Pathogen-specific epitopes as epidemiological tools for defining the magnitude of Mycobacterium leprae transmission in areas endemic for leprosy

Abstract

During recent years, comparative genomic analysis has allowed the identification of Mycobacterium leprae-specific genes with potential application for the diagnosis of leprosy. In a previous study, 58 synthetic peptides derived from these sequences were tested for their ability to induce production of IFN-γ in PBMC from endemic controls (EC) with unknown exposure to M. leprae, household contacts of leprosy patients and patients, indicating the potential of these synthetic peptides for the diagnosis of sub- or preclinical forms of leprosy. In the present study, the patterns of IFN-γ release of the individuals exposed or non-exposed to M. leprae were compared using an Artificial Neural Network algorithm, and the most promising M. leprae peptides for the identification of exposed people were selected. This subset of M. leprae-specific peptides allowed the differentiation of groups of individuals from sites hyperendemic for leprosy versus those from areas with lower level detection rates. A progressive reduction in the IFN-γ levels in response to the peptides was seen when contacts of multibacillary (MB) patients were compared to other less exposed groups, suggesting a down modulation of IFN-γ production with an increase in bacillary load or exposure to M. leprae. The data generated indicate that an IFN-γ assay based on these peptides applied individually or as a pool can be used as a new tool for predicting the magnitude of M. leprae transmission in a given population.

Figure 1. Selection of M. leprae-specific peptides.

Fifty-eight M. leprae-specific peptides were previously tested for induction of IFN-γ release by PBMC from leprosy patients and contacts, endemic and non-endemic controls . The IFN-γ levels induced by the peptides in non-exposed (EC_low) and M. leprae-exposed individuals (HCMB) were used for selecting the best set of peptides allowing discrimination of the exposed group by applying an ANN algorithm. The final 12- peptide ANN made the right choice in 96% of the tests, identifying M.leprae-exposed or non-exposed individuals. *, individuals recruited from the city of Rio de Janeiro.

Figure 2. Leprosy detection rates and responsiveness to M. leprae specific peptides.

Peripheral blood mononuclear cells (PBMCs) from individuals with different levels of exposure to M. leprae were stimulated with 17 M.leprae-specific peptides, and the concentration of IFN-γ measured in culture supernatants. The boxes include response rates of 75% of the sample, and the horizontal bars in bold identify the medians. Points outside the deviation correspond to outliers. ○, Values between 1.5 and 3 box lengths from the upper or lower edge of the box. *, Values more than 3 box lengths from the upper or lower edge of the box. A: A Dutch group of healthy non-endemic controls (NEC_Netherlands); B: healthy controls from Porto Alegre, Brazil (NEC_Brazi); C: healthy endemic controls from an area with medium annual new case detection rate for leprosy (Meireles, Fortaleza, CE, Brazil; EC_low); D: another area with hyperendemic leprosy annual new case detection rate (Bom Jardim, Fortaleza, CE, Brazil; EC_high); E: a Dutch group of tuberculosis patients (TB).

Figure 3. Responsiveness to M. leprae-specific peptides in household contacts of leprosy patients.

The ex vivo stimulation of PBMC was done as described in Fig. 2 legend. A: Household contacts of paucibacillary (HCPB); and B: multibacillary leprosy patients (HCMB). The responses to the 17 M. leprae-specific peptides in PGL-I positive and negative HCPB are shown in separate plots (C,D). Detection of IgM anti-PGL1 in sera was performed using a specific ELISA.

Figure 4. Responsiveness to M. leprae-specific peptides in PB and MB leprosy patients.

The ex vivo stimulation of PBMC was done as described in Fig. 2 legend. A: Paucibacillary (PB); and B: multibacillary (MB) leprosy patients.

Figure 5. Level of exposure to M. leprae and response to the bacillus or M. leprae-specific peptides.

Medians of the IFN-γ levels induced by M.leprae-specific peptides (A, C, D) or sonicated M. leprae (B) are shown for groups displayed in increasing order of exposure to M. leprae from left to right in the “x” axis. Detection of IgM anti-PGL1 in sera was performed using a specific ELISA (E).

Figure 6. IFN-γ production in response to pools of M. leprae-specific peptides.

PBMCs from PB (A), HCMB (B), EC_high (C) and EC_low (D) groups stimulated with the 9 mer peptide pool (p52, p61, p68, p69 – 0.1, 1.0 and 10 µg/mL) and the 15 mer peptide pool(p38, p51, p56, p59, p65, p67, p70, p71, p88, p91, p92 - 0.1, 1.0 and 10 µg/ml). After 5 days culture, supernatants were harvested and assessed for levels of IFN-γ by ELISA. Each circle indicates an individual and the dash the median.

Figure 7. A model for modulation of IFN-γ production during asymptomatic M. leprae infection and active disease.