Les tapis microbiens sont des communautés benthiques, calcifiées (i.e. microbialites) ou non, diverses à la fois phylogénétiquement et métaboliquement. Les tapis microbiens fossiles constituent les plus anciennes traces de vie sur Terre et leurs représentants modernes peuvent donc être utilisés pour comprendre le fonctionnement de ces écosystèmes anciens. J'ai étudié les communautés microbiennes (archées, bactéries et eucaryotes) de plusieurs microbialites (lac Alchichica, Mexique) et tapis microbiens (dans une mare du salar de Llamara, Chili) afin de caractériser finement leur structure phylogénétique et d'améliorer notre compréhension de leur fonctionnement. J'ai pour cela utilisé une approche combinant des outils moléculaires (métabarcoding, métagénomique) à des données environnementales (paramètres physico-chimiques de la colonne d'eau ou composition minérale des microbialites). Mon travail de thèse a permis d'affiner le modèle de formation des microbialites d'Alchichica, en montrant notamment que, en plus de la photosynthèse oxygénique cyanobactérienne, le potentiel à précipiter des carbonates de la photosynthèse eucaryote et, surtout, de la photosynthèse anoxygénique est important. Les communautés des tapis de Llamara étaient quant à elles caractérisées par la présence de nombreuses lignées d'archées et de bactéries très divergentes, dont certaines ont été identifiées pour la première fois dans ce travail. Nos analyses ont aussi souligné la diversité des organismes impliqués dans les cycles du soufre et de l'azote au sein de ces systèmes et permis d'identifier de potentielles interactions biotiques entre des lignées procaryotes dont l'écologie est peu connue. Enfin, nous avons mis en évidence que les paramètres environnementaux influencent fortement la composition des communautés associées à ces microbialites et à ces tapis microbiens. L'ensemble de ces résultats permet de mieux comprendre le fonctionnement de ces systèmes ainsi que les facteurs qui influencent leur structure phylogénétique et fonctionnelle. / Microbial mats are phylogenetically and functionally diverse benthic microbial communities, which can be sometimes calcified (i.e. microbialites). Fossil microbial mats constitute the oldest traces of life on Earth and their modern representatives are thus used as analogues of those primordial ecosystems to gain insights into their functioning. I have studied the microbial communities (archaea, bacteria and eukaryotes) of several microbialites (lake Alchichica, Mexico) and microbial mats (in a small pond in the salar de Llamara, Chile). The main objectives of my PhD were to finely characterize their phylogenetic structure and to improve our understanding of the functioning of these complex ecosystems. To do so, I have applied a multi-disciplinary approach combining molecular approaches (metabarcoding, metagenomics) to environmental data (physico-chemical parameters of the water column or mineral composition of the microbialites).The results presented in this thesis allowed refining our model of microbialite formation in Lake Alchichica. We showed that, in addition to cyanobacterial photosynthesis, both eukaryotic and, particularly, anoxygenic photosyntheses were potentially important to promote carbonate precipitation. Llamara mat communities were characterised by the presence of numerous novel archaeal and bacterial lineages, some of which were identified for the first time in this work. Our analyses have also highlighted the diversity of organisms involved in both sulphur and nitrogen cycles in these mats and identified potential biotic interactions between poorly known prokaryotic lineages. Finally, we showed that the composition of the microbial communities associated to these microbialites and microbial mats was strongly influenced by environmental parameters. Overall, these results represent a substantial contribution to our understanding of the ecology of these systems as well as of the factors that influence their phylogenetic and functional structures.

