Gene‐Expression Patterns in Whole Blood Identify Subjects at Risk for Recurrent Tuberculosis

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

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

Identification of C. elegans ASNA-1 domains and tissue requirements that differentially influence platinum sensitivity and growth control

ASNA1 plays an essential role in cisplatin chemotherapy response, type 2 diabetes, and heart disease. It is also an important biomarker in the treatment response of many diseases. Biochemically, ASNA1 has two mutually exclusive redox-modulated roles: a tail-anchored protein (TAP) targeting function in the reduced state and a holdase/chaperone function in the oxidized state. Assigning biochemical roles of mammalian ASNA1 to biomedical functions is crucial for successful therapy development. Our previous work showed the relevance of the C. elegans ASNA-1 homolog in modeling cisplatin response and insulin secretion. Here we analyzed two-point mutants in highly conserved residues in C. elegans ASNA-1 and determined their importance in separating the cisplatin response function from its roles in insulin secretion. asna-1(ΔHis164) and asna-1(A63V) point mutants, which both preferentially exist in the oxidized state, displayed cisplatin sensitivity phenotype as well as TAP insertion defect but not an insulin secretion defect. Further, using targeted depletion we analyzed the tissue requirements of asna-1 for C. elegans growth and development. Somatic depletion of ASNA-1 as well as simultaneous depletion of ASNA-1 in neurons and intestines resulted in an L1 arrest. We concluded that, targeting single residues in ASNA-1 affecting Switch I/Switch II domain function, in comparison to complete knockdown counteracted cisplatin resistance without jeopardizing other important biological functions. Taken together, our study shows that effects on health caused by ASNA1 mutations can have different biochemical bases.

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.

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

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.

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

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

Gene expression pattern analysis using dual-color RT-MLPA and integrative genome-wide association studies of eQTL for tuberculosis suscepitibility

Background

When infected with Mycobacterium tuberculosis, only a small proportion of the population will develop active TB, and the role of host genetic factors in different TB infection status was not fully understood.

Methods

Forty-three patients with active tuberculosis and 49 with latent tuberculosis were enrolled in the prospective cohort. Expressing levels of 27 candidate mRNAs, which were previously demonstrated to differentially expressed in latent and active TB, were measured by dual color reverse transcription multiplex ligation dependent probe amplification assay (dcRT-MLPA). Using expression levels of these mRNAs as quantitative traits, associations between expression abundance and genome-wild single nucleotide polymorphisms (SNPs) were calculated. Finally, identified candidate SNPs were further assessed for their associations with TB infection status in a validation cohort with 313 Chinese Han cases.

Results

We identified 9 differentially expressed mRNAs including il7r, il4, il8, tnfrsf1b, pgm5, ccl19, il2ra, marco and fpr1 in the prospective cohort. Through expression quantitative trait loci mapping, we screened out 8 SNPs associated with these mRNAs. Then, CG genotype of the SNP rs62292160 was finally verified to be significantly associated with higher transcription levels of IL4 in LTBI than in TB patients.

Conclusion

We reported that the SNP rs62292160 in Chinese Han population may link to higher expression of il4 in latent tuberculosis. Our findings provided a new genetic variation locus for further exploration of the mechanisms of TB and a possible target for TB genetic susceptibility studies, which might aid the clinical decision to precision treatment of TB.

Association of Plasma Matrix Metalloproteinase and Tissue Inhibitors of Matrix Metalloproteinase Levels With Adverse Treatment Outcomes Among Patients With Pulmonary Tuberculosis

IMPORTANCE

Identifying biomarkers of treatment response is an urgent need in the treatment of tuberculosis (TB). Matrix metalloproteinases (MMPs) and tissue inhibitors of matrix metalloproteinases (TIMPs) are potential diagnostic biomarkers in pulmonary TB (PTB).

OBJECTIVE

To assess whether baseline plasma levels of MMPs and TIMPs are also prognostic biomarkers for adverse treatment outcomes in patients with PTB.

DESIGN, SETTING, AND PARTICIPANTS

Two different cohorts (test and validation) of individuals with PTB were recruited from 2 different sets of primary care centers in Chennai, India, and were followed up for treatment outcomes. Participants were individuals with newly diagnosed TB that was sputum smear and culture positive and drug sensitive. A total of 68 cases and 133 controls were in the test cohort and 20 cases and 40 controls were in the validation cohort. A nested case-control study was performed by matching case patients to control participants in a 1:2 ratio for age, sex, and body mass index. Data for the test cohort was taken from a study performed from 2014 to 2019, and data for the validation cohort, from a study performed from 2008 to 2012. The data analysis was performed from November 2019 to May 2020.

INTERVENTIONS

Individuals with PTB were treated with antituberculosis chemotherapy for 6 months and followed up for 1 year after completion of treatment.

MAIN OUTCOMES AND MEASURES

Individuals with PTB with adverse outcomes (treatment failure, all-cause mortality, or recurrent TB) were defined as cases and those with favorable outcomes (recurrence-free cure) were defined as controls. Plasma levels of MMPs and TIMPs were measured before treatment as potential biomarkers.

RESULTS

In all, 68 cases and 133 matched controls were enrolled in the study (170 [85%] males and 31 [15%] females; median age, 45 years [range, 23-73 years]) in the test cohort and 20 cases with 40 matched controls (51 [85%] males and 9 [15%] females; median age, 45 years [range, 19-61 years]) in the validation cohort. Baseline plasma levels of 5 MMPs and 2 TIMPs in the test cohort and 5 MMPs and all 4 TIMPS in the validation cohort were significantly higher in cases vs controls. In the test cohort, the geometric means (GMs), cases vs controls, were as follows: for MMP-1, 3680 vs 2484 pg/mL (P = .008); for MMP-2, 6523 vs 4762 pg/mL (P < .001); for MMP-7, 3346 vs 2100 pg/mL (P < .001); for MMP-8, 1915 vs 1066 pg/mL (P < .001); for MMP-9, 2774 vs 2336 pg/mL (P = .009); for TIMP-1, 4491 vs 2910 pg/mL (P < .001); and for TIMP-2, 3082 vs 2115 pg/mL (P < .001). In the validation cohort, the GMs, cases vs controls were as follows: for MMP-1, 3680 vs 2484 pg/mL (P < .001); for MMP-2, 6523 vs 4762 pg/mL (P < .001); for MMP-7, 3346 vs 2100 pg/mL (P < .001); for MMP-9, 1915 vs 1066 pg/mL (P < .001); for MMP-13, 2774 vs 2336 pg/mL (P < .001); for TIMP-1, 4491 vs 2910 pg/mL (P = .003); for TIMP-2, 3082 vs 2115 pg/mL (P = .003); for TIMP-3, 2066 vs 1020 pg/mL (P < .001); and for TIMP-4, 2130 vs 694 pg/mL (P < .001). Plasma levels of MMPs and TIMPs were associated with increased risk of adverse outcomes according to both univariate and multivariable analysis in the test cohort (eg, univariate analysis: odds ratio [OR] for MMP-8, 2.04; 95% CI, 1.33-3.14; P = .001; multivariable analysis: OR for MMP-8, 2.16; 95% CI, 1.34-3.47; P = .001). Combined receiver operating characteristic analysis revealed significant area under the curve (AUC), with high sensitivity and specificity in both cohorts (eg, for a combination of MMP-2, MMP-7, and TIMP-1 in the test cohort: sensitivity, 84%; specificity, 83%; and AUC, 0.886; for a combination of MMP-2, MMP-7, TIMP-1, and TIMP-2 in the validation cohort: sensitivity, 85%; specificity, 95%; and AUC, 0.944).

