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1.
Elife ; 62017 05 09.
Article in English | MEDLINE | ID: mdl-28483042

ABSTRACT

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 (Näsström 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.


Subject(s)
Metabolomics/methods , Plasma/chemistry , Salmonella typhi/growth & development , Salmonella typhi/metabolism , Typhoid Fever/diagnosis , Typhoid Fever/pathology , Bangladesh , Humans , Mass Spectrometry , Senegal
2.
Elife ; 32014 Jun 05.
Article in English | MEDLINE | ID: mdl-24902583

ABSTRACT

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.


Subject(s)
Metabolome , Salmonella paratyphi A/metabolism , Salmonella typhi/metabolism , Typhoid Fever/blood , Typhoid Fever/microbiology , Area Under Curve , Bacterial Proteins/metabolism , Biomarkers/metabolism , Case-Control Studies , Fluoroquinolones/administration & dosage , Gas Chromatography-Mass Spectrometry , Gatifloxacin , Humans , Metabolomics , Multivariate Analysis , Nepal , Ofloxacin/administration & dosage , Pattern Recognition, Automated , Principal Component Analysis , ROC Curve , Randomized Controlled Trials as Topic
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