Proteomic profiling of bacterial host adaptation: Racing the Red Queen

Research output: ThesisDoctoral Thesis (compilation)

Standard

Proteomic profiling of bacterial host adaptation : Racing the Red Queen. / Kilsgård, Ola.

Lund : Department of Immunotechnology, Lund University, 2016.

Research output: ThesisDoctoral Thesis (compilation)

Harvard

Kilsgård, O 2016, 'Proteomic profiling of bacterial host adaptation: Racing the Red Queen', Doctor, Department of Immunotechnology, Lund.

APA

Kilsgård, O. (2016). Proteomic profiling of bacterial host adaptation: Racing the Red Queen. Department of Immunotechnology, Lund University.

CBE

Kilsgård O. 2016. Proteomic profiling of bacterial host adaptation: Racing the Red Queen. Lund: Department of Immunotechnology, Lund University.

MLA

Kilsgård, Ola Proteomic profiling of bacterial host adaptation: Racing the Red Queen Lund: Department of Immunotechnology, Lund University. 2016.

Vancouver

Kilsgård O. Proteomic profiling of bacterial host adaptation: Racing the Red Queen. Lund: Department of Immunotechnology, Lund University, 2016.

Author

Kilsgård, Ola. / Proteomic profiling of bacterial host adaptation : Racing the Red Queen. Lund : Department of Immunotechnology, Lund University, 2016.

RIS

TY - THES

T1 - Proteomic profiling of bacterial host adaptation

T2 - Racing the Red Queen

AU - Kilsgård, Ola

N1 - Defence details Date: 2016-12-02 Time: 09:15 Place: Belfrage lecture hall, Klinikgatan 32, Lund University, Faculty of Engineering LTH, Lund External reviewer(s) Name: Schmidt, Frank Title: Dr Affiliation: ZIK functional genomics, University of Greifswald, Greifswald, Germany ---

PY - 2016/11/7

Y1 - 2016/11/7

N2 - Despite the discovery of antibiotics almost a century ago, infectious diseases continue to be a substantial cause of human mortality and morbidity worldwide, especially in developing countries. The adverse affects of infectious diseases are thought to increase over the coming years as the widespread misuse of antibiotic leads to the emergence of strains for which current therapies are ineffective. The last decades has also seen a large increase of animal pathogens crossing the species barrier to cause disease in humans. To be able to reverse these negative trends we need better knowledge of the events leading to the adaptation of these pathogens to their host. This thesis aspires to increase our understanding of bacterial host adaptation with the hope of finding new targets for diagnostic and therapeutic treatments.In this thesis the development and application of novel mass spectrometry based methods for investigating bacterial host adaptation is studied. The developed methods are based on state of the art mass spectrometry proteomics, which allows the identification and quantification of in principal any expressed protein from a biological sample. The power of this analysis method was used to simultaneously quantify sets of bacterial and host proteins with a specific role in the infection course. These protein measurements are then used as standardization curves to obtain and account for any variation between biological states. The developed methods are combined to construct a quantitative model, depicting host – pathogen interactions and changes during infection progression. The model was used to determine the degree of host adaptation resulting of sequential passaging of the human pathogen Streptococcus pyogenes in a mouse infection model.In summery, this thesis has increased out understanding of the complex interactions leading to host adaptation of bacterial pathogens by the development of a quantitative model for bacterial infections. In addition, this thesis suggests a new approach for biomarker discovery and validation, by using standardization curves of potential biomarkers. The research conducted in this thesis has the potential to lead to increased clinical diagnostic and treatment opportunities of infectious diseases.

AB - Despite the discovery of antibiotics almost a century ago, infectious diseases continue to be a substantial cause of human mortality and morbidity worldwide, especially in developing countries. The adverse affects of infectious diseases are thought to increase over the coming years as the widespread misuse of antibiotic leads to the emergence of strains for which current therapies are ineffective. The last decades has also seen a large increase of animal pathogens crossing the species barrier to cause disease in humans. To be able to reverse these negative trends we need better knowledge of the events leading to the adaptation of these pathogens to their host. This thesis aspires to increase our understanding of bacterial host adaptation with the hope of finding new targets for diagnostic and therapeutic treatments.In this thesis the development and application of novel mass spectrometry based methods for investigating bacterial host adaptation is studied. The developed methods are based on state of the art mass spectrometry proteomics, which allows the identification and quantification of in principal any expressed protein from a biological sample. The power of this analysis method was used to simultaneously quantify sets of bacterial and host proteins with a specific role in the infection course. These protein measurements are then used as standardization curves to obtain and account for any variation between biological states. The developed methods are combined to construct a quantitative model, depicting host – pathogen interactions and changes during infection progression. The model was used to determine the degree of host adaptation resulting of sequential passaging of the human pathogen Streptococcus pyogenes in a mouse infection model.In summery, this thesis has increased out understanding of the complex interactions leading to host adaptation of bacterial pathogens by the development of a quantitative model for bacterial infections. In addition, this thesis suggests a new approach for biomarker discovery and validation, by using standardization curves of potential biomarkers. The research conducted in this thesis has the potential to lead to increased clinical diagnostic and treatment opportunities of infectious diseases.

KW - Proteomics

KW - Mass Spectrometry

KW - Systems biology

KW - Biomarker

KW - Host adaptation

KW - Bacteria

KW - Streptococcus pyogenes

M3 - Doctoral Thesis (compilation)

SN - 978-91-7753-062-6

PB - Department of Immunotechnology, Lund University

CY - Lund

ER -