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

Flow cytometry-based method using diversity of cytokine production differentiates between Mycobacterium tuberculosis infection and disease

Authors present a pilot study of the development of innovative flow cytometry-based assay with a potential for use in tuberculosis diagnostics. Currently available tests do not provide robust discrimination between latent tuberculosis infection (TBI) and tuberculosis disease (TB). The desired application is to distinguish between the two conditions by evaluating the production of a combination of three cytokines: IL-2 (interleukin-2), IFNɣ (interferon gamma) and TNFɑ (tumor necrosis factor alpha) in CD4+ and CD8+ T cells. The study was conducted on 68 participants, divided into two arms according to age (paediatric and adults). Each arm was further split into three categories (non-infection (NI), TBI, TB) based on the immune reaction to Mycobacterium tuberculosis (M.tb) after a close contact with pulmonary TB. Each blood sample was stimulated with specific M.tb antigens present in QuantiFERON tubes (TB1 and TB2). We inferred TBI or TB based on the predominant cytokine response of the CD4+ and/or CD8+ T cells. Significant differences were detected between the NI, TBI and the TB groups in TB1 in the CD4+TNFɑ+parameter in children. Along with IL-2, TNFɑ seems to be the most promising diagnostic marker in both CD4+and CD8+ T cells. However, more detailed analyses on larger cohorts are needed to confirm the observed tendencies.

Circulating cell-free RNA in blood as a host response biomarker for detection of tuberculosis

Tuberculosis (TB) remains a leading cause of death from an infectious disease worldwide, partly due to a lack of effective strategies to screen and triage individuals with potential TB. Whole blood RNA signatures have been tested as biomarkers for TB, but have failed to meet the World Health Organization's (WHO) optimal target product profiles (TPP). Here, we use RNA sequencing and machine-learning to investigate the utility of plasma cell-free RNA (cfRNA) as a host-response biomarker for TB in cohorts from Uganda, Vietnam and Philippines. We report a 6-gene cfRNA signature, which differentiates TB-positive and TB-negative individuals with AUC = 0.95, 0.92, and 0.95 in test, training and validation, respectively. This signature meets WHO TPPs (sensitivity: 97.1% [95% CI: 80.9-100%], specificity: 85.2% [95% CI: 72.4-100%]) regardless of geographic location, sample collection method and HIV status. Overall, our results identify plasma cfRNA as a promising host response biomarker to diagnose TB.

An integrative multi-omics approach to characterize interactions between tuberculosis and diabetes mellitus

Tuberculosis-diabetes mellitus (TB-DM) is linked to a distinct inflammatory profile, which can be assessed using multi-omics analyses. Here, a machine learning algorithm was applied to multi-platform data, including cytokines and gene expression in peripheral blood and eicosanoids in urine, in a Brazilian multi-center TB cohort. There were four clinical groups: TB-DM(n = 24), TB only(n = 28), DM(HbA1c ≥ 6.5%) only(n = 11), and a control group of close TB contacts who did not have TB or DM(n = 13). After cross-validation, baseline expression or abundance of MMP-28, LTE-4, 11-dTxB2, PGDM, FBXO6, SECTM1, and LINCO2009 differentiated the four patient groups. A distinct multi-omic-derived, dimensionally reduced, signature was associated with TB, regardless of glycemic status. SECTM1 and FBXO6 mRNA levels were positively correlated with sputum acid-fast bacilli grade in TB-DM. Values of the biomarkers decreased during the course of anti-TB therapy. Our study identified several markers associated with the pathophysiology of TB-DM that could be evaluated in future mechanistic investigations.

Pathogen recognition pathway gene variants and inflammasome sensors gene expression in tuberculosis patients under treatment

BACKGROUND

Several epidemiological studies have suggested that genetic variations in encoding pattern recognition receptors (PRRs) genes such as Toll Like Receptors (TLRs) and their signaling products, may influence the susceptibility, severity and outcome of tuberculosis (TB). After sensing a pathogen, the cell responds producing an inflammatory response, to restrain the pathogen's successful course of infection. Herein we assessed single nucleotide polymorphisms (SNP) and gene expression from pathogen recognition and inflammasome pathways in Brazilian TB patients.

METHODS AND RESULTS

For genetic association analysis we included MYD88 and TLR4, PRRs sensing proteins. Allele distribution for MYD88 rs6853 (A > G) and TLR4 rs7873784 (C > G) presented conserved among the tested samples with statistically differential distribution in TB patients versus controls. However, when testing according to sample ethnicity (African or Caucasian-derived individuals) we identified that the rs6853 G/G genotype was associated with a lower susceptibility to TB in Caucasian population. Meanwhile, the rs7873784 G/G genotype was associated with a higher TB susceptibility in Afro-descendant ethnicity individuals. We also aimed to verify MYD88 and the inflammasome genes NLRP1 and NLRC4 expression in order to connect to active TB and/or clinical aspects.

CONCLUSIONS

We identified that inflammasome gene expression in TB patients under treatment display a similar pattern as in healthy controls, indicating that TB treatment impairs NLRP1 inflammasome activation.

Alterations of lipid-related genes during anti-tuberculosis treatment: insights into host immune responses and potential transcriptional biomarkers

Background

The optimal diagnosis and treatment of tuberculosis (TB) are challenging due to underdiagnosis and inadequate treatment monitoring. Lipid-related genes are crucial components of the host immune response in TB. However, their dynamic expression and potential usefulness for monitoring response to anti-TB treatment are unclear.

Methodology

In the present study, we used a targeted, knowledge-based approach to investigate the expression of lipid-related genes during anti-TB treatment and their potential use as biomarkers of treatment response.

Results and discussion

The expression levels of 10 genes (ARPC5, ACSL4, PLD4, LIPA, CHMP2B, RAB5A, GABARAPL2, PLA2G4A, MBOAT2, and MBOAT1) were significantly altered during standard anti-TB treatment. We evaluated the potential usefulness of this 10-lipid-gene signature for TB diagnosis and treatment monitoring in various clinical scenarios across multiple populations. We also compared this signature with other transcriptomic signatures. The 10-lipid-gene signature could distinguish patients with TB from those with latent tuberculosis infection and non-TB controls (area under the receiver operating characteristic curve > 0.7 for most cases); it could also be useful for monitoring response to anti-TB treatment. Although the performance of the new signature was not better than that of previous signatures (i.e., RISK6, Sambarey10, Long10), our results suggest the usefulness of metabolism-centric biomarkers.

Conclusions

Lipid-related genes play significant roles in TB pathophysiology and host immune responses. Furthermore, transcriptomic signatures related to the immune response and lipid-related gene may be useful for TB diagnosis and treatment monitoring.

Granulocytes subsets and their divergent functions in host resistance to Mycobacterium tuberculosis - a 'tipping-point' model of disease exacerbation

Granulocytes are innate immune effector cells with essential functions in host resistance to bacterial infections. I will discuss emerging evidence that during Mycobacterium tuberculosis infection, counter-intuitively, eosinophils are host-protective while neutrophils are host detrimental. Additionally, I will propose a 'tipping-point' model in which neutrophils are an integral part of a feedforward loop driving tuberculosis disease exacerbation.

A half-century of research on tuberculosis: Successes and challenges

Great progress has been made over the past half-century, but TB remains a formidable global health problem, particularly in low- and middle-income countries. Understanding the mechanisms of pathogenesis and necessary and sufficient conditions for protection are critical. The need for inexpensive and sensitive point-of-care diagnostic tests for earlier detection of infection and disease, shorter and less-toxic drug regimens for drug-sensitive and -resistant TB, and a more effective vaccine than BCG is immense. New and better tools, greater support for international research, collaborations, and training will be required to dramatically reduce the burden of this devastating disease which still kills 1.6 million people annually.

Serum Protein Electrophoresis Bands As Biomarkers for Drug-Sensitive Pulmonary Tuberculosis

INTRODUCTION

India has the highest cases of tuberculosis worldwide. According to WHO (2022), the incidence of tuberculosis in India is 210 per 100,000 population. Their incidence of new positive smear cases is 75 per 100,000 population per year. In tuberculosis, the level of albumin decreases while globulin increases leading to a low albumin to globulin (A/G) ratio, and electrophoresis of serum proteins are good diagnostic approach and provides essential information for monitoring treatment outcomes.

