Meiotic DNA breaks drive multifaceted mutagenesis in the human germ line.

Meiotic recombination commences with hundreds of programmed DNA breaks; however, the degree to which they are accurately repaired remains poorly understood. We report that meiotic break repair is eightfold more mutagenic for single-base substitutions than was previously understood, leading to de novo mutation in one in four sperm and one in 12 eggs. Its impact on indels and structural variants is even higher, with 100- to 1300-fold increases in rates per break. We uncovered new mutational signatures and footprints relative to break sites, which implicate unexpected biochemical processes and error-prone DNA repair mechanisms, including translesion synthesis and end joining in meiotic break repair. We provide evidence that these mechanisms drive mutagenesis in human germ lines and lead to disruption of hundreds of genes genome wide.

Correction: Viral burden is associated with age, vaccination, and viral variant in a population-representative study of SARS-CoV-2 that accounts for time-since-infection-related sampling bias.

[This corrects the article DOI: 10.1371/journal.ppat.1011461.].

Viral burden is associated with age, vaccination, 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 burden, 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. By analysing the adjusted Ct values using partial least squares regression, we found that among unvaccinated individuals with no known prior exposure, viral burden was 44% lower among Alpha variant infections, compared to those with the predecessor strain, B.1.177. Vaccination reduced viral burden by 67%, and among vaccinated individuals, viral burden was 286% higher among Delta variant, compared to Alpha variant, infections. In addition, viral burden increased by 17% for every 10-year age increment of the infected individual. In summary, within-host viral burden increases with age, is reduced by vaccination, and is influenced by the interplay of vaccination status and viral variant.

Large-scale calibration and simulation of COVID-19 epidemiologic scenarios to support healthcare planning.

The COVID-19 pandemic has provided stiff challenges for planning and resourcing in health services in the UK and worldwide. Epidemiological models can provide simulations of how infectious disease might progress in a population given certain parameters. We adapted an agent-based model of COVID-19 to inform planning and decision-making within a healthcare setting, and created a software framework that automates processes for calibrating the model parameters to health data and allows the model to be run at national population scale on National Health Service (NHS) infrastructure. We developed a method for calibrating the model to three daily data streams (hospital admissions, intensive care occupancy, and deaths), and demonstrate that on cross-validation the model fits acceptably to unseen data streams including official estimates of COVID-19 incidence. Once calibrated, we use the model to simulate future scenarios of the spread of COVID-19 in England and show that the simulations provide useful projections of future COVID-19 clinical demand. These simulations were used to support operational planning in the NHS in England, and we present the example of the use of these simulations in projecting future clinical demand during the rollout of the national COVID-19 vaccination programme. Being able to investigate uncertainty and test sensitivities was particularly important to the operational planning team. This epidemiological model operates within an ecosystem of data technologies, drawing on a range of NHS, government and academic data sources, and provides results to strategists, planners and downstream data systems. We discuss the data resources that enabled this work and the data challenges that were faced.

Estimating SARS-CoV-2 variant fitness and the impact of interventions in England using statistical and geo-spatial agent-based models.

The SARS-CoV-2 epidemic has been extended by the evolution of more transmissible viral variants. In autumn 2020, the B.1.177 lineage became the dominant variant in England, before being replaced by the B.1.1.7 (Alpha) lineage in late 2020, with the sweep occurring at different times in each region. This period coincided with a large number of non-pharmaceutical interventions (e.g. lockdowns) to control the epidemic, making it difficult to estimate the relative transmissibility of variants. In this paper, we model the spatial spread of these variants in England using a meta-population agent-based model which correctly characterizes the regional variation in cases and distribution of variants. As a test of robustness, we additionally estimated the relative transmissibility of multiple variants using a statistical model based on the renewal equation, which simultaneously estimates the effective reproduction number R. Relative to earlier variants, the transmissibility of B.1.177 is estimated to have increased by 1.14 (1.12-1.16) and that of Alpha by 1.71 (1.65-1.77). The vaccination programme starting in December 2020 is also modelled. Counterfactual simulations demonstrate that the vaccination programme was essential for reopening in March 2021, and that if the January lockdown had started one month earlier, up to 30 k (24 k-38 k) deaths could have been prevented. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial.

