Extensive recombination events and horizontal gene transfer shaped the Legionella pneumophila genomes

<p>Abstract</p> <p>Background</p> <p><it>Legionella pneumophila </it>is an intracellular pathogen of environmental protozoa. When humans inhale contaminated aerosols this bacterium may cause a severe pneumonia called Legionnaires' disease. Despite the abundance of dozens of <it>Legionella </it>species in aquatic reservoirs, the vast majority of human disease is caused by a single serogroup (Sg) of a single species, namely <it>L. pneumophila </it>Sg1. To get further insights into genome dynamics and evolution of Sg1 strains, we sequenced strains Lorraine and HL 0604 1035 (Sg1) and compared them to the available sequences of Sg1 strains Paris, Lens, Corby and Philadelphia, resulting in a comprehensive multigenome analysis.</p> <p>Results</p> <p>We show that <it>L. pneumophila </it>Sg1 has a highly conserved and syntenic core genome that comprises the many eukaryotic like proteins and a conserved repertoire of over 200 Dot/Icm type IV secreted substrates. However, recombination events and horizontal gene transfer are frequent. In particular the analyses of the distribution of nucleotide polymorphisms suggests that large chromosomal fragments of over 200 kbs are exchanged between <it>L. pneumophila </it>strains and contribute to the genome dynamics in the natural population. The many secretion systems present might be implicated in exchange of these fragments by conjugal transfer. Plasmids also play a role in genome diversification and are exchanged among strains and circulate between different <it>Legionella </it>species.</p> <p>Conclusion</p> <p>Horizontal gene transfer among bacteria and from eukaryotes to <it>L. pneumophila </it>as well as recombination between strains allows different clones to evolve into predominant disease clones and others to replace them subsequently within relatively short periods of time.</p

Stochastic Differential Systems with Memory: Theory, Examples and Applications

The purpose of this article is to introduce the reader to certain aspects of stochastic differential systems, whose evolution depends on the past history of the state. Chapter I begins with simple motivating examples. These include the noisy feedback loop, the logistic time-lag model with Gaussian noise , and the classical ``heat-bath model of R. Kubo , modeling the motion of a ``large molecule in a viscous fluid. These examples are embedded in a general class of stochastic functional differential equations (sfde\u27s). We then establish pathwise existence and uniqueness of solutions to these classes of sfde\u27s under local Lipschitz and linear growth hypotheses on the coefficients. It is interesting to note that the above class of sfde\u27s is not covered by classical results of Protter, Metivier and Pellaumail and Doleans-Dade. In Chapter II, we prove that the Markov (Feller) property holds for the trajectory random field of a sfde. The trajectory Markov semigroup is not strongly continuous for positive delays, and its domain of strong continuity does not contain tame (or cylinder) functions with evaluations away from zero. To overcome this difficulty, we introduce a class of quasitame functions. These belong to the domain of the weak infinitesimal generator, are weakly dense in the underlying space of continuous functions and generate the Borel $\sigma$-algebra of the state space. This chapter also contains a derivation of a formula for the weak infinitesimal generator of the semigroup for sufficiently regular functions, and for a large class of quasitame functions. In Chapter III, we study pathwise regularity of the trajectory random field in the time variable and in the initial path. Of note here is the non-existence of the stochastic flow for the singular sdde $dx(t)= x(t-r) dW(t)$ and a breakdown of linearity and local boundedness. This phenomenon is peculiar to stochastic delay equations. It leads naturally to a classification of sfde\u27s into regular and singular types. Necessary and sufficient conditions for regularity are not known. The rest of Chapter III is devoted to results on sufficient conditions for regularity of linear systems driven by white noise or semimartingales, and Sussman-Doss type nonlinear sfde\u27s. Building on the existence of a compacting stochastic flow, we develop a multiplicative ergodic theory for regular linear sfde\u27s driven by white noise, or general helix semimartingales (Chapter IV). In particular, we prove a Stable Manifold Theorem for such systems. In Chapter V, we seek asymptotic stability for various examples of one-dimensional linear sfde\u27s. Our approach is to obtain upper and lower estimates for the top Lyapunov exponent. Several topics are discussed in Chapter VI. These include the existence of smooth densities for solutions of sfde\u27s using the Malliavin calculus, an approximation technique for multidimensional diffusions using sdde\u27s with small delays, and affine sfde\u27s