Standardized Phylogenetic Classification of Human Respiratory Syncytial Virus below the Subgroup Level.

A globally implemented unified phylogenetic classification for human respiratory syncytial virus (HRSV) below the subgroup level remains elusive. We formulated global consensus of HRSV classification on the basis of the challenges and limitations of our previous proposals and the future of genomic surveillance. From a high-quality curated dataset of 1,480 HRSV-A and 1,385 HRSV-B genomes submitted to GenBank and GISAID (https://www.gisaid.org) public sequence databases through 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 and provided guidelines for defining prospective lineages. Our classification demonstrated robustness in its applicability to both complete and partial genomes. We envision that this unified HRSV classification proposal will strengthen HRSV molecular epidemiology on a global scale.

How much should we sequence? An analysis of the Swiss SARS-CoV-2 surveillance effort.

During the SARS-CoV-2 pandemic, many countries directed substantial resources toward genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats. We aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic data set from Switzerland, comprising more than 143k sequences. We employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters. The impact of downsampling on VOC detection is disparate for the three VOC lineages, but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively. A genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage-dependent-something that is unknown at the time of sequencing-and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.IMPORTANCESwitzerland had one of the most comprehensive genomic surveillance systems during the COVID-19 pandemic. Such programs need to strike a balance between societal benefits and program costs. Our study aims to answer the question: How would surveillance outcomes have changed had we sequenced less? We find that some outcomes but also certain viral lineages are more affected than others by sequencing less. However, sequencing to around a third of the original effort still captured many important outcomes for the variants of concern such as their first detection but affected more strongly other measures like the detection of first transmission clusters for some lineages. Our work highlights the importance of setting predefined targets for a national genomic surveillance program based on which sequencing effort should be determined. Additionally, the use of a centralized surveillance platform facilitates aggregating data on a national level for rapid public health responses as well as post-analyses.

SARS-CoV-2 infection in immunosuppression evolves sub-lineages which independently accumulate neutralization escape mutations.

One mechanism of variant formation may be evolution during long-term infection in immunosuppressed people. To understand the viral phenotypes evolved during such infection, we tested SARS-CoV-2 viruses evolved from an ancestral B.1 lineage infection lasting over 190 days post-diagnosis in an advanced HIV disease immunosuppressed individual. Sequence and phylogenetic analysis showed two evolving sub-lineages, with the second sub-lineage replacing the first sub-lineage in a seeming evolutionary sweep. Each sub-lineage independently evolved escape from neutralizing antibodies. The most evolved virus for the first sub-lineage (isolated day 34) and the second sub-lineage (isolated day 190) showed similar escape from ancestral SARS-CoV-2 and Delta-variant infection elicited neutralizing immunity despite having no spike mutations in common relative to the B.1 lineage. The day 190 isolate also evolved higher cell-cell fusion and faster viral replication and caused more cell death relative to virus isolated soon after diagnosis, though cell death was similar to day 34 first sub-lineage virus. These data show that SARS-CoV-2 strains in prolonged infection in a single individual can follow independent evolutionary trajectories which lead to neutralization escape and other changes in viral properties.

Evolution and neutralization escape of the SARS-CoV-2 BA.2.86 subvariant.

Omicron BA.2.86 subvariant differs from Omicron BA.2 as well as recently circulating variants by over 30 mutations in the spike protein alone. Here we report on the isolation of the live BA.2.86 subvariant from a diagnostic swab collected in South Africa which we tested for escape from neutralizing antibodies and viral replication properties in cell culture. We found that BA.2.86 does not have significantly more escape relative to Omicron XBB.1.5 from neutralizing immunity elicited by either Omicron XBB-family subvariant infection or from residual neutralizing immunity of recently collected sera from the South African population. BA.2.86 does have extensive escape relative to ancestral virus with the D614G substitution (B.1 lineage) when neutralized by sera from pre-Omicron vaccinated individuals and relative to Omicron BA.1 when neutralized by sera from Omicron BA.1 infected individuals. BA.2.86 and XBB.1.5 show similar viral infection dynamics in the VeroE6-TMPRSS2 and H1299-ACE2 cell lines. We also investigate the relationship of BA.2.86 to BA.2 sequences. The closest BA.2 sequences are BA.2 samples from Southern Africa circulating in early 2022. Similarly, many basal BA.2.86 sequences were sampled in Southern Africa. This suggests that BA.2.86 potentially evolved in this region, and that unobserved evolution led to escape from neutralizing antibodies similar in scale to recently circulating strains of SARS-CoV-2.

