Understanding the limits to generalizability of experimental evolutionary models.

Post print version of article deposited in accordance with SHERPA RoMEO guidelines. The final definitive version is available online at: http://www.nature.com/nature/journal/v455/n7210/abs/nature07152.htmlGiven the difficulty of testing evolutionary and ecological theory in situ, in vitro model systems are attractive alternatives; however, can we appraise whether an experimental result is particular to the in vitro model, and, if so, characterize the systems likely to behave differently and understand why? Here we examine these issues using the relationship between phenotypic diversity and resource input in the T7-Escherichia coli co-evolving system as a case history. We establish a mathematical model of this interaction, framed as one instance of a super-class of host-parasite co-evolutionary models, and show that it captures experimental results. By tuning this model, we then ask how diversity as a function of resource input could behave for alternative co-evolving partners (for example, E. coli with lambda bacteriophages). In contrast to populations lacking bacteriophages, variation in diversity with differences in resources is always found for co-evolving populations, supporting the geographic mosaic theory of co-evolution. The form of this variation is not, however, universal. Details of infectivity are pivotal: in T7-E. coli with a modified gene-for-gene interaction, diversity is low at high resource input, whereas, for matching-allele interactions, maximal diversity is found at high resource input. A combination of in vitro systems and appropriately configured mathematical models is an effective means to isolate results particular to the in vitro system, to characterize systems likely to behave differently and to understand the biology underpinning those alternatives

Robust estimation of microbial diversity in theory and in practice

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figure

Virus Adaptation by Manipulation of Host's Gene Expression

Viruses adapt to their hosts by evading defense mechanisms and taking over cellular metabolism for their own benefit. Alterations in cell metabolism as well as side-effects of antiviral responses contribute to symptoms development and virulence. Sometimes, a virus may spill over from its usual host species into a novel one, where usually will fail to successfully infect and further transmit to new host. However, in some cases, the virus transmits and persists after fixing beneficial mutations that allow for a better exploitation of the new host. This situation would represent a case for a new emerging virus. Here we report results from an evolution experiment in which a plant virus was allowed to infect and evolve on a naïve host. After 17 serial passages, the viral genome has accumulated only five changes, three of which were non-synonymous. An amino acid substitution in the viral VPg protein was responsible for the appearance of symptoms, whereas one substitution in the viral P3 protein the epistatically contributed to exacerbate severity. DNA microarray analyses show that the evolved and ancestral viruses affect the global patterns of host gene expression in radically different ways. A major difference is that genes involved in stress and pathogen response are not activated upon infection with the evolved virus, suggesting that selection has favored viral strategies to escape from host defenses

Ongoing Phenotypic and Genomic Changes in Experimental Coevolution of RNA Bacteriophage Qβ and Escherichia coli

According to the Red Queen hypothesis or arms race dynamics, coevolution drives continuous adaptation and counter-adaptation. Experimental models under simplified environments consisting of bacteria and bacteriophages have been used to analyze the ongoing process of coevolution, but the analysis of both parasites and their hosts in ongoing adaptation and counter-adaptation remained to be performed at the levels of population dynamics and molecular evolution to understand how the phenotypes and genotypes of coevolving parasite–host pairs change through the arms race. Copropagation experiments with Escherichia coli and the lytic RNA bacteriophage Qβ in a spatially unstructured environment revealed coexistence for 54 days (equivalent to 163–165 replication generations of Qβ) and fitness analysis indicated that they were in an arms race. E. coli first adapted by developing partial resistance to infection and later increasing specific growth rate. The phage counter-adapted by improving release efficiency with a change in host specificity and decrease in virulence. Whole-genome analysis indicated that the phage accumulated 7.5 mutations, mainly in the A2 gene, 3.4-fold faster than in Qβ propagated alone. E. coli showed fixation of two mutations (in traQ and csdA) faster than in sole E. coli experimental evolution. These observations suggest that the virus and its host can coexist in an evolutionary arms race, despite a difference in genome mutability (i.e., mutations per genome per replication) of approximately one to three orders of magnitude

Nasty Viruses, Costly Plasmids, Population Dynamics, and the Conditions for Establishing and Maintaining CRISPR-Mediated Adaptive Immunity in Bacteria

Clustered, Regularly Interspaced Short Palindromic Repeats (CRISPR) abound in the genomes of almost all archaebacteria and nearly half the eubacteria sequenced. Through a genetic interference mechanism, bacteria with CRISPR regions carrying copies of the DNA of previously encountered phage and plasmids abort the replication of phage and plasmids with these sequences. Thus it would seem that protection against infecting phage and plasmids is the selection pressure responsible for establishing and maintaining CRISPR in bacterial populations. But is it? To address this question and provide a framework and hypotheses for the experimental study of the ecology and evolution of CRISPR, I use mathematical models of the population dynamics of CRISPR-encoding bacteria with lytic phage and conjugative plasmids. The results of the numerical (computer simulation) analysis of the properties of these models with parameters in the ranges estimated for Escherichia coli and its phage and conjugative plasmids indicate: (1) In the presence of lytic phage there are broad conditions where bacteria with CRISPR-mediated immunity will have an advantage in competition with non-CRISPR bacteria with otherwise higher Malthusian fitness. (2) These conditions for the existence of CRISPR are narrower when there is envelope resistance to the phage. (3) While there are situations where CRISPR-mediated immunity can provide bacteria an advantage in competition with higher Malthusian fitness bacteria bearing deleterious conjugative plasmids, the conditions for this to obtain are relatively narrow and the intensity of selection favoring CRISPR weak. The parameters of these models can be independently estimated, the assumption behind their construction validated, and the hypotheses generated from the analysis of their properties tested in experimental populations of bacteria with lytic phage and conjugative plasmids. I suggest protocols for estimating these parameters and outline the design of experiments to evaluate the validity of these models and test these hypotheses