Mathematical models are powerful tools in HIV epidemiology, producing quantitative projections of key indicators such as HIV incidence and prevalence. In order to improve the accuracy of predictions, such models need to incorporate a number of behavioural and biological heterogeneities, especially those related to the sexual network within which HIV transmission occurs. An individual-based model, which explicitly models sexual partnerships, is thus often the most natural type of model to choose. In this paper we present PopART-IBM, a computationally efficient individual-based model capable of simulating 50 years of an HIV epidemic in a large, high-prevalence community in under a minute. We show how the model calibrates within a Bayesian inference framework to detailed age- and sex-stratified data from multiple sources on HIV prevalence, awareness of HIV status, ART status, and viral suppression for an HPTN 071 (PopART) study community in Zambia, and present future projections of HIV prevalence and incidence for this community in the absence of trial intervention.

OpenABM-Covid19-An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing.

SARS-CoV-2 has spread across the world, causing high mortality and unprecedented restrictions on social and economic activity. Policymakers are assessing how best to navigate through the ongoing epidemic, with computational models being used to predict the spread of infection and assess the impact of public health measures. Here, we present OpenABM-Covid19: an agent-based simulation of the epidemic including detailed age-stratification and realistic social networks. By default the model is parameterised to UK demographics and calibrated to the UK epidemic, however, it can easily be re-parameterised for other countries. OpenABM-Covid19 can evaluate non-pharmaceutical interventions, including both manual and digital contact tracing, and vaccination programmes. It can simulate a population of 1 million people in seconds per day, allowing parameter sweeps and formal statistical model-based inference. The code is open-source and has been developed by teams both inside and outside academia, with an emphasis on formal testing, documentation, modularity and transparency. A key feature of OpenABM-Covid19 are its Python and R interfaces, which has allowed scientists and policymakers to simulate dynamic packages of interventions and help compare options to suppress the COVID-19 epidemic.

The epidemiological impact of the NHS COVID-19 app.

The COVID-19 pandemic has seen the emergence of digital contact tracing to help to prevent the spread of the disease. A mobile phone app records proximity events between app users, and when a user tests positive for COVID-19, their recent contacts can be notified instantly. Theoretical evidence has supported this new public health intervention1-6, but its epidemiological impact has remained uncertain7. Here we investigate the impact of the National Health Service (NHS) COVID-19 app for England and Wales, from its launch on 24 September 2020 to the end of December 2020. It was used regularly by approximately 16.5 million users (28% of the total population), and sent approximately 1.7 million exposure notifications: 4.2 per index case consenting to contact tracing. We estimated that the fraction of individuals notified by the app who subsequently showed symptoms and tested positive (the secondary attack rate (SAR)) was 6%, similar to the SAR for manually traced close contacts. We estimated the number of cases averted by the app using two complementary approaches: modelling based on the notifications and SAR gave an estimate of 284,000 (central 95% range of sensitivity analyses 108,000-450,000), and statistical comparison of matched neighbouring local authorities gave an estimate of 594,000 (95% confidence interval 317,000-914,000). Approximately one case was averted for each case consenting to notification of their contacts. We estimated that for every percentage point increase in app uptake, the number of cases could be reduced by 0.8% (using modelling) or 2.3% (using statistical analysis). These findings support the continued development and deployment of such apps in populations that are awaiting full protection from vaccines.

Modeling the effect of exposure notification and non-pharmaceutical interventions on COVID-19 transmission in Washington state.

