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Fraser, C.

Publications and source records attributed to Fraser, C..

At least 19 recordsLinked to original sources

A peptide-based screen for cell death inhibitors identifies the cytoprotective compound CDL36

Small molecule inhibitors of cell death have wide-ranging potential applications, both as tool compounds in the laboratory and as clinical modulators of pathologic cell death. Previous screening efforts have identified candidate compounds targeting the pro-apoptotic, pore-forming BCL-2 family proteins BAX and BAK, but the complex interactions of these proteins at the mitochondrial outer membrane (with other proteins and the membrane itself) present challenges for compound screening. Although no inhibitors of BAX or BAK have advanced to clinical testing to date, candidate inhibitors have thus far been identified via screening of membrane-containing systems such as liposomes and isolated mitochondria. To address some of the challenges of chemical screening for apoptosis inhibitors, we conducted a small molecule screen utilizing BH3 profiling, a method that quantifies mitochondrial outer membrane permeabilization (MOMP) upon treatment with pro-apoptotic peptides derived from BCL-2 family proteins. Of over 40,000 compounds screened, we identified a series of compounds that prevent MOMP in response to pro-apoptotic peptides. The most potent of these, CDL36, binds to BAX and prevents MOMP at early timepoints. In longer term viability assays, the cytoprotective effect of CDL36 is most potent against death induced by doxorubicin, a widely used chemotherapeutic agent that causes dose-limiting cardiovascular toxicity. Our results elucidate the mechanism of action of new and existing cell death inhibitors, providing a foundation for further development of these inhibitors and potential insights into the mechanisms mediating doxorubicin toxicity in patients.

molecular biology↗

Quantifying Somatic Mutation Burden: An Assay Validation Framework and Implementation in SomaticCODEC

Validation of somatic mutation burden assays is fundamentally constrained by the absence of a robust ground truth, limiting the interpretability of performance metrics. To address this, we propose a framework based primarily on relative validation, complemented by a suite of secondary metrics aligned to common failure modes. We implement this approach in SomaticCODEC, a ready-to-run assay for quantifying SNV burden in primary human samples, demonstrating strong linearity across mixtures of sperm and blood samples (R2 = 0.91) and high intra-batch precision (CV = 3.3%). This framework provides a practical approach for validating somatic mutation burden assays without requiring a ground truth.

genomics↗

Natural selection driven by escape from shifting antibody classes shapes SARS-CoV-2 evolution

The phenotypic fitness landscape defines the action of natural selection on pathogens, linking changes in their phenotypes to transmission and evolution. The rapidly changing nature of epidemic spread and antigenic landscapes pushes viruses to evolve on fitness seascapes. As a result, evolution of viruses such as SARS-CoV-2 proceeds in a neverending series of waves, driven by epistatic interactions and by the arms race between viral adaptation and human immunity. Phenotypic characterisation of these rapidly changing fitness seascapes is an open challenge. Using a Phenotypic Selection Inference framework that links phylogenetic estimates of mutation fitness effects with deep mutational scanning data, we traced how selective pressures on viral phenotypes have shifted throughout the COVID-19 pandemic. Natural selection has favoured enhanced ACE2 binding since the emergence of SARS-COV-2, with relatively constant selective pressure even for the most recent variants. The strength of selection for antibody escape was comparable to ACE2 binding during early evolution, but as population immunity rose, escape from class 3 and then class 2 antibodies became dominant. For variants circulating in 2024, natural selection shifted toward class 3 antibody escape, while those circulating in 2025 have experienced dynamic, rapidly changing pressures for escape from all antibody classes. These transitions reflect an ongoing arms race between viral adaptation and human immunity. Our findings reveal that SARS-CoV-2 antigenic evolution is governed by dynamic, class-specific immune pressures, and that selection for replication capacity has been continuously present during the pandemic, presumably to compensate for the effects of antigenic escape on viral replication. Our approach for the inference of phenotypic selection provides a framework to understand and anticipate the evolution of future variants.

evolutionary biology↗

Paclitaxel-induced mitotic arrest results in a convergence of apoptotic dependencies that can be safely exploited by BCL-XL degradation to overcome cancer chemoresistance