CONCLUSIONS AND RELEVANCE

Baseline plasma MMP and TIMP levels may be correlates of risk and prognostic biomarkers for treatment failure, relapse, and death in individuals with PTB and merit further evaluation as predictive biomarkers for stratification of patients to shortened or intensified treatment regimens.

A blood RNA transcript signature for TB exposure in household contacts

Background

Current tools for diagnosing latent TB infection (LTBI) detect immunological memory of past exposure but are unable to determine whether exposure is recent. We sought to identify a whole-blood transcriptome signature of recent TB exposure.

Methods

We studied household contacts of TB patients; healthy volunteers without recent history of TB exposure; and patients with active TB. We performed whole-blood RNA sequencing (in all), an interferon gamma release assay (IGRA; in contacts and healthy controls) and PET/MRI lung scans (in contacts only). We evaluated differentially-expressed genes in household contacts (log2 fold change ≥1 versus healthy controls; false-discovery rate < 0.05); compared these to differentially-expressed genes seen in the active TB group; and assessed the association of a composite gene expression score to independent exposure/treatment/immunological variables.

Results

There were 186 differentially-expressed genes in household contacts (n = 26, age 22–66, 46% male) compared with healthy controls (n = 5, age 29–38, 100% male). Of these genes, 141 (76%) were also differentially expressed in active TB (n = 14, age 27–69, 71% male). The exposure signature included genes from inflammatory response, type I interferon signalling and neutrophil-mediated immunity pathways; and genes such as BATF2 and SCARF1 known to be associated with incipient TB. The composite gene-expression score was higher in IGRA-positive contacts (P = 0.04) but not related to time from exposure, isoniazid prophylaxis, or abnormalities on PET/MRI (all P > 0.19).

Conclusions

Transcriptomics can detect TB exposure and, with further development, may be an approach of value for epidemiological research and targeting public health interventions.

Performance of metabonomic serum analysis for diagnostics in paediatric tuberculosis

We applied a metabonomic strategy to identify host biomarkers in serum to diagnose paediatric tuberculosis (TB) disease. 112 symptomatic children with presumptive TB were recruited in The Gambia and classified as bacteriologically-confirmed TB, clinically diagnosed TB, or other diseases. Sera were analysed using ¹H nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). Multivariate data analysis was used to distinguish patients with TB from other diseases. Diagnostic accuracy was evaluated using Receiver Operating Characteristic (ROC) curves. Model performance was tested in a validation cohort of 36 children from the UK. Data acquired using ¹H NMR demonstrated a sensitivity, specificity and Area Under the Curve (AUC) of 69% (95% confidence interval [CI], 56-73%), 83% (95% CI, 73-93%), and 0.78 respectively, and correctly classified 20% of the validation cohort from the UK. The most discriminatory MS data showed a sensitivity of 67% (95% CI, 60-71%), specificity of 86% (95% CI, 75-93%) and an AUC of 0.78, correctly classifying 83% of the validation cohort. Amongst children with presumptive TB, metabolic profiling of sera distinguished bacteriologically-confirmed and clinical TB from other diseases. This novel approach yielded a diagnostic performance for paediatric TB comparable to that of Xpert MTB/RIF and interferon gamma release assays.

Global Transcriptome Analysis Identifies a Diagnostic Signature for Early Disseminated Lyme Disease and Its Resolution

A bioinformatics approach was employed to identify transcriptome alterations in the peripheral blood mononuclear cells of well-characterized human subjects who were diagnosed with early disseminated Lyme disease (LD) based on stringent microbiological and clinical criteria. Transcriptomes were assessed at the time of presentation and also at approximately 1 month (early convalescence) and 6 months (late convalescence) after initiation of an appropriate antibiotic regimen. Comparative transcriptomics identified 335 transcripts, representing 233 unique genes, with significant alterations of at least 2-fold expression in acute- or convalescent-phase blood samples from LD subjects relative to healthy donors. Acute-phase blood samples from LD subjects had the largest number of differentially expressed transcripts (187 induced, 54 repressed). This transcriptional profile, which was dominated by interferon-regulated genes, was sustained during early convalescence. 6 months after antibiotic treatment the transcriptome of LD subjects was indistinguishable from that of healthy controls based on two separate methods of analysis. Return of the LD expression profile to levels found in control subjects was concordant with disease outcome; 82% of subjects with LD experienced at least one symptom at the baseline visit compared to 43% at the early convalescence time point and only a single patient (9%) at the 6-month convalescence time point. Using the random forest machine learning algorithm, we developed an efficient computational framework to identify sets of 20 classifier genes that discriminated LD from other bacterial and viral infections. These novel LD biomarkers not only differentiated subjects with acute disseminated LD from healthy controls with 96% accuracy but also distinguished between subjects with acute and resolved (late convalescent) disease with 97% accuracy.IMPORTANCE Lyme disease (LD), caused by Borrelia burgdorferi, is the most common tick-borne infectious disease in the United States. We examined gene expression patterns in the blood of individuals with early disseminated LD at the time of diagnosis (acute) and also at approximately 1 month and 6 months following antibiotic treatment. A distinct acute LD profile was observed that was sustained during early convalescence (1 month) but returned to control levels 6 months after treatment. Using a computer learning algorithm, we identified sets of 20 classifier genes that discriminate LD from other bacterial and viral infections. In addition, these novel LD biomarkers are highly accurate in distinguishing patients with acute LD from healthy subjects and in discriminating between individuals with active and resolved infection. This computational approach offers the potential for more accurate diagnosis of early disseminated Lyme disease. It may also allow improved monitoring of treatment efficacy and disease resolution.

