Whole transcriptome sequencing reveals neutrophils’ transcriptional landscape associated with active tuberculosis

Whole blood transcriptional profiles and the pathogenesis of tuberculous meningitis

Mortality and morbidity from tuberculous meningitis (TBM) are common, primarily due to inflammatory response to Mycobacterium tuberculosis infection, yet the underlying mechanisms remain poorly understood. We aimed to uncover genes and pathways associated with TBM pathogenesis and mortality, and determine the best predictors of death, utilizing whole-blood RNA sequencing from 281 Vietnamese adults with TBM, 295 pulmonary tuberculosis (PTB), and 30 healthy controls. Through weighted gene co-expression network analysis, we identified hub genes and pathways linked to TBM severity and mortality, with a consensus analysis revealing distinct patterns between HIV-positive and HIV-negative individuals. We employed multivariate elastic-net Cox regression to select candidate predictors of death, then logistic regression and internal bootstrap validation to choose best predictors. Increased neutrophil activation and decreased T and B cell activation pathways were associated with TBM mortality. Among HIV-positive individuals, mortality associated with increased angiogenesis, while HIV-negative individuals exhibited elevated TNF signaling and impaired extracellular matrix organization. Four hub genes-MCEMP1, NELL2, ZNF354C, and CD4-were strong TBM mortality predictors. These findings indicate that TBM induces a systemic inflammatory response similar to PTB, highlighting critical genes and pathways related to death, offering insights for potential therapeutic targets alongside a novel four-gene biomarker for predicting outcomes.

Single-cell transcriptomics of blood identified IFIT1+ neutrophil subcluster expansion in NTM-PD patients

OBJECTIVE

Non-tuberculous mycobacterial pulmonary disease (NTM-PD) is caused by an imbalance between pathogens and impaired host immune responses. Mycobacterium avium complex (MAC) and Mycobacterium abscessus (MAB) are the two major pathogens that cause NTM-PD. In this study, we sought to dissect the transcriptomes of peripheral blood immune cells at the single-cell resolution in NTM-PD patients and explore potential clinical markers for NTM-PD diagnosis and treatment.

METHODS

Peripheral blood samples were collected from six NTM-PD patients, including three MAB-PD patients, three MAC-PD patients, and two healthy controls. We employed single-cell RNA sequencing (scRNA-seq) to define the transcriptomic landscape at a single-cell resolution. A comprehensive scRNA-seq analysis was performed, and flow cytometry was conducted to validate the results of scRNA-seq.

RESULTS

A total of 27,898 cells were analyzed. Nine T-cells, six mononuclear phagocytes (MPs), and four neutrophil subclusters were defined. During NTM infection, naïve T-cells were reduced, and effector T-cells increased. High cytotoxic activities were shown in T-cells of NTM-PD patients. The proportion of inflammatory and activated MPs subclusters was enriched in NTM-PD patients. Among neutrophil subclusters, an IFIT1+ neutrophil subcluster was expanded in NTM-PD compared to healthy controls. This suggests that IFIT1+ neutrophil subcluster might play an important role in host defense against NTM. Functional enrichment analysis of this subcluster suggested that it is related to interferon response. Cell-cell interaction analysis revealed enhanced CXCL8-CXCR1/2 interactions between the IFIT1+ neutrophil subcluster and NK cells, NKT cells, classical mononuclear phagocytes subcluster 1 (classical Mo1), classical mononuclear phagocytes subcluster 2 (classical Mo2) in NTM-PD patients compared to healthy controls.

CONCLUSIONS

Our data revealed disease-specific immune cell subclusters and provided potential new targets of NTM-PD. Specific expansion of IFIT1+ neutrophil subclusters and the CXCL8-CXCR1/2 axis may be involved in the pathogenesis of NTM-PD. These insights may have implications for the diagnosis and treatment of NTM-PD.

