Phylodynamics and Human-Mediated Dispersal of a Zoonotic Virus

Talbi, Chiraz; Lemey, Philippe; Suchard, Marc A.; Abdelatif, Elbia; Elharrak, Mehdi; Nourlil, Jalal; Faouzi, Abdellah; Echevarrı́a, Juan E.; Vázquez-Morón, Sonia; Rambaut, Andrew; Campiz, Nicholas; Tatem, Andrew J.; Holmes, Edward C.; Bourhy, Hervé

doi:10.1371/journal.ppat.1001166

Cited by 135 publications

(183 citation statements)

References 44 publications

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“…Lineage movements occurring on branches representing short evolutionary times, such as those identified between Serengeti and Morogoro (>750 km), indicate rates of dispersal much higher than those recorded for endemic wildlife rabies (Biek 2007) and imply human mediated movements as seen in parts of North Africa (Talbi et al. 2010).…”

Section: Discussionmentioning

confidence: 99%

Elucidating the phylodynamics of endemic rabies virus in eastern Africa using whole-genome sequencing

et al. 2015

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Many of the pathogens perceived to pose the greatest risk to humans are viral zoonoses, responsible for a range of emerging and endemic infectious diseases. Phylogeography is a useful tool to understand the processes that give rise to spatial patterns and drive dynamics in virus populations. Increasingly, whole-genome information is being used to uncover these patterns, but the limits of phylogenetic resolution that can be achieved with this are unclear. Here, whole-genome variation was used to uncover fine-scale population structure in endemic canine rabies virus circulating in Tanzania. This is the first whole-genome population study of rabies virus and the first comprehensive phylogenetic analysis of rabies virus in East Africa, providing important insights into rabies transmission in an endemic system. In addition, sub-continental scale patterns of population structure were identified using partial gene data and used to determine population structure at larger spatial scales in Africa. While rabies virus has a defined spatial structure at large scales, increasingly frequent levels of admixture were observed at regional and local levels. Discrete phylogeographic analysis revealed long-distance dispersal within Tanzania, which could be attributed to human-mediated movement, and we found evidence of multiple persistent, co-circulating lineages at a very local scale in a single district, despite on-going mass dog vaccination campaigns. This may reflect the wider endemic circulation of these lineages over several decades alongside increased admixture due to human-mediated introductions. These data indicate that successful rabies control in Tanzania could be established at a national level, since most dispersal appears to be restricted within the confines of country borders but some coordination with neighbouring countries may be required to limit transboundary movements. Evidence of complex patterns of rabies circulation within Tanzania necessitates the use of whole-genome sequencing to delineate finer scale population structure that can that can guide interventions, such as the spatial scale and design of dog vaccination campaigns and dog movement controls to achieve and maintain freedom from disease.

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Section: Discussionmentioning

confidence: 99%

Elucidating the phylodynamics of endemic rabies virus in eastern Africa using whole-genome sequencing

et al. 2015

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“…was used (Drummond et al, 2012) with the GTR model, a relaxed uncorrelated Lognormal molecular clock model (Drummond et al, 2006) and a Skygrid coalescent tree prior (Gill et al, 2013). To evaluate the early dispersal and the most important migrations, a discrete phylogeographic model was applied using Bayesian Stochastic Search Variable Selection (BSSVS) analyses and the robust counting approach (Edwards et al, 2011; Lemey et al, 2009; Minin et al, 2008; O'Brien et al, 2009; Talbi et al, 2010). The MCMC chains were run for 100 million generations at least three times with a burn-in of 10%.…”

Section: Methodsmentioning

confidence: 99%

On the contribution of Angola to the initial spread of HIV-1

Pineda-Peña

Varanda

Sousa

et al. 2016

Infection, Genetics and Evolution

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Angola borders and has long-term links with Democratic Republic of Congo (DRC) as well as high levels of Human Immunodeficiency virus (HIV) genetic diversity, indicating a potential role in the initial spread of the HIV-1 pandemic. Herein, we analyze 564 C2V3 and 354 pol publicly available sequences from DRC, Republic of Congo (RC) and Angola to better understand the initial spread of the virus in this region. Phylogeographic analyses were performed with the BEAST software and migration records from the first half of the 20th century in DRC were collected from colonial archives. While our results pinpoint the origin of the pandemic to Kinshasa (DRC) around 1906, our results indicate that the introduction of HIV-1 to Angola could have occurred early between 1910 and 1930. Furthermore, most of the initial HIV-1 migrations out of Kinshasa were directed not only to Lubumbashi (DRC), but also to Angola and Brazzaville. Migration records corroborate these findings, indicating that the early exportation of the virus to Angola might be related to the high number of Angolan immigrants in Kinshasa at that time, originated mostly from the North of Angola. In summary, our results place Angola at the epicenter of early HIV dissemination, together with DRC and RC.

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“…Analyses were performed under a GTR + I + G nucleotide substitution model, a Bayesian skyline coalescence model (Drummond et al, 2002, Drummond et al, 2005, a relaxed uncorrelated lognormal molecular clock model (Drummond et al, 2006), and a reversible discrete Bayesian phylogeographic model with a continuous-time Markov chain (CTMC) rate reference prior (Ferreira and Suchard, 2008). The number of viral migrations between locations was estimated using 'Markov Jump' counts Suchard, 2008a, 2008b) of location-state transitions along the posterior tree distribution as previously described (Nunes et al, 2012;Talbi et al, 2010). MCMC chains were run for 1-25 × 10 7 generations.…”

Section: Evolutionary and Phylogeographic Analysesmentioning

confidence: 99%