Immune Biomarkers for Diagnosis and Treatment Monitoring of Tuberculosis: Current Developments and Future Prospects

Tuberculosis (TB) treatment monitoring is paramount to clinical decision-making and the host biomarkers appears to play a significant role. The currently available diagnostic technology for TB detection is inadequate. Although GeneXpert detects total DNA present in the sample regardless live or dead bacilli present in clinical samples, all the commercial tests available thus far have low sensitivity. Humoral responses against Mycobacterium tuberculosis (Mtb) antigens are generally low, which precludes the use of serological tests for TB diagnosis, prognosis, and treatment monitoring. Mtb-specific CD4⁺ T cells correlate with Mtb antigen/bacilli burden and hence might serve as good biomarkers for monitoring treatment progress. Omics-based techniques are capable of providing a more holistic picture for disease mechanisms and are more accurate in predicting TB disease outcomes. The current review aims to discuss some of the recent advances on TB biomarkers, particularly host biomarkers that have the potential to diagnose and differentiate active TB and LTBI as well as their use in disease prognosis and treatment monitoring.

Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis

Mycobacterium tuberculosis (M. tuberculosis) infection in humans can cause active disease or latent infection. However, the factors contributing to the maintenance of latent infection vs. disease progression are poorly understood. In this study, we used a genome-wide RNA sequencing (RNA-seq) approach to identify host factors associated with M. tuberculosis infection status and a novel gene signature that can distinguish active disease from latent infection. By RNA-seq, we characterized transcriptional differences in purified protein derivative (PPD)-stimulated peripheral blood mononuclear cells (PBMCs) among three groups: patients with active tuberculosis (ATB), individuals with latent TB infection (LTBI), and TB-uninfected controls (CON). A total of 401 differentially expressed genes enabled grouping of individuals into three clusters. A validation study by quantitative real-time PCR (qRT-PCR) confirmed the differential expression of TNFRSF10C, IFNG, PGM5, EBF3, and A2ML1 between the ATB and LTBI groups. Additional clinical validation was performed to evaluate the diagnostic performance of these five biomarkers using 130 subjects. The 3-gene signature set of TNFRSF10C, EBF3, and A2ML1 enabled correct classification of 91.5% of individuals, with a high sensitivity of 86.2% and specificity of 94.9%. Diagnostic performance of the 3-gene signature set was validated using a clinical cohort of 147 subjects with suspected ATB. The sensitivity and specificity of the 3-gene set for ATB were 82.4 and 92.4%, respectively. In conclusion, we detected distinct gene expression patterns in PBMCs stimulated by PPD depending on the status of M. tuberculosis infection. Furthermore, we identified a 3-gene signature set that could distinguish ATB from LTBI, which may facilitate rapid diagnosis and treatment for more effective disease control.

Constitutive STAT3 phosphorylation and IL-6/IL-10 co-expression are associated with impaired T-cell function in tuberculosis patients

T-cells critically contribute to protection against Mycobacterium tuberculosis infection, and impaired T-cell responses can lead to disease progression. Pro-inflammatory and immunosuppressive cytokines affect T-cells, and fine-tuned regulation of cytokine signaling via the Jak/STAT signaling pathways is crucial for appropriate T-cell function. Constitutive STAT3 phosphorylation as a consequence of aberrant cytokine signaling has been described to occur in pathognomonic T-cell responses in inflammatory and autoimmune diseases. We characterized blood samples from tuberculosis patients (n=28) and healthy contacts (n=28) from Ghana for M. tuberculosis-specific T-cell responses, constitutive cytokine production, and SOCS3 and pSTAT3 expression. Lentiviral modulation of primary CD4+ T-cells was performed to determine the effects of SOCS3 on T-cell functions. T-cells from tuberculosis patients expressed higher levels of IL-10 and IL-6 and lower levels of T helper type (TH)17 cytokines after M. tuberculosis-specific stimulation compared to healthy contacts. In addition, tuberculosis patients had higher IL-10 and IL-6 levels in the supernatants of non-stimulated immune cells and plasma samples compared to healthy contacts. Notably, aberrant cytokine expression was accompanied by high constitutive pSTAT3 levels and SOCS3 expression in T-cells. Multivariate analysis identified an IL-6/IL-10 co-expression-based principal component in tuberculosis patients that correlated with high pSTAT3 levels. SOCS3 contributed to a regulatory component, and tuberculosis patients with high SOCS3 expression showed decreased TH1 cytokine expression and impaired IL-2-induced STAT5 phosphorylation. SOCS3 over-expression in primary CD4+ T-cells confirmed the SOCS3 inhibitory function on IL-2-induced STAT5 phosphorylation. We conclude that constitutive pSTAT3 and high SOCS3 expression are influential factors that indicate impaired T-cell functions in tuberculosis patients.

Highlights on the Application of Genomics and Bioinformatics in the Fight Against Infectious Diseases: Challenges and Opportunities in Africa

Genomics and bioinformatics are increasingly contributing to our understanding of infectious diseases caused by bacterial pathogens such as Mycobacterium tuberculosis and parasites such as Plasmodium falciparum. This ranges from investigations of disease outbreaks and pathogenesis, host and pathogen genomic variation, and host immune evasion mechanisms to identification of potential diagnostic markers and vaccine targets. High throughput genomics data generated from pathogens and animal models can be combined with host genomics and patients’ health records to give advice on treatment options as well as potential drug and vaccine interactions. However, despite accounting for the highest burden of infectious diseases, Africa has the lowest research output on infectious disease genomics. Here we review the contributions of genomics and bioinformatics to the management of infectious diseases of serious public health concern in Africa including tuberculosis (TB), dengue fever, malaria and filariasis. Furthermore, we discuss how genomics and bioinformatics can be applied to identify drug and vaccine targets. We conclude by identifying challenges to genomics research in Africa and highlighting how these can be overcome where possible.

Type 1 interferon-inducible gene expression in QuantiFERON Gold TB-positive uveitis: A tool to stratify a high versus low risk of active tuberculosis?

QuantiFERON-Gold TB (QFT)-positive patients with undetermined cause of uveitis are problematic in terms of whether to diagnose and treat them for tuberculosis (TB). Here, we investigated whether peripheral blood expression of type 1 interferon (IFN)-inducible genes may be of use to stratify QFT-positive patients with uveitis into groups of high versus low risk of having active TB-associated uveitis. We recruited all new uveitis patients in Cipto Mangunkusumo Hospital, Jakarta, Indonesia for one year. We included 12 patients with uveitis and clinically diagnosed active pulmonary TB, 58 QFT-positive patients with uveitis of unknown cause, 10 newly diagnosed sputum-positive active pulmonary TB patients without uveitis and 23 QFT-negative healthy controls. Expression of 35 type 1 IFN-inducible genes was measured in peripheral blood cells from active pulmonary TB patients without uveitis and healthy controls. Differentially expressed genes were identified and used for further clustering analyses of the uveitis groups. A type-1 IFN gene signature score was calculated and the optimal cut-off value for this score to differentiate active pulmonary TB from healthy controls was determined and applied to QFT-positive patients with uveitis of unknown cause. Ten type 1 IFN-inducible genes were differentially expressed between active pulmonary TB and healthy controls. Expression of these 10 genes in QFT-positive patients with uveitis of unknown cause revealed three groups: 1); patients resembling active pulmonary TB, 2); patients resembling healthy controls, and 3); patients displaying an in-between gene expression pattern. A type 1 IFN gene signature score ≥5.61 displayed high sensitivity (100%) and specificity (91%) for identification of active TB. Application of this score to QFT-positive patients with uveitis of unknown cause yielded two groups with expected different likelihood (high vs. low) of having active-TB uveitis, and therefore may be useful in clinical management decisions.

