scholarly journals Inference of Transmission Network Structure from HIV Phylogenetic Trees

2016 ◽  
Author(s):  
Federica Giardina ◽  
Ethan Obie Romero-Severson ◽  
Jan Albert ◽  
Tom Britton ◽  
Thomas Leitner
Keyword(s):  
Phylogenetic Trees ◽  
Evolutionary Process ◽  
Evolutionary Model ◽  
Network Models ◽  
Patient Specific ◽  
Contact Network ◽  
Contact Networks ◽  
Different Types ◽  
Approximate Bayesian ◽  
Hiv 1

AbstractPhylogenetic inference is an attractive mean to reconstruct transmission histories and epidemics. As the interest lies in how HIV-1 spread in a human population, many previous studies have ignored details about the evolutionary process of the pathogen. Because phylogenetics investigates the evolutionary history of the pathogen rather than the spread between hosts per se, we first investigated the effects of including a within-host evolutionary model in epidemiological simulations. In particular, we investigated if the resulting phvlogenv could recover different types of contact networks. To further improve realism, we also introduced patient-specific differences in infectivitv across disease stages, and on the epidemic level we considered incomplete sampling and the age of the epidemic. Second, we implemented an inference method based on approximate Bayesian computation (ABC) to discriminate among three well-studied network models and jointly estimate both network parameters and key epidemiological quantities such as the infection rate. Our ABC framework used both topological and distance-based tree statistics for comparison between simulated and observed trees. Overall, our simulations showed that a virus time-scaled phvlogenv (genealogy) may be substantially different from the between-host transmission tree. This has important implications for the interpretation of what a phvlogenv reveals about the underlying epidemic contact network. In particular, we found that while the within-host evolutionary process obscures the transmission tree, the diversification process and infectivitv dynamics also add discriminatory power to differentiate between different types of contact networks. We also found that the possibility to differentiate contact networks depends on how far an epidemic has progressed, where distance-based tree statistics have more power early in an epidemic. Finally, we applied our ABC inference on two different outbreaks from the Swedish HIV-1 epidemic.

Advances from the nexus of animal behaviour and pathogen transmission: new directions and opportunities using contact networks

Behaviour ◽  
2018 ◽  
Vol 155 (7-9) ◽  
pp. 567-583 ◽  
Author(s):  
Stephan T. Leu ◽  
Stephanie S. Godfrey
Keyword(s):  
High Resolution ◽  
Disease Transmission ◽  
Network Models ◽  
Population Level ◽  
Pathogen Transmission ◽  
Molecular Techniques ◽  
Gps Tracking ◽  
Contact Network ◽  
Computational Techniques ◽  
Contact Networks

Abstract Contact network models have enabled significant advances in understanding the influence of behaviour on parasite and pathogen transmission. They are an important tool that links variation in individual behaviour, to epidemiological consequences at the population level. Here, in our introduction to this special issue, we highlight the importance of applying network approaches to disease ecological and epidemiological questions, and how this has provided a much deeper understanding of these research areas. Recent advances in tracking host behaviour (bio-logging: e.g., GPS tracking, barcoding) and tracking pathogens (high-resolution sequencing), as well as methodological advances (multi-layer networks, computational techniques) started producing exciting new insights into disease transmission through contact networks. We discuss some of the exciting directions that the field is taking, some of the challenges, and importantly the opportunities that lie ahead. For instance, we suggest to integrate multiple transmission pathways, multiple pathogens, and in some systems, multiple host species, into the next generation of network models. Corresponding opportunities exist in utilising molecular techniques, such as high-resolution sequencing, to establish causality in network connectivity and disease outcomes. Such novel developments and the continued integration of network tools offers a more complete understanding of pathogen transmission processes, their underlying mechanisms and their evolutionary consequences.

scholarly journals Reconstructing contact network parameters from viral phylogenies

2016 ◽  
Author(s):  
Rosemary M. McCloskey ◽  
Richard H. Liang ◽  
Art F.Y. Poon
Keyword(s):  
Sequential Monte Carlo ◽  
Preferential Attachment ◽  
Structural Parameters ◽  
Simulated Data ◽  
Network Models ◽  
Similarity Score ◽  
Contact Network ◽  
Parameter Estimates ◽  
Human Populations ◽  
Approximate Bayesian

