Distinct phases of blood gene expression pattern through tuberculosis treatment reflect modulation of the humoral immune response

How Mycobacterium tuberculosis builds a home: Single-cell analysis reveals M. tuberculosis ESX-1-mediated accumulation of anti-inflammatory macrophages in infected mouse lungs

Mycobacterium tuberculosis (MTB) infects and replicates in lung mononuclear phagocytes (MNPs) with astounding ability to evade elimination. ESX-1, a type VII secretion system, acts as a virulence determinant that contributes to MTB's ability to survive within MNPs, but its effect on MNP recruitment and/or differentiation remains unknown. Here, using single-cell RNA sequencing, we studied the role of ESX-1 in MNP heterogeneity and response in mice and murine bone marrow-derived macrophages (BMDM). We found that ESX-1 is required for MTB to recruit diverse MNP subsets with high MTB burden. Further, MTB induces an anti-inflammatory signature in MNPs and BMDM in an ESX-1 dependent manner. Similarly, spatial transcriptomics revealed an upregulation of anti-inflammatory signals in MTB lesions, where monocyte-derived macrophages concentrate near MTB-infected cells. Together, our findings suggest that MTB ESX-1 mediates the recruitment and differentiation of anti-inflammatory MNPs, which MTB can infect and manipulate for survival.

Genomes in clinical care

In the era of precision medicine, genome sequencing (GS) has become more affordable and the importance of genomics and multi-omics in clinical care is increasingly being recognized. However, how to scale and effectively implement GS on an institutional level remains a challenge for many. Here, we present Genome First and Ge-Med, two clinical implementation studies focused on identifying the key pillars and processes that are required to make routine GS and predictive genomics a reality in the clinical setting. We describe our experience and lessons learned for a variety of topics including test logistics, patient care processes, data reporting, and infrastructure. Our model of providing clinical care and comprehensive genomic analysis from a single source may be used by other centers with a similar structure to facilitate the implementation of omics-based personalized health concepts in medicine.

Mycobacterium tuberculosis SecA2-dependent activation of host Rig-I/MAVs signaling is not conserved in Mycobacterium marinum

Retinoic acid inducible gene I (Rig-I) is a cytosolic pattern recognition receptor canonically described for its important role in sensing viral RNAs. Increasingly, bacterially-derived RNA from intracellular bacteria such as Mycobacterium tuberculosis, have been shown to activate the same host Rig-I/Mitochondrial antiviral sensing protein (MAVS) signaling pathway to drive a type-I interferon response that contributes to bacterial pathogenesis in vivo. In M. tuberculosis, this response is mediated by the protein secretion system SecA2, but little is known about whether this process is conserved in other pathogenic mycobacteria or the mechanism by which these nucleic acids gain access to the host cytoplasm. Because the M. tuberculosis and M. marinum SecA2 protein secretion systems share a high degree of genetic and functional conservation, we hypothesized that Rig-I/MAVS activation and subsequent induction of IFN-β secretion by host macrophages will also be conserved between these two mycobacterial species. To test this, we generated a ΔsecA2 M. marinum strain along with complementation strains expressing either the M. marinum or M. tuberculosis secA2 genes. Our results suggest that the ΔsecA2 strain has a growth defect in vitro but not in host macrophages. These intracellular growth curves also suggested that the calculation applied to estimate the number of bacteria added to macrophage monolayers in infection assays underestimates bacterial inputs for the ΔsecA2 strain. Therefore, to better examine secreted IFN-β levels when bacterial infection levels are equal across strains we plated bacterial CFUs at 2hpi alongside our ELISA based infections. This enabled us to normalize secreted levels of IFN-β to a standard number of bacteria. Applying this approach to both WT and MAVS-/- bone marrow derived macrophages we observed equal or higher levels of secreted IFN-β from macrophages infected with the ΔsecA2 M. marinum strain as compared to WT. Together our findings suggest that activation of host Rig-I/MAVS cytosolic sensors and subsequent induction of IFN-β response in a SecA2-dependent manner is not conserved in M. marinum under the conditions tested.

Assessment of the Cepheid 3-gene Host Response Fingerstick Blood Test (MTB-HR) on rapid diagnosis of tuberculosis

ABSTRACTThe World Health Organization has identified high-priority target product profiles for new TB diagnostics which include rapid biomarker-based, non-sputum-based diagnostic testing, using an easily accessible sample. The Cepheid 3-gene Host Response Fingerstick Blood Prototype Test (MTB-HR) quantifies relative mRNA levels of a 3-gene signature (GBP5, DUSP3, and KLF2) from a whole-blood sample on the GeneXpert platform. The objective of the present study was to evaluate the performance of the MTB-HR to distinguish between active tuberculosis (ATB), latent Mycobacterium tuberculosis infection (LTBI), other pulmonary diseases, and healthy volunteers at a tertiary care centre. Among 653 participants enrolled in this study, 192 were diagnosed as having ATB, and the remaining 461 were classified as non-ATB, including 137 cases of LTBI, 224 cases of other pulmonary diseases, and 100 healthy volunteers. The corresponding AUCs of the MTB-HR in distinguishing untreated ATB from non-ATB, LTBI, other pulmonary diseases, and healthy volunteers were 0.814 (95% CI, 0.760-0.868, sensitivity 76.1%, specificity 71.6%), 0.739 (95% CI, 0.667-0.812, sensitivity 59.7%, specificity 78.1%), 0.825 (95% CI, 0.770-0.880, sensitivity 82.1%, specificity 65.6%), 0.892 (95% CI, 0.839-0.945, sensitivity 76.1%, specificity 88.0%), respectively. When only samples with TAT of less than 1 h were included, the AUC of the MTB-HR in distinguishing untreated ATB from non-ATB was largest, 0.920 (95% CI, 0.822-1.000, sensitivity 81.3%, specificity 87.7%). In conclusion, the MTB-HR assay shows potential as a rapid, blood-based screening and triage test for ATB, especially for untreated ATB, with the advantage of increased diagnostic yield since blood is more readily available.

Mycobacterium tuberculosis carrying the rifampicin drug-resistance-conferring rpoB mutation H445Y is associated with suppressed immunity through type I interferons

IMPORTANCE

This study highlights the impact of specific rifampicin-resistance-conferring mutations on the host immune response to Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB). Clinical reports have previously suggested that multi-drug-resistant) TB patients exhibit altered peripheral immune responses as compared with their drug-sensitive TB counterparts. The murine model of infection with Mtb strains carrying drug-resistance-conferring mutations recapitulated these findings and allowed us to mechanistically interrogate the pathways responsible for driving the divergent immune responses. Our findings underscore the need for greater investigation into bacterial heterogeneity to better appreciate the diversity in host-pathogen interactions during TB disease.

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.

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.

