scholarly journals Increased RNA virus population diversity improves adaptability

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Florian Mattenberger ◽  
Marina Vila-Nistal ◽  
Ron Geller

AbstractThe replication machinery of most RNA viruses lacks proofreading mechanisms. As a result, RNA virus populations harbor a large amount of genetic diversity that confers them the ability to rapidly adapt to changes in their environment. In this work, we investigate whether further increasing the initial population diversity of a model RNA virus can improve adaptation to a single selection pressure, thermal inactivation. For this, we experimentally increased the diversity of coxsackievirus B3 (CVB3) populations across the capsid region. We then compared the ability of these high diversity CVB3 populations to achieve resistance to thermal inactivation relative to standard CVB3 populations in an experimental evolution setting. We find that viral populations with high diversity are better able to achieve resistance to thermal inactivation at both the temperature employed during experimental evolution as well as at a more extreme temperature. Moreover, we identify mutations in the CVB3 capsid that confer resistance to thermal inactivation, finding significant mutational epistasis. Our results indicate that even naturally diverse RNA virus populations can benefit from experimental augmentation of population diversity for optimal adaptation and support the use of such viral populations in directed evolution efforts that aim to select viruses with desired characteristics.

2020 ◽  
Author(s):  
Florian Mattenberger ◽  
Marina Vila-Nistal ◽  
Ron Geller

Abstract The replication machinery of most RNA viruses lacks proofreading mechanisms. As a result, RNA virus populations harbor a large amount of genetic diversity that confers them the ability to rapidly adapt to changes in their environment. In this work, we investigate whether further increasing the initial population diversity of a model RNA virus can improve adaptation to a single selection pressure, thermal inactivation. For this, we experimentally increased the diversity of coxsackievirus B3 (CVB3) populations across the capsid region. We then compared the ability of such high diversity CVB3 populations to achieve resistance to thermal inactivation relative to standard CVB3 populations in an experimental evolution setting. We find that high diversity viral populations are better able to achieve resistance to thermal inactivation at both the temperature employed during experimental evolution as well as at a more extreme temperature. Moreover, we identify mutations in the CVB3 capsid that confer resistance to thermal inactivation, finding significant mutational epistasis. Our results indicate that even naturally diverse RNA virus populations can benefit from experimental augmentation of population diversity for optimal adaptation and support the use of such viral populations in directed evolution efforts that aim to select for viruses with desired characteristics.


2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Lele Zhao ◽  
Siobain Duffy

AbstractGeneralist viruses, those with a comparatively larger host range, are considered more likely to emerge on new hosts. The potential to emerge in new hosts has been linked to viral genetic diversity, a measure of evolvability. However, there is no consensus on whether infecting a larger number of hosts leads to higher genetic diversity, or whether diversity is better maintained in a homogeneous environment, similar to the lifestyle of a specialist virus. Using experimental evolution with the RNA bacteriophage phi6, we directly tested whether genetic generalism (carrying an expanded host range mutation) or environmental generalism (growing on heterogeneous hosts) leads to viral populations with more genetic variation. Sixteen evolved viral lineages were deep sequenced to provide genetic evidence for population diversity. When evolved on a single host, specialist and generalist genotypes both maintained the same level of diversity (measured by the number of single nucleotide polymorphisms (SNPs) above 1%, P = 0.81). However, the generalist genotype evolved on a single host had higher SNP levels than generalist lineages under two heterogeneous host passaging schemes (P = 0.001, P < 0.001). RNA viruses’ response to selection in alternating hosts reduces standing genetic diversity compared to those evolving in a single host to which the virus is already well-adapted.