Finding a Needle in the Virus Metagenome Haystack - Micro-Metagenome Analysis Captures a Snapshot of the Diversity of a Bacteriophage Armoire

Viruses are ubiquitous in the oceans and critical components of marine microbial communities, regulating nutrient transfer to higher trophic levels or to the dissolved organic pool through lysis of host cells. Hydrothermal vent systems are oases of biological activity in the deep oceans, for which knowledge of biodiversity and its impact on global ocean biogeochemical cycling is still in its infancy. In order to gain biological insight into viral communities present in hydrothermal vent systems, we developed a method based on deep-sequencing of pulsed field gel electrophoretic bands representing key viral fractions present in seawater within and surrounding a hydrothermal plume derived from Loki's Castle vent field at the Arctic Mid-Ocean Ridge. The reduction in virus community complexity afforded by this novel approach enabled the near-complete reconstruction of a lambda-like phage genome from the virus fraction of the plume. Phylogenetic examination of distinct gene regions in this lambdoid phage genome unveiled diversity at loci encoding superinfection exclusion- and integrase-like proteins. This suggests the importance of fine-tuning lyosgenic conversion as a viral survival strategy, and provides insights into the nature of host-virus and virus-virus interactions, within hydrothermal plumes. By reducing the complexity of the viral community through targeted sequencing of prominent dsDNA viral fractions, this method has selectively mimicked virus dominance approaching that hitherto achieved only through culturing, thus enabling bioinformatic analysis to locate a lambdoid viral “needle" within the greater viral community “haystack". Such targeted analyses have great potential for accelerating the extraction of biological knowledge from diverse and poorly understood environmental viral communities

Population dynamics of a salmonella lytic phage and its host : implications of the host bacterial growth rate in modelling

The prevalence and impact of bacteriophages in the ecology of bacterial communities coupled with their ability to control pathogens turn essential to understand and predict the dynamics between phage and bacteria populations. To achieve this knowledge it is essential to develop mathematical models able to explain and simulate the population dynamics of phage and bacteria. We have developed an unstructured mathematical model using delay-differential equations to predict the interactions between a broad-host-range Salmonella phage and its pathogenic host. The model takes into consideration the main biological parameters that rule phage-bacteria interactions likewise the adsorption rate, latent period, burst size, bacterial growth rate, and substrate uptake rate, among others. The experimental validation of the model was performed with data from phage-interaction studies in a 5 L bioreactor. The key and innovative aspect of the model was the introduction of variations in the latent period and adsorption rate values that are considered as constants in previous developed models. By modelling the latent period as a normal distribution of values and the adsorption rate as a function of the bacterial growth rate it was possible to accurately predict the behaviour of the phage-bacteria population. The model was shown to predict simulated data with a good agreement with the experimental observations and explains how a lytic phage and its host bacteria are able to coexist.Financial support was received through the Strategic Project PEst-OE/EQB/LA0023/2013 from the FCT-Fundacao para a Ciencia e Tecnologia (http://www.fct.pt) and the projects "BioHealth - Biotechnology and Bioengineering approaches to improve health quality'', Ref. NORTE-07-0124 FEDER-000027, co-funded by the Programa Operacional Regional do Norte (ON.2 - O Novo Norte), QREN, FEDER and "Consolidating Research Expertise and Resources on Cellular and Molecular Biotechnology at CEB/IBB'', Ref. FCOMP-01-0124-FEDER-027462. Silvio B. Santos was supported by the grant SFRH/BPD/75311/2010 and Carla Carvalho was supported by the grant SFRH/BPD/79365/2011 both from the FCT-Fundacao para a Ciencia e Tecnologia (http://www.fct.pt). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Biological and biomedical implications of the co-evolution of pathogens and their hosts

Co-evolution between host and pathogen is, in principle, a powerful determinant of the biology and genetics of infection and disease. Yet co-evolution has proven difficult to demonstrate rigorously in practice, and co-evolutionary thinking is only just beginning to inform medical or veterinary research in any meaningful way, even though it can have a major influence on how genetic variation in biomedically important traits is interpreted. Improving our understanding of the biomedical significance of co-evolution will require changing the way in which we look for it, complementing the phenomenological approach traditionally favored by evolutionary biologists with the exploitation of the extensive data becoming available on the molecular biology and molecular genetics of host–pathogen interactions