Titration and Extensive Serial Passages of Yaba Virus In Vitro

A sensitive assay system of Yaba virus (YV) was established in a cynomolgus monkey kidney cell line, JINET, in which the virus caused multilayered cellular foci countable even with the unaided eye. The specificity of the foci induced by YV in these cells was demonstrated by (1) the focus-forming ability was destroyed by heating at 60 C for 12 min; (2) the focus formation was inhibited by specific antiserum; (3) specific fluorescence was detected only in cells composing the foci when tested by fluorescent antibody technique; (4) a linear relationship was observed between the virus concentration and the number of foci formed; (5) YV preparation passed 20 times in JINET cells still possessed “tumorigenicity” in cynomolgus monkeys. The sensitivity of JINET cells to YV was comparable to that of cynomolgus monkeys, and YV was successively propagated in JINET cells with 2 log increase in infectivity titer during over 40 serial passages. Application of this assay system to growth kinetic studies of YV and quantitation of neutralizing antibody to YV is also discussed.     

Adaptation in Tunably Rugged Fitness Landscapes: The Rough Mount Fuji Model

Much of the current theory of adaptation is based on Gillespie’s mutational landscape model (MLM), which assumes that the fitness values of genotypes linked by single mutational steps are independent random variables. On the other hand, a growing body of empirical evidence shows that real fitness landscapes, while possessing a considerable amount of ruggedness, are smoother than predicted by the MLM. In the present article we propose and analyze a simple fitness landscape model with tunable ruggedness based on the rough Mount Fuji (RMF) model originally introduced by Aita et al. in the context of protein evolution. We provide a comprehensive collection of results pertaining to the topographical structure of RMF landscapes, including explicit formulas for the expected number of local fitness maxima, the location of the global peak, and the fitness correlation function. The statistics of single and multiple adaptive steps on the RMF landscape are explored mainly through simulations, and the results are compared to the known behavior in the MLM model. Finally, we show that the RMF model can explain the large number of second-step mutations observed on a highly fit first-step background in a recent evolution experiment with a microvirid bacteriophage.     

The Evolutionary Dynamics of Bluetongue Virus

Bluetongue virus (BTV) is a midge-borne member of the genus Orbivirus that causes an eponymous debilitating livestock disease of great agricultural impact and which has expanded into Europe in recent decades. Reassortment among the ten segments comprising the double-stranded (ds) RNA genome of BTV has played an important role in generating the epidemic strains of this virus in Europe. In this study, we investigated the dynamics of BTV genome segment evolution utilizing time-structured data sets of complete sequences from four segments, totalling 290 sequences largely sampled from ruminant hosts. Our analysis revealed that BTV genome segments generally evolve under strong purifying selection and at substitution rates that are generally lower (mean rates of ~0.5–7 × 10⁻⁴ nucleotide substitutions per site, per year) than vector-borne positive-sense viruses with single-strand (ss) RNA genomes. These also represent the most robust estimates of the nucleotide substitution rate in a dsRNA virus generated to date. Additionally, we determined that patterns of geographic structure and times to most recent common ancestor differ substantially between each segment, including a relatively recent origin for the diversity of segment 10 within the past millennium. Together, these findings demonstrate the effect of reassortment to decouple the evolutionary dynamics of BTV genome segments.     

C亚型SHIVCHN19P4强毒株在中国恒河猴体内的传代研究

目的研究C亚型SHIVCHN19P4强毒株在中国恒河猴体内传代中病毒学和免疫学等反应的变化特点,分离制备SHIVCHN19P4中国恒河猴传代适应株病毒。方法选择4只健康成年恒河猴,其中两只经后肢静脉感染SHIVCHN19P4病毒,60 d后,分别采集EDTA抗凝全血静脉途径传代至另两只猴,使用流式细胞术、PCR、结合抗体检测和序列分析等方法研究传代动物病毒学、免疫学和序列变异特点。选择性从传代动物感染急性期外周血中分离PBMC,CD8＋T细胞敲除后与正常PBMC共培养分离病毒。结果 4只传代动物均获得系统性感染,且传代后病毒毒力明显增强,序列分析发现SHIVCHN19P4病毒序列在传代过程中发生适应性改变;同时,成功分离制备SHIVCHN19P4传代适应性病毒株。结论 SHIVCHN19P4在中国恒河猴体内适应性传代研究为进一步建立C亚型SHIV强毒株/SAIDS模型奠定了良好的实验基础,为研究C亚型HIV-1流行株致病特点以及预防性黏膜疫苗和杀微生物的有效性评价提供了数据支持。     

Group Selection and Contribution of Minority Variants during Virus Adaptation Determines Virus Fitness and Phenotype

Understanding how a pathogen colonizes and adapts to a new host environment is a primary aim in studying emerging infectious diseases. Adaptive mutations arise among the thousands of variants generated during RNA virus infection, and identifying these variants will shed light onto how changes in tropism and species jumps can occur. Here, we adapted Coxsackie virus B3 to a highly permissive and less permissive environment. Using deep sequencing and bioinformatics, we identified a multi-step adaptive process to adaptation involving residues in the receptor footprints that correlated with receptor availability and with increase in virus fitness in an environment-specific manner. We show that adaptation occurs by selection of a dominant mutation followed by group selection of minority variants that together, confer the fitness increase observed in the population, rather than selection of a single dominant genotype.     

The Evolutionary Dynamics of Human Influenza B Virus

Despite their close phylogenetic relationship, type A and B influenza viruses exhibit major epidemiological differences in humans, with the latter both less common and less often associated with severe disease. However, it is unclear what processes determine the evolutionary dynamics of influenza B virus, and how influenza viruses A and B interact at the evolutionary scale. To address these questions we inferred the phylogenetic history of human influenza B virus using complete genome sequences for which the date (day) of isolation was available. By comparing the phylogenetic patterns of all eight viral segments we determined the occurrence of segment reassortment over a 30-year sampling period. An analysis of rates of nucleotide substitution and selection pressures revealed sporadic occurrences of adaptive evolution, most notably in the viral hemagglutinin and compatible with the action of antigenic drift, yet lower rates of overall and nonsynonymous nucleotide substitution compared to influenza A virus. Overall, these results led us to propose a model in which evolutionary changes within and between the antigenically distinct 'Yam88' and 'Vic87' lineages of influenza B virus are the result of changes in herd immunity, with reassortment continuously generating novel genetic variation. Additionally, we suggest that the interaction with influenza A virus may be central in shaping the evolutionary dynamics of influenza B virus, facilitating the shift of dominance between the Vic87 and the Yam88 lineages.     

The Effect of Bacterial Recombination on Adaptation on Fitness Landscapes with Limited Peak Accessibility

There is ample empirical evidence revealing that fitness landscapes are often complex: the fitness effect of a newly arisen mutation can depend strongly on the allelic state at other loci. However, little is known about the effects of recombination on adaptation on such fitness landscapes. Here, we investigate how recombination influences the rate of adaptation on a special type of complex fitness landscapes. On these landscapes, the mutational trajectories from the least to the most fit genotype are interrupted by genotypes with low relative fitness. We study the dynamics of adapting populations on landscapes with different compositions and numbers of low fitness genotypes, with and without recombination. Our results of the deterministic model (assuming an infinite population size) show that recombination generally decelerates adaptation on these landscapes. However, in finite populations, this deceleration is outweighed by the accelerating Fisher-Muller effect under certain conditions. We conclude that recombination has complex effects on adaptation that are highly dependent on the particular fitness landscape, population size and recombination rate.     

Quantitative Modeling of Tumor Dynamics and Radiotherapy

Cancer is a complex disease, necessitating research on many different levels; at the subcellular level to identify genes, proteins and signaling pathways associated with the disease; at the cellular level to identify, for example, cell-cell adhesion and communication mechanisms; at the tissue level to investigate disruption of homeostasis and interaction with the tissue of origin or settlement of metastasis; and finally at the systems level to explore its global impact, e.g. through the mechanism of cachexia. Mathematical models have been proposed to identify key mechanisms that underlie dynamics and events at every scale of interest, and increasing effort is now being paid to multi-scale models that bridge the different scales. With more biological data becoming available and with increased interdisciplinary efforts, theoretical models are rendering suitable tools to predict the origin and course of the disease. The ultimate aims of cancer models, however, are to enlighten our concept of the carcinogenesis process and to assist in the designing of treatment protocols that can reduce mortality and improve patient quality of life. Conventional treatment of cancer is surgery combined with radiotherapy or chemotherapy for localized tumors or systemic treatment of advanced cancers, respectively. Although radiation is widely used as treatment, most scheduling is based on empirical knowledge and less on the predictions of sophisticated growth dynamical models of treatment response. Part of the failure to translate modeling research to the clinic may stem from language barriers, exacerbated by often esoteric model renderings with inaccessible parameterization. Here we discuss some ideas for combining tractable dynamical tumor growth models with radiation response models using biologically accessible parameters to provide a more intuitive and exploitable framework for understanding the complexity of radiotherapy treatment and failure.     

The Evolutionary Dynamics of Protein-Protein Interaction Networks Inferred from the Reconstruction of Ancient Networks

Cellular functions are based on the complex interplay of proteins, therefore the structure and dynamics of these protein-protein interaction (PPI) networks are the key to the functional understanding of cells. In the last years, large-scale PPI networks of several model organisms were investigated. A number of theoretical models have been developed to explain both the network formation and the current structure. Favored are models based on duplication and divergence of genes, as they most closely represent the biological foundation of network evolution. However, studies are often based on simulated instead of empirical data or they cover only single organisms. Methodological improvements now allow the analysis of PPI networks of multiple organisms simultaneously as well as the direct modeling of ancestral networks. This provides the opportunity to challenge existing assumptions on network evolution. We utilized present-day PPI networks from integrated datasets of seven model organisms and developed a theoretical and bioinformatic framework for studying the evolutionary dynamics of PPI networks. A novel filtering approach using percolation analysis was developed to remove low confidence interactions based on topological constraints. We then reconstructed the ancient PPI networks of different ancestors, for which the ancestral proteomes, as well as the ancestral interactions, were inferred. Ancestral proteins were reconstructed using orthologous groups on different evolutionary levels. A stochastic approach, using the duplication-divergence model, was developed for estimating the probabilities of ancient interactions from today''s PPI networks. The growth rates for nodes, edges, sizes and modularities of the networks indicate multiplicative growth and are consistent with the results from independent static analysis. Our results support the duplication-divergence model of evolution and indicate fractality and multiplicative growth as general properties of the PPI network structure and dynamics.     

Population Dynamics of Evolutionary Change: Demographic Parameters as Indicators of Fitness

I evaluated demographic parameters as indicators of fitness by calculating the net reproductive rate (R₀), exponential rate of change (r), lifetime reproductive success (LRS), and Malthusian parameter (m) for nine genotypes and four phenotypes (two alleles at each of two independent loci) of an age-structured population. The given starting conditions included age-specific survival rates of males and females and age-specific fecundity of females for each genotype (to simplify the problem I presumed no differences in survivorship or fecundity of genotypes with the same phenotype) and the same age structure for each genotype. The prevailing genotype had the greatestm, but it did not have the greatestr,R₀, or LRS, or even the greatest survivorship of either juveniles or adults, or the greatest fecundity. This result indicates thatmis the only correct measure of fitness (i.e., as a predictor of which genotype should prevail from among a group of genotypes) and that comparisons ofr,R₀, LRS, juvenile or adult survival rates, or fecundity may be misleading indicators of which genotype should prevail (i.e., be most “fit”) over time (i.e., be selected for).     

Exploiting the Adaptation Dynamics to Predict the Distribution of Beneficial Fitness Effects

Adaptation of asexual populations is driven by beneficial mutations and therefore the dynamics of this process, besides other factors, depends on the distribution of beneficial fitness effects. It is known that on uncorrelated fitness landscapes, this distribution can only be of three types: truncated, exponential and power law. We performed extensive stochastic simulations to study the adaptation dynamics on rugged fitness landscapes, and identified two quantities that can be used to distinguish the underlying distribution of beneficial fitness effects. The first quantity studied here is the fitness difference between successive mutations that spread in the population, which is found to decrease in the case of truncated distributions, remains nearly a constant for exponentially decaying distributions and increases when the fitness distribution decays as a power law. The second quantity of interest, namely, the rate of change of fitness with time also shows quantitatively different behaviour for different beneficial fitness distributions. The patterns displayed by the two aforementioned quantities are found to hold good for both low and high mutation rates. We discuss how these patterns can be exploited to determine the distribution of beneficial fitness effects in microbial experiments.     

Exploring the Molecular Epidemiology and Evolutionary Dynamics of Influenza A Virus in Taiwan

The evolution and population dynamics of human influenza in Taiwan is a microcosm of the viruses circulating worldwide, which has not yet been studied in detail. We collected 343 representative full genome sequences of human influenza A viruses isolated in Taiwan between 1979 and 2009. Phylogenetic and antigenic data analysis revealed that H1N1 and H3N2 viruses consistently co-circulated in Taiwan, although they were characterized by different temporal dynamics and degrees of genetic diversity. Moreover, influenza A viruses of both subtypes underwent internal gene reassortment involving all eight segments of the viral genome, some of which also occurred during non-epidemic periods. The patterns of gene reassortment were different in the two subtypes. The internal genes of H1N1 viruses moved as a unit, separately from the co-evolving HA and NA genes. On the other hand, the HA and NA genes of H3N2 viruses tended to segregate consistently with different sets of internal gene segments. In particular, as reassortment occurred, H3HA always segregated as a group with the PB1, PA and M genes, while N2NA consistently segregated with PB2 and NP. Finally, the analysis showed that new phylogenetic lineages and antigenic variants emerging in summer were likely to be the progenitors of the epidemic strains in the following season. The synchronized seasonal patterns and high genetic diversity of influenza A viruses observed in Taiwan make possible to capture the evolutionary dynamic and epidemiological rules governing antigenic drift and reassortment and may serve as a “warning” system that recapitulates the global epidemic.     

Complete Genome Analysis of Three Live Attenuated Rinderpest Virus Vaccine Strains Derived through Serial Passages in Different Culture Systems

The genomes of three South Korean Rinderpest virus vaccine strains (L72, LA77, and LA96) were analyzed in order to investigate their genetic variability. These three vaccine strains were all derived from the same virus strain origin (Fusan) through repeated passages in different culture systems. The full genome length of the three strains was 15,882 nucleotides, and the sequence similarity between the three South Korean RPV strains at the nucleotide level was 98.1 to 98.9%. The genetic distance between Nakamura III, L72, LA77, LA96, and LATC06 and the Kabete strain was greater than that between the Fusan and Kabete strains for the P, V, and C genes. The difference in pathogenicity among these strains might be due to the V gene, which has a positive (>1) selection ratio based on the analysis of synonymous (dS) and nonsynonymous (dN) substitution rates (dN/dS ratio [ω]).