Impaired resolution of blood transcriptomes through tuberculosis treatment with diabetes comorbidity

BACKGROUND

People with diabetes are more likely to develop tuberculosis (TB) and to have poor TB-treatment outcomes than those without. We previously showed that blood transcriptomes in people with TB-diabetes (TB-DM) co-morbidity have excessive inflammatory and reduced interferon responses at diagnosis. It is unknown whether this persists through treatment and contributes to the adverse outcomes.

METHODS

Pulmonary TB patients recruited in South Africa, Indonesia and Romania were classified as having TB-DM, TB with prediabetes, TB-related hyperglycaemia or TB-only, based on glycated haemoglobin concentration at TB diagnosis and after 6 months of TB treatment. Gene expression in blood at diagnosis and intervals throughout treatment was measured by unbiased RNA-Seq and targeted Multiplex Ligation-dependent Probe Amplification. Transcriptomic data were analysed by longitudinal mixed-model regression to identify whether genes were differentially expressed between clinical groups through time. Predictive models of TB-treatment response across groups were developed and cross-tested.

RESULTS

Gene expression differed between TB and TB-DM patients at diagnosis and was modulated by TB treatment in all clinical groups but to different extents, such that differences remained in TB-DM relative to TB-only throughout. Expression of some genes increased through TB treatment, whereas others decreased: some were persistently more highly expressed in TB-DM and others in TB-only patients. Genes involved in innate immune responses, anti-microbial immunity and inflammation were significantly upregulated in people with TB-DM throughout treatment. The overall pattern of change was similar across clinical groups irrespective of diabetes status, permitting models predictive of TB treatment to be developed.

CONCLUSIONS

Exacerbated transcriptome changes in TB-DM take longer to resolve during TB treatment, meaning they remain different from those in uncomplicated TB after treatment completion. This may indicate a prolonged inflammatory response in TB-DM, requiring prolonged treatment or host-directed therapy for complete cure. Development of transcriptome-based biomarker signatures of TB-treatment response should include people with diabetes for use across populations.

Point-of-care test for tuberculosis: a boon in diagnosis

Rapid diagnosis of tuberculosis (TB) is an effective measure to eradicate this infectious disease worldwide. Traditional methods for screening TB patients do not provide an immediate diagnosis and thus delay treatment. There is an urgent need for the early detection of TB through point-of-care tests (POCTs). Several POCTs are widely available at primary healthcare facilities that assist in TB screening. In addition to the currently used POCTs, advancements in technology have led to the discovery of newer methods that provide accurate and fast information independent of access to laboratory facilities. In the present article, the authors tried to include and describe the potential POCTs for screening TB in patients. Several molecular diagnostic tests, such as nucleic acid amplification tests, including GeneXpert and TB-loop-mediated isothermal amplification, are currently being used as POCTs. Besides these methods, the pathogenic component of Mycobacterium tuberculosis can also be utilized as a biomarker for screening purposes through immunological assays. Similarly, the host immune response to infection has also been utilized as a marker for the diagnosis of TB. These novel biomarkers might include Mtb85, interferon-γ inducible protein-10, volatile organic compounds, acute-phase proteins, etc. Radiological tests have also been observed as POCTs in the TB screening POCT panel. Various POCTs are performed on samples other than sputum, which further eases the screening process. These POCTs should not require large-scale manpower and infrastructure. Hence, POCT should be able to identify patients with M. tuberculosis infection at the primary healthcare level only. There are several other advanced techniques that have been proposed as future POCTs and have been discussed in the present article.

Host-directed immunotherapy of viral and bacterial infections: past, present and future

The advent of COVID-19 and the persistent threat of infectious diseases such as tuberculosis, malaria, influenza and HIV/AIDS remind us of the marked impact that infections continue to have on public health. Some of the most effective protective measures are vaccines but these have been difficult to develop for some of these infectious diseases even after decades of research. The development of drugs and immunotherapies acting directly against the pathogen can be equally challenging, and such pathogen-directed therapeutics have the potential disadvantage of selecting for resistance. An alternative approach is provided by host-directed therapies, which interfere with host cellular processes required for pathogen survival or replication, or target the host immune response to infection (immunotherapies) to either augment immunity or ameliorate immunopathology. Here, we provide a historical perspective of host-directed immunotherapeutic interventions for viral and bacterial infections and then focus on SARS-CoV-2 and Mycobacterium tuberculosis, two major human pathogens of the current era, to indicate the key lessons learned and discuss candidate immunotherapeutic approaches, with a focus on drugs currently in clinical trials.

Scalable transcriptomics analysis with Dask: applications in data science and machine learning

BACKGROUND

Gene expression studies are an important tool in biological and biomedical research. The signal carried in expression profiles helps derive signatures for the prediction, diagnosis and prognosis of different diseases. Data science and specifically machine learning have many applications in gene expression analysis. However, as the dimensionality of genomics datasets grows, scalable solutions become necessary.

METHODS

In this paper we review the main steps and bottlenecks in machine learning pipelines, as well as the main concepts behind scalable data science including those of concurrent and parallel programming. We discuss the benefits of the Dask framework and how it can be integrated with the Python scientific environment to perform data analysis in computational biology and bioinformatics.

RESULTS

This review illustrates the role of Dask for boosting data science applications in different case studies. Detailed documentation and code on these procedures is made available at https://github.com/martaccmoreno/gexp-ml-dask .

CONCLUSION

By showing when and how Dask can be used in transcriptomics analysis, this review will serve as an entry point to help genomic data scientists develop more scalable data analysis procedures.

Viperin impairs the innate immune response through the IRAK1-TRAF6-TAK1 axis to promote Mtb infection

Mycobacterium tuberculosis (Mtb) infection is a long-standing public health threat, and the development of host-directed therapy for eradicating Mtb infection requires better insights into Mtb-host interactions. Viperin [virus-inhibitory protein, endoplasmic reticulum-associated, interferon (IFN) inducible] is an IFN-inducible protein with broad antiviral activities. Here, we demonstrated that Viperin was increased in abundance in patients with lymphatic and pulmonary tuberculosis (TB). Viperin-deficient mice had decreased Mtb bacterial loads and enhanced macrophage responses compared with their wild-type counterparts. Viperin suppressed the formation of a complex containing interleukin-1 receptor-associated kinase 1, TNF receptor-associated factor 6, and transforming growth factor β-activated kinase 1 (TAK1) and inhibited the TAK1-dependent activation of IκB kinase α/β, thereby impairing the production of nitric oxide and proinflammatory cytokines. These results suggest that Viperin promotes Mtb infection by inhibiting host innate immune responses in macrophages, suggesting that Viperin may be a candidate target for adjunct host-directed therapy in patients with TB.

Tuberculosis Treatment Monitoring and Outcome Measures: New Interest and New Strategies

Despite the advent of new diagnostics, drugs and regimens, tuberculosis (TB) remains a global public health threat. A significant challenge for TB control efforts has been the monitoring of TB therapy and determination of TB treatment success. Current recommendations for TB treatment monitoring rely on sputum and culture conversion, which have low sensitivity and long turnaround times, present biohazard risk, and are prone to contamination, undermining their usefulness as clinical treatment monitoring tools and for drug development. We review the pipeline of molecular technologies and assays that serve as suitable substitutes for current culture-based readouts for treatment response and outcome with the potential to change TB therapy monitoring and accelerate drug development.

