Genomic history of the seventh pandemic of cholera in Africa

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Abstract

The seventh cholera pandemic has heavily affected Africa, although the origin and continental spread of the disease remain undefined. We used genomic data from 1070 Vibrio cholerae O1 isolates, across 45 African countries and over a 49-year period, to show that past epidemics were attributable to a single expanded lineage. This lineage was introduced at least 11 times since 1970, into two main regions, West Africa and East/Southern Africa, causing epidemics that lasted up to 28 years. The last five introductions into Africa, all from Asia, involved multidrug-resistant sublineages that replaced antibiotic-susceptible sublineages after 2000. This phylogenetic framework describes the periodicity of lineage introduction and the stable routes of cholera spread, which should inform the rational design of control measures for cholera in Africa.

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Improving the accuracy of demographic and molecular clock model comparison while accommodating phylogenetic uncertainty.

Guy Baele, Philippe Lemey, Trevor Bedford … (2012)

Recent developments in marginal likelihood estimation for model selection in the field of Bayesian phylogenetics and molecular evolution have emphasized the poor performance of the harmonic mean estimator (HME). Although these studies have shown the merits of new approaches applied to standard normally distributed examples and small real-world data sets, not much is currently known concerning the performance and computational issues of these methods when fitting complex evolutionary and population genetic models to empirical real-world data sets. Further, these approaches have not yet seen widespread application in the field due to the lack of implementations of these computationally demanding techniques in commonly used phylogenetic packages. We here investigate the performance of some of these new marginal likelihood estimators, specifically, path sampling (PS) and stepping-stone (SS) sampling for comparing models of demographic change and relaxed molecular clocks, using synthetic data and real-world examples for which unexpected inferences were made using the HME. Given the drastically increased computational demands of PS and SS sampling, we also investigate a posterior simulation-based analogue of Akaike's information criterion (AIC) through Markov chain Monte Carlo (MCMC), a model comparison approach that shares with the HME the appealing feature of having a low computational overhead over the original MCMC analysis. We confirm that the HME systematically overestimates the marginal likelihood and fails to yield reliable model classification and show that the AICM performs better and may be a useful initial evaluation of model choice but that it is also, to a lesser degree, unreliable. We show that PS and SS sampling substantially outperform these estimators and adjust the conclusions made concerning previous analyses for the three real-world data sets that we reanalyzed. The methods used in this article are now available in BEAST, a powerful user-friendly software package to perform Bayesian evolutionary analyses.

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Updated Global Burden of Cholera in Endemic Countries

Mohammad Alauddin Mohammad Ali, Allyson Nelson, Anna Lena Lopez … (2015)

Background The global burden of cholera is largely unknown because the majority of cases are not reported. The low reporting can be attributed to limited capacity of epidemiological surveillance and laboratories, as well as social, political, and economic disincentives for reporting. We previously estimated 2.8 million cases and 91,000 deaths annually due to cholera in 51 endemic countries. A major limitation in our previous estimate was that the endemic and non-endemic countries were defined based on the countries’ reported cholera cases. We overcame the limitation with the use of a spatial modelling technique in defining endemic countries, and accordingly updated the estimates of the global burden of cholera. Methods/Principal Findings Countries were classified as cholera endemic, cholera non-endemic, or cholera-free based on whether a spatial regression model predicted an incidence rate over a certain threshold in at least three of five years (2008-2012). The at-risk populations were calculated for each country based on the percent of the country without sustainable access to improved sanitation facilities. Incidence rates from population-based published studies were used to calculate the estimated annual number of cases in endemic countries. The number of annual cholera deaths was calculated using inverse variance-weighted average case-fatality rate (CFRs) from literature-based CFR estimates. We found that approximately 1.3 billion people are at risk for cholera in endemic countries. An estimated 2.86 million cholera cases (uncertainty range: 1.3m-4.0m) occur annually in endemic countries. Among these cases, there are an estimated 95,000 deaths (uncertainty range: 21,000-143,000). Conclusion/Significance The global burden of cholera remains high. Sub-Saharan Africa accounts for the majority of this burden. Our findings can inform programmatic decision-making for cholera control.

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Artemis and ACT: viewing, annotating and comparing sequences stored in a relational database

Tim Carver, Matthew Berriman, Adrian Tivey … (2008)

Motivation: Artemis and Artemis Comparison Tool (ACT) have become mainstream tools for viewing and annotating sequence data, particularly for microbial genomes. Since its first release, Artemis has been continuously developed and supported with additional functionality for editing and analysing sequences based on feedback from an active user community of laboratory biologists and professional annotators. Nevertheless, its utility has been somewhat restricted by its limitation to reading and writing from flat files. Therefore, a new version of Artemis has been developed, which reads from and writes to a relational database schema, and allows users to annotate more complex, often large and fragmented, genome sequences. Results: Artemis and ACT have now been extended to read and write directly to the Generic Model Organism Database (GMOD, http://www.gmod.org) Chado relational database schema. In addition, a Gene Builder tool has been developed to provide structured forms and tables to edit coordinates of gene models and edit functional annotation, based on standard ontologies, controlled vocabularies and free text. Availability: Artemis and ACT are freely available (under a GPL licence) for download (for MacOSX, UNIX and Windows) at the Wellcome Trust Sanger Institute web sites: http://www.sanger.ac.uk/Software/Artemis/ http://www.sanger.ac.uk/Software/ACT/ Contact: artemis@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.