Infection of Monocytes From Tuberculosis Patients With Two Virulent Clinical Isolates of Mycobacterium tuberculosis Induces Alterations in Myeloid Effector Functions

Tobacco smoke exposure recruits inflammatory airspace monocytes that establish permissive lung niches for Mycobacterium tuberculosis

Tobacco smoking doubles the risk of active tuberculosis (TB) and accounts for up to 20% of all active TB cases globally. How smoking promotes lung microenvironments permissive to Mycobacterium tuberculosis (Mtb) growth remains incompletely understood. We investigated primary bronchoalveolar lavage cells from current and never smokers by performing single-cell RNA sequencing (scRNA-seq), flow cytometry, and functional assays. We observed the enrichment of immature inflammatory monocytes in the lungs of smokers compared with nonsmokers. These monocytes exhibited phenotypes consistent with recent recruitment from blood, ongoing differentiation, increased activation, and states similar to those with chronic obstructive pulmonary disease. Using integrative scRNA-seq and flow cytometry, we identified CD93 as a marker for a subset of these newly recruited smoking-associated lung monocytes and further provided evidence that the recruitment of monocytes into the lung was mediated by CCR2-binding chemokines, including CCL11. We also show that these cells exhibit elevated inflammatory responses upon exposure to Mtb and accelerated intracellular growth of Mtb compared with mature macrophages. This elevated Mtb growth could be inhibited by anti-inflammatory small molecules, providing a connection between smoking-induced pro-inflammatory states and permissiveness to Mtb growth. Our findings suggest a model in which smoking leads to the recruitment of immature inflammatory monocytes from the periphery to the lung, which results in the accumulation of these Mtb-permissive cells in the airway. This work defines how smoking may lead to increased susceptibility to Mtb and identifies host-directed therapies to reduce the burden of TB among those who smoke.

Type I interferons and Mycobacterium tuberculosis whole cell lysate induce distinct transcriptional responses in M. tuberculosis infection

Type I interferon (IFN)-induced genes have the potential for distinguishing active tuberculosis (ATB) from latent TB infection (LTBI) and healthy controls (HC), monitoring treatment, and detection of individuals at risk of progression to active disease. We examined the differential effects of IFN-α, IFN-β and Mycobacterium tuberculosis whole cell lysate (Mtb WCL) stimulation on the expression of selected IFN-stimulated genes in peripheral blood mononuclear cells from individuals with either LTBI, ATB, and healthy controls. Stimulation with IFN-α and IFN-β induced a higher expression of the interrogated genes while Mtb WCL stimulation induced expression similar to that observed at baseline, with the exception of IL-1A and IL-1B genes that were downregulated. The expression of IFN-α-induced FCGR1A gene, IFN-β-induced FCGR1A, FCGR1B, and SOCS3 genes, and Mtb WCL-induced IFI44, IFI44L, IFIT1, and IFITM3 genes differed significantly between LTBI and ATB. These findings suggest stimulation-driven gene expression patterns could potentially discriminate LTBI and ATB. Mechanistic studies are necessary to define the processes through which distinct type I IFNs and downstream ISGs determine infection outcomes and identify potential host-directed therapeutic strategies.

Differential gene expression analysis combined with molecular dynamics simulation study to elucidate the novel potential biomarker involved in pulmonary TB

Tuberculosis (TB) is a lethal multisystem disease that attacks the lungs' first line of defense. A substantial threat to public health and a primary cause of death is pulmonary TB. This study aimed to identify and investigate the probable differentially expressed genes (DEGs) primarily involved in Pulmonary TB. Accordingly, three independent gene expression data sets, numbered GSE139825, GSE139871, and GSE54992, were utilized for this purpose. The identified DEGs were used for bioinformatics-based analysis, including physical gene interaction, Gene Ontology (GO), network analysis and pathway studies using the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG). The computational analysis predicted that TNFAIP6 is the significant DEG in the gene expression profiling of TB datasets. According to gene ontology analysis, TNFAIP6 is also essential in injury and inflammation. Further, TNFA1P6 is strongly linked to arsenic poisoning, evident from the results of NetworkAnalyst, a comprehensive and interactive platform for gene expression profiling via network visual analytics. As a result, the TNFAIP6 gene was ultimately chosen as a candidate DEG and subsequently employed for in silico structural characterization studies. The tertiary structure of TNFAIP6 was modelled using the ROBETTA server, followed by validation with SAVES and ProSA webserver. Additionally, structural dynamic studies, including molecular dynamics simulation (MDS) and essential dynamics analysis, including principal component (PC) based free energy landscape (FEL) analysis, was used for checking the stability of TNFAIP6 models. The dynamics result established the structural rigidity of modelled TNFAIP6 through RMSD, RMSF and RoG results. The FEL analysis revealed the restricted conformational flexibility of TNFAIP6 by displaying a single minimum energy basin in the contour plot. The comprehensive computational analysis established that TNFAIP6 could serve as a viable biomarker to assess the severity of pulmonary TB.