Genetic Resistance to Mycobacterium tuberculosis Infection and Disease

Natural history studies of tuberculosis (TB) have revealed a spectrum of clinical outcomes after exposure to Mycobacterium tuberculosis, the cause of TB. Not all individuals exposed to the bacterium will become diseased and depending on the infection pressure, many will remain infection-free. Intriguingly, complete resistance to infection is observed in some individuals (termed resisters) after intense, continuing M. tuberculosis exposure. After successful infection, the majority of individuals will develop latent TB infection (LTBI). This infection state is currently (and perhaps imperfectly) defined by the presence of a positive tuberculin skin test (TST) and/or interferon gamma release assay (IGRA), but no detectable clinical disease symptoms. The majority of healthy individuals with LTBI are resistant to clinical TB, indicating that infection is remarkably well-contained in these non-progressors. The remaining 5-15% of LTBI positive individuals will progress to active TB. Epidemiological investigations have indicated that the host genetic component contributes to these infection and disease phenotypes, influencing both susceptibility and resistance. Elucidating these genetic correlates is therefore a priority as it may translate to new interventions to prevent, diagnose or treat TB. The most successful approaches in resistance/susceptibility investigation have focused on specific infection and disease phenotypes and the resister phenotype may hold the key to the discovery of actionable genetic variants in TB infection and disease. This review will not only discuss lessons from epidemiological studies, but will also focus on the contribution of epidemiology and functional genetics to human genetic resistance to M. tuberculosis infection and disease.

Type I interferons in tuberculosis: Foe and occasionally friend

Tuberculosis remains one of the leading causes of mortality worldwide, and, despite its clinical significance, there are still significant gaps in our understanding of pathogenic and protective mechanisms triggered by Mycobacterium tuberculosis infection. Type I interferons (IFN) regulate a broad family of genes that either stimulate or inhibit immune function, having both host-protective and detrimental effects, and exhibit well-characterized antiviral activity. Transcriptional studies have uncovered a potential deleterious role for type I IFN in active tuberculosis. Since then, additional studies in human tuberculosis and experimental mouse models of M. tuberculosis infection support the concept that type I IFN promotes both bacterial expansion and disease pathogenesis. More recently, studies in a different setting have suggested a putative protective role for type I IFN. In this study, we discuss the mechanistic and contextual factors that determine the detrimental versus beneficial outcomes of type I IFN induction during M. tuberculosis infection, from human disease to experimental mouse models of tuberculosis.

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

To better understand the host immune response involved in the progression from latent tuberculosis infection (LTBI) to active tuberculosis (TB) and identify the potential signatures for discriminating TB from LTBI, we performed a genome-wide transcriptional profile of Mycobacterium tuberculosis (M.TB)–specific antigens-stimulated peripheral blood mononuclear cells (PBMCs) from patients with TB, LTBI individuals and healthy controls (HCs). A total of 209 and 234 differentially expressed genes were detected in TB vs. LTBI and TB vs. HCs, respectively. Nineteen differentially expressed genes with top fold change between TB and the other 2 groups were validated using quantitative real-time PCR (qPCR), and showed 94.7% consistent expression pattern with microarray test. Six genes were selected for further validation in an independent sample set of 230 samples. Expression of the resistin (RETN) and kallikrein 1 (KLK1) genes showed the greatest difference between the TB and LTBI or HC groups (P < 0.0001). Receiver operating characteristic curve (ROC) analysis showed that the areas under the curve (AUC) for RETN and KLK1 were 0.844 (0.783–0.904) and 0.833 (0.769–0.897), respectively, when discriminating TB from LTBI. The combination of these two genes achieved the best discriminative capacity [AUC = 0.916 (0.872–0.961)], with a sensitivity of 71.2% (58.7%–81.7%) and a specificity of 93.6% (85.7%–97.9%). Our results provide a new potentially diagnostic signature for discriminating TB and LTBI and have important implications for better understanding the pathogenesis involved in the transition from latent infection to TB activation.

Suppressor of Cytokine Signaling 3 in Macrophages Prevents Exacerbated Interleukin-6-Dependent Arginase-1 Activity and Early Permissiveness to Experimental Tuberculosis

Suppressor of cytokine signaling 3 (SOCS3) is a feedback inhibitor of interleukin (IL)-6 signaling in macrophages. In the absence of this molecule, macrophages become extremely prone to an IL-6-dependent expression of arginase-1 (Arg1) and nitric oxide synthase (NOS)2, the prototype markers for alternative or classical macrophage activation, respectively. Because both enzymes are antipodean macrophage effector molecules in Mycobacterium tuberculosis (Mtb) infection, we assessed the relevance of SOCS3 for macrophage activation during experimental tuberculosis using macrophage-specific SOCS3-deficient (LysM^creSOCS3^loxP/loxP) mice. Aerosol infection of LysM^creSOCS3^loxP/loxP mice resulted in remarkably higher bacterial loads in infected lungs and exacerbated pulmonary inflammation. This increased susceptibility to Mtb infection was accompanied by enhanced levels of both classical and alternative macrophage activation. However, high Arg1 expression preceded the increased induction of NOS2 and at early time points of infection mycobacteria were mostly found in cells positive for Arg1. This sequential activation of Arg1 and NOS2 expression in LysM^creSOCS3^loxP/loxP mice appears to favor the initial replication of Mtb particularly in Arg1-positive cells. Neutralization of IL-6 in Mtb-infected LysM^creSOCS3^loxP/loxP mice reduced arginase activity and restored control of mycobacterial replication in LysM^creSOCS3^loxP/loxP mice. Our data reveal an unexpected role of SOCS3 during experimental TB: macrophage SOCS3 restrains early expression of Arg1 and helps limit Mtb replication in resident lung macrophages, thereby limiting the growth of mycobacteria. Together, SOCS3 keeps IL-6-dependent divergent macrophage responses such as Nos2 and Arg1 expression under control and safeguard protective macrophage effector mechanisms.