Les picocyanobactéries marines Prochlorococcus et Synechococcus sont les organismes photosynthétiques les plus abondants sur la planète et sont présentes dans presque tous les océans. Au cours de cette thèse, j'ai cherché à mieux comprendre les liens entre diversité génétique et adaptation à la niche écologique chez ces deux genres. Tout d'abord, l'étude de la répartition des populations de picocyanobactéries à l'échelle mondiale à l'aide d'un marqueur taxonomique très résolutif m'a permis de définir des unités taxonomiques écologiquement significatives, et d'identifier les principaux facteurs abiotiques influençant leur répartition. La deuxième partie de ce travail a visé à identifier les bases génétiques de l'adaptation des picocyanobactéries marines à des niches écologiques distinctes. L'étude comparative de 81 génomes non-redondants de ces organismes a révélé le rôle combiné des gains et pertes de gènes et des substitutions d'acides aminés dans la diversification des deux genres, et l'analyse de la répartition des gènes de picocyanobactéries marines dans l'océan mondial m'a permis de montrer que chaque communauté, adaptée à un environnement donné, possède un répertoire de gènes distinct. Enfin, le dernier volet de cette thèse a consisté en la caractérisation physiologique et transcriptomique de cinq souches de Synechococcus soumises à des stress lumineux et thermique afin d'analyser la variabilité écotypique de la réponse au stress. Les résultats obtenus au cours de cette thèse ont donc permis d'améliorer notre connaissance des niches écologiques occupées par les picocyanobactéries marines, et de mieux comprendre les mécanismes leur ayant permis de s'y adapter. / The marine picocyanobacteria Synechococcus and Prochlorococcus are the two most abundant photosynthetic organisms on earth and are present in almost all oceans. During this PhD thesis, I explored the links between genetic diversity and niche adaptation in these two genera. First, the analysis of the distribution of picocyanobacterial populations at the global scale using a high-resolution taxonomic marker allowed me to define ecologically significant taxonomic units, to improve the delineation of their ecological niches and to identify the main abiotic factors influencing their in situ distribution. The second part of this work aimed at identifying the genetic bases of adaptation of marine picocyanobacteria to distinct niches. The comparative analysis of 81 non-redundant genomes of these organisms revealed the combined role of gene gains and losses and of substitutions in protein sequences in the diversification of both genera, and the analysis of the distribution of all known picocyanobacterial genes in the global ocean allowed me to show that each community, adapted to specific environmental conditions, possesses a distinct gene repertoire. Finally, the last part of this work has consisted in the physiological and transcriptomic characterization of five Synechococcus strains, which were submitted to light and thermal stresses in order to better understand the ecotypic variability of the stress response in this genus. Altogether, results obtained during this PhD provided many new insights into the ecological niches occupied by marine picocyanobacteria and the mechanisms allowing them to adapt to these various niches.

Grâce aux avancées de la technologie et nouvelles stratégies OMICS, de nombreuses études se sont intéressées au microbiote vaginal ces dernières années. Elles ont révélé l'impact de ce dernier sur la santé de la femme. En effet, un déséquilibre de la flore vaginale la rend vulnérable, la prédisposant à la vaginose bactérienne ainsi qu’à des complications gynéco-obstétricales sévères. La pathogénèse de la vaginose reste encore méconnue et le traitement classique par antibiothérapie échoue dans plus de 50% des cas. En analysant 50 prélèvements vaginaux provenant de patientes atteintes de vaginose et de femmes saines vivant en France et au Sénégal, nous avons constaté une plus grande diversité bactérienne chez les patientes par rapport aux témoins avec l'augmentation d'espèces telles que Gardnerella vaginalis, Atopobium vaginae ainsi que les procaryotes sensibles à l'oxygène, y compris les Cocci anaérobies à Gram-positif et les Prevotella. Les femmes saines renfermaient plus d’espèces de Lactobacillaceae et de Proteobacteria dans leurs flores. La combinaison de la métagénomique et la culturomique a permis d’identifier un complexe de 11 espèces/genres bactériens associés à la vaginose. L’utilisation de la culturomique a permis d’accroître le répertoire des bactéries humaines avec l’isolement de 27 nouvelles espèces. Le faible taux de recouvrement entre les données de métagénomique et celles de culturomique montre la nécessité de persévérer dans l’isolement des bactéries par culturomique. L’obtention d'isolats permettra d'explorer in vitro les compétitions entre les bactéries et pourrait servir également de matière première pour développer un traitement par bactériothérapie / Over the last decades, thanks to the technologic progresses including advanced molecular techniques and new OMICS strategies, many