MATERIALS AND METHODS

The present study includes 50 cases of pulmonary tuberculosis and 50 age-sex-matched healthy controls. Initially, serum protein estimation and electrophoresis were performed in newly diagnosed patients and controls. All drugs were given as National Tuberculosis Elimination Programme (NTEP) guidelines and blood samples were collected at two-month, four-month, and six-month intervals, and different serum protein fractions were compared and analyzed.

RESULTS

The total serum protein was significantly lower in the cases than in the controls; 6.12±0.61 vs. 7.02±0.56 g/dL (p˂0.0020, t-value=3.12). The mean serum albumin was also significantly lower in the cases compared to the controls; 1.65±0.69 vs. 3.87±0.47g/dL (p˂0.0001, t-value=10.98). The α1 globulin started to rise after four months of treatment and at six months level was 0.262±0.32 g/dL. The level of γ globulin continuously decreases after antituberculous treatment to 1.56±0.67 gm/dL at six months.

CONCLUSION

The cause of the decrease in total protein and albumin may be due to malnutrition leading to low cellular immunity. Serum protein level and protein electrophoresis should be analyzed as routine tests in patients before, during, and after treatment. It helps us in identifying patients at risk of pulmonary tuberculosis as well prognosis of the disease. This study is a valuable guide in deciding the effective management of tuberculosis patients with drug treatment plans and appropriate dietary intake. Hence, it highlights the complex relationship that exists between poverty and disease.

Dectin-1-Independent Macrophage Phagocytosis of Mycobacterium abscessus

Mycobacterium abscessus, a species of nontuberculous mycobacteria (NTM), is an opportunistic pathogen that is readily cleared by healthy lungs but can cause pulmonary infections in people with chronic airway diseases. Although knowledge pertaining to molecular mechanisms of host defense against NTM is increasing, macrophage receptors that recognize M. abscessus remain poorly defined. Dectin-1, a C-type lectin receptor identified as a fungal receptor, has been shown to be a pathogen recognition receptor (PRR) for both M. tuberculosis and NTM. To better understand the role of Dectin-1 in host defense against M. abscessus, we tested whether blocking Dectin-1 impaired the uptake of M. abscessus by human macrophages, and we compared M. abscessus pulmonary infection in Dectin-1-deficient and wild-type mice. Blocking antibody for Dectin-1 did not reduce macrophage phagocytosis of M. abscessus, but did reduce the ingestion of the fungal antigen zymosan. Laminarin, a glucan that blocks Dectin-1 and other PRRs, caused decreased phagocytosis of both M. abscessus and zymosan. Dectin-1-/- mice exhibited no defects in the control of M. abscessus infection, and no differences were detected in immune cell populations between wild type and Dectin-1-/- mice. These data demonstrate that murine defense against M. abscessus pulmonary infection, as well as ingestion of M. abscessus by human macrophages, can occur independent of Dectin-1. Thus, additional PRR(s) recognized by laminarin participate in macrophage phagocytosis of M. abscessus.

Host-pathogen relationship in retreated tuberculosis with major rifampicin resistance-conferring mutations

Introduction

It is assumed that host defense systems eliminating the pathogen and regulating tissue damage make a strong impact on the outcome of tuberculosis (TB) disease and that these processes are affected by rifampicin (RIF) resistance-conferring mutations of Mycobacterium tuberculosis (Mtb). However, the host responses to the pathogen harboring different mutations have not been studied comprehensively in clinical settings. We analyzed clinico-epidemiological factors and blood transcriptomic signatures associated with major rpoB mutations conferring RIF resistance in a cohort study.

Methods

Demographic data were collected from 295 active pulmonary TB patients with treatment history in Hanoi, Vietnam. When recruited, drug resistance-conferring mutations and lineage-specific variations were identified using whole-genome sequencing of clinical Mtb isolates. Before starting retreatment, total RNA was extracted from the whole blood of HIV-negative patients infected with Mtb that carried either the rpoB H445Y or rpoB S450L mutation, and the total RNA was subjected to RNA sequencing after age-gender matching. The individual RNA expression levels in the blood sample set were also measured using real-time RT-PCR. Logistic and linear regression models were used to assess possible associations.

Results

In our cohort, rpoB S450L and rpoB H445Y were major RIF resistance-conferring mutations [32/87 (36.8%) and 15/87 (17.2%), respectively]. H445Y was enriched in the ancient Beijing genotype and was associated with nonsynonymous mutations of Rv1830 that has been reported to regulate antibiotic resilience. H445Y was also more frequently observed in genetically clustered strains and in samples from patients who had received more than one TB treatment episode. According to the RNA sequencing, gene sets involved in the interferon-γ and-α pathways were downregulated in H445Y compared with S450L. The qRT-PCR analysis also confirmed the low expression levels of interferon-inducible genes, including BATF2 and SERPING1, in the H445Y group, particularly in patients with extensive lesions on chest X-ray.

Discussion

Our study results showed that rpoB mutations as well as Mtb sublineage with additional genetic variants may have significant effects on host response. These findings strengthen the rationale for investigation of host-pathogen interactions to develop countermeasures against epidemics of drug-resistant TB.

Association of Selected Cardiovascular Markers With Tuberculosis: Community-Based Exploratory Cross-Sectional Analytical Study in Puducherry

Introduction India accounts for one-fourth of the global tuberculosis (TB) burden and also faces a rising burden of non-communicable diseases. Only a few have studied the association between the infective pathogenesis of TB and cardiovascular diseases (CVD). Methods A cross-sectional exploratory analytical design was used to compare CVD risk factors and immunological and radiological parameters. This was a pilot study conducted in two primary health centers in urban Puducherry between February 2020 and March 2021. Household contacts (HHC) were either spouses or siblings of the newly diagnosed pulmonary tuberculosis (PTB) patients selected for comparison as their exposure to infection would be similar to those who were diseased yet did not develop illness. Assuming a difference of 5% in CVD risk between the general population and TB patients, with a 95% confidence interval, the sample size calculated was 153 in each group by nMaster v2.0. Considering the feasibility and resource constrain, we recruited 50 newly diagnosed PTB patients, their age- and gender-matched 50 HHC and 50 PTB patients who completed treatment a year before. CVD risk factors were compared using chi-square or Fisher exact test. Interleukins-6 (IL-6), interferon-gamma (INF-γ), highly specific - C reactive protein (hs-CRP), and carotid intima-media thickness (CIMT) were compared using ANOVA or Kruskal-Wallis test. Results Most participants from each group belonged to lower socio-economic strata and were males (40/50). Alcohol intake was higher among newly diagnosed and treatment-completed PTB patients (82.5% vs 72.5%). Excess salt intake (58%) was present more in newly diagnosed PTB patients. General and abdominal obesity were seen more among HHC (64% and 84%) and treatment-completed PTB patients (50% and 74%). IL-6 was higher in newly diagnosed PTB patients, whereas INF-γ and hs-CRP were higher in treatment-completed PTB patients. The largest proportion of those having high CIMT values was also in the treatment-completed PTB patients. Conclusion Levels of immune markers hint at the role of inflammation due to TB disease being related to the high CIMT values among the newly diagnosed and treatment-completed PTB patients. CVD risk was higher among TB patients even if they had completed treatment and were declared cured.

A multi-center, prospective cohort study of whole blood gene expression in the tuberculosis-diabetes interaction

Diabetes mellitus (DM) increases tuberculosis (TB) severity. We compared blood gene expression in adults with pulmonary TB, with or without diabetes mellitus (DM) from sites in Brazil and India. RNA sequencing (RNAseq) performed at baseline and during TB treatment. Publicly available baseline RNAseq data from South Africa and Romania reported by the TANDEM Consortium were also analyzed. Across the sites, differentially expressed genes varied for each condition (DM, TB, and TBDM) and no pattern classified any one group across all sites. A concise signature of TB disease was identified but this was expressed equally in TB and TBDM. Pathway enrichment analysis failed to distinguish TB from TBDM, although there was a trend for greater neutrophil and innate immune pathway activation in TBDM participants. Pathways associated with insulin resistance, metabolic dysfunction, diabetic complications, and chromosomal instability were positively correlated with glycohemoglobin. The immune response to pulmonary TB as reflected by whole blood gene expression is substantially similar with or without comorbid DM. Gene expression pathways associated with the microvascular and macrovascular complications of DM are upregulated during TB, supporting a syndemic interaction between these coprevalent diseases.