Latent Tuberculosis Patients Have an Increased Frequency of IFN-γ-Producing CD5+ B Cells, Which Respond Efficiently to Mycobacterial Proteins

Tuberculosis (TB) remains a public health problem worldwide and is one of the deadliest infectious diseases, only after the current COVID-19 pandemic. Despite significant advances in the TB field, there needs to be more immune response comprehension; for instance, the role played by humoral immunity is still controversial. This study aimed to identify the frequency and function of B1 and immature/transitional B cells in patients with active and latent TB (ATB and LTB, respectively). Here we show that LTB patients have an increased frequency of CD5+ B cells and decreased CD10+ B cells. Furthermore, LTB patients stimulated with mycobacteria's antigens increase the frequency of IFN-γ-producing B cells, whereas cells from ATB do not respond. Moreover, under the mycobacterial protein stimulus, LTB promotes a pro-inflammatory environment characterized by a high level of IFN-γ but also can produce IL-10. Regarding the ATB group, they cannot produce IFN-γ, and mycobacterial lipids and proteins stimulate only the IL-10 production. Finally, our data showed that in ATB, but not in LTB, B cell subsets correlate with clinical and laboratory parameters, suggesting that these CD5+ and CD10+ B cell subpopulations have the potential to be biomarkers to differentiate between LTB and ATB. In conclusion, LTB has increased CD5+ B cells, and these cells can maintain a rich microenvironment of IFN-γ, IL-10, and IL-4. In contrast, ATB only maintains an anti-inflammatory environment when stimulated with mycobacterial proteins or lipids.

Latent tuberculosis and computational biology: A less-talked affair

Tuberculosis (TB) is a pervasive and devastating air-borne disease caused by the organisms belonging to the Mycobacterium tuberculosis (Mtb) complex. Currently, it is the global leader in infectious disease-related death in adults. The proclivity of TB to enter the latent state has become a significant impediment to the global effort to eradicate TB. Despite decades of research, latent tuberculosis (LTB) mechanisms remain poorly understood, making it difficult to develop efficient treatment methods. In this review, we seek to shed light on the current understanding of the mechanism of LTB, with an accentuation on the insights gained through computational biology. We have outlined various well-established computational biology components, such as omics, network-based techniques, mathematical modelling, artificial intelligence, and molecular docking, to disclose the crucial facets of LTB. Additionally, we highlighted important tools and software that may be used to conduct a variety of systems biology assessments. Finally, we conclude the article by addressing the possible future directions in this field, which might help a better understanding of LTB progression.

Neutrophil-Lymphocyte Ratio and Monocyte-Lymphocyte Ratio According to the Radiologic Severity of Mycobacterium avium Complex Pulmonary Disease

BACKGROUND

To date, no study has investigated whether the neutrophil-lymphocyte ratio (NLR) and monocyte-lymphocyte ratio (MLR) have a clinical value in Mycobacterium avium complex (MAC)-pulmonary disease (PD).

METHODS

We aimed to assess whether the baseline NLR and MLR were different according to the severity of MAC-PD based on the radiologic classification by retrospectively analyzing 549 patients treated in a tertiary referral center in South Korea.

RESULTS

Both NLR and MLR were significantly higher as 3.33 and 0.43 respectively in the fibrocavitary type, followed by 2.34 and 0.27 in the cavitary nodular bronchiectatic type and significantly lower as 1.88 and 0.23 in the non-cavitary nodular bronchiectatic type.

CONCLUSION

The baseline NLR and MLR showed a distinct difference in accordance with the radiologic severity of MAC-PD.

Dual RNA Sequencing of Mycobacterium tuberculosis-Infected Human Splenic Macrophages Reveals a Strain-Dependent Host-Pathogen Response to Infection

Tuberculosis (TB) is caused by Mycobacterium tuberculosis (Mtb), leading to pulmonary and extrapulmonary TB, whereby Mtb is disseminated to many other organs and tissues. Dissemination occurs early during the disease, and bacteria can be found first in the lymph nodes adjacent to the lungs and then later in the extrapulmonary organs, including the spleen. The early global gene expression response of human tissue macrophages and intracellular clinical isolates of Mtb has been poorly studied. Using dual RNA-seq, we have explored the mRNA profiles of two closely related clinical strains of the Latin American and Mediterranean (LAM) family of Mtb in infected human splenic macrophages (hSMs). This work shows that these pathogens mediate a distinct host response despite their genetic similarity. Using a genome-scale host–pathogen metabolic reconstruction to analyze the data further, we highlight that the infecting Mtb strain also determines the metabolic response of both the host and pathogen. Thus, macrophage ontogeny and the genetic-derived program of Mtb direct the host–pathogen interaction.

Is Mycobacterium tuberculosis carcinogenic to humans?

We highlight the ability of the tuberculosis (TB) causing bacterial pathogen, Mycobacterium tuberculosis (Mtb), to induce key characteristics that are associated with established IARC classified Group 1 and Group 2A carcinogenic agents. There is sufficient evidence from epidemiological case-control, cohort and meta-analysis studies of increased lung cancer (LC) risk in pre-existing/active/old TB cases. Similar to carcinogens and other pathogenic infectious agents, exposure to aerosol-containing Mtb sprays in mice produce malignant transformation of cells that result in squamous cell carcinoma. Convincing, mechanistic data show several characteristics shared between TB and LC which include chronic inflammation, genomic instability and replicative immortality, just to name a few cancer hallmarks. These hallmarks of cancer may serve as precursors to malignant transformation. Together, these findings form the basis of our postulate that Mtb is a complete human pulmonary carcinogen. We also discuss how Mtb may act as both an initiating agent and promoter of tumor growth. Forthcoming experimental studies will not only serve as proof-of-concept but will also pivot our understanding of how to manage/treat TB cases as well as offer solutions to clinical conundrums of TB lesions masquerading as tumors. Clinical validation of our concept may also help pave the way for next generation personalized medicine for the management of pulmonary TB/cancer particularly for cases that are not responding well to conventional chemotherapy or TB drugs.