Plasma cytokine levels characterize disease pathogenesis and treatment response in tuberculosis patients

BACKGROUND

Mycobacterium (M.) tuberculosis-caused immunopathology is characterized by aberrant expression of plasma cytokines in human tuberculosis. Disease severity and long-term anti-mycobacterial treatment are potentially influenced by immunopathology and normalization of plasma cytokine levels during therapy may indicate treatment efficacy and recovery.

STUDY DESIGN AND METHODS

In this study, we analyzed the concentrations of selected plasma cytokines (i.e., IL-6, IP-10, IL-10, IL-22, IFNγ, GM-CSF, IL-8) and M. tuberculosis sputum burden in patients with tuberculosis (n = 76). Cytokine levels were compared to healthy contacts (n = 40) and changes under treatment were monitored (i.e., 6 and 16 weeks after treatment start). According to differences in M. tuberculosis sputum burden and conversion, tuberculosis patients were classified as paucibacillary as well as 'rapid' or 'slow' treatment responders. A subgroup of tuberculosis patients had fatal disease courses.

RESULTS

Six of seven cytokines were significantly higher in tuberculosis patients as compared to contacts and four of these (i.e., IL-6, IP-10, IL-10, and IL-22) were detectable in the majority of tuberculosis patients. IL-6 showed the strongest discriminating capacity for tuberculosis disease and in combination with IL-10 concentrations efficiently classified paucibacillary tuberculosis cases as well as those with fatal disease outcome. In addition, IL-6 and IP-10 levels decreased significantly after 6 weeks of treatment and analyses of subgroups with differential treatment response showed delayed decline of IL-6 levels in slow treatment responders.

CONCLUSIONS

Combinations of different plasma cytokine (namely, IL-6, IL-10, and IP-10) efficiently classified tuberculosis patients with differential mycobacterial burden and especially IL-6 qualified as a biomarker candidate for early treatment response.

Immunological Aspects of Diagnosis and Management of Childhood Tuberculosis

The diagnosis of tuberculosis (TB) in children is difficult because of the low sensitivity and specificity of traditional microbiology techniques in this age group. Whereas in adults the culture of Mycobacterium tuberculosis (M. tuberculosis), the gold standard test, detects 80% of positive cases, it only detects around 30-40% of cases in children. The new methods based on the immune response to M. tuberculosis infection could be affected by many factors. It is necessary to evaluate the medical record, clinical features, presence of drug-resistant M. tuberculosis strains, comorbidities, and BCG vaccination history for the diagnosis in children. There is no ideal biomarker for all TB cases in children. A new strategy based on personalized diagnosis could be used to evaluate specific molecules produced by the host immune response and make therapeutic decisions in each child, thereby changing standard immunological signatures to personalized signatures in TB. In this way, immune diagnosis, prognosis, and the use of potential immunomodulators as adjunct TB treatments will meet personalized treatment.

A three-marker protein biosignature distinguishes tuberculosis from other respiratory diseases in Gambian children

Background

Our study aimed to identify a host cytokine biosignature that could distinguish childhood tuberculosis (TB) from other respiratory diseases (OD).

Methods

Cytokine responses in prospectively recruited children with symptoms suggestive of TB were measured in whole blood assay supernatants, harvested after overnight incubation, using a Luminex platform. We used logistic regression models with Least Absolute Shrinkage and Selection Operator (LASSO) penalty to identify the optimal biosignature associated with confirmed TB disease in the training set. We subsequently assessed its performance in the test set.

Findings

Of the 431 children included in the study, 44 had bacteriologically confirmed TB, 60 had clinically diagnosed TB while 327 had OD. All children were HIV-negative. Application of LASSO regression models to the training set (n = 260) resulted in the combination of IL-1ra, IL-7 and IP-10 from unstimulated samples as the optimally discriminant cytokine biosignature associated with bacteriologically confirmed TB. In the test set (n = 171), this biosignature distinguished children diagnosed with TB disease, irrespective of microbiological confirmation, from OD with area under the receiver operator characteristic curve (AUC) of 0•74 (95% CI: 0•67, 0•81), and demonstrated sensitivity and specificity of 72•2% (95% CI: 60•4, 82•1%) and 75•0% (95% CI: 64•9, 83•4%) respectively, with its performance independent of their age group and their age- and sex-adjusted nutritional status.

Interpretation

This novel biosignature of childhood TB derived from unstimulated supernatants is promising. Independent validation with further optimisation will improve its performance and translational potential.