Transcriptional profiles predict treatment outcome in patients with tuberculosis and diabetes at diagnosis and at two weeks after initiation of anti-tuberculosis treatment

BACKGROUND

Globally, the tuberculosis (TB) treatment success rate is approximately 85%, with treatment failure, relapse and death occurring in a significant proportion of pulmonary TB patients. Treatment success is lower among people with diabetes mellitus (DM). Predicting treatment outcome early after diagnosis, especially in TB-DM patients, would allow early treatment adaptation for individuals and may improve global TB control.

METHODS

Samples were collected in a longitudinal cohort study of adult TB patients from South Africa (n  =  94) and Indonesia (n  =  81), who had concomitant DM (n  =  59), intermediate hyperglycaemia (n  =  79) or normal glycaemia/no DM (n  =  37). Treatment outcome was monitored, and patients were categorized as having a good (cured) or poor (failed, recurrence, died) outcome during treatment and 12 months follow-up. Whole blood transcriptional profiles before, during and at the end of TB treatment were characterized using unbiased RNA-Seq and targeted gene dcRT-MLPA.

FINDINGS

We report differences in whole blood transcriptome profiles, which were observed before initiation of treatment and throughout treatment, between patients with a good versus poor TB treatment outcome. An eight-gene and a 22-gene blood transcriptional signature distinguished patients with a good TB treatment outcome from patients with a poor TB treatment outcome at diagnosis (AUC = 0·815) or two weeks (AUC = 0·834) after initiation of TB treatment, respectively. High accuracy was obtained by cross-validating this signature in an external cohort (AUC = 0·749).

INTERPRETATION

These findings suggest that transcriptional profiles can be used as a prognostic biomarker for treatment failure and success, even in patients with concomitant DM.

FUNDING

The research leading to these results, as part of the TANDEM Consortium, received funding from the European Community's Seventh Framework Programme (FP7/2007-2013 Grant Agreement No. 305279) and the Netherlands Organization for Scientific Research (NWO-TOP Grant Agreement No. 91214038). The research leading to the results presented in the Indian validation cohort was supported by Research Council of Norway Global Health and Vaccination Research (GLOBVAC) projects: RCN 179342, 192534, and 248042, the University of Bergen (Norway).

Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape

Funding

Pathological and protective roles of dendritic cells in Mycobacterium tuberculosis infection: Interaction between host immune responses and pathogen evasion

Dendritic cells (DCs) are principal defense components that play multifactorial roles in translating innate immune responses to adaptive immunity in Mycobacterium tuberculosis (Mtb) infections. The heterogeneous nature of DC subsets follows their altered functions by interacting with other immune cells, Mtb, and its products, enhancing host defense mechanisms or facilitating pathogen evasion. Thus, a better understanding of the immune responses initiated, promoted, and amplified or inhibited by DCs in Mtb infection is an essential step in developing anti-tuberculosis (TB) control measures, such as host-directed adjunctive therapy and anti-TB vaccines. This review summarizes the recent advances in salient DC subsets, including their phenotypic classification, cytokine profiles, functional alterations according to disease stages and environments, and consequent TB outcomes. A comprehensive overview of the role of DCs from various perspectives enables a deeper understanding of TB pathogenesis and could be useful in developing DC-based vaccines and immunotherapies.

Increasing reproducibility, robustness, and generalizability of biomarker selection from meta-analysis using Bayesian methodology

A major limitation of gene expression biomarker studies is that they are not reproducible as they simply do not generalize to larger, real-world, heterogeneous populations. Frequentist multi-cohort gene expression meta-analysis has been frequently used as a solution to this problem to identify biomarkers that are truly differentially expressed. However, the frequentist meta-analysis framework has its limitations-it needs at least 4-5 datasets with hundreds of samples, is prone to confounding from outliers and relies on multiple-hypothesis corrected p-values. To address these shortcomings, we have created a Bayesian meta-analysis framework for the analysis of gene expression data. Using real-world data from three different diseases, we show that the Bayesian method is more robust to outliers, creates more informative estimates of between-study heterogeneity, reduces the number of false positive and false negative biomarkers and selects more generalizable biomarkers with less data. We have compared the Bayesian framework to a previously published frequentist framework and have developed a publicly available R package for use.

Omics Biomarkers for Monitoring Tuberculosis Treatment: A Mini-Review of Recent Insights and Future Approaches

Poor sensitivity of sputum conversion for monitoring tuberculosis (TB) treatment that makes identification of a non-sputum-based biomarker is urgently needed. Monitoring biomarkers in TB treatment is used to decide whether critical thresholds have been reached and helps clinicians to conclude the therapeutic success. In this mini review, we highlight recent studies on omics-related contributes to identifying of a novel biomarker as surrogate markers for the cure and predicting future reactivation risk following TB treatment. We catalogue the studies published to seek the progress made in transcriptomics, proteomics, and metabolomics in pulmonary TB. We also discuss how integrative multi-omics data will provide further understanding and effective TB treatment, such as revealing the interrelationships at multiple molecular levels, facilitating the identification of biologically interconnected processes, and accelerating precision medicine in TB treatment. However, proper validation in prospective longitudinal studies with long-term follow-up and outcome assessment must be conducted before the biomarkers are utilized in clinical practice.

Contribution and Future of High-Throughput Transcriptomics in Battling Tuberculosis

While Tuberculosis (TB) infection remains a serious challenge worldwide, big data and “omic” approaches have greatly contributed to the understanding of the disease. Transcriptomics have been used to tackle a wide variety of queries including diagnosis, treatment evolution, latency and reactivation, novel target discovery, vaccine response or biomarkers of protection. Although a powerful tool, the elevated cost and difficulties in data interpretation may hinder transcriptomics complete potential. Technology evolution and collaborative efforts among multidisciplinary groups might be key in its exploitation. Here, we discuss the main fields explored in TB using transcriptomics, and identify the challenges that need to be addressed for a real implementation in TB diagnosis, prevention and therapy.

A new blood-based RNA signature (R9), for monitoring effectiveness of tuberculosis treatment in a South Indian longitudinal cohort

Tuberculosis (TB) treatment involves a multidrug regimen for six months, and until two months, it is unclear if treatment is effective. This delay can lead to the evolution of drug resistance, lung damage, disease spread, and transmission. We identify a blood-based 9-gene signature using a computational pipeline that constructs and interrogates a genome-wide transcriptome-integrated protein-interaction network. The identified signature is able to determine treatment response at week 1-2 in three independent public datasets. Signature-based R9-score correctly detected treatment response at individual timepoints (204 samples) from a newly developed South Indian longitudinal cohort involving 32 patients with pulmonary TB. These results are consistent with conventional clinical metrics and can discriminate good from poor treatment responders at week 2 (AUC 0.93(0.81-1.00)). In this work, we provide proof of concept that the R9-score can determine treatment effectiveness, making a case for designing a larger clinical study.

