Toll-like receptors blocking restores in vitro microbicidal activity in latent tuberculosis-infected subjects

Recognition of Mycobacterium tuberculosis by macrophage Toll-like receptor and its role in autophagy

BACKGROUND

The pathogen responsible for tuberculosis is called Mycobacterium tuberculosis. Its interaction with macrophages has a significant impact on the onset and progression of the disease.

METHODS

The respiratory pathway allows Mycobacterium tuberculosis to enter the body's lungs where it battles immune cells before being infected latently or actively. In the progress of tuberculosis, Mycobacterium tuberculosis activates the body's immune system and creates inflammatory factors, which cause tissue inflammation to infiltrate and the creation of granulomas, which seriously harms the body. Toll-like receptors of macrophage can mediate host recognition of Mycobacterium tuberculosis, initiate immune responses, and participate in macrophage autophagy. New host-directed therapeutic approaches targeting autophagy for drug-resistant Mycobacterium tuberculosis have emerged, providing new ideas for the effective treatment of tuberculosis.

CONCLUSIONS

In-depth understanding of the mechanisms by which macrophage autophagy interacts with intracellular Mycobacterium tuberculosis, as well as the study of potent and specific autophagy-regulating molecules, will lead to much-needed advances in drug discovery and vaccine design, which will improve the prevention and treatment of human tuberculosis.

Protein Expression of TLR2, TLR4, and TLR9 on Monocytes in TB, HIV, and TB/HIV

Toll-like receptors (TLRs) have a critical role in recognizing pathogenic patterns and initiating immune responses against TB and HIV. Previously, studies described the gene expression of TLRs in patients with TB and HIV. Here, we demonstrated TLRs protein expressions and their association with clinical status and plasma markers in TB, HIV, and TB/HIV coinfection. The phenotyping of TLR2, TLR4, and TLR9 on CD14+ monocytes and their subsets were determined by multicolor flow cytometry. Host plasma biomarkers and microbial indices were measured using Luminex Multiplex assay and standard of care tools, respectively. TLR2 expression significantly enhanced in TB, slightly increased in HIV but slightly reduced in TB/HIV coinfection compared to apparently health controls (HC). On the other hand, TLR4 expression was significantly increased in TB, HIV, and TB/HIV compared to HC. Expression of TLR4 was equally enhanced on classical and intermediate monocytes while higher TLR2 expression on intermediate than classical monocytes. TLR4 had a positive correlation pattern with plasma biomarkers while TLR2 had an inverse correlation pattern. TLR4 is associated with disease severity while TLR2 is with the immune-competent status of patients. Our findings demonstrated that the pattern of TLR expression is disease as well as monocyte subset specific and distinct factors drive these differences.

From immunology to artificial intelligence: revolutionizing latent tuberculosis infection diagnosis with machine learning

Latent tuberculosis infection (LTBI) has become a major source of active tuberculosis (ATB). Although the tuberculin skin test and interferon-gamma release assay can be used to diagnose LTBI, these methods can only differentiate infected individuals from healthy ones but cannot discriminate between LTBI and ATB. Thus, the diagnosis of LTBI faces many challenges, such as the lack of effective biomarkers from Mycobacterium tuberculosis (MTB) for distinguishing LTBI, the low diagnostic efficacy of biomarkers derived from the human host, and the absence of a gold standard to differentiate between LTBI and ATB. Sputum culture, as the gold standard for diagnosing tuberculosis, is time-consuming and cannot distinguish between ATB and LTBI. In this article, we review the pathogenesis of MTB and the immune mechanisms of the host in LTBI, including the innate and adaptive immune responses, multiple immune evasion mechanisms of MTB, and epigenetic regulation. Based on this knowledge, we summarize the current status and challenges in diagnosing LTBI and present the application of machine learning (ML) in LTBI diagnosis, as well as the advantages and limitations of ML in this context. Finally, we discuss the future development directions of ML applied to LTBI diagnosis.