Host transcriptional responses following ex vivo re-challenge with Mycobacterium tuberculosis vary with disease status

The identification of immune correlates that are predictive of disease outcome for tuberculosis remains an ongoing challenge. To address this issue, we evaluated gene expression profiles from peripheral blood mononuclear cells following ex vivo challenge with Mycobacterium tuberculosis, among participants with active TB disease (ATBD, n = 10), latent TB infection (LTBI, n = 10), and previous active TB disease (after successful treatment; PTBD, n = 10), relative to controls (n = 10). Differential gene expression profiles were assessed by suppression-subtractive hybridization, dot blot, real-time polymerase chain reaction, and the comparative cycle threshold methods. Comparing ATBD to control samples, greater fold-increases of gene expression were observed for a number of chemotactic factors (CXCL1, CXCL3, IL8, MCP1, MIP1α). ATBD was also associated with higher IL1B gene expression, relative to controls. Among LTBI samples, gene expression of several chemotactic factors (CXCL2, CXCL3, IL8) was similarly elevated, compared to individuals with PTBD. Our results demonstrated that samples from participants with ATBD and LTBI have distinct gene expression profiles in response to ex vivo M. tuberculosis infection. These findings indicate the value in further characterizing the peripheral responses to M. tuberculosis challenge as a route to defining immune correlates of disease status or outcome.

Clinical and genomic responses to ultra-short course chemotherapy in spinal tuberculosis

Traditional treatments for spinal tuberculosis (TB) involve chemotherapy and surgery. In the present study, it has been identified that chemotherapy lasting <6 months [ultra-short course chemotherapy (UCCT)], rather than the 6-18 months of the traditional regimen, is effective in sustaining TB clearance following complete surgical debridement. This current study aims to compare the changes in peripheral blood gene expression prior to and following UCCT, subsequent to complete debridement of spinal TB lesions. The study includes 5 patients without TB and 27 patients with spinal, divided into three groups: Group 1 (untreated group, n=8); group 2 (UCCT treatment group, n=9); and group 3 (UCCT treatment 1 year follow-up group, n=10). Gene changes were detected using DNA microarray analysis, confirmed through reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and the results were examined using the DAVID Knowledgebase to identify the pathways and functions of differentially expressed genes. TB lesions were active in group 1, while groups 2 and 3 showed no signs of active TB, as indicated by clinical manifestations and imaging. Comparison of the transcription profiles of the control and study groups showed that treatment of spinal TB resulted in upregulation of genes that are associated with immune response pathways; RT-qPCR produced similar findings. In conclusion, these results indicate that UCCT is an effective treatment against TB following complete surgical debridement. Furthermore, DNA microarray analysis proved a useful tool to evaluate the effects of spinal TB treatment on the expression of genes associated with immune response pathways.

Mass spectrometry applied to the identification of Mycobacterium tuberculosis and biomarker discovery

An adequate and effective tuberculosis (TB) diagnosis system has been identified by the World Health Organization as a priority in the fight against this disease. Over the years, several methods have been developed to identify the bacillus, but bacterial culture remains one of the most affordable methods for most countries. For rapid and accurate identification, however, it is more feasible to implement molecular techniques, taking advantage of the availability of public databases containing protein sequences. Mass spectrometry (MS) has become an interesting technique for the identification of TB. Here, we review some of the most widely employed methods for identifying Mycobacterium tuberculosis and present an update on MS applied for the identification of mycobacterial species.

Microarray and network-based identification of functional modules and pathways of active tuberculosis

Diagnose of active tuberculosis (TB) is challenging and treatment response is also difficult to efficiently monitor. The aim of this study was to use an integrated analysis of microarray and network-based method to the samples from publically available datasets to obtain a diagnostic module set and pathways in active TB. Towards this goal, background protein-protein interactions (PPI) network was generated based on global PPI information and gene expression data, following by identification of differential expression network (DEN) from the background PPI network. Then, ego genes were extracted according to the degree features in DEN. Next, module collection was conducted by ego gene expansion based on EgoNet algorithm. After that, differential expression of modules between active TB and controls was evaluated using random permutation test. Finally, biological significance of differential modules was detected by pathways enrichment analysis based on Reactome database, and Fisher's exact test was implemented to extract differential pathways for active TB. Totally, 47 ego genes and 47 candidate modules were identified from the DEN. By setting the cutoff-criteria of gene size >5 and classification accuracy ≥0.9, 7 ego modules (Module 4, Module 7, Module 9, Module 19, Module 25, Module 38 and Module 43) were extracted, and all of them had the statistical significance between active TB and controls. Then, Fisher's exact test was conducted to capture differential pathways for active TB. Interestingly, genes in Module 4, Module 25, Module 38, and Module 43 were enriched in the same pathway, formation of a pool of free 40S subunits. Significant pathway for Module 7 and Module 9 was eukaryotic translation termination, and for Module 19 was nonsense mediated decay enhanced by the exon junction complex (EJC). Accordingly, differential modules and pathways might be potential biomarkers for treating active TB, and provide valuable clues for better understanding of molecular mechanism of active TB.

Early Whole Blood Transcriptional Signatures Are Associated with Severity of Lung Inflammation in Cynomolgus Macaques with Mycobacterium tuberculosis Infection

Whole blood transcriptional profiling offers great diagnostic and prognostic potential. Although studies identified signatures for pulmonary tuberculosis (TB) and transcripts that predict the risk for developing active TB in humans, the early transcriptional changes immediately following Mycobacterium tuberculosis infection have not been evaluated. We evaluated the gene expression changes in the cynomolgus macaque model of TB, which recapitulates all clinical aspects of human M. tuberculosis infection, using a human microarray and analytics platform. We performed genome-wide blood transcriptional analysis on 38 macaques at 11 postinfection time points during the first 6 mo of M. tuberculosis infection. Of 6371 differentially expressed transcripts between preinfection and postinfection, the greatest change in transcriptional activity occurred 20-56 d postinfection, during which fluctuation of innate and adaptive immune response-related transcripts was observed. Modest transcriptional differences between active TB and latent infection were observed over the time course with substantial overlap. The pattern of module activity previously published for human active TB was similar in macaques with active disease. Blood transcript activity was highly correlated with lung inflammation (lung [¹⁸F]fluorodeoxyglucose [FDG] avidity) measured by positron emission tomography and computed tomography at early time points postinfection. The differential signatures between animals with high and low lung FDG were stronger than between clinical outcomes. Analysis of preinfection signatures of macaques revealed that IFN signatures could influence eventual clinical outcomes and lung FDG avidity, even before infection. Our data support that transcriptional changes in the macaque model are translatable to human M. tuberculosis infection and offer important insights into early events of M. tuberculosis infection.

High-throughput and computational approaches for diagnostic and prognostic host tuberculosis biomarkers

High-throughput techniques strive to identify new biomarkers that will be useful for the diagnosis, treatment, and prevention of tuberculosis (TB). However, their analysis and interpretation pose considerable challenges. Recent developments in the high-throughput detection of host biomarkers in TB are reported in this review.

