Predicting evolution and visualizing high-dimensional fitness landscapes

The tempo and mode of an adaptive process is strongly determined by the structure of the fitness landscape that underlies it. In order to be able to predict evolutionary outcomes (even on the short term), we must know more about the nature of realistic fitness landscapes than we do today. For example, in order to know whether evolution is predominantly taking paths that move upwards in fitness and along neutral ridges, or else entails a significant number of valley crossings, we need to be able to visualize these landscapes: we must determine whether there are peaks in the landscape, where these peaks are located with respect to one another, and whether evolutionary paths can connect them. This is a difficult task because genetic fitness landscapes (as opposed to those based on traits) are high-dimensional, and tools for visualizing such landscapes are lacking. In this contribution, we focus on the predictability of evolution on rugged genetic fitness landscapes, and determine that peaks in such landscapes are highly clustered: high peaks are predominantly close to other high peaks. As a consequence, the valleys separating such peaks are shallow and narrow, such that evolutionary trajectories towards the highest peak in the landscape can be achieved via a series of valley crossingsComment: 12 pages, 7 figures. To appear in "Recent Advances in the Theory and Application of Fitness Landscapes" (A. Engelbrecht and H. Richter, eds.). Springer Series in Emergence, Complexity, and Computation, 201

Association of LEC and tnpA Helicobacter pylori genes with gastric cancer in a Brazilian population

<p>Abstract</p> <p>Background</p> <p><it>H. pylori </it>seroprevalence in Brazilians varies and is dependent on socioeconomic status, sanitation conditions and ethnicity; furthermore, <it>H. pylori </it>is not always associated with the incidence of gastric cancer, suggesting the role of more virulent strains. The purpose of this study was to analyze the association of more virulent <it>H. pylori </it>strains with gastric cancer.</p> <p>Methods</p> <p>DNA was extracted from gastric biopsies of thirty-four cases of gastric cancer (11 intestinal-type, 23 diffuse-type), and thirty-four of patients with endoscopic gastritis. The presence of <it>cag</it>PAI genes (<it>cagA</it>, <it>cagA </it>promoter, <it>cagE</it>, <it>cagM</it>, <it>tnpB</it>, <it>tnpA</it>, <it>cagT </it>and the left end of the <it>cag</it>II (LEC)) and <it>babA </it>were analyzed by PCR.</p> <p>Results</p> <p>Comparison of <it>H. pylori </it>isolates from gastric cancer and gastritis patients showed significant associations of <it>tnpA </it>and LEC with gastric cancer (73.5% [OR, 6.66; 95% CI, 2.30-19.25] and 58.8% [OR, 10.71; 95% CI, 3.07-37.28] of cases, respectively). Other <it>cag</it>PAI genes were detected in both groups at similar frequencies.</p> <p>Conclusions</p> <p><it>tnpA </it>and LEC of <it>H. pylori cag</it>PAI were associated with gastric cancer; nonetheless, these results were restricted within this group of patients and further studies are needed to confirm these results in a larger sample and determine their role in gastric carcinogenesis.</p

Identification of Prophages in Bacterial Genomes by Dinucleotide Relative Abundance Difference

BACKGROUND: Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many virulence-associated genes are reported to be prophage encoded. Present computational methods to detect prophages are either by identifying possible essential proteins such as integrases or by an extension of this technique, which involves identifying a region containing proteins similar to those occurring in prophages. These methods suffer due to the problem of low sequence similarity at the protein level, which suggests that a nucleotide based approach could be useful. METHODOLOGY: Earlier dinucleotide relative abundance (DRA) have been used to identify regions, which deviate from the neighborhood areas, in genomes. We have used the difference in the dinucleotide relative abundance (DRAD) between the bacterial and prophage DNA to aid location of DNA stretches that could be of prophage origin in bacterial genomes. Prophage sequences which deviate from bacterial regions in their dinucleotide frequencies are detected by scanning bacterial genome sequences. The method was validated using a subset of genomes with prophage data from literature reports. A web interface for prophage scan based on this method is available at http://bicmku.in:8082/prophagedb/dra.html. Two hundred bacterial genomes which do not have annotated prophages have been scanned for prophage regions using this method. CONCLUSIONS: The relative dinucleotide distribution difference helps detect prophage regions in genome sequences. The usefulness of this method is seen in the identification of 461 highly probable loci pertaining to prophages which have not been annotated so earlier. This work emphasizes the need to extend the efforts to detect and annotate prophage elements in genome sequences