Funding

Steinberg Fellowship (McGill University); Grand Challenges Canada; MRC Program Grant.

Serological biomarkers for monitoring response to treatment of pulmonary and extrapulmonary tuberculosis in children and adolescents

Key measures to halt the spread of tuberculosis (TB) include early diagnosis, effective treatment, and monitoring disease management. We sought to evaluate the use of serum immunoglobulin levels against antigens present in cell envelope of Mycobacterium tuberculosis to monitor TB treatment response in children and adolescents with pulmonary (PTB) or extrapulmonary TB (EPTB). Blood samples were collected prior to and one, two, and six months following treatment initiation. Serum immunoglobulin levels against cardiolipin, sulfatide, mycolic acid and Mce1A protein were measured by ELISA. Serum from 53 TB patients and 12 healthy participants were analyzed. After six months of successful treatment, there was a significant decrease (p < 0.0001) in IgM levels against cardiolipin, sulfatide, mycolic acid and Mce1A protein and IgG levels against Mce1A protein when compared to baseline immunoglobulin levels. There was no significant variation in antibody levels during follow-up between participants with PTB and EPTB, confirmed and unconfirmed TB diagnosis, and HIV infection status. Antibody levels in control participants without TB did not decrease during follow-up. These results suggest that immunoglobulin responses to mycobacterial cell wall products may be a useful tool to monitor treatment response in children and adolescents with PTB or EPTB.

Microparticles in the pathogenesis of TB: Novel perspectives for diagnostic and therapy management of Mycobacterium tuberculosis infection

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis, usually chronic and has a progressive clinical course. Despite the availability of effective chemotherapy, TB is a leading killer of young adults worldwide and the global multi-drug resistant TB is reaching epidemic proportions. Interrupt transmission through early detection and treatment of the patients is a main element of the drug-resistant TB control strategy. However, many drugable targets in pathogens are already inhibited by current antibiotics and there is not a biomarker that indicate normal or pathogenic biological processes, or pharmacological responses to therapeutic intervention. Studies directed at evaluate key elements of host response to infection may identify biomarkers with measurable characteristics that indicate pathogenic biological processes. Cell-derived microparticles (MPs) are membrane-coated vesicles that represent subcellular elements and have been identified increasingly in a broad range of diseases and emerging as potential novel biomarker to pathological processes. In addition, MPs carry contents from their cells of origin as bioactive molecules as cytokines, enzymes, surface receptors, antigens and genetic information and may provide a means of communication between cells. Molecules-loaded MPs may interplay with the immune system and therefore can acts on inflammation, cell activation and migration. Therefore, MPs may be an important factor to immune process during Mtb infection, especially in pulmonary granulomas and influence the outcome of infection. Their characterization may facilitate an appropriate diagnosis, optimize pharmacological strategies and might be further explored as potential targets for future clinical interventions.

M. Ottenhoff T, M. Cliff J, C. Haks M. Gene expression profiles classifying clinical stages of tuberculosis and monitoring treatment responses in Ethiopian HIV-negative and HIV-positive cohorts

Background

Validation of previously identified candidate biomarkers and identification of additional candidate gene expression profiles to facilitate diagnosis of tuberculosis (TB) disease and monitoring treatment responses in the Ethiopian context is vital for improving TB control in the future.

Methods

Expression levels of 105 immune-related genes were determined in the blood of 80 HIV-negative study participants composed of 40 active TB cases, 20 latent TB infected individuals with positive tuberculin skin test (TST+), and 20 healthy controls with no Mycobacterium tuberculosis (Mtb) infection (TST-), using focused gene expression profiling by dual-color Reverse-Transcription Multiplex Ligation-dependent Probe Amplification assay. Gene expression levels were also measured six months after anti-TB treatment (ATT) and follow-up in 38 TB patients.

Results

The expression of 15 host genes in TB patients could accurately discriminate between TB cases versus both TST+ and TST- controls at baseline and thus holds promise as biomarker signature to classify active TB disease versus latent TB infection in an Ethiopian setting. Interestingly, the expression levels of most genes that markedly discriminated between TB cases versus TST+ or TST- controls did not normalize following completion of ATT therapy at 6 months (except for PTPRCv1, FCGR1A, GZMB, CASP8 and GNLY) but had only fully normalized at the 18 months follow-up time point. Of note, network analysis comparing TB-associated host genes identified in the current HIV-negative TB cohort to TB-associated genes identified in our previously published Ethiopian HIV-positive TB cohort, revealed an over-representation of pattern recognition receptors including TLR2 and TLR4 in the HIV-positive cohort which was not seen in the HIV-negative cohort. Moreover, using ROC cutoff ≥ 0.80, FCGR1A was the only marker with classifying potential between TB infection and TB disease regardless of HIV status.

