Publications
186 results found
Helekal D, Keeling M, Grad YH, et al., 2023, Estimating the fitness cost and benefit of antimicrobial resistance from pathogen genomic data., J R Soc Interface, Vol: 20
Increasing levels of antibiotic resistance in many bacterial pathogen populations are a major threat to public health. Resistance to an antibiotic provides a fitness benefit when the bacteria are exposed to this antibiotic, but resistance also often comes at a cost to the resistant pathogen relative to susceptible counterparts. We lack a good understanding of these benefits and costs of resistance for many bacterial pathogens and antibiotics, but estimating them could lead to better use of antibiotics in a way that reduces or prevents the spread of resistance. Here, we propose a new model for the joint epidemiology of susceptible and resistant variants, which includes explicit parameters for the cost and benefit of resistance. We show how Bayesian inference can be performed under this model using phylogenetic data from susceptible and resistant lineages and that by combining data from both we are able to disentangle and estimate the resistance cost and benefit parameters separately. We applied our inferential methodology to several simulated datasets to demonstrate good scalability and accuracy. We analysed a dataset of Neisseria gonorrhoeae genomes collected between 2000 and 2013 in the USA. We found that two unrelated lineages resistant to fluoroquinolones shared similar epidemic dynamics and resistance parameters. Fluoroquinolones were abandoned for the treatment of gonorrhoea due to increasing levels of resistance, but our results suggest that they could be used to treat a minority of around 10% of cases without causing resistance to grow again.
Dingle KE, Freeman J, Didelot X, et al., 2023, Penicillin Binding Protein Substitutions Cooccur with Fluoroquinolone Resistance in Epidemic Lineages of Multidrug-Resistant Clostridioides difficile., mBio, Vol: 14
Clostridioides difficile remains a key cause of healthcare-associated infection, with multidrug-resistant (MDR) lineages causing high-mortality (≥20%) outbreaks. Cephalosporin treatment is a long-established risk factor, and antimicrobial stewardship is a key control. A mechanism underlying raised cephalosporin MICs has not been identified in C. difficile, but among other species, this is often acquired via amino acid substitutions in cell wall transpeptidases (penicillin binding proteins [PBPs]). Here, we investigated five C. difficile transpeptidases (PBP1 to PBP5) for recent substitutions, associated cephalosporin MICs, and co-occurrence with fluoroquinolone resistance. Previously published genome assemblies (n = 7,096) were obtained, representing 16 geographically widespread lineages, including healthcare-associated ST1(027). Recent amino acid substitutions were found within PBP1 (n = 50) and PBP3 (n = 48), ranging from 1 to 10 substitutions per genome. β-Lactam MICs were measured for closely related pairs of wild-type and PBP-substituted isolates separated by 20 to 273 single nucleotide polymorphisms (SNPs). Recombination-corrected phylogenies were constructed to date substitution acquisition. Key substitutions such as PBP3 V497L and PBP1 T674I/N/V emerged independently across multiple lineages. They were associated with extremely high cephalosporin MICs; 1 to 4 doubling dilutions >wild-type, up to 1,506 μg/mL. Substitution patterns varied by lineage and clade, showed geographic structure, and occurred post-1990, coincident with the gyrA and/or gyrB substitutions conferring fluoroquinolone resistance. In conclusion, recent PBP1 and PBP3 substitutions are associated with raised cephalosporin MICs in C. difficile. Their co-occurrence with fluoroquinolone resistance hinders attempts to understand the relative importance of these drugs in the dissemination of epidemic lineages. Further controlled studie
Kendall M, Tsallis D, Wymant C, et al., 2023, Epidemiological impacts of the NHS COVID-19 app in England and Wales throughout its first year., Nat Commun, Vol: 14
The NHS COVID-19 app was launched in England and Wales in September 2020, with a Bluetooth-based contact tracing functionality designed to reduce transmission of SARS-CoV-2. We show that user engagement and the app's epidemiological impacts varied according to changing social and epidemic characteristics throughout the app's first year. We describe the interaction and complementarity of manual and digital contact tracing approaches. Results of our statistical analyses of anonymised, aggregated app data include that app users who were recently notified were more likely to test positive than app users who were not recently notified, by a factor that varied considerably over time. We estimate that the app's contact tracing function alone averted about 1 million cases (sensitivity analysis 450,000-1,400,000) during its first year, corresponding to 44,000 hospital cases (SA 20,000-60,000) and 9,600 deaths (SA 4600-13,000).