Convolutional neural network based on T-SPOT.TB assay promoting the discrimination between active tuberculosis and latent tuberculosis infection

OBJECTIVES

The study aims to investigate the potential of convolutional neural network (CNN) based on spot image of T-SPOT assay for distinguishing active tuberculosis (ATB) from latent tuberculosis infection (LTBI).

METHODS

CNN was applied to recognize and classify T-SPOT spot image. Logistic regression was used to establish prediction model based on CNN.

RESULTS

Areas under the receiver operating characteristic curve (AUCs) of early secreted antigenic target 6 (ESAT-6) CNN, culture filtrate protein 10 (CFP-10) CNN, and phytohemagglutinin (PHA) CNN were more than 0.7 in differentiating ATB from LTBI, while the performance of these indicators was significantly better than that of spot number. Furthermore, prediction model based on the combination of CNNs yielded an AUC of 0.898. The model presented a sensitivity of 85.76% and a specificity of 90.23%.

CONCLUSIONS

The current study identified CNN based on T-SPOT spot image with the potential to serve as a tool for TB diagnostics.

Assessing Outlier Probabilities in Transcriptomics Data When Evaluating a Classifier

Outliers in the training or test set used to fit and evaluate a classifier on transcriptomics data can considerably change the estimated performance of the model. Hence, an either too weak or a too optimistic accuracy is then reported and the estimated model performance cannot be reproduced on independent data. It is then also doubtful whether a classifier qualifies for clinical usage. We estimate classifier performances in simulated gene expression data with artificial outliers and in two real-world datasets. As a new approach, we use two outlier detection methods within a bootstrap procedure to estimate the outlier probability for each sample and evaluate classifiers before and after outlier removal by means of cross-validation. We found that the removal of outliers changed the classification performance notably. For the most part, removing outliers improved the classification results. Taking into account the fact that there are various, sometimes unclear reasons for a sample to be an outlier, we strongly advocate to always report the performance of a transcriptomics classifier with and without outliers in training and test data. This provides a more diverse picture of a classifier's performance and prevents reporting models that later turn out to be not applicable for clinical diagnoses.

Circulating Cell-Free RNA in Blood as a Host Response Biomarker for the Detection of Tuberculosis

Tuberculosis (TB) remains a leading cause of death from an infectious disease worldwide. This is partly due to a lack of tools to effectively screen and triage individuals with potential TB. Whole blood RNA signatures have been extensively studied as potential biomarkers for TB, but they have failed to meet the World Health Organization's (WHOs) target product profiles (TPPs) for a non-sputum triage or diagnostic test. In this study, we investigated the utility of plasma cell-free RNA (cfRNA) as a host response biomarker for TB. We used RNA profiling by sequencing to analyze plasma samples from 182 individuals with a cough lasting at least two weeks, who were seen at outpatient clinics in Uganda, Vietnam, and the Philippines. Of these individuals, 100 were diagnosed with microbiologically-confirmed TB. Our analysis of the plasma cfRNA transcriptome revealed 541 differentially abundant genes, the top 150 of which were used to train 15 machine learning models. The highest performing model led to a 9-gene signature that had a diagnostic accuracy of 89.1% (95% CI: 83.6-93.4%) and an area under the curve of 0.934 (95% CI: 0.8674-1) for microbiologically-confirmed TB. This 9-gene signature exceeds the optimal WHO TPPs for a TB triage test (sensitivity: 96.2% [95% CI: 80.9-100%], specificity: 89.7% [95% CI: 72.4-100%]) and was robust to differences in sample collection, geographic location, and HIV status. Overall, our results demonstrate the utility of plasma cfRNA for the detection of TB and suggest the potential for a point-of-care, gene expression-based assay to aid in early detection of TB.

Utility of a three-gene transcriptomic signature in the diagnosis of tuberculosis in a low-endemic hospital setting

BACKGROUND

Host transcriptomic blood signatures have demonstrated diagnostic potential for tuberculosis (TB), requiring further validation across different geographical settings. Discriminating TB from other diseases with similar clinical manifestations is crucial for the development of an accurate immunodiagnostic tool. In this exploratory cohort study, we evaluated the performance of potential blood-based transcriptomic signatures in distinguishing TB disease from non-TB lower respiratory tract infections in hospitalised patients in a TB low-endemic country.

METHOD

Quantitative real-time polymerase chain reaction qPCR) was used to evaluate 26 previously published genes in blood from 31 patients (14 TB and 17 lower respiratory tract infection cases) admitted to Oslo University Hospital in Norway. The diagnostic accuracies of differentially expressed genes were determined by receiver operating characteristic curves.

RESULTS

A significant difference (p < .01) in the age distribution was observed between patients with TB (mean age, 40 ± 15 years) and lower respiratory tract infection (mean age 59 ± 12 years). Following adjustment for age, ETV7, GBP1, GBP5, P2RY14 and BLK were significantly differentially expressed between patients with TB and those with LRI. A general discriminant analysis generated a three-gene signature (BAFT2, ETV7 and CD1C), which diagnosed TB with an area under the receiver operating characteristic curve (AUC) of 0.86 (95% CI, 0.69 - 1.00), sensitivity of 69.23% (95% CI, 38.57%-90.91%) and specificity of 94.12% (95% CI, 71.31%-99.85%).

CONCLUSION

The three-genes signature may have potential to improve diagnosis of TB in a hospitalised low-burden setting. However, the influence of confounding variables or covariates such as age requires further evaluation in larger studies.

Development of diagnostic algorithm using machine learning for distinguishing between active tuberculosis and latent tuberculosis infection

BACKGROUND

The discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging. The present study aims to investigate the value of diagnostic models established by machine learning based on multiple laboratory data for distinguishing Mycobacterium tuberculosis (Mtb) infection status.

METHODS

T-SPOT, lymphocyte characteristic detection, and routine laboratory tests were performed on participants. Diagnostic models were built according to various algorithms.

RESULTS

A total of 892 participants (468 ATB and 424 LTBI) and another 263 participants (125 ATB and 138 LTBI), were respectively enrolled at Tongji Hospital (discovery cohort) and Sino-French New City Hospital (validation cohort). Receiver operating characteristic (ROC) curve analysis showed that the value of individual indicator for differentiating ATB from LTBI was limited (area under the ROC curve (AUC) < 0.8). A total of 28 models were successfully established using machine learning. Among them, the AUCs of 25 models were more than 0.9 in test set. It was found that conditional random forests (cforest) model, based on the implementation of the random forest and bagging ensemble algorithms utilizing conditional inference trees as base learners, presented best discriminative power in segregating ATB from LTBI. Specially, cforest model presented an AUC of 0.978, with the sensitivity of 93.39% and the specificity of 91.18%. Mtb-specific response represented by early secreted antigenic target 6 (ESAT-6) and culture filtrate protein 10 (CFP-10) spot-forming cell (SFC) in T-SPOT assay, as well as global adaptive immunity assessed by CD4 cell IFN-γ secretion, CD8 cell IFN-γ secretion, and CD4 cell number, were found to contribute greatly to the cforest model. Superior performance obtained in the discovery cohort was further confirmed in the validation cohort. The sensitivity and specificity of cforest model in validation set were 92.80% and 89.86%, respectively.

CONCLUSIONS

Cforest model developed upon machine learning could serve as a valuable and prospective tool for identifying Mtb infection status. The present study provided a novel and viable idea for realizing the clinical diagnostic application of the combination of machine learning and laboratory findings.