AbstractModels of the spread of disease in a population often make the simplifying assumption that the population is homogeneously mixed, or is divided into homogeneously mixed compartments. However, human populations have complex structures formed by social contacts, which can have a significant influence on the rate of epidemic spread. Contact network models capture this structure by explicitly representing each contact which could possibly lead to a transmission. We developed a method based on kernel approximate Bayesian computation (kernel-ABC) for estimating structural parameters of the contact network underlying an observed viral phylogeny. The method combines adaptive sequential Monte Carlo for ABC, Gillespie simulation for propagating epidemics though networks, and a kernel-based tree similarity score. We used the method to fit the Barabási-Albert network model to simulated transmission trees, and also applied it to viral phylogenies estimated from five published HIV sequence datasets. On simulated data, we found that the preferential attachment power and the number of infected nodes in the network can often be accurately estimated. On the other hand, the mean degree of the network, as well as the total number of nodes, were not estimable with kernel-ABC. We observed substantial heterogeneity in the parameter estimates on real datasets, with point estimates for the preferential attachment power ranging from 0.06 to 1.05. These results underscore the importance of considering contact structures when performing phylodynamic inference. Our method offers the potential to quantitatively investigate the contact network structure underlying viral epidemics.

The identification of a novel HIV-1 second-generation recombinant form (CRF01_AE/CRF07_BC) among men who have sex with men in Jiangsu, China

2020 ◽  
Vol 18 ◽  
Author(s):  
Yin Yueqi ◽  
Zhou Ying ◽  
Lu Jing ◽  
Guo Hongxiong ◽  
Chen Jianshuang ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Phylogenetic Trees ◽  
Second Generation ◽  
Emergency Situation ◽  
The World ◽  
Break Points ◽  
Sex With Men ◽  
Full Length Genome ◽  
Virus Strains ◽  
Hiv 1

Background: CRF01_AE and CRF07_BC are the two major HIV-1 virus strains circulating in China. The proportion of dominant subtypes (CRF01_AE and CRF07_BC) among MSM in Jiangsu province was over 80%. A large number of URFs have been found in China in recently years. Objective: This study aimed to report on novel HIV-1 recombinants. Method: We constructed Phylogenetic trees using the maximum likelihood (ML) method with 1000 bootstrap replicates in IQ-TREE 1.6.8 software and determined recombination break points using SimPlot 3.5.1. Results: We identified a novel, second-generation HIV-1 recombinant (JS020202) between CRF01_AE and CRF07_BC. The analysis of near full-length genome (NFLG) showed there were at least 8 breakpoints inner virus, which differed from any previously identified CRF and URF around the world. Conclusion: Novel diverse CRF01_AE/07_BC suggested the complexity trends of HIV-1 genetics. The emergency situation of diverse recombinant strains should be monitored continuously.

scholarly journals The role of diversity and tolerance in economic development

2021 ◽  
Author(s):  
Witold Kwasnicki
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Industrial Development ◽  
Evolutionary Process ◽  
Evolutionary Model ◽  
Industry Development ◽  
Radical Innovations ◽  
Long Run

AbstractThis paper presents an evolutionary model of industry development, and uses simulations to investigation the role of diversity and heterogeneity in firms’ behaviour, and hence industrial development. The simulations suggest that economic growth is increased with greater variety, in the sense of the evolutionary process approaching the equilibrium faster and also, in the long run, moving faster from one equilibrium to a new, more advanced, equilibrium. This occurs due to higher variety caused by a more tolerant environment, and due to the higher probability of emergence of radical innovations.

scholarly journals Application of Biomimetics to Architectural and Urban Design: A Review across Scales

2020 ◽  
Vol 12 (23) ◽  
pp. 9813 ◽  
Author(s):  
Yuta Uchiyama ◽  
Eduardo Blanco ◽  
Ryo Kohsaka
Keyword(s):  
Urban Design ◽  
Architectural Design ◽  
Evolutionary Process ◽  
Future Research ◽  
Conceptual Level ◽  
Sustainable Society ◽  
Types Of Knowledge ◽  
The Social ◽  
Different Types ◽  
Shed Light

