Urine metabolome in women with Chlamydia trachomatis infection

Abstract

The aim of this study was to characterize the urine metabolome of women with Chlamydia trachomatis (CT) uro-genital infection (n = 21), comparing it with a group of CT-negative subjects (n = 98). By means of a proton-based nuclear magnetic resonance (1H-NMR) spectroscopy, we detected and quantified the urine metabolites of a cohort of 119 pre-menopausal Caucasian women, attending a STI Outpatients Clinic in Italy. In case of a CT positive result, CT molecular genotyping was performed by omp1 gene semi-nested PCR followed by RFLP analysis. We were able to identify several metabolites whose concentrations were significantly higher in the urine samples of CT-positive subjects, including sucrose, mannitol, pyruvate and lactate. In contrast, higher urinary levels of acetone represented the main feature of CT-negative women. These results were not influenced by the age of patients nor by the CT serovars (D, E, F, G, K) responsible of the urethral infections. Since the presence of sugars can increase the stability of chlamydial proteins, higher levels of sucrose and mannitol in the urethral lumen, related to a higher sugar consumption, could have favoured CT infection acquisition or could have been of aid for the bacterial viability. Peculiar dietary habits of the subjects enrolled, in term of type and amount of food consumed, could probably explain these findings. Lactate and pyruvate could result from CT-induced immunopathology, as a product of the inflammatory microenvironment. Further studies are needed to understand the potential role of these metabolites in the pathogenesis of CT infection, as well as their diagnostic/prognostic use.

Fig 1. Graphic design of the workflow for urines preparation and ¹H-NMR spectra processing.

Urine samples were centrifuged and 700 μl of the supernatant were added to 0.2 mL of 3-(trimethylsilyl)-propionic-2,2,3,3-d4 acid (TSP) sodium salt 10 mM in deuterated water. The pH values of the solutions were adjusted to 7.0 by means of NaOH 1M and the samples were subjected to ¹H-NMR spectroscopy. The spectra obtained by ¹H-NMR were aligned and baseline-adjusted (normalization) and the signals were assigned to a specific metabolite by comparing their chemical shift and multiplicity with dedicated databases and libraries. Quantification of the molecules was achieved after the calculation of the area under each peak by means of a rectangular integration. The added TSP, at a known concentration, was employed as internal standard.

Fig 2. rPCA model calculated on the space constituted by the concentration of the molecules listed in Table 1.

In the scoreplot (A), CT-negative (CT-) and CT-positive (CT+) subjects are represented in black and gray respectively, with lines connecting each subject to the median of its group. In the barplot (B), describing the correlation between the concentration of each molecule and its importance over PC 1, dark gray bars highlight statistically significant correlations (P<0.05).