Advances in understanding immune homeostasis in latent tuberculosis infection

Nearly one-fourth of the global population is infected by Mycobacterium tuberculosis (Mtb), and approximately 90%-95% remain asymptomatic as latent tuberculosis infection (LTBI), an estimated 5%-10% of those with latent infections will eventually progress to active tuberculosis (ATB). Although it is widely accepted that LTBI transitioning to ATB results from a disruption of host immune balance and a weakening of protective immune responses, the exact underlying immunological mechanisms that promote this conversion are not well characterized. Thus, it is difficult to accurately predict tuberculosis (TB) progression in advance, leaving the LTBI population as a significant threat to TB prevention and control. This article systematically explores three aspects related to the immunoregulatory mechanisms and translational research about LTBI: (1) the distinct immunocytological characteristics of LTBI and ATB, (2) LTBI diagnostic markers discovery related to host anti-TB immunity and metabolic pathways, and (3) vaccine development focus on LTBI. This article is categorized under: Infectious Diseases > Molecular and Cellular Physiology Infectious Diseases > Genetics/Genomics/Epigenetics Immune System Diseases > Genetics/Genomics/Epigenetics.

Cost-Effective Whole Transcriptome Sequencing Landscape and Diagnostic Potential Biomarkers in Active Tuberculosis

Tuberculosis (TB) is a prevalent and severe infectious disease that poses a significant threat to human health. However, it is frequently disregarded as there are not enough quick and accurate ways to diagnose tuberculosis. Here, we develop a strategy for tuberculosis detection to address the challenges, including an experimental strategy, namely, Double Adapter Directional Capture sequencing (DADCSeq), an easily operated and low-cost whole transcriptome sequencing method, and a computational method to identify hub differentially expressed genes as well as the diagnosis of TB based on whole transcriptome data using DADCSeq on peripheral blood mononuclear cells (PBMCs) from active TB and latent TB or healthy control. Applying our approach to create a robust and stable TB multi-mRNA risk probability model (TBMMRP) that can accurately distinguish active and latent TB patients, including active TB and healthy controls in clinical cohorts, this diagnostic biomarker was successfully validated by several independent cross-platform cohorts with favorable performance in differentiating active TB from latent TB or active TB from healthy controls and further demonstrated superior or similar diagnostic accuracy compared to previous diagnostic markers. Overall, we develop a low-cost and effective strategy for tuberculosis diagnosis; as the clinical cohort increases, we can expand to different disease kinds and learn new features through our disease diagnosis strategy.

Microbiome Alteration in Lung Tissues of Tuberculosis Patients Revealed by Metagenomic Next-Generation Sequencing and Immune-Related Transcriptional Profile Identified by Transcriptome Sequencing

This study explored alterations in the respiratory microbiome and transcriptome after Mycobacterium tuberculosis infection in tuberculosis (TB) patients. Metagenomic next-generation sequencing (mNGS) was adopted to reveal the microbiome in lung tissues from 110 TB and 25 nontuberculous (NonTB) patients. Transcriptome sequencing was performed in TB tissues (n = 3), tissues adjacent to TB (ParaTB, n = 3), and NonTB tissues (n = 3) to analyze differentially expressed genes (DEGs) and functional pathways. The microbial β diversity (p = 0.01325) in TB patients differed from that in the NonTB group, with 17 microbial species distinctively distributed. Eighty-three co-up-regulated DEGs were identified in the TB versus NonTB and the TB versus ParaTB comparison groups, and six were associated with immune response to Mtb. These DEGs were significantly enriched in the signaling pathways such as immune response, NF-κB, and B cell receptor. Data in the lung tissue microbiome and transcriptome in TB patients offer a sufficient understanding of the pathogenesis of TB.

Necrosis, netosis, and apoptosis in pulmonary tuberculosis and type-2 diabetes mellitus. Clues from the patient's serum

Pulmonary tuberculosis (PTB) and type 2 diabetes mellitus (T2DM) are two inflammatory diseases whose pathology involves neutrophils (NEU) as key participants. Countless inflammatory elements produced at the lesion sites leak into the blood and are distributed systemically. The study aimed to investigate the effect of the serum of patients with PTB, T2DM, and PTB + T2DM on the cellular and nuclear morphology of healthy NEU. Monolayers of NEU were prepared and incubated with sera from PTB (n꓿ 10), T2DM (n꓿10), PTB + T2DM (n꓿ 10) patients, or sera from healthy people (n = 10). Monolayers were stained for histones, elastase, and myeloperoxidase for NETosis, annexin V for apoptosis, and Iris fuchsia for necrosis. Hoechst stain (DNA) was used to identify the nuclear alterations. Necrosis was the predominant alteration. Sera from PTB + T2DM were the most potent change inducers. Normal sera did not induce cell alterations. The blood of TBP and T2DM patients carries a myriad of abnormal elements that induce necrosis of NEU in normal people, thus reflecting what might occur in the neutrophils of the patients themselves. These findings reinforce the participation of NEU in the pathology of these diseases. Necrosis is expected to be the most frequent neutrophil-induced alteration in tuberculosis and diabetes mellitus.

Effect of Lacking ZKSCAN3 on Autophagy, Lysosomal Biogenesis and Senescence

Transcription factors can affect autophagy activity by promoting or inhibiting the expression of autophagic and lysosomal genes. As a member of the zinc finger family DNA-binding proteins, ZKSCAN3 has been reported to function as a transcriptional repressor of autophagy, silencing of which can induce autophagy and promote lysosomal biogenesis in cancer cells. However, studies in Zkscan3 knockout mice showed that the deficiency of ZKSCAN3 did not induce autophagy or increase lysosomal biogenesis. In order to further explore the role of ZKSCAN3 in the transcriptional regulation of autophagic genes in human cancer and non-cancer cells, we generated ZKSCAN3 knockout HK-2 (non-cancer) and Hela (cancer) cells via the CRISPR/Cas9 system and analyzed the differences in gene expression between ZKSCAN3 deleted cells and non-deleted cells through fluorescence quantitative PCR, western blot and transcriptome sequencing, with special attention to the differences in expression of autophagic and lysosomal genes. We found that ZKSCAN3 may be a cancer-related gene involved in cancer progression, but not an essential transcriptional repressor of autophagic or lysosomal genes, as the lacking of ZKSCAN3 cannot significantly promote the expression of autophagic and lysosomal genes.

Study of the shared gene signatures of polyarticular juvenile idiopathic arthritis and autoimmune uveitis

Objective

To explore the shared gene signatures and potential molecular mechanisms of polyarticular juvenile idiopathic arthritis (pJIA) and autoimmune uveitis (AU).

Method

The microarray data of pJIA and AU from the Gene Expression Omnibus (GEO) database were downloaded and analyzed. The GEO2R tool was used to identify the shared differentially expressed genes (DEGs) and genes of extracellular proteins were identified among them. Then, weighted gene co-expression network analysis (WGCNA) was used to identify the shared immune-related genes (IRGs) related to pJIA and AU. Moreover, the shared transcription factors (TFs) and microRNAs (miRNAs) in pJIA and AU were acquired by comparing data from HumanTFDB, hTFtarget, GTRD, HMDD, and miRTarBase. Finally, Metascape and g: Profiler were used to carry out function enrichment analyses of previously identified gene sets.

Results

We found 40 up-regulated and 15 down-regulated shared DEGs via GEO2R. Then 24 shared IRGs in positivity-related modules, and 18 shared IRGs in negatively-related modules were found after WGCNA. After that, 3 shared TFs (ARID1A, SMARCC2, SON) were screened. And the constructed TFs-shared DEGs network indicates a central role of ARID1A. Furthermore, hsa-miR-146 was found important in both diseases. The gene sets enrichment analyses suggested up-regulated shared DEGs, TFs targeted shared DEGs, and IRGs positivity-correlated with both diseases mainly enriched in neutrophil degranulation process, IL-4, IL-13, and cytokine signaling pathways. The IRGs negatively correlated with pJIA and AU mainly influence functions of the natural killer cell, cytotoxicity, and glomerular mesangial cell proliferation. The down-regulated shared DEGs and TFs targeted shared DEGs did not show particular functional enrichment.

Conclusion

Our study fully demonstrated the flexibility and complexity of the immune system disorders involved in pJIA and AU. Neutrophil degranulation may be considered the shared pathogenic mechanism, and the roles of ARID1A and MiR-146a are worthy of further in-depth study. Other than that, the importance of periodic inspection of kidney function is also noteworthy.