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Search Results: 1 - 10 of 213220 matches for " William P Hanage "
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Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach
Jing Tang ,William P. Hanage,Christophe Fraser,Jukka Corander
PLOS Computational Biology , 2009, DOI: 10.1371/journal.pcbi.1000455
Abstract: The evolution of bacterial populations has recently become considerably better understood due to large-scale sequencing of population samples. It has become clear that DNA sequences from a multitude of genes, as well as a broad sample coverage of a target population, are needed to obtain a relatively unbiased view of its genetic structure and the patterns of ancestry connected to the strains. However, the traditional statistical methods for evolutionary inference, such as phylogenetic analysis, are associated with several difficulties under such an extensive sampling scenario, in particular when a considerable amount of recombination is anticipated to have taken place. To meet the needs of large-scale analyses of population structure for bacteria, we introduce here several statistical tools for the detection and representation of recombination between populations. Also, we introduce a model-based description of the shape of a population in sequence space, in terms of its molecular variability and affinity towards other populations. Extensive real data from the genus Neisseria are utilized to demonstrate the potential of an approach where these population genetic tools are combined with an phylogenetic analysis. The statistical tools introduced here are freely available in BAPS 5.2 software, which can be downloaded from http://web.abo.fi/fak/mnf/mate/jc/softwa?re/baps.html.
Fuzzy species among recombinogenic bacteria
William P Hanage, Christophe Fraser, Brian G Spratt
BMC Biology , 2005, DOI: 10.1186/1741-7007-3-6
Abstract: Alleles at individual loci were widely distributed among the named species but this distorting effect of recombination was largely buffered by using concatenated sequences, which resolved clusters corresponding to the three species most numerous in the sample, N. meningitidis, N. lactamica and N. gonorrhoeae. A few isolates arose from the branch that separated N. meningitidis from N. lactamica leading us to describe these species as 'fuzzy'.A multilocus approach using large samples of closely related isolates delineates species even in the highly recombinogenic human Neisseria where individual loci are inadequate for the task. This approach should be applied by taxonomists to large samples of other groups of closely-related bacteria, and especially to those where species delineation has historically been difficult, to determine whether genotypic clusters can be delineated, and to guide the definition of species.The definition of bacterial species, and a concept of species applicable to all bacteria, are problems that have long exercised systematists and microbiologists [1-4]. While species names have been assigned to groups of organisms sharing many common phenotypic traits, and a certain minimum level of genomic similarity, attempts to define species using DNA sequences have been relatively unsuccessful. The existence of very different levels of sequence diversity among named species, and the variable extent of gene flow within and between bacterial taxa [5], complicates species concepts and definitions. Indeed, for many, bacterial species are constructs of the human mind, arising from our desire to impose order on the bacterial kingdom [6,7], rather than natural subdivisions imposed by underlying genetic processes, and a central question is not so much how species should best be assigned, but whether such entities exist and can be delineated.Molecular approaches to assigning bacteria to species began with the introduction of DNA-DNA hybridization, which allowed an
Within-Host Bacterial Diversity Hinders Accurate Reconstruction of Transmission Networks from Genomic Distance Data
Colin J. Worby ,Marc Lipsitch,William P. Hanage
PLOS Computational Biology , 2014, DOI: doi/10.1371/journal.pcbi.1003549
Abstract: The prospect of using whole genome sequence data to investigate bacterial disease outbreaks has been keenly anticipated in many quarters, and the large-scale collection and sequencing of isolates from cases is becoming increasingly feasible. While sequence data can provide many important insights into disease spread and pathogen adaptation, it remains unclear how successfully they may be used to estimate individual routes of transmission. Several studies have attempted to reconstruct transmission routes using genomic data; however, these have typically relied upon restrictive assumptions, such as a shared topology of the phylogenetic tree and a lack of within-host diversity. In this study, we investigated the potential for bacterial genomic data to inform transmission network reconstruction. We used simulation models to investigate the origins, persistence and onward transmission of genetic diversity, and examined the impact of such diversity on our estimation of the epidemiological relationship between carriers. We used a flexible distance-based metric to provide a weighted transmission network, and used receiver-operating characteristic (ROC) curves and network entropy to assess the accuracy and uncertainty of the inferred structure. Our results suggest that sequencing a single isolate from each case is inadequate in the presence of within-host diversity, and is likely to result in misleading interpretations of transmission dynamics – under many plausible conditions, this may be little better than selecting transmission links at random. Sampling more frequently improves accuracy, but much uncertainty remains, even if all genotypes are observed. While it is possible to discriminate between clusters of carriers, individual transmission routes cannot be resolved by sequence data alone. Our study demonstrates that bacterial genomic distance data alone provide only limited information on person-to-person transmission dynamics.