Extracellular vesicle-mediated regulation of macrophage polarization in bacterial infections

Extracellular vesicles (EVs) are nanoscale membrane-enveloped vesicles secreted by prokaryotic and eukaryotic cells, which are commonly defined as membrane vesicles (MVs) and exosomes, respectively. They play critical roles in the bacteria-bacteria and bacteria-host interactions. In infectious diseases caused by bacteria, as the first line of defense against pathogens, the macrophage polarization mode commonly determines the success or failure of the host's response to pathogen aggression. M1-type macrophages secrete pro-inflammatory factors that support microbicidal activity, while alternative M2-type macrophages secrete anti-inflammatory factors that perform an antimicrobial immune response but partially allow pathogens to replicate and survive intracellularly. Membrane vesicles (MVs) released from bacteria as a distinctive secretion system can carry various components, including bacterial effectors, nucleic acids, or lipids to modulate macrophage polarization in host-pathogen interaction. Similar to MVs, bacteria-infected macrophages can secrete exosomes containing a variety of components to manipulate the phenotypic polarization of "bystander" macrophages nearby or long distance to differentiate into type M1 or M2 to regulate the course of inflammation. Exosomes can also repair tissue damage associated with the infection by upregulating the levels of anti-inflammatory factors, downregulating the pro-inflammatory factors, and regulating cellular biological behaviors. The study of the mechanisms by which EVs modulate macrophage polarization has opened new frontiers in delineating the molecular machinery involved in bacterial pathogenesis and challenges in providing new strategies for diagnosis and therapy.

Tuberculosis alters immune-metabolic pathways resulting in perturbed IL-1 responses

Tuberculosis (TB) remains a major public health problem and we lack a comprehensive understanding of how Mycobacterium tuberculosis (M. tb) infection impacts host immune responses. We compared the induced immune response to TB antigen, BCG and IL-1β stimulation between latently M. tb infected individuals (LTBI) and active TB patients. This revealed distinct responses between TB/LTBI at transcriptomic, proteomic and metabolomic levels. At baseline, we identified a novel immune-metabolic association between pregnane steroids, the PPARγ pathway and elevated plasma IL-1ra in TB. We observed dysregulated IL-1 responses after BCG stimulation in TB patients, with elevated IL-1ra responses being explained by upstream TNF differences. Additionally, distinct secretion of IL-1α/IL-1β in LTBI/TB after BCG stimulation was associated with downstream differences in granzyme mediated cleavage. Finally, IL-1β driven signalling was dramatically perturbed in TB disease but was completely restored after successful treatment. This study improves our knowledge of how immune responses are altered during TB disease, and may support the design of improved preventive and therapeutic tools, including host-directed strategies.

Evaluation of IFIT3 and ORM1 as Biomarkers for Discriminating Active Tuberculosis from Latent Infection

OBJECTIVE

Current commercially available immunological tests cannot be used for discriminating active tuberculosis (TB) from latent TB infection. To evaluate the value of biomarker candidates in the diagnosis of active TB, this study aimed to identify differentially expressed genes in peripheral blood mononuclear cells (PBMCs) between patients with active TB and individuals with latent TB infection by transcriptome sequencing.

METHODS

The differentially expressed genes in unstimulated PBMCs and in Mycobacterium tuberculosis (Mtb) antigen-stimulated PBMCs from patients with active TB and individuals with latent TB infection were identified by transcriptome sequencing. Selected candidate genes were evaluated in cohorts consisting of 110 patients with TB, 30 individuals with latent TB infections, and 50 healthy controls by quantitative real-time RT-PCR. Receiver operating characteristic (ROC) curve analysis was performed to calculate the diagnostic value of the biomarker candidates.

RESULTS

Among the differentially expressed genes in PBMCs without Mtb antigen stimulation, interferon-induced protein with tetratricopeptide repeats 3 (IFIT3) had the highest area under curve (AUC) value (0.918, 95% CI: 0.852-0.984, P<0.0001) in discriminating patients with active TB from individuals with latent TB infection, with a sensitivity of 91.86% and a specificity of 84.00%. In Mtb antigen-stimulated PBMCs, orosomucoid 1 (ORM1) had a high AUC value (0.833, 95% CI: 0.752-0.915, P<0.0001), with a sensitivity of 81.94% and a specificity of 70.00%.

CONCLUSION

IFIT3 and ORM1 might be potential biomarkers for discriminating active TB from latent TB infection.

Metabolites enhance innate resistance to human Mycobacterium tuberculosis infection

To determine the mechanisms that mediate resistance to Mycobacterium tuberculosis (M. tuberculosis) infection in household contacts (HHCs) of patients with tuberculosis (TB), we followed 452 latent TB infection-negative (LTBI-) HHCs for 2 years. Those who remained LTBI- throughout the study were identified as nonconverters. At baseline, nonconverters had a higher percentage of CD14+ and CD3-CD56+CD27+CCR7+ memory-like natural killer (NK) cells. Using a whole-transcriptome and metabolomic approach, we identified deoxycorticosterone acetate as a metabolite with elevated concentrations in the plasma of nonconverters, and further studies showed that this metabolite enhanced glycolytic ATP flux in macrophages and restricted M. tuberculosis growth by enhancing antimicrobial peptide production through the expression of the surface receptor sialic acid binding Ig-like lectin-14. Another metabolite, 4-hydroxypyridine, from the plasma of nonconverters significantly enhanced the expansion of memory-like NK cells. Our findings demonstrate that increased levels of specific metabolites can regulate innate resistance against M. tuberculosis infection in HHCs of patients with TB who never develop LTBI or active TB.

Anti-tuberculosis treatment strategies and drug development: challenges and priorities

Despite two decades of intensified research to understand and cure tuberculosis disease, biological uncertainties remain and hamper progress. However, owing to collaborative initiatives including academia, the pharmaceutical industry and non-for-profit organizations, the drug candidate pipeline is promising. This exceptional success comes with the inherent challenge of prioritizing multidrug regimens for clinical trials and revamping trial designs to accelerate regimen development and capitalize on drug discovery breakthroughs. Most wanted are markers of progression from latent infection to active pulmonary disease, markers of drug response and predictors of relapse, in vitro tools to uncover synergies that translate clinically and animal models to reliably assess the treatment shortening potential of new regimens. In this Review, we highlight the benefits and challenges of 'one-size-fits-all' regimens and treatment duration versus individualized therapy based on disease severity and host and pathogen characteristics, considering scientific and operational perspectives.

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

Neutrophils have been recognized to play an important role in the pathogenesis of tuberculosis in recent years. Interferon-induced blood transcriptional signatures in ATB are predominantly driven by neutrophils. In this study, we performed global RNA-seq on peripheral blood neutrophils from active tuberculosis patients (ATB, n=15); latent tuberculosis infections (LTBI, n=22); and healthy controls (HC, n=21). The results showed that greater perturbations of gene expression patterns happened in neutrophils from ATB individuals than HC or those with LTBI, and a total of 344 differentially expressed genes (DEGs) were observed. Functional enrichment analysis showed that besides the interferon signaling pathway, multiple pattern recognition receptor pathways were significantly activated in ATB, such as NOD-like receptors and Toll-like receptors. Meanwhile, we also observed that the expression of genes related to endocytosis, secretory granules, and neutrophils degranulation were downregulated. Our data also showed that the NF-κB signaling pathway might be inhibited in patients with ATB, which could increase Mycobacterium tuberculosis survival and lead to active tuberculosis status. Furthermore, we validated the accuracy of some differentially expressed genes in an independent cohort using quantitative PCR, and obtained three novel genes (RBM3, CSRNP1, SRSF5) with the ability to discriminate active tuberculosis from LTBI and HC.

Human M1 macrophages express unique innate immune response genes after mycobacterial infection to defend against tuberculosis

Mycobacterium tuberculosis (Mtb) is responsible for approximately 1.5 million deaths each year. Though 10% of patients develop tuberculosis (TB) after infection, 90% of these infections are latent. Further, mice are nearly uniformly susceptible to Mtb but their M1-polarized macrophages (M1-MΦs) can inhibit Mtb in vitro, suggesting that M1-MΦs may be able to regulate anti-TB immunity. We sought to determine whether human MΦ heterogeneity contributes to TB immunity. Here we show that IFN-γ-programmed M1-MΦs degrade Mtb through increased expression of innate immunity regulatory genes (Inregs). In contrast, IL-4-programmed M2-polarized MΦs (M2-MΦs) are permissive for Mtb proliferation and exhibit reduced Inregs expression. M1-MΦs and M2-MΦs express pro- and anti-inflammatory cytokine-chemokines, respectively, and M1-MΦs show nitric oxide and autophagy-dependent degradation of Mtb, leading to increased antigen presentation to T cells through an ATG-RAB7-cathepsin pathway. Despite Mtb infection, M1-MΦs show increased histone acetylation at the ATG5 promoter and pro-autophagy phenotypes, while increased histone deacetylases lead to decreased autophagy in M2-MΦs. Finally, Mtb-infected neonatal macaques express human Inregs in their lymph nodes and macrophages, suggesting that M1 and M2 phenotypes can mediate immunity to TB in both humans and macaques. We conclude that human MФ subsets show unique patterns of gene expression that enable differential control of TB after infection. These genes could serve as targets for diagnosis and immunotherapy of TB.

BCG therapy downregulates HLA-I on malignant cells to subvert antitumor immune responses in bladder cancer

Patients with high-risk non muscle-invasive bladder cancer (NMIBC) frequently relapse after standard intravesical BCG therapy and may have a dismal outcome. Resistance mechanisms to such immunotherapy remain misunderstood. Here, using cancer cell lines, freshly resected human bladder tumors and cohorts of bladder cancer patients pre- and post-BCG therapy, we demonstrate two distinct patterns of immune subversion upon BCG relapse. In the first pattern, intracellular BCG infection of cancer cells induced a post-transcriptional downregulation of HLA-I membrane expression via an inhibition of the autophagy flux. Patients with HLA-I deficient cancer cells post-BCG therapy displayed a myeloid immunosuppressive tumor microenvironment with epithelial-to-mesenchymal transition (EMT) characteristics and dismal outcomes. Conversely, patients with HLA-I proficient cancer cells post-BCG therapy presented with CD8+ T cell tumor infiltrates, upregulation of inflammatory cytokines and inhibitory immune checkpoint molecules. Those patients had a very favorable outcome. We surmise that HLA-I expression in bladder cancers at relapse post-BCG does not result from immunoediting but rather from an immune subversion process directly induced by BCG on cancer cells, which predicts dismal prognosis. Cancer cells HLA-I scoring by immunohistochemistry (IHC) staining can be easily implemented by pathologists in routine practice in order to stratify future urothelial cancer patient treatment strategies.

Dimethyl fumarate eliminates differentially culturable Mycobacterium tuberculosis in an intranasal murine model of tuberculosis

Tuberculosis (TB) claims nearly 1.5 million lives annually. Current TB treatment requires a combination of several drugs administered for at least 6 months. Mycobacterium tuberculosis (Mtb), the causative agent of TB, can persist in infected humans and animals for decades. Moreover, during infection, Mtb produces differentially culturable bacteria (DCB) that do not grow in standard media but can be resuscitated in liquid media supplemented with sterile Mtb culture filtrates or recombinant resuscitation-promoting factors (Rpfs). Here, we demonstrate that, in an intranasal murine model of TB, Mtb DCB are detectable in the lungs after 4 weeks of infection, and their loads remain largely unchanged during a further 8 weeks. Treatment of the infected mice with dimethyl fumarate (DMF), a known drug with immunomodulatory properties, for 8 weeks eliminates Mtb DCB from the lungs and spleens. Standard TB treatment consisting of rifampicin, isoniazid, and pyrazinamide for 8 weeks reduces Mtb loads by nearly four orders of magnitude but does not eradicate DCB. Nevertheless, no DCB can be detected in the lungs and spleens after 8 weeks of treatment with DMF, rifampicin, isoniazid, and pyrazinamide. Our data suggest that addition of approved anti-inflammatory drugs to standard treatment regimens may improve TB treatment and reduce treatment duration.

Signature required: The transcriptional response to tuberculosis

The majority of humans infected with Mycobacterium tuberculosis never experience clinical symptoms or signs, but predicting those who will remains out of reach. Here, we discuss recent studies that reveal patterns and pathways that determine who is at highest risk for progression.

A 10-gene biosignature of tuberculosis treatment monitoring and treatment outcome prediction

The clinical utility of blood transcriptomic biosignatures for the treatment monitoring and outcome prediction of tuberculosis (TB) remains limited. In this study, we aimed to discover and validate biomarkers for pulmonary TB treatment monitoring and outcome prediction based on kinetic responses of gene expression during treatment. In particular, differentially expressed genes (DEGs) were identified by time-series comparison. Subsequently, DEGs with the monotonic expression alterations during the treatment were selected. Ten consistently down-regulated genes (CD274, KIF1B, IL15, TLR1, TLR5, FCGR1A, GBP1, NOD2, GBP2, EGF) exhibited significant potential in treatment monitoring, demonstrated via biological and technical validation. Additionally, the biosignature showed potential in predicting the cured versus relapsed patients. Furthermore, the biosignature could be utilized for TB diagnosis, latent tuberculosis infection/active TB differential diagnosis, and risk of progression to active TB. Benchmarking analysis of the 10-gene biosignature with other biosignatures showed equivalent performance in tested data sets. In conclusion, we established a 10-gene transcriptomic biosignature that represents the kinetic responses of TB treatment. Subsequent studies are warranted to validate, refine and translate the biosignature into a precise assay to assist clinical decisions in a broad spectrum of TB management.

Iguratimod Alleviates Myocardial Ischemia/Reperfusion Injury Through Inhibiting Inflammatory Response Induced by Cardiac Fibroblast Pyroptosis via COX2/NLRP3 Signaling Pathway

Background: NLRP3 inflammasome contributes a lot to sterile inflammatory response and pyroptosis in ischemia/reperfusion (I/R) injury. Cardiac fibroblasts (CFs) are regarded as semi-professional inflammatory cells and they exert an immunomodulatory role in heart. Iguratimod provides a protective role in several human diseases through exerting a powerful anti-inflammatory effect. However, it is still unclear whether iguratimod could alleviate myocardial I/R injury and whether inflammation triggered by NLRP3-related pyroptosis of CFs is involved in this process. Methods: Transcriptomics analysis for GSE160516 dataset was conducted to explore the biological function of differentially expressed genes during myocardial I/R. In vivo, mice underwent ligation of left anterior descending coronary artery for 30 min followed by 24 h reperfusion. In vitro, primary CFs were subjected to hypoxia for 1 h followed by reoxygenation for 3 h (H/R). Iguratimod was used prior to I/R or H/R. Myocardial infarct area, serum level of cardiac troponin I (cTnI), pathology of myocardial tissue, cell viability, lactate dehydrogenase (LDH) release, and the expression levels of mRNA and protein for pyroptosis-related molecules were measured. Immunofluorescence was applied to determine the cellular localization of NLRP3 protein in cardiac tissue. Results: During myocardial I/R, inflammatory response was found to be the most significantly enriched biological process, and nucleotide-binding oligomerization domain (NOD)-like receptor signaling was a crucial pathway in mediating cardiac inflammation. In our experiments, pretreatment with iguratimod significantly ameliorated I/R-induced myocardial injury and H/R-induced pyroptosis of CFs, as evidenced by reduced myocardial infarct area, serum cTnI level, and LDH release in supernatants, as well as improved pathology of cardiac tissue and cell viability. Immunofluorescence analysis showed that NLRP3 was mainly localized in CFs. Moreover, iguratimod inhibited the expression of pro-inflammatory cytokines and pyroptosis-related molecules, including NLRP3, cleaved caspase-1, and GSDMD-N. Conclusion: Our results suggested that inflammatory response mediated by NOD-like receptor signaling is of vital importance in myocardial I/R injury. Iguratimod protected cardiomyocytes through reducing the cascade of inflammation in heart by inhibiting cardiac fibroblast pyroptosis via the COX2/NLRP3 signaling pathway.

Blood transcriptomics reveal the evolution and resolution of the immune response in tuberculosis

Blood transcriptomics have revealed major characteristics of the immune response in active TB, but the signature early after infection is unknown. In a unique clinically and temporally well-defined cohort of household contacts of active TB patients that progressed to TB, we define minimal changes in gene expression in incipient TB increasing in subclinical and clinical TB. While increasing with time, changes in gene expression were highest at 30 d before diagnosis, with heterogeneity in the response in household TB contacts and in a published cohort of TB progressors as they progressed to TB, at a bulk cohort level and in individual progressors. Blood signatures from patients before and during anti-TB treatment robustly monitored the treatment response distinguishing early and late responders. Blood transcriptomics thus reveal the evolution and resolution of the immune response in TB, which may help in clinical management of the disease.