Conclusions

Our data indicate that complex gene expression signatures are required to measure blood transcriptomic responses during and after successful ATT to fully diagnose TB disease and characterise drug-induced relapse-free cure, combining genes which resolve completely during the 6-months treatment phase of therapy with genes that only fully return to normal levels during the post-treatment resolution phase.

Host Gene Expression Kinetics During Treatment of Tuberculosis in HIV-Coinfected Individuals Is Independent of Highly Active Antiretroviral Therapy

Background

Limitations in diagnostic tools to discriminate between active tuberculosis and latent Mycobacterium tuberculosis infection and for monitoring antituberculosis treatment responses are major challenges in tuberculosis control, especially in human immunodeficiency virus (HIV)-coinfected individuals.

Methods

Expression levels of 105 immune-related genes were determined in 131 HIV-infected patients with active tuberculosis (n = 48), patients with latent M. tuberculosis infection (LTBI; n = 37), and controls with no M. tuberculosis infection (n = 46) in Addis Ababa, Ethiopia, using focused gene expression profiling with a dual-color reverse-transcription multiplex ligation-dependent probe amplification assay.

Results

Within the cohort of HIV-positive subjects, the expression profiles of 7 genes at baseline (FCGR1A, RAB24, TLR1, TLR4, MMP9, NLRC4, and IL1B) could accurately discriminate between active tuberculosis and both latent and no M. tuberculosis infection, largely independently of (in)eligibility for highly active antiretroviral therapy (HAART). Six months after antituberculosis treatment, biomarker profiles of patients with tuberculosis became indistinguishable from those of patients with LTBI and controls. Importantly, host gene expression kinetics during antituberculosis treatment in HIV-coinfected individuals was found to be independent of HAART use.

Conclusions

Blood transcriptomic profiles can potentially be used as biomarkers to discriminate the different clinical stages of tuberculosis in HIV-coinfected individuals and to monitor tuberculosis treatment responses in both HAART recipients and untreated individuals.

The role of metabolomics in tuberculosis treatment research

Despite the fact that tuberculosis (TB) is a curable disease, it still results in approximately 1.8 million deaths annually. Various inadequacies in the current TB treatment strategies are major contributors to this high disease prevalence, including the long duration of therapy, the severe side effects associated with TB drugs, treatment failure due to drug resistance, post-treatment disease relapse, and HIV co-infection. In this review, we describe how metabolomics has contributed toward better explaining/elucidating the mechanisms of drug action/metabolism, drug toxicity and microbial drug resistance, and how metabolite biomarkers may serve as prognostic indicators for predicting treatment outcome as well as for the development of new TB drugs. We also discuss possible future contributions that metabolomics can make toward more efficient, less toxic TB treatment strategies.

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.

Quantitative Proteomics of Cerebrospinal Fluid in Paediatric Pneumococcal Meningitis

Streptococcus pneumoniae is responsible for diseases causing major global public health problems, including meningitis, pneumonia and septicaemia. Despite recent advances in antimicrobial therapy, pneumococcal meningitis remains a life-threatening disease. Furthermore, long-term sequelae are a major concern for survivors. Hence, a better understanding of the processes occurring in the central nervous system is crucial to the development of more effective management strategies. We used mass spectrometry based quantitative proteomics to identify protein changes in cerebrospinal fluid from children with Streptococcus pneumoniae infection, compared with children admitted to hospital with bacterial meningitis symptoms but negative diagnosis. Samples were analysed, by label free proteomics, in two independent cohorts (cohort 1: cases (n = 8) and hospital controls (n = 4); cohort 2: cases (n = 8), hospital controls (n = 8)). Over 200 human proteins were differentially expressed in each cohort, of which 65% were common to both. Proteins involved in the immune response and exosome signalling were significantly enriched in the infected samples. For a subset of proteins derived from the proteome analysis, we corroborated the proteomics data in a third cohort (hospital controls (n = 15), healthy controls (n = 5), cases (n = 20)) by automated quantitative western blotting, with excellent agreement with our proteomics findings. Proteomics data are available via ProteomeXchange with identifier PXD004219.