Levels of microRNA miR-16 and miR-155 are altered in serum of patients with tuberculosis and associate with responses to therapy

Identification of blood biomarkers that can be useful for predicting Mycobacterium tuberculosis (M.TB) infection, effect of therapy and Multi Drug Resistant (MDR) TB infected individuals is clinically useful for combating tuberculosis epidemic. In this study, we have evaluated the levels of selected miRNAs in serum of TB and MDR TB patients. In addition, we have studied their levels in serum of patients post-therapy. The levels of 4-miRNAs (miR-16, miR-29a, miR-125b and miR-155) were measured in 30 newly diagnosed TB patients, 19 Multi Drug Resistant (MDR) TB patients, 10 patients who completed TB therapy and were TB negative. 30 healthy individuals were recruited as controls. The levels of the miRNAs were estimated by qRT-PCR. Of the four miRNAs studied, the levels of miR-16 were significantly elevated and miR-155 were significantly reduced in serum of TB patients as compared to uninfected controls. The Receiver Operating Characteristic (ROC) curve of miR-16 and miR-155 exhibited a significant distinguishing efficiency with an AUC value of 1 (95% CI, 1 to 1) and 0.967 (95% CI, 0.92-1.04) respectively. Following the therapy, the levels of miR-16 and miR-155 returned to those observed in healthy subjects. In patients with MDR TB, miR-155 was lower as compared to healthy controls and TB treated group but higher as compared to TB naïve patients. miR-16 levels were lowest in serum of MDR TB patients compared to TB naïve, TB treated group and healthy controls. In conclusion, miR-16 and miR-155 in serum may act as surrogate biomarker for studying TB infection, progression of therapy and MDR TB.

The Transcriptional Signature of Active Tuberculosis Reflects Symptom Status in Extra-Pulmonary and Pulmonary Tuberculosis

Background

Mycobacterium tuberculosis infection is a leading cause of infectious death worldwide. Gene-expression microarray studies profiling the blood transcriptional response of tuberculosis (TB) patients have been undertaken in order to better understand the host immune response as well as to identify potential biomarkers of disease. To date most of these studies have focused on pulmonary TB patients with gene-expression profiles of extra-pulmonary TB patients yet to be compared to those of patients with pulmonary TB or sarcoidosis.

Methods

A novel cohort of patients with extra-pulmonary TB and sarcoidosis was recruited and the transcriptional response of these patients compared to those with pulmonary TB using a variety of transcriptomic approaches including testing a previously defined 380 gene meta-signature of active TB.

Results

The 380 meta-signature broadly differentiated active TB from healthy controls in this new dataset consisting of pulmonary and extra-pulmonary TB. The top 15 genes from this meta-signature had a lower sensitivity for differentiating extra-pulmonary TB from healthy controls as compared to pulmonary TB. We found the blood transcriptional responses in pulmonary and extra-pulmonary TB to be heterogeneous and to reflect the extent of symptoms of disease.

Conclusions

The transcriptional signature in extra-pulmonary TB demonstrated heterogeneity of gene expression reflective of symptom status, while the signature of pulmonary TB was distinct, based on a higher proportion of symptomatic individuals. These findings are of importance for the rational design and implementation of mRNA based TB diagnostics.

SOCS3 revisited: a broad regulator of disease, now ready for therapeutic use?

Since their discovery, SOCS have been characterised as regulatory cornerstones of intracellular signalling. While classically controlling the JAK/STAT pathway, their inhibitory effects are documented across several cascades, underpinning their essential role in homeostatic maintenance and disease. After 20 years of extensive research, SOCS3 has emerged as arguably the most important family member, through its regulation of both cytokine- and pathogen-induced cascades. In fact, low expression of SOCS3 is associated with autoimmunity and oncogenesis, while high expression is linked to diabetes and pathogenic immune evasion. The induction of SOCS3 by both viruses and bacteria and its impact upon inflammatory disorders, underscores this protein's increasing clinical potential. Therefore, with the aim of highlighting SOCS3 as a therapeutic target for future development, this review revisits its multi-faceted immune regulatory functions and summarises its role in a broad ranges of diseases.

Challenges in the clinical assessment of novel tuberculosis drugs

To tackle the global TB epidemic effectively, novel treatment strategies are critically needed to shorten the duration of TB therapy and treat drug-resistant TB. Drug development for TB, stymied for decades, has enjoyed a renaissance over the past several years. However, the development of new TB regimens is hindered by the limitations in our understanding and use of preclinical models; the paucity of accurate, early surrogate markers of cure, and challenges in untangling the individual contributions of drugs to multidrug regimens in a complex, multi-compartment disease. Lack of profit motive, advocacy, and imagination has contributed mightily to the dearth of drugs we have on the shelf to treat this ancient disease. Areas that will speed the development of new regimens for TB include novel murine and in vitro pharmacodynamics models, clinical endpoints that are not culture-based, innovative clinical trial designs, and an infusion of much-needed funding.

Diagnostic 'omics' for active tuberculosis

The decision to treat active tuberculosis (TB) is dependent on microbiological tests for the organism or evidence of disease compatible with TB in people with a high demographic risk of exposure. The tuberculin skin test and peripheral blood interferon-γ release assays do not distinguish active TB from a cleared or latent infection. Microbiological culture of mycobacteria is slow. Moreover, the sensitivities of culture and microscopy for acid-fast bacilli and nucleic acid detection by PCR are often compromised by difficulty in obtaining samples from the site of disease. Consequently, we need sensitive and rapid tests for easily obtained clinical samples, which can be deployed to assess patients exposed to TB, discriminate TB from other infectious, inflammatory or autoimmune diseases, and to identify subclinical TB in HIV-1 infected patients prior to commencing antiretroviral therapy. We discuss the evaluation of peripheral blood transcriptomics, proteomics and metabolomics to develop the next generation of rapid diagnostics for active TB. We catalogue the studies published to date seeking to discriminate active TB from healthy volunteers, patients with latent infection and those with other diseases. We identify the limitations of these studies and the barriers to their adoption in clinical practice. In so doing, we aim to develop a framework to guide our approach to discovery and development of diagnostic biomarkers for active TB.

A review of clinical models for the evaluation of human TB vaccines

While much progress has been made in the fight against the scourge of tuberculosis (TB), we are still some way from reaching the ambitious targets of eliminating it as a global public health problem by the mid twenty-first century. A new and effective vaccine that protects against pulmonary TB disease will be an essential element of any control strategy. Over a dozen vaccines are currently in development, but recent efficacy trial data from one of the most advanced candidates have been disappointing. Limitations of current preclinical animal models exist, together with a lack of a complete understanding of host immunity to TB or robust correlates of disease risk and protection. Therefore, in the context of such obstacles, we discuss the lessons identified from recent efficacy trials, current concepts of biomarkers and correlates of protection, the potential of innovative clinical models such as human challenge and conducting trials in high-incidence settings to evaluate TB vaccines in humans, and the use of systems vaccinology and novel technologies including transcriptomics and metabolomics, that may facilitate their utility.