Revisiting tuberculosis screening: An insight to complementary diagnosis and prospective molecular approaches for the recognition of the dormant TB infection in human and cattle hosts

Tuberculosis (TB) is defined as a chronic infection in both human and cattle hosts and many subclinical cases remain undetected. After the pathogen is inhaled by a host, phagocyted bacilli can persist inside macrophages surviving intracellularly. Hosts develop granulomatous lesions in the lungs or lymph nodes, limiting infection. However, bacilli become persister cells. Immunological diagnosis of TB is performed basically by routine tuberculin skin test (TST), and in some cases, by ancillary interferon-gamma release assay (IGRA). The concept of human latent TB infection (LTBI) by M. tuberculosis is recognized in cohorts without symptoms by routine clinical diagnostic tests, and nowadays IGRA tests are used to confirm LTBI with either active or latent specific antigens of M. tuberculosis. On the other hand, dormant infection in cattle by M. bovis has not been described by TST or IGRA testing as complications occur by cross-reactive immune responses to homolog antigens of environmental mycobacteria or a false-negative test by anergic states of a wained bovine immunity, evidencing the need for deciphering more specific biomarkers by new-generation platforms of analysis for detection of M. bovis dormant infection. The study and description of bovine latent TB infection (boLTBI) would permit the recognition of hidden animal infection with an increase in the sensitivity of routine tests for an accurate estimation of infected dairy cattle. Evidence of immunological and experimental analysis of LTBI should be taken into account to improve the study and the description of the still neglected boLTBI.

Activation Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells Promoting the Discrimination Between Active Tuberculosis and Latent Tuberculosis Infection

Background

Rapid and effective discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains a challenge. There is an urgent need for developing practical and affordable approaches targeting this issue.

Methods

Participants with ATB and LTBI were recruited at Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort) based on positive T-SPOT results from June 2020 to January 2021. The expression of activation markers including HLA-DR, CD38, CD69, and CD25 was examined on Mycobacterium tuberculosis (MTB)-specific CD4⁺ T cells defined by IFN-γ, TNF-α, and IL-2 expression upon MTB antigen stimulation.

Results

A total of 90 (40 ATB and 50 LTBI) and another 64 (29 ATB and 35 LTBI) subjects were recruited from the Qiaokou cohort and Caidian cohort, respectively. The expression patterns of Th1 cytokines including IFN-γ, TNF-α, and IL-2 upon MTB antigen stimulation could not differentiate ATB patients from LTBI individuals well. However, both HLA-DR and CD38 on MTB-specific cells showed discriminatory value in distinguishing between ATB patients and LTBI individuals. As for developing a single candidate biomarker, HLA-DR had the advantage over CD38. Moreover, HLA-DR on TNF-α⁺ or IL-2⁺ cells had superiority over that on IFN-γ⁺ cells in differentiating ATB patients from LTBI individuals. Besides, HLA-DR on MTB-specific cells defined by multiple cytokine co-expression had a higher ability to discriminate patients with ATB from LTBI individuals than that of MTB-specific cells defined by one kind of cytokine expression. Specially, HLA-DR on TNF-α⁺IL-2⁺ cells produced an AUC of 0.901 (95% CI, 0.833–0.969), with a sensitivity of 93.75% (95% CI, 79.85–98.27%) and specificity of 72.97% (95% CI, 57.02–84.60%) as a threshold of 44% was used. Furthermore, the performance of HLA-DR on TNF-α⁺IL-2⁺ cells for differential diagnosis was obtained with validation cohort data: 90.91% (95% CI, 72.19–97.47%) sensitivity and 68.97% (95% CI, 50.77–82.73%) specificity.

Conclusions

We demonstrated that HLA-DR on MTB-specific cells was a potentially useful biomarker for accurate discrimination between ATB and LTBI.

Transcriptional signatures of human peripheral blood mononuclear cells can identify the risk of tuberculosis progression from latent infection among individuals with silicosis

Host immune factor plays an important role in the progression of latent tuberculosis infection (LTBI) to active tuberculosis (TB) disease. However, whether global gene expression measured in blood biomarkers allows the identification of prospective signatures for TB risk remains unknown. Hence, we aimed to assess the ability of the transcriptome signatures in the human peripheral blood mononuclear cells (PBMCs) of LTBI subjects to differentiate future TB progressors from non-progressors. In a randomized clinical trial of TB preventive treatment of 513 participants with silicosis, we randomly collected PBMC samples from 50 LTBI subjects in the observational group, which was monitored for TB disease progression for 37 months. The prospective signatures of TB risk between the two participants who developed active TB (progressors) and four matched individuals who remained healthy (non-progressors) were compared using differential expression analysis, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Weighted Gene Co-expression Network Analysis. The 20 TB-specific differentially expressed genes, which were significantly downregulated in TB progressors, were revealed to be associated with interferon-gamma response-related genes. Therefore, the PBMC transcriptome profiles analyzed in this study may help identify LTBI individuals who are at risk of progressing to active TB among silicosis patients and may provide new insights for targeted intervention to prevent disease progression.

Tuberculosis lymph node granulomas: using transcriptomics to discover immunopathology paradigms and guide host-directed therapy

Immunometabolism is a burgeoning field of investigation in tuberculosis host defense, susceptibility, and pathophysiology. Unbiased approaches to studying tuberculosis have, as expected, confirmed that pathways of immunometabolism are crucial in these disease processes. In this issue of the JCI, Reichmann et al. studied carefully controlled human lymph node tuberculosis and uncovered Sphingosine kinase 1 as a druggable target of interest that could support the infected host. Future host-directed therapy research might seek to establish the different cellular consequences of sphingolipid pathway manipulation. Animal models will be especially useful to establish the role of this pathway, which might target diseased organs to improve mycobactericidal effect and limit pathology.

Doxycycline host-directed therapy in human pulmonary tuberculosis

BACKGROUNDMatrix metalloproteinases (MMPs) are key regulators of tissue destruction in tuberculosis (TB) and may be targets for host-directed therapy. We conducted a phase II double-blind, randomized, controlled trial investigating doxycycline, a licensed broad-spectrum MMP inhibitor, in patients with pulmonary TB.METHODSThirty patients with pulmonary TB were enrolled within 7 days of initiating anti-TB treatment and randomly assigned to receive either 100 mg doxycycline or placebo twice a day for 14 days, in addition to standard care.RESULTSWhole blood RNA-sequencing demonstrated that doxycycline accelerated restoration of dysregulated gene expression in TB towards normality, rapidly down-regulating type I and II interferon and innate immune response genes, and up-regulating B-cell modules relative to placebo. The effects persisted for 6 weeks after doxycycline discontinuation, concurrent with suppressed plasma MMP-1. Doxycycline significantly reduced sputum MMP-1, -8, -9, -12 and -13, suppressed type I collagen and elastin destruction, reduced pulmonary cavity volume without altering sputum mycobacterial loads, and was safe.CONCLUSIONAdjunctive doxycycline with standard anti-TB treatment suppressed pathological MMPs in PTB patients. Larger studies on adjunctive doxycycline to limit TB immunopathology are merited.TRIAL REGISTRATIONClinicalTrials.gov NCT02774993.FUNDINGSingapore National Medical Research Council (NMRC/CNIG/1120/2014, NMRC/Seedfunding/0010/2014, NMRC/CISSP/2015/009a); the Singapore Infectious Diseases Initiative (SIDI/2013/013); National University Health System (PFFR-28 January 14, NUHSRO/2014/039/BSL3-SeedFunding/Jul/01); the Singapore Immunology Network Immunomonitoring platform (BMRC/IAF/311006, H16/99/b0/011, NRF2017_SISFP09); an ExxonMobil Research Fellowship, NUHS Clinician Scientist Program (NMRC/TA/0042/2015, CSAINV17nov014); the UK Medical Research Council (MR/P023754/1, MR/N006631/1); a NUS Postdoctoral Fellowship (NUHSRO/2017/073/PDF/03); The Royal Society Challenge Grant (CHG\R1\170084); the Sir Henry Dale Fellowship, Wellcome Trust (109377/Z/15/Z); and A*STAR.