Paclitaxel and other microtubule-targeting agents are cornerstone therapies for diverse cancers, including lung, breast, cervical, pancreatic, and ovarian malignancies. Paclitaxel induces tumor cell apoptosis during mitosis by disrupting microtubule dynamics required for chromosome segregation. However, despite initial responsiveness, many tumors develop resistance, limiting therapeutic durability. Here, we used high-grade serous ovarian carcinoma (HGSOC), the most common and lethal subtype of ovarian cancer, as a model to dissect the mechanisms underlying this resistance. We find that paclitaxel-induced mitotic arrest triggers degradation of the pro-survival protein MCL-1 and upregulation of BCL-XL, followed by inactivating phosphorylation of BCL-XL at Ser62 to promote apoptosis. In resistant cells, this MCL-1 downregulation is insufficient to commit cells to apoptosis but instead results in a transient convergence of apoptotic dependencies by forcing BCL-XL to sequester the pro-apoptotic proteins BIM, BAX, and BAK. During this state, BCL-XL inhibition induces synergistic apoptosis, even in chemoresistant cells. Surprisingly, we also discover that loss of substrate attachment recapitulates this apoptotic convergence both in vitro and in vivo, with HGSOC cells growing in metastasis-promoting malignant ascites displaying heightened apoptotic priming and dependence on BCL-XL relative to solid tumors. In HGSOC xenografts, targeted degradation of BCL-XL using the platelet-sparing proteolysis-targeting chimera (PROTAC) DT2216 matches the efficacy of paclitaxel monotherapy while avoiding the chronic thrombocytopenia induced by BCL-XL inhibitors such as navitoclax (ABT-263). Strikingly, combination therapy leveraging the synergy between paclitaxel and DT2216 leads to complete eradication of HGSOC cell line and patient-derived xenografts. Moreover, DT2216 treatment blunts the rapid apoptotic adaptation caused by other BCL-XL inhibitors, indicating that targeted degradation of pro-survival proteins may yield more durable responses than inhibition alone. These findings uncover a mechanistic framework for safely exploiting the apoptotic dependency convergence caused by mitotic arrest and substrate detachment and support the clinical development of BCL-XL-targeting PROTACs to overcome chemoresistance in ovarian cancer and other solid tumors.

cancer biology↗

Attenuation of HIV severity by slightly deleterious mutations can explain the long-term trajectory of virulence evolution.

HIV-1 is a well-studied example of a pathogen that has evolved an intermediate level of virulence that maximises transmission. For a trait to evolve it must be heritable, and although viral load--a proxy for disease severity--has been shown to be a heritable trait, it is surprising that specific heritable viral factors remain mostly elusive. Rapid within-host evolution is also expected to diminish heritability. We hypothesised that rather than a small number of mutations of large effect determining viral load, the number of slightly deleterious mutations could be key. As a proof of principle, we explored how viral load is expected to evolve within and between hosts using a nested modelling approach that links within-host evolution with epidemiological outcomes. For mutations of sufficiently small effect, a mutation-selection balance is gradually reached during infection, resulting in slow changes in viral load despite rapid rates of genomic evolution. In simulated epidemics, we generated realistic population distributions of viral loads and estimates of heritability. The existence of many slightly deleterious mutations provides a mechanism that can help to explain why viral loads change slowly during infection, broad distributions of viral loads among individuals, and why searches for viral factors that determine viral load have had limited success.

evolutionary biology↗

A real-time forecasting framework for emerging infectious diseases affecting animal populations

Infectious disease forecasting has become increasingly important in public health, as demonstrated during the COVID-19 pandemic. However, forecasting tools for emergency animal diseases, particularly those offering real-time decision support when parameters governing disease dynamics are unknown, remain limited. We introduce a generalised modelling framework for near-real-time forecasting of the temporal and spatial spread of infectious livestock diseases using data from the early stages of an outbreak. We applied the framework to the 2007 equine influenza outbreak in Australia, generating prediction targets at three timepoints across four regional clusters. Our targets included future daily case counts, outbreak size, peak timing and duration, and spatial distributions of future spread. We evaluated how well the forecasts predicted daily cases and the spatial distribution of case counts, using skill scores as a benchmark for future model improvements. Forecast accuracy, certainty, and skill improved significantly after the outbreaks peak, while early predictions were more variable, suggesting that pre-peak forecasts should be interpreted with caution. Spatial forecasts maintained positive skill throughout the outbreak, supporting their use in guiding response priorities. This framework provides a tool for real-time decision-making during livestock disease outbreaks and establishes a foundation for future refinements and applications to other animal diseases.

bioinformatics↗

Biased estimates of phylogenetic branch lengths resulting from the discretised Gamma model of site rate heterogeneity

A standard method in phylogenetic reconstruction for representing variation in substitution rates between sites in the genome is the discrete Gamma model (DGM). Relative rates are assumed to be distributed according to a discretised Gamma distribution, where the probabilities that a site is included in each class are equal. Here, we identify a serious bias in the branch lengths of reconstructed phylogenies when the DGM is used, with the magnitude of the effect varying with the number of sequences in the alignment. We demonstrate the existence of the bias in both simulated dataset and using real HIV-1 sequences; in both cases branch lengths are overestimated. We show that the alternative "FreeRate" model, which assumes no parametric distribution and allows the class probabilities to vary, is not subject to the issue. We further establish that the reason for the behaviour is the equal class probabilities, not the discretisation itself. We explore the mathematics of for the phenomenon, showing how maximum likelihood branch lengths under the DGM may differ from the true ones used to generate the tree, and that branch lengths will be overestimated where there is a long-tail of fast-evolving sites in the true rate distribution, which is the usual situation in real datasets. We recommend that the DGM be retired from general use. While FreeRate is an immediately available replacement, it is known to be difficult to fit, and thus there is scope for innovation in rate heterogeneity models.

evolutionary biology↗

Synthetic integrin antibodies discovered by yeast display reveal αV subunit pairing preferences with β subunits

Eight of the 24 integrin heterodimers bind to the tripeptide Arg-Gly-Asp (RGD) motif in their extracellular ligands, and play essential roles in cell adhesion, migration, and homeostasis. Despite similarity in recognizing the RGD motif and some redundancy, these integrins can selectively recognize RGD-containing ligands including fibronectin, vitronectin, fibrinogen, nephronectin and the prodomain of the transforming growth factors to fulfill specific functions in cellular processes. Subtype-specific antibodies against RGD-binding integrins are desirable for investigating their specific functions. In this study, we discovered 11 antibodies that exhibit high specificity and affinity towards integrins V{beta}3, V{beta}5, V{beta}6, V{beta}8, and 5{beta}1 from a synthetic yeast-displayed Fab library. Of these, 6 are function-blocking antibodies containing an R(G/L/T) D motif in their CDR3 sequences. We report antibody binding specificity, kinetics, and binding affinity for purified integrin ectodomains as well as intact integrins on the cell surface. We further employed these antibodies to reveal binding preferences of the V subunit for its 5 {beta}-subunit partners: {beta}6={beta}8>{beta}3>{beta}1={beta}5.

cell biology↗

Directional predictions of HIV transmission with optimised genomics in cohorts of serodiscordant couples

Viral genetic information from people living with HIV can deepen our understanding of the infections epidemiology at many scales. To better understand the potentials and limits of tools that utilise such information, we show the performance of two representative tools (HIV-TRACE and phyloscanner) in describing HIV transmission dynamics, with different types of genetic data, and compare with previous findings. The samples were collected from three cohort studies in Sub-Saharan Africa and were deep sequenced to produce both short Illumina reads and long PacBio reads. By comparing phyloscanners performance with short and long reads, we show that long reads provide improved phylogenetic resolution for the classic transmission topology in joint within-host trees. Our pipeline accurately predicted the direction of transmission 88%-92% of the time. We also show that the timing of sample collection plays an important role in the reconstruction of directionality using deep sequencing data. Consensus sequences were also generated and used as HIV-TRACE input to show different patterns of clustering sensitivity and specificity for data from different genomic regions or the entire genome. Finally, we discuss adjusting expectations about sensitivity and specificity of different types of sequence data, considering rapid pathogen evolution, and highlight the potentials of high within-host phylogenetic resolution in HIV. In conclusion, viral genetic data collected and presented differently could greatly influence our ability to describe the underlying dynamics. Methods for source attribution analysis have reached levels of superior accuracy. However, residual uncertainty emphasizes sequence analysis alone cannot conclusively prove linkage at the individual level. ImportanceUnderstanding HIV transmission dynamics is key to designing effective HIV testing and prevention strategies. By using different sequencing techniques on well-characterised cohorts, we were able to evaluate the effect of genetic data resolution on the accuracy of identifying likely transmission pairs and the direction of transmission within pairs. We find that the longer reads generated by PacBio sequencing are more suitable for transmission analyses.

genomics↗

Learning patterns of HIV-1 co-resistance to broadly neutralizing antibodies with reduced subtype bias using multi-task learning

