Identification of enterotoxigenic Escherichia coli (ETEC) clades with long-term global distribution

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Enterotoxigenic Escherichia coli (ETEC), a major cause of infectious diarrhea, produce heat-stable and/or heat-labile enterotoxins and at least 25 different colonization factors that target the intestinal mucosa. The genes encoding the enterotoxins and most of the colonization factors are located on plasmids found across diverse E. coli serogroups. Whole-genome sequencing of a representative collection of ETEC isolated between 1980 and 2011 identified globally distributed lineages characterized by distinct colonization factor and enterotoxin profiles. Contrary to current notions, these relatively recently emerged lineages might harbor chromosome and plasmid combinations that optimize fitness and transmissibility. These data have implications for understanding, tracking and possibly preventing ETEC disease.

Related collections

Most cited references 33

Record: found
Abstract: found
Article: found

Is Open Access

Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations

Jukka Corander, Pekka Marttinen, Jukka Sirén … (2008)

Background During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have appeared in the scientific literature. Most of these methods utilize molecular markers for the inferences, while some are also capable of handling DNA sequence data. In a number of earlier works, we have introduced an array of statistical methods for population genetic inference that are implemented in the software BAPS. However, the complexity of biological problems related to genetic structure analysis keeps increasing such that in many cases the current methods may provide either inappropriate or insufficient solutions. Results We discuss the necessity of enhancing the statistical approaches to face the challenges posed by the ever-increasing amounts of molecular data generated by scientists over a wide range of research areas and introduce an array of new statistical tools implemented in the most recent version of BAPS. With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model. Also, alleles representing a different ancestry compared to the average observed genomic positions can be tracked for the sampled individuals, and a priori specified hypotheses about genetic population structure can be directly compared using Bayes' theorem. In general, we have improved further the computational characteristics of the algorithms behind the methods implemented in BAPS facilitating the analyses of large and complex datasets. In particular, analysis of a single dataset can now be spread over multiple computers using a script interface to the software. Conclusion The Bayesian modelling methods introduced in this article represent an array of enhanced tools for learning the genetic structure of populations. Their implementations in the BAPS software are designed to meet the increasing need for analyzing large-scale population genetics data. The software is freely downloadable for Windows, Linux and Mac OS X systems at .

0 comments Cited 319 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Hierarchical and Spatially Explicit Clustering of DNA Sequences with BAPS Software

Tain-Lu Cheng, Thomas R. Connor, Jukka Sirén … (2013)

Phylogeographical analyses have become commonplace for a myriad of organisms with the advent of cheap DNA sequencing technologies. Bayesian model-based clustering is a powerful tool for detecting important patterns in such data and can be used to decipher even quite subtle signals of systematic differences in molecular variation. Here, we introduce two upgrades to the Bayesian Analysis of Population Structure (BAPS) software, which enable 1) spatially explicit modeling of variation in DNA sequences and 2) hierarchical clustering of DNA sequence data to reveal nested genetic population structures. We provide a direct interface to map the results from spatial clustering with Google Maps using the portal http://www.spatialepidemiology.net/ and illustrate this approach using sequence data from Borrelia burgdorferi. The usefulness of hierarchical clustering is demonstrated through an analysis of the metapopulation structure within a bacterial population experiencing a high level of local horizontal gene transfer. The tools that are introduced are freely available at http://www.helsinki.fi/bsg/software/BAPS/.

0 comments Cited 308 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Population genomics of post-vaccine changes in pneumococcal epidemiology

Nicholas Croucher, Jonathan A. Finkelstein, Stephen I. Pelton … (2013)

Whole genome sequencing of 616 asymptomatically carried pneumococci was used to study the impact of the 7-valent pneumococcal conjugate vaccine. Comparison of closely related isolates revealed the role of transformation in facilitating capsule switching to non-vaccine serotypes and the emergence of drug resistance. However, such recombination was found to occur at significantly different rates across the species, and the evolution of the population was primarily driven by changes in the frequency of distinct genotypes extant pre-vaccine. These alterations resulted in little overall effect on accessory genome composition at the population level, contrasting with the fall in pneumococcal disease rates after the vaccine’s introduction.