Contact tracing is increasingly used to combat COVID-19, and digital implementations are now being deployed, many based on Apple and Google's Exposure Notification System. These systems utilize non-traditional smartphone-based technology, presenting challenges in understanding possible outcomes. In this work, we create individual-based models of three Washington state counties to explore how digital exposure notifications combined with other non-pharmaceutical interventions influence COVID-19 disease spread under various adoption, compliance, and mobility scenarios. In a model with 15% participation, we found that exposure notification could reduce infections and deaths by approximately 8% and 6% and could effectively complement traditional contact tracing. We believe this can provide health authorities in Washington state and beyond with guidance on how exposure notification can complement traditional interventions to suppress the spread of COVID-19.

Electroporation and genetic supply of Cas9 increase the generation efficiency of CRISPR/Cas9 knock-in alleles in C57BL/6J mouse zygotes.

CRISPR/Cas9 machinery delivered as ribonucleoprotein (RNP) to the zygote has become a standard tool for the development of genetically modified mouse models. In recent years, a number of reports have demonstrated the effective delivery of CRISPR/Cas9 machinery via zygote electroporation as an alternative to the conventional delivery method of microinjection. In this study, we have performed side-by-side comparisons of the two RNP delivery methods across multiple gene loci and conclude that electroporation compares very favourably with conventional pronuclear microinjection, and report an improvement in mutagenesis efficiency when delivering CRISPR via electroporation for the generation of simple knock-in alleles using single-stranded oligodeoxynucleotide (ssODN) repair templates. In addition, we show that the efficiency of knock-in mutagenesis can be further increased by electroporation of embryos derived from Cas9-expressing donor females. The maternal supply of Cas9 to the zygote avoids the necessity to deliver the relatively large Cas9 protein, and high efficiency generation of both indel and knock-in allele can be achieved by electroporation of small single-guide RNAs and ssODN repair templates alone. Furthermore, electroporation, compared to microinjection, results in a higher rate of embryo survival and development. The method thus has the potential to reduce the number of animals used in the production of genetically modified mouse models.

Factors influencing meiotic recombination revealed by whole-genome sequencing of single sperm.

Recombination is critical to meiosis and evolution, yet many aspects of the physical exchange of DNA via crossovers remain poorly understood. We report an approach for single-cell whole-genome DNA sequencing by which we sequenced 217 individual hybrid mouse sperm, providing a kilobase-resolution genome-wide map of crossovers. Combining this map with molecular assays measuring stages of recombination, we identified factors that affect crossover probability, including PRDM9 binding on the non-initiating template homolog and telomere proximity. These factors also influence the time for sites of recombination-initiating DNA double-strand breaks to find and engage their homologs, with rapidly engaging sites more likely to form crossovers. We show that chromatin environment on the template homolog affects positioning of crossover breakpoints. Our results also offer insights into recombination in the pseudoautosomal region.

The role of the Na+/Ca2+ exchangers in Ca2+ dynamics in ventricular myocytes.

The role of the Na+/Ca2+ exchanger (NCX) as the main pathway for Ca2+ extrusion from ventricular myocytes is well established. However, both the role of the Ca2+ entry mode of NCX in regulating local Ca2+ dynamics and the role of the Ca2+ exit mode during the majority of the physiological action potential (AP) are subjects of controversy. The functional significance of NCXs location in T-tubules and potential co-localization with ryanodine receptors was examined using a local Ca2+ control model of low computational cost. Our simulations demonstrate that under physiological conditions local Ca2+ and Na+ gradients are critical in calculating the driving force for NCX and hence in predicting the effect of NCX on AP. Under physiological conditions when 60% of NCXs are located on T-tubules, NCX may be transiently inward within the first 100 ms of an AP and then transiently outward during the AP plateau phase. Thus, during an AP NCX current (INCX) has three reversal points rather than just one. This provides a resolution to experimental observations where Ca2+ entry via NCX during an AP is inconsistent with the time at which INCX is thought to become inward. A more complex than previously believed dynamic regulation of INCX during AP under physiological conditions allows us to interpret apparently contradictory experimental data in a consistent conceptual framework. Our modelling results support the claim that NCX regulates the local control of Ca2+ and provide a powerful tool for future investigations of the control of sarcoplasmic reticulum (SR) Ca2+ release under pathological conditions.

Functional significance of Na+/Ca2+ exchangers co-localization with ryanodine receptors.

Co-localization of Na+/Ca2+ exchangers (NCX) with ryanodine receptors (RyRs) is debated. We incorporate local NCX current in a biophysically detailed model of L-type Ca2+ channels (LCCs) and RyRs and study the effect of NCX on the regulation of Ca2+-induced Ca2+ release and the shape of the action potential. In canine ventricular cells, under pathological conditions, e.g., impaired LCCs, local NCXs become an enhancer of sarcoplasmic reticulum release. Under such conditions incorporation of local NCXs is critical to accurately capture mechanisms of excitation-contraction coupling.

Mechanisms of excitation-contraction coupling in an integrative model of the cardiac ventricular myocyte.

It is now well established that characteristic properties of excitation-contraction (EC) coupling in cardiac myocytes, such as high gain and graded Ca(2+) release, arise from the interactions that occur between L-type Ca(2+) channels (LCCs) and nearby ryanodine-sensitive Ca(2+) release channels (RyRs) in localized microdomains. Descriptions of Ca(2+)-induced Ca(2+) release (CICR) that account for these local mechanisms are lacking from many previous models of the cardiac action potential, and those that do include local control of CICR are able to reconstruct properties of EC coupling, but require computationally demanding stochastic simulations of approximately 10(5) individual ion channels. In this study, we generalize a recently developed analytical approach for deriving simplified mechanistic models of CICR to formulate an integrative model of the canine cardiac myocyte which is computationally efficient. The resulting model faithfully reproduces experimentally measured properties of EC coupling and whole cell phenomena. The model is used to study the role of local redundancy in L-type Ca(2+) channel gating and the role of dyad configuration on EC coupling. Simulations suggest that the characteristic steep rise in EC coupling gain observed at hyperpolarized potentials is a result of increased functional coupling between LCCs and RyRs. We also demonstrate mechanisms by which alterations in the early repolarization phase of the action potential, resulting from reduction of the transient outward potassium current, alters properties of EC coupling.

A note on the asymptotic reduction of the Hodgkin-Huxley equations for nerve impulses.

The (standard) FitzHugh reduction of the Hodgkin-Huxley equations for the propagation of nerve impulses ignores the dynamics of the activation gates. This assumption is invalid and leads to an over-estimation of the wave speed by a factor of 5 and the wrong dependence of wave speed on sodium channel conductance. The error occurs because a non-dimensional parameter, which is assumed to be small in the FitzHugh reduction, is in fact large (approximately 18). We analyse the Hodgkin-Huxley equations for propagating nerve impulses in the limit that this non-dimensional parameter is large, and show that the analytical results are consistent with numerical simulations of the Hodgkin-Huxley equations.

An analytical study of the physiology and pathology of the propagation of cardiac action potentials.

Many cardiac diseases are caused by the abnormal propagation of electrical waves. Previous experimental and modelling work is reviewed, then a detailed study of the mathematics of cardiac propagation is presented. Pathologies are examined in the context of the models by varying parameters in the models to mimic different pathological states. Ionic models of cells are simplified to form analytically tractable models of the propagation of electrical cardiac waves. The roles that sodium channel activation and inactivation play in determining the conduction velocity are studied in detail, and the roles of resting potential currents in conduction block are calculated. The effect of curvature on the conduction velocity is examined, and the conditions in which curvature leads to conduction block and fibrillation are discussed. Hyperkalaemia (important during ischaemia) is modelled, and the model correctly describes the bi-phasic relation between propagation velocity and extracellular potassium.