The evolution of the phage shock protein response system: interplay between protein function, genomic organization, and system function.

Sensing the environment and responding appropriately to it are key capabilities for the survival of an organism. All extant organisms must have evolved suitable sensors, signaling systems, and response mechanisms allowing them to survive under the conditions they are likely to encounter. Here, we investigate in detail the evolutionary history of one such system: The phage shock protein (Psp) stress response system is an important part of the stress response machinery in many bacteria, including Escherichia coli K12. Here, we use a systematic analysis of the genes that make up and regulate the Psp system in E. coli in order to elucidate the evolutionary history of the system. We compare gene sharing, sequence evolution, and conservation of protein-coding as well as noncoding DNA sequences and link these to comparative analyses of genome/operon organization across 698 bacterial genomes. Finally, we evaluate experimentally the biological advantage/disadvantage of a simplified version of the Psp system under different oxygen-related environments. Our results suggest that the Psp system evolved around a core response mechanism by gradually co-opting genes into the system to provide more nuanced sensory, signaling, and effector functionalities. We find that recruitment of new genes into the response machinery is closely linked to incorporation of these genes into a psp operon as is seen in E. coli, which contains the bulk of genes involved in the response. The organization of this operon allows for surprising levels of additional transcriptional control and flexibility. The results discussed here suggest that the components of such signaling systems will only be evolutionarily conserved if the overall functionality of the system can be maintained.

Assessing coverage of protein interaction data using capture-recapture models.

Protein interaction networks comprise thousands of individual binary links between distinct proteins. Whilst these data have attracted considerable attention and been the focus of many different studies, the networks, their structure, function, and how they change over time are still not fully known. More importantly, there is still considerable uncertainty regarding their size, and the quality of the available data continues to be questioned. Here, we employ statistical models of the experimental sampling process, in particular capture-recapture methods, in order to assess the false discovery rate and size of protein interaction networks. We uses these methods to gauge the ability of different experimental systems to find the true binary interactome. Our model allows us to obtain estimates for the size and false-discovery rate from simple considerations regarding the number of repeatedly interactions, and provides suggestions as to how we can exploit this information in order to reduce the effects of noise in such data. In particular our approach does not require a reference dataset. We estimate that approximately more than half of the true physical interactome has now been sampled in yeast.

Phylodynamics for cell biologists.

Multicellular organisms are composed of cells connected by ancestry and descent from progenitor cells. The dynamics of cell birth, death, and inheritance within an organism give rise to the fundamental processes of development, differentiation, and cancer. Technical advances in molecular biology now allow us to study cellular composition, ancestry, and evolution at the resolution of individual cells within an organism or tissue. Here, we take a phylogenetic and phylodynamic approach to single-cell biology. We explain how "tree thinking" is important to the interpretation of the growing body of cell-level data and how ecological null models can benefit statistical hypothesis testing. Experimental progress in cell biology should be accompanied by theoretical developments if we are to exploit fully the dynamical information in single-cell data.

Ecology. Species-area relations in tropical forests.

A power law called the species-area relationship describes the finding that the number of species is proportional to the size of the area in which they are found, raised to an exponent (usually, a number between 0.2 and 0.3). In their Perspective, May and Stumpf discuss new results from a survey of five tropical forest census areas containing a total of a million trees. They explain how this large data set can be used to fine-tune the existing power law so that it provides a better prediction of species diversity in small census samples.

Genealogical and evolutionary inference with the human Y chromosome.

Population genetics has emerged as a powerful tool for unraveling human history. In addition to the study of mitochondrial and autosomal DNA, attention has recently focused on Y-chromosome variation. Ambiguities and inaccuracies in data analysis, however, pose an important obstacle to further development of the field. Here we review the methods available for genealogical inference using Y-chromosome data. Approaches can be divided into those that do and those that do not use an explicit population model in genealogical inference. We describe the strengths and weaknesses of these model-based and model-free approaches, as well as difficulties associated with the mutation process that affect both methods. In the case of genealogical inference using microsatellite loci, we use coalescent simulations to show that relatively simple generalizations of the mutation process can greatly increase the accuracy of genealogical inference. Because model-free and model-based approaches have different biases and limitations, we conclude that there is considerable benefit in the continued use of both types of approaches.

SNPSTR: a database of compound microsatellite-SNP markers.

There has been widespread and growing interest in genetic markers suitable for drawing population genetic inferences about past demographic events and to detect the effects of selection. In addition to single nucleotide polymorphisms (SNPs), microsatellites (or short tandem repeats, STRs) have received great attention in the analysis of human population history. In the SNPSTR database (http://www.imperial.ac.uk/theoreticalgenomics/data-software) we catalogue a relatively new type of compound genetic marker called SNPSTR which combines a microsatellite marker (STR) with one or more tightly linked SNPs. Here, the SNP(s) and the microsatellite are less than 250 bp apart so each SNPSTR can be considered a small haplotype with no recombination occurring between the two individual markers. Thus, SNPSTRs have the potential to become a very useful tool in the field of population genetics. The SNPSTR database contains all inferable human SNPSTRs as well as those in mouse, rat, dog and chicken, i.e. all model organisms for which extensive SNP datasets are available.

