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

Viral Gene Therapy

The development of technologies that allow targeting of specific cells has progressed substantially in recent years for several types of vectors, particularly viral vectors, which have been used in 70% of gene therapy clinical trials. Particular viruses have been selected as gene delivery vehicles because of their capacities to carry foreign genes and their ability to efficiently deliver these genes associated with efficient gene expression. This book is designed to present the most recent advances in viral gene therap

Targeted Gene Delivery Therapies for Cervical Cancer

Despite being largely preventable through early vaccination and screening strategies, cervical cancer is the most common type of gynecological malignancy worldwide and constitutes one of the leading causes of cancer deaths in women. Patients with advanced or recurrent disease have a very poor prognosis; hence, novel therapeutic modalities to improve clinical outcomes in cervical malignancy are needed. In this regard, targeted gene delivery therapy is presented as a promising approach, which leads to the development of multiple strategies focused on different aspects. These range from altered gene restoration, immune system potentiation, and oncolytic virotherapy to the use of nanotechnology and the design of improved and enhanced gene delivery systems, among others. In the present manuscript, we review the current progress made in targeted gene delivery therapy for cervical cancer, the advantages and drawbacks and their clinical application. At present, multiple targeted gene delivery systems have been reported with encouraging preclinical results. However, the translation to humans has not yet shown a significant clinical benefit due principally to the lack of efficient vectors. Real efforts are being made to develop new gene delivery systems, to improve tumor targeting and to minimize toxicity in normal tissues.This research was supported by the Fundación Mutua Madrileña (project FMM-AP16683-2017) and Consejería de Salud Junta de Andalucía (PI-0089-2017)

Phylodynamic Patterns in Pathogen Ecology and Evolution.

The rapid evolution of viral pathogens requires us to consider epidemiological, ecological and evolutionary processes as coupled together and occurring at the same timescale. Rotavirus and influenza account for high levels of morbidity and mortality worldwide and are two important examples of such dynamics. In this work, I investigate the different evolutionary and ecological processes that shape the antigenic structure and phylogenetic characteristics of these two viruses. In the first part of my work, I use a theoretical model of influenza A/H3N2 to identify the relative importance of antigenic novelty, competition between lineages, and changes in the susceptibility of the host population to circulating strains in determining the evolutionary and epidemiological trajectory of the virus. I develop this model further to correspond with patterns of immunity and infection observed in rotavirus, and investigate how reassortment, the swapping of gene segments between viruses, influences the formation and replacement of rotavirus genotypes through immune mediated processes. In the second part of my work, I use a tool (SeasMig), which I developed, to infer alternative stochastically generated migration and mutation events along phylogenetic trees in a Bayesian manner. Using SeasMig, I first show how the seasonality of A/H3N2 influenza incidence corresponds to rates of immigration and emigration of the virus. Subsequently, I tease out the different evolutionary and ecological processes, which drive changes in the US rotavirus population following onset of routine vaccination. My work has implications for identifying likely evolutionary mechanisms, which may lead to reduced vaccine efficacy, and for vaccine strain selection.PhDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113494/1/dzinder_1.pd

A Genomic Portrait of Hepatitis C Virus and MicroRNA-122

Hepatitis C virus (HCV) uniquely requires the liver specific microRNA-122 (miR- 122) for replication, yet global effects on endogenous microRNA (miRNA) targets during infection are unexplored. In this body of work, we employed highthroughput sequencing and crosslinking immunoprecipitation (HITS-CLIP) experiments of human Argonaute (AGO) during HCV infection. We demonstrate robust AGO binding on the 5\u27 untranslated region of HCV RNA at known and predicted miR-122 sites, thereby establishing conclusive biochemical evidence of endogenous miR-122 action on HCV RNA that firmly agrees with previous genetic evidence. We further characterize novel AGO binding on HCV RNA to determine its dependence on miR-122, miRNAs generally, replication competence and time. These results establish an unbiased interaction landscape between HCV RNA and cellular miRNAs, mostly miR-122. On the human transcriptome, we observed reduced AGO binding and functional mRNA de-repression of miR-122 targets during virus infection. This miR-122 sponge effect was relieved and redirected to miR-15 targets by swapping the miRNA tropism of the virus. Single-cell expression data from reporters containing miR-122 sites showed significant de-repression during HCV infection depending on expression level and site number. Based on these results, we describe a quantitative mathematical model of HCV induced miR-122 sequestration and propose that such miR-122 inhibition by HCV RNA may result in global de-repression of host miR-122 targets. This in turn may provide an environment fertile for the long-term oncogenic potential of HCV. This last point presented a fitting entree into miR-122 biology, given its known tumor suppressive activity in the liver. To conclude this work, we performed AGO-CLIP in miR-122 knockout mouse livers as well as in human liver samples, to determine the in vivo targetome for this miRNA across two species. Surprisingly, we discovered widespread and non-canonical miR-122 binding throughout the transcriptome. Furthermore, a substantial fraction of this binding was not conserved between mouse and human transcriptomes, despite the fact that miR-122 is highly conserved. These results, in concert with AGOCLIP in HCV infected cells, point to a model where HCV may have evolved the use of miR-122 for its high abundance and its well buffered capacity to be inhibited with minimal detrimental effects to the host, and perhaps benefits for the virus. In sum, this thesis reveals how miR-122 is redistributed in the cell following HCV infection. As a molecular mechanism, chronic inhibition of miR-122 by HCV RNA is proposed to impact, and may very well help induce, the complex constellation of liver diseases that characterize this infection in humans

