Cholera is an acute diarrhoeal disease that remains a global threat to public health in countries where access to safe water and adequate sanitation cannot be guaranteed. Vibrio cholerae, the bacterial pathogen responsible for this disease, can cause a range of symptoms in infected individuals, from intense diarrhea leading to severe dehydration, to asymptomatic carriage of the bacteria. Although our understanding of cholera on a macro-epidemiological scale has been considerably improved by the development of high-throughput sequencing techniques and by advances in bacterial genomics, no studies have yet been conducted to characterize its evolution at the scale of infected individuals. Furthermore, the role of asymptomatic carriers in an epidemic and the reason behind the absence of symptoms in these infected individuals remains unknown. The main objective of this thesis is therefore to characterize the genomic diversity of V. cholerae at the level of individuals and households, but also to evaluate the potential role of the gut microbiome in the susceptibility to contract this acute enteric disease and to present severe symptoms. First, we characterize the genomic diversity of colonies isolated from symptomatic patients. The whole genome sequencing of strains from patients in Bangladesh and Haiti reveals that this diversity is detectable in the form of point mutations within hosts, but remains limited. Much of the variation detected within patients appears to be due to the gain and loss of phages and plasmids within the V. cholerae population, with occasional exchanges between the pathogen and other commensal members of the gut microbiota. These results challenge the commonly accepted assumption that V. cholerae infections are predominantly clonal, and confirm that horizontal gene transfer is an important factor in the evolution of V. cholerae. In addition, our results show that some of these variants may also have a phenotypic effect, for example by impacting biofilm formation, and can be selected within infected individuals. Next, we apply a combination of whole genome sequencing and metagenomic approaches to improve the detection of intra-host variants, both in symptomatic patients and in asymptomatic carriers. Our study shows that the metagenomic approach offers a better resolution in the detection of the diversity in the microbial population, but remains difficult to apply in asymptomatic patients, due to the low number of V. cholerae cells in these individuals. Overall, we find that the level of diversity within the intra-host bacterial population is similar between symptomatic and asymptomatic patients. We also detect the presence of hypermutator strains in some patients. In addition, while mutations in patients with hypermutator phenotypes did not appear to be driven by selection, signs of parallel evolution are detected in patients with fewer mutations, suggesting adaptive mechanisms within the host. Our results underline the power of metagenomics combined with whole genome sequencing to characterize intra-host diversity in acute cholera infection, but also in asymptomatic carriers, while identifying for the first time an hypermutator phenotype in infected patients. Finally, we are interested in factors related to susceptibility to the disease and related to the severity of symptoms. Based on a recent study using 16S rRNA amplicon sequencing to show the potential link between the intestinal microbiome and susceptibility to V. cholerae infection, our study uses metagenomic sequencing methods on the same samples from this previous study to characterize the taxonomic and functional profiles of the gut microbiome of household contacts exposed to V. cholerae. Samples are collected prior to infection of these household contacts, and used to identify predictors of symptomatic disease. Using a machine learning algorithm, we can identify species, gene families and metabolic pathways in the microbiome at the time of exposure to V. cholerae to detect potential biomarkers correlated with risk of infection and symptom severity. Our results show that the use of metagenomic sequencing improves the precision and accuracy of predictions compared to 16S rRNA amplicon sequencing. Our analyses also predict disease severity, although with greater uncertainty than the prediction of infection. Bacterial taxa from the genera Prevotella and Bifidobacterium have been identified as potential markers of protection against infection, as well as genes involved in iron metabolism. Our results highlight the power of metagenomics to predict disease progression and identify specific species and genes that could be involved in experimental tests to study the mechanisms related to the microbiome explaining potential protection against cholera.