Microevolution of Helicobacter pylori during prolonged infection of single hosts and within families

Our understanding of basic evolutionary processes in bacteria is still very limited. For example, multiple recent dating estimates are based on a universal inter-species molecular clock rate, but that rate was calibrated using estimates of geological dates that are no longer accepted. We therefore estimated the short-term rates of mutation and recombination in Helicobacter pylori by sequencing an average of 39,300 bp in 78 gene fragments from 97 isolates. These isolates included 34 pairs of sequential samples, which were sampled at intervals of 0.25 to 10.2 years. They also included single isolates from 29 individuals (average age: 45 years) from 10 families. The accumulation of sequence diversity increased with time of separation in a clock-like manner in the sequential isolates. We used Approximate Bayesian Computation to estimate the rates of mutation, recombination, mean length of recombination tracts, and average diversity in those tracts. The estimates indicate that the short-term mutation rate is 1.4×10−6 (serial isolates) to 4.5×10−6 (family isolates) per nucleotide per year and that three times as many substitutions are introduced by recombination as by mutation. The long-term mutation rate over millennia is 5–17-fold lower, partly due to the removal of non-synonymous mutations due to purifying selection. Comparisons with the recent literature show that short-term mutation rates vary dramatically in different bacterial species and can span a range of several orders of magnitude

Automated unique input output sequence generation for conformance testing of FSMs

This paper describes a method for automatically generating unique input output (UIO) sequences for FSM conformance testing. UIOs are used in conformance testing to verify the end state of a transition sequence. UIO sequence generation is represented as a search problem and genetic algorithms are used to search this space. Empirical evidence indicates that the proposed method yields considerably better (up to 62% better) results compared with random UIO sequence generation

Force-induced misfolding in RNA

RNA folding is a kinetic process governed by the competition of a large number of structures stabilized by the transient formation of base pairs that may induce complex folding pathways and the formation of misfolded structures. Despite of its importance in modern biophysics, the current understanding of RNA folding kinetics is limited by the complex interplay between the weak base-pair interactions that stabilize the native structure and the disordering effect of thermal forces. The possibility of mechanically pulling individual molecules offers a new perspective to understand the folding of nucleic acids. Here we investigate the folding and misfolding mechanism in RNA secondary structures pulled by mechanical forces. We introduce a model based on the identification of the minimal set of structures that reproduce the patterns of force-extension curves obtained in single molecule experiments. The model requires only two fitting parameters: the attempt frequency at the level of individual base pairs and a parameter associated to a free energy correction that accounts for the configurational entropy of an exponentially large number of neglected secondary structures. We apply the model to interpret results recently obtained in pulling experiments in the three-helix junction S15 RNA molecule (RNAS15). We show that RNAS15 undergoes force-induced misfolding where force favors the formation of a stable non-native hairpin. The model reproduces the pattern of unfolding and refolding force-extension curves, the distribution of breakage forces and the misfolding probability obtained in the experiments.Comment: 28 pages, 11 figure

A graph theoretical analysis of the energy landscape of model polymers

In systems characterized by a rough potential energy landscape, local energetic minima and saddles define a network of metastable states whose topology strongly influences the dynamics. Changes in temperature, causing the merging and splitting of metastable states, have non trivial effects on such networks and must be taken into account. We do this by means of a recently proposed renormalization procedure. This method is applied to analyze the topology of the network of metastable states for different polypeptidic sequences in a minimalistic polymer model. A smaller spectral dimension emerges as a hallmark of stability of the global energy minimum and highlights a non-obvious link between dynamic and thermodynamic properties.Comment: 15 pages, 15 figure

MICC: A tool for computing short distances in the curve complex

The complex of curves $\mathcal{C}(S_g)$ of a closed orientable surface of genus $g \geq 2$ is the simplicial complex having its vertices, $\mathcal{C}^0(S_g)$, are isotopy classes of essential curves in $S_g$. Two vertices co-bound an edge of the $1$-skeleton, $\mathcal{C}^1(S_g)$, if there are disjoint representatives in $S_g$. A metric is obtained on $\mathcal{C}^0(S_g)$ by assigning unit length to each edge of $\mathcal{C}^1(S_g)$. Thus, the distance between two vertices, $d(v,w)$, corresponds to the length of a geodesic---a shortest edge-path between $v$ and $w$ in $\mathcal{C}^1 (S_g)$. Recently, Birman, Margalit and the second author introduced the concept of {\em initially efficient geodesics} in $\mathcal{C}^1(S_g)$ and used them to give a new algorithm for computing the distance between vertices. In this note we introduce the software package MICC ({\em Metric in the Curve Complex}), a partial implementation of the initially efficient geodesic algorithm. We discuss the mathematics underlying MICC and give applications. In particular, we give examples of distance four vertex pairs, for $g=2$ and 3. Previously, there was only one known example, in genus $2$, due to John Hempel.Comment: 19 pages, 9 figures, Version 2 has updated figures and reference