Designing fast converging phylogenetic methods

Absolute fast converging phylogenetic reconstruction methods are provably guaranteed to recover the true tree with high probability from sequences that grow only polynomially in the number of leaves, once the edge lengths are bounded arbitrarily from above and below. Only a few methods have been determined to be absolute fast converging; these have all been developed in just the last few years, and most are polynomial time. In this paper, we compare pre-existing fast converging methods as well as some new polynomial time methods that we have developed. Our study, based upon simulating evolution under a wide range of model conditions, establishes that our new methods outperform both neighbor joining and the previous fast converging methods, returning very accurate large trees, when these other methods do poorly.     

Mutations in Global Regulators Lead to Metabolic Selection during Adaptation to Complex Environments

Adaptation to ecologically complex environments can provide insights into the evolutionary dynamics and functional constraints encountered by organisms during natural selection. Adaptation to a new environment with abundant and varied resources can be difficult to achieve by small incremental changes if many mutations are required to achieve even modest gains in fitness. Since changing complex environments are quite common in nature, we investigated how such an epistatic bottleneck can be avoided to allow rapid adaptation. We show that adaptive mutations arise repeatedly in independently evolved populations in the context of greatly increased genetic and phenotypic diversity. We go on to show that weak selection requiring substantial metabolic reprogramming can be readily achieved by mutations in the global response regulator arcA and the stress response regulator rpoS. We identified 46 unique single-nucleotide variants of arcA and 18 mutations in rpoS, nine of which resulted in stop codons or large deletions, suggesting that subtle modulations of ArcA function and knockouts of rpoS are largely responsible for the metabolic shifts leading to adaptation. These mutations allow a higher order metabolic selection that eliminates epistatic bottlenecks, which could occur when many changes would be required. Proteomic and carbohydrate analysis of adapting E. coli populations revealed an up-regulation of enzymes associated with the TCA cycle and amino acid metabolism, and an increase in the secretion of putrescine. The overall effect of adaptation across populations is to redirect and efficiently utilize uptake and catabolism of abundant amino acids. Concomitantly, there is a pronounced spread of more ecologically limited strains that results from specialization through metabolic erosion. Remarkably, the global regulators arcA and rpoS can provide a “one-step” mechanism of adaptation to a novel environment, which highlights the importance of global resource management as a powerful strategy to adaptation.     

Coalescent histories on phylogenetic networks and detection of hybridization despite incomplete lineage sorting

Analyses of the increasingly available genomic data continue to reveal the extent of hybridization and its role in the evolutionary diversification of various groups of species. We show, through extensive coalescent-based simulations of multilocus data sets on phylogenetic networks, how divergence times before and after hybridization events can result in incomplete lineage sorting with gene tree incongruence signatures identical to those exhibited by hybridization. Evolutionary analysis of such data under the assumption of a species tree model can miss all hybridization events, whereas analysis under the assumption of a species network model would grossly overestimate hybridization events. These issues necessitate a paradigm shift in evolutionary analysis under these scenarios, from a model that assumes a priori a single source of gene tree incongruence to one that integrates multiple sources in a unifying framework. We propose a framework of coalescence within the branches of a phylogenetic network and show how this framework can be used to detect hybridization despite incomplete lineage sorting. We apply the model to simulated data and show that the signature of hybridization can be revealed as long as the interval between the divergence times of the species involved in hybridization is not too small. We reanalyze a data set of 106 loci from 7 in-group Saccharomyces species for which a species tree with no hybridization has been reported in the literature. Our analysis supports the hypothesis that hybridization occurred during the evolution of this group, explaining a large amount of the incongruence in the data. Our findings show that an integrative approach to gene tree incongruence and its reconciliation is needed. Our framework will help in systematically analyzing genomic data for the occurrence of hybridization and elucidating its evolutionary role.     

Properties of metabolic graphs: biological organization or representation artifacts?

Background  

Standard graphs, where each edge links two nodes, have been extensively used to represent the connectivity of metabolic networks. It is based on this representation that properties of metabolic networks, such as hierarchical and small-world structures, have been elucidated and null models have been proposed to derive biological organization hypotheses. However, these graphs provide a simplistic model of a metabolic network's connectivity map, since metabolic reactions often involve more than two reactants. In other words, this map is better represented as a hypergraph. Consequently, a question that naturally arises in this context is whether these properties truly reflect biological organization or are merely an artifact of the representation.     

