Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Q fever is a zoonosis caused by the Gram-negative bacterium Coxiella burnetii. Currently, there is only one licensed human vaccine for Q fever, but its high level of reactogenicity necessitates the urgent need for developing a safer and efficacious alternative. Prior research has highlighted the utility of anti-C. burnetii phase I (smooth form) lipopolysaccharide (LPS) IgG antibodies in conferring protection against Q fever. Drawing on this foundation, this thesis describes the generation and evaluation of novel LPS-based glycoconjugate vaccine candidates aimed at combating Q fever. The initial phase of the work involved synthesising the vaccine candidates using LPS extracted from inactivated C. burnetii. Purified LPS was conjugated with carrier proteins including tetanus toxoid heavy chain (TThc) and CRM197, using two different chemistries. The selection of carrier proteins and conjugation chemistries was informed by their scalability and potential for clinical development. As a result, this work led to the development of two LPS-based glycoconjugate vaccine candidates, QCON-CT and QCON-ET. The capacity of these vaccine candidates to induce a functional immune response was subsequently evaluated using a mouse model. Both vaccine candidates were capable of eliciting a serum anti-C. burnetii phase I LPS IgG response. In particular, QCON-CT, when formulated with Alum adjuvant, induced significantly higher anti-LPS IgG titres compared with an existing licensed inactivated veterinary vaccine. In addition, a comprehensive in silico pipeline was developed using a dataset generated from a randomised, phase 2b, typhoid fever controlled human infection model (CHIM) study to evaluate molecular signatures post-vaccination. In this study, a plain polysaccharide-based vaccine was compared with a glycoconjugate vaccine containing the same polysaccharide antigen. This in turn provides a large dataset for transcriptomic analysis development. Methods were developed to contrast immunological profiles of the two vaccine types, quantifying various metrics including differential gene expression, T cell-dependent functions induced by the glycoconjugate vaccine, and likely antigen-specific antibody clonotype abundances. Establishing this pipeline not only aided the understanding of typhoid fever by identifying the very first molecular markers associated with vaccine-induced protection, but also enabled RNA-Seq data generated from the Q fever mouse study to be leveraged by transcriptomic analyses. Using this in silico pipeline, it was determined that both glycoconjugate vaccine candidates against Q fever induced a convergent humoral response, characterised by the upregulation of several likely LPS-specific B cell receptor (BCR) clonotypes. These findings, in alignment with the in vitro readouts, indicate the promising effectiveness that can be achieved by the LPS-based glycoconjugate vaccine approach. Overall, a path towards further clinical development of the Q fever glycoconjugate vaccine candidates is delineated by the results generated in this thesis, highlighting their potential in addressing global public health needs by facilitating the control and prevention of Q fever outbreaks worldwide. The mechanistic insights and methodologies developed herein not only provide a framework for future vaccine research, but also hold promise for application in combating many other infectious diseases.

Type

Thesis / Dissertation

Publication Date

02/05/2024

Keywords

bioinformatics, molecular markers, vaccine response, Coxiella burnetii, glycoconjugate, vaccine, vaccine synthesis, transcriptomics