studies have focused on the vaginal microbiota. Thus, revealing the impact of the vaginal flora on women health. Indeed, the disruption of the vaginal bacterial community makes it prone to bacterial vaginosis and severe obstetrical and gynecological disorders. The pathogenesis of bacterial vaginosis is still unknown, and relapses are very frequent. Conventional treatment with antibiotic therapy fails in more than 50% of cases. The analysis of 50 vaginal samples from bacterial vaginosis patients and healthy women living in France and Senegal, showed a higher bacterial diversity in patients compared to controls with the increase of species such as Gardnerella vaginalis, Atopobium vaginae as well as oxygen-sensitive prokaryotes including Gram-positive anaerobic cocci, and Prevotella spp. Healthy women harbored more Lactobacillaceae species and Proteobacteria in their microbiota. The combination of metagenomics and culturomics has allowed the identification of a complex of 11 bacterial species/genera associated with bacterial vaginosis. The use of the culturomics approach has extended the repertoire of human-associated bacteria, with the isolation of 27 new bacterial species. The low range overlap between metagenomic and culturomics data indicates the need to continue the isolation of bacteria by culturomics. Obtaining isolates will make it possible to explore in vitro the competitions between the bacteria but can also be used as primary material for the development new treatments by bacteriotherapy

This chapter focuses on the role of antioxidant vitamins in protecting the gastrointestinal (GI) tract from oxidative stress. A systems medicine approach is used since it alone is sufficiently comprehensive to capture the broad range of relevant complexities and interrelationships relevant to GI protection. Systems medicine utilizes and integrates the vast amount of information gained from genomics and metagenomics, as well as environmental factors, and applies this information to better patient care. A major goal of system medicine is to develop paradigms to treat or slow the progression of chronic diseases, that is, disease prevention. GI disorders are quintessential examples of chronic inflammation with its attendant oxidative stress. Genomics and metagenomics have provided great insight into the underlying molecular mechanisms for GI disorders and will eventually help define individualized diets to minimize chronic inflammation. While the role of antioxidant nutrients and micronutrients is promising, there is a need for large-scale well-designed clinical trials supported by studies using animal models.

La métagénomique sert à étudier les communautés microbiennes en analysant de l’ADN extrait directement d’échantillons pris dans la nature, elle permet également d’établir un catalogue très étendu des gènes présents dans les communautés microbiennes. Ce catalogue doit être comparé contre les gènes déjà référencés dans les bases des données afin de retrouver des séquences similaires et ainsi déterminer la fonction des séquences qui le composent. Au cours de cette thèse, nous avons développé MetaCLADE, une nouvelle méthodologie qui améliore la détection des domaines protéiques déjà référencés pour des séquences issues des données métagénomiques et métatranscriptomiques. Pour le développement de MetaCLADE, nous avons modifié un système d’annotations de domaines protéiques qui a été développé au sein du Laboratoire de Biologie Computationnelle et Quantitative appelé CLADE (CLoser sequences for Annotations Directed by Evolution) [17]. En général les méthodes pour l’annotation de domaines protéiques caractérisent les domaines connus avec des modèles probabilistes. Ces modèles probabilistes, appelés Sequence Consensus Models (SCMs) sont construits à partir d’un alignement des séquences homologues appartenant à différents clades phylogénétiques et ils représentent le consensus à chaque position de l’alignement. Cependant, quand les séquences qui forment l’ensemble des homologues sont très divergentes, les signaux des SCMs deviennent trop faibles pour être identifiés et donc l’annotation échoue. Afin de résoudre ce problème d’annotation de domaines très divergents, nous avons utilisé une approche fondée sur l’observation que beaucoup de contraintes fonctionnelles et structurelles d’une protéine ne sont pas globalement conservées parmi toutes les espèces, mais elles peuvent être conservées localement dans des clades. L’approche consiste donc à élargir le catalogue de modèles probabilistes en créant de nouveaux modèles qui mettent l’accent sur les caractéristiques propres à chaque clade. MetaCLADE, un outil conçu dans l’objectif d’annoter avec précision des séquences issues des expériences métagénomiques et métatranscriptomiques utilise cette libraire afin de trouver des correspondances entre les modèles et une base de données de séquences métagénomiques ou métatranscriptomiques. En suite, il se sert d’une étape pré-calculée pour le filtrage des séquences qui permet de déterminer la probabilité qu’une prédiction soit considérée vraie. Cette étape pré-calculée est un processus d’apprentissage