Functional and evolutionary genomics of antibiotic resistance in tuberculosis: from biology to global DR-TB control
- Autores: Miguel Ángel Moreno Molina
- Directores de la Tesis: Iñaki Comas Espadas (dir. tes.), Mª Antonia Ferrús Pérez (tut. tes.)
- Lectura: En la Universitat Politècnica de València ( España ) en 2023
- Idioma: inglés
- Tribunal Calificador de la Tesis: Álvaro San Millán Cruz (presid.), Leonor Sánchez Busó (secret.), Francesc Coll Cerezo (voc.)
- Programa de doctorado: Programa de Doctorado en Biotecnología por la Universitat Politècnica de València
- Materias:
- Enlaces
- Tesis en acceso abierto en: RiuNet
- Resumen
Antibiotic resistance in tuberculosis is a serious global health problem and a growing obstacle to the control of the disease. In this thesis we use genomics as a tool to study different aspects of the biology of the bacterium in relation to the development of antibiotic resistance and provide new knowledge to meet the challenge of its eradication.
First, we characterize new genomic determinants of resistance to isoniazid by using an approach based on functional genomics and phylogenetic association. The method consists of transposon sequencing of bacterial populations exposed to the antibiotic to determine the genes involved in both sensitivity and resistance, and their filtering with genomic data from a global collection of clinical strains. We have verified the importance of the metabolic pathways of bacterial wall synthesis in the mechanism of antibiotic action, and also discovered new genes involved in cellular redox balance that confer low-level resistance to the bacteria. These results can be used to develop new diagnostic techniques or therapeutic targets, and the method is applicable to new antibiotics to predict future resistance determinants.
Second, we explored the bacterial diversity of tuberculosis at its natural site of infection and the population dynamics of antibiotic resistance. We have analyzed samples from different parts of the lung lesion from patients in Georgia, a country with a high incidence of resistant tuberculosis, and detected a significant number of polyclonal infections (caused by two or more different strains). These different strains can in turn be resistant to different antibiotics, which makes it essential to detect them in time to offer the patient the most appropriate treatment possible. The surgical specimens gave us a more complete picture of bacterial diversity than sputum, the routine clinical specimen, and allowed us to detect polyclonal infections more accurately. The data show that we are underestimating these types of infections in high TB burden countries and they may adversely affect treatment outcome, so in these settings a second sampling during the course of the antibiotic regimen would be advisable.
Third, we evaluated the role of one of the most important comorbidities of tuberculosis, HIV, in the development of resistance during the first weeks of treatment. To this end, we have sampled patients from Mozambique with and without HIV on a serial basis during the first month to analyze the impact of co-infection on both immune and antibiotic selective pressures. We have detected a higher total diversity in seronegative patients and furthermore, in comparison, HIV+ patients present difficulties in eliminating this diversity during the early stages of treatment that could affect their success. Thanks to deep sequencing, we have also been able to observe an accumulation of variants in resistance-related genes, and we have associated some of them with changes in the MICs (minimum inhibitory concentrations) of the samples. These small changes during the first month may serve as predictors of a reduced ability to eliminate bacterial diversity, and could indicate future treatment failure.
In summary, in this thesis we have focused on better understanding the bacterial and host factors that have an impact on the development of antibiotic resistant tuberculosis and as a result will allow the development of new diagnostics and epidemiological models to control it. Genomic sequencing is a great tool to study this and other pathogens in real time, and offers the possibility of detecting resistance quickly and with high certainty in the clinical setting. A correct diagnosis ensures adequate, shorter and more successful treatment, and also prevents transmission to new hosts. The techniques and results presented here contribute to achieve these objectives and improve the global control of the resistant tuberculosis epidemic.