Application of biomimetics has expanded progressively to other fields in recent years, including urban and architectural design, scaling up from materials to a larger scale. Besides its contribution to design and functionality through a long evolutionary process, the philosophy of biomimetics contributes to a sustainable society at the conceptual level. The aim of this review is to shed light on trends in the application of biomimetics to architectural and urban design, in order to identify potential issues and successes resulting from implementation. In the application of biomimetics to architectural design, parts of individual “organisms”, including their form and surface structure, are frequently mimicked, whereas in urban design, on a larger scale, biomimetics is applied to mimic whole ecosystems. The overall trends of the reviewed research indicate future research necessity in the field of on biomimetic application in architectural and urban design, including Biophilia and Material. As for the scale of the applications, the urban-scale research is limited and it is a promising research which can facilitate the social implementation of biomimetics. As for facilitating methods of applications, it is instrumental to utilize different types of knowledge, such as traditional knowledge, and providing scientific clarification of functions and systems based on reviews. Thus, interdisciplinary research is required additionally to reach such goals.

scholarly journals Aminoacyl-tRNA Synthetases, the Genetic Code, and the Evolutionary Process

2000 ◽  
Vol 64 (1) ◽  
pp. 202-236 ◽  
Author(s):  
Carl R. Woese ◽  
Gary J. Olsen ◽  
Michael Ibba ◽  
Dieter Söll
Keyword(s):  
Genetic Code ◽  
Phylogenetic Trees ◽  
Genetic Material ◽  
Evolutionary Process ◽  
Group Iv ◽  
Evolutionary Relationships ◽  
Evolutionary Stage ◽  
Trna Synthetases ◽  
Aminoacyl Trna Synthetases ◽  
The Individual

SUMMARY The aminoacyl-tRNA synthetases (AARSs) and their relationship to the genetic code are examined from the evolutionary perspective. Despite a loose correlation between codon assignments and AARS evolutionary relationships, the code is far too highly structured to have been ordered merely through the evolutionary wanderings of these enzymes. Nevertheless, the AARSs are very informative about the evolutionary process. Examination of the phylogenetic trees for each of the AARSs reveals the following. (i) Their evolutionary relationships mostly conform to established organismal phylogeny: a strong distinction exists between bacterial- and archaeal-type AARSs. (ii) Although the evolutionary profiles of the individual AARSs might be expected to be similar in general respects, they are not. It is argued that these differences in profiles reflect the stages in the evolutionary process when the taxonomic distributions of the individual AARSs became fixed, not the nature of the individual enzymes. (iii) Horizontal transfer of AARS genes between Bacteria and Archaea is asymmetric: transfer of archaeal AARSs to the Bacteria is more prevalent than the reverse, which is seen only for the “gemini group.” (iv) The most far-ranging transfers of AARS genes have tended to occur in the distant evolutionary past, before or during formation of the primary organismal domains. These findings are also used to refine the theory that at the evolutionary stage represented by the root of the universal phylogenetic tree, cells were far more primitive than their modern counterparts and thus exchanged genetic material in far less restricted ways, in effect evolving in a communal sense.

scholarly journals SARS-CoV-2 Spike Affinity and Dynamics Exclude the Strict Requirement of an Intermediate Host

2021 ◽  
Author(s):  
Matteo Castelli ◽  
Luigi Scietti ◽  
Nicola Clementi ◽  
Mattia Cavallaro ◽  
Silvia Faravelli ◽  
...  
Keyword(s):  
Intermediate Host ◽  
Receptor Binding ◽  
Animal Species ◽  
Evolutionary Process ◽  
Evolutionary Model ◽  
Model Based ◽  
Rhinolophus Affinis ◽  
Strict Requirement ◽  
Spike Dynamics

SARS-CoV-2 proximal origin is still unclear, limiting the possibility of foreseeing other spillover events with pandemic potential. Here we propose an evolutionary model based on the thorough dissection of SARS-CoV-2 and RaTG13 - the closest bat ancestor - spike dynamics, kinetics and binding to ACE2. Our results indicate that both spikes share nearly identical, high affinities for Rhinolophus affinis bat and human ACE2, pointing out to negligible species barriers directly related to receptor binding. Also, SARS-CoV-2 spike shows a higher degree of dynamics and kinetics optimization that favors ACE2 engagement. Therefore, we devise an affinity-independent evolutionary process that likely took place in R. affinis bats and limits the eventual involvement of other animal species in initiating the pandemic to the role of vector.