qui prend en compte la fragmentation de séquences métagénomiques pour les classer.Nous avons montré que l’approche multi source en combinaison avec une stratégie de méta apprentissage prenant en compte la fragmentation atteint une très haute performance. / Metagenomics is used to study microbial communities by the analyze of DNA extracted directly from environmental samples. It allows to establish a catalog very extended of genes present in the microbial communities. This catalog must be compared against the genes already referenced in the databases in order to find similar sequences and thus determine their function. In the course of this thesis, we have developed MetaCLADE, a new methodology that improves the detection of protein domains already referenced for metagenomic and metatranscriptomic sequences. For the development of MetaCLADE, we modified an annotation system of protein domains that has been developed within the Laboratory of Computational and Quantitative Biology clade called (closer sequences for Annotations Directed by Evolution) [17]. In general, the methods for the annotation of protein domains characterize protein domains with probabilistic models. These probabilistic models, called sequence consensus models (SCMs) are built from the alignment of homolog sequences belonging to different phylogenetic clades and they represent the consensus at each position of the alignment. However, when the sequences that form the homolog set are very divergent, the signals of the SCMs become too weak to be identified and therefore the annotation fails. In order to solve this problem of annotation of very divergent domains, we used an approach based on the observation that many of the functional and structural constraints in a protein are not broadly conserved among all species, but they can be found locally in the clades. The approach is therefore to expand the catalog of probabilistic models by creating new models that focus on the specific characteristics of each clade. MetaCLADE, a tool designed with the objective of annotate with precision sequences coming from metagenomics and metatranscriptomics studies uses this library in order to find matches between the models and a database of metagenomic or metatranscriptomic sequences. Then, it uses a pre-computed step for the filtering of the sequences which determine the probability that a prediction is a true hit. This pre-calculated step is a learning process that takes into account the fragmentation of metagenomic sequences to classify them. We have shown that the approach multi source in combination with a strategy of meta-learning taking into account the fragmentation outperforms current methods.

Microbes are ubiquitous in virtually all habitats on Earth and affect human life in multiple ways, from the health-balancing role of the human microbiome, to the involvement of microbial communities in the global nitrogen and carbon cycles. The capacity of microbes to survive and grow in diverse environments relates directly to their ability to utilize available resources, be they from other microbes or from the environment itself. Hence, understanding how the environment shapes the metabolic functionality of individual microbes and complex communities constitutes an important area of research. In the first part of my thesis work, I explored how environmental nutrient composition and intracellular transcriptional regulation data can be integrated to provide insight into the temporal metabolic behavior of a bacterium through the use of genome-scale stoichiometric modeling approaches (Flux Balance Analysis). Thus I developed the method of Temporal Expression-based Analysis of Metabolism (TEAM), and applied it to Shewanella oneidensis, a bacterium studied for its important bioenergy and bioremediation applications. I found that TEAM improves on previous models' predictions of S. oneidensis metabolic fluxes, and recovers the overflow metabolism that has been seen experimentally. This study demonstrated the value of incorporating environmental context and transcriptional data for the prediction of time-dependent metabolic behavior. In the second part of my work, I extended the exploration of microbial metabolism from single species to complex communities in order to understand the robustness of metabolic functions. Specifically, I implemented novel mathematical analyses of metagenomic sequencing data to ask how functional stability of microbial communities could ensue despite large taxonomic variability. Upon representing in matrix form the metabolic capabilities of all genera found in 202 available metabolic ecosystem datasets, I compared the different communities with each other and with various randomized analogues. My results reveal new connections between the abundance of an organism in the community and the functions that it encodes. Furthermore, I found that genus abundances govern the metabolic robustness of a community more than the distribution of genetically encoded functions among the community members, suggesting that communities rely largely on ecological interactions to regulate their overall functionality.

Tesis por compendio / [EN] Legionella pneumophila is a strictly environmental and opportunistic pathogen that can cause severe pneumonia after inhalation of aerosols with enough bacterial load. Outbreaks and sporadic cases are usually localized in temperate environments, and the reservoirs are often water-related sources where biofilms are created. The existence of non-cultivable forms of the bacteria increases the risk for public health, as culture-based methods may miss them, thus complicating the environmental investigations of the sources. Genetic classification through the Sequence-Based Typing (SBT) technique allowed an increased discrimination among L. pneumophila strains compared to previous methods. SBT data can also be used for genetic variability and population structure studies, but a more exhaustive analysis can be performed using high-throughput genome sequencing strategies. This thesis describes the use of both SBT and genomic sequencing to evaluate and provide solutions to different public health needs in L. pneumophila epidemiology. We have focused in the Comunidad Valenciana (CV), the second region in Spain with the highest incidence of Legionellosis, with special interest in the city of Alcoy, where recurrent outbreaks have occurred since 1998. Firstly, SBT data were used to gain a deeper insight into the genetic variability and distribution of the most abundant Sequence Types (ST) in the CV area. We have shown that the level of variability in this region is comparable to that from other countries, revealing the existence of both locally and broadly extended profiles. Approximately half of the observed genetic diversity was found to result from geographical and temporal structure. Secondly, L. pneumophila detection from environmental sources remains a challenge for public health. A comparison between water and biofilm samples using a sensitive touchdown PCR (TD-PCR) strategy revealed that the use of biofilms increased by ten-fold the detection rate. This method allowed evaluating the hidden uncultivable L. pneumophila diversity in the locality of Alcoy and the real-time investigation of a Legionellosis outbreak affecting a hotel in Calpe (Southeast of Spain) in 2012. Thirdly, genomic sequencing was applied to a set of 69 strains isolated during 13 outbreaks occurred in Alcoy in the period 1999-2010, mainly the recurrent ST578. Higher intra-outbreak variability than expected was observed, pointing to the potential existence of multiple sources in this endemic area or high environmental diversity. Interestingly, above 98% of the genomic variability in this ST was found as being incorporated through recombination processes rather than through point mutations. Finally, a metagenomic analysis of environmental biofilms from Alcoy revealed a microbial community dominated by Proteobacteria, Cyanobacteria, Actinobacteria and Bacteroidetes. Despite the known endemism of Legionella in this area, the genus was only found in a relative abundance ranging 0.01-0.07%, which explains the low recovery from environmental sources. In summary, the results from this thesis can benefit public health efforts to control this pathogen in the environment, as we provide new insight into its molecular epidemiology, with immediate applications to surveillance and outbreak investigations. / [ES] Legionella pneumophila es un patógeno oportunista estrictamente ambiental capaz de causar neumonía debido a la inhalación de aerosoles con suficiente carga bacteriana. Los brotes y casos esporádicos suelen producirse en ambientes templados y los reservorios encontrarse en zonas con agua donde pueden crearse biopelículas microbianas. La existencia de formas no cultivables de la bacteria aumenta el riesgo para la salud pública, ya que los métodos estándar basados en cultivo microbiológico no pueden detectarlas, complicando las investigaciones ambientales. La clasificación genética basada en el método Sequence-Based Typing (SBT) permite un mayor poder de discriminación entre cepas de L. pneumophila en comparación con métodos previos. Los datos derivados del SBT pueden utilizarse para estudios de variabilidad genética y estructura poblacional. Sin embargo, puede llevarse a cabo un análisis más exhaustivo mediante técnicas de secuenciación genómica de alto rendimiento. Esta tesis describe la utilización tanto de SBT como de secuenciación genómica para evaluar e incluso proponer soluciones a diferentes necesidades en salud pública relacionadas con la epidemiología de L. pneumophila. Nos centramos en la Comunidad Valenciana (CV), la segunda región en España con mayor incidencia de Legionelosis, con especial interés en la localidad de Alcoy, donde ocurren brotes de forma recurrente. En primer lugar, utilizamos datos derivados de SBT para conocer mejor la variabilidad y la distribución de los perfiles genéticos (Sequence Types, ST) en el área de la CV. Mostramos que el nivel de variabilidad en sólo esta región es comparable a la de otros países, con perfiles extendidos local y globalmente. Aproximadamente la mitad de la diversidad genética observada se estima que procede de estructuración geográfica y temporal. En segundo lugar, la detección de L. pneumophila a partir de fuentes ambientales sigue suponiendo un reto para la salud pública. En esta tesis realizamos una comparación entre la detección mediante touchdown PCR (TD-PCR) a partir de muestras de agua y biopelículas microbianas y mostramos