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.

Circulating C1q levels in health and disease, more than just a biomarker

C1q is the recognition molecule of the classical pathway of the complement system. By binding to its targets, such as antigen-bound immunoglobulins or C-reactive protein, C1q contributes to the innate defense against infections. However, C1q also plays several other roles beyond its traditional role in complement activation. Circulating levels of C1q are determined in routine diagnostics as biomarker in several diseases. Decreased C1q levels are present in several autoimmune conditions. The decreased levels reflect the consumption of C1q by complement activation and serves as a biomarker for disease activity. In contrast, increased C1q levels are present in infectious and inflammatory diseases and may serve as a diagnostic biomarker. The increased levels of C1q are still incompletely understood but are suggested to modulate the adaptive immune response as C1q is known to impact on the maturation status of antigen-presenting cells and C1q impacts directly on T cells leading to decreased T-cell activity in high C1q conditions. In this review, we provide a comprehensive overview of the current literature on circulating levels of C1q in health and disease, and discuss how C1q can both protect against infections as well as maintain tolerance by regulating adaptive immunity.

Identification of Serum Cytokine Biomarkers Associated with Multidrug Resistant Tuberculosis (MDR-TB)

Existing tools (including GeneXpert) for diagnosis of multidrug resistant TB (MDR-TB) have limited utility when sputum samples for microbiological analyses cannot be obtained. There is the need for immunological biomarkers which could serve as putative diagnostic markers of MDR-TB. We measured and compared the serum cytokine levels of inflammatory cytokines (IFN-γ, TNF-α, IL12p70, IL-17A, granzyme B) and anti-inflammatory cytokines (IL-10, IL-6, IL-4) among MDR-TB, drug-susceptible (DS)-TB and healthy controls (no-TB) using the Human Magnetic Luminex Multiplex Immunoassay. Levels of IFN-γ and IL-4 were respectively 1.5 log lower and 1.9 log higher in MDR-TB compared to DS-TB cases. Moreover, IFN-γ, TNF-α, IL-10, IL-6, and IL-4 levels were significantly higher in individuals with MDR-TB and DS-TB cases compared to healthy controls. Pairs of cytokines, IL-4 and IFN-γ (p = 0.019), IL-4 and TNF (p = 0.019), and Granzyme B and TNF-α (p = 0.019), showed significant positive correlation in MDR-TB. Serum cytokine profiles can be exploited for immunodiagnostics, as made evident by the Interferon Gamma Release Assays (IGRAs) for TB infection. Using area under the curve values, no single or multiple cytokine combinations could discriminate between DS- and MDR-TB in this study. Studies with a larger sample size and more cytokines could better address the issue.

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.

Distinct blood transcriptomic signature of treatment in latent tuberculosis infected individuals at risk of developing active disease

Although only a small fraction will ever develop the active form of tuberculosis (ATB) disease, chemoprophylaxis treatment in latent TB infected (LTBI) individuals is an effective strategy to control pathogen transmission. Characterizing immune responses in LTBI upon chemoprophylactic treatment is important to facilitate treatment monitoring, and thus improve TB control strategies. Here, we studied changes in the blood transcriptome in a cohort of 42 LTBI and 8 ATB participants who received anti-TB therapy. Based on the expression of previously published gene signatures of progression to ATB, we stratified the LTBI cohort in two groups and examined if individuals deemed to be at elevated risk of developing ATB before treatment (LTBI-Risk) differed from others (LTBI-Other). We found that LTBI-Risk and LTBI-Other groups were associated with two distinct transcriptomic treatment signatures, with the LTBI-Risk signature resembling that of treated ATB patients. Notably, overlapping genes between LTBI-Risk and ATB treatment signatures were associated with risk of progression to ATB and interferon (IFN) signaling, and were selectively downregulated upon treatment in the LTBI-Risk but not the LTBI-Other group. Our results suggest that transcriptomic reprogramming following treatment of LTBI is heterogeneous and can be used to distinguish LTBI-Risk individuals from the LTBI cohort at large.

Gene Set Enrichment Analysis Reveals Individual Variability in Host Responses in Tuberculosis Patients

Group-aggregated responses to tuberculosis (TB) have been well characterized on a molecular level. However, human beings differ and individual responses to infection vary. We have combined a novel approach to individual gene set analysis (GSA) with the clustering of transcriptomic profiles of TB patients from seven datasets in order to identify individual molecular endotypes of transcriptomic responses to TB. We found that TB patients differ with respect to the intensity of their hallmark interferon (IFN) responses, but they also show variability in their complement system, metabolic responses and multiple other pathways. This variability cannot be sufficiently explained with covariates such as gender or age, and the molecular endotypes are found across studies and populations. Using datasets from a Cynomolgus macaque model of TB, we revealed that transcriptional signatures of different molecular TB endotypes did not depend on TB progression post-infection. Moreover, we provide evidence that patients with molecular endotypes characterized by high levels of IFN responses (IFN-rich), suffered from more severe lung pathology than those with lower levels of IFN responses (IFN-low). Harnessing machine learning (ML) models, we derived gene signatures classifying IFN-rich and IFN-low TB endotypes and revealed that the IFN-low signature allowed slightly more reliable overall classification of TB patients from non-TB patients than the IFN-rich one. Using the paradigm of molecular endotypes and the ML-based predictions allows more precisely tailored treatment regimens, predicting treatment-outcome with higher accuracy and therefore bridging the gap between conventional treatment and precision medicine.

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.

Exaggerated IL-17A activity in human in vivo recall responses discriminates active tuberculosis from latent infection and cured disease

Host immune responses at the site of Mycobacterium tuberculosis (Mtb) infection can mediate pathogenesis of tuberculosis (TB) and onward transmission of infection. We hypothesized that pathological immune responses would be enriched at the site of host-pathogen interactions modelled by a standardized tuberculin skin test (TST) challenge in patients with active TB compared to those without disease, and interrogated immune responses by genome-wide transcriptional profiling. We show exaggerated interleukin (IL)-17A and Th17 responses among 48 individuals with active TB compared to 191 with latent TB infection, associated with increased neutrophil recruitment and matrix metalloproteinase-1 expression, both involved in TB pathogenesis. Curative antimicrobial treatment reversed these observed changes. Increased IL-1β and IL-6 responses to mycobacterial stimulation were evident in both circulating monocytes and in molecular changes at the site of TST in individuals with active TB, supporting a model in which monocyte-derived IL-1β and IL-6 promote Th17 differentiation within tissues. Modulation of these cytokine pathways may provide a rational strategy for host-directed therapy in active TB.

