Engineered biomarkers for leprosy diagnosis using labeled and label-free analysis

Biosensor-Based Multiple Cross Displacement Amplification for the Rapid Detection of Mycobacterium leprae

Leprosy is an ancient disease caused by Mycobacterium leprae (ML) that remains a public health problem in poverty-stricken areas worldwide. Although many ML detection techniques have been used, a rapid and sensitive tool is essential for the early detection and treatment of leprosy. Herein, we developed a rapid ML detection technique by combining multiple cross displacement amplification (MCDA) with a nanoparticle-based lateral flow biosensor (LFB), termed ML-MCDA-LFB. MCDA induced a rapid isothermal reaction using specific primers targeting the RLEP gene, and the LFB enabled instant visual amplicon detection. The pure genomic DNA of ML and nucleic acids from various pathogens were employed to evaluate and optimize the ML-MCDA-LFB assay. The optimal conditions for ML-MCDA-LFB were 68 °C and 35 min, respectively. The limit of detection for pure ML genomic DNA was 150 fg per vessel, and the specificity of detection was 100% for the experimental strains. Additionally, the entire detection process could be performed within 40 min, including the isothermal amplification (35 min) and result confirmation (1-2 min). Hence, the ML-MCDA-LFB assay was shown to be a rapid, sensitive, and visual method for detecting ML and could be used as a potential tool for early clinical diagnosis and field screening of leprosy.

Highly sensitive and rapid determination of Mycobacterium leprae based on real-time multiple cross displacement amplification

BACKGROUND

Mycobacterium leprae (ML) is the pathogen that causes leprosy, which has a long history and still exists today. ML is an intracellular mycobacterium that dominantly induces leprosy by causing permanent damage to the skin, nerves, limbs and eyes as well as deformities and disabilities. Moreover, ML grows slowly and is nonculturable in vitro. Given the prevalence of leprosy, a highly sensitive and rapid method for the early diagnosis of leprosy is urgently needed.

RESULTS

In this study, we devised a novel tool for the diagnosis of leprosy by combining restriction endonuclease, real-time fluorescence analysis and multiple cross displacement amplification (E-RT-MCDA). To establish the system, primers for the target gene RLEP were designed, and the optimal conditions for E-RT-MCDA at 67 °C for 36 min were determined. Genomic DNA from ML, various pathogens and clinical samples was used to evaluate and optimize the E-RT-MCDA assay. The limit of detection (LoD) was 48.6 fg per vessel for pure ML genomic DNA, and the specificity of detection was as high as 100%. In addition, the detection process could be completed in 36 min by using a real-time monitor.

CONCLUSION

The E-RT-MCDA method devised in the current study is a reliable, sensitive and rapid technique for leprosy diagnosis and could be used as a potential tool in clinical settings.

Epitope mapping from Mycobacterium leprae proteins: Convergent data from in silico and in vitro approaches for serodiagnosis of leprosy

Knowledge of immunodominant B-cell epitopes is essential to design powerful diagnostic strategies aiming for antibody detection. Outstanding progress in computational prediction has achieved a significant contribution to the biomedical fields, including immunodiagnosis. In silico analysis may have an even more important role when information concerning antigens from etiologic agents of neglected diseases, such as leprosy, is scarce. The aim of this study was to provide mapping of B-cell epitopes from two Mycobacterium leprae-derived antigens (Ag85B and ML2055), confirm their antigenicity, and to assess the ability of in silico immunoinformatics tools to accurately predict them. Linear B-cell epitopes predicted by ABCpred and SVMTrip servers were compared to antigenic regions of synthetic overlapping peptides that exhibited reactivity to antibodies from patients with leprosy. Our in vitro results identified several immunodominant regions that had also been indicated by in silico prediction, providing agreement between experimental and simulated data. After chemical synthesis, we used enzyme-linked immunosorbent assays to determine the effectiveness of the first identified sequence (GTNVPAEFLENFVHG) which had 72 % sensitivity and 78 % specificity (AUC = 0.79) while the second one (PVSSEAQPGDPNAPS) had 72 % sensitivity and 93.8 % specificity (AUC = 0.85). Using dot blotting, an easy-to-read visual test, both peptides could distinguish sera from patients with leprosy from those with tuberculosis and from sera of healthy volunteers. Our findings suggest that these synthetic peptides, with some refinement, may be useful as serological diagnostic antigens for leprosy. In addition, it was displayed that immunoinformatics provides reliable information for mapping potential B-cell epitopes for development of peptide-based diagnostic assays for neglected diseases.