This thesis focuses on the evolutionary history of the papillomaviruses (PVs) using phylogenetic approaches. Two aspects have been examined: the first is the level of phylogenetic compatibility among PV genes and the second is determining the ancestral diversification mechanisms of the PVs in order to explain the origin of the observed associations with host species. Bayesian phylogenetic analysis has been used to make evolutionary inferences. The existence of phylogenetic compatibility among genes was examined by estimating constrained and unconstrained phylogenies for pairs of PV genes. The Bayes' factor statistic derived from comparison of the constrained and unconstrained models indicated significant evidence against identical phylogenies between any of the 6 PV genes investigated and may indicate the existence of ancestral recombination events. The formation of new host-virus associations can occur via a process of 'codivergence', where, following host speciation, the ancestral virus association is effectively inherited by the descendant host species; 'prior divergence' of the virus, which results in multiple virus associations with the host; and 'host transfer', in which the virus lineage is transferred between contemporaneous host species. To distinguish between these mechanisms of virus diversification, an approach based on temporal comparisons of host and virus divergence times was devised. Difficulties associated with the direct estimation of PV divergence times led to the incorporation of a biased sampling approach into Bayesian phylogenetic estimation. This allowed for viral divergence events to be biased in favour of codivergence but allowed sampling of times that violate this assumption and therefore indicate either prior divergence or host transfer. Statistical evaluation of the proportion of violations at each viral divergence identified significant evidence of prior divergence events behind many of the observed PV-host associations and one ancestral host transfer event.

Neither the archaeological nor the historical data have yet allowed a full understanding of the nature of the Germanic settlement in England. Analysis of the genetic structure of past history has mostly been carried out by inference from extant populations. However, genetic flow through migration over time is likely to have altered the genetic composition of modem samples. Analysis of the genetic composition of ancient populations (provided the authenticity of their DNA is obtained) gives a direct sight into the past. Thus, mitochondrial DNA from pre-Saxon (4th century), early Saxon (5th -7th century) and late Saxon (9th – 11th century) settlements has been analysed to obtain a better understanding of the population history of Britain. A methodology has been optimised, by which, ancient DNA from 1,000-1,800 year old archaeological material was extracted and ~200-bp fragments of the HVS-1, amplified and sequenced. Rigorous controls for work in human ancient DNA were undertaken to prevent and recognise contamination. Established authenticity criteria were followed, including expected ancient DNA behaviour, internal replication of sequences and confirmation by independent labs. The sample size obtained has enabled a population-level study of communities of ancient Britain. In addition, an extensive database of >6500 mitochondrial DNA sequences was compiled for comparisons. Several estimates of haplotype and nucleotide genetic diversity were computed for modem and ancient populations. Counter-intuitively, the modem population of England, encompassing all successive waves of migration to the island, has a lower diversity than the ancient population, suggesting that diversity has been lost over the last millennium. In addition, mtDNA genetic continuity between ancient and modem England seems to have been intermpted. Founder analyses of early (5th -7th century) and late (9th -11th century) periods indicate that, whereas the late period seems to have had Viking genetic influences, the early period has no close relationship with Germanic populations. Instead, the females of the early Anglo-Saxon period seem to represent the native British population. The female contribution of the Anglo-Saxon invasion would have therefore been minor, at least at that time and at these sites. The close genetic affinity between the ancient British population and the northern most populations of Europe suggests they might have shared a common past during pre-history. It is proposed that, after post-glacial times, inhabitants of areas now submerged expanded to northern territories. The early settlements analysed reflect that very early expansion. Some time since then, reduction in diversity seem to have occurred (possibly due to variation in family size after repeated epidemics) leading to the present day mtDNA composition of England.