Construction of quasipotentials for stochastic dynamical systems: An optimization approach.

The construction of effective and informative landscapes for stochastic dynamical systems has proven a long-standing and complex problem. In many situations, the dynamics may be described by a Langevin equation while constructing a landscape comes down to obtaining the quasipotential, a scalar function that quantifies the likelihood of reaching each point in the state space. In this work we provide a novel method for constructing such landscapes by extending a tool from control theory: the sum-of-squares method for generating Lyapunov functions. Applicable to any system described by polynomials, this method provides an analytical polynomial expression for the potential landscape, in which the coefficients of the polynomial are obtained via a convex optimization problem. The resulting landscapes are based on a decomposition of the deterministic dynamics of the original system, formed in terms of the gradient of the potential and a remaining "curl" component. By satisfying the condition that the inner product of the gradient of the potential and the remaining dynamics is everywhere negative, our derived landscapes provide both upper and lower bounds on the true quasipotential; these bounds becoming tight if the decomposition is orthogonal. The method is demonstrated to correctly compute the quasipotential for high-dimensional linear systems and also for a number of nonlinear examples.

RNA replication kinetics, genetic polymorphism and selection in the case of the hepatitis C virus.

We show in a simple theoretical quasispecies model that the replication dynamics of hepatitis C virus and a related model-system, the bovine viral diarrhoea virus, result in an effective reduction of RNA templates in infected cells. Viral fitness does not translate directly into RNA sequence replication efficiency, and hence the abundance of the viral master sequences diminishes over time. Our results suggest that genes not involved in RNA replication accumulate mutations over time because they do not undergo selection during this phase. The selection of viral RNA occurs not only during replication but also during the ensuing stages of the viral life cycle: (i) envelopment of viral RNA and (ii) successful infection of other cells, which also requires functionality of non-replicative genes. In particular, viral fitness requires the ability of the genome to encode structural proteins which do not encounter selective pressure during RNA replication. We conclude by discussing the potential value of antiviral drugs which inhibit selection on parts of the viral genome.

Genetic diversity and models of viral evolution for the hepatitis C virus.

In this review we discuss the application of theoretical frameworks to the interpretation of viral gene sequence data, with particular reference to the hepatitis C virus (HCV). The increasing availability of such data means that it is now possible (and necessary) to proceed from simple qualitative models of viral evolution, to more quantitative frameworks based on statistical inference, notably population genetics and molecular phylogenetics. We argue that these approaches are invaluable tools to the virologist and are essential for understanding the dynamics of viral infection and the outcome of therapeutic strategies. We use several recent HCV data-sets to illustrate the methods.

Mapping the parameters of prion-induced neuropathology.

We present a theoretical framework that enables us to dissect out the parametric dependencies of the pathogenesis of prion diseases. We are able to determine the influence of both host-dependent factors (connectivity, cell density, protein synthesis rate, and cell death) and strain-dependent factors (cell tropism, virulence, and replication rate). We use a model based on a linked system of differential equations on a lattice to explore how the regional distribution of central nervous system pathology in Creutzfeldt-Jakob disease, Gerstmann-Sträussler-Scheinker syndrome, and fatal familial insomnia relates to each of these factors. The model then is used to make qualitative predictions about the pathology for two possible hypothetical triggers of neuronal loss in prion diseases. Pathological progression in overexpressing mouse models has been shown to depend on the site of initial infection. The model allows us to compare the pathologies resulting from different inoculation routes.

A predominantly indigenous paternal heritage for the Austronesian-speaking peoples of insular Southeast Asia and Oceania.

Modern humans reached Southeast Asia and Oceania in one of the first dispersals out of Africa. The resulting temporal overlap of modern and archaic humans-and the apparent morphological continuity between them-has led to claims of gene flow between Homo sapiens and H. erectus. Much more recently, an agricultural technology from mainland Asia spread into the region, possibly in association with Austronesian languages. Using detailed genealogical study of Y chromosome variation, we show that the majority of current Austronesian speakers trace their paternal heritage to Pleistocene settlers in the region, as opposed to more-recent agricultural immigrants. A fraction of the paternal heritage, however, appears to be associated with more-recent immigrants from northern populations. We also show that the northern Neolithic component is very unevenly dispersed through the region, with a higher contribution in Southeast Asia and a nearly complete absence in Melanesia. Contrary to claims of gene flow (under regional continuity) between H. erectus and H. sapiens, we found no ancestral Y chromosome lineages in a set of 1,209 samples. The finding excludes the possibility that early hominids contributed significantly to the paternal heritage of the region.