Yes / There are more than 200 published species within the Lactobacillus genus complex (LGC), the majority of which have sequenced type strain genomes available. Although genome-based species delimitation cutoffs are accepted as the gold standard by the community, these are seldom actually checked for new or already published species. In addition, the availability of genome data is revealing inconsistencies in the species-level classification of many strains. We constructed a de novo species taxonomy for the LGC based on 2,459 publicly available genomes, using a 94% core nucleotide identity cutoff. We reconciled these de novo species with published species and subspecies names by (i) identifying genomes of type strains and (ii) comparing 16S rRNA genes of the genomes with 16S rRNA genes of type strains. We found that genomes within the LGC could be divided into 239 de novo species that were discontinuous and exclusive. Comparison of these de novo species to published species led to the identification of nine sets of published species that can be merged and one species that can be split. Further, we found at least eight de novo species that constitute new, unpublished species. Finally, we reclassified 74 genomes on the species level and identified for the first time the species of 98 genomes. Overall, the current state of LGC species taxonomy is largely consistent with genome-based species delimitation cutoffs. There are, however, exceptions that should be resolved to evolve toward a taxonomy where species share a consistent diversity in terms of sequence divergence. / This study was supported by the Research Foundation Flanders (grant 11A0618N), the Flanders Innovation and Entrepreneurship Agency (grants IWT-SB 141198 and IWT/50052), and the University of Antwerp (grant FFB150344).

Foodborne diseases are a growing health problem today and can be caused by eating food contaminated with bacteria. To monitor known foodborne diseases, institutions keep track of bacteria in surveillance projects. Whole genome sequencing is becoming the new standard method for comparing isolates, which generates large amounts of data. Today, the standard analyses are focused on conserved regions in genomes. The dynamics in less conserved regions can be studied by creating pan-genomes. A pan-genome consists of conserved genes, called core genes, and genes of varied conservation grade, called accessory genes. This thesis aimed to analyse pan-genomes of large datasets from six bacterial species coming from surveillance projects: Campylobacter coli, Campylobacter jejuni, Escherichia coli, Listeria monocytogenes, Salmonella enterica, and Streptococcus pneumoniae. The purpose was to investigate the species dynamics in the genomes and to look at properties of the genomes not included in the standard analyses that are used in surveillance projects today. Bacterial Pan Genome Analysis tool was used for the pan-genome analysis of the six species and datasets of 1,000-2,000 genomes per species were analysed. All species were estimated to have open pan-genomes, meaning the pan-genomes are increasing in size as more genomes are added. Escherichia coli and Salmonella enterica had more dynamic and open genomes compared to the other species. They had the highest number of accessory genes relative to their genome sizes and had the largest accessory segments between core genes. The synteny of the core genes showed high conservation for a part of the core genes in all species. Some core genes always sat directly after each other in the analysed genomes, never having accessory genes between them. Other core genes always had accessory genes between them, indicating very open regions in the genomes. The core genes were evenly distributed through the reference genomes with some regions showing increased gene density for all species. Some regions had a higher gene density for core genes often followed by core genes, and others for core genes often followed by accessory genes. However, the placement of genes needs to be investigated further with more reference genomes to be able to draw confident conclusions.

No description available.

En bio-informatique, comprendre comment les molécules d’ADN ont évolué au cours du temps reste un problème ouvert etcomplexe. Des algorithmes ont été proposés pour résoudre ce problème, mais ils se limitent soit à l’évolution d’un caractèredonné (par exemple, un nucléotide précis), ou se focalisent a contrario sur de gros génomes nucléaires (plusieurs milliardsde paires de base), ces derniers ayant connus de multiples événements de recombinaison – le problème étant NP completquand on considère l’ensemble de toutes les opérations possibles sur ces séquences, aucune solution n’existe à l’heureactuelle. Dans cette thèse, nous nous attaquons au problème de reconstruction des séquences ADN ancestrales en nousfocalisant sur des chaînes nucléotidiques de taille intermédiaire, et ayant connu assez peu de recombinaison au coursdu temps : les génomes de chloroplastes. Nous montrons qu’à cette échelle le problème de la reconstruction d’ancêtrespeut être résolu, même quand on considère l’ensemble de tous les génomes chloroplastiques complets actuellementdisponibles. Nous nous concentrons plus précisément sur l’ordre et le contenu ancestral en gènes, ainsi que sur lesproblèmes techniques que cette reconstruction soulève dans le cas des chloroplastes. Nous montrons comment obtenirune prédiction des séquences codantes d’une qualité telle qu’elle permette ladite reconstruction, puis comment obtenir unarbre phylogénétique en accord avec le plus grand nombre possible de gènes, sur lesquels nous pouvons ensuite appuyernotre remontée dans le temps – cette dernière étant en cours de finalisation. Ces méthodes, combinant l’utilisation d’outilsdéjà disponibles (dont la qualité a été évaluée) à du calcul haute performance, de l’intelligence artificielle et de la biostatistique,ont été appliquées à une collection de plus de 450 génomes chloroplastiques. / In Bioinformatics, understanding how DNA molecules have evolved over time remains an open and complex problem.Algorithms have been proposed to solve this problem, but they are limited either to the evolution of a given character (forexample, a specific nucleotide), or conversely focus on large nuclear genomes (several billion base pairs ), the latter havingknown multiple recombination events - the problem is NP complete when you consider the set of all possible operationson these sequences, no solution exists at present. In this thesis, we tackle the problem of reconstruction of ancestral DNAsequences by focusing on the nucleotide chains of intermediate size, and have experienced relatively little recombinationover time: chloroplast genomes. We show that at this level the problem of the reconstruction of ancestors can be resolved,even when you consider the set of all complete chloroplast genomes currently available. We focus specifically on the orderand ancestral gene content, as well as the technical problems this raises reconstruction in the case of chloroplasts. Weshow how to obtain a prediction of the coding sequences of a quality such as to allow said reconstruction and how toobtain a phylogenetic tree in agreement with the largest number of genes, on which we can then support our back in time- the latter being finalized. These methods, combining the use of tools already available (the quality of which has beenassessed) in high performance computing, artificial intelligence and bio-statistics were applied to a collection of more than450 chloroplast genomes.

No description available.