Total IgM and Anti-Phosphatidylcholine IgM Antibody Secretion Continue After Clearance of Mycobacterium bovis Bacillus Calmette-Guerin Pleural Infection

The cellular immune response to Mycobacterium tuberculosis infection has been well characterized, while the humoral antibody response remains underexplored. We aimed to examine the total and anti-phospholipid IgM levels in the pleural lavage from mice with Mycobacterium bovis BCG extrapulmonary infection. We found that the levels of total and anti-phosphatidylcholine IgM antibodies remained significantly higher in infected mice as compared to non-infected mice up to day 90 after BCG infection, while the anti-cardiolipin IgM antibody levels decreased with bacteria clearance. Our findings suggest that IgM antibodies are secreted and their composition vary during early and late immune response to BCG pleurisy.

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.

Diagnostic value of blood gene expression signatures in active tuberculosis in Thais: a pilot study

Tuberculosis (TB) is a major global health problem. Routine laboratory tests or newly developed molecular detection are limited to the quality of sputum sample. Here we selected genes specific to TB by a minimum redundancy-maximum relevancy package using publicly available microarray data and determine level of selected genes in blood collected from a Thai TB cohort of 40 active TB patients, 38 healthy controls and 18 previous TB patients using quantitative real-time PCR. FCGR1A, FCGR1B variant 1, FCGR1B variant 2, APOL1, GBP5, PSTPIP2, STAT1, KCNJ15, MAFB and KAZN had significantly higher expression level in active TB individuals as compared with healthy controls and previous TB cases (P<0.01). A mathematical method was applied to calculate TB predictive score, which contains the level of expression of seven genes and this score can identify active TB cases with 82.5% sensitivity and 100% specificity as compared with conventional culture confirmation. In addition, TB predictive scores in active TB patients were reduced to normal after completion of standard short-course therapy, which was mostly in concordant with the disease outcome. These finding suggested that blood gene expression measurement and TB Sick Score could have potential value in terms of diagnosis of TB and anti-TB treatment monitoring.

Are microRNAs suitable biomarkers of immunity to tuberculosis?

Background

MicroRNAs (miRNAs) are crucial regulators of human immunity e.g. against Mycobacterium tuberculosis. Against the background of still alarming high mortality of tuberculosis effective biomarkers to improve diagnosis of M. tuberculosis infection and successful treatment are of major importance.

Conclusions

This review summarizes recent surrogate tissue studies for identification of miRNA biomarker candidates in human tuberculosis with a special focus on reproducibility and conformance. In addition we provide assistance for the design of biomarker studies to circumvent major pitfalls.

A subset of circulating blood mycobacteria-specific CD4 T cells can predict the time to Mycobacterium tuberculosis sputum culture conversion

We investigated 18 HIV-negative patients with MDR-TB for M. tuberculosis (Mtb)- and PPD-specific CD4 T cell responses and followed them over 6 months of drug therapy. Twelve of these patients were sputum culture (SC) positive and six patients were SC negative upon enrollment. Our aim was to identify a subset of mycobacteria-specific CD4 T cells that would predict time to culture conversion. The total frequency of mycobacteria-specific CD4 T cells at baseline could not distinguish patients showing positive or negative SC. However, a greater proportion of late-differentiated (LD) Mtb- and PPD-specific memory CD4 T cells was found in SC positive patients than in those who were SC negative (p = 0.004 and p = 0.0012, respectively). Similarly, a higher co-expression of HLA-DR+ Ki67+ on Mtb- and PPD-specific CD4 T cells could also discriminate between sputum SC positive versus SC negative (p = 0.004 and p = 0.001, respectively). Receiver operating characteristic (ROC) analysis revealed that baseline levels of Ki67+ HLA-DR+ Mtb- and PPD-specific CD4 T cells were predictive of the time to sputum culture conversion, with area-under-the-curve of 0.8 (p = 0.027). Upon treatment, there was a significant decline of these Ki67+ HLA-DR+ T cell populations in the first 2 months, with a progressive increase in mycobacteria-specific polyfunctional IFNγ+ IL2+ TNFα+ CD4 T cells over 6 months. Thus, a subset of activated and proliferating mycobacterial-specific CD4 T cells (Ki67+ HLA-DR+) may provide a valuable marker in peripheral blood that predicts time to sputum culture conversion in TB patients at the start of treatment.