que estas últimas proporcionan un aumento de 10 veces en la tasa de detección de la bacteria. Este método permitió evaluar la diversidad no cultivable de L. pneumophila en la localidad de Alcoy y la investigación a tiempo real de un brote en un hotel en Calpe (Sudeste de España) en 2012. A continuación, aplicamos la secuenciación genómica a 69 cepas aisladas durante 13 brotes ocurridos en Alcoy en el período 1999-2010, principalmente el recurrente ST578. Se observó mayor variabilidad entre cepas de un mismo brote que la esperada, lo cual apunta a la existencia potencial de múltiples fuentes en este área, o alta diversidad ambiental. Además, se observó que más del 98% de la variabilidad genómica fue introducida por procesos de recombinación y no de mutación puntual. Finalmente, se realizó un análisis metagenómico de biopelículas ambientales recogidas en Alcoy. Se encontró que la comunidad está dominada por Proteobacteria, Cyanobacteria, Actinobacteria y Bacteroidetes. A pesar del conocido endemismo de Legionella en el área, este género sólo se encontró en una abundancia relativa entre 0.01-0.07%, lo cual explica su baja tasa de recuperación a partir de muestras ambientales. En resumen, los resultados de esta tesis pueden ser de utilidad para los programas de control de este patógeno llevados a cabo por las autoridades de salud pública, ya que proporcionan una nueva percepción de su epidemiología molecular, con aplicación inmediata a la vigilancia e investigación de brotes. / [CA] Legionella pneumophila és un patogen oportunista estrictament ambiental capaç d'ocasionar pneumònia degut a la inhalació d'aerosols amb la suficient carga bacteriana. Els brots i casos esporàdics solen ocórrer en ambients temperats, i els reservoris solen trobar-se en zones amb aigua on poden crear-se biopel·lícules microbianes. La existència de formes no cultivables del bacteri augmenten el risc per a la salut pública, ja que els mètodes estàndard basats en el cultiu microbiològic no poden detectar-les, complicant les investigacions ambientals. La classificació genètica basada en el mètode Sequence-Based Typing (SBT) permet un major poder de discriminació entre soques de L. pneumophila en comparació amb previs mètodes. Les dades derivades del SBT poden utilitzar-se per a estudis de variabilitat genètica i estructura poblacional, però un anàlisis més exhaustiu pot dur-se a terme a través de tècniques de seqüenciació genòmica d'alt rendiment. Esta tesis descriu la utilització tant del SBT com de la seqüenciació genòmica per a avaluar i proposar solucions a diferents necessitats en salut pública relacionades amb l'epidemiologia de L. pneumophila. Ens centrem en la Comunitat Valenciana (CV), la segona regió d'Espanya amb la major incidència de Legionel·losi, amb especial interès en la localitat d'Alcoi, on els brots ocorren de forma recurrent des de 1998. Primer, hem utilitzat dades derivades del SBT per a conèixer millor la variabilitat i la distribució dels perfils genètics (Sequence Types, ST) en l'àrea de la CV. Mostrem que el nivell de variabilitat en només aquesta regió és comparable a la d'altres països, amb perfils estesos tant de forma local com més amplia. Aproximadament la meitat de la diversitat genètica observada s'estima que procedeix d'estructuració geogràfica i temporal. Segon, la detecció de L. pneumophila a partir de fonts ambientals continua suposant un repte per a la salut pública. En aquesta tesis realitzem una comparació entre la detecció mitjançant touchdown PCR (TD-PCR) a partir de mostres d'aigua i biopel·lícules microbianes i mostrem que aquestes últimes proporcionen un augment de deu vegades en la tassa de detecció. A més, aquest mètode ens va permetre avaluar la diversitat no cultivable de L. pneumophila a la localitat d'Alcoi i la investigació a temps real d'un brot de Legionelosis que va afectar a un hotel en Calp (Sud-est d'Espanya) a l'any 2012. Tercer, vam aplicar la seqüenciació genòmica a 69 soques aïllades durant 13 brots ocorreguts a Alcoi en el període 1999-2010, principalment el recurrent ST578. Es va observar una major variabilitat entre soques d'un mateix brot de l'esperada, apuntant a l'existència potencial de múltiples fonts en aquesta àrea, considerada endèmica, o alta diversitat ambiental. A més, es va observar que més del 98% de la variabilitat genòmica havia sigut introduïda a partir de processos de recombinació i no de mutació puntual. Finalment, es va realitzar una anàlisi metagenòmica de biopel·lícules ambientals recollides a Alcoi. Varem trobar que la comunitat està dominada per Proteobacteria, Cyanobacteria, Actinobacteria i Bacteroidetes. A pesar del conegut endemisme de Legionella en l'àrea, aquest gènere només es va trobar en una abundància relativa entre 0.01-0.07%, el qual explica la seua baixa tassa de recuperació a partir de mostres ambientals. En resum, els resultats d'aquesta tesi poden ser d'utilitat per als programes de control d'aquest patogen duts a terme per les autoritats de salut pública, ja que proporcionen una nova percepció de la seua epidemiologia molecular, amb aplicació immediata a la vigilància i la investigació de brots. / Sánchez Busó, L. (2015). Genetic and genomic variability of Legionella pneumophila: applications to molecular epidemiology and public health [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/52854 / TESIS / Premios Extraordinarios de tesis doctorales / Compendio

No description available.

