A molnupiravir-associated mutational signature in global SARS-CoV-2 genomes.

Molnupiravir, an antiviral medication widely used against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), acts by inducing mutations in the virus genome during replication. Most random mutations are likely to be deleterious to the virus and many will be lethal; thus, molnupiravir-induced elevated mutation rates reduce viral load1,2. However, if some patients treated with molnupiravir do not fully clear the SARS-CoV-2 infections, there could be the potential for onward transmission of molnupiravir-mutated viruses. Here we show that SARS-CoV-2 sequencing databases contain extensive evidence of molnupiravir mutagenesis. Using a systematic approach, we find that a specific class of long phylogenetic branches, distinguished by a high proportion of G-to-A and C-to-T mutations, are found almost exclusively in sequences from 2022, after the introduction of molnupiravir treatment, and in countries and age groups with widespread use of the drug. We identify a mutational spectrum, with preferred nucleotide contexts, from viruses in patients known to have been treated with molnupiravir and show that its signature matches that seen in these long branches, in some cases with onward transmission of molnupiravir-derived lineages. Finally, we analyse treatment records to confirm a direct association between these high G-to-A branches and the use of molnupiravir.

Context-specific emergence and growth of the SARS-CoV-2 Delta variant.

The SARS-CoV-2 Delta (Pango lineage B.1.617.2) variant of concern spread globally, causing resurgences of COVID-19 worldwide1,2. The emergence of the Delta variant in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 SARS-CoV-2 genomes from England together with 93,649 genomes from the rest of the world to reconstruct the emergence of Delta and quantify its introduction to and regional dissemination across England in the context of changing travel and social restrictions. Using analysis of human movement, contact tracing and virus genomic data, we find that the geographic focus of the expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced more than 1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers reduced onward transmission from importations; however, the transmission chains that later dominated the Delta wave in England were seeded before travel restrictions were introduced. Increasing inter-regional travel within England drove the nationwide dissemination of Delta, with some cities receiving more than 2,000 observable lineage introductions from elsewhere. Subsequently, increased levels of local population mixing-and not the number of importations-were associated with the faster relative spread of Delta. The invasion dynamics of Delta depended on spatial heterogeneity in contact patterns, and our findings will inform optimal spatial interventions to reduce the transmission of current and future variants of concern, such as Omicron (Pango lineage B.1.1.529).

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.

Positive selection in dNTPase SAMHD1 throughout mammalian evolution.

The vertebrate protein SAMHD1 is highly unusual in having roles in cellular metabolic regulation, antiviral restriction, and regulation of innate immunity. Its deoxynucleoside triphosphohydrolase activity regulates cellular dNTP concentration, reducing levels below those required by lentiviruses and other viruses to replicate. To counter this threat, some primate lentiviruses encode accessory proteins that bind SAMHD1 and induce its degradation; in turn, positive diversifying selection has been observed in regions bound by these lentiviral proteins, suggesting that primate SAMHD1 has coevolved to evade these countermeasures. Moreover, deleterious polymorphisms in human SAMHD1 are associated with autoimmune disease linked to uncontrolled DNA synthesis of endogenous retroelements. Little is known about how evolutionary pressures affect these different SAMHD1 functions. Here, we examine the deeper history of these interactions by testing whether evolutionary signatures in SAMHD1 extend to other mammalian groups and exploring the molecular basis of this coevolution. Using codon-based likelihood models, we find positive selection in SAMHD1 within each mammal lineage for which sequence data are available. We observe positive selection at sites clustered around T592, a residue that is phosphorylated to regulate SAMHD1 activity. We verify experimentally that mutations within this cluster affect catalytic rate and lentiviral restriction, suggesting that virus-host coevolution has required adaptations of enzymatic function. Thus, persistent positive selection may have involved the adaptation of SAMHD1 regulation to balance antiviral, metabolic, and innate immunity functions.

Deep sequencing reveals persistence of cell-associated mumps vaccine virus in chronic encephalitis.

