Enteric (or typhoid) fever is a systemic infection mainly caused by Salmonella Typhi and Salmonella Paratyphi A. The disease is common in areas with poor water quality and insufficient sanitation. Humans are the only reservoir for transmission of the disease. The presence of asymptomatic chronic carriers is a complicating factor for the transmission. There are major limitations regarding the current diagnostic methods both for acute infection and chronic carriage. Metabolomics is a methodology studying metabolites in biological systems under influence of environmental or physiological perturbations. It has been applied to study several infectious diseases, with the goal of detecting diagnostic biomarkers. In this thesis, a mass spectrometry-based metabolomics approach, including chemometric bioinformatics techniques for data analysis, has been used to evaluate the potential of metabolite biomarker patterns for diagnosis of enteric fever at different stages of the disease.
In Paper I, metabolite patterns related to acute enteric fever were investigated. Human plasma samples from patients in Nepal with culture-confirmed S. Typhi or S. Paratyphi A infection were compared to afebrile controls. A metabolite pattern discriminating between acute enteric fever and afebrile controls, as well as between the two causative agents of enteric fever was detected. The strength of using a panel of metabolites instead of single metabolites as biomarkers was also highlighted. In Paper II, metabolite patterns for acute enteric fever, this time focusing only on S. Typhi infections, were investigated. Human plasma from patients in Bangladesh with culture-positive or -negative but clinically suspected S. Typhi infection were compared to febrile controls. Differences were found in metabolite patterns between the culture-positive S. Typhi group and the febrile controls with a heterogeneity among the suspected S. Typhi samples. Consistencies in metabolite patterns were found to the results from Paper I. In addition, a validation cohort with culture-positive S. Typhi samples and a control group including patients with malaria and infections caused by other pathogens was analysed. Differences in metabolite patterns were detected between S. Typhi samples and all controls as well as between S. Typhi and malaria. Consistencies in metabolite patterns were found to the primary Bangladeshi cohort and the Nepali cohort from Paper I. Paper III focused on chronic Salmonella carriers. Human plasma samples from patients in Nepal undergoing cholecystectomy with confirmed S. Typhi or S. Paratyphi A gallbladder carriage were compared to non-carriage controls. The Salmonella carriage samples were distinguished from the non-carriage controls and differential signatures were also found between the S. Typhi and S. Paratyphi A carriage samples. Comparing metabolites found during chronic carriage and acute enteric fever (in Paper I) resulted in a panel of metabolites significant only during chronic carriage. This work has contributed to highlight the potential of using metabolomics as a tool to find diagnostic biomarker patterns associated with different stages of enteric fever.
The host-pathogen interactions induced by Salmonella Typhi and Salmonella Paratyphi A during enteric fever are poorly understood. This knowledge gap, and the human restricted nature of these bacteria, limit our understanding of the disease and impede the development of new diagnostic approaches. To investigate metabolite signals associated with enteric fever we performed two-dimensional gas chromatography with time-of-flight mass spectrometry (GCxGC/TOFMS) on plasma from patients with S. Typhi and S. Paratyphi A infections and asymptomatic controls, identifying 695 individual metabolite peaks. Applying supervised pattern recognition, we found highly significant and reproducible metabolite profiles separating S. Typhi cases, S. Paratyphi A cases, and controls, calculating that a combination of six metabolites could accurately define the etiological agent. For the first time we show that reproducible and serovar specific systemic biomarkers can be detected during enteric fever. Our work defines several biologically plausible metabolites that can be used to detect enteric fever, and unlocks the potential of this method in diagnosing other systemic bacterial infections.
Salmonella Typhi is the causative agent of typhoid. Typhoid is diagnosed by blood culture, a method that lacks sensitivity, portability and speed. We have previously shown that specific metabolomic profiles can be detected in the blood of typhoid patients from Nepal (Nasstrom et al., 2014). Here, we performed mass spectrometry on plasma from Bangladeshi and Senegalese patients with culture confirmed typhoid fever, clinically suspected typhoid, and other febrile diseases including malaria. After applying supervised pattern recognition modelling, we could significantly distinguish metabolite profiles in plasma from the culture confirmed typhoid patients. After comparing the direction of change and degree of multivariate significance, we identified 24 metabolites that were consistently up- or down regulated in a further Bangladeshi/Senegalese validation cohort, and the Nepali cohort from our previous work. We have identified and validated a metabolite panel that can distinguish typhoid from other febrile diseases, providing a new approach for typhoid diagnostics.