The production of chemicals using microbes is an area of significant interest for academia and industry. Significant resources are often devoted to strain development not only for the increase of productivity and yield but also for the improvement of robustness and tolerance to industrial production conditions. The genetic regulatory network of microbial organisms has evolved to maximize growth and survival in a variety of dynamic environmental conditions found in nature. Many of these responses can be suboptimal for the purpose of industrial manufacture of valuable bioproducts. A small number of methods have been developed to explore the effect of perturbing these networks with the objective of obtaining improved strains. This thesis explores the use of transcriptional regulatory network rewiring as a general strategy for improvement of strains used in the production of chemical compounds. Libraries generated using a regulatory network rewiring strategy - addition of nodes to wildtype background - were screened for enhanced production of a target compound or other phenotypes of interest. Combinatorial libraries of promoters and coding regions of transcriptional regulators were used to test the strategy towards the improvement of phenotypical limitations of M. smegmatis (growth rate) and for the isolation of strains with improved production of lycopene in P. pastoris. The method was shown to allow for the identification of potential fast growing strains in M. smegmatis and for the isolation of strains with improved production of lycopene in P. pastoris. In the lycopene project, a strain was isolated that was shown to produce significantly higher levels of lycopene in suboptimal aeration conditions as well as modest improvements in non-limited cultures, providing a hint that the strategy could be applied for the development of strains with large phenotypical diversity, and towards the understanding of complex factors limiting production of compounds of interest.

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Majoritairement monoparamétriques les biocapteurs actuels sont limités en termes de sensibilité et de spécificité. Pour une analyse complète de la toxicité, ils doivent être associés afin d’en recouper les résultats. Dans ce contexte, la spectroscopie Raman offre de nouvelles perspectives. Véritables empreintes moléculaires, les spectres Raman offrent une vision multiparamétrique globale de la physiologie des échantillons biologiques observés. Basée sur l’hypothèse selon laquelle les variations moléculaires engendrées par une substance sur un microorganisme en impactent l’empreinte spectrale, cette thèse explore le potentiel de la spectroscopie Raman pour la mise en évidence de signatures spectrales d’effets toxiques donnés. Devant la richesse du signal, les étapes d’analyses sont des enjeux majeurs. Dans une première partie une méthode statistique permettant une meilleure mise en évidence des différences spectrales a été élaborée. Ces travaux ont conduit à une 1ère preuve de concept à partir de l’observation des effets de l’arsenic sur la bactérie E. coli. Pour confirmer l’aspect spécifique des signatures spectrales engendrées, l’étude est ensuite élargie à l’observation de quatre microorganismes exposés à différents types de substances (herbicide, métal…). En effet, l’analyse des spectres conduit à l’identification des macromolécules impactées par la toxicité permettant une vue d’ensemble de ses effets. Enfin, des eaux environnementales fournies par l’entreprise Tronico Vigicell (partenaire CIFRE de la thèse) sont analysées. Ces travaux s’inscrivent ainsi dans la recherche de solutions pour l’amélioration des techniques de surveillance de pollutions environnementales. / In the field of toxicological bioassays, the current biosensors are mostly monoparametric and limited in terms of sensitivity and specificity. A more complete toxicity analysis thus calls for combinations to cross-check the results. In this context, the latest progress in Raman spectroscopy opens new research perspectives on a fast method of observing metabolic responses against toxic agents. Indeed, Raman spectra constitute molecular fingerprints of the observed biological samples, offering a global multiparametric view of their physiology. Based on the premise that the molecular variations triggered by a substance on a microorganism affect its spectral fingerprint, this thesis explores the Raman spectroscopy potential of identifying spectral signatures of targeted toxic effects. That said, proper physiological spectral fingerprints analysis requires complex chemometric methods. In the first part of this work, a particular attention has been given to the elaboration of a statistical strategy to highlight the effects of arsenic on the E. coli bacteria. To confirm the specific aspects of the generated spectral signatures, the study has then been extended to the observation of four microorganisms exposed to different kinds of toxic substances (antibiotic, metal, pesticides, phenol compounds). Spectral analyses lead to the identification of the most impacted macromolecules, allowing evidencing of specific toxic effects. Finally, in partnership with the company Tronico Vigicell (CIFRE partner of the thesis) this approach has also been tested on environmental water samples, making this work an integral part of the search for better environmental pollution monitoring solutions.

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