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

Albayrak, Nurhan; Dirix, Violette; Aerts, Laetitia; Praet, Anne Van; Godefroid, Audrey; Dauby, Nicolás; Windey, Patricia; Muylle, Inge; Mascart, Françoise; Corbière, Véronique

doi:10.1002/jlb.4a1020-641rr

Cited by 7 publications

(6 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The amount of NK cells was also found to be remarkedly decreased after 7 day-stimulation with MTB antigens. 42 Our results also showed that MTB lysates impaired the proliferative capacity of NK cells, most likely due to virulence factors released after the destruction of bacterial cells. 52 This effect is reminiscent of a previous study demonstrating that cytomegalovirus infection has the potential to shape the NK cell repertoire, thus resulting in the selective expansion or inhibition of specific NK cell subsets.…”

Section: Discussionsupporting

confidence: 55%

See 1 more Smart Citation

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

Chen¹,

Li²,

Yuan³

et al. 2023

IDR

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionsupporting

confidence: 55%

“…[37][38][39] The CD57 + phenotypes of tuberculosis patients in different states of the disease are also divergent. [40][41][42] This may be the reason for the huge heterogeneity in CD57 + phenotype among TB group in our study.…”

Section: Discussionmentioning

confidence: 73%

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

Chen¹,

Li²,

Yuan³

et al. 2023

IDR

View full text Add to dashboard Cite

show abstract

“…NK cells are essential components of the innate immune response and play a crucial defensive role in the early stages of MTB invasion [ 50 ]. NK cells are primarily derived from bone marrow and can secrete various cytokines, among which interferon-γ (IFN-γ) is one of the most important.…”

Section: Immunological Mechanisms Of Ltbimentioning

confidence: 99%

“…Moreover, there are differences in the phenotypes of NK cells among ATB patients, individuals with LTBI, and healthy controls. Recently, Albayrak et al [ 50 ] classified NK cells found in the blood into three types based on their phenotypes, including CD56 bright , CD56 dim , and CD56 neg NK cells. They found that the ratio of total NK cells and CD56 neg NK cells was lower in individuals with ATB than in those with LTBI.…”

Section: Immunological Mechanisms Of Ltbimentioning

confidence: 99%

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

Li,

Yang,

Zhuang

et al. 2023

Military Med Res

View full text Add to dashboard Cite

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.

show abstract

“…In recent years, several genome-wide transcriptomic studies have been conducted to identify variations in host gene expression profiles in relation to different states of M. tuberculosis infection [ 10–12 ]. However, while most studies have primarily focused on discerning differences between patients with active TB and individuals with LTBI [ 10 , 13 ], little is known about the diverse host responses among household contacts (HHCs). Thus, the objective of this study was to conduct a prospective investigation in mainland China, aiming to evaluate transcriptome signatures in human peripheral blood mononuclear cells (PBMCs) of HHCs with distinct clinical outcomes.…”

Section: Introductionmentioning

confidence: 99%

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

Qi,

Yang,

Cai

et al. 2023

Emerging Microbes & Infections

View full text Add to dashboard Cite

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.

show abstract

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

Cited by 7 publications

References 30 publications

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

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

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

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

Contact Info

Product

Resources

About