A metabolomics analysis and the development of a fluorescent assay for kynurenine for the diagnosis of sepsis in trauma patients

Patel, Kamlesh (2021). A metabolomics analysis and the development of a fluorescent assay for kynurenine for the diagnosis of sepsis in trauma patients. University of Birmingham. Ph.D.

Text - Accepted Version
Available under License All rights reserved.

Download (4MB) | Preview


Traumatic injuries are a leading cause of death worldwide. Whilst the physical injuries can be treated patients are still at risk of developing an infection and becoming septic. It is hard to diagnose sepsis in patients of trauma as the inflammatory response to sepsis is masked by the inflammatory response to the traumatic injury. Current diagnostic techniques involve culturing blood samples or identifying a site of infection, neither of which are fast enough to allow for the best patient outcome. As such there is much need for a point of care diagnostic test. This work attempted to tackle this problem in two ways. First by analysing a metabolomics data set to identify biomarkers of sepsis in burns patients. Second, by developing a quantitative fluorescent assay for the detection of kynurenine, a biomarker of sepsis.

The data analysis was performed on a metabolomics data set acquired from clinical samples from burns patients. Three different classifiers were used to create models on the data set, k-nearest neighbours, naive Bayes and logistic regression. Classifier performance was above average on the data set, with the k-NN technique providing an AUC value of 0.82 and sensitivity and specificity of 85 % and 70 % respectively on the early-sample class-balanced subset of the data. The t-test and minimum redundancy maximum relevancy (MRMR) feature selection techniques were performed on the data set along with lasso with logistic regression. The t-test and logistic regression identified glucose and lactate as being the most important features whereas MRMR identified glucose and not lactate. These are both already well known biomarkers used in controlling the outcome of sepsis patients.

A literature search identified the metabolite kynurenine as being a positive biomarker for sepsis in patients of trauma. A fluorescent molecule was synthesised which upon binding to kynurenine causes a large bathochromic shift in the emission spectrum of the fluorescent sensor from 470 nm to 560 nm.

A fluorescent assay was created using the standard addition technique to quantify the amount of kynurenine in a urine sample. The standard addition technique was chosen as it removes matrix affects which would be present when using biological samples. Tests performed on pure samples of kynurenine, gave results within 5 % of the actual concentration. Synthetic urine was then used, giving results within 10 % of the actual concentration.

HPLC experiments were performed to quantify the amount of kynurenine in actual urine samples. The HPLC protocol was validated with kynurenine in solutions of water and synthetic urine, however complications arose when using urine which meant the clinical samples could not be accurately quantified. As such, a qualitative experiment showed linear fluorescence plots when performing the standard addition technique with actual urine samples.

The results indicate the assay will work in urine. Being fluorescence based it has the potential to move into a point of care device. Future work would go towards quantifying the kynurenine concentration in clinical samples and then optimising the assay parameters once known concentrations can be determined.

Type of Work: Thesis (Doctorates > Ph.D.)
Award Type: Doctorates > Ph.D.
Licence: All rights reserved
College/Faculty: Colleges (2008 onwards) > College of Engineering & Physical Sciences
School or Department: School of Chemistry
Funders: Engineering and Physical Sciences Research Council, National Institute for Health Research
Subjects: Q Science > Q Science (General)
Q Science > QD Chemistry
T Technology > TP Chemical technology
URI: http://etheses.bham.ac.uk/id/eprint/11281


Request a Correction Request a Correction
View Item View Item


Downloads per month over past year