Routine childhood vaccination against measles, mumps and rubella has virtually abolished virus-related morbidity and mortality. Notwithstanding this, we describe here devastating neurological complications associated with the detection of live-attenuated mumps virus Jeryl Lynn (MuVJL5) in the brain of a child who had undergone successful allogeneic transplantation for severe combined immunodeficiency (SCID). This is the first confirmed report of MuVJL5 associated with chronic encephalitis and highlights the need to exclude immunodeficient individuals from immunisation with live-attenuated vaccines. The diagnosis was only possible by deep sequencing of the brain biopsy. Sequence comparison of the vaccine batch to the MuVJL5 isolated from brain identified biased hypermutation, particularly in the matrix gene, similar to those found in measles from cases of SSPE. The findings provide unique insights into the pathogenesis of paramyxovirus brain infections.

Norovirus Whole-Genome Sequencing by SureSelect Target Enrichment: a Robust and Sensitive Method.

Norovirus full-genome sequencing is challenging due to sequence heterogeneity among genomes. Previous methods have relied on PCR amplification, which is problematic due to primer design, and transcriptome sequencing (RNA-Seq), which nonspecifically sequences all RNA, including host and bacterial RNA, in stool specimens. Target enrichment uses a panel of custom-designed 120-mer RNA baits that are complementary to all publicly available norovirus sequences, with multiple baits targeting each position of the genome, which overcomes the challenge of primer design. Norovirus genomes are enriched from stool RNA extracts to minimize the sequencing of nontarget RNA. SureSelect target enrichment and Illumina sequencing were used to sequence full genomes from 507 norovirus-positive stool samples with reverse transcription-real-time PCR cycle threshold (CT) values of 10 to 43. Sequencing on an Illumina MiSeq system in batches of 48 generated, on average, 81% on-target reads per sample and 100% genome coverage with >12,000-fold read depth. Samples included genotypes GI.1, GI.2, GI.3, GI.6, GI.7, GII.1, GII.2, GII.3, GII.4, GII.5, GII.6, GII.7, GII.13, GII.14, and GII.17. When outliers were accounted for, we generated >80% genome coverage for all positive samples, regardless of CT values. A total of 164 samples were tested in parallel with conventional PCR genotyping of the capsid shell domain; 164/164 samples were successfully sequenced, compared to 158/164 samples that were amplified by PCR. Four of the samples that failed capsid PCR analysis had low titers, which suggests that target enrichment is more sensitive than gel-based PCR. Two samples failed PCR due to primer mismatches; target enrichment uses multiple baits targeting each position, thus accommodating sequence heterogeneity among norovirus genomes.

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.

Global genomic surveillance of monkeypox virus.

Monkeypox virus (MPXV) is endemic in Western and Central Africa and, in May 2022, a clade IIb lineage (B.1) caused a global outbreak outside Africa, resulting in its detection in 116 countries/territories. To understand the global phylogenetics of MPXV, we analysed all available MPXV sequences, including 10,670 sequences from 65 countries collected between 1958 and 2024. Our analysis reveals high mobility of clade I viruses within Central Africa, sustained human-to-human transmission of clade IIb lineage A viruses within the Eastern Mediterranean region, and distinct mutational signatures that can distinguish sustained human-to-human from animal-to-animal transmission. Moreover, distinct clade I sequences from Sudan suggest local MPXV circulation in areas of Eastern Africa over the past four decades. Our study underscores the importance of genomic surveillance in tracking spatiotemporal dynamics of MXPV clades and the need to strengthen such surveillance, including in some parts of Eastern Africa.

Evolution and host-specific adaptation of Pseudomonas aeruginosa.

The major human bacterial pathogen Pseudomonas aeruginosa causes multidrug-resistant infections in people with underlying immunodeficiencies or structural lung diseases such as cystic fibrosis (CF). We show that a few environmental isolates, driven by horizontal gene acquisition, have become dominant epidemic clones that have sequentially emerged and spread through global transmission networks over the past 200 years. These clones demonstrate varying intrinsic propensities for infecting CF or non-CF individuals (linked to specific transcriptional changes enabling survival within macrophages); have undergone multiple rounds of convergent, host-specific adaptation; and have eventually lost their ability to transmit between different patient groups. Our findings thus explain the pathogenic evolution of P. aeruginosa and highlight the importance of global surveillance and cross-infection prevention in averting the emergence of future epidemic clones.

Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny.