Exploring a combined biomarker for tuberculosis treatment response: protocol for a prospective observational cohort study

INTRODUCTION

An improved understanding of factors explaining tuberculosis (TB) treatment response is urgently needed to help clinicians optimise and personalise treatment and assist scientists undertaking novel treatment regimen trials. Promising outcome proxy measures, including sputum bacillary load and host immune response, are widely reported with variable results. However, they have not been studied together in combination with antibiotic exposure. The aim of this observational cohort study is to investigate which antibiotic exposures correlate with sputum bacillary load and which with the host immune response. Subsequently, we will explore if these correlations can be used to inform a candidate combined biomarker predicting cure.

METHODS AND ANALYSIS

All patients aged ≥ 18, diagnosed with drug-sensitive pulmonary TB (culture or molecular test), eligible for standard anti-TB treatment, at selected London, UK TB Services, will be invited to participate in this observational cohort study (target sample size=210). Patients will be asked to give blood for host transcriptomics and antibiotic plasma exposure, in addition to standard of care sputum samples for bacillary load. Antibiotic plasma concentrations will be quantified using a validated liquid chromatograph triple quadrupole mass spectrometer (LC-MS/MS) assay and sputum bacillary load by mycobacterial growth incubator tube time to positivity. Expression from a total of 35 prespecified host blood genes will be quantified using NanoString®. Antibiotic exposure, sputum bacillary load and host blood transcriptomic time series data will be analysed using nonlinear mixed-effects models. Correlations between combinations of longitudinal biomarkers and microbiological cure at the end of treatment and remaining relapse free for 1 year thereafter will be analysed using logistic regression and Cox proportional hazard models.

ETHICS AND DISSEMINATION

The observational cohort study has been approved by the UK's HRA REC (20/SW/0007). Written informed consent will be obtained. Results will be disseminated via publication, presentation and through engagement with institutes/companies developing novel anti-TB treatment combinations.

Multi-country evaluation of RISK6, a 6-gene blood transcriptomic signature, for tuberculosis diagnosis and treatment monitoring

There is a crucial need for non-sputum-based TB tests. Here, we evaluate the performance of RISK6, a human-blood transcriptomic signature, for TB screening, triage and treatment monitoring. RISK6 performance was also compared to that of two IGRAs: one based on RD1 antigens (QuantiFERON-TB Gold Plus, QFT-P, Qiagen) and one on recombinant M. tuberculosis HBHA expressed in Mycobacterium smegmatis (IGRA-rmsHBHA). In this multicenter prospective nested case-control study conducted in Bangladesh, Georgia, Lebanon and Madagascar, adult non-immunocompromised patients with bacteriologically confirmed active pulmonary TB (ATB), latent TB infection (LTBI) and healthy donors (HD) were enrolled. ATB patients were followed-up during and after treatment. Blood RISK6 scores were assessed using quantitative real-time PCR and evaluated by area under the receiver-operating characteristic curve (ROC AUC). RISK6 performance to discriminate ATB from HD reached an AUC of 0.94 (95% CI 0.89-0.99), with 90.9% sensitivity and 87.8% specificity, thus achieving the minimal WHO target product profile for a non-sputum-based TB screening test. Besides, RISK6 yielded an AUC of 0.93 (95% CI 0.85-1) with 90.9% sensitivity and 88.5% specificity for discriminating ATB from LTBI. Moreover, RISK6 showed higher performance (AUC 0.90, 95% CI 0.85-0.94) than IGRA-rmsHBHA (AUC 0.75, 95% CI 0.69-0.82) to differentiate TB infection stages. Finally, RISK6 signature scores significantly decreased after 2 months of TB treatment and continued to decrease gradually until the end of treatment reaching scores obtained in HD. We confirmed the performance of RISK6 signature as a triage TB test and its utility for treatment monitoring.

FasL regulatory B-cells during Mycobacterium tuberculosis infection and TB disease

Tuberculosis (TB) disease remains a major health crisis. Infection with Mycobacterium tuberculosis (M.tb) cause a range of diseases ranging from latent infection to active TB disease. This active state of the disease is characterised by the formation of granulomas (a physical barrier in the lung), a structure thought to protect the host by controlling the infection through preventing the growth of the bacilli. Subsequently, the surviving bacteria become inactive and in most cases, TB reactivation is prevented by the immune response of the host. B-cells perform numerous immunological functions beyond antibody production to positively regulate the response to pathogenic assault. A subgroup of B-cells with regulatory functions express death-inducing ligands, such as Fas ligand (FasL). Expression and interaction of the Fas receptor-ligand promotes the induction of apoptosis and the induction of T-cell tolerance. Here, we focus on the significance of B-cells by addressing their FasL phenotype and regulatory functions during TB, with reference to disease in humans, non-human primates and mice.

Interferons: Tug of War Between Bacteria and Their Host

Type I and III interferons (IFNs) are archetypally antiviral cytokines that are induced in response to recognition of foreign material by pattern recognition receptors (PRRs). Though their roles in anti-viral immunity are well established, recent evidence suggests that they are also crucial mediators of inflammatory processes during bacterial infections. Type I and III IFNs restrict bacterial infection in vitro and in some in vivo contexts. IFNs mainly function through the induction of hundreds of IFN-stimulated genes (ISGs). These include PRRs and regulators of antimicrobial signaling pathways. Other ISGs directly restrict bacterial invasion or multiplication within host cells. As they regulate a diverse range of anti-bacterial host responses, IFNs are an attractive virulence target for bacterial pathogens. This review will discuss the current understanding of the bacterial effectors that manipulate the different stages of the host IFN response: IFN induction, downstream signaling pathways, and target ISGs.

Host transcriptional response to TB preventive therapy differentiates two sub-groups of IGRA-positive individuals

We hypothesised that individuals with immunological sensitisation to Mycobacterium tuberculosis (Mtb), conventionally regarded as evidence of latent tuberculosis infection (LTBI), would demonstrate binary responses to preventive therapy (PT), reflecting the differential immunological consequences of the sterilisation of viable infection in those with active Mtb infection versus no Mtb killing in those who did not harbour viable bacilli. We investigated longitudinal whole blood transcriptional profile responses to PT of Interferon gamma release assay (IGRA)-positive tuberculosis contacts and IGRA-negative, tuberculosis-unexposed controls. Longitudinal unsupervised clustering analysis with a subset of 474 most variable genes in antigen-stimulated blood separated the IGRA-positive participants into two distinct subgroups, one of which clustered with the IGRA-negative controls. 117 probes were differentially expressed over time between the two cluster groups, many of them associated with immunological pathways important in mycobacterial control. We contend that the differential host RNA response reflects lack of Mtb viability in the group that clustered with the IGRA-negative unexposed controls, and Mtb viability in the group (1/3 of IGRA-positives) that clustered away. Gene expression patterns in the blood of IGRA-positive individuals emerging during the course of PT, which reflect Mtb viability, could have major implications in the identification of risk of progression, treatment stratification and biomarker development.