Lymphocyte-Related Immunological Indicators for Stratifying Mycobacterium tuberculosis Infection

Background

Easily accessible tools that reliably stratify Mycobacterium tuberculosis (MTB) infection are needed to facilitate the improvement of clinical management. The current study attempts to reveal lymphocyte-related immune characteristics of active tuberculosis (ATB) patients and establish immunodiagnostic model for discriminating ATB from latent tuberculosis infection (LTBI) and healthy controls (HC).

Methods

A total of 171 subjects consisted of 54 ATB, 57 LTBI, and 60 HC were consecutively recruited at Tongji hospital from January 2019 to January 2021. All participants were tested for lymphocyte subsets, phenotype, and function. Other examination including T-SPOT and microbiological detection for MTB were performed simultaneously.

Results

Compared with LTBI and HC, ATB patients exhibited significantly lower number and function of lymphocytes including CD4⁺ T cells, CD8⁺ T cells and NK cells, and significantly higher T cell activation represented by HLA-DR and proportion of immunosuppressive cells represented by Treg. An immunodiagnostic model based on the combination of NK cell number, HLA-DR⁺CD3⁺ T cells, Treg, CD4⁺ T cell function, and NK cell function was built using logistic regression. Based on receiver operating characteristic curve analysis, the area under the curve (AUC) of the diagnostic model was 0.920 (95% CI, 0.867-0.973) in distinguishing ATB from LTBI, while the cut-off value of 0.676 produced a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and specificity of 91.23% (95% CI, 81.06%-96.20%). Meanwhile, AUC analysis between ATB and HC according to the diagnostic model was 0.911 (95% CI, 0.855-0.967), with a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and a specificity of 90.00% (95% CI, 79.85%-95.34%).

Conclusions

Our study demonstrated that the immunodiagnostic model established by the combination of lymphocyte-related indicators could facilitate the status differentiation of MTB infection.

Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis Infection

Background

Distinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging.

Methods

Between 2013 and 2019, 2,059 (1,097 ATB and 962 LTBI) and another 883 (372 ATB and 511 LTBI) participants were recruited based on positive T-SPOT.TB (T-SPOT) results from Qiaokou (training) and Caidian (validation) cohorts, respectively. Blood routine examination (BRE) was performed simultaneously. Diagnostic model was established according to multivariate logistic regression.

Results

Significant differences were observed in all indicators of BRE and T-SPOT assay between ATB and LTBI. Diagnostic model built on BRE showed area under the curve (AUC) of 0.846 and 0.850 for discriminating ATB from LTBI in the training and validation cohorts, respectively. Meanwhile, TB-specific antigens spot-forming cells (SFC) (the larger of early secreted antigenic target 6 and culture filtrate protein 10 SFC in T-SPOT assay) produced lower AUC of 0.775 and 0.800 in the training and validation cohorts, respectively. The diagnostic model based on combination of BRE and T-SPOT showed an AUC of 0.909 for differentiating ATB from LTBI, with 78.03% sensitivity and 90.23% specificity when a cutoff value of 0.587 was used in the training cohort. Application of the model to the validation cohort showed similar performance. The AUC, sensitivity, and specificity were 0.910, 78.23%, and 90.02%, respectively. Furthermore, we also assessed the performance of our model in differentiating ATB from LTBI with lung lesions. Receiver operating characteristic analysis showed that the AUC of established model was 0.885, while a threshold of 0.587 yield a sensitivity of 78.03% and a specificity of 85.69%, respectively.

Conclusions

The diagnostic model based on combination of BRE and T-SPOT could provide a reliable differentiation between ATB and LTBI.

Validation of Differentially Expressed Immune Biomarkers in Latent and Active Tuberculosis by Real-Time PCR

Tuberculosis (TB) remains a major global threat and diagnosis of active TB ((ATB) both extra-pulmonary (EPTB), pulmonary (PTB)) and latent TB (LTBI) infection remains challenging, particularly in high-burden countries which still rely heavily on conventional methods. Although molecular diagnostic methods are available, e.g., Cepheid GeneXpert, they are not universally available in all high TB burden countries. There is intense focus on immune biomarkers for use in TB diagnosis, which could provide alternative low-cost, rapid diagnostic solutions. In our previous gene expression studies, we identified peripheral blood leukocyte (PBL) mRNA biomarkers in a non-human primate TB aerosol-challenge model. Here, we describe a study to further validate select mRNA biomarkers from this prior study in new cohorts of patients and controls, as a prerequisite for further development. Whole blood mRNA was purified from ATB patients recruited in the UK and India, LTBI and two groups of controls from the UK (i) a low TB incidence region (CNTRLA) and (ii) individuals variably-domiciled in the UK and Asia ((CNTRLB), the latter TB high incidence regions). Seventy-two mRNA biomarker gene targets were analyzed by qPCR using the Roche Lightcycler 480 qPCR platform and data analyzed using GeneSpring™ 14.9 bioinformatics software. Differential expression of fifty-three biomarkers was confirmed between MTB infected, LTBI groups and controls, seventeen of which were significant using analysis of variance (ANOVA): CALCOCO2, CD52, GBP1, GBP2, GBP5, HLA-B, IFIT3, IFITM3, IRF1, LOC400759 (GBP1P1), NCF1C, PF4V1, SAMD9L, S100A11, TAF10, TAPBP, and TRIM25. These were analyzed using receiver operating characteristic (ROC) curve analysis. Single biomarkers and biomarker combinations were further assessed using simple arithmetic algorithms. Minimal combination biomarker panels were delineated for primary diagnosis of ATB (both PTB and EPTB), LTBI and identifying LTBI individuals at high risk of progression which showed good performance characteristics. These were assessed for suitability for progression against the standards for new TB diagnostic tests delineated in the published World Health Organization (WHO) technology product profiles (TPPs).

A Two-Gene Signature for Tuberculosis Diagnosis in Persons With Advanced HIV

Background: Transcriptomic signatures for tuberculosis (TB) have been proposed and represent a promising diagnostic tool. Data remain limited in persons with advanced HIV.

Methods: We enrolled 30 patients with advanced HIV (CD4 <100 cells/mm³) in India; 16 with active TB and 14 without. Whole-blood RNA sequencing was performed; these data were merged with a publicly available dataset from Uganda (n = 33; 18 with TB and 15 without). Transcriptomic profiling and machine learning algorithms identified an optimal gene signature for TB classification. Receiver operating characteristic analysis was used to assess performance.

Results: Among 565 differentially expressed genes identified for TB, 40 were shared across India and Uganda cohorts. Common upregulated pathways reflect Toll-like receptor cascades and neutrophil degranulation. The machine-learning decision-tree algorithm selected gene expression values from RAB20 and INSL3 as most informative for TB classification. The signature accurately classified TB in discovery cohorts (India AUC 0.95 and Uganda AUC 1.0; p < 0.001); accuracy was fair in external validation cohorts.

Conclusions: Expression values of RAB20 and INSL3 genes in peripheral blood compose a biosignature that accurately classified TB status among patients with advanced HIV in two geographically distinct cohorts. The functional analysis suggests pathways previously reported in TB pathogenesis.

Host Blood RNA Transcript and Protein Signatures for Sputum-Independent Diagnostics of Tuberculosis in Adults

