Role of biotic interactions in generating and maintaining biodiversity

Dissertation presented to obtain the Ph.D degree in Biology.Microbial populations constantly face pressures imposed by exposure to host immune systems and antibiotics. Thus it is important to have a better understanding of how they can adapt to such pressures. In this context, studying the process of adaptation of commensal bacteria towards becoming a pathogen and how resistance to antibiotics affects bacterial fitness are pressing questions.(...

Fitness Measurements of Evolved Esherichia coli

Bacteria can adapt very rapidly to novel selective pressures. In the transition from commensalism to pathogenicity bacteria have to face and adapt to the host immune system. Specifically, the antagonistic interaction imposed by one of the first line of defense of innate immunity cells, macrophages, on commensal bacteria, such as Escherichia coli (E. coli), can lead to its rapid adaptation. Such adaptation is characterized by the emergence of clones with mutations that allow them to better escape macrophage phagocytosis. Here, we describe how to quantify the amount of fitness increase of bacterial clones that evolved under the constant selective pressure of macrophages, from a murine cell line RAW 264.7. The most widely used assay for measuring fitness changes along an evolutionary laboratory experiment is a competitive fitness assay. This assay consists of determining how fast an evolved strain outcompetes the ancestral in a competition where each starts at equal frequency. The strains compete in the same environment of the evolution experiment and if the evolved strain has acquired strong beneficial mutations it will become significantly overrepresented in repeated competitive fitness assays.LAO/ITQB, FCT

Evolution of Escherichia coli to Macrophage Cell Line

The genomes of species of Escherichia coli (E. coli) show an extraordinary amount of diversity, which include commensal strains and strains belonging to different pathovars. Many strains of E. coli, which can cause mild or severe pathologies in humans, have a commensal ancestor. Understanding the evolutionary changes that can lead to a transition from commensal to pathogen is an important task, which requires integration of different methodologies. One method is experimental evolution of bacteria, in controlled environments, that mimic some of the selective pressures, likely to be important during the transition to pathogenesis. The success of such a transition will depend, at least partially, on ability of E. coli to adapt to the presence of cells of the immune system. Here, we describe a protocol for performing experimental evolution of a commensal strain of E. coli, a derivative of the well studied K12, under the constant selective pressure imposed by cells of the innate immune system, specifically RAW 264.7 murine macrophage cell line.LAO/ITQB, FCT

A novel high-content phenotypic screen to identify inhibitors of mitochondrial DNA maintenance in trypanosomes

Kinetoplastid parasites cause diverse neglected diseases in humans and livestock, with an urgent need for new treatments. The survival of kinetoplastids depends on their uniquely structured mitochondrial genome (kDNA), the eponymous kinetoplast. Here, we report the development of a high-content screen for pharmacologically induced kDNA loss, based on specific staining of parasites and automated image analysis. As proof of concept, we screened a diverse set of ∼14,000 small molecules and exemplify a validated hit as a novel kDNA-targeting compound

The Genetic Basis of <i>Escherichia coli</i> Pathoadaptation to Macrophages

<div><p>Antagonistic interactions are likely important driving forces of the evolutionary process underlying bacterial genome complexity and diversity. We hypothesized that the ability of evolved bacteria to escape specific components of host innate immunity, such as phagocytosis and killing by macrophages (MΦ), is a critical trait relevant in the acquisition of bacterial virulence. Here, we used a combination of experimental evolution, phenotypic characterization, genome sequencing and mathematical modeling to address how fast, and through how many adaptive steps, a commensal <i>Escherichia coli</i> (<i>E. coli</i>) acquire this virulence trait. We show that when maintained <i>in vitro</i> under the selective pressure of host MΦ commensal <i>E. coli</i> can evolve, in less than 500 generations, virulent clones that escape phagocytosis and MΦ killing <i>in vitro</i>, while increasing their pathogenicity <i>in vivo</i>, as assessed in mice. This pathoadaptive process is driven by a mechanism involving the insertion of a single transposable element into the promoter region of the <i>E. coli yrfF</i> gene. Moreover, transposition of the IS186 element into the promoter of <i>Lon</i> gene, encoding an ATP-dependent serine protease, is likely to accelerate this pathoadaptive process. Competition between clones carrying distinct beneficial mutations dominates the dynamics of the pathoadaptive process, as suggested from a mathematical model, which reproduces the observed experimental dynamics of <i>E. coli</i> evolution towards virulence. In conclusion, we reveal a molecular mechanism explaining how a specific component of host innate immunity can modulate microbial evolution towards pathogenicity.</p></div

Emergency of morphological diversity in the bacterial populations adapting to MΦ.

<p>(A) Examples of the variability for colony morphology that emerged in <i>E. coli</i> populations adapting to MΦ, from left to right – ANC stands for morphology of ancestral, SCV for the small colony variants morphology and MUC for the mucoid colony morphology. (B) Dynamics of frequency change of the evolved phenotypes in each replicate evolving populations (M1 to M6): white squares indicate ANC, black triangles SCV, black circles MUC phenotypes.</p

Mutations acquired by evolved clones identified through whole genome re-sequencing (WGS).

<p>Mutations in intergenic regions have the two flanking genes listed (e.g., <i>clpX</i>/<i>lon</i>). SNPs are represented by an arrow between the ancestral and the evolved nucleotide. Whenever a SNP gives rise to a non-synonymous mutation the amino acid replacement is also indicated. The symbol Δ means a deletion. For intergenic mutations, the numbers in the Mutation row represent nucleotides relative to each of the neighboring genes, here + indicates the distance downstream of the stop codon of a gene and − indicates the distance upstream of the gene, that is relative to the start codon. Insertions of IS elements are denoted by the specific IS element followed by the number of repeated bases caused by its insertion.</p

Predictions of model of clonal interference for changes in mucoid frequencies with time.

<p>Simulations of the adaptive dynamics over the period of the experiment (30 days). The frequencies of mucoid phenotypes are plotted and can be compared to those observed in the experiments (<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003802#ppat-1003802-g001" target="_blank">Fig. 1B</a>). The values of parameters used and the dynamics of haplotypes that compete for fixation are shown in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003802#ppat.1003802.s009" target="_blank">Figure S9</a>.</p

<i>In vitro</i> evolved <i>E. coli</i> show increased virulence <i>in vivo</i>.

<p><b>A</b>) Survival of mice infected with different doses of ancestral (ANC, in blue), mucoid bacteria evolved in the presence of MΦ (MUC, in red) or bacteria evolved in the absence of MΦ (CON, in green). The number of mice are shown inside the bars, <b>B</b>) Survival probability of mice infected with ANC, MUC and CON, represented as lines from the fit of a binomial General Linear Model used to infer LD₅₀, <b>C</b>) Kaplan-Meier curves and <b>D</b>) % maximum reduction in temperature or weight at the LD₅₀ dose for the MUC (n = 10), ANC (n = 11) and CON (n = 5) (Error bars correspond to 2SE, * indicates p<0.05).</p