PHYLOGENETIC AND DRUG- AND VACCINE-RESISTANCE PROFILES OF HEPATITIS B VIRUS AMONG CHILDREN WITH HIV CO-INFECTION IN PAKISTAN

Introduction: HIV-1 and hepatitis B virus (HBV) share common routes of transmission and therefore co-infection is common. In 2019, an HIV-1 outbreak that resulted in >1000 children being infected, predominantly through nosocomial transmission, occurred in Sindh, Pakistan. We conducted a phylogenetic and drug resistance analysis of the HBV Reverse Transcriptase (RT) gene in children with HIV-1 and HBV co-infection. Methodology: Blood samples were collected from 321 children with HIV who were recruited as part of a study to investigate the HIV-1 outbreak. All samples were tested for HBV surface antigen (HBsAg) using an ELISA assay, and positive samples were used to amplify and sequence the HBV RT gene. The phylogenetic relationship between sequences was analyzed, and drug- and vaccine- resistance mutations in the RT gene were explored. Results: Of 321 samples, 23% (n = 75) were positive for HBsAg on ELISA. Phylogenetic analysis of the sequences revealed that 63.5% of HBV sequences were sub-genotype D1, while the rest were sub-genotype D2. Cluster analysis revealed grouping of sub-genotype D1 sequences exclusively with Pakistani sequences, while clustering of sub-genotypes D2 predominantly with global sequences. The 236Y mutation associated with resistance to tenofovir was observed in 2.8% of HBV sequences. Additionally, seven vaccine escape mutations were observed, the most common being 128 V. Conclusion: Our study suggests ongoing transmission of HBV D1 and D2 sub-genotypes in the HIV-1 co-infected population, likely nosocomially, given common routes of HVB and HIV-1 transmission. The prevalence of major HBV drug- and vaccine-resistant mutations remains low. Surveillance for further transmissions and the possible emergence of major drug- or vaccine-resistant variants is required

Interpreting viral deep sequencing data with GLUE

Using deep sequencing technologies such as Illumina’s platform, it is possible to obtain reads from the viral RNA population revealing the viral genome diversity within a single host. A range of software tools and pipelines can transform raw deep sequencing reads into Sequence Alignment Mapping (SAM) files. We propose that interpretation tools should process these SAM files, directly translating individual reads to amino acids in order to extract statistics of interest such as the proportion of different amino acid residues at specific sites. This preserves per-read linkage between nucleotide variants at different positions within a codon location. The samReporter is a subsystem of the GLUE software toolkit which follows this direct read translation approach in its processing of SAM files. We test samReporter on a deep sequencing dataset obtained from a cohort of 241 UK HCV patients for whom prior treatment with direct-acting antivirals has failed; deep sequencing and resistance testing have been suggested to be of clinical use in this context. We compared the polymorphism interpretation results of the samReporter against an approach that does not preserve per-read linkage. We found that the samReporter was able to properly interpret the sequence data at resistance-associated locations in nine patients where the alternative approach was equivocal. In three cases, the samReporter confirmed that resistance or an atypical substitution was present at NS5A position 30. In three further cases, it confirmed that the sofosbuvir-resistant NS5B substitution S282T was absent. This suggests the direct read translation approach implemented is of value for interpreting viral deep sequencing data

Simultaneous determination of HCV genotype and NS5B resistance associated substitutions using dried serum spots from São Paulo state, Brazil

Hepatitis C virus (HCV) is responsible for more than 180 million infections worldwide, and about 80 % of infections are reported in Low and Middle-income countries (LMICs). Therapy is based on the administration of interferon (INF), ribavirin (RBV) or more recently Direct-Acting Antivirals (DAAs). However, amino acid substitutions associated with resistance (RAS) have been extensively described and can contribute to treatment failure, and diagnosis of RAS requires considerable infrastructure, not always locally available. Dried serum spots (DSS) sampling is an alternative specimen collection method, which embeds drops of serum onto filter paper to be transported by posting to a centralized laboratory. Here, we assessed feasibility of genotypic analysis of HCV from DSS in a cohort of 80 patients from São Paulo state Brazil. HCV RNA was detected on DSS specimens in 83 % of samples of HCV infected patients. HCV genotypes 1a, 1b, 2a, 2c and 3a were determined using the sequence of the palm domain of NS5B region, and RAS C316N/Y, Q309R and V321I were identified in HCV 1b samples. Concerning therapy outcome, 75 % of the patients who used INF +RBV as a previous protocol of treatment did not respond to DAAs, and 25 % were end-of-treatment responders. It suggests that therapy with INF plus RBV may contribute for non-response to a second therapeutic protocol with DAAs. One patient that presented RAS (V321I) was classified as non-responder, and combination of RAS C316N and Q309R does not necessarily imply in resistance to treatment in this cohort of patients. Data presented herein highlights the relevance of studying circulating variants for a better understanding of HCV variability and resistance to the therapy. Furthermore, the feasibility of carrying out genotyping and RAS phenotyping analysis by using DSS card for the potential of informing future treatment interventions could be relevant to overcome the limitations of processing samples in several location worldwide, especially in LMICs

geno2pheno[ngs-freq]: a genotypic interpretation system for identifying viral drug resistance using next-generation sequencing data

