Methods for Viral Intra-Host and Inter-Host Data Analysis for Next-Generation Sequencing Technologies

The deep coverage offered by next-generation sequencing (NGS) technology has facilitated the reconstruction of intra-host RNA viral populations at an unprecedented level of detail. However, NGS data requires sophisticated analysis dealing with millions of error-prone short reads. This dissertation will first review the challenges and methods for viral NGS genomic data analysis in the NGS era. Second, it presents a software tool CliqueSNV for inferring viral quasispecies based on extracting pairs of statistically linked mutations from noisy reads, which effectively reduces sequencing noise and enables identifying minority haplotypes with a frequency below the sequencing error rate. Finally, the dissertation describes algorithms VOICE and MinDistB for inference of relatedness between viral samples, identification of transmission clusters, and sources of infection

A Novel Methodology for Isolating Broadly Neutralizing HIV-1 Human Monoclonal Antibodies

Abstract also published in AIDS Research and Human Retroviruses. November 2013, 29(11): A-53. doi:10.1089/aid.2013.1500Poster presentationpublished_or_final_versio

Elicitation of broadly neutralizing HIV-1 antibodies by guiding the immune responses using primary and secondary immunogens

Abstract also published in AIDS Research and Human Retroviruses. November 2013, 29(11): A-44. doi:10.1089/aid.2013.1500Poster presentationpublished_or_final_versio

Dynamics, evolutionary and epidemiological patterns of RNA viruses

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.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

Computational approaches for improving treatment and prevention of viral infections

The treatment of infections with HIV or HCV is challenging. Thus, novel drugs and new computational approaches that support the selection of therapies are required. This work presents methods that support therapy selection as well as methods that advance novel antiviral treatments. geno2pheno[ngs-freq] identifies drug resistance from HIV-1 or HCV samples that were subjected to next-generation sequencing by interpreting their sequences either via support vector machines or a rules-based approach. geno2pheno[coreceptor-hiv2] determines the coreceptor that is used for viral cell entry by analyzing a segment of the HIV-2 surface protein with a support vector machine. openPrimeR is capable of finding optimal combinations of primers for multiplex polymerase chain reaction by solving a set cover problem and accessing a new logistic regression model for determining amplification events arising from polymerase chain reaction. geno2pheno[ngs-freq] and geno2pheno[coreceptor-hiv2] enable the personalization of antiviral treatments and support clinical decision making. The application of openPrimeR on human immunoglobulin sequences has resulted in novel primer sets that improve the isolation of broadly neutralizing antibodies against HIV-1. The methods that were developed in this work thus constitute important contributions towards improving the prevention and treatment of viral infectious diseases.Die Behandlung von HIV- oder HCV-Infektionen ist herausfordernd. Daher werden neue Wirkstoffe, sowie neue computerbasierte Verfahren benötigt, welche die Therapie verbessern. In dieser Arbeit wurden Methoden zur Unterstützung der Therapieauswahl entwickelt, aber auch solche, welche neuartige Therapien vorantreiben. geno2pheno[ngs-freq] bestimmt, ob Resistenzen gegen Medikamente vorliegen, indem es Hochdurchsatzsequenzierungsdaten von HIV-1 oder HCV Proben mittels Support Vector Machines oder einem regelbasierten Ansatz interpretiert. geno2pheno[coreceptor-hiv2] bestimmt den HIV-2 Korezeptorgebrauch dadurch, dass es einen Abschnitt des viralen Oberflächenproteins mit einer Support Vector Machine analysiert. openPrimeR kann optimale Kombinationen von Primern für die Multiplex-Polymerasekettenreaktion finden, indem es ein Mengenüberdeckungsproblem löst und auf ein neues logistisches Regressionsmodell für die Vorhersage von Amplifizierungsereignissen zurückgreift. geno2pheno[ngs-freq] und geno2pheno[coreceptor-hiv2] ermöglichen die Personalisierung antiviraler Therapien und unterstützen die klinische Entscheidungsfindung. Durch den Einsatz von openPrimeR auf humanen Immunoglobulinsequenzen konnten Primersätze generiert werden, welche die Isolierung von breit neutralisierenden Antikörpern gegen HIV-1 verbessern. Die in dieser Arbeit entwickelten Methoden leisten somit einen wichtigen Beitrag zur Verbesserung der Prävention und Therapie viraler Infektionskrankheiten

Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here

Saving Bones: a direct comparison of FTIR-ATR, whole bone percent nitrogen, and NIR

89th Annual Meeting of the American-Association-of-Physical-Anthropologists (AAPA), Los Angeles, CA, APR 15-18, 202