Increase of CD4+CD25highFoxP3+ cells impairs in vitro human microbicidal activity against Mycobacterium tuberculosis during latent and acute pulmonary tuberculosis

Background

Regulatory T cells (Tregs) play a critical role during Mycobacterium tuberculosis (Mtb) infection, modulating host responses while neutralizing excessive inflammation. However, their impact on regulating host protective immunity is not completely understood. Here, we demonstrate that Treg cells abrogate the in vitro microbicidal activity against Mtb.

Methods

We evaluated the in vitro microbicidal activity of peripheral blood mononuclear cells (PBMCs) from patients with active tuberculosis (TB), individuals with latent tuberculosis infection (LTBI, TST+/IGRA+) and healthy control (HC, TST-/IGRA-) volunteers. PBMCs, depleted or not of CD4⁺CD25⁺ T-cells, were analyzed to determine frequency and influence on microbicidal activity during in vitro Mtb infection with four clinical isolates (S1, S5, R3, and R6) and one reference strain (H37Rv).

Results

The frequency of CD4⁺CD25^highFoxP3⁺ cells were significantly higher in Mtb infected whole blood cultures from both TB patients and LTBI individuals when compared to HC. Data from CD4⁺CD25⁺ T-cells depletion demonstrate that increase of CD4⁺CD25^highFoxP3⁺ is associated with an impairment of Th-1 responses and a diminished in vitro microbicidal activity of LTBI and TB groups.

Conclusions

Tregs restrict host anti-mycobacterial immunity during active disease and latent infection and thereby may contribute to both disease progression and pathogen persistence.

Our immune system has an enormous capacity of recognizing and responding to foreign antigens and, likewise, presents an extremely efficient mechanism of controlling these responses. Here, we investigated how a specific cell type with regulatory abilities can interfere in the immunological response against tuberculosis bacillus. For this, we used blood samples from individuals sensitized with the bacillus and patients with active pulmonary tuberculosis to understand how these cells act and their impact on the host/parasite relationship in the development of the disease. We could observe the negative impact that such regulatory cells cause during the immune response against Mycobacterium tuberculosis, decreasing the control/elimination of the bacillus in asymptomatic individuals and patients with tuberculosis. We also observed a recovery in the immune response when Treg cells were removed during in vitro challenge, restoring the capacity of Mtb clearance. Thus, these regulatory cells, when present, may represent a possible facilitator of the asymptomatic permanence of the bacillus, or even of the development of the disease itself. These data allowed us to see latency and tuberculosis from a new angle and thus postulate new approaches to fight tuberculosis.

A Role of Intracellular Toll-Like Receptors (3, 7, and 9) in Response to Mycobacterium tuberculosis and Co-Infection with HIV

Mycobacterium tuberculosis (Mtb) is a highly infectious acid-fast bacillus and is known to cause tuberculosis (TB) in humans. It is a leading cause of death from a sole infectious agent, with an estimated 1.5 million deaths yearly worldwide, and up to one third of the world's population has been infected with TB. The virulence and susceptibility of Mtb are further amplified in the presence of Human Immunodeficiency Virus (HIV). Coinfection with Mtb and HIV forms a lethal combination. Previous studies had demonstrated the synergistic effects of Mtb and HIV, with one disease accelerating the disease progression of the other through multiple mechanisms, including the modulation of the immune response to these two pathogens. The response of the endosomal pattern recognition receptors to these two pathogens, specifically toll-like receptors (TLR)-3, -7, and -9, has not been elucidated, with some studies producing mixed results. This article seeks to review the roles of TLR-3, -7, and -9 in response to Mtb infection, as well as Mtb-HIV-coinfection via Toll-interleukin 1 receptor (TIR) domain-containing adaptor inducing INF-β (TRIF)-dependent and myeloid differentiation factor 88 (MyD88)-dependent pathways.