Transcriptional profiles discriminate patients with pulmonary tuberculosis from non-tuberculous individuals depending on the presence of non-insulin diabetes mellitus

Our objective was to identify transcriptional biomarkers in peripheral blood mononuclear cells (PBMC) that discriminate individuals with latent tuberculosis infection (LTBI) from those with pulmonary tuberculosis (PTB) in subjects with non-insulin-dependent diabetes mellitus (NIDDM) and in individuals without NIDDM. Using gene expression microarrays we identified differentially expressed genes from lungs of mice infected with Mycobacterium tuberculosis (Mtb) or a mutant (ΔsigH) representing a non-inflammatory model. Genes expressed in blood, with inflammatory related functions were evaluated in humans by RT-qPCR. NCF1 and ORM transcripts have the better discriminatory capacity to identify PTB subjects from LTBI and non-infected controls (NICs) independently of the presence of NIDDM. The sequential evaluation of the mRNA levels of NCF1 and ORM as multiple diagnostic tests showed 95% Sensitivity (Se) and 80% Specificity (Sp). In addition, FPR2 promises to be a good biomarker for the PTB detection in subjects with NIDDM (Se=100%; Sp=90%).

T cells and adaptive immunity to Mycobacterium tuberculosis in humans

The adaptive immune response mediated by T cells is critical for control of Mycobacterium tuberculosis (M. tuberculosis) infection in humans. However, the M. tuberculosis antigens and host T-cell responses that are required for an effective adaptive immune response to M. tuberculosis infection are yet to be defined. Here, we review recent findings on CD4(+) and CD8(+) T-cell responses to M. tuberculosis infection and examine the roles of distinct M. tuberculosis-specific T-cell subsets in control of de novo and latent M. tuberculosis infection, and in the evolution of T-cell immunity to M. tuberculosis in response to tuberculosis treatment. In addition, we discuss recent studies that elucidate aspects of M. tuberculosis-specific adaptive immunity during human immunodeficiency virus co-infection and summarize recent findings from vaccine trials that provide insight into effective adaptive immune responses to M. tuberculosis infection.

The human immune response to tuberculosis and its treatment: a view from the blood

The immune response upon infection with the pathogen Mycobacterium tuberculosis is poorly understood, hampering the discovery of new treatments and the improvements in diagnosis. In the last years, a blood transcriptional signature in tuberculosis has provided knowledge on the immune response occurring during active tuberculosis disease. This signature was absent in the majority of asymptomatic individuals who are latently infected with M. tuberculosis (referred to as latent). Using modular and pathway analyses of the complex data has shown, now in multiple studies, that the signature of active tuberculosis is dominated by overexpression of interferon-inducible genes (consisting of both type I and type II interferon signaling), myeloid genes, and inflammatory genes. There is also downregulation of genes encoding B and T-cell function. The blood signature of tuberculosis correlates with the extent of radiographic disease and is diminished upon effective treatment suggesting the possibility of new improved strategies to support diagnostic assays and methods for drug treatment monitoring. The signature suggested a previously under-appreciated role for type I interferons in development of active tuberculosis disease, and numerous mechanisms have now been uncovered to explain how type I interferon impedes the protective response to M. tuberculosis infection.

Acquired immunodeficiencies and tuberculosis: focus on HIV/AIDS and diabetes mellitus

The spread of human immunodeficiency virus (HIV) infection within Africa led to marked increases in numbers of cases of tuberculosis (TB), and although the epidemic peaked in 2006, there were still 1.8 million new cases in 2013, with 29.2 million prevalent cases. Half of all TB cases in Africa are in those with HIV co-infection. A brief review of the well-documented main immunological mechanisms of HIV-associated increased susceptibility to TB is presented. However, a new threat is facing TB control, which presents itself in the form of a rapid increase in the number of people living with type II diabetes mellitus (T2DM), particularly in areas that are already hardest hit by the TB epidemic. T2DM increases susceptibility to TB threefold, and the TB burden attributable to T2DM is 15%. This review addresses the much smaller body of research information available on T2DM-TB, compared to HIV-TB comorbidity. We discuss the altered clinical presentation of TB in the context of T2DM comorbidity, changes in innate and adaptive immune responses, including lymphocyte subsets and T-cell phenotypes, the effect of treatment of the different comorbidities, changes in biomarker expression and genetic predisposition to the respective morbidities, and other factors affecting the comorbidity. Although significant gains have been made in improving our understanding of the underlying mechanisms of T2DM-associated increased susceptibility, knowledge gaps still exist that require urgent attention.

Excessive Cytolytic Responses Predict Tuberculosis Relapse After Apparently Successful Treatment

BACKGROUND

Currently, there are no tools to accurately predict tuberculosis relapse. This study aimed to determine whether patients who experience tuberculosis relapse have different immune responses to mycobacteria in vitro than patients who remain cured for 2 years.

METHODS

Patients with an initial episode of pulmonary tuberculosis were recruited in South Africa. Diluted blood, collected at diagnosis and after 2 and 4 weeks of treatment, was cultured with live Mycobacterium tuberculosis for 6 days, and cellular RNA was frozen. Gene expression in samples from 10 patients who subsequently experienced relapse, confirmed by strain genotyping, was compared to that in samples from patients who remained cured, using microarrays.

RESULTS

At diagnosis, expression of 668 genes was significantly different in samples from patients who experienced relapse, compared with expression in patients who remained successfully cured; these differences persisted for at least 4 weeks. Gene ontology and biological pathways analyses revealed significant upregulation of genes involved in cytotoxic cell-mediated killing. Results were confirmed by real-time quantitative reverse-transcription polymerase chain reaction analysis in a wider patient cohort.

CONCLUSIONS

These data show that patients who will subsequently experience relapse exhibit altered immune responses, including excessively robust cytolytic responses to M. tuberculosis in vitro, at the time of diagnosis, compared with patients who will achieve durable cure. Together with microbiological and clinical indices, these differences could be exploited in drug development.