Mughal SR, Niazi SA, Do T, et al., 2023, Genomic Diversity among Actinomyces naeslundii Strains and Closely Related Species., Microorganisms, Vol: 11, ISSN: 2076-2607
The aim of this study was to investigate and clarify the ambiguous taxonomy of Actinomyces naeslundii and its closely related species using state-of-the-art high-throughput sequencing techniques, and, furthermore, to determine whether sub-clusters identified within Actinomyces oris and Actinomyces naeslundii in a previous study by multi locus sequence typing (MLST) using concatenation of seven housekeeping genes should either be classified as subspecies or distinct species. The strains in this study were broadly classified under Actinomyces naeslundii group as A. naeslundii genospecies I and genospecies II. Based on MLST data analysis, these were further classified as A. oris and A. naeslundii. The whole genome sequencing of selected strains of A. oris (n = 17) and A. naeslundii (n = 19) was carried out using Illumina Genome Analyzer IIxe and Roche 454 allowing paired-end and single-reads sequencing, respectively. The sequences obtained were aligned using CLC Genomic workbench version 5.1 and annotated using RAST (Rapid Annotation using Subsystem Technology) release version 59 accessible online. Additionally, genomes of seven publicly available strains of Actinomyces (k20, MG1, c505, OT175, OT171, OT170, and A. johnsonii) were also included. Comparative genomic analysis (CGA) using Mauve, Progressive Mauve, gene-by-gene, Core, and Pan Genome, and finally Digital DNA-DNA homology (DDH) analysis was carried out. DDH values were obtained using in silico genome-genome comparison. Evolutionary analysis using ClonalFrame was also undertaken. The mutation and recombination events were compared using chi-square test among A. oris and A. naeslundii isolates (analysis methods are not included in the study). CGA results were consistent with previous traditional classification using MLST. It was found that strains of Actinomyces k20, MG1, c505, and OT175 clustered in A. oris group of isolates, while OT171, OT170, and A. johnsonii appeared as separate branches. Similar clusterin
Didelot X, Franceschi V, Frost SDW, et al., 2023, Model design for nonparametric phylodynamic inference and applications to pathogen surveillance., Virus Evol, Vol: 9, ISSN: 2057-1577
Inference of effective population size from genomic data can provide unique information about demographic history and, when applied to pathogen genetic data, can also provide insights into epidemiological dynamics. The combination of nonparametric models for population dynamics with molecular clock models which relate genetic data to time has enabled phylodynamic inference based on large sets of time-stamped genetic sequence data. The methodology for nonparametric inference of effective population size is well-developed in the Bayesian setting, but here we develop a frequentist approach based on nonparametric latent process models of population size dynamics. We appeal to statistical principles based on out-of-sample prediction accuracy in order to optimize parameters that control shape and smoothness of the population size over time. Our methodology is implemented in a new R package entitled mlesky. We demonstrate the flexibility and speed of this approach in a series of simulation experiments and apply the methodology to a dataset of HIV-1 in the USA. We also estimate the impact of non-pharmaceutical interventions for COVID-19 in England using thousands of SARS-CoV-2 sequences. By incorporating a measure of the strength of these interventions over time within the phylodynamic model, we estimate the impact of the first national lockdown in the UK on the epidemic reproduction number.