Identifying resistance to antiretroviral drugs is crucial for ensuring the successful treatment of patients infected with viruses such as human immunodeficiency virus (HIV) or hepatitis C virus (HCV). In contrast to Sanger sequencing, next-generation sequencing (NGS) can detect resistance mutations in minority populations. Thus, genotypic resistance testing based on NGS data can offer novel, treatment-relevant insights. Since existing web services for analyzing resistance in NGS samples are subject to long processing times and follow strictly rulesbased approaches, we developed geno2pheno[ngs-freq], a web service for rapidly identifying drug resistance in HIV-1 and HCV samples. By relying on frequency files that provide the read counts of nucleotides or codons along a viral genome, the time-intensive step of processing raw NGS data is eliminated. Once a frequency file has been uploaded, consensus sequences are generated for a set of user-defined prevalence cutoffs, such that the constructed sequences contain only those nucleotides whose codon prevalence exceeds a given cutoff. After locally aligning the sequences to a set of references, resistance is predicted using the well-established approaches of geno2pheno[resistance] and geno2pheno[hcv]. geno2pheno[ngs-freq] can assist clinical decision making by enabling users to explore resistance in viral populations with different abundances and is freely available at http: //ngs.geno2pheno.org

Algorithms for Analysis of Heterogeneous Cancer and Viral Populations Using High-Throughput Sequencing Data

Next-generation sequencing (NGS) technologies experienced giant leaps in recent years. Short read samples reach millions of reads, and the number of samples has been growing enormously in the wake of the COVID-19 pandemic. This data can expose essential aspects of disease transmission and development and reveal the key to its treatment. At the same time, single-cell sequencing saw the progress of getting from dozens to tens of thousands of cells per sample. These technological advances bring new challenges for computational biology and require the development of scalable, robust methods to deal with a wide range of problems varying from epidemiology to cancer studies. The first part of this work is focused on processing virus NGS data. It proposes algorithms that can facilitate the initial data analysis steps by filtering genetically related sequencing and the tool investigating intra-host virus diversity vital for biomedical research and epidemiology. The second part addresses single-cell data in cancer studies. It develops evolutionary cancer models involving new quantitative parameters of cancer subclones to understand the underlying processes of cancer development better

The differential influence of HIV-1 subtype C,nucleoside analog resistance mutations: K65R, A62V, S68N and Y115F susceptibility to tenofovir.

Masters Degree. University of KwaZulu-Natal, Durban.The use of Tenofovir Disoproxil Fumerate (TDF) for the treatment of HIV-1 infection has been recommended for the first-line as well as a second-line antiretroviral regimen in South Africa, due to its high antiretroviral activity and low toxicity level. However, the efficacy of the drug could be threatened by the emergence of drug resistance mutations. The development of TDF resistance poses a public health threat. TDF resistance can be acquired through a selection of the K65R mutation or the K70E mutation (though less frequently) under TDF selection pressure. Besides, K65R and K70E mutations, recent studies have identified other mutations associated with TDF resistance such as A62V, K65N, S68G/N/D, K70E/Q/T, L74I, V75L, and Y115F. These mutations were particularly observed to be in association with the K65R mutation and were reported to be more common in HIV-1 subtype C viruses. Also, these mutations could cause high-level resistance to TDF, especially when in combination with K65R. However, in-vitro studies are required to demonstrate their influence on viral fitness and TDF susceptibility. In this study, we investigated the impact of K65R, A62V, S68D, Y115F, and K65R+S68N on replication capacity and TDF susceptibility. The reverse transcriptase (RT) region was amplified from a drug-naive HIV-1 subtype C isolate obtained from a patient enrolled in the Tropism study (BREC: BF088/07) and cloned into a TOPO vector using a TOPO TA cloning kit. The HIV-1 RT mutations (K65R, A62V, S68D, Y115F, K65R+A62V, K65R+S68D, K65R+S68G, K65R+S68N, and K65R+Y115F) were introduced into the TOPO+RTsubC recombinant using the Quikchange lightning Multi site-directed mutagenesis kit. Next, recombinant viruses were created by co-transfection of the mutant RT amplicons and a pNL4-3-deleted-reverse transcriptase (RT) (pNL43ΔRT) backbone into GXR cells by electroporation. The replication capacity of the mutant viruses was assessed using a replication method that utilized a green fluorescent protein (GFP) reporter cell line and flow cytometry. We evaluated the replication capacity using the exponential growth curve function in Excel to determine the percentage GFP-expressing cells between days 2 and 6. The impact of the mutant viruses on susceptibility to TDF was performed in a luciferase-based assay. The 50% inhibitory concentration (IC50) was calculated using Graph Pad Prism. Drug susceptibility was expressed as the fold change in IC50 of mutant virus compared with the wild type virus. Of the 5 TDF- selected mutants analysed: A62V, K65R, and Y115F mutants display a reduction in replicative fitness whereas, S68D and K65R+S68N showed high viral fitness. Interestingly, the TDF- selected resistance mutations we analysed, showed high susceptibility (A62V, S68D, and Y115F) and reduced susceptibility (K65R and K65R+S68N) to TDF. Our findings support the hypothesis that TDF- selected mutations only confer reduced susceptibility to TDF. Hence, further study is needed on various combinations of TDF-selected resistance mutations to further solidify this claim.Ethical Approval for thesis is on page iv

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