In recent years molecular biology has become an integral part of the clinical laboratory. With an ever increasing number of methodologies and applications being presented each year it has increased our knowledge of how bacteria cause disease as well as our ability to predict disease outcome. The main focus of this thesis has been to develop methods for identifying biomarkers and prediction methods for bacterial infectious diseases by taking advantage of the ever increasing possibilities of molecular biology. We applied cutting edge techniques in order to establish novel platforms for identifying and characterizing biomarkers of disease. In paper one we describe a novel approach to measure levels of antibiotic resistance and viability of C. trachomatis, a method that is a clear improvement over existing techniques. In the second paper we describe the development of two assays designed to type pertussis toxin subunit 1 in circulating strains, in order to facilitate multi center studies for vaccine escape surveillance. In paper three we develop a novel microarray application designed to identify a large number of bacterial traits of H. pylori simultaneously with human genetic polymorphisms in order to identify a collection of risk factors that could be used as a prediction tool for gastric cancer risk. In the last paper we define the “antigenome” of H. pylori and identified 14 promising, previously unreported antigens as well as a number of potential biomarkers. The platform technologies described in this collection of papers will hopefully help us identifying novel ways of fighting and predicting bacterial disease in future studies.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-6509 |
Date | January 2006 |
Creators | Storm, Martin |
Publisher | Uppsala universitet, Institutionen för medicinska vetenskaper, Uppsala : Acta Universitatis Upsaliensis |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Doctoral thesis, comprehensive summary, info:eu-repo/semantics/doctoralThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, 1651-6206 ; 112 |
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