Differential expression of maturation and activation markers on NK cells in patients with active and latent tuberculosis

Transcriptional profiling of human peripheral blood mononuclear cells in household contacts of pulmonary tuberculosis patients provides insights into mechanisms of Mycobacterium tuberculosis control and elimination

Household contacts (HHCs) of patients with active tuberculosis (ATB) are at higher risk of Mycobacterium tuberculosis (M. tuberculosis) infection. However, the immune factors responsible for different defense responses in HHCs are unknown. Hence, we aimed to evaluate transcriptome signatures in human peripheral blood mononuclear cells (PBMCs) of HHCs to aid risk stratification. We recruited 112 HHCs of ATB patients and followed them for 6 years. Among the HHCs, only 2 developed ATB, while the remaining HHCs were classified into three groups: (1) HHC-1 group (n = 23): HHCs with consistently positive T-SPOT.TB test, negative chest radiograph, and no clinical symptoms or evidence of ATB during the 6-year follow-up period; (2) HHC-2 group (n = 15): HHCs with an initial positive T-SPOT result that later became negative without evidence of ATB; (3) HHC-3 group (n = 14): HHCs with a consistently negative T-SPOT.TB test and no clinical or radiological evidence of ATB. HHC-2 and HHC-3 were combined as HHC-23 group for analysis. RNA sequencing (RNA-seq) in PBMCs, with and without purified protein derivative (PPD) stimulation, identified significant differences in gene signatures between HHC-1 and HHC-23. Gene ontology analysis revealed functions related to bacterial pathogens, leukocyte chemotaxis, and inflammatory and cytokine responses. Modules associated with clinical features in the HHC-23 group were linked to the IL-17 signaling pathway, ferroptosis, complement and coagulation cascades, and the TNF signaling pathway. Validation using real-time PCR confirmed key genes like ATG-7, CXCL-3, and TNFRSF1B associated with infection outcomes in HHCs. Our research enhances understanding of disease mechanisms in HHCs. HHCs with persistent latent tuberculosis infection (HHC-1) showed significantly different gene expression compared to HHCs with no M. tuberculosis infection (HHC-23). These findings can help identify HHCs at risk of developing ATB and guide targeted public health interventions.

Expression of HLA-DR and KLRG1 enhances the cytotoxic potential and cytokine secretion capacity of CD3+ T cells in tuberculosis patients

BACKGROUND

Human T cells play an important role in immunity against tuberculosis (TB) infection. Activating receptor HLA-DR and inhibitory receptor KLRG1 are critical regulators of T cell function during viral infection and tumorigenesis, but they have been less studied in TB infection.

METHODS

In this study, we explored the relationship between CD3+ T cell expression of HLA-DR and KLRG1 receptors and function against TB infection. Flow cytometry was conducted to assess the immunomodulatory effects of HLA-DR and KLRG1 receptors on CD3+ T cells in patients with different TB infection status.

RESULTS

We found activating receptors HLA-DR, NKG2C, CD57 and NKP46, and inhibitory receptors KLRG1 and KIR on CD3+ T cells in different TB infection status showed different distribution patterns; the cytotoxic potential and cytokine secretion capacity of CD3+ T cells after Mtb-specific antigen stimulation were significantly enhanced in TB infection groups. Further studies revealed HLA-DR+ T and KLRG1+ T cells expressed higher activating and inhibitory receptors than the negative population. In addition, the expression of cytotoxic potential and cytokine secretion capacity of HLA-DR+ T and KLRG1+ T cells was significantly higher than that of HLA-DR- T and KLRG1- T cells.

CONCLUSIONS

Expression of HLA-DR and KLRG1 enhances the cytotoxic potential and cytokine secretion capacity of CD3+ T cells in TB patients, suggesting CD3+ T cells expressing HLA-DR and KLRG1 are important effector cell phenotypes involved in the host anti-TB infection. HLA-DR and KLRG1 expressed by CD3+ T cells may be potential predictive markers of TB disease progression and clinical immune assessment.

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.

The CD56-CD16+ NK cell subset in chronic infections

Long-term human diseases can shape the immune system, and natural killer (NK) cells have been documented to differentiate into distinct subsets specifically associated with chronic virus infections. One of these subsets found in large frequencies in HIV-1 are the CD56-CD16+ NK cells, and this population's association with chronic virus infections is the subject of this review. Human NK cells are classically defined by CD56 expression, yet increasing evidence supports the NK cell status of the CD56-CD16+ subset which we discuss herein. We then discuss the evidence linking CD56-CD16+ NK cells to chronic virus infections, and the potential immunological pathways that are altered by long-term infection that could be inducing the population's differentiation. An important aspect of NK cell regulation is their interaction with human leukocyte antigen (HLA) class-I molecules, and we highlight work that indicates both virus and genetic-mediated variations in HLA expression that have been linked to CD56-CD16+ NK cell frequencies. Finally, we offer a perspective on CD56-CD16+ NK cell function, taking into account recent work that implies the subset is comparable to CD56+CD16+ NK cell functionality in antibody-dependent cell cytotoxicity response, and the definition of CD56-CD16+ NK cell subpopulations with varying degranulation capacity against target cells.

