Metabonomics reveals drastic changes in anti-inflammatory/pro-resolving polyunsaturated fatty acids-derived lipid mediators in leprosy disease

Abstract

Despite considerable efforts over the last decades, our understanding of leprosy pathogenesis remains limited. The complex interplay between pathogens and hosts has profound effects on host metabolism. To explore the metabolic perturbations associated with leprosy, we analyzed the serum metabolome of leprosy patients. Samples collected from lepromatous and tuberculoid patients before and immediately after the conclusion of multidrug therapy (MDT) were subjected to high-throughput metabolic profiling. Our results show marked metabolic alterations during leprosy that subside at the conclusion of MDT. Pathways showing the highest modulation were related to polyunsaturated fatty acid (PUFA) metabolism, with emphasis on anti-inflammatory, pro-resolving omega-3 fatty acids. These results were confirmed by eicosanoid measurements through enzyme-linked immunoassays. Corroborating the repertoire of metabolites altered in sera, metabonomic analysis of skin specimens revealed alterations in the levels of lipids derived from lipase activity, including PUFAs, suggesting a high lipid turnover in highly-infected lesions. Our data suggest that omega-6 and omega-3, PUFA-derived, pro-resolving lipid mediators contribute to reduced tissue damage irrespectively of pathogen burden during leprosy disease. Our results demonstrate the utility of a comprehensive metabonomic approach for identifying potential contributors to disease pathology that may facilitate the development of more targeted treatments for leprosy and other inflammatory diseases.

Figure 1. Metabonomics analysis of sera from leprosy patients.

(a) Principal component analysis of metabolic alterations on sera from borderline tuberculoid (BT) and polar lepromatous leprosy (LL) patients. Raw DI-FT-ICR-MS data in both negative and positive ionization modes were combined and PCA was performed using Multibase (http://www.numericaldynamics.com/). Sample groups are indicated by the dashed lines. (b) Metabolic pathways altered in the polar forms of leprosy. m/z of interest detected in both negative and positive ionization modes were searched against the KEGG database (http://www.genome.jp/kegg/) using the MassTRIX software (version 2, http://metabolomics.helmholtz-muenchen.de/masstrix2/). Bars indicate the number of metabolic features from each KEGG pathway that was affected by infection. Gray bars represent the number of metabolic features that were found in higher levels in BT patients (>2 fold), whereas white bars represent the metabolic features found in higher levels in LL patients.

Figure 2. Principal component analysis of the metabonomics data.

Raw DI-FT-ICR-MS data in both negative and positive ionization modes were combined and PCA was performed using Multibase (http://www.numericaldynamics.com/). Plots show the separation of groups based on the pole of disease (BT, LL) and treatment status (before, after). Sample groups are indicated by the dashed lines.

Figure 3. Serum levels of eicosanoids in borderline tuberculoid and polar lepromatous patients determined by EIAs.

Box-plots represent serum levels of PGD₂ (a), PGE₂ (b), LTB₄ (c) and LXA₄ (d) assessed in healthy controls, BT and LL patients, as indicated. Median values are indicated by lines. Outliers were detected using the Grubbs' test and removed. Group comparisons were evaluated with Kruskall–Wallis non-parametric analysis of variance (ANOVA) and Dunn's multiple-range post hoc test. PGD₂, prostaglandin D₂; PGE₂, prostaglandin E₂; LTB₄, leukotriene B₄; LXA₄, lipoxin A₄. P-values higher than 0.05 are not shown.

Figure 4. Circulating levels of eicosanoids in borderline tuberculoid and polar lepromatous patients before and after MDT determined by EIAs.

Paired values of serum concentrations of PGD₂ (a), PGE₂ (b), LTB₄ (c) and LXA₄ (d) from each patient, as assessed in BT and LL patients before and right after MDT conclusion. Each line represents one patient. Paired t tests were used for statistical analysis. PGD₂, prostaglandin D₂; PGE₂, prostaglandin E₂; LTB₄, leukotriene B₄; LXA₄, lipoxin A₄. P-values higher than 0.05 are not shown.

Figure 5. Serum levels of resolvin D1 in borderline tuberculoid and polar lepromatous patients determined by EIAs.

Box plots represent serum levels of RvD1 assessed in healthy controls, BT and LL patients before (A) and right after MDT conclusion (B), as indicated. Median values are indicated by lines. Group comparisons were evaluated with Kruskall–Wallis non-parametric analysis of variance (ANOVA) and Dunn's multiple-range post hoc test. Paired values of serum concentrations of RvD1 from each patient before and right after MDT conclusion, as assessed in BT and LL patients, are shown in C and D, respectively. Each line represents one patient. Paired t tests were used for statistical analysis. P-values higher than 0.05 are not shown.