B-Cells and Antibodies as Contributors to Effector Immune Responses in Tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is still a major threat to mankind, urgently requiring improved vaccination and therapeutic strategies to reduce TB-disease burden. Most present vaccination strategies mainly aim to induce cell-mediated immunity (CMI), yet a series of independent studies has shown that B-cells and antibodies (Abs) may contribute significantly to reduce the mycobacterial burden. Although early studies using B-cell knock out animals did not support a major role for B-cells, more recent studies have provided new evidence that B-cells and Abs can contribute significantly to host defense against Mtb. B-cells and Abs exist in many different functional subsets, each equipped with unique functional properties. In this review, we will summarize current evidence on the contribution of B-cells and Abs to immunity toward Mtb, their potential utility as biomarkers, and their functional contribution to Mtb control.

Gastrointestinal microbiota composition predicts peripheral inflammatory state during treatment of human tuberculosis

The composition of the gastrointestinal microbiota influences systemic immune responses, but how this affects infectious disease pathogenesis and antibiotic therapy outcome is poorly understood. This question is rarely examined in humans due to the difficulty in dissociating the immunologic effects of antibiotic-induced pathogen clearance and microbiome alteration. Here, we analyze data from two longitudinal studies of tuberculosis (TB) therapy (35 and 20 individuals) and a cross sectional study from 55 healthy controls, in which we collected fecal samples (for microbiome analysis), sputum (for determination of Mycobacterium tuberculosis (Mtb) bacterial load), and peripheral blood (for transcriptomic analysis). We decouple microbiome effects from pathogen sterilization by comparing standard TB therapy with an experimental TB treatment that did not reduce Mtb bacterial load. Random forest regression to the microbiome-transcriptome-sputum data from the two longitudinal datasets reveals that renormalization of the TB inflammatory state is associated with Mtb pathogen clearance, increased abundance of Clusters IV and XIVa Clostridia, and decreased abundance of Bacilli and Proteobacteria. We find similar associations when applying machine learning to peripheral gene expression and microbiota profiling in the independent cohort of healthy individuals. Our findings indicate that antibiotic-induced reduction in pathogen burden and changes in the microbiome are independently associated with treatment-induced changes of the inflammatory response of active TB, and the response to antibiotic therapy may be a combined effect of pathogen killing and microbiome driven immunomodulation.

Antibiotic therapy can lead to pathogen clearance, but also to alterations in the gut microbiota and systemic immune responses. Here, the authors analyze data from patients with tuberculosis and healthy subjects to show that pathogen clearance and gut microbiota alterations are independently associated with antibiotic-induced changes of the inflammatory response of active tuberculosis.

The Peripheral Blood Transcriptome Is Correlated With PET Measures of Lung Inflammation During Successful Tuberculosis Treatment

Pulmonary tuberculosis (PTB) is characterized by lung granulomas, inflammation and tissue destruction. Here we used within-subject peripheral blood gene expression over time to correlate with the within-subject lung metabolic activity, as measured by positron emission tomography (PET) to identify biological processes and pathways underlying overall resolution of lung inflammation. We used next-generation RNA sequencing and [¹⁸F]FDG PET-CT data, collected at diagnosis, week 4, and week 24, from 75 successfully cured PTB patients, with the [¹⁸F]FDG activity as a surrogate for lung inflammation. Our linear mixed-effects models required that for each individual the slope of the line of [¹⁸F]FDG data in the outcome and the slope of the peripheral blood transcript expression data correlate, i.e., the slopes of the outcome and explanatory variables had to be similar. Of 10,295 genes that changed as a function of time, we identified 639 genes whose expression profiles correlated with decreasing [¹⁸F]FDG uptake levels in the lungs. Gene enrichment over-representation analysis revealed that numerous biological processes were significantly enriched in the 639 genes, including several well known in TB transcriptomics such as platelet degranulation and response to interferon gamma, thus validating our novel approach. Others not previously associated with TB pathobiology included smooth muscle contraction, a set of pathways related to mitochondrial function and cell death, as well as a set of pathways connecting transcription, translation and vesicle formation. We observed up-regulation in genes associated with B cells, and down-regulation in genes associated with platelet activation. We found 254 transcription factor binding sites to be enriched among the 639 gene promoters. In conclusion, we demonstrated that of the 10,295 gene expression changes in peripheral blood, only a subset of 639 genes correlated with inflammation in the lungs, and the enriched pathways provide a description of the biology of resolution of lung inflammation as detectable in peripheral blood. Surprisingly, resolution of PTB inflammation is positively correlated with smooth muscle contraction and, extending our previous observation on mitochondrial genes, shows the presence of mitochondrial stress. We focused on pathway analysis which can enable therapeutic target discovery and potential modulation of the host response to TB.

Transcriptomic Profiles of Confirmed Pediatric Tuberculosis Patients and Household Contacts Identifies Active Tuberculosis, Infection, and Treatment Response Among Indian Children

BACKGROUND

Gene expression profiling is emerging as a tool for tuberculosis diagnosis and treatment response monitoring, but limited data specific to Indian children and incident tuberculosis infection (TBI) exist.

METHODS

Sixteen pediatric Indian tuberculosis cases were age- and sex-matched to 32 tuberculosis-exposed controls (13 developed incident TBI without subsequent active tuberculosis). Longitudinal samples were collected for ribonucleic acid sequencing. Differential expression analysis generated gene lists that identify tuberculosis diagnosis and tuberculosis treatment response. Data were compared with published gene lists. Population-specific risk score thresholds were calculated.

RESULTS

Seventy-one genes identified tuberculosis diagnosis and 25 treatment response. Within-group expression was partially explained by age, sex, and incident TBI. Transient changes in gene expression were identified after both infection and treatment. Application of 27 published gene lists to our data found variable performance for tuberculosis diagnosis (sensitivity 0.38-1.00, specificity 0.48-0.93) and treatment response (sensitivity 0.70-0.80, specificity 0.40-0.80). Our gene lists found similarly variable performance when applied to published datasets for diagnosis (sensitivity 0.56-0.85, specificity 0.50-0.85) and treatment response (sensitivity 0.49- 0.86, specificity 0.50-0.84).

CONCLUSIONS

Gene expression profiles among Indian children with confirmed tuberculosis were distinct from adult-derived gene lists, highlighting the importance of including distinct populations in differential gene expression models.

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.

Impact of Intermediate Hyperglycemia and Diabetes on Immune Dysfunction in Tuberculosis

BACKGROUND

People with diabetes have an increased risk of developing active tuberculosis (TB) and are more likely to have poor TB-treatment outcomes, which may impact on control of TB as the prevalence of diabetes is increasing worldwide. Blood transcriptomes are altered in patients with active TB relative to healthy individuals. The effects of diabetes and intermediate hyperglycemia (IH) on this transcriptomic signature were investigated to enhance understanding of immunological susceptibility in diabetes-TB comorbidity.