The ability to predict HIV-1 resistance to broadly neutralizing antibodies (bnAbs) will increase bnAb therapeutic benefits. Machine learning is a powerful approach for such prediction. One challenge is that some HIV-1 subtypes in currently available training datasets are underrepresented, which likely affects models generalizability across subtypes. A second challenge is that combinations of bnAbs are required to avoid the inevitable resistance to a single bnAb, and computationally determining optimal combinations of bnAbs is an unsolved problem. Recently, machine learning models trained using resistance outcomes for multiple antibodies at once, a strategy called multi-task learning (MTL), have been shown to achieve better performance in several cases than previous approaches. We develop a new model and show that, beyond the boost in performance, MTL also helps address the previous two challenges. Specifically, we demonstrate empirically that MTL can mitigate bias from underrepresented subtypes, and that MTL allows the model to learn patterns of co-resistance between antibodies, thus providing tools to predict antibodies epitopes and to potentially select optimal bnAb combinations. Our analyses, publicly available at https://github.com/iaime/LBUM, can be adapted to other infectious diseases that are treated with antibody therapy.

bioinformatics↗

Inhibiting Stromal Class I HDACs Curbs Pancreatic Cancer Progression

Oncogenic lesions in pancreatic ductal adenocarcinoma (PDAC) hijack the epigenetic machinery in stromal components to establish a desmoplastic and therapeutic resistant tumor microenvironment (TME). Here we identify Class I histone deacetylases (HDACs) as key epigenetic factors facilitating the induction of pro-desmoplastic and pro-tumorigenic transcriptional programs in pancreatic stromal fibroblasts. Mechanistically, HDAC-mediated changes in chromatin architecture enable the activation of pro-desmoplastic programs directed by serum response factor (SRF) and forkhead box M1 (FOXM1). HDACs also coordinate fibroblast pro-inflammatory programs inducing leukemia inhibitory factor (LIF) expression, supporting paracrine pro-tumorigenic crosstalk. HDAC depletion in cancer-associated fibroblasts (CAFs) and treatment with the HDAC inhibitor entinostat (Ent) in PDAC mouse models reduce stromal activation and curb tumor progression. Notably, HDAC inhibition (HDACi) enriches a lipogenic fibroblast subpopulation, a potential precursor for myofibroblasts in the PDAC stroma. Overall, our study reveals the stromal targeting potential of HDACi, highlighting the utility of this epigenetic modulating approach in PDAC therapeutics.

cancer biology↗

Viral burdens are associated with age and viral variant in a population-representative study of SARS-CoV-2 that accounts for time-since-infection related sampling bias.

In this study, we evaluated the impact of viral variant, in addition to other variables, on within-host viral burdens, by analysing cycle threshold (Ct) values derived from nose and throat swabs, collected as part of the UK COVID-19 Infection Survey. Because viral burden distributions determined from community survey data can be biased due to the impact of variant epidemiology on the time-since-infection of samples, we developed a method to explicitly adjust observed Ct value distributions to account for the expected bias. Analysing the adjusted Ct values using partial least squares regression, we found that among unvaccinated individuals with no known prior infection, the average Ct value was 0.94 lower among Alpha variant infections, compared those with the predecessor strain, B.1.177. However, among vaccinated individuals, it was 0.34 lower among Delta variant infections, compared to those with the Alpha variant. In addition, the average Ct value decreased by 0.20 for every 10 year age increment of the infected individual. In summary, within-host viral burdens are associated with age, in addition to the interplay of vaccination status and viral variant.

genetics↗

LKB1 loss rewires JNK-induced apoptotic protein dynamics through NUAKs and sensitizes KRAS-mutant NSCLC to combined KRASG12C + MCL-1 blockade

The efficacy of molecularly targeted anti-cancer therapies may be limited by the presence of co-occurring mutations within a tumor1-3. Conversely, these alterations may confer collateral vulnerabilities that can be leveraged for the development of novel therapeutic approaches. KRAS-mutant lung cancers are distinguished by recurrent inactivating mutations in the tumor suppressor STK11/LKB14 that facilitate tumorigenesis by modulating energy balance5, 6, enhancing metastatic potential7,8 and enabling immune evasion9,10. However, whether LKB1 plays a role in modulating cellular responses to therapeutic stress is largely unknown. Here we show that LKB1 suppresses JNK-dependent stress signaling in KRAS-mutant lung cancer cells upon acute loss of oncogenic signaling. In LKB1-deficient KRAS-mutant cells, inhibition of KRAS or its downstream effector MEK leads to hyperactivation of JNK due to loss of NUAK-mediated PP1B phosphatase activity. JNK-mediated inhibitory phosphorylation of BCL-XL rewires apoptotic dependencies, rendering LKB1-deficient cells vulnerable to MCL-1 inhibition. These results uncover a previously unknown role for LKB1 in regulating stress signaling and the mitochondrial apoptotic response of cancer cells independent of its tumor suppressor activity mediated by AMPK11-13 and SIK14,15 kinases. Additionally, our study reveals a therapy-induced vulnerability in LKB1-deficient KRAS-mutant lung cancer cells that could be exploited as a genotype-informed strategy to improve the efficacy of KRAS-targeted therapies.