2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Lijun Sun ◽  
Tianfei Chen ◽  
Qiuwen Zhang

As a novel swarm intelligence algorithm, artificial bee colony (ABC) algorithm inspired by individual division of labor and information exchange during the process of honey collection has advantage of simple structure, less control parameters, and excellent performance characteristics and can be applied to neural network, parameter optimization, and so on. In order to further improve the exploration ability of ABC, an artificial bee colony algorithm with random location updating (RABC) is proposed in this paper, and the modified search equation takes a random location in swarm as a search center, which can expand the search range of new solution. In addition, the chaos is used to initialize the swarm population, and diversity of initial population is improved. Then, the tournament selection strategy is adopted to maintain the population diversity in the evolutionary process. Through the simulation experiment on a suite of unconstrained benchmark functions, the results show that the proposed algorithm not only has stronger exploration ability but also has better effect on convergence speed and optimization precision, and it can keep good robustness and validity with the increase of dimension.


2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Chang-Jian Sun ◽  
Fang Gao

The marine predators algorithm (MPA) is a novel population-based optimization method that has been widely used in real-world optimization applications. However, MPA can easily fall into a local optimum because of the lack of population diversity in the late stage of optimization. To overcome this shortcoming, this paper proposes an MPA variant with a hybrid estimation distribution algorithm (EDA) and a Gaussian random walk strategy, namely, HEGMPA. The initial population is constructed using cubic mapping to enhance the diversity of individuals in the population. Then, EDA is adapted into MPA to modify the evolutionary direction using the population distribution information, thus improving the convergence performance of the algorithm. In addition, a Gaussian random walk strategy with medium solution is used to help the algorithm get rid of stagnation. The proposed algorithm is verified by simulation using the CEC2014 test suite. Simulation results show that the performance of HEGMPA is more competitive than other comparative algorithms, with significant improvements in terms of convergence accuracy and convergence speed.


BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Saskia Pfrengle ◽  
Judith Neukamm ◽  
Meriam Guellil ◽  
Marcel Keller ◽  
Martyna Molak ◽  
...  

Abstract Background Hansen’s disease (leprosy), widespread in medieval Europe, is today mainly prevalent in tropical and subtropical regions with around 200,000 new cases reported annually. Despite its long history and appearance in historical records, its origins and past dissemination patterns are still widely unknown. Applying ancient DNA approaches to its major causative agent, Mycobacterium leprae, can significantly improve our understanding of the disease’s complex history. Previous studies have identified a high genetic continuity of the pathogen over the last 1500 years and the existence of at least four M. leprae lineages in some parts of Europe since the Early Medieval period. Results Here, we reconstructed 19 ancient M. leprae genomes to further investigate M. leprae’s genetic variation in Europe, with a dedicated focus on bacterial genomes from previously unstudied regions (Belarus, Iberia, Russia, Scotland), from multiple sites in a single region (Cambridgeshire, England), and from two Iberian leprosaria. Overall, our data confirm the existence of similar phylogeographic patterns across Europe, including high diversity in leprosaria. Further, we identified a new genotype in Belarus. By doubling the number of complete ancient M. leprae genomes, our results improve our knowledge of the past phylogeography of M. leprae and reveal a particularly high M. leprae diversity in European medieval leprosaria. Conclusions Our findings allow us to detect similar patterns of strain diversity across Europe with branch 3 as the most common branch and the leprosaria as centers for high diversity. The higher resolution of our phylogeny tree also refined our understanding of the interspecies transfer between red squirrels and humans pointing to a late antique/early medieval transmission. Furthermore, with our new estimates on the past population diversity of M. leprae, we gained first insights into the disease’s global history in relation to major historic events such as the Roman expansion or the beginning of the regular transatlantic long distance trade. In summary, our findings highlight how studying ancient M. leprae genomes worldwide improves our understanding of leprosy’s global history and can contribute to current models of M. leprae’s worldwide dissemination, including interspecies transmissions.


2021 ◽  
Author(s):  
Marin Ježić ◽  
Janine Melanie Schwarz ◽  
Simone Prospero ◽  
Kiril Sotirovski ◽  
Mihajlo Risteski ◽  
...  