METHODS

Whole blood samples were collected from active TB patients with diabetes (glycated hemoglobin [HbA1c] ≥6.5%) or IH (HbA1c = 5.7% to <6.5%), TB-only patients, and healthy controls in 4 countries: South Africa, Romania, Indonesia, and Peru. Differential blood gene expression was determined by RNA-seq (n = 249).

RESULTS

Diabetes increased the magnitude of gene expression change in the host transcriptome in TB, notably showing an increase in genes associated with innate inflammatory and decrease in adaptive immune responses. Strikingly, patients with IH and TB exhibited blood transcriptomes much more similar to patients with diabetes-TB than to patients with only TB. Both diabetes-TB and IH-TB patients had a decreased type I interferon response relative to TB-only patients.

CONCLUSIONS

Comorbidity in individuals with both TB and diabetes is associated with altered transcriptomes, with an expected enhanced inflammation in the presence of both conditions, but also reduced type I interferon responses in comorbid patients, suggesting an unexpected uncoupling of the TB transcriptome phenotype. These immunological dysfunctions are also present in individuals with IH, showing that altered immunity to TB may also be present in this group. The TB disease outcomes in individuals with IH diagnosed with TB should be investigated further.

A circRNA-miRNA-mRNA regulatory network associated with the treatment response to tuberculosis

OBJECTIVES

The high morbidity and mortality of tuberculosis (TB) have severe socio-economic consequences, and there is an urgent need to explore the mechanisms driving TB development and progression. The aim of this study was to analyze the regulatory RNAs and target genes involved in TB, in order to identify key genetic biomarkers for diagnosing and treating TB.

METHODS

Circular RNAs (circRNAs), microRNAs (miRNAs) and messenger RNA (mRNAs) expression profiles of TB patients and healthy controls were downloaded from the GEO database. A circRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network was constructed using the differentially expressed circRNAs (DEcircRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs). The DEmRNAs in this network were functionally annotated using GO and KEGG analyses, and ordinal regression analysis was used to identify the genes correlated to the treatment response in TB patients.

RESULTS

We identified 133 DEmRNAs, 37 DEcircRNAs and 173 DEmiRNAs between the TB and healthy controls, from which 30 DECircRNAs, 27 DEmiRNAs and 35 DEmRNAs were used to construct the ceRNA network. CACNA1I, IGF2BP3, LPCAT2, SPOCK2 and IRF2 were significantly correlated with the anti-TB therapeutic response (P < 0.05).

CONCLUSION

A TB-associated DEcircRNA-miRNA-mRNA ceRNA network was constructed, of which some DEmRNAs potentially influence the treatment response.

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.

Inverse correlation between serum complement component C1q levels and whole blood type-1 interferon signature in active tuberculosis and QuantiFERON-positive uveitis: implications for diagnosis

Objectives

To examine the relation between serum C1q levels and blood type‐1 interferon signature (type‐1 IFN signature) in active pulmonary tuberculosis (APTB) and to determine whether combined measurement of serum C1q and type‐1 IFN signature may add to the diagnosis of QuantiFERON‐positive (QFT⁺) patients with uveitis of unknown cause.

Methods

C1q was determined (ELISA) in serum from two distinct Indonesian cohorts, and in total, APTB (n = 72), QFT⁺ uveitis of unknown aetiology (n = 58), QFT⁻ uveitis (n = 51) patients and healthy controls (HC; n = 73) were included. The type‐1 IFN signature scores were previously determined.

Results

Serum C1q was higher in APTB than HC (P < 0.001). APTB patients with uveitis had higher serum C1q than APTB patients without uveitis (P = 0.0207). Serum C1q correlated inversely with type‐1 IFN signature scores in APTB (P = 0.0036, r² = 0.3526), revealing that these biomarkers for active TB disease can be mutually exclusive. Stratification of QFT⁺ patients with uveitis of unknown cause, by serum C1q and type‐1 IFN signature, yielded four groups with different likelihood of suffering from active TB uveitis.

Conclusion

Serum C1q is elevated in APTB, especially in those cases with uveitis. We propose that combined measurement of blood type‐1 IFN signature and serum C1q may provide added value in the diagnosis of active TB disease. Combined measurement of type‐1 IFN signature and serum C1q in QFT⁺ patients without signs of active TB disease, but suffering from uveitis of unknown cause, may be of help to identify cases with low or high likelihood of having active TB uveitis, which may facilitate clinical management decisions.

Gene network in pulmonary tuberculosis based on bioinformatic analysis

BACKGROUND

Pulmonary tuberculosis (PTB) is one of the serious infectious diseases worldwide; however, the gene network involved in the host response remain largely unclear.

METHODS

This study integrated two cohorts profile datasets GSE34608 and GSE83456 to elucidate the potential gene network and signaling pathways in PTB. Differentially expressed genes (DEGs) were obtained for Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis using Metascape database. Protein-Protein Interaction (PPI) network of DEGs was constructed by the online database the Search Tool for the Retrieval of Interacting Genes (STRING). Modules were identified by the plug-in APP Molecular Complex Detection (MCODE) in Cytoscape. GO and KEGG pathway of Module 1 were further analyzed by STRING. Hub genes were selected for further expression validation in dataset GSE19439. The gene expression level was also investigated in the dataset GSE31348 to display the change pattern during the PTB treatment.

RESULTS

Totally, 180 shared DEGs were identified from two datasets. Gene function and KEGG pathway enrichment revealed that DEGs mainly enriched in defense response to other organism, response to bacterium, myeloid leukocyte activation, cytokine production, etc. Seven modules were clustered based on PPI network. Module 1 contained 35 genes related to cytokine associated functions, among which 14 genes, including chemokine receptors, interferon-induced proteins and Toll-like receptors, were identified as hub genes. Expression levels of the hub genes were validated with a third dataset GSE19439. The signature of this core gene network showed significant response to Mycobacterium tuberculosis (Mtb) infection, and correlated with the gene network pattern during anti-PTB therapy.

CONCLUSIONS

Our study unveils the coordination of causal genes during PTB infection, and provides a promising gene panel for PTB diagnosis. As major regulators of the host immune response to Mtb infection, the 14 hub genes are also potential molecular targets for developing PTB drugs.

Epigenetic regulation of apoptosis via the PARK7 interactome in peripheral blood mononuclear cells donated by tuberculosis patients vs. healthy controls and the response to treatment: A systems biology approach

AIMS

The aims of our study were to determine for the first time differentially expressed genes (DEGs) and enriched molecular pathways involving the PARK7 interactome in PBMCs donated from tuberculosis patients.

METHODS

Data on a previously reconstructed PARK7 interactome (Vavougios et al., 2017) from datasets GDS4966 (Case-Control) and GDS4781 (Treatment Series) were retrieved from the Gene Expression Omnibus (GEO) repository. Gene Enrichment analysis was performed via the STRING algorithm and the GeneTrail2 software.