A Single Nucleotide Change Affects Fur-Dependent Regulation of sodB in H. pylori

Helicobacter pylori is a significant human pathogen that has adapted to survive the many stresses found within the gastric environment. Superoxide Dismutase (SodB) is an important factor that helps H. pylori combat oxidative stress. sodB was previously shown to be repressed by the Ferric Uptake Regulator (Fur) in the absence of iron (apo-Fur regulation) [1]. Herein, we show that apo regulation is not fully conserved among all strains of H. pylori. apo-Fur dependent changes in sodB expression are not observed under iron deplete conditions in H. pylori strains G27, HPAG1, or J99. However, Fur regulation of pfr and amiE occurs as expected. Comparative analysis of the Fur coding sequence between G27 and 26695 revealed a single amino acid difference, which was not responsible for the altered sodB regulation. Comparison of the sodB promoters from G27 and 26695 also revealed a single nucleotide difference within the predicted Fur binding site. Alteration of this nucleotide in G27 to that of 26695 restored apo-Fur dependent sodB regulation, indicating that a single base difference is at least partially responsible for the difference in sodB regulation observed among these H. pylori strains. Fur binding studies revealed that alteration of this single nucleotide in G27 increased the affinity of Fur for the sodB promoter. Additionally, the single base change in G27 enabled the sodB promoter to bind to apo-Fur with affinities similar to the 26695 sodB promoter. Taken together these data indicate that this nucleotide residue is important for direct apo-Fur binding to the sodB promoter

Supramolecular Organization of the Repetitive Backbone Unit of the Streptococcus pneumoniae Pilus

Streptococcus pneumoniae, like many other Gram-positive bacteria, assembles long filamentous pili on their surface through which they adhere to host cells. Pneumococcal pili are formed by a backbone, consisting of the repetition of the major component RrgB, and two accessory proteins (RrgA and RrgC). Here we reconstruct by transmission electron microscopy and single particle image reconstruction method the three dimensional arrangement of two neighbouring RrgB molecules, which represent the minimal repetitive structural domain of the native pilus. The crystal structure of the D2-D4 domains of RrgB was solved at 1.6 Å resolution. Rigid-body fitting of the X-ray coordinates into the electron density map enabled us to define the arrangement of the backbone subunits into the S. pneumoniae native pilus. The quantitative fitting provide evidence that the pneumococcal pilus consists uniquely of RrgB monomers assembled in a head-to-tail organization. The presence of short intra-subunit linker regions connecting neighbouring domains provides the molecular basis for the intrinsic pilus flexibility

Structure and dynamics of the pan-genome of Streptococcus pneumoniae and closely related species

Background Streptococcus pneumoniae is one of the most important causes of microbial diseases in humans. The genomes of 44 diverse strains of S. pneumoniae were analyzed and compared with strains of non-pathogenic streptococci of the Mitis group. Results Despite evidence of extensive recombination, the S. pneumoniae phylogenetic tree revealed six major lineages. With the exception of serotype 1, the tree correlated poorly with capsular serotype, geographical site of isolation and disease outcome. The distribution of dispensable genes, genes present in not all, but more than one strain, was consistent with phylogeny, although horizontal gene transfer events attenuated this correlation in the case of ancient lineages. Homologous recombination, involving short stretches of DNA, was the dominant 13 evolutionary process of the core genome of S. pneumoniae. Genetic exchange occurred both within and across the borders of the species, and S. mitis was the main reservoir of genetic diversity of S. pneumoniae. The pan-genome size of S. pneumoniae increased logarithmically with the number of strains and linearly with the number of polymorphic sites of the sampled genomes, suggesting that acquired genes accumulate proportionately to the age of clones. Most genes associated with pathogenicity were shared by all S. pneumoniae strains, but were also present in S. mitis, S. oralis and S. infantis, indicating that these genes are not sufficient to determine virulence. Conclusion Genetic exchange with related species sharing the same ecological niche is the main mechanism of evolution of S. pneumoniae. The open pan genome guarantees the species a quick and economical response to diverse environments

An Anomalous Type IV Secretion System in Rickettsia Is Evolutionarily Conserved

Bacterial type IV secretion systems (T4SSs) comprise a diverse transporter family functioning in conjugation, competence, and effector molecule (DNA and/or protein) translocation. Thirteen genome sequences from Rickettsia, obligate intracellular symbionts/pathogens of a wide range of eukaryotes, have revealed a reduced T4SS relative to the Agrobacterium tumefaciens archetype (vir). However, the Rickettsia T4SS has not been functionally characterized for its role in symbiosis/virulence, and none of its substrates are known.Superimposition of T4SS structural/functional information over previously identified Rickettsia components implicate a functional Rickettsia T4SS. virB4, virB8 and virB9 are duplicated, yet only one copy of each has the conserved features of similar genes in other T4SSs. An extraordinarily duplicated VirB6 gene encodes five hydrophobic proteins conserved only in a short region known to be involved in DNA transfer in A. tumefaciens. virB1, virB2 and virB7 are newly identified, revealing a Rickettsia T4SS lacking only virB5 relative to the vir archetype. Phylogeny estimation suggests vertical inheritance of all components, despite gene rearrangements into an archipelago of five islets. Similarities of Rickettsia VirB7/VirB9 to ComB7/ComB9 proteins of epsilon-proteobacteria, as well as phylogenetic affinities to the Legionella lvh T4SS, imply the Rickettsiales ancestor acquired a vir-like locus from distantly related bacteria, perhaps while residing in a protozoan host. Modern modifications of these systems likely reflect diversification with various eukaryotic host cells.We present the rvh (Rickettsiales vir homolog) T4SS, an evolutionary conserved transporter with an unknown role in rickettsial biology. This work lays the foundation for future laboratory characterization of this system, and also identifies the Legionella lvh T4SS as a suitable genetic model

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