scholarly journals Assessment of Overlap of Phylogenetic Transmission Clusters and Communities in Simple Sexual Contact Networks: Applications to HIV-1

PLoS ONE ◽  
2016 ◽  
Vol 11 (2) ◽  
pp. e0148459 ◽  
Author(s):  
Luc Villandre ◽  
David A. Stephens ◽  
Aurelie Labbe ◽  
Huldrych F. Günthard ◽  
Roger Kouyos ◽  
...  
Keyword(s):  
Sexual Contact ◽  
Contact Networks ◽  
Hiv 1

scholarly journals Spatial analyses of wildlife contact networks

2015 ◽  
Vol 12 (102) ◽  
pp. 20141004 ◽  
Author(s):  
Stephen Davis ◽  
Babak Abbasi ◽  
Shrupa Shah ◽  
Sandra Telfer ◽  
Mike Begon
Keyword(s):  
Critical Role ◽  
Host Density ◽  
Spatial Arrangement ◽  
Spatial Proximity ◽  
Contact Network ◽  
Spatial Constraints ◽  
Contact Networks ◽  
Proximity Graphs ◽  
Contact Rates ◽  
Pathogen Persistence

Datasets from which wildlife contact networks of epidemiological importance can be inferred are becoming increasingly common. A largely unexplored facet of these data is finding evidence of spatial constraints on who has contact with whom, despite theoretical epidemiologists having long realized spatial constraints can play a critical role in infectious disease dynamics. A graph dissimilarity measure is proposed to quantify how close an observed contact network is to being purely spatial whereby its edges are completely determined by the spatial arrangement of its nodes. Statistical techniques are also used to fit a series of mechanistic models for contact rates between individuals to the binary edge data representing presence or absence of observed contact. These are the basis for a second measure that quantifies the extent to which contacts are being mediated by distance. We apply these methods to a set of 128 contact networks of field voles ( Microtus agrestis ) inferred from mark–recapture data collected over 7 years and from four sites. Large fluctuations in vole abundance allow us to demonstrate that the networks become increasingly similar to spatial proximity graphs as vole density increases. The average number of contacts, , was (i) positively correlated with vole density across the range of observed densities and (ii) for two of the four sites a saturating function of density. The implications for pathogen persistence in wildlife may be that persistence is relatively unaffected by fluctuations in host density because at low density is low but hosts move more freely, and at high density is high but transmission is hampered by local build-up of infected or recovered animals.

A novel topology identification method based on compressive sensing for multidimensional networks

2020 ◽  
Vol 34 (30) ◽  
pp. 2050294
Author(s):  
Shuheng Fang ◽  
Zhengmin Kong ◽  
Ping Hu ◽  
Li Ding
Keyword(s):  
Compressive Sensing ◽  
Matching Pursuit ◽  
Network Models ◽  
Reconstruction Algorithm ◽  
Identification Problem ◽  
Topology Identification ◽  
Network Recovery ◽  
Threshold Mechanism ◽  
Different Types ◽  
2D Network

In real-world scenarios, it is difficult to know about the complete topology of a huge network with different types of links. In this brief, we propose a method to identify the topology of multidimensional networks from information transmission data. We consider information propagating over edges of a two-dimensional (2D) network, where one type of links is known and the other type is unknown. Given the state of all nodes at each unit time, we can transform the topology identification problem into a compressive sensing framework. A modified reconstruction algorithm, called Sparsity Adaptive Matching Pursuit with Mixed Threshold Mechanism (SAMPMTM), is proposed to tackle the problem. Compared with the classical Sparsity Adaptive Matching Pursuit (SAMP) algorithm, the proposed SAMPMTM algorithm can reduce the conflict rate and improve the accuracy of network recovery. We further demonstrate the performance of this improved algorithm through Monte-Carlo simulations under different network models.

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