The SARS-CoV-2 genome occupies a unique place in infection biology - it is the most highly sequenced genome on earth (making up over 20% of public sequencing datasets) with fine scale information on sampling date and geography, and has been subject to unprecedented intense analysis. As a result, these phylogenetic data are an incredibly valuable resource for science and public health. However, the vast majority of the data was sequenced by tiling amplicons across the full genome, with amplicon schemes that changed over the pandemic as mutations in the viral genome interacted with primer binding sites. In combination with the disparate set of genome assembly workflows and lack of consistent quality control (QC) processes, the current genomes have many systematic errors that have evolved with the virus and amplicon schemes. These errors have significant impacts on the phylogeny, and therefore over the last few years, many thousands of hours of researchers time has been spent in "eyeballing" trees, looking for artefacts, and then patching the tree. Given the huge value of this dataset, we therefore set out to reprocess the complete set of public raw sequence data in a rigorous amplicon-aware manner, and build a cleaner phylogeny. Here we provide a global tree of 3,960,704 samples, built from a consistently assembled set of high quality consensus sequences from all available public data as of March 2023, viewable at https://viridian.taxonium.org. Each genome was constructed using a novel assembly tool called Viridian (https://github.com/iqbal-lab-org/viridian), developed specifically to process amplicon sequence data, eliminating artefactual errors and mask the genome at low quality positions. We provide simulation and empirical validation of the methodology, and quantify the improvement in the phylogeny. Phase 2 of our project will address the fact that the data in the public archives is heavily geographically biased towards the Global North. We therefore have contributed new raw data to ENA/SRA from many countries including Ghana, Thailand, Laos, Sri Lanka, India, Argentina and Singapore. We will incorporate these, along with all public raw data submitted between March 2023 and the current day, into an updated set of assemblies, and phylogeny. We hope the tree, consensus sequences and Viridian will be a valuable resource for researchers.

Impact of transient acquired hypermutability on the inter- and intra-species competitiveness of Pseudomonas aeruginosa.

Once acquired, hypermutation is unrelenting, and in the long-term, leads to impaired fitness due to its cumulative impact on the genome. This raises the question of why hypermutators arise so frequently in microbial ecosystems. In this work, we explore this problem by examining how the transient acquisition of hypermutability affects inter- and intra-species competitiveness, and the response to environmental insults such as antibiotic challenge. We do this by engineering Pseudomonas aeruginosa to allow the expression of an important mismatch repair gene, mutS, to be experimentally controlled over a wide dynamic range. We show that high levels of mutS expression induce genomic stasis (hypomutation), whereas lower levels of induction lead to progressively higher rates of mutation. Whole-genome sequence analyses confirmed that the mutational spectrum of the inducible hypermutator is similar to the distinctive profile associated with mutS mutants obtained from the airways of people with cystic fibrosis (CF). The acquisition of hypermutability conferred a distinct temporal fitness advantage over the wild-type P. aeruginosa progenitor strain, in both the presence and the absence of an antibiotic selection pressure. However, over a similar time-scale, acquisition of hypermutability had little impact on the population dynamics of P. aeruginosa when grown in the presence of a competing species (Staphylococcus aureus). These data indicate that in the short term, acquired hypermutability primarily confers a competitive intra-species fitness advantage.

SARS-CoV-2 evolution in the Omicron era.

Since SARS-CoV-2 BA.5 (Omicron) emerged and spread in 2022, Omicron lineages have markedly diversified. Here we review the evolutionary trajectories and processes that underpin the emergence of these lineages, and identify the most prevalent sublineages. We discuss the potential origins of second-generation BA.2 lineages. Simple and complex recombination, antigenic drift and convergent evolution have enabled SARS-CoV-2 to accumulate mutations that alter its antigenicity. We also discuss the potential evolutionary trajectories of SARS-CoV-2 in the future.

Mutational spectra are associated with bacterial niche.

As observed in cancers, individual mutagens and defects in DNA repair create distinctive mutational signatures that combine to form context-specific spectra within cells. We reasoned that similar processes must occur in bacterial lineages, potentially allowing decomposition analysis to detect both disruption of DNA repair processes and exposure to niche-specific mutagens. Here we reconstruct mutational spectra for 84 clades from 31 diverse bacterial species and find distinct mutational patterns. We extract signatures driven by specific DNA repair defects using hypermutator lineages, and further deconvolute the spectra into multiple signatures operating within different clades. We show that these signatures are explained by both bacterial phylogeny and replication niche. By comparing mutational spectra of clades from different environmental and biological locations, we identify niche-associated mutational signatures, and then employ these signatures to infer the predominant replication niches for several clades where this was previously obscure. Our results show that mutational spectra may be associated with sites of bacterial replication when mutagen exposures differ, and can be used in these cases to infer transmission routes for established and emergent human bacterial pathogens.