Bayesian modeling of recombination events in bacterial populations
Pekka Marttinen, Adam Baldwin, William P Hanage, Chris Dowson, Eshwar Mahenthiralingam, Jukka Corander
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-421
Abstract: We introduce a Bayesian spatial structural model representing the continuum of origins over sites within the observed sequences, including a probabilistic characterization of uncertainty related to the origin of any particular site. To enable a statistically accurate and practically feasible approach to the analysis of large-scale data sets representing a single genus, we have developed a novel software tool (BRAT, Bayesian Recombination Tracker) implementing the model and the corresponding learning algorithm, which is capable of identifying the posterior optimal structure and to estimate the marginal posterior probabilities of putative origins over the sites.A multitude of challenging simulation scenarios and an analysis of real data from seven housekeeping genes of 120 strains of genus Burkholderia are used to illustrate the possibilities offered by our approach. The software is freely available for download at URL http://web.abo.fi/fak/mnf//mate/jc/software/brat.html webcite.Statistical approaches to investigating spatial heterogeneity within DNA sequences have attained a considerable interest for decades. However, the foci of such investigations have varied to a large extent from the analysis of spatially heterogeneous base compositions pioneered by works such as [1] and [2], to a kaleidoscope of methods for detecting anomalous evolutionary patterns caused e.g., by gene conversions, viral recombinations etc [3-7]. Here we focus on the statistical discovery of recombinant (homologous or non-homologous) segments within multilocus DNA sequences from bacteria representing heterogeneous populations of fairly closely related species. For a discussion of the various perspectives on the genomic evolution of bacteria, see, e.g. [8-11]. In this article, we use the word population rather loosely to describe a group of related bacteria. This group may correspond for example to a species, or a subgroup of species that is on its way to become a new species (see e.g. [10]). At
Assessing the reliability of eBURST using simulated populations with known ancestry
Katherine ME Turner, William P Hanage, Christophe Fraser, Thomas R Connor, Brian G Spratt
BMC Microbiology , 2007, DOI: 10.1186/1471-2180-7-30
Abstract: For strictly clonal simulations, where all allelic change is due to point mutation, the groups of related strains identified by eBURST were very similar to those expected from the true ancestry and most of the true ancestor-descendant relationships (90–98%) were identified by eBURST. Populations simulated with low or moderate levels of recombination showed similarly high performance but the reliability of eBURST declined with increasing recombination to mutation ratio. Populations simulated under a high recombination to mutation ratio were dominated by a single large straggly eBURST group, which resulted from the incorrect linking of unrelated groups of strains into the same eBURST group. The reliability of the ancestor-descendant links in eBURST diagrams was related to the proportion of strains in the largest eBURST group, which provides a useful guide to when eBURST is likely to be unreliable.Examination of eBURST groups within populations of a range of bacterial species showed that most were within the range in which eBURST is reliable, and only a small number (e.g. Burkholderia pseudomallei and Enterococcus faecium) appeared to have such high rates of recombination that eBURST is likely to be unreliable. The study also demonstrates how three simple tests in eBURST v3 can be used to detect unreliable eBURST performance and recognise populations in which there appears to be a high rate of recombination relative to mutation.In recent years there has been increasing emphasis on the use of digital data to characterise strains of bacterial species. Multiple single nucleotide polymorphisms and multiple variable number tandem repeats have been used for digital strain characterisation of species that genetically are highly uniform [1-5] and multilocus sequence typing (MLST) has been used widely for more variable species [6,7]. In MLST, the relatedness among strains is typically displayed as a dendrogram, based on differences in allelic profiles, which identifies clusters
Low effective dispersal of asexual genotypes in heterogeneous landscapes by the endemic pathogen Penicillium marneffei.