Visualizing and quantifying structural diversity around mobile resistance genes.

Understanding the evolution of mobile genes is important for understanding the spread of antimicrobial resistance (AMR). Many clinically important AMR genes have been mobilized by mobile genetic elements (MGEs) on the kilobase scale, such as integrons and transposons, which can integrate into both chromosomes and plasmids and lead to rapid spread of the gene through bacterial populations. Looking at the flanking regions of these mobile genes in diverse genomes can highlight common structures and reveal patterns of MGE spread. However, historically this has been a largely descriptive process, relying on gene annotation and expert knowledge. Here we describe a general method to visualize and quantify the structural diversity around genes using pangraph to find blocks of homologous sequence. We apply this method to a set of 12 clinically important beta-lactamase genes and provide interactive visualizations of their flanking regions at https://liampshaw.github.io/flanking-regions. We show that nucleotide-level variation in the mobile gene itself generally correlates with increased structural diversity in its flanking regions, demonstrating a relationship between rates of mutational evolution and rates of structural evolution, and find a bias for greater structural diversity upstream. Our framework is a starting point to investigate general rules that apply to the horizontal spread of new genes through bacterial populations.

APOBEC3 deaminase editing in mpox virus as evidence for sustained human transmission since at least 2016.

Historically, mpox has been characterized as an endemic zoonotic disease that transmits through contact with the reservoir rodent host in West and Central Africa. However, in May 2022, human cases of mpox were detected spreading internationally beyond countries with known endemic reservoirs. When the first cases from 2022 were sequenced, they shared 42 nucleotide differences from the closest mpox virus (MPXV) previously sampled. Nearly all these mutations are characteristic of the action of APOBEC3 deaminases, host enzymes with antiviral function. Assuming APOBEC3 editing is characteristic of human MPXV infection, we developed a dual-process phylogenetic molecular clock that-inferring a rate of ~6 APOBEC3 mutations per year-estimates that MPXV has been circulating in humans since 2016. These observations of sustained MPXV transmission present a fundamental shift to the perceived paradigm of MPXV epidemiology as a zoonosis and highlight the need for revising public health messaging around MPXV as well as outbreak management and control.

Fitness effects of mutations to SARS-CoV-2 proteins.

Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here, we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.

Viral genetic clustering and transmission dynamics of the 2022 mpox outbreak in Portugal.

Pathogen genome sequencing during epidemics enhances our ability to identify and understand suspected clusters and investigate their relationships. Here, we combine genomic and epidemiological data of the 2022 mpox outbreak to better understand early viral spread, diversification and transmission dynamics. By sequencing 52% of the confirmed cases in Portugal, we identified the mpox virus sublineages with the highest impact on case numbers and fitted them into a global context, finding evidence that several international sublineages probably emerged or spread early in Portugal. We estimated a 62% infection reporting rate and that 1.3% of the population of men who have sex with men in Portugal were infected. We infer the critical role played by sexual networks and superspreader gatherings, such as sauna attendance, in the dissemination of mpox virus. Overall, our findings highlight genomic epidemiology as a tool for the real-time monitoring and control of mpox epidemics, and can guide future vaccine policy in a highly susceptible population.

Recommendations on data sharing in HIV drug resistance research.

