nearest sequenced neighbor, which had been collected in September 2020 and belongs to the B.1.1 lineage, largely extinct in 2022. 33 of these mutations were coding and occurred in the Spike protein. Of these, 17 are lineage-defining in some of the variants of concern (VOCs) or are in sites where another mutation is lineage-defining in a variant of concern, and/or shown to be involved in antibody evasion, and/or detected in other cases of persistent COVID-19; these include some "usual suspects," such as Spike:L452R, E484Q, K417T, Y453F, and N460K. Molecular clock analysis indicates that mutations in this lineage accumulated at an increased rate compared to the ancestral B.1.1 strain. This increase is driven by the accumulation of nonsynonymous mutations, for an average dN/dS value of 2.2, indicating strong positive selection during within-patient evolution. Additionally, there is reason to believe that the virus had persisted for at least some time in the gastrointestinal tract, as evidenced by the presence of mutations that are rare in the general population samples but common in samples from wastewater. Our analysis adds to the growing body of research on evolution of SARS-CoV-2 in chronically infected patients and its relationship to the emergence of variants of concern.
Subject(s)
COVID-19ABSTRACT
Pathogen nomenclature systems are a key component of effective communication and collaboration for researchers and public health workers. Since February 2021, the Pango nomenclature for SARS-CoV-2 has been sustained by crowdsourced lineage proposals as new isolates were added to a growing global dataset. This approach to dynamic lineage designation is dependent on a large and active epidemiological community identifying and curating each new lineage. This is vulnerable to time-critical delays as well as regional and personal bias. To address these issues, we developed a simple heuristic approach that divides a phylogenetic tree into lineages based on shared ancestral genotypes. We additionally provide a framework that automatically prioritizes the lineages by growth rate and association with key mutations or locations, extensible to any pathogen. Our implementation is efficient on extremely large phylogenetic trees and produces similar results to existing Pango lineage designations when applied to SARS-CoV-2. 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.
ABSTRACT
South Africa's fourth COVID-19 wave was driven predominantly by three lineages (BA.1, BA.2 and BA.3) of the SARS-CoV-2 Omicron variant of concern. We have now identified two new lineages, BA.4 and BA.5. The spike proteins of BA.4 and BA.5 are identical, and comparable to BA.2 except for the addition of 69-70del, L452R, F486V and the wild type amino acid at Q493. The 69-70 deletion in spike allows these lineages to be identified by the proxy marker of S-gene target failure with the TaqPath COVID-19 qPCR assay. BA.4 and BA.5 have rapidly replaced BA.2, reaching more than 50% of sequenced cases in South Africa from the first week of April 2022 onwards. Using a multinomial logistic regression model, we estimate growth advantages for BA.4 and BA.5 of 0.08 (95% CI: 0.07 - 0.09) and 0.12 (95% CI: 0.09 - 0.15) per day respectively over BA.2 in South Africa.