Engineering Tools to Probe and Manipulate the Immune System at Single-Cell Resolution

My thesis focuses on developing experimental and computational tools to probe and manipulate cellular transcriptomes in the context of human health and disease. Chapter 1 and 2 focus on published work where we leverage single-cell RNA sequencing (scRNA-seq) to understand human immune variability, characterize cell-type specific biases of multiple viral variants within an animal, and assess temporal immune response in the brain to delivery of genetic cargo via an adeno-associated virus (AAV). Chapter 3 and 4 present progress I have made on tools for exporting RNA extracellularly and engineering of a transcription factor for modulating macrophage state. For probing cellular transcriptome states, we have developed a platform using multiplexed single-cell sequencing and out-of-clinic capillary blood extraction to understand temporal and inter-individual variability of gene expression within immune cell types. Our platform enables simplified, cost-effective profiling of the human immune system across subjects and time at single-cell resolution. To demonstrate the power of our platform, we performed a three day time-of-day study of four healthy individuals, generating gene expression data for 24,087 cells across 22 samples. We detected genes with cell type-specific time-of-day expression and identified robust genes and pathways particular to each individual, all of which could have been missed if analyzed with bulk RNA-sequencing. Also, using scRNA-seq, we have developed a method to screen and characterize cellular tropism of multiple AAV variants. Additionally, I have looked at AAV-mediated transcriptomic changes in animals injected with AAV-PHP.eB three days and twenty-five days post-injection. I have found that there is an upregulation of genes involved in p53 signaling in endothelial cells three days post-injection. In the context of manipulating cellular transcriptomic states, I demonstrate that a fusion between RNA targeting enzyme, dCas13, and capsid-forming neuronal protein, Arc, is able to form a capsid-like structure capable of encapsulating RNA. I also present methods and preliminary data for tuning macrophage states through mutations in transcription factor EB (TFEB) using scRNA-seq as a readout.</p

Mining virus genomes for host predictive signals

The total dependence of a virus on its host for its survival leads to a fundamental entanglement with its host’s cellular machinery. This drives a coevolutionary relationship that leaves an imprint of the host in viral genomes. The aim of this thesis was to develop machine learning approaches to identify and exploit these host predictive signals. We present methods that use these signals both to build classifiers that can assign putative information to virus genomes and to locate the discriminative features on viral proteins thereby identifying regions that are important in the host relationship. The first step aimed to identify discriminative features that capture the different aspects of the virus host relationship. We generated a range of feature sets from alternative representations of the viral genomes that each aimed to exploit the different levels of biological information present. We used a supervised machine learning approach to compare a range of feature sets for their ability to predict host taxonomic information. Next, we opened these “black box” classifiers and to extract the discriminative information learnt by the model to identify regions of a viral protein that are associated with their host relationship. We used the ‘local’ nature of some of the predictive feature sets to transform an amino acid sequence into host signals. Finally, we developed a multi-view generative mixture model, MVC, to tease apart the complex signals that are embedded in viral genomes via different evolutionary processes. This Bayesian approach uses the clustering of the data defined by labels of interest to guide the features associated with those labels into the "relevant view". The MVC model is able to identify features associated with weak effect in the data

SIV infection results in detrimental phenotypic and functional alterations of the naive and memory B cell compartments that are initiated during acute infection

Multiple B cell abnormalities have been described in humans infected with HIV. These abnormalities include hypergammaglobulinaemia, diminished B cell response to mitogenic stimuli, lymphoma and a depletion of the memory B cell population. There is also evidence to suggest that B cells in HIV infected patients are functionally impaired. The initial antibody response to HIV infection is slow to appear and antibody responses to B cell mediated vaccines in HIV infected individuals are less robust and less durable than in uninfected individuals. Although B cell abnormalities have been characterized in humans, efforts to link these abnormalities to a specific defect within the B cell compartment have not been entirely successful. The SIV/macaque model of HIV infection of humans provides a means for addressing questions about the naïve and memory B cell populations, whose activity may be differentially compromised by HIV infection, but lacking is the ability to resolve these functionally relevant B cell populations in the rhesus macaque. In this study, we established CD27 as a definitive memory B cell marker in the rhesus macaque. Further, we demonstrated that the naïve and memory B cell populations are depleted from the periphery within 14 days of SIV infection and that the memory B cell population recovered more quickly. We also showed that chronic SIV infection resulted in a loss of CD40 mediated naïve B cell survival, indicating a potential mechanism through which SIV infection may lead to the production of non-reactive or self reactive antibody producing cells. Together, these findings demonstrated that B cell dysfunctions associated with SIV infection are not limited to the memory B cell population as previously thought, but rather that naïve B cell deficits may be more severe than what has been observed in the memory compartment. Increased focus on abrogating alterations that occur within the naïve compartment have the potential to improve viral control in infected individuals. This study of phenotypic and functional B cell changes over the course of infection will aid in the development of strategies that have the potential to improve prophylactic and therapeutic B cell mediated vaccine efficacy