Tricks to translating TB transcriptomics

Transcriptomics and other high-throughput methods are increasingly applied to questions relating to tuberculosis (TB) pathogenesis. Whole blood transcriptomics has repeatedly been applied to define correlates of TB risk and has produced new insight into the late stage of disease pathogenesis. In a novel approach, authors of a recently published study in Science Translational Medicine applied complex data analysis of existing TB transcriptomic datasets, and in vitro models, in an attempt to identify correlates of protection in TB, which are crucially required for the development of novel TB diagnostics and therapeutics to halt this global epidemic. Utilizing latent TB infection (LTBI) as a surrogate of protection, they identified IL-32 as a mediator of interferon gamma (IFNγ)-vitamin D dependent antimicrobial immunity and a marker of LTBI. Here, we provide a review of all TB whole-blood transcriptomic studies to date in the context of identifying correlates of protection, discuss potential pitfalls of combining complex analyses originating from such studies, the importance of detailed metadata to interpret differential patient classification algorithms, the effect of differing circulating cell populations between patient groups on the interpretation of resulting biomarkers and we decipher weighted gene co-expression network analysis (WGCNA), a recently developed systems biology tool which holds promise of identifying novel pathway interactions in disease pathogenesis. In conclusion, we propose the development of an integrated OMICS platform and open access to detailed metadata, in order for the TB research community to leverage the vast array of OMICS data being generated with the aim of unraveling the holy grail of TB research: correlates of protection.

Latent tuberculosis infection--Revisiting and revising concepts

Host- and pathogen-specific factors interplay with the environment in a complex fashion to determine the outcome of infection with Mycobacterium tuberculosis (Mtb), resulting in one of three possible outcomes: cure, latency or active disease. Although much remains unknown about its pathophysiology, latent tuberculosis infection (LTBI) defined by immunologic evidence of Mtb infection is a continuum between self-cure and asymptomatic, yet active tuberculosis (TB) disease. Strain virulence, intensity of exposure to the index case, size of the bacterial inoculum, and host factors such as age and co-morbidities, each contribute to where one settles on the continuum. Currently, the diagnosis of LTBI is based on reactive tuberculin skin testing (TST) and/or a positive interferon-gamma release assay (IGRA). Neither diagnostic test reflects the activity of the infectious focus or the risk of progression to active TB. This is a critical shortcoming, as accurate and efficient detection of those with LTBI at higher risk of progression to TB disease would allow for provision of targeted preventive therapy to those most likely to benefit. Host biomarkers may prove of value in stratifying risk of development of TB. New guidelines are required for interpretation of discordance between TST and IGRA, which may be due in part to a lack of stability (that is reproducibility) of IGRA or TST results or to a delay in conversion of IGRA to positivity compared to TST. In this review, the authors elaborate on the definition, diagnosis, pathophysiology and natural history of LTBI, as well as promising methods for better stratifying risk of progression to TB. The review is centered on the human host and the clinical and epidemiologic features of LTBI that are relevant to the development of new and improved diagnostic tools.

Expression of inhibitory regulators of innate immunity in patients with active tuberculosis

BACKGROUND

Tuberculosis (TB) is an important cause of morbidity and mortality worldwide. Toll-like-receptors (TLRs) are important for the recognition of the causative agent Mycobacterium tuberculosis. Negative regulation of TLRs is necessary to control deleterious inflammatory damage, but could provide a means of immune evasion by M. tuberculosis as well.

METHODS

To obtain insight in the extent of expression of inhibitory regulators of immunity in patients with active TB, peripheral-blood-mononuclear-cells (PBMCs) and plasma were obtained from 54 TB patients and 29 healthy blood donors from Chittagong, Bangladesh. Bilateral alveolar macrophages were obtained from an infected versus a contralateral normal lung segment of 9 patients. Statistical analyses were performed using Mann-Whitney U and Wilcoxon matched pairs testing. Correlations were calculated using the Spearman rho test.

RESULTS

PBMCs harvested from TB patients demonstrated increased mRNA expression of IL-1-receptor-associated-kinase-M, suppressor-of-cytokine-signalling-3 and Toll-interacting-protein. Flow cytometry revealed enhanced expression of IL-1-receptor-like-1 (ST2) on lymphocytes. Plasma soluble ST2 was elevated in patients with TB and correlated with established TB biomarkers, most strongly with soluble interleukin-2 receptor subunit α and interleukin-8. Alveolar macrophage mRNA expression of negative TLR regulators did not differ between the infected and contralateral lung side.

CONCLUSION

These results show enhanced expression of distinct negative regulators of innate immunity in PBMCs of patients with TB and identify plasma soluble ST2 as a potential novel biomarker for TB disease activity.

Quest for correlates of protection against tuberculosis

A major impediment to tuberculosis (TB) vaccine development is the lack of reliable correlates of immune protection or biomarkers that would predict vaccine efficacy. Gamma interferon (IFN-γ) produced by CD4(+) T cells and, recently, multifunctional CD4(+) T cells secreting IFN-γ, tumor necrosis factor (TNF), and interleukin-2 (IL-2) have been used in vaccine studies as a measurable immune parameter, reflecting activity of a vaccine and potentially predicting protection. However, accumulating experimental evidence suggests that host resistance against Mycobacterium tuberculosis infection is independent of IFN-γ and TNF secretion from CD4(+) T cells. Furthermore, the booster vaccine MVA85A, despite generating a high level of multifunctional CD4(+) T cell response in the host, failed to confer enhanced protection in vaccinated subjects. These findings suggest the need for identifying reliable correlates of protection to determine the efficacy of TB vaccine candidates. This article focuses on alternative pathways that mediate M. tuberculosis control and their potential for serving as markers of protection. The review also discusses the significance of investigating the natural human immune response to M. tuberculosis to identify the correlates of protection in vaccination.

Clinical immunology and multiplex biomarkers of human tuberculosis

The discovery of tuberculosis (TB) biomarkers is an important goal in current TB research, because the availability of such markers would have significant impact on TB prevention and treatment. Correlates of protection would greatly facilitate vaccine development and evaluation, whereas correlates of TB disease risk would facilitate early diagnosis and help installing early or preventive treatment. Currently, no such markers are available. This review describes several strategies that are currently being pursued to identify TB biomarkers and places these in a clinical context. The approaches discussed include both targeted and untargeted hypothesis-free strategies. Among the first are the measurements of specific biomarkers in antigen-stimulated peripheral blood, in serum or plasma, and detailed immune cell phenotyping. Among the latter are proteomic, genomic, and transcriptomic (mRNA, miRNA) approaches. Recent and promising developments are described.

Toward a unified biosignature for tuberculosis

Accurate and rapid diagnosis of active tuberculosis (TB) disease is still hampered by inadequate tools. Although current assays relying on single-marker readouts mostly display inadequate sensitivity and/or specificity, host-related multimarker signatures are especially poorly developed. As a consequence, research programs have been initiated to search for combinations of markers-so-called biosignatures with superior performance. Many such investigations harness high-throughput platforms to analyze the host response during infection and disease. A major challenge for these activities is the analysis of vast amounts of data produced. Specialized bioinformatic tools are being applied to identify the most robust biosignatures for classification of exposed and diseased individuals and prognosis of risk of disease in endemic areas. Validation of the most promising biosignatures in ongoing multicohort studies will bring us a step closer to the identification of an accurate unified signature.