Identification of Three Distinct Phylogenetic Groups of CAX Cation/Proton Antiporters

Ca²⁺/cation antiporter (CaCA) proteins are integral membrane proteins that transport Ca²⁺ or other cations using the H⁺ or Na⁺ gradient generated by primary transporters. The CAX (for CAtion eXchanger) family is one of the five families that make up the CaCA superfamily. CAX genes have been found in bacteria, Dictyostelium, fungi, plants, and lower vertebrates, but only a small number of CAXs have been functionally characterized. In this study, we explored the diversity of CAXs and their phylogenetic relationships. The results demonstrate that there are three major types of CAXs: type I (CAXs similar to Arabidopsis thaliana CAX1, found in plants, fungi, and bacteria), type II (CAXs with a long N-terminus hydrophilic region, found in fungi, Dictyostelium, and lower vertebrates), and type III (CAXs similar to Escherichia coli ChaA, found in bacteria). Some CAXs were found to have secondary structures that are different from the canonical six transmembrane (TM) domains–acidic motif-five TM domain structure. Our phylogenetic tree indicated no evidence to support the cyanobacterial origin of plant CAXs or the classification of Arabidopsis exchangers CAX7 to CAX11. For the first time, these results clearly define the CAX exchanger family and its subtypes in phylogenetic terms. The surprising diversity of CAXs demonstrates their potential range of biochemical properties and physiologic relevance. Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users. [Reviewing Editor: David Guttman]     

Vulpinic acids inhibit influenza (RNA) viruses but not herpes (DNA) viruses

Three synthetic vulpinic acids inhibited two influenza RNA viruses, type A (Philippine) and B (Paraha), in tissue culture with ID₅₀ values ranging from 3.9 to 15.5 g/ml. They had no activity against a third influenza virus or against two herpes viruses.

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Résumé Trois acides vulpiniques de synthèse inhibent deux virus à DNA de l'influenza, types A (Philippine) et B (Paraha), en culture tissulalre avec des valeurs d'ID₅₀ s'étalant de 3.9 à 15.5 g/ml. Ces acides vulpiniques ne présentent d'activité ni contre un trolalème virus de l'influenza, ni contre deux virus de l'herpes.

     

An Evaluation of Methods for Inferring Boolean Networks from Time-Series Data

Regulatory networks play a central role in cellular behavior and decision making. Learning these regulatory networks is a major task in biology, and devising computational methods and mathematical models for this task is a major endeavor in bioinformatics. Boolean networks have been used extensively for modeling regulatory networks. In this model, the state of each gene can be either ‘on’ or ‘off’ and that next-state of a gene is updated, synchronously or asynchronously, according to a Boolean rule that is applied to the current-state of the entire system. Inferring a Boolean network from a set of experimental data entails two main steps: first, the experimental time-series data are discretized into Boolean trajectories, and then, a Boolean network is learned from these Boolean trajectories. In this paper, we consider three methods for data discretization, including a new one we propose, and three methods for learning Boolean networks, and study the performance of all possible nine combinations on four regulatory systems of varying dynamics complexities. We find that employing the right combination of methods for data discretization and network learning results in Boolean networks that capture the dynamics well and provide predictive power. Our findings are in contrast to a recent survey that placed Boolean networks on the low end of the “faithfulness to biological reality” and “ability to model dynamics” spectra. Further, contrary to the common argument in favor of Boolean networks, we find that a relatively large number of time points in the time-series data is required to learn good Boolean networks for certain data sets. Last but not least, while methods have been proposed for inferring Boolean networks, as discussed above, missing still are publicly available implementations thereof. Here, we make our implementation of the methods available publicly in open source at http://bioinfo.cs.rice.edu/.     

A High Diversity of Eurasian Lineage Low Pathogenicity Avian Influenza A Viruses Circulate among Wild Birds Sampled in Egypt

Surveillance for influenza A viruses in wild birds has increased substantially as part of efforts to control the global movement of highly pathogenic avian influenza A (H5N1) virus. Studies conducted in Egypt from 2003 to 2007 to monitor birds for H5N1 identified multiple subtypes of low pathogenicity avian influenza A viruses isolated primarily from migratory waterfowl collected in the Nile Delta. Phylogenetic analysis of 28 viral genomes was performed to estimate their nearest ancestors and identify possible reassortants. Migratory flyway patterns were included in the analysis to assess gene flow between overlapping flyways. Overall, the viruses were most closely related to Eurasian, African and/or Central Asian lineage low pathogenicity viruses and belonged to 15 different subtypes. A subset of the internal genes seemed to originate from specific flyways (Black Sea-Mediterranean, East African-West Asian). The remaining genes were derived from a mixture of viruses broadly distributed across as many as 4 different flyways suggesting the importance of the Nile Delta for virus dispersal. Molecular clock date estimates suggested that the time to the nearest common ancestor of all viruses analyzed ranged from 5 to 10 years, indicating frequent genetic exchange with viruses sampled elsewhere. The intersection of multiple migratory bird flyways and the resulting diversity of influenza virus gene lineages in the Nile Delta create conditions favoring reassortment, as evident from the gene constellations identified by this study. In conclusion, we present for the first time a comprehensive phylogenetic analysis of full genome sequences from low pathogenic avian influenza viruses circulating in Egypt, underscoring the significance of the region for viral reassortment and the potential emergence of novel avian influenza A viruses, as well as representing a highly diverse influenza A virus gene pool that merits continued monitoring.