• Human immunodeficiency virus (HIV) drug resistance has implications for antiretroviral treatment strategies and for containing the HIV pandemic because the development of HIV drug resistance leads to the requirement for antiretroviral drugs that may be less effective, less well-tolerated, and more expensive than those used in first-line regimens. • HIV drug resistance studies are designed to determine which HIV mutations are selected by antiretroviral drugs and, in turn, how these mutations affect antiretroviral drug susceptibility and response to future antiretroviral treatment regimens. • Such studies collectively form a vital knowledge base essential for monitoring global HIV drug resistance trends, interpreting HIV genotypic tests, and updating HIV treatment guidelines. • Although HIV drug resistance data are collected in many studies, such data are often not publicly shared, prompting the need to recommend best practices to encourage and standardize HIV drug resistance data sharing. • In contrast to other viruses, sharing HIV sequences from phylogenetic studies of transmission dynamics requires additional precautions as HIV transmission is criminalized in many countries and regions. • Our recommendations are designed to ensure that the data that contribute to HIV drug resistance knowledge will be available without undue hardship to those publishing HIV drug resistance studies and without risk to people living with HIV.

PanGraph: scalable bacterial pan-genome graph construction.

The genomic diversity of microbes is commonly parameterized as SNPs relative to a reference genome of a well-characterized, but arbitrary, isolate. However, any reference genome contains only a fraction of the microbial pangenome, the total set of genes observed in a given species. Reference-based approaches are thus blind to the dynamics of the accessory genome, as well as variation within gene order and copy number. With the widespread usage of long-read sequencing, the number of high-quality, complete genome assemblies has increased dramatically. In addition to pangenomic approaches that focus on the variation in the sets of genes present in different genomes, complete assemblies allow investigations of the evolution of genome structure and gene order. This latter problem, however, is computationally demanding with few tools available that shed light on these dynamics. Here, we present PanGraph, a Julia-based library and command line interface for aligning whole genomes into a graph. Each genome is represented as a path along vertices, which in turn encapsulate homologous multiple sequence alignments. The resultant data structure succinctly summarizes population-level nucleotide and structural polymorphisms and can be exported into several common formats for either downstream analysis or immediate visualization.

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.

Evolution of the SARS-CoV-2 Mutational Spectrum.

SARS-CoV-2 evolves rapidly in part because of its high mutation rate. Here, we examine whether this mutational process itself has changed during viral evolution. To do this, we quantify the relative rates of different types of single-nucleotide mutations at 4-fold degenerate sites in the viral genome across millions of human SARS-CoV-2 sequences. We find clear shifts in the relative rates of several types of mutations during SARS-CoV-2 evolution. The most striking trend is a roughly 2-fold decrease in the relative rate of G→T mutations in Omicron versus early clades, as was recently noted by Ruis et al. (2022. Mutational spectra distinguish SARS-CoV-2 replication niches. bioRxiv, doi:10.1101/2022.09.27.509649). There is also a decrease in the relative rate of C→T mutations in Delta, and other subtle changes in the mutation spectrum along the phylogeny. We speculate that these changes in the mutation spectrum could arise from viral mutations that affect genome replication, packaging, and antagonization of host innate-immune factors, although environmental factors could also play a role. Interestingly, the mutation spectrum of Omicron is more similar than that of earlier SARS-CoV-2 clades to the spectrum that shaped the long-term evolution of sarbecoviruses. Overall, our work shows that the mutation process is itself a dynamic variable during SARS-CoV-2 evolution and suggests that human SARS-CoV-2 may be trending toward a mutation spectrum more similar to that of other animal sarbecoviruses.

Joint visualization of seasonal influenza serology and phylogeny to inform vaccine composition.

Seasonal influenza vaccines must be updated regularly to account for mutations that allow influenza viruses to escape our existing immunity. A successful vaccine should represent the genetic diversity of recently circulating viruses and induce antibodies that effectively prevent infection by those recent viruses. Thus, linking the genetic composition of circulating viruses and the serological experimental results measuring antibody efficacy is crucial to the vaccine design decision. Historically, genetic and serological data have been presented separately in the form of static visualizations of phylogenetic trees and tabular serological results to identify vaccine candidates. To simplify this decision-making process, we have created an interactive tool for visualizing serological data that has been integrated into Nextstrain's real-time phylogenetic visualization framework, Auspice. We show how the combined interactive visualizations may be used by decision makers to explore the relationships between complex data sets for both prospective vaccine virus selection and retrospectively exploring the performance of vaccine viruses.

A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spike.