RESULTS

17 and 22 PARK7 interactores were determined as DEGs in the active TB vs HD and Treatment Series subset analyses, correspondingly, associated with significantly enriched pathways (FDR <0.05) involving p53 and PTEN mediated, stress responsive apoptosis regulation pathways. The treatment subset was characterized by the emergence of an additional layer of transcriptional regulation mediated by polycomb proteins among others, as well as TLR-mediated and cytokine survival signaling. Finally, the enrichment of a Parkinson's disease signature including PARK7 interactors was determined by its differential regulation both in the exploratory analyses (FDR = 0.024), as well as the confirmatory analyses (FDR = 1.81e^-243).

CONCLUSIONS

Our in silico analysis revealed for the first time the role of PARK7's interactome in regulating the epigenetics of the PBMC lifecycle and Mtb symbiosis.

An RNA-seq Based Machine Learning Approach Identifies Latent Tuberculosis Patients With an Active Tuberculosis Profile

A better understanding of the response against Tuberculosis (TB) infection is required to accurately identify the individuals with an active or a latent TB infection (LTBI) and also those LTBI patients at higher risk of developing active TB. In this work, we have used the information obtained from studying the gene expression profile of active TB patients and their infected –LTBI- or uninfected –NoTBI- contacts, recruited in Spain and Mozambique, to build a class-prediction model that identifies individuals with a TB infection profile. Following this approach, we have identified several genes and metabolic pathways that provide important information of the immune mechanisms triggered against TB infection. As a novelty of our work, a combination of this class-prediction model and the direct measurement of different immunological parameters, was used to identify a subset of LTBI contacts (called TB-like) whose transcriptional and immunological profiles are suggestive of infection with a higher probability of developing active TB. Validation of this novel approach to identifying LTBI individuals with the highest risk of active TB disease merits further longitudinal studies on larger cohorts in TB endemic areas.

Combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes

Tuberculosis (TB) is a global health concern. Treatment is prolonged, and patients on anti-TB therapy (ATT) often experience treatment failure for various reasons. There is an urgent need to identify signatures for early detection of failure and initiation of a treatment switch.

We investigated how gene biomarkers and/or basic patient characteristics could be used to define signatures for treatment outcomes in Indian adult pulmonary-TB patients treated with standard ATT. Using blood samples at baseline, a 12-gene signature combined with information on gender, previously-diagnosed TB, severe thinness, smoking and alcohol consumption was highly predictive of treatment failure at 6 months. Likewise a 4-protein biomarker signature combined with the same patient characteristics was almost as highly predictive of treatment failure. Combining biomarkers and basic patient characteristics may be useful for predicting and hence identification of treatment failure at an early stage of TB therapy.

Sivakumaran et al. show that a 12-gene signature combined with gender, previously diagnosed tuberculosis (TB), severe thinness, smoking, and alcohol consumption predict the treatment outcome at 6 months. This study suggests that the combination of biomarkers and basic patient characteristics may better predict the treatment failure at an early stage of TB therapy.

A regulatory variant in the C1Q gene cluster is associated with tuberculosis susceptibility and C1qA plasma levels in a South African population

Several genetic studies have implicated genes that encode for components of the innate immune response in tuberculosis (TB) susceptibility. The complement system is an early player in the innate immune response and provides the host with initial protection by promoting phagocytosis of apoptotic or necrotic cells. The C1q molecule is the first component of the classical pathway that leads to the activation of complement by binding to immune complexes and is encoded by the C1Q gene cluster. We investigated variants in this region to determine its association with TB susceptibility. Five single nucleotide polymorphisms (SNPs) (rs12033074, rs631090, rs172378, rs587585, and rs665691) were genotyped using TaqMan® SNP assays in 456 TB cases and 448 healthy controls and analysed by logistic regression models. The rs587585 variant showed a significant additive allelic association where the minor G allele was found more frequently in TB cases than in controls in both the discovery (p = 0.023; OR = 1.30; 95% CI, 1.04-1.64) and validation cohort (p = 0.038; OR = 1.31; 95% CI, 1.22-1.40). In addition, we detected increased C1qA expression when comparing cases and controls (p = 0.037) and linked this to a dosage effect of the G allele, which increased C1qA expression in TB cases. This is the first study to report the association of C1Q gene polymorphisms with progression to tuberculosis.

RISK6, a 6-gene transcriptomic signature of TB disease risk, diagnosis and treatment response

Improved tuberculosis diagnostics and tools for monitoring treatment response are urgently needed. We developed a robust and simple, PCR-based host-blood transcriptomic signature, RISK6, for multiple applications: identifying individuals at risk of incident disease, as a screening test for subclinical or clinical tuberculosis, and for monitoring tuberculosis treatment. RISK6 utility was validated by blind prediction using quantitative real-time (qRT) PCR in seven independent cohorts. Prognostic performance significantly exceeded that of previous signatures discovered in the same cohort. Performance for diagnosing subclinical and clinical disease in HIV-uninfected and HIV-infected persons, assessed by area under the receiver-operating characteristic curve, exceeded 85%. As a screening test for tuberculosis, the sensitivity at 90% specificity met or approached the benchmarks set out in World Health Organization target product profiles for non-sputum-based tests. RISK6 scores correlated with lung immunopathology activity, measured by positron emission tomography, and tracked treatment response, demonstrating utility as treatment response biomarker, while predicting treatment failure prior to treatment initiation. Performance of the test in capillary blood samples collected by finger-prick was noninferior to venous blood collected in PAXgene tubes. These results support incorporation of RISK6 into rapid, capillary blood-based point-of-care PCR devices for prospective assessment in field studies.

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

Monocytes play a critical role during infection with Mycobacterium tuberculosis (Mtb). They are recruited to the lung, where they participate in the control of infection during active tuberculosis (TB). Alternatively, inflammatory monocytes may participate in inflammation or serve as niches for Mtb infection. Monocytes response to infection may vary depending on the particularities of the clinical isolate of Mtb from which they are infected. In this pilot study, we have examined the baseline mRNA profiles of circulating human monocytes from patients with active TB (MoTB) compared with monocytes from healthy individuals (MoCT). Circulating MoTB displayed a pro-inflammatory transcriptome characterized by increased gene expression of genes associated with cytokines, monocytopoiesis, and down-regulation of MHC class II gene expression. In response to in vitro infection with two clinical isolates of the LAM family of Mtb (UT127 and UT205), MoTB displayed an attenuated inflammatory mRNA profile associated with down-regulation the TREM1 signaling pathway. Furthermore, the gene expression signature induced by Mtb UT205 clinical strain was characterized by the enrichment of genes in pathways and biological processes mainly associated with a signature of IFN-inducible genes and the inhibition of cell death mechanisms compared to MoTB-127, which could favor the establishment and survival of Mtb within the monocytes. These results suggest that circulating MoTB have an altered transcriptome that upon infection with Mtb may help to maintain chronic inflammation and infection. Moreover, this functional abnormality of monocytes may also depend on potential differences in virulence of circulating clinical strains of Mtb.