To achieve the ambitious targets for tuberculosis (TB) prevention, care, and control stated by the End TB Strategy, new health care strategies, diagnostic tools are warranted. Host-derived biosignatures are explored for their TB diagnostic potential in accordance with the WHO target product profiles (TPPs) for point-of-care (POC) testing. We aimed to identify sputum-independent TB diagnostic signatures in newly diagnosed adult pulmonary-TB (PTB) patients recruited in the context of a prospective household contact cohort study conducted in Andhra Pradesh, India. Whole-blood mRNA samples from 158 subjects (PTB, n = 109; age-matched household controls, n = 49) were examined by dual-color Reverse-Transcriptase Multiplex Ligation-dependent Probe-Amplification (dcRT-MLPA) for the expression of 198 pre-defined genes and a Mesoscale discovery assay for the concentration of 18 cytokines/chemokines in TB-antigen stimulated QuantiFERON supernatants. To identify signatures, we applied a two-step approach; in the first step, univariate filtering was used to identify and shortlist potentially predictive biomarkers; this step may be seen as removing redundant biomarkers. In the second step, a logistic regression approach was used such that group membership (PTB vs. household controls) became the binary response in a Lasso regression model. We identified an 11-gene signature that distinguished PTB from household controls with AUCs of ≥0.98 (95% CIs: 0.94–1.00), and a 4-protein signature (IFNγ, GMCSF, IL7 and IL15) that differentiated PTB from household controls with AUCs of ≥0.87 (95% CIs: 0.75–1.00), in our discovery cohort. Subsequently, we evaluated the performance of the 11-gene signature in two external validation data sets viz, an independent cohort at the Glenfield Hospital, University Hospitals of Leicester NHS Trust, Leicester, UK (GSE107994 data set), and the Catalysis treatment response cohort (GSE89403 data set) from South Africa. The 11-gene signature validated and distinguished PTB from healthy and asymptomatic M. tuberculosis infected household controls in the GSE107994 data set, with an AUC of 0.95 (95% CI: 0.91–0.98) and 0.94 (95% CI: 0.89–0.98). More interestingly in the GSE89403 data set, the 11-gene signature distinguished PTB from household controls and patients with other lung diseases with an AUC of 0.93 (95% CI: 0.87–0.99) and 0.73 (95% CI: 0.56–0.89). These criteria meet the WHO TTP benchmarks for a non–sputum-based triage test for TB diagnosis. We suggest that further validation is required before clinical implementation of the 11-gene signature we have identified markers will be possible.

Evolution of Drug-Resistant Mycobacterium tuberculosis Strains and Their Adaptation to the Human Lung Environment

In the last two decades, multi (MDR), extensively (XDR), extremely (XXDR) and total (TDR) drug-resistant Mycobacterium tuberculosis (M.tb) strains have emerged as a threat to public health worldwide, stressing the need to develop new tuberculosis (TB) prevention and treatment strategies. It is estimated that in the next 35 years, drug-resistant TB will kill around 75 million people and cost the global economy $16.7 trillion. Indeed, the COVID-19 pandemic alone may contribute with the development of 6.3 million new TB cases due to lack of resources and enforced confinement in TB endemic areas. Evolution of drug-resistant M.tb depends on numerous factors, such as bacterial fitness, strain's genetic background and its capacity to adapt to the surrounding environment, as well as host-specific and environmental factors. Whole-genome transcriptomics and genome-wide association studies in recent years have shed some insights into the complexity of M.tb drug resistance and have provided a better understanding of its underlying molecular mechanisms. In this review, we will discuss M.tb phenotypic and genotypic changes driving resistance, including changes in cell envelope components, as well as recently described intrinsic and extrinsic factors promoting resistance emergence and transmission. We will further explore how drug-resistant M.tb adapts differently than drug-susceptible strains to the lung environment at the cellular level, modulating M.tb-host interactions and disease outcome, and novel next generation sequencing (NGS) strategies to study drug-resistant TB.

Low-Density Granulocytes Affect T-SPOT.TB Assay by Inhibiting the Production of Interferon-γ in T Cells via PD-L1/PD-1 Pathway

Background

T-SPOT TB (T-SPOT) assay is widely used for detection of Mycobacterium tuberculosis infection that is based on the detection of M. tuberculosis-specific interferon-γ-secreting T cells (ISCs) in peripheral blood mononuclear cells (PBMCs). Recently, high frequencies of low-density granulocytes (LDGs) were found in the PBMCs of tuberculosis patients. Whether these LDGs affect the detection of T-SPOT has not been investigated. The impact of LDGs on T-SPOT assay and related mechanism were investigated in this study.

Methods

The correlations between the frequencies of LDGs and the results of T-SPOT were analyzed. T-SPOT with LDG-removed PBMCs and PBMCs with exogenous addition of LDGs were performed. The possible mechanism was explored by detecting the levels of negative immune regulatory molecules on LDGs. The impact of programmed death ligand 1 (PD-L1) on T-SPOT was evaluated and confirmed by function blocking with neutralizing antibody.

Results

The positive rates of T-SPOT and ISCs in tuberculosis patients with low LDGs frequency (n = 22) were significantly higher than those with high LDGs frequency (n = 39). Removal or exogenous addition of LDGs significantly increased or decreased the ISCs and the positive rate of T-SPOT. The frequencies of interferon-γ-producing T cells were negatively correlated with the frequencies of LDGs. The expression of PD-L1 was significantly elevated on LDGs. Pretreatment of LDGs with anti-PD-L1 antibody significantly counteracted the impact of LDGs on T-SPOT. Treatment of PBMCs with anti-PD-L1 antibody resulted in comparable ISCs with that of LDG removal.

Conclusion

LDGs can inhibit the production of interferon-γ in T cells and decrease the positive rated of T-SPOT assay via highly expressed PD-L1.

Characterization of and advanced diagnostic methods for ocular tuberculosis and tuberculosis

Tuberculosis (TB) is an airborne infection caused by Mycobacterium tuberculosis that usually affects the lungs. Timely treatment of active TB, diagnosis and prevention of latent TB are very important. However, extrapulmonary TB affects almost any tissues around the eye and orbit, and it then requires a high degree of suspicion to accurately diagnose. Diagnostic delays are common and may lead to morbidity. For ophthalmologists and infectious disease specialists, it is important to work together to accurately diagnose and treat ocular tuberculosis (OTB) to prevent vision loss. This review reports the latest advanced diagnostic methods for active TB and latent TB as well as various known manifestations of OTB. Important elements of diagnosis and treatment are also reviewed.

Differential expression of CD64 in patients with Mycobacterium tuberculosis infection: A potential biomarker for clinical diagnosis and prognosis

To evaluate the clinical utility of neutrophil (n)CD64 index to diagnose pulmonary tuberculosis (PTB) and extrapulmonary TB (ePTB) and to predict the outcome of Mycobacterium tuberculosis infection. We recruited 189 patients with active TB and 140 controls and measured the differential expression of nCD64 index using flow cytometry. The receiver operating characteristics (ROC) curve analysis was performed to estimate the diagnostic performance of the nCD64 index and T‐SPOT.TB assay for the diagnosis of TB. Furthermore, we analysed whether the nCD64 index in patients with TB was correlated with inflammatory indicators. Finally, we assessed the prognosis of patients by following the dynamic changes of the nCD64 index once a week. The nCD64 index was significantly higher in active TB group (PTB and ePTB), than in the anti‐TB and healthy controls (HC) groups. The sensitivity and specificity of nCD64 index for the differential diagnosis of PTB and pneumonia (PN) patients were 68.33% and 77.55%, respectively. The sensitivity and specificity of nCD64 index for the diagnosis of tuberculous meningitis (TBM) were 53.85% and 100%, respectively. Furthermore, there was a weak correlation between the nCD64 index and inflammatory indicators. More importantly, with the improvement in patient condition, the nCD64 index started to decline in the first week of anti‐TB therapy and significantly decreased at 4 weeks after treatment. Our study demonstrated that the CD64 assay is a rapid, non‐invasive and stable method for clinical application, and the nCD64 index can serve as a potential biomarker for the diagnosis and prognosis of TB.

Type I IFN exacerbates disease in tuberculosis-susceptible mice by inducing neutrophil-mediated lung inflammation and NETosis

Tuberculosis (TB) is a leading cause of mortality due to infectious disease, but the factors determining disease progression are unclear. Transcriptional signatures associated with type I IFN signalling and neutrophilic inflammation were shown to correlate with disease severity in mouse models of TB. Here we show that similar transcriptional signatures correlate with increased bacterial loads and exacerbate pathology during Mycobacterium tuberculosis infection upon GM-CSF blockade. Loss of GM-CSF signalling or genetic susceptibility to TB (C3HeB/FeJ mice) result in type I IFN-induced neutrophil extracellular trap (NET) formation that promotes bacterial growth and promotes disease severity. Consistently, NETs are present in necrotic lung lesions of TB patients responding poorly to antibiotic therapy, supporting the role of NETs in a late stage of TB pathogenesis. Our findings reveal an important cytokine-based innate immune effector network with a central role in determining the outcome of M. tuberculosis infection.

GM-CSF is involved in control over M. tuberculosis infection. Here the authors show that GM-CSF reduces type 1 interferon driven neutrophil recruitment, NETosis and bacterial growth in the lungs of infected mice, and provide evidence that this NETosis occurs in infected humans who are not responsive to antibiotic therapy.