A major challenge in understanding SARS-CoV-2 evolution is interpreting the antigenic and functional effects of emerging mutations in the viral spike protein. Here, we describe a deep mutational scanning platform based on non-replicative pseudotyped lentiviruses that directly quantifies how large numbers of spike mutations impact antibody neutralization and pseudovirus infection. We apply this platform to produce libraries of the Omicron BA.1 and Delta spikes. These libraries each contain ∼7,000 distinct amino acid mutations in the context of up to ∼135,000 unique mutation combinations. We use these libraries to map escape mutations from neutralizing antibodies targeting the receptor-binding domain, N-terminal domain, and S2 subunit of spike. Overall, this work establishes a high-throughput and safe approach to measure how ∼105 combinations of mutations affect antibody neutralization and spike-mediated infection. Notably, the platform described here can be extended to the entry proteins of many other viruses.

Fitness effects of mutations to SARS-CoV-2 proteins.

Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino-acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.

Reversions to consensus are positively selected in HIV-1 and bias substitution rate estimates.

Human immunodeficiency virus 1 (HIV-1) is a rapidly evolving virus able to evade host immunity through rapid adaptation during chronic infection. The HIV-1 group M has diversified since its zoonosis into several subtypes at a rate of the order of 10-3 changes per site per year. This rate varies between different parts of the genome, and its inference is sensitive to the timescale and diversity spanned by the sequence data used. Higher rates are estimated on short timescales and particularly for within-host evolution, while rate estimates spanning decades or the entire HIV-1 pandemic tend to be lower. The underlying causes of this difference are not well understood. We investigate here the role of rapid reversions toward a preferred evolutionary sequence state on multiple timescales. We show that within-host reversion mutations are under positive selection and contribute substantially to sequence turnover, especially at conserved sites. We then use the rates of reversions and non-reversions estimated from longitudinal within-host data to parameterize a phylogenetic sequence evolution model. Sequence simulation of this model on HIV-1 phylogenies reproduces diversity and apparent evolutionary rates of HIV-1 in gag and pol, suggesting that a tendency to rapidly revert to a consensus-like state can explain much of the time dependence of evolutionary rate estimates in HIV-1.

Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data.

Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Switzerland in 2020-the sixth largest effort globally. Using a representative subset of these data, we estimated viral introductions to Switzerland and their persistence over the course of 2020. We contrasted these estimates with simple null models representing the absence of certain public health measures. We show that Switzerland's border closures decoupled case introductions from incidence in neighboring countries. Under a simple model, we estimate an 86 to 98% reduction in introductions during Switzerland's strictest border closures. Furthermore, the Swiss 2020 partial lockdown roughly halved the time for sampled introductions to die out. Last, we quantified local transmission dynamics once introductions into Switzerland occurred using a phylodynamic model. We found that transmission slowed 35 to 63% upon outbreak detection in summer 2020 but not in fall. This finding may indicate successful contact tracing over summer before overburdening in fall. The study highlights the added value of genome sequencing data for understanding transmission dynamics.

Evolution of the SARS-CoV-2 mutational spectrum.

SARS-CoV-2 evolves rapidly in part because of its high mutation rate. Here we examine whether this mutational process itself has changed during viral evolution. To do this, we quantify the relative rates of different types of single nucleotide mutations at four-fold degenerate sites in the viral genome across millions of human SARS-CoV-2 sequences. We find clear shifts in the relative rates of several types of mutations during SARS-CoV-2 evolution. The most striking trend is a roughly two-fold decrease in the relative rate of G→T mutations in Omicron versus early clades, as was recently noted by Ruis et al (2022). There is also a decrease in the relative rate of C→T mutations in Delta, and other subtle changes in the mutation spectrum along the phylogeny. We speculate that these changes in the mutation spectrum could arise from viral mutations that affect genome replication, packaging, and antagonization of host innate-immune factors-although environmental factors could also play a role. Interestingly, the mutation spectrum of Omicron is more similar than that of earlier SARS-CoV-2 clades to the spectrum that shaped the long-term evolution of sarbecoviruses. Overall, our work shows that the mutation process is itself a dynamic variable during SARS-CoV-2 evolution, and suggests that human SARS-CoV-2 may be trending towards a mutation spectrum more similar to that of other animal sarbecoviruses.