Chrome Extension
WeChat Mini Program
Use on ChatGLM

1 H NMR spectroscopy-based metabolomics analysis for the diagnosis of symptomatic E. coli -associated urinary tract infection (UTI)

BMC Microbiology(2017)

Cited 19|Views31
No score
Abstract
Background Urinary tract infection (UTI) is one of the most common diagnoses in girls and women, and to a lesser extent in boys and men younger than 50 years. Escherichia coli , followed by Klebsiella spp. and Proteus spp. , cause 75-90% of all infections. Infection of the urinary tract is identified by growth of a significant number of a single species in the urine, in the presence of symptoms. Urinary culture is an accurate diagnostic method but takes several hours or days to be carried out. Metabolomics analysis aims to identify biomarkers that are capable of speeding up diagnosis. Methods Urine samples from 51 patients with a prior diagnosis of Escherichia coli -associated UTI, from 21 patients with UTI caused by other pathogens (bacteria and fungi), and from 61 healthy controls were analyzed. The 1 H-NMR spectra were acquired and processed. Multivariate statistical models were applied and their performance was validated using permutation test and ROC curve. Results Orthogonal Partial Least Squares-discriminant Analysis (OPLS-DA) showed good separation (R 2 Y = 0.76, Q2=0.45, p < 0.001) between UTI caused by Escherichia coli and healthy controls. Acetate and trimethylamine were identified as discriminant metabolites. The concentrations of both metabolites were calculated and used to build the ROC curves. The discriminant metabolites identified were also evaluated in urine samples from patients with other pathogens infections to test their specificity. Conclusions Acetate and trimethylamine were identified as optimal candidates for biomarkers for UTI diagnosis. The conclusions support the possibility of a fast diagnostic test for Escherichia coli -associated UTI using acetate and trimethylamine concentrations.
More
Translated text
Key words
1 H NMR spectroscopy,E. coli
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined