Genome-wide transcriptional profiling identifies potential signatures in discriminating active tuberculosis from latent infection

Transcriptomics-based anti-tuberculous mechanism of traditional Chinese polyherbal preparation NiuBeiXiaoHe intermediates

Background

Integrated traditional Chinese medicine and biomedicine is an effective method to treat tuberculosis (TB). In our previous research, traditional Chinese medicine preparation NiuBeiXiaoHe (NBXH) achieved obvious anti-TB effects in animal experiments and clinical practice. However, the action mechanism of NBXH has not been elucidated.

Method

Peripheral blood mononuclear cells (PBMCs) were collected to extract mRNA and differentially expressed (DE) genes were obtained using gene microarray technology. Finally, GEO databases and RT-qPCR were used to verify the results of expression profile.

Result

After MTB infection, most upregulated DE genes in mice were immune-related genes, including cxcl9, camp, cfb, c4b, serpina3g, and ngp. Downregulated DE genes included lrrc74b, sult1d1, cxxc4, and grip2. After treatment with NBXH, especially high-dose NBXH, the abnormal gene expression was significantly corrected. Some DE genes have been confirmed in multiple GEO datasets or in pulmonary TB patients through RT-qPCR.

Conclusion

MTB infection led to extensive changes in host gene expression and mainly caused the host's anti-TB immune responses. The treatment using high-dose NBXH partially repaired the abnormal gene expression, further enhanced the anti-TB immunity included autophagy and NK cell-mediated cytotoxicity, and had a certain inhibitory effect on overactivated immune responses.

Toll-Like Receptor Genes and Risk of Latent Tuberculosis Infection in People Infected with HIV-1

The purpose of this study was to determine the contribution of genetic factors, i.e., the level of expression and polymorphisms of Toll-like receptors (TLR), to the susceptibility of latent tuberculosis infection in a Russian cohort of individuals infected with HIV. The patients (n = 317) with confirmed HIV infection were divided into two groups according to the results of the STANDARD E TB-Feron test: 63 cases with a latent TB infection and 274 controls without LTBI. Total DNA and RNA were isolated from whole-blood samples. SNP genotyping and expression levels of five TLR genes (TLR1, TLR2, TLR4, TLR6, and TLR8) were determined by means of real-time PCR. There were no significant differences in the expression levels of the TLRs between the case and control groups. In addition, we did not observe any significant association between the analyzed SNPs and the susceptibility of Latent tuberculosis infection (LTBI) in patients with HIV. However, patients from an entire cohort with the rs4986790-GG (TLR4) and rs5743708-GG (TLR2) genotypes were characterized by lower CD4 T-cell counts compared to carriers of alternative alleles. Moreover, we found a significant risk of a hazardous drop in the CD4 T-cell count below 350 cells/mm3 associated with the rs4986790-G (TLR4) allele. Latent tuberculosis infection in individuals infected with HIV does not significantly modify the level of TLR gene expression.

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.

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.

Diagnosis of pulmonary tuberculosis via identification of core genes and pathways utilizing blood transcriptional signatures: a multicohort analysis

Background

Blood transcriptomics can be used for confirmation of tuberculosis diagnosis or sputumless triage, and a comparison of their practical diagnostic accuracy is needed to assess their usefulness. In this study, we investigated potential biomarkers to improve our understanding of the pathogenesis of active pulmonary tuberculosis (PTB) using bioinformatics methods.

Methods

Differentially expressed genes (DEGs) were analyzed between PTB and healthy controls (HCs) based on two microarray datasets. Pathways and functional annotation of DEGs were identified and ten hub genes were selected. They were further analyzed and selected, then verified with an independent sample set. Finally, their diagnostic power was further evaluated between PTB and HCs or other diseases.

Results

62 DEGs mostly related to type I IFN pathway, IFN-γ-mediated pathway, etc. in GO term and immune process, and especially RIG-I-like receptor pathway were acquired. Among them, OAS1, IFIT1 and IFIT3 were upregulated and were the main risk factors for predicting PTB, with adjusted risk ratios of 1.36, 3.10, and 1.32, respectively. These results further verified that peripheral blood mRNA expression levels of OAS1, IFIT1 and IFIT3 were significantly higher in PTB patients than HCs (all P < 0.01). The performance of a combination of these three genes (three-gene set) had exceeded that of all pairwise combinations of them in discriminating TB from HCs, with mean AUC reaching as high as 0.975 with a sensitivity of 94.4% and a specificity of 100%. The good discernibility capacity was evaluated d via 7 independent datasets with an AUC of 0.902, as well as mean sensitivity of 87.9% and mean specificity of 90.2%. In regards to discriminating PTB from other diseases (i.e., initially considered to be possible TB, but rejected in differential diagnosis), the three-gene set equally exhibited an overall strong ability to separate PTB from other diseases with an AUC of 0.999 (sensitivity: 99.0%; specificity: 100%) in the training set, and 0.974 with a sensitivity of 96.4% and a specificity of 98.6% in the test set.

Conclusion

The described commonalities and unique signatures in the blood profiles of PTB and the other control samples have considerable implications for PTB biosignature design and future diagnosis, and provide insights into the biological processes underlying PTB.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02035-4.

Tuberculous Granuloma: Emerging Insights From Proteomics and Metabolomics

Mycobacterium tuberculosis infection, which claims hundreds of thousands of lives each year, is typically characterized by the formation of tuberculous granulomas — the histopathological hallmark of tuberculosis (TB). Our knowledge of granulomas, which comprise a biologically diverse body of pro- and anti-inflammatory cells from the host immune responses, is based mainly upon examination of lungs, in both human and animal studies, but little on their counterparts from other organs of the TB patient such as the brain. The biological heterogeneity of TB granulomas has led to their diverse, relatively uncoordinated, categorization, which is summarized here. However, there is a pressing need to elucidate more fully the phenotype of the granulomas from infected patients. Newly emerging studies at the protein (proteomics) and metabolite (metabolomics) levels have the potential to achieve this. In this review we summarize the diverse nature of TB granulomas based upon the literature, and amplify these accounts by reporting on the relatively few, emerging proteomics and metabolomics studies on TB granulomas. Metabolites (for example, trimethylamine-oxide) and proteins (such as the peptide PKAp) associated with TB granulomas, and knowledge of their localizations, help us to understand the resultant phenotype. Nevertheless, more multidisciplinary ‘omics studies, especially in human subjects, are required to contribute toward ushering in a new era of understanding of TB granulomas – both at the site of infection, and on a systemic level.

Differential Diagnosis of Latent Tuberculosis Infection and Active Tuberculosis: A Key to a Successful Tuberculosis Control Strategy

As an ancient infectious disease, tuberculosis (TB) is still the leading cause of death from a single infectious agent worldwide. Latent TB infection (LTBI) has been recognized as the largest source of new TB cases and is one of the biggest obstacles to achieving the aim of the End TB Strategy. The latest data indicate that a considerable percentage of the population with LTBI and the lack of differential diagnosis between LTBI and active TB (aTB) may be potential reasons for the high TB morbidity and mortality in countries with high TB burdens. The tuberculin skin test (TST) has been used to diagnose TB for > 100 years, but it fails to distinguish patients with LTBI from those with aTB and people who have received Bacillus Calmette–Guérin vaccination. To overcome the limitations of TST, several new skin tests and interferon-gamma release assays have been developed, such as the Diaskintest, C-Tb skin test, EC-Test, and T-cell spot of the TB assay, QuantiFERON-TB Gold In-Tube, QuantiFERON-TB Gold-Plus, LIAISON QuantiFERON-TB Gold Plus test, and LIOFeron TB/LTBI. However, these methods cannot distinguish LTBI from aTB. To investigate the reasons why all these methods cannot distinguish LTBI from aTB, we have explained the concept and definition of LTBI and expounded on the immunological mechanism of LTBI in this review. In addition, we have outlined the research status, future directions, and challenges of LTBI differential diagnosis, including novel biomarkers derived from Mycobacterium tuberculosis and hosts, new models and algorithms, omics technologies, and microbiota.

Up-regulated long noncoding RNA AC007128.1 and its genetic polymorphisms associated with Tuberculosis susceptibility

Background

Tuberculosis (TB) remains a major public health problem. Long non-coding RNAs (lncRNAs) are important regulators of gene expression. In this study, we explored the association between the expression of lncRNA AC007128.1 and TB susceptibility.

Methods

Three single-nucleotide polymorphisms (SNPs) (rs12333784, rs6463794, and rs720964) of lncRNA AC007128.1 were selected using the 1000 Genomes Project database and offline software Haploview V4.2, and were genotyped by a customized 2×48-Plex SNPscan™ Kit.

Results

We identified two differentially expressed lncRNA including AC007128.1 and AP001065.3 in comparisons of expression profiles between ATB vs. LTBI, LTBI vs. HCs, and AC700128.1 expression was specifically and significantly up-regulated in TB patients by verification of external data. Gene Ontology functional enrichment analysis and co-expression network showed up-regulated mRNA was mainly involved in negative regulation of the G protein-coupled receptor (GPCR) signaling pathway, and FPR1 and CYP27B1 were involved in the co-expression of AC007128.1. Using the 1000 Genomes Project, software Haploview V4.2, and SNP genotype, we screened out SNP rs12333784 which locus at 7p21.3 in AC007128.1 associated with TB susceptibility. The G carrier of rs12333784 was then finally verified to be significantly associated with pulmonary TB (PTB) and extrapulmonary tuberculosis (EPTB) susceptibility (pBonferroni =0.03878), and a similar but more significant effect was observed under the dominant model analysis (pBonferroni =0.013, OR =1.349, 95% CI, 1.065–1.709). In addition, the GG + GA genotype of SNP rs12333784 was significantly correlated with higher glucose (GLU) (P=0.03), higher gamma-glutamyl transferase (GGT) (P=0.05), and higher erythrocyte sedimentation rate (ESR) (P=0.05).

Conclusions

Our findings show lncRNA AC007128.1 can be regarded as biomarkers discriminating between ATB and LTBI and may also be a diagnostic biomarker for LBTI. These findings may aid clinical decision making in the management of TB.

Addressing Latent Tuberculosis: New Advances in Mimicking the Disease, Discovering Key Targets, and Designing Hit Compounds

Despite being discovered and isolated more than one hundred years ago, tuberculosis (TB) remains a global public health concern arch. Our inability to eradicate this bacillus is strongly related with the growing resistance, low compliance to current drugs, and the capacity of the bacteria to coexist in a state of asymptomatic latency. This last state can be sustained for years or even decades, waiting for a breach in the immune system to become active again. Furthermore, most current therapies are not efficacious against this state, failing to completely clear the infection. Over the years, a series of experimental methods have been developed to mimic the latent state, currently used in drug discovery, both in vitro and in vivo. Most of these methods focus in one specific latency inducing factor, with only a few taking into consideration the complexity of the granuloma and the genomic and proteomic consequences of each physiological factor. A series of targets specifically involved in latency have been studied over the years with promising scaffolds being discovered and explored. Taking in account that solving the latency problem is one of the keys to eradicate the disease, herein we compile current therapies and diagnosis techniques, methods to mimic latency and new targets and compounds in the pipeline of drug discovery.

Performance of diagnostic and predictive host blood transcriptomic signatures for Tuberculosis disease: A systematic review and meta-analysis

INTRODUCTION

Host blood transcriptomic biomarkers have potential as rapid point-of-care triage, diagnostic, and predictive tests for Tuberculosis disease. We aimed to summarise the performance of host blood transcriptomic signatures for diagnosis of and prediction of progression to Tuberculosis disease; and compare their performance to the recommended World Health Organisation target product profile.

METHODS

A systematic review and meta-analysis of the performance of host blood mRNA signatures for diagnosing and predicting progression to Tuberculosis disease in HIV-negative adults and adolescents, in studies with an independent validation cohort. Medline, Scopus, Web of Science, and EBSCO libraries were searched for articles published between January 2005 and May 2019, complemented by a search of bibliographies. Study selection, data extraction and quality assessment were done independently by two reviewers. Meta-analysis was performed for signatures that were validated in ≥3 comparable cohorts, using a bivariate random effects model.

RESULTS

Twenty studies evaluating 25 signatures for diagnosis of or prediction of progression to TB disease in a total of 68 cohorts were included. Eighteen studies evaluated 24 signatures for TB diagnosis and 17 signatures met at least one TPP minimum performance criterion. Three diagnostic signatures were validated in clinically relevant cohorts to differentiate TB from other diseases, with pooled sensitivity 84%, 87% and 90% and pooled specificity 79%, 88% and 74%, respectively. Four studies evaluated signatures for progression to TB disease and performance of one signature, assessed within six months of TB diagnosis, met the minimal TPP for a predictive test for progression to TB disease.

CONCLUSION

Host blood mRNA signatures hold promise as triage tests for TB. Further optimisation is needed if mRNA signatures are to be used as standalone diagnostic or predictive tests for therapeutic decision-making.

Serum proteomics of active tuberculosis patients and contacts reveals unique processes activated during Mycobacterium tuberculosis infection

Tuberculosis (TB) is the most lethal infection among infectious diseases. The specific aim of this study was to establish panels of serum protein biomarkers representative of active TB patients and their household contacts who were either infected (LTBI) or uninfected (EMI-TB Discovery Cohort, Pontevedra Region, Spain). A TMT (Tamdem mass tags) 10plex-based quantitative proteomics study was performed in quintuplicate containing a total of 15 individual serum samples per group. Peptides were analyzed in an LC-Orbitrap Elite platform, and raw data were processed using Proteome Discoverer 2.1. A total of 418 proteins were quantified. The specific protein signature of active TB patients was characterized by an accumulation of proteins related to complement activation, inflammation and modulation of immune response and also by a decrease of a small subset of proteins, including apolipoprotein A and serotransferrin, indicating the importance of lipid transport and iron assimilation in the progression of the disease. This signature was verified by the targeted measurement of selected candidates in a second cohort (EMI-TB Verification Cohort, Maputo Region, Mozambique) by ELISA and nephelometry techniques. These findings will aid our understanding of the complex metabolic processes associated with TB progression from LTBI to active disease.

ATBdiscrimination: An in Silico Tool for Identification of Active Tuberculosis Disease Based on Routine Blood Test and T-SPOT.TB Detection Results

Tuberculosis remains one of the deadliest infectious diseases worldwide. Only 5-15% of people infected with Mycobacterium tuberculosis develop active TB disease (ATB), while others remain latently infected (LTBI) during their lifetime, which has a completely different clinical treatment schedule. However, most current clinical diagnostic methods are based on the immune response of M. tuberculosis infections and cannot distinguish ATB from LTBIs. Thus, the rapid diagnosis of active or latent tuberculosis infections remains a serious challenge for clinicians. In this work, based on the test data of a total of 478 patients, 36 blood biochemical data were specially included with T-SPOT.TB detection results which are all from routine clinical practice as commercially available. Then a discrimination method to detect ATB infections was successfully developed based on these data by the random forest algorithm. This method presents a robust classification performance with AUC as 0.9256 and 0.8731 for the cross-validation set and the external validation set, respectively. This work suggests an innovative strategy for identification of ATB disease from a single drop of blood with advantages of being timely, efficient, and economical. It also provides valuable information for the comprehensive understanding of TB with deep associations between TB infection and routine blood test data. The web server of this identification method, called ATBdiscrimination, is now available online at http://lishuyan.lzu.edu.cn/ATB/ATBdiscrimination.html .

Altered Systemic Adipokine Levels in Pulmonary Tuberculosis and Changes following Treatment

Pulmonary tuberculosis (PTB) is associated with modulation of levels of adipokines, specifically adiponectin and leptin, but the effect of standard antituberculosis treatment (ATT) on the systemic levels of adiponectin, resistin, and leptin has not been well explored. To identify the association of adipokines with PTB and their relationship with disease severity and bacterial burden, we measured the levels of adiponectin, resistin, and leptin in PTB individuals and compared them with latent tuberculosis (LTB) and healthy control (HC) individuals. Pulmonary tuberculosis was characterized by diminished circulating levels of adiponectin and leptin and heightened circulating levels of resistin in comparison to that in LTB and HC individuals. However, PTB with bilateral or cavitary disease did not exhibit any increased systemic levels of these adipokines in comparison with those with unilateral or non-cavitary disease, respectively. In addition, none of the adipokines exhibited a positive correlation with bacterial burdens, but adiponectin alone exhibited a negative correlation with body mass index in PTB individuals. Finally, on successful completion of ATT, PTB individuals exhibited significantly increased levels of adiponectin and leptin and significantly decreased levels of resistin. Therefore, our data identify an important association of systemic adipokine levels with PTB disease and its alteration following ATT.

Identification of unique key genes and miRNAs in latent tuberculosis infection by network analysis

Tuberculosis (TB) is a chronic infectious disease caused by Mycobacterium tuberculosis (M.tb). New cases are now mainly caused by the progression of latent tuberculosis infection (LTBI). Thus, methods to diagnose and treat LTBI are urgently needed to prevent the development of active TB in infected individuals and the subsequent spread of the disease. In this study, a systems biology approach was utilized to obtain numerous microarray data sets for mRNAs and microRNAs (miRNAs) expressed in the peripheral blood mononuclear cells (PBMCs) of TB patients and individuals with LTBI. Within these data sets, we identified the differentially expressed mRNAs and miRNAs and further investigated which differentially expressed genes and miRNAs were uniquely expressed during LTBI. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was employed to analyze the functional annotations and pathway classifications of the identified genes. To further understand the unique miRNA-gene regulatory network of LTBI, we constructed a protein-protein interaction (PPI) network for the targeted genes. The PPI network included 39 genes that were differentially and uniquely expressed in PBMCs of individuals with LTBI, and KEGG pathway enrichment analysis showed that these genes were predominantly involved in the PI3K-Akt signaling pathway, which plays an important role in chronic inflammation. DIANA TOOLs-mirPath analysis revealed that the identified miRNAs in the miRNA-gene regulatory network for LTBI were mainly associated with the Hippo signaling pathway, which functions in the development of inflammation. Quantitative real-time PCR verified the up expression of hsa-miR-212-3p and its predicted target gene -MAPK1 which had low expression and was a major component of the PPI network, and MAPK1 expression was correlated with the clinicopathological characteristics of LTBI by receiver operating characteristic (ROC) curve analysis. Therefore, MAPK1 has potential to be a new investigable marker during LTBI, which merits our further study and solution. The unique aberrant miRNA-gene regulatory network and the related PPI network identified in this study provide insight into the molecular mechanisms of the immune response to LTBI, and thus, may aid in the development of a novel treatment strategy.

The value of transcriptomics in advancing knowledge of the immune response and diagnosis in tuberculosis

Blood transcriptomics analysis of tuberculosis has revealed an interferon-inducible gene signature that diminishes in expression after successful treatment; this promises improved diagnostics and treatment monitoring, which are essential for the eradication of tuberculosis. Sensitive radiography revealing lung abnormalities and blood transcriptomics have demonstrated heterogeneity in patients with active tuberculosis and exposed asymptomatic people with latent tuberculosis, suggestive of a continuum of infection and immune states. Here we describe the immune response to infection with Mycobacterium tuberculosis revealed through the use of transcriptomics, as well as differences among clinical phenotypes of infection that might provide information on temporal changes in host immunity associated with evolving infection. We also review the diverse blood transcriptional signatures, composed of small sets of genes, that have been proposed for the diagnosis of tuberculosis and the identification of at-risk asymptomatic people and suggest novel approaches for the development of such biomarkers for clinical use.

Latent tuberculosis infection: Opportunities and challenges

Diagnosing and treating latent tuberculosis (TB) infection (LTBI) is recognized by the World Health Organization as an important strategy to accelerate the decline in global TB and achieve TB elimination. Even among low-TB burden countries that have achieved high rates of detection and successful treatment for active TB, a number of barriers have prevented implementing or expanding LTBI treatment programmes. Of those infected with TB, relatively few will develop active disease and the current diagnostic tests have a low predictive value. LTBI treatment using isoniazid (INH) has low completion rates due to the long duration of therapy and poor tolerability. Both patients and physicians often perceive the risk of toxicity to be greater than the risk of reactivation TB. As a result, LTBI treatment has had a limited or negligible role outside of countries with high resources and low burden of disease. New tools have emerged including the interferon-gamma release assays that more accurately diagnose LTBI, particularly in people vaccinated with Bacillus Calmette-Guerin (BCG). Shorter, better tolerated treatment using rifamycins are proving safe and effective alternatives to INH. While still imperfect, TB prevention using these new diagnostic and treatment tools appear cost effective in modelling studies in the United States and have the potential to improve TB prevention efforts globally. Continued research to understand the host-organism interactions within the spectrum of LTBI is needed to develop better tools. Until then, overcoming the barriers and optimizing our current tools is essential for progressing toward TB elimination.