Antimicrobial resistance (AMR) is rapidly becoming a public health issue, as more and more infectious bacteria become resistant to our known antibiotics. Suggested reasons for the proliferation of these strains are misuse and overuse of antimicrobials, especially on an industrial level, in agriculture, livestock and aquaculture. These resistances are not unique for pathogenic bacteria but originates in nature where complicated systems of microbes interact with each other. Freshwater environments hold special interest as they provide drinking water, have unique biodiversity, and provide other ecosystem services. Soil environments have the most diverse microbial communities and are often the source of new discoveries in microbial functions and AMR interactions. Since the vast majority of microbes can’t be maintained in pure culture or replicated in the laboratory setting, metagenomic methods have proven to be vital for understanding the diversity and occurrence of AMR in the environment that would otherwise have remained unexplored and unaccounted for. By producing metagenomic pipelines that utilize parallel computing to handle vast amounts of data, a catalogue of AMR in 390 samples mainly from Scandinavia was created from two datasets. One of the datasets had been previously processed and published, while the other was managed from raw reads to metagenomic assembled bins. This revealed a difference in the distribution of resistance mechanisms that microbes utilize to achieve AMR based on lifestyle and that AMR can be found in most taxa as well as in any freshwater and soil environments.

To address the shortcomings in existing Markov model implementations in handling large amount of metagenomic data with comparable or better accuracy in classification, we developed a new algorithm based on pseudo-count supplemented standard Markov model (SMM), which leverages the power of higher order models to more robustly classify reads at different taxonomic levels. Assessment on simulated metagenomic datasets demonstrated that overall SMM was more accurate in classifying reads to their respective taxa at all ranks compared to the interpolated methods. Higher order SMMs (9th order or greater) also outperformed BLAST alignments in assigning taxonomic labels to metagenomic reads at different taxonomic ranks (genus and higher) on tests that masked the read originating species (genome models) in the database. Similar results were obtained by masking at other taxonomic ranks in order to simulate the plausible scenarios of non-representation of the source of a read at different taxonomic levels in the genome database. The performance gap became more pronounced with higher taxonomic levels. To eliminate contaminations in datasets and to further improve our alignment-free approach, we developed a new framework based on a genome segmentation and clustering algorithm. This framework allowed removal of adapter sequences and contaminant DNA, as well as generation of clusters of similar segments, which were then used to sample representative read fragments to constitute training datasets. The parameters of a logistic regression model were learnt from these training datasets using a Bayesian optimization procedure. This allowed us to establish thresholds for classifying metagenomic reads by SMM. This led to the development of a Python-based frontend that combines our SMM algorithm with the logistic regression optimization, named POSMM (Python Optimized Standard Markov Model). POSMM provides a much-needed alternative to metagenome profiling programs. Our algorithm that builds the genome models on the fly, and thus obviates the need to build a database, complements alignment-based classification and can thus be used in concert with alignment-based classifiers to raise the bar in metagenome profiling.