Identifying Host and Bacterial Biomarkers to Predict Sepsis

Abstract

Sepsis is a serious concern for healthcare programmes worldwide and is associated with 11 million deaths annually. E. coli accounts for 20% of bloodstream infections worldwide and is responsible for 17% of sepsis related mortality. Early diagnosis and treatment are critical and delays in initiating antimicrobial therapy are linked to mortality. Identifying biomarkers to predict patients that might succumb to sepsis is vital to aid in early diagnosis. It was hypothesised that E. coli bacteraemia isolates and isolates from different sources of bacteraemia would elicit a distinctive host response and be genetically unique. Blood culture positive isolates (n=165) were collected from the Hywel Dda University Health Board. Most of the isolates were assigned to the B2 and D phylogroups and belonged to either ST131 or ST73. Antimicrobial resistance in the collection was lower than national averages. Host models of infection were used to identify phenotypic responses of the bacterial collection. IL-8 and MIP3α were increased following stimulation by bacteraemia isolates compared to non-pathogenic strains. Greater IL-8 in whole blood was associated with a urinary and abdominal bacteraemia. Isolates that were resistant to human plasma elicited a higher IL-6, IL-8 and resistin response in whole blood compared to plasma sensitive isolates. Blood culture positive bacteraemia isolates had significantly more virulence factors than control isolates. Bacteraemia isolates expressed more P fimbriae genes. The S fimbrial adhesin genes were found to be significantly different between urinary and abdominal isolates. Abdominal isolates had significantly more sfaC (32%) while urinary isolates had more sfaX (22%). GWAS analysis revealed 6 potential gene targets based on bacterial phenotypes. These were ynbC, yhgE, ybjE, yejF, tufB and yohF. The results contained within this thesis describe new targets for predicting bacteraemia and sepsis and underline the importance of using host and pathogen as sources for biomarkers.