cancer biology↗

A Mesenchymal Tumor Cell State Confers Increased Dependency on the BCL-XL Anti-apoptotic Protein in Kidney Cancer

Genome-wide genetic screens have identified cellular dependencies in many cancers. Using the Broad Institutes Achilles shRNA screening dataset, we mined for targetable dependencies by cell lineage. Our studies identified a strong dependency on BCL2L1, which encodes the BCL-XL anti-apoptotic protein, in a subset of kidney cancer cells. Genetic and pharmacological inactivation of BCL-XL, but not the related anti-apoptotic proteins BCL-2, led to fitness defects in renal cancer cells, and also sensitized them to chemotherapeutics. Neither BCL-XL levels (absolute or normalized to BCL-2) nor the status of the VHL gene, which is frequently mutated in kidney cancer, predicted BCL-XL dependence. Transcriptional profiling, however, identified a BCL-XL dependency mRNA signature, which included elevated mesenchymal gene expression in BCL-XL dependent cells. Promoting mesenchymal transition increased BCL-XL dependence; whereas, conversion to a more differentiated state overcame BCL-XL dependence in kidney cancer cells. The BCL-XL dependency mRNA signature was observed in almost a third of human clear cell Renal Cell Carcinomas (ccRCCs), which were also associated with worse clinical outcomes. Finally, an orally bioavailable BCL-XL inhibitor, A-1331852, showed anti-tumor efficacy in vivo. Altogether, our studies uncovered an unexpected link between cancer cell state and dependence on the anti-apoptotic BCL-XL protein and justify further testing on BCL-XL blockade as a potential way to target a clinically aggressive subset of human kidney cancers. One Sentence SummaryCell state, but not pVHL and/or HIF status, defines the dependency of kidney cancer cells on the BCL-XL anti-apoptotic protein.

cancer biology↗

Cortical Oscillatory Dysrhythmias in Visual Snow Syndrome: A MEG Study

Visual Snow (VS) refers to the persistent visual experience of static in the whole visual field of both eyes. It is often reported by patients with migraine and co-occurs with conditions like tinnitus and tremor. The underlying pathophysiology of the condition is poorly understood. Previously we hypothesised, that VSS may be characterised by disruptions to rhythmical activity within the visual system1. To test this, data from 18 patients diagnosed with visual snow syndrome (VSS), and 16 matched controls, were acquired using Magnetoencephalography (MEG). Participants were presented with visual grating stimuli, known to elicit decreases in alpha-band (8-13Hz) power and increases in gamma-band power (40-70Hz). Data were mapped to source-space using a beamformer. Across both groups, decreased alpha power and increased gamma power localised to early visual cortex. Data from primary visual cortex (V1) were compared between groups. No differences were found in either alpha or gamma peak frequency or the magnitude of alpha power, p>.05. However, compared with controls, our VSS cohort displayed significantly increased V1 gamma power, p=.035. This new electromagnetic finding concurs with previous fMRI and PET findings suggesting that in VSS, the visual cortex is hyper-excitable. The coupling of alpha-phase to gamma amplitude (i.e., phase-amplitude coupling, PAC) within V1 was also quantified. Compared with controls, the VSS group had significantly reduced alpha-gamma PAC, p<.05, indicating a potential excitation-inhibition imbalance in VSS, as well as a potential disruption to top-down "noise-cancellation" mechanisms. Overall, these results suggest that rhythmical brain activity in primary visual cortex is both hyperexcitable and disorganised in VSS, consistent with visual snow being a condition of thalamocortical dysrhythmia.

