Newton001 Systems Biology of Typhoid Fever

Enteric fever caused by Salmonella Typhi and Paratyphi A is wide spread throughout the world. particularly burdensome in South-East Asia, with approximately >22 million new infections resulting in a 1% fatality rate annually. Control of the disease is hindered due to insufficient understanding of disease pathogenesis and immune responses to the infection, inaccurate diagnostic tests and limited efficacy of licensed vaccines. Thus understanding human host-responses to enteric infections is pivotal in developing improved diagnostic tests and vaccines.
The Oxford Vaccine Group (OVG) has recently developed a human challenge model for S. Typhi and Paratyphi A. Briefly, human adult volunteers were orally infected with a pathogenic dose of S. Typhi and Paratyphi A and closely monitored the following days until treatment with antibiotics. This model was subsequently used to test vaccine efficacy by vaccinating participants prior to ingestion of the bacteria. The various samples collected provide a rich dataset consisting of clinical and immunological measurements invaluable to understand disease pathogenesis and human molecular responses to infection. Associated with such large datasets and different levels of data (molecular, serological and clinical) is the challenge of analysis and data integration, which we address through using systems biology approaches.
Systems biology/vaccinology is an interdisciplinary field that combines systems-wide measurements, networks, and predictive modelling in the context of biology, vaccines and infectious disease. Computational modelling and integration of multiple levels of data (clinical, immunological, and molecular) develops a multi-facetted understanding of disease pathogenesis and biological mechanisms underlying host-responses to infections/vaccination. Particularly important in this context are regulatory mechanisms, which consist of complex networks involving multiple transcriptional and genetic components. Recently, it has become clear that long non-coding RNAs (lncRNAs) play a pivotal role in the regulation of biological processes by a diverse range of mechanisms. Integrative analysis of transcriptional signatures related to expression of lncRNAs allows us to identify molecular events associated with clinical and immunological outcomes.
We are aiming to thoroughly integrate these different datasets to fully investigate the intricacy of human host-responses to infections. We believe that this approach is necessary in order to further shed light on the undisputed complexity of the immune system. As these samples are derived from the human host and a uniquely controlled experimental design, the results will likely elucidate important clues as to how the host reacts to enteric infections and how S. Typhi/Paratyphi A potentially modulate the host-response. By partnering with the Computational Systems Biology Lab at the University of Sao Paulo we are combining one of the largest clinical trials groups in Europe with an excellence in vaccine trials with a team of computational biologists leading in the field of systems vaccinology.

In recent years, the field of systems biology has experienced a profound gain of momentum with the integration of computational biology applied to human samples collected during clinical trials. At the Oxford Vaccine Group we are leading on clinical trials in vaccinology and immunology using a human challenge model for typhoid fever. Due to its highly controlled experimental design, this is model provides a unique opportunity to understand host-responses to enteric infection and vaccination as well as providing proof-of-principle for novel, integrative analysis algorithms. We specifically set out to tackle three important questions:
1) Transcriptional signatures predictive of vaccine responses.
2) Identifying diagnostic signatures.
3) Assessing the role of long non-coding RNAs to typhoid fever.

In order to interrogate the data and establish gene expression profiles to vaccination against typhoid as well as enteric infection, we have partnered with Dr. Helder Nakaya at the University of São Paulo, who pioneered the field of systems vaccinology in recent years. We aim to characterize the molecular disease profile of typhoid fever by integrating a multiplicity of data to develop novel hypothesis regarding disease pathogenesis in humans. Besides investigating gene expression profiles, we will also use these data to interrogate expression of long non-coding RNAs (lncRNAs). These regulatory molecules are likely to have a significant impact on the regulation of host responses to infection. Applying computational methods to integrate regulatory molecules with gene expression and clinical phenotypes is likely to produce novel insights into host-responses to typhoid fever and live oral vaccines.
By forming a strong partnership between the Oxford Vaccine Group and the Computational Systems Biology Laboratory at the University of Sao Paulo, we not only aim to gain novel insights into infections but also build significant computational capacity in the UK.

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