Bioengineering of Adeno-Associated Virus Serotype 5 for Increased Liver Transduction and Retention of Low Humoral Seroreactivity

Commonly utilized recombinant adeno-associated virus (rAAV) capsids for delivering therapeutic genes to the human liver have significant seroprevalences in the human population, preventing many potential patients from receiving AAV-based gene therapies. As such, AAV serotype 5 (AAV5) has been commonly utilized in liver gene therapy due to its advantageous minimal humoral seroreactivity compared to other serotypes. However, AAV5 can only be used for diseases were only a small fraction of normal protein expression is required due to AAV5’s poor liver infectivity especially when compared with other frequently utilized hepatotropic serotypes. To increase the efficacy of AAV5 based gene therapy for liver diseases, we constructed a random library of AAV5 mutants by error prone PCR and staggered extension protocol(stEP) and screened for variants with increased liver transduction in Huh7 cells. After 7 rounds of selection, two of five selected variants, MV50 and MV53, demonstrated significantly increased transduction efficiency in Huh7 and primary human hepatocytes from donors. Insights into the mechanisms behind the enhancement of infectivity allowed for further rational engineering of these mutants. Swapping the VP1/VP2 common region of AAV8 and AAV9 onto the mutated AAV5 variants further increased their transduction efficiency in primary human hepatocytes. Additionally, results from the VP1/VP2 swapping and the directed evolution yielded insights into a previously uncharacterized domain in the AAV5 capsid that is important for binding and internalization. All variants also had similar seroreactivity towards pooled human IVIG when compared with wild type AAV5 and significantly less seroreactivity compared to wild type AAV9. These evolved AAV5 capsids have the potential to expand the patient population that can receive AAV-based liver gene therapies.Doctor of Philosoph

Engineering Vectors for Non-Invasive Gene Delivery to the Central Nervous System using Multiplexed-CREATE

Viruses are widely modified and used as gene delivery vectors for various applications in science and therapeutics. To this end, my thesis focuses on modifying the recombinant adeno-associated viral (rAAV) vectors that are identified as a safer choice for cargo delivery compared to other known viral vectors. They are widely used in the scientific communities, have seen promising outcomes in gene therapy clinical trials, and as of today have three products approved to use in humans. However, the natural repertoire of rAAVs have broad tropism when delivered systemically, and there is room for further improvement on the efficiency and specificity, especially for gene delivery in the central nervous system (CNS). The prior work done in Dr. Gradinaru lab addresses the issue by using a directed evolution approach called CREATE, Cre recombination-based AAV targeted evolution, to identify AAV-PHP.B and AAV-PHP.eB capsids, which broadly transduce the CNS (Deverman et al, 2016; Chan et al, 2017). CREATE selects for functional lox-flipped viral DNA that crosses the blood-brain barrier (BBB) and successfully transduces a specific nerve cell-type expressing Cre, thereby applying a strong selection pressure. However, the method is limited by its ability to identify a handful of enriched variants, and may also be prone to false positives resulting from experimental biases. The effort to fully understand the selection landscape, and to select for capsids that are not just efficient towards a cell-type but also specific towards it, led to the development of Multiplexed-CREATE (M-CREATE). M-CREATE allows parallel positive selections across different cell-types of interest, enables post-hoc negative selections across off-targets using a next-generation sequencing (NGS) based capsid recovery, and retains the principles of Cre-dependent functional recovery from CREATE. The method has a synthetic library generation approach to minimize biases within selection rounds, a variant replicate feature to identify the signal versus noise within a biological system, and an analysis pipeline to group families of enriched variants based on amino acid motifs, all of which together increases the confidence in the outcome and the throughput from a single experiment. Selections across brain endothelial cells, neurons, and astrocytes yielded several AAV-PHP.B-like variants that broadly transduce the CNS, AAV-PHP.V variants that can efficiently transduce the vascular cells forming the BBB, a AAV-PHP.N variant that transduces neurons with greater specificity, and AAV-PHP.C variants that cross the BBB without murine strain specificity across tested strains. The AAV-PHP.C variants have different amino acid motifs compared to the AAV-PHP.Bs that have been previously shown to have limited CNS transduction across some mouse strains due to its interaction with the strain specific host cell surface receptor, ly6a, a homolog of which is not found in humans. (Hordeaux et al, 2018, Hordeaux et al, 2019; Huang et al, 2019; Batista et al, 2019) Therefore AAV-PHP.Cs offer some hope towards translation across other species. In summary, the M-CREATE methodology turns out to be a high-confidence, robust selection platform to yield several novel viral capsids for use in neuroscience and potential gene therapy related applications.</p