Chestnut blight has spread throughout Europe since the introduction of its causal agent Cryphonectria parasitica over 70 years ago. In our study, we have analysed diversity of vegetative compatibility (vc) and microsatellite genotypes of C. parasitica, as well as sequence diversity of Cryphonectria hypovirus 1 (CHV1) in six populations from Switzerland, Croatia and North Macedonia. Resampling of local populations that were already investigated more than a decade ago allowed us to analyse the spatial and temporal population structure across an invasive range of the pathogen in Europe. Regardless which genetic marker was used, the over 60 year-old Swiss and Croatian populations had a high population diversity, while more recent North Macedonian populations were mostly clonal. These diversity differences between the investigated populations remained stable over time. A high diversity of CHV1 was observed in all three countries, with North Macedonian strains forming a separate cluster from strains obtained in other countries. No correlation between vc diversity and CHV1 prevalence was observed, suggesting a well-established and maintained natural hypovirulence in all countries, further corroborated by an observed increase in genetic diversity of Croatian C. parasitica populations over time, without collapse of CHV1 prevalence.


2009 ◽  
Vol 2009 ◽  
pp. 1-11 ◽  
Author(s):  
Henrik Berg

It is commonly believed that diversity is crucial for an evolutionary system to succeed, especially when the problem to be solved contains local optima from which the population cannot easily escape. There exist numerous methods to measure population diversity, but none of these have been shown to be consistently useful. In this paper, a new diversity measure is introduced, and it is shown that high diversity according to this new measure generally leads to a more successful overall evolution in most of the cases considered.


2011 ◽  
Vol 1 (6) ◽  
pp. 643-648 ◽  
Author(s):  
Antonio V Bordería ◽  
Kenneth A Stapleford ◽  
Marco Vignuzzi

2012 ◽  
Vol 616-618 ◽  
pp. 2064-2067
Author(s):  
Yong Gang Che ◽  
Chun Yu Xiao ◽  
Chao Hai Kang ◽  
Ying Ying Li ◽  
Li Ying Gong

To solve the primary problems in genetic algorithms, such as slow convergence speed, poor local searching capability and easy prematurity, the immune mechanism is introduced into the genetic algorithm, and thus population diversity is maintained better, and the phenomena of premature convergence and oscillation are reduced. In order to compensate the defects of immune genetic algorithm, the Hénon chaotic map, which is introduced on the above basis, makes the generated initial population uniformly distributed in the solution space, eventually, the defect of data redundancy is reduced and the quality of evolution is improved. The proposed chaotic immune genetic algorithm is used to optimize the complex functions, and there is an analysis compared with the genetic algorithm and the immune genetic algorithm, the feasibility and effectiveness of the proposed algorithm are proved from the perspective of simulation experiments.


2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Xiaodan Liang ◽  
Dong Wu ◽  
Yang Liu ◽  
Maowei He ◽  
Liling Sun

In the past few decades, metaheuristic algorithms (MA) have been developed tremendously and have been successfully applied in many fields. In recent years, a large number of new MA have been proposed. Slime mould algorithm (SMA) is a novel swarm-based intelligence optimization algorithm. SMA solves the optimization problem by imitating the foraging and movement behavior of slime mould. It can effectively obtain a promising global optimal solution. However, it still suffers some shortcomings such as the unstable convergence speed, the imprecise search accuracy, and incapability of identifying a local optimal solution when faced with complicated optimization problems. With the purpose of overcoming the shortcomings of SMA, this paper proposed a multistrategy enhanced version of SMA called ESMA. The three enhanced strategies are chaotic initialization strategy (CIS), orthogonal learning strategy (OLS), and boundary reset strategy (BRS). The CIS is used to generate an initial population with diversity in the early stage of ESMA, which can increase the convergence speed of the algorithm and the quality of the final solution. Then, the OLS is used to discover the useful information of the best solutions and offer a potential search direction, which enhances the local search ability and raises the convergence rate. Finally, the BRS is used to correct individual positions, which ensures the population diversity and enhances the overall search capabilities of ESMA. The performance of ESMA was validated on the 30 IEEE CEC2014 functions and three IIR model identification problems, compared with other nine well-regarded and state-of-the-art algorithms. Simulation results and analysis prove that the ESMA has a superior performance. The three strategies involved in ESMA have significantly improved the performance of the basic SMA.


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