Phylogenetically resolving epidemiologic linkage

Romero-Severson, Ethan; Bulla, Ingo; Leitner, Thomas

doi:10.1073/pnas.1522930113

Cited by 94 publications

(143 citation statements)

References 54 publications

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“…The nature of HIV evolution 23 (both within and between hosts) and the lack of an external reference 29 (root) in distance defined networks, prevents determination of the direction of transmission or whether transmission events proceeded directly between participants or via a third party. However, distance defined transmission networks do allow us to recognize closely related strains and the subpopulation(s) within which they are observed, 30 Figure 2.…”

Section: Discussionmentioning

confidence: 99%

HIV-1 Genetic Diversity Among Incident Infections in Mbeya, Tanzania

Billings

Sanders‐Buell

Bose

et al. 2017

AIDS Research and Human Retroviruses

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In preparation for vaccine trials, HIV-1 genetic diversity was surveyed between 2002 and 2006 through the Cohort Development study in the form of a retrospective and prospective observational study in and around the town of Mbeya in Tanzania's Southwest Highlands. This study describes the molecular epidemiology of HIV-1 strains obtained from 97 out of 106 incident HIV-1 infections identified in three subpopulations of participants (one rural, two urban) from the Mbeya area. Near full-genome or half-genome sequencing showed a subtype distribution of 40% C, 17% A1, 1% D, and 42% inter-subtype recombinants. Compared to viral subtyping results previously obtained from the retrospective phase of this study, the overall proportion of incident viral strains did not change greatly during the study course, suggesting maturity of the epidemic. A comparison to a current Phase I-II vaccine being tested in Africa shows ∼17% amino acid sequence difference between the gp120 of the vaccine and subtype C incident strains. Phylogenetic and recombinant breakpoint analysis of the incident strains revealed the emergence of CRF41_CD and many unique recombinants, as well as the presence of six local transmission networks most of which were confined to the rural subpopulation. In the context of vaccine cohort selection, these results suggest distinct infection transmission dynamics within these three geographically close subpopulations. The diversity and genetic sequences of the HIV-1 strains obtained during this study will greatly contribute to the planning, immunogen selection, and analysis of vaccine-induced immune responses observed during HIV-1 vaccine trials in Tanzania and neighboring countries.

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Section: Discussionmentioning

confidence: 99%

HIV-1 Genetic Diversity Among Incident Infections in Mbeya, Tanzania

Billings

Sanders‐Buell

Bose

et al. 2017

AIDS Research and Human Retroviruses

View full text Add to dashboard Cite

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“…Also, HIV transmission histories could be correctly inferred by phylogenetic methods . This remains an area of active investigation …”

Section: Selection As a Potential Confounder In Phyloanatomical Analysismentioning

confidence: 99%

“…98 This remains an area of active investigation. [99][100][101] Selection pressures have been found to differ between anatomical compartments. The most extreme form of differing selection pressures arise when specific mutations are required to invade a compartment.…”

Section: S Elec Ti On a S A P Otential Confounder In Phyloanatomic mentioning

confidence: 99%

Virus dynamics and phyloanatomy: Merging population dynamic and phylogenetic approaches

Bons

Regoes

2018

Immunological Reviews

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In evolutionary biology and epidemiology, phylodynamic methods are widely used to infer population biological characteristics, such as the rates of replication, death, migration, or, in the epidemiological context, pathogen spread. More recently, these methods have been used to elucidate the dynamics of viruses within their hosts. Especially the application of phylogeographic approaches has the potential to shed light on anatomical colonization pathways and the exchange of viruses between distinct anatomical compartments. We and others have termed this phyloanatomy. Here, we review the promise and challenges of phyloanatomy, and compare them to more classical virus dynamics and population genetic approaches. We argue that the extremely strong selection pressures that exist within the host may represent the main obstacle to reliable phyloanatomic analysis.

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“…By understanding disease transmission, those investigating a disease can more effectively combat its spread. Computational methods for molecular epidemiology have had a positive impact on public health in a number of cases [2,3], and continue to be used for the study of infectious disease transmission [4].…”

Section: Introductionmentioning

confidence: 99%

TreeFix-TP: Phylogenetic Error-Correction for Infectious Disease Transmission Network Inference

Sledzieski

Zhang

Măndoiu

et al. 2019

Preprint

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Background: Many existing methods for estimation of infectious disease transmission networks use a phylogeny of the infecting strains as the basis for transmission network inference, and accurate network inference relies on accuracy of this underlying evolutionary history. However, phylogenetic reconstruction can be highly error prone and more sophisticated methods can fail to scale to larger outbreaks, negatively impacting downstream transmission network inference. Additionally, there are no currently available methods which are able to use within-host diversity to improve phylogenetic reconstruction. Results: We introduce a new method, TreeFix-TP, for accurate and scalable reconstruction of transmission phylogenies based on an error-correction framework. Our method uses intra-host strain diversity and host information to balance a parsimonious evaluation of the implied transmission network with statistical hypothesis testing on sequence data likelihood. The reconstructed tree minimizes the number of required disease transmissions while being as well supported by sequence data as the maximum likelihood phylogeny. We use a simulation framework for viral transmission and evolution to demonstrate that TreeFix-TP improves phylogenetic accuracy and downstream transmission network accuracy. We also use real data from ten HCV outbreaks and demonstrate how error-correction improves source detection. Conclusions:Our results show that using TreeFix-TP can lead to significant improvement in transmission phylogeny inference and that its performance is robust to variations in transmission and evolutionary parameters. Our experiments also demonstrate the importance of sampling multiple strain sequences from each infected host for accurate transmission network inference. TreeFix-TP is freely available open-source from https://compbio.engr.uconn.edu/software/treefix-tp/.

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Phylogenetically resolving epidemiologic linkage

Cited by 94 publications

References 54 publications

HIV-1 Genetic Diversity Among Incident Infections in Mbeya, Tanzania

HIV-1 Genetic Diversity Among Incident Infections in Mbeya, Tanzania

Virus dynamics and phyloanatomy: Merging population dynamic and phylogenetic approaches

TreeFix-TP: Phylogenetic Error-Correction for Infectious Disease Transmission Network Inference

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