Leprosy Cell Models for Research

Leprosy, also known as Hansen's disease, is a chronic infectious disease caused by Mycobacterium leprae. According to the World Health Organization (WHO), approximately 127,558 new cases were reported globally in 2020, with a prevalence of 0.2 per 10,000 population. The disease primarily affects the skin, peripheral nerves, upper respiratory tract, and eyes. Key risk factors include poverty, overcrowding, and genetic susceptibility. The 5-year survival rate for leprosy is generally high with treatment, but delayed diagnosis can lead to permanent disability. The WHO aims to eliminate leprosy as a public health problem, defined as a prevalence of less than 1 case per 10,000 population.

Leprosy serves as a valuable model for studying host-pathogen interactions, immune evasion, and nerve damage. The disease presents with a spectrum of clinical forms, from tuberculoid to lepromatous, reflecting different immune responses. Public datasets such as those from the WHO and NCBI provide genomic and transcriptomic data on M. leprae and host responses. Open questions include the mechanisms of immune evasion, drug resistance, and the role of genetic factors in susceptibility. The inability to culture M. leprae in vitro has driven the development of alternative models, including gene-edited cell lines and animal models.

Leprosy is not a carcinogenic disease, but its pathogenesis involves several key pathways:

• • Immune response pathways:

1. Toll-like receptor (TLR) signaling: Activation by M. leprae antigens leads to cytokine production.

2. NF-kB pathway: Regulates inflammatory responses and bacterial killing.

3. JAK-STAT pathway: Mediates interferon-gamma signaling, crucial for granuloma formation.

• • Nerve damage pathways:

1. Schwann cell interaction: M. leprae binds to Schwann cells via PGL-1 and laminin-2, leading to demyelination.

2. Apoptosis and autophagy: Modulated by bacterial factors, contributing to nerve injury.

Host genetic factors influence leprosy susceptibility. Key genes and variants are listed below. Data are from ClinVar and NCBI Gene.

Key signaling networks in leprosy pathogenesis include:

• • TLR/NF-kB pathway:
• • TLR1/2 heterodimers recognize M. leprae lipoproteins.
• • MyD88 recruitment leads to NF-kB activation and pro-inflammatory cytokines.
• • JAK-STAT pathway:
• • IFN-gamma activates JAK1/2 and STAT1, promoting Th1 responses.
• • In lepromatous leprosy, this pathway is suppressed.
• • PI3K/AKT/mTOR pathway:
• • Modulates autophagy and phagosome maturation.
• • M. leprae can activate AKT to inhibit apoptosis.
• • Wnt signaling:
• • Involved in Schwann cell dedifferentiation and nerve repair.

Several cell lines are used to study M. leprae infection. Key examples:

Organoids derived from skin or nerve tissue offer advantages: they mimic tissue architecture, allow long-term culture, and enable studies of host-pathogen interactions in a more physiological context.

Animal models for leprosy include:

• • Nine-banded armadillo: Natural host, develops systemic disease.
• • Mouse footpad model: Used for drug efficacy and immune studies.
• • Genetically engineered mouse models (GEMMs):
• • NOD/SCID mice reconstituted with human immune cells.
• • Knockout mice for immune genes (e.g., TLR1, NRAMP1).
• • Induced models: Zebrafish infected with M. leprae for real-time imaging.

CRISPR-Cas9 technology enables the creation of isogenic cell lines with specific genetic modifications to study leprosy. Examples include:

• • NRAMP1 (SLC11A1) knockout in THP-1 cells to assess macrophage function.
• • TLR1 knock-in of the T1805G variant in HaCaT cells to study immune signaling.
• • PARK2 knockout in Schwann cells to investigate autophagy defects.

Commercially available, sequence-verified gene-edited cell models accelerate research by providing reproducible tools for target validation and drug screening. These models are generated using CRISPR and other gene-editing technologies, ensuring consistent genetic backgrounds.

Gene-edited cell lines enable functional validation of genes implicated in leprosy susceptibility. For example:

• • Knockout of NRAMP1 in macrophages confirms its role in restricting M. leprae growth.
• • Knock-in of TLR1 variants demonstrates impaired cytokine production.
• • CRISPR screens identify host factors required for bacterial uptake.

Isogenic pairs of cell lines (wild-type vs. mutant) are used for high-throughput drug screening. For instance:

• • Comparing wild-type and PARK2-knockout Schwann cells to test neuroprotective drugs.
• • Modeling drug resistance by introducing mutations in drug targets (e.g., dapsone resistance in folP1).
• • Screening for compounds that overcome resistance in M. leprae-infected cells.

CRISPR synthetic lethality screens in leprosy models can identify host dependencies. For example:

• • Genome-wide knockout screens in M. leprae-infected macrophages reveal essential host genes.
• • These genes serve as potential biomarkers for diagnosis or targets for host-directed therapies.