Didelot X, Helekal D, Kendall M, et al., 2022, Distinguishing imported cases from locally acquired cases within a geographically limited genomic sample of an infectious disease, BIOINFORMATICS, ISSN: 1367-4803
Moore MP, Laager M, Ribeca P, et al., 2022, <i>KmerAperture</i>: Retaining<i>k</i>-mer synteny for alignment-free extraction of core and accessory differences between bacterial genomes
<jats:title>ABSTRACT</jats:title><jats:p>By decomposing genome sequences into<jats:italic>k</jats:italic>-mers, it is possible to estimate genome differences without alignment. Techniques such as<jats:italic>k-</jats:italic>mer minimisers (MinHash), have been developed and are often accurate approximations of distances based on full<jats:italic>k</jats:italic>-mer sets. These and other alignment-free methods avoid the large temporal and computational expense of alignment or mapping. However, these<jats:italic>k</jats:italic>-mer set comparisons are not entirely accurate within-species and can be completely inaccurate within-lineage. This is due, in part, to their inability to distinguish core polymorphism from accessory differences. Here we present a new approach,<jats:italic>KmerAperture</jats:italic>, which uses information on the<jats:italic>k</jats:italic>-mer relative genomic positions to determine the type of polymorphism causing differences in<jats:italic>k</jats:italic>-mer presence and absence between pairs of genomes. Single SNPs are expected to result in contiguous series of relative unique<jats:italic>k</jats:italic>-mers of length<jats:italic>L</jats:italic>=<jats:italic>k</jats:italic>. On the other hand, series of length<jats:italic>L</jats:italic>><jats:italic>k</jats:italic>may be caused by accessory differences of length<jats:italic>L</jats:italic>-<jats:italic>k</jats:italic>+1; when the start and end of the sequence are contiguous with homologous sequence. Alternatively, they may be caused by multiple SNPs within<jats:italic>k</jats:italic>bp from each other and<jats:italic>KmerAperture</jats:italic>can determine whether that is the case. To demonstrate use cases<jats:italic>KmerAperture</jats:italic>was benchmarked using
Didelot X, Parkhill J, 2022, A scalable analytical approach from bacterial genomes to epidemiology, PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, Vol: 377, ISSN: 0962-8436
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- Citations: 2
Didelot X, Evans CM, 2022, London parochial burial records from 1563 to 1665 indicate higher plague death rates for males than females: Some possible demographic and social explanations, PLOS ONE, Vol: 17, ISSN: 1932-6203
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- Citations: 1
Didelot X, Helekal D, Kendall M, et al., 2022, Distinguishing imported cases from locally acquired cases within a geographically limited genomic sample of an infectious disease
<jats:title>ABSTRACT</jats:title><jats:p>The ability to distinguish imported cases from locally acquired cases has important consequences for the selection of public health control strategies. Genomic data can be useful for this, for example using a phylogeographic analysis in which genomic data from multiple locations is compared to determine likely migration events between locations. However, these methods typically require good samples of genomes from all locations, which is rarely available. Here we propose an alternative approach that only uses genomic data from a location of interest. By comparing each new case with previous cases from the same location we are able to detect imported cases, as they have a different genealogical distribution than that of locally acquired cases. We show that, when variations in the size of the local population are accounted for, our method has good sensitivity and excellent specificity for the detection of imports. We applied our method to data simulated under the structured coalescent model and demonstrate relatively good performance even when the local population has the same size as the external population. Finally, we applied our method to several recent genomic datasets from both bacterial and viral pathogens, and show that it can, in a matter of seconds or minutes, deliver important insights on the number of imports to a geographically limited sample of a pathogen population.</jats:p>
Didelot X, Ribeca P, 2022, KPop: An assembly-free and scalable method for the comparative analysis of microbial genomes
<jats:title>Abstract</jats:title><jats:p>It has become increasingly difficult for traditional analysis techniques based on assembly and variant calling to cope with the recent explosion in the amount of available sequencing data, especially in the field of microbial genomics. Here we introduce KPop, a novel versatile method based on full <jats:italic>k</jats:italic>-mer spectra and dataset-specific transformations, that allows for the accurate comparison of hundreds of thousands of assembled or unassembled microbial genomes in a matter of hours. We validate the method on simulated datasets and show that it can correctly classify sequences into lineages and rapidly identify related sequences. We also demonstrate its usefulness on several real-life datasets, in the case of both viral and bacterial pathogens. The KPop open-source code is available on GitHub at <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/PaoloRibeca/KPop">https://github.com/PaoloRibeca/KPop</jats:ext-link>.</jats:p>
Carson J, Ledda A, Ferretti L, et al., 2022, The bounded coalescent model: Conditioning a genealogy on a minimum root date, JOURNAL OF THEORETICAL BIOLOGY, Vol: 548, ISSN: 0022-5193
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- Citations: 1
Ortiz AT, Kendall M, Storey N, et al., 2022, Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks., bioRxiv
Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches to reconstruct outbreaks exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is stable among repeated serial samples from the same host, is transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.
