Dynamics, evolutionary and epidemiological patterns of RNA viruses

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Viral infections, specifically those caused by RNA viruses such as Human Immunodeficiency virus (HIV), Hepatitis C virus (HCV) or Influenza, are among the most important public health concerns to humans due to their high prevalence and associated mortality. Prevention and treatment campaigns against these viruses usually had limited efficacy, partly because their biological features allow them to reach very high levels of diversity, both at the within- and between-host levels. Research focused on understanding the processes and mechanisms involved in the evolution of RNA viruses, and on the clinical and/or epidemiological consequences of their diversification, is important for improving the management of their epidemics. The aim of this PhD thesis is to study different aspects of the mid- and long-term evolution of RNA viruses, with special interest in molecular epidemiology. For this, different datasets (viral alignments, obtained either from public databases or by sequencing patient’s derived samples from the studied populations) were obtained and analyzed by means of evolutionary and statistical approaches. Firstly, phylogenetic, coalescent and statistical analyses were performed to depict the HIV epidemic in two different Spanish regions: Euskadi (Basque Country) and Comunitat Valenciana (Valencian Community). A significant number of patients from both regions, especially those from the Comunitat Valenciana, were included in local transmission clusters. Men who have unprotected sex with men (MSM) were significantly more prone to form transmission clusters than other risk groups. The high vulnerability of MSM to HIV infection was also evidenced by the detection of an extraordinarily large transmission cluster, affecting more than 100 patients solely in the city of Valencia. Interestingly, the recent expansion of the highly pathogenic HIV CRF19_cpx among local Valencian MSM was also reported, for the first time outside Cuba. Secondly, by means of Bayesian coalescent analyses, the genomic evolutionary rates of different HIV-1 subtypes (A1, B, C, D, G) and CRFs (CRF01_AE, CRF02_AG) were estimated and compared. The results obtained revealed that HIV-1 A1, C and CRF01_AE evolve significantly faster than subtypes B, D, G and CRF02_AG. Thirdly, datasets containing sequences from the 6 major genotypes causing the HCV pandemic were analyzed, inferring the prevalence, evolutionary history and genetic barrier of naturally-occurring resistance mutations (RAVs) to direct acting antivirals (DAAs) in these genotypes. The obtained results demonstrate that RAVs are common in all HCV genotypes, and that there is an overall low genetic barrier for the selection of RAVs. Interestingly, some of these resistance mutations present a high potential to be transmitted between patients at risk. In the fourth place, the distribution of positively selected sites along the genomes of HCV subtypes 1a and 1b was analyzed. The results show that positive selection is acting in all HCV genes, and that positively selected sites are associated with the presence of CD8 epitopes, while conserved sites are associated with RNA secondary structure and CD4 epitopes. Finally, the effect of using RNA substitution models on the phylogenetic inference of viroids and RNA viruses was assessed. Such models were found to fit best for all the species analyzed. Compared to viral phylogenies inferred only from DNA models, using RNA models usually leads to significantly longer tree length estimates, while has no significant effect on tree topology inference. The results obtained from this work will not only have direct applications to HIV control campaigns in Spain and HCV treatment refinement, but also provide new insights into different aspects of the evolution of RNA viruses.
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