Magnetic resonance imaging characterization of microbial infections

The investigation of microbial infections relies to a large part on animal models of infection, if host pathogen interactions or the host response are considered. Especially for the assessment of novel therapeutic agents, animal models are required. Non-invasive imaging methods to study such models have gained increasing importance over the recent years. In particular, magnetic resonance imaging (MRI) affords a variety of diagnostic options, and can be used for longitudinal studies. In this review, we introduce the most important MRI modalities that show how MRI has been used for the investigation of animal models of infection previously and how it may be applied in the future.

The dual role of biomarkers for understanding basic principles and devising novel intervention strategies in tuberculosis

There is great need for better control measures for tuberculosis (TB). High-throughput analyses, such as transcriptomic and metabolic profiling, offer a promising path toward clinically useful biosignatures. With the help of biomarkers, it will be possible not only to reliably perform diagnosis but also to gain a better understanding of the disease process and, in the future, even predict the onset of disease in infected individuals. Biomarkers based on transcriptomic and metabolic profiles as well as on cytokine composition provide important insights into the basic biological principles of TB and give an opportunity to reliably distinguish TB patients from healthy individuals. Use of biomarkers for point-of-care diagnosis, however, is still a distant goal, which to achieve will require extensive analysis of TB biosignatures across different cohorts and a combination of different platforms.

Biomarkers of latent TB infection

For the last 100 years, the tuberculin skin test (TST) has been the only diagnostic tool available for latent TB infection (LTBI) and no biomarker per se is available to diagnose the presence of LTBI. With the introduction of M. tuberculosis-specific IFN-gamma release assays (IGRAs), a new area of in vitro immunodiagnostic tests for LTBI based on biomarker readout has become a reality. In this review, we discuss existing evidence on the clinical usefulness of IGRAs and the indefinite number of potential new biomarkers that can be used to improve diagnosis of latent TB infection. We also present early data suggesting that the monocyte-derived chemokine inducible protein-10 may be useful as a novel biomarker for the immunodiagnosis of latent TB infection.

Novel biomarker combination improves the diagnosis of serious bacterial infections in Malawian children

Background

High throughput technologies offer insight into disease processes and heightens opportunities for improved diagnostics. Using transcriptomic analyses, we aimed to discover and to evaluate the clinical validity of a combination of reliable and functionally important biomarkers of serious bacterial infection (SBI).

Methods

We identified three previously reported biomarkers of infection (neutrophil gelatinase-associated lipocalin (NGAL), granulysin and resistin) and measured gene expression using quantitative real-time PCR. Protein products related to the three transcripts were measured by immunoassays.

Results

Relative gene expression values of NGAL and resistin were significantly increased, and expression of granulysin significantly decreased in cases compared to controls. Plasma concentrations of NGAL and resistin were significantly increased in children with confirmed SBI compared to children with no detectable bacterial infection (NBI), and to controls (287 versus 128 versus 62 ng/ml and 195 versus 90 versus 18 ng/ml, respectively, p < 0.05). Plasma protein concentrations of NGAL and resistin were significantly increased in non-survivors compared to survivors (306 versus 211 and 214 versus 150 ng/ml, p = 0.02). The respective areas under the curve (AUC) for NGAL, resistin and procalcitonin in predicting SBI were 0.79, 0.80 and 0.86, whilst a combination of NGAL, resistin and procalcitonin achieved an AUC of 0.90.

Conclusions

We have demonstrated a unique combination of diagnostic biomarkers of SBI using transcriptomics, and demonstrated translational concordance with the corresponding protein. The addition of NGAL and resistin protein measurement to procalcitonin significantly improved the diagnosis of SBI.

Gram-negative and Gram-positive bacterial infections give rise to a different metabolic response in a mouse model

Metabolomics has become an important tool to study host-pathogen interactions and to discover potential novel therapeutic targets. In an attempt to develop a better understanding of the process of pathogenesis and the associated host response we have used a quantitative ¹H NMR approach to study the metabolic response to different bacterial infections. Here we describe that metabolic changes found in serum of mice that were infected with Staphylococcus aureus, Streptococcus pneumoniae, Escherichia coli and Pseudomonas aeruginosa can distinguish between infections caused by Gram-positive and Gram-negative bacterial strains. By combining the results of the mouse study with those of bacterial footprinting culture experiments, bacterially secreted metabolites could be identified as potential bacterium-specific biomarkers for P. aeruginosa infections but not for the other strains. Multivariate statistical analysis revealed correlations between metabolic, cytokine and physiological responses. In TLR4 and TLR2 knockout mice, host-response pathway correlated metabolites could be identified and allowed us for the first time to distinguish between bacterial- and host-induced metabolic changes. Since Gram-positive and Gram-negative bacteria activate different receptor pathways in the host, our results suggest that it may become possible in the future to use a metabolomics approach to improve on current clinical microbiology diagnostic methods.

