Characterization of mutations in the receptor binding site of influenza A viruses determining virus host, tissue, and cell tropisms using systems biology approaches

Influenza A viruses (IAVs) cause occasional pandemics and seasonal epidemics, thus presenting continuous challenges to public health. Vaccination is the primary strategy for the prevention and control of influenza outbreaks. The antigenicity matched high-yield seed strain is critical for the success of influenza vaccine. Currently, there are several limitations for the influenza vaccine manufacture: 1) the conventional methods for generating such strains are time consuming; 2) egg-based vaccines, the predominant production platform, have several disadvantages including the emergence of viral antigenic variants that can be induced during egg passage; 3) vaccine seed viruses often do not grow efficiently in mammalian cell lines. Previous studies suggested that mutations in the receptor binding site (RBS) that locates at the globular head of the HA1 can change IAVs’ binding specificity, antigenicity, and yield and thus RBS would be an potential target for engineering vaccine seed strain. However, systematic analysis of the mutations on RBS affecting those viral phenotypes is lacking. Specifically, this dissertation has following aims: Firstly, we developed a novel method to rapidly generate high-yield candidate vaccine strains by integrating error-prone PCR, site-directed mutagenesis strategies, and reverse genetics. The error-prone PCR- based reverse genetic system could also be applied to gain-ofunction studies for influenza virus and other pathogens; Secondly, in this dissertation, we identified an Y161F mutation in the hemagglutinin (HA) that enhanced the infectivity and thermostability of virus without changing its original antigenic properties which would prompted the development of cell-based vaccines; Thirdly, the molecular mechanisms underlying host adaption of equine-origin influenza A(H3N8) virus from horses to dogs are unknown. This dissertation identified that a substitution of W222L in the HA of the equine-origin A(H3N8) virus facilitated its host adaption to dogs. This mutation increased binding avidity of the virus specifically to sialyl Lewis X motifs, which were found abundantly in the submucosal glands of dog trachea but not in equine trachea. To summary, this dissertation investigated the role of RBS in IAVs biology and expanded the current knowledge toward IAV vaccine strain engineering, IAV host adaption and evolution

Developing bioinformatics approaches for the analysis of influenza virus whole genome sequence data

Influenza viruses represent a major public health burden worldwide, resulting in an estimated 500,000 deaths per year, with potential for devastating pandemics. Considerable effort is expended in the surveillance of influenza, including major World Health Organization (WHO) initiatives such as the Global Influenza Surveillance and Response System (GISRS). To this end, whole-genome sequencning (WGS), and corresponding bioinformatics pipelines, have emerged as powerful tools. However, due to the inherent diversity of influenza genomes, circulation in several different host species, and noise in short-read data, several pitfalls can appear during bioinformatics processing and analysis. 2.1.2 Results Conventional mapping approaches can be insufficient when a sub-optimal reference strain is chosen. For short-read datasets simulated from human-origin influenza H1N1 HA sequences, read recovery after single-reference mapping was routinely as low as 90% for human-origin influenza sequences, and often lower than 10% for those from avian hosts. To this end, I developed software using de Bruijn 47Graphs (DBGs) for classification of influenza WGS datasets: VAPOR. In real data benchmarking using 257 WGS read sets with corresponding de novo assemblies, VAPOR provided classifications for all samples with a mean of >99.8% identity to assembled contigs. This resulted in an increase of the number of mapped reads by 6.8% on average, up to a maximum of 13.3%. Additionally, using simulations, I demonstrate that classification from reads may be applied to detection of reassorted strains. 2.1.3 Conclusions The approach used in this study has the potential to simplify bioinformatics pipelines for surveillance, providing a novel method for detection of influenza strains of human and non-human origin directly from reads, minimization of potential data loss and bias associated with conventional mapping, and facilitating alignments that would otherwise require slow de novo assembly. Whilst with expertise and time these pitfalls can largely be avoided, with pre-classification they are remedied in a single step. Furthermore, this algorithm could be adapted in future to surveillance of other RNA viruses. VAPOR is available at https://github.com/connor-lab/vapor. Lastly, VAPOR could be improved by future implementation in C++, and should employ more efficient methods for DBG representation

International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance: Building the Future of Public Health Surveillance

Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-04204pubpub1117

High-throughput methods for characterizing the immune repertoire

Thesis (Ph. D. in Biomedical Engineering and Computational Biology)--Harvard-MIT Program in Health Sciences and Technology, February 2013."September 2012." Cataloged from PDF version of thesis.Includes bibliographical references (p. 147-160).The adaptive immune system is one of the primary mediators in almost every major human disease, including infections, cancer, autoimmunity, and inflammation-based disorders. It fundamentally functions as a molecular classifier, and stores a memory of its previous exposures. However, until recently, methods to unlock this information or to exploit its power in the form of new therapeutic antibodies or affinity reagents have been limited by the use of traditional, low-throughput technologies. In this thesis, we leverage recent advances in high-throughput DNA sequencing technology to develop new methods to characterize and probe the immune repertoire in unprecedented detail. We use this technology to 1) characterize the rapid dynamics of the immune repertoire in response to influenza vaccination, 2) characterize elite neutralizing antibodies to HIV, to better understand the constraints for designing an HIV vaccine, and 3) develop new methodologies for discovering auto-antigens, and assaying large libraries of protein antigens in general. We hope that these projects will serve as stepping-stones towards filling the gap left by low-throughput methods in the development of antibody technologies.by Uri Laserson.Ph.D.in Biomedical Engineering and Computational Biolog

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