neuroscience↗

Epidemiological dynamics of bacteriocin competition and antibiotic resistance

Bacteriocins, toxic peptides involved in the competition between bacterial strains, are extremely diverse. Previous work on bacteriocin dynamics has highlighted the role of non-transitive rock-paper-scissors competition in maintaining the coexistence of different bacteriocin profiles. The focus to date has primarily been on bacteriocin interactions at the within-host scale. Yet, in species such as Streptococcus pneumoniae with relatively short periods of colonisation and limited within-host diversity, ecological outcomes are also shaped by processes at the epidemiological (between-host) scale. Here, we first investigate bacteriocin dynamics and diversity in epidemiological models. We find that in these models, bacteriocin diversity is more readily maintained than in within-host models, and with more possible combinations of coexisting bacteriocin profiles. Indeed, maintenance of diversity in epidemiological models does not require rock-paper-scissors dynamics; it can also occur through a competition-colonisation trade-off. Second, we investigate the link between bacteriocin diversity and diversity at antibiotic resistance loci. Previous work has proposed that bacterial duration of colonisation modulates the fitness of antibiotic resistance. Due to their inhibitory effects, bacteriocins are a plausible candidate for playing a role in the duration of colonisation episodes. We extend the epidemiological model of bacteriocin dynamics to incorporate an antibiotic resistance locus and demonstrate that bacteriocin diversity can indeed maintain the coexistence of antibiotic sensitive and resistant strains.

evolutionary biology↗

Age-dependent regulation of SARS-CoV-2 cell entry genes and cell death programs correlates with COVID-19 disease severity

Angiotensin-converting enzyme 2 (ACE2) maintains cardiovascular and renal homeostasis but also serves as the entry receptor for the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), the causal agent of novel coronavirus disease 2019 (COVID-19)1. COVID-19 disease severity, while highly variable, is typically lower in pediatric patients than adults (particularly the elderly), but increased rates of hospitalizations requiring intensive care are observed in infants than in older children. The reasons for these differences are unknown. To detect potential age-based correlates of disease severity, we measured ACE2 protein expression at the single cell level in human lung tissue specimens from over 100 donors from [~]4 months to 75 years of age. We found that expression of ACE2 in distal lung epithelial cells generally increases with advancing age but exhibits extreme intra- and inter-individual heterogeneity. Notably, we also detected ACE2 expression on neonatal airway epithelial cells and within the lung parenchyma. Similar patterns were found at the transcript level: ACE2 mRNA is expressed in the lung and trachea shortly after birth, downregulated during childhood, and again expressed at high levels in late adulthood in alveolar epithelial cells. Furthermore, we find that apoptosis, which is a natural host defense system against viral infection, is also dynamically regulated during lung maturation, resulting in periods of heightened apoptotic priming and dependence on pro-survival BCL-2 family proteins including MCL-1. Infection of human lung cells with SARS-CoV-2 triggers an unfolded protein stress response and upregulation of the endogenous MCL-1 inhibitor Noxa; in juveniles, MCL-1 inhibition is sufficient to trigger apoptosis in lung epithelial cells - this may limit virion production and inflammatory signaling. Overall, we identify strong and distinct correlates of COVID-19 disease severity across lifespan and advance our understanding of the regulation of ACE2 and cell death programs in the mammalian lung. Furthermore, our work provides the framework for potential translation of apoptosis modulating drugs as novel treatments for COVID-19.

cell biology↗

SARS-CoV-2 genomics beyond the consensus sequence: evidence for circulating mixed viral populations

Extensive global sampling and whole genome sequencing of the pandemic virus SARS-CoV-2 have enabled researchers to characterise its spread, and to identify mutations that may increase transmission or enable the virus to escape therapies or vaccines. Two important components of viral spread are how frequently variants arise within individuals, and how likely they are to be transmitted. Here, we characterise the within-host diversity of SARS-CoV-2, and the extent to which genetic diversity is transmitted, by quantifying variant frequencies in 1390 clinical samples from the UK, many from individuals in known epidemiological clusters. We show that SARS-CoV-2 infections are characterised by low levels of within-host diversity across the entire viral genome, with evidence of strong evolutionary constraint in Spike, a key target of vaccines and antibody-based therapies. Although within-host variants can be observed in multiple individuals in the same phylogenetic or epidemiological cluster, highly infectious individuals with high viral load carry only a limited repertoire of viral diversity. Most viral variants are either lost, or occasionally fixed, at the point of transmission, consistent with a narrow transmission bottleneck. These results suggest potential vaccine-escape mutations are likely to be rare in infectious individuals. Nonetheless, we identified Spike variants present in multiple individuals that may affect receptor binding or neutralisation by antibodies. Since the fitness advantage of escape mutations in highly-vaccinated populations is likely to be substantial, resulting in rapid spread if and when they do emerge, these findings underline the need for continued vigilance and monitoring.

genomics↗