A lung-specific mutational signature enables inference of viral and bacterial respiratory niche.

Exposure to different mutagens leaves distinct mutational patterns that can allow inference of pathogen replication niches. We therefore investigated whether SARS-CoV-2 mutational spectra might show lineage-specific differences, dependent on the dominant site(s) of replication and onwards transmission, and could therefore rapidly infer virulence of emergent variants of concern (VOCs). Through mutational spectrum analysis, we found a significant reduction in G>T mutations in the Omicron variant, which replicates in the upper respiratory tract (URT), compared to other lineages, which replicate in both the URT and lower respiratory tract (LRT). Mutational analysis of other viruses and bacteria indicates a robust, generalizable association of high G>T mutations with replication within the LRT. Monitoring G>T mutation rates over time, we found early separation of Omicron from Beta, Gamma and Delta, while mutational patterns in Alpha varied consistent with changes in transmission source as social restrictions were lifted. Mutational spectra may be a powerful tool to infer niches of established and emergent pathogens.

Emergence and widespread circulation of a recombinant SARS-CoV-2 lineage in North America.

Although recombination is a feature of coronavirus evolution, previously detected recombinant lineages of SARS-CoV-2 have shown limited circulation thus far. Here, we present a detailed phylogenetic analysis of four SARS-CoV-2 lineages to investigate the possibility of virus recombination among them. Our analyses reveal well-supported phylogenetic differences between the Orf1ab region encoding viral non-structural proteins and the rest of the genome, including Spike (S) protein and remaining reading frames. By accounting for several deletions in NSP6, Orf3a, and S, we conclude that the B.1.628 major cluster, now designated as lineage XB, originated from a recombination event between viruses of B.1.631 and B.1.634 lineages. This scenario is supported by the spatiotemporal distribution of these lineages across the USA and Mexico during 2021, suggesting that the recombination event originated in this geographical region. This event raises important questions regarding the role and potential effects of recombination on SARS-CoV-2 evolution.

Emergence of SARS-CoV-2 Omicron lineages BA.4 and BA.5 in South Africa.

Three lineages (BA.1, BA.2 and BA.3) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant of concern predominantly drove South Africa's fourth Coronavirus Disease 2019 (COVID-19) wave. We have now identified two new lineages, BA.4 and BA.5, responsible for a fifth wave of infections. The spike proteins of BA.4 and BA.5 are identical, and similar to BA.2 except for the addition of 69-70 deletion (present in the Alpha variant and the BA.1 lineage), L452R (present in the Delta variant), F486V and the wild-type amino acid at Q493. The two lineages differ only outside of the spike region. The 69-70 deletion in spike allows these lineages to be identified by the proxy marker of S-gene target failure, on the background of variants not possessing this feature. BA.4 and BA.5 have rapidly replaced BA.2, reaching more than 50% of sequenced cases in South Africa by the first week of April 2022. Using a multinomial logistic regression model, we estimated growth advantages for BA.4 and BA.5 of 0.08 (95% confidence interval (CI): 0.08-0.09) and 0.10 (95% CI: 0.09-0.11) per day, respectively, over BA.2 in South Africa. The continued discovery of genetically diverse Omicron lineages points to the hypothesis that a discrete reservoir, such as human chronic infections and/or animal hosts, is potentially contributing to further evolution and dispersal of the virus.

Progress and challenges in virus genomic epidemiology.

Genomic epidemiology, which links pathogen genomes with associated metadata to understand disease transmission, has become a key component of outbreak response. Decreasing costs of genome sequencing and increasing computational power provide opportunities to generate and analyse large viral genomic datasets that aim to uncover the spatial scales of transmission, the demographics contributing to transmission patterns, and to forecast epidemic trends. Emerging sources of genomic data and associated metadata provide new opportunities to further unravel transmission patterns. Key challenges include how to integrate genomic data with metadata from multiple sources, how to generate efficient computational algorithms to cope with large datasets, and how to establish sampling frameworks to enable robust conclusions.