Anti-phospholipid antibody levels as biomarker for monitoring tuberculosis treatment response

Standard methods to monitor tuberculosis (TB) treatment response rely on sputum microscopy and culture conversion. Alternatives to these methods are needed for those patients whose sputum tests are smear or culture negative. Here, we examine anti-phospholipid IgM antibody level changes as a biomarker for treatment response in smear positive TB patients. Serum samples were obtained from 40 pulmonary TB patients at the start and end of the intensive phase treatment (IPT) from the CDC-TB Trials Consortium randomized clinical trial in Kampala, Uganda. Samples were screened by ELISA for IgM levels against five phospholipids found in Mycobacterium tuberculosis and host cells. Lipid antigens included cardiolipin (CL), phosphatidyl inositol (PI), phosphatidyl ethanolamine (PE), phosphatidyl choline (PTC), and sphingolipid (SL). Levels of IgM against all phospholipids significantly decreased (p = 0.034, 0.001, 0.008 0.008, 0.040, respectively) following anti-TB drug treatment in patients without lung cavitary disease at baseline. The mean sensitivity of this test in these patients was 83% when the IgM response to a single lipid antigen was used; it was >90% when responses to 2 or more lipids were assessed. In contrast, cavitary TB patients showed an overall IgM increase, with a significant rise against PE (p = 0.025). There was no significant difference in the change in antibody levels between patients who remained culture-positive and those who culture-converted after 40 doses of drug therapy. The measurement of IgM anti-phospholipid antibodies may be a useful biomarker to monitor treatment response in non-cavitary TB patients.

Use of non-aqueous fractionation and metabolomics to study chloroplast function in Arabidopsis

Chloroplasts are the chemical factories of plant cells because they are able to fix inorganic carbon and -convert it to a wide-range of photoassimilates that are exported to the cytosol and other sub-cellular compartments. If the regulation of these processes is to be understood, the in vivo concentrations of a large number of metabolites have to be measured in all of these compartments separately. Sophisticated analytical approaches and continued advances in the technology of mass spectrometry coupled to a variety of fractionation and separation techniques allow the reliable analysis of a comprehensive complement of metabolites in photosynthetic tissues. Metabolomic approaches allow the multi-parallel analysis of a wide-range of metabolic intermediates and have been used for rapid phenotyping of different genotypes and environmental effects in plants. In addition to this, methods have been developed to analyse metabolite levels in different sub-cellular compartments of plant cells. Here, we describe methods for sub-cellular fractionation of Arabidopsis leaves using a non-aqueous density gradient technique, sample preparation suitable for metabolite profiling using gas-chromatography-mass spectrometry, and calculation of sub-cellular metabolite concentrations.

Discovering plant metabolic biomarkers for phenotype prediction using an untargeted approach

Biomarkers are used to predict phenotypical properties before these features become apparent and, therefore, are valuable tools for both fundamental and applied research. Diagnostic biomarkers have been discovered in medicine many decades ago and are now commonly applied. While this is routine in the field of medicine, it is of surprise that in agriculture this approach has never been investigated. Up to now, the prediction of phenotypes in plants was based on growing plants and assaying the organs of interest in a time intensive process. For the first time, we demonstrate in this study the application of metabolomics to predict agronomic important phenotypes of a crop plant that was grown in different environments. Our procedure consists of established techniques to screen untargeted for a large amount of metabolites in parallel, in combination with machine learning methods. By using this combination of metabolomics and biomathematical tools metabolites were identified that can be used as biomarkers to improve the prediction of traits. The predictive metabolites can be selected and used subsequently to develop fast, targeted and low-cost diagnostic biomarker assays that can be implemented in breeding programs or quality assessment analysis. The identified metabolic biomarkers allow for the prediction of crop product quality. Furthermore, marker-assisted selection can benefit from the discovery of metabolic biomarkers when other molecular markers come to its limitation. The described marker selection method was developed for potato tubers, but is generally applicable to any crop and trait as it functions independently of genomic information.

Human gene expression profiles of susceptibility and resistance in tuberculosis

Tuberculosis (TB) still poses a profound burden on global health, owