| Literature DB >> 21994738 |
Kurt J Vandegrift1,2, Nina Wale2, Jonathan H Epstein2.
Abstract
The aim of this manuscript is to describe how modern advances in our knowledge of viruses and viral evolution can be applied to the fields of disease ecology and conservation. We review recent progress in virology and provide examples of how it is informing both empirical research in field ecology and applied conservation. We include a discussion of needed breakthroughs and ways to bridge communication gaps between the field and the lab. In an effort to foster this interdisciplinary effort, we have also included a table that lists the definitions of key terms. The importance of understanding the dynamics of zoonotic pathogens in their reservoir hosts is emphasized as a tool to both assess risk factors for spillover and to test hypotheses related to treatment and/or intervention strategies. In conclusion, we highlight the need for smart surveillance, viral discovery efforts and predictive modeling. A shift towards a predictive approach is necessary in today's globalized society because, as the 2009 H1N1 pandemic demonstrated, identification post-emergence is often too late to prevent global spread. Integrating molecular virology and ecological techniques will allow for earlier recognition of potentially dangerous pathogens, ideally before they jump from wildlife reservoirs into human or livestock populations and cause serious public health or conservation issues.Entities:
Keywords: conservation; disease ecology; emerging disease; endangered species; metagenomics; phylodynamics; smart surveillance; vaccination; virology
Mesh:
Year: 2011 PMID: 21994738 PMCID: PMC3185704 DOI: 10.3390/v3040379
Source DB: PubMed Journal: Viruses ISSN: 1999-4915 Impact factor: 5.818
Definitions of key terms used in the text.
| Admixture | The formation of a hybrid population through the mixing of two ancestral, or long-separated, populations. |
| Bayesian Skyline Plot | A method for estimating historical population dynamics from a sample of sequences without assuming a predefined demographic model. |
| Coalescent Theory | A mathematical framework which describes the distribution of gene trees in populations. It provides mathematical methods for connecting demographic or ecological models with a phylogenetic tree. |
| Demography | Demography is the statistical study of populations. In the field of ecology, demography encompasses the study of the size, structure and distribution of populations, and spatial and/or temporal changes in them in response to birth, migration, aging and death. However, here we use a more rigid definition of demography—as the pattern and rate of population growth. |
| Effective population size (Ne) | The number of breeding individuals in an idealized population that would show the same amount of dispersion of allele frequencies under random genetic drift, or the same amount of inbreeding, as the natural population under consideration. The analogue of Ne for viruses, the ‘effective number of infections’ is related to the number of infected host individuals and to the number of new transmission events [ |
| Metagenomics | A discipline which uses next-generation sequencing technologies to characterize the entirety of genomic material found in environmental samples. |
| Molecular Clock | The molecular clock is derived from the hypothesis that sequence evolution, while random, occurs at stable rate such that the time since the divergence of two or more sequences can be estimated. Recent ‘relaxed molecular clock’ analysis can account for variation in the rate of sequence evolution through time or between lineages. |
| Phylogeny | The relations among a set of sequences showing which shares a most recent common ancestor with other sequences. |
| Phylogeography | The study of the principles and processes governing the geographical distribution of genealogical lineages. |
| Population Structure | In the field of population genetics, population structure is defined as the absence of random mating within a population. This is the definition used here. In ecology, population structure is defined by several key parameters including number of individuals in a population, age distribution of individuals, probabilities of survival (or mortality), and rates of fecundity. |
| Reassortment | A process that occurs in segmented viruses by which one or more segments ‘swap’ to create a new viral genome. This drives the process of antigenic shift in Influenza A viruses. |
| Recombination | The process by which new genotypes are created by the combination of distinct lineages. In sexual organisms it occurs during meiotic division, by the exchange of DNA between different chromosomes or ‘crossing-over’. Viral recombination occurs during viral replication and is an important factor in viral evolution (for more details see Worobey and Holmes, 1999 [ |
| Reversion | Mutation of a virus such that it changes ‘back’ to its wild-type state. |
| Life History | The timing of an organism’s schedule of reproduction and death. Species with long life histories, also known as ‘K’ strategists, tend to have low reproductive rates, stable populations, long generation times and long lifespans. |
| Aggregation | Where the parasite population is not randomly distributed among hosts, such that the variance is greater than the mean. The macroparasites in a host population are often best described by the negative binomial distribution such that a minority of hosts possess the majority of the parasites. |
| R0 (Basic Reproduction Number) | In the case of viruses and other microparasites, R0 is the average number of secondary infections which an infection produces. As such it is a measure of parasite fitness. |
| Reservoir Host | A host species that can independently maintain a disease and act as a source of infection to other host species. Infection in reservoirs is usually more persistent and less harmful than that of other hosts. |
| Zoonotic disease | A disease transmissible from animals to humans or |
Figure 1.Phylodynamic techniques. (a) A rooted molecular phylogeny represents the evolutionary relationships between individual viral sequences, as represented by circles. These phylogenies may reflect transmission chains, however sampling must be sufficient for them to do so, while recombination may obscure ‘true’ relationships between viral sequences. (b) Simple molecular clock theory, predicated on the neutral theory of molecular evolution [48] assumes that mutation occurs at a constant rate over time, thus the time that has elapsed since a pair of virus strains diverged from a common ancestor may be quantified. Methods that account for differences in the evolutionary rates of different strains, and for variation in these rates through time, have been recently developed [49]. Here variants represented by thick lines evolve much faster than those represented by thin lines. (c) Using a phylogeographic approach, the location at which a sequence was sampled may be mapped onto the viral phylogeny and the likely spreading trajectory of the virus inferred. While parsimony approaches have been popular, powerful Bayesian methods that account for uncertainty of dispersal process and historical phylogeny have been developed to reconstruct viral dispersal events [44]. Crosses on the phylogeny represent such viral dispersal events, in this example. (d) Coalescent theory provides the basis for many phylodynamic approaches. Here, circles on the same row represent temporally simultaneous infections. Working back from sampled infections (red circles), lineages can be traced back to the most recent common ancestor (black circle) via hypothetical, unsampled ancestors (grey circles). The time it takes for sampled lineages to coalesce is dependent on a variety of variables (i.e., viral effective population size, population structure, selection, stochastic infection die-out and recombination). A variety of methods are available to test for selection and recombination. Figure and legend adapted with permission from Macmillan Publishers Ltd: Nature (Pybus, O.G., Rambaut, A. Evolutionary analysis of the dynamics of viral infectious disease), copyright (2009) [50].