Fisher Matthew C,Hanage William P,de Hoog Sybren,Johnson Elizabeth
PLOS Pathogens , 2005,
Abstract: Long-distance dispersal in microbial eukaryotes has been shown to result in the establishment of populations on continental and global scales. Such "ubiquitous dispersal" has been claimed to be a general feature of microbial eukaryotes, homogenising populations over large scales. However, the unprecedented sampling of opportunistic infectious pathogens created by the global AIDS pandemic has revealed that a number of important species exhibit geographic endemicity despite long-distance migration via aerially dispersed spores. One mechanism that might tend to drive such endemicity in the face of aerial dispersal is the evolution of niche-adapted genotypes when sexual reproduction is rare. Dispersal of such asexual physiological "species" will be restricted when natural habitats are heterogeneous, as a consequence of reduced adaptive variation. Using the HIV-associated endemic fungus Penicillium marneffei as our model, we measured the distribution of genetic variation over a variety of spatial scales in two host species, humans and bamboo rats. Our results show that, despite widespread aerial dispersal, isolates of P. marneffei show extensive spatial genetic structure in both host species at local and country-wide scales. We show that the evolution of the P. marneffei genome is overwhelmingly clonal, and that this is perhaps the most asexual fungus yet found. We show that clusters of genotypes are specific to discrete ecological zones and argue that asexuality has led to the evolution of niche-adapted genotypes, and is driving endemicity, by reducing this pathogen's potential to diversify in nature.
Biomedical Ph.D. Students Enrolled in Two Elite Universities in the United Kingdom and the United States Report Adopting Multiple Learning Relationships
Matthew W. Kemp, Benjamin M. Lazarus, Gabriel G. Perron, William P. Hanage, Elaine Chapman
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0103075
Abstract: Objective The ability to form multiple learning relationships is a key element of the doctoral learning environment in the biomedical sciences. Of these relationships, that between student and supervisor has long been viewed as key. There are, however, limited data to describe the student perspective on what makes this relationship valuable. In the present study, we discuss the findings of semi-structured interviews with biomedical Ph.D. students from the United Kingdom and the United States to: i) determine if the learning relationships identified in an Australian biomedical Ph.D. cohort are also important in a larger international student cohort; and ii) improve our understanding of student perceptions of value in their supervisory relationships. Study Design 32 students from two research intensive universities, one in the United Kingdom (n = 17), and one in the United States (n = 15) were recruited to participate in a semi-structured interview. Verbatim transcripts were transcribed, validated and analysed using a Miles and Huberman method for thematic analysis. Results Students reported that relationships with other Ph.D. students, post-doctoral scientists and supervisors were all essential to their learning. Effective supervisory relationships were perceived as the primary source of high-level project guidance, intellectual support and confidence. Relationships with fellow students were viewed as essential for the provision of empathetic emotional support. Technical learning was facilitated, almost exclusively, by relationships with postdoctoral staff. Conclusions These data make two important contributions to the scholarship of doctoral education in the biomedical sciences. Firstly, they provide further evidence for the importance of multiple learning relationships in the biomedical doctorate. Secondly, they clarify the form of a ‘valued’ supervisory relationship from a student perspective. We conclude that biomedical doctoral programs should be designed to contain a minimum level of formalised structure to promote the development of multiple learning relationships that are perceived as key to student learning.
Low Effective Dispersal of Asexual Genotypes in Heterogeneous Landscapes by the Endemic Pathogen Penicillium marneffei
Matthew C Fisher ,William P Hanage,Sybren de Hoog,Elizabeth Johnson,Michael D Smith,Nicholas J White,Nongnuch Vanittanakom
PLOS Pathogens , 2005, DOI: 10.1371/journal.ppat.0010020
Abstract: Long-distance dispersal in microbial eukaryotes has been shown to result in the establishment of populations on continental and global scales. Such “ubiquitous dispersal” has been claimed to be a general feature of microbial eukaryotes, homogenising populations over large scales. However, the unprecedented sampling of opportunistic infectious pathogens created by the global AIDS pandemic has revealed that a number of important species exhibit geographic endemicity despite long-distance migration via aerially dispersed spores. One mechanism that might tend to drive such endemicity in the face of aerial dispersal is the evolution of niche-adapted genotypes when sexual reproduction is rare. Dispersal of such asexual physiological “species” will be restricted when natural habitats are heterogeneous, as a consequence of reduced adaptive variation. Using the HIV-associated endemic fungus Penicillium marneffei as our model, we measured the distribution of genetic variation over a variety of spatial scales in two host species, humans and bamboo rats. Our results show that, despite widespread aerial dispersal, isolates of P. marneffei show extensive spatial genetic structure in both host species at local and country-wide scales. We show that the evolution of the P. marneffei genome is overwhelmingly clonal, and that this is perhaps the most asexual fungus yet found. We show that clusters of genotypes are specific to discrete ecological zones and argue that asexuality has led to the evolution of niche-adapted genotypes, and is driving endemicity, by reducing this pathogen's potential to diversify in nature.