Volk D, Yang-Turner F, Didelot X, et al., 2022, Catwalk: identifying closely related sequences in large microbial sequence databases, MICROBIAL GENOMICS, Vol: 8, ISSN: 2057-5858
Dingle KE, Freeman J, Didelot X, et al., 2022, Penicillin Binding Protein Substitutions Co-occur with Fluoroquinolone Resistance in ‘Epidemic’ Lineages of Multi Drug-Resistant <i>Clostridioides difficile</i>
<jats:title>ABSTRACT</jats:title><jats:p><jats:italic>Clostridioides difficile</jats:italic> remains a key cause of healthcare-associated infection, with multi-drug-resistant (MDR) lineages causing high mortality (≥20%) outbreaks. Cephalosporin treatment is a long-established risk factor, and antimicrobial stewardship a key control. A mechanism underlying raised cephalosporin MICs has not been identified in <jats:italic>C. difficile</jats:italic>, but among other species resistance is often acquired <jats:italic>via</jats:italic> amino acid substitutions in cell wall transpeptidases (penicillin binding proteins, PBPs). Here, we investigated five <jats:italic>C. difficile</jats:italic> transpeptidases (PBP1-5) for recent substitutions. Previously published genome assemblies (n=7096) were obtained, representing sixteen geographically widespread lineages, including healthcare-associated MDR ST1(027), ST3(001) and ST17(018). Recent amino acid substitutions were found within PBP1 (n=50) and PBP3 (n=48), ranging from 1-10 substitutions per genome. β-lactam MICs were measured for closely related pairs of wild-type and PBP substituted isolates separated by 20-273 SNPs. Recombination-corrected, dated phylogenies were constructed to date substitution acquisition. Key substitutions such as PBP3 V497L and PBP1 T674I/N/V emerged independently across multiple lineages. They were associated with extremely high cephalosporin MICs; 1-4 doubling dilutions >wild-type up to ≤1506μg/ml. Substitution patterns varied by lineage and clade, showed geographic structure, and notably occurred post-1990, coincident with the acquisition of <jats:italic>gyrA</jats:italic>/<jats:italic>B</jats:italic> substitutions conferring fluoroquinolone resistance. In conclusion, recent PBP1 and PBP3 substitutions are associated with raised cephalosporin MICs in <jats:italic>C. difficile</ja
Ledda A, Cummins M, Shaw LP, et al., 2022, Hospital outbreak of carbapenem-resistant Enterobacterales associated with a bla OXA-48 plasmid carried mostly by Escherichia coli ST399, Microbial Genomics, Vol: 8, ISSN: 2057-5858
A hospital outbreak of carbapenem-resistant Enterobacterales was detected by routine surveillance. Whole genome sequencing and subsequent analysis revealed a conserved promiscuous blaOXA-48 carrying plasmid as the defining factor within this outbreak. Four different species of Enterobacterales were involved in the outbreak. Escherichia coli ST399 accounted for 35 of all the 55 isolates. Comparative genomics analysis using publicly available E. coli ST399 genomes showed that the outbreak E. coli ST399 isolates formed a unique clade. We developed a mathematical model of pOXA-48-like plasmid transmission between host lineages and used it to estimate its conjugation rate, giving a lower bound of 0.23 conjugation events per lineage per year. Our analysis suggests that co-evolution between the pOXA-48-like plasmid and E. coli ST399 could have played a role in the outbreak. This is the first study to report carbapenem-resistant E. coli ST399 carrying blaOXA-48 as the main cause of a plasmid-borne outbreak within a hospital setting. Our findings suggest complementary roles for both plasmid conjugation and clonal expansion in the emergence of this outbreak.