Immune checkpoint modulating T cells and NK cells response to Mycobacterium tuberculosis infection

Many subversive mechanisms promote the occurrence and development of chronic infectious diseases and cancer, among which the down-regulated expression of immune-activating receptors and the enhanced expression of immune-inhibitory receptors accelerate the occurrence and progression of the disease. Recently, the use of immune checkpoint inhibitors has shown remarkable efficacy in the treatment of tumors in multiple organs. However, the expression of immune checkpoint molecules on natural killer (NK) cells by Mycobacterium tuberculosis (Mtb) infection and its impact on NK cell effector functions have been poorly studied. In this review, we focus on what is currently known about the expression of various immune checkpoints in NK cells following Mtb infection and how it alters NK cell-mediated host cytotoxicity and cytokine secretion. Unraveling the function of NK cells after the infection of host cells by Mtb is crucial for a comprehensive understanding of the innate immune mechanism of NK cells involved in tuberculosis and the evaluation of the efficacy of immunotherapies using immune checkpoint inhibitors to treat tuberculosis. In view of some similarities in the immune characteristics of T cells and NK cells, we reviewed the molecular mechanism of the interaction between T cells and Mtb, which can help us to further understand and explore the specific interaction mechanism between NK cells and Mtb.

Attenuated Cytokine-Induced Memory-Like Natural Killer Cell Responses to Mycobacterium tuberculosis in Tuberculosis Patients

Purpose

This study aimed to investigate the phenotype, proliferation and functional alterations of cytokine-induced memory-like natural killer (CIML NK) cells from healthy subjects and TB patients, and assessed the efficacy of CIML NK cells in response to H37Rv-infected U937 cells in vitro.

Methods

Fresh peripheral blood mononuclear cells (PBMCs) were isolated from healthy people and tuberculosis patients and activated for 16h using low-dose IL-15, or IL-12, IL-15, IL-18 combination or IL-12, IL-15, IL-18 and MTB H37Rv lysates, respectively, followed by low-dose IL-15 maintenance for another 7 days. Then, the PBMCs were co-cultured with K562 and H37Rv-infected U937, and the purified NK cells were co-cultured with H37Rv infected U937. The phenotype, proliferation and response function of CIML NK cells were assessed using flow cytometry. Finally, colony forming units were enumerated to confirm the survival of intracellular MTB.

Results

CIML NK phenotypes from TB patients were similar to healthy controls. CIML NK cells undergo higher rates of proliferation after IL-12/15/18 pre-activation. Moreover, the poor expansion potential of CIML NK cells co-stimulated with MTB lysates. CIML NK cells from healthy individuals showed enhanced IFN-γ functional to H37Rv infected U937 cells, along with significantly enhanced killing of H37Rv. However, the CIML NK cells from TB patients show attenuated IFN-γ production and now enhanced the ability of killing intracellular MTB compared to those from healthy donors after co-cultured with H37Rv infected U937.

Conclusion

CIML NK cells from healthy individuals exist the increased ability of IFN-γ secretion and boosted anti-MTB activity in vitro, which from TB patients show impaired IFN-γ production and no enhanced anti-MTB activity compared to those from healthy donors. Additionally, we observe the poor expansion potential of CIML NK cells co-stimulated with antigens from MTB. These results open up new possibilities for NK cell-based anti-tuberculosis immunotherapeutic strategies.

CD56-negative NK cells: Frequency in peripheral blood, expansion during HIV-1 infection, functional capacity, and KIR expression

Human NK cells are usually defined as CD3-CD56+ lymphocytes. However, a CD56-CD16+ (CD56neg) lymphocyte population that displays NK-associated markers expands during chronic viral infections such as HIV-1 and HCV, and, to lesser extent, in herpesvirus infections. This CD56neg NK cell subset has been understudied because it requires the exclusion of other lymphocytes to accurately identify its presence. Many questions remain regarding the origin, development, phenotype, and function of the CD56neg NK cell population. Our objective was to determine the frequency of this NK subset in healthy controls and its alteration in viral infections by performing a meta-analysis. In addition to this, we analyzed deposited CyTOF and scRNAseq datasets to define the phenotype and subsets of the CD56neg NK cell population, as well as their functional variation. We found in 757 individuals, from a combined 28 studies and 6 datasets, that the CD56neg subset constitutes 5.67% of NK cells in healthy peripheral blood, while HIV-1 infection increases this population by a mean difference of 10.69%. Meta-analysis of surface marker expression between NK subsets showed no evidence of increased exhaustion or decreased proliferation within the CD56neg subset. CD56neg NK cells have a distinctive pattern of KIR expression, implying they have a unique potential for KIR-mediated education. A perforin-CD94-NKG2C-NKp30- CD56neg population exhibited different gene expression and degranulation responses against K562 cells compared to other CD56neg cells. This analysis distinguishes two functionally distinct subsets of CD56neg NK cells. They are phenotypically diverse and have differing capacity for education by HLA class-I interactions with KIRs.