Assigning strains to bacterial species via the internet
Cynthia J Bishop, David M Aanensen, Gregory E Jordan, Mogens Kilian, William P Hanage, Brian G Spratt
BMC Biology , 2009, DOI: 10.1186/1741-7007-7-3
Abstract: Seven house-keeping gene sequences were obtained from 420 streptococcal strains to produce a viridans group database. The reference tree produced using the concatenated sequences identified sequence clusters which, by examining the position on the tree of the type strain of each viridans group species, could be equated with species clusters. MLSA also identified clusters that may correspond to new species, and previously described species whose status needs to be re-examined. A generic website and software for electronic taxonomy was developed. This site http://www.eMLSA.net webcite allows the sequences of the seven gene fragments of a query strain to be entered and for the species assignment to be returned, according to its position within an assigned species cluster on the reference tree.The MLSA approach resulted in the identification of well-resolved species clusters within this taxonomically challenging group and, using the software we have developed, allows unknown strains to be assigned to viridans species via the internet. Submission of new strains will provide a growing resource for the taxonomy of viridans group streptococci, allowing the recognition of potential new species and taxonomic anomalies. More generally, as the software at the MLSA website is generic, MLSA schemes and strain databases for other groups of related species can be hosted at this website, providing a portal for microbial electronic taxonomy.The methods used to assign strains to bacterial species, and the definition of species, have been much debated [1-4]. There is widespread recognition that the current methods of defining prokaryotic species are no longer adequate and there has been little progress in developing an agreed concept of species that can guide a new definition of species [5-7]. The current approach for distinguishing species within a genus, and for defining new species, is based on polyphasic taxonomy, which incorporates all available phenotypic and genotypic data into
Historical Zoonoses and Other Changes in Host Tropism of Staphylococcus aureus, Identified by Phylogenetic Analysis of a Population Dataset
Marcus A. Shepheard, Vicki M. Fleming, Thomas R. Connor, Jukka Corander, Edward J. Feil, Christophe Fraser, William P. Hanage
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0062369
Abstract: Background Staphylococcus aureus exhibits tropisms to many distinct animal hosts. While spillover events can occur wherever there is an interface between host species, changes in host tropism only occur with the establishment of sustained transmission in the new host species, leading to clonal expansion. Although the genomic variation underpinning adaptation in S. aureus genotypes infecting bovids and poultry has been well characterized the frequency of switches from one host to another remains obscure. We sought to identify sustained switches in host tropism in the S. aureus population, both anthroponotic and zoonotic, and their distribution over the species phylogeny. Methodologies/Results We have used a sample of 3042 isolates, representing 696 distinct MLST genotypes, from a well-established database (www.mlst.net). Using an empirical parsimony approach (AdaptML) we have investigated the distribution of switches in host association between both human and non-human (henceforth referred to as animal) hosts. We reconstructed a credible description of past events in the form of a phylogenetic tree; the nodes and leaves of which are statistically associated with either human or animal habitats, estimated from extant host-association and the degree of sequence divergence between genotypes. We identified 15 likely historical switching events; 13 anthroponoses and two zoonoses. Importantly, we identified two human-associated clade candidates (CC25 and CC59) that have arisen from animal-associated ancestors; this demonstrates that a human-specific lineage can emerge from an animal host. We also highlight novel rabbit-associated genotypes arising from a human ancestor. Conclusions S. aureus is an organism with the capacity to switch into and adapt to novel hosts, even after long periods of isolation in a single host species. Based on this evidence, animal-adapted S. aureus lineages exhibiting resistance to antibiotics must be considered a major threat to public health, as they can adapt to the human population.
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