Larsen J, Raisen CL, Ba X, et al., 2022, Emergence of methicillin resistance predates the clinical use of antibiotics, NATURE, Vol: 602, Pages: 135-+, ISSN: 0028-0836
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- Citations: 10
Fountain-Jones NM, Kraberger S, Gagne RB, et al., 2022, Hunting alters viral transmission and evolution in a large carnivore, NATURE ECOLOGY & EVOLUTION, Vol: 6, Pages: 174-+, ISSN: 2397-334X
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- Citations: 2
Carson J, Ledda A, Ferretti L, et al., 2022, The bounded coalescent model: conditioning a genealogy on a minimum root date
<jats:title>Abstract</jats:title><jats:p>The coalescent model represents how individuals sampled from a population may have originated from a last common ancestor. The bounded coalescent model is obtained by conditioning the coalescent model such that the last common ancestor must have existed after a certain date. This conditioned model arises in a variety of applications, such as speciation, horizontal gene transfer or transmission analysis, and yet the bounded coalescent model has not been previously analysed in detail. Here we describe a new algorithm to simulate from this model directly, without resorting to rejection sampling. We show that this direct simulation algorithm is more computationally efficient than the rejection sampling approach. We also show how to calculate the probability of the last common ancestor occurring after a given date, which is required to compute the probability of realisations under the bounded coalescent model. Our results are applicable in both the isochronous (when all samples have the same date) and heterochronous (where samples can have different dates) settings. We explore the effect of setting a bound on the date of the last common ancestor, and show that it affects a number of properties of the resulting phylogenies. All our methods are implemented in a new R package called BoundedCoalescent which is freely available online.</jats:p>
Ortiz AT, Coronel J, Vidal JR, et al., 2021, Genomic signatures of pre-resistance in Mycobacterium tuberculosis, NATURE COMMUNICATIONS, Vol: 12
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- Citations: 9
Helekal D, Ledda A, Volz E, et al., 2021, Bayesian Inference of Clonal Expansions in a Dated Phylogeny, SYSTEMATIC BIOLOGY, ISSN: 1063-5157
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- Citations: 3
Didelot X, Parkhill J, 2021, A scalable analytical approach from bacterial genomes to epidemiology
<jats:title>Summary</jats:title><jats:p>Recent years have seen a remarkable increase in the practicality of sequencing whole genomes from large numbers of bacterial isolates. The availability of this data has huge potential to deliver new insights into the evolution and epidemiology of bacterial pathogens, but the scalability of the analytical methodology has been lagging behind that of the sequencing technology. Here we present a step-by-step approach for such large-scale genomic epidemiology analyses, from bacterial genomes to epidemiological interpretations. A central component of this approach is the dated phylogeny, which is a phylogenetic tree with branch lengths measured in units of time. The construction of dated phylogenies from bacterial genomic data needs to account for the disruptive effect of recombination on phylogenetic relationships, and we describe how this can be achieved. Dated phylogenies can then be used to perform fine-scale or large-scale epidemiological analyses, depending on the proportion of cases for which genomes are available. A key feature of this approach is computational scalability, and in particular the ability to process hundreds or thousands of genomes within a matter of hours. This is a clear advantage of the step-by-step approach described here. We discuss other advantages and disadvantages of the approach, as well as potential improvements and avenues for future research.</jats:p>
Wan Y, Myall AC, Boonyasiri A, et al., 2021, Integrated analysis of patient networks and plasmid genomes reveals a regional, multi-species outbreak of carbapenemase-producing Enterobacterales carrying both<i>bla</i><sub>IMP</sub>and<i>mcr-9</i>genes
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Carbapenemase-producing Enterobacterales (CPE) are challenging in the healthcare setting, with resistance to multiple classes of antibiotics and a high associated mortality. The incidence of CPE is rising globally, despite enhanced awareness and control efforts. This study describes an investigation of the emergence of IMP-encoding CPE amongst diverse Enterobacterales species between 2016 and 2019 in patients across a London regional hospital network.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We carried out a network analysis of patient pathways, using electronic health records, to identify contacts between IMP-encoding CPE positive patients. Genomes of IMP-encoding CPE isolates were analysed and overlayed with patient contacts to imply potential transmission events.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Genomic analysis of 84 Enterobacterales isolates revealed diverse species (predominantly<jats:italic>Klebsiella</jats:italic>spp,<jats:italic>Enterobacter</jats:italic>spp,<jats:italic>E. coli</jats:italic>), of which 86% (72/84) harboured an IncHI2 plasmid, which carried both<jats:italic>bla</jats:italic><jats:sub>IMP</jats:sub>and the mobile colistin resistance gene<jats:italic>mcr-9</jats:italic>(68/72). Phylogenetic analysis of IncHI2 plasmids identified three lineages which showed significant association with patient contact and movements between four hospital sites and across medical specialities, which had been missed on initial investigations.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Combined, our patient network and plasmid analyses demonstrate an interspecies, plasmid-med
Didelot X, Geidelberg L, COVID-19 Genomics UK COG-UK consortium, et al., 2021, Model design for non-parametric phylodynamic inference and applications to pathogen surveillance., bioRxiv
Inference of effective population size from genomic data can provide unique information about demographic history, and when applied to pathogen genetic data can also provide insights into epidemiological dynamics. The combination of non-parametric models for population dynamics with molecular clock models which relate genetic data to time has enabled phylodynamic inference based on large sets of time-stamped genetic sequence data. The methodology for non-parametric inference of effective population size is well-developed in the Bayesian setting, but here we develop a frequentist approach based on non-parametric latent process models of population size dynamics. We appeal to statistical principles based on out-of-sample prediction accuracy in order to optimize parameters that control shape and smoothness of the population size over time. We demonstrate the flexibility and speed of this approach in a series of simulation experiments, and apply the methodology to reconstruct the previously described waves in the seventh pandemic of cholera. We also estimate the impact of non-pharmaceutical interventions for COVID-19 in England using thousands of SARS-CoV-2 sequences. By incorporating a measure of the strength of these interventions over time within the phylodynamic model, we estimate the impact of the first national lockdown in the UK on the epidemic reproduction number.
Helekal D, Ledda A, Volz E, et al., 2021, Bayesian inference of clonal expansions in a dated phylogeny
<jats:title>ABSTRACT</jats:title><jats:p>Microbial population genetics models often assume that all lineages are constrained by the same population size dynamics over time. However, many neutral and selective events can invalidate this assumption, and can contribute to the clonal expansion of a specific lineage relative to the rest of the population. Such differential phylodynamic properties between lineages result in asymmetries and imbalances in phylogenetic trees that are sometimes described informally but which are difficult to analyse formally. To this end, we developed a model of how clonal expansions occur and affect the branching patterns of a phylogeny. We show how the parameters of this model can be inferred from a given dated phylogeny using Bayesian statistics, which allows us to assess the probability that one or more clonal expansion events occurred. For each putative clonal expansion event we estimate their date of emergence and subsequent phylodynamic trajectories, including their long-term evolutionary potential which is important to determine how much effort should be placed on specific control measures. We demonstrate the applicability of our methodology on simulated and real datasets.</jats:p>
Wang L, Didelot X, Bi Y, et al., 2021, Assessing the extent of community spread caused by mink-derived SARS-CoV-2 variants, INNOVATION, Vol: 2, ISSN: 2666-6758
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- Citations: 10
Knight DR, Imwattana K, Kullin B, et al., 2021, Major genetic discontinuity and novel toxigenic species in Clostridioides difficile taxonomy, ELIFE, Vol: 10, ISSN: 2050-084X
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- Citations: 25
Nimmo C, van Dorp L, Ortiz AT, et al., 2021, BEDAQUILINE RESISTANCE IN MYCOBACTERIUM TUBERCULOSIS PREDATES ITS CLINICAL USE, Publisher: BMJ PUBLISHING GROUP, Pages: A51-A52, ISSN: 0040-6376
Didelot X, Kendall M, Xu Y, et al., 2021, Genomic epidemiology analysis of infectious disease outbreaks using TransPhylo., Current Protocols, Vol: 1, Pages: 1-23, ISSN: 2691-1299
Comparing the pathogen genomes from several cases of an infectious disease has the potential to help us understand and control outbreaks. Many methods exist to reconstruct a phylogeny from such genomes, which represents how the genomes are related to one another. However, such a phylogeny is not directly informative about transmission events between individuals. TransPhylo is a software tool implemented as an R package designed to bridge the gap between pathogen phylogenies and transmission trees. TransPhylo is based on a combined model of transmission between hosts and pathogen evolution within each host. It can simulate both phylogenies and transmission trees jointly under this combined model. TransPhylo can also reconstruct a transmission tree based on a dated phylogeny, by exploring the space of transmission trees compatible with the phylogeny. A transmission tree can be represented as a coloring of a phylogeny where each color represents a different host of the pathogen, and TransPhylo provides convenient ways to plot these colorings and explore the results. This article presents the basic protocols that can be used to make the most of TransPhylo. © 2021 The Authors. Basic Protocol 1: First steps with TransPhylo Basic Protocol 2: Simulation of outbreak data Basic Protocol 3: Inference of transmission Basic Protocol 4: Exploring the results of inference.
Didelot X, 2021, Phylogenetic Methods for Genome-Wide Association Studies in Bacteria, BACTERIAL PANGENOMICS, 2 EDITION, Vol: 2242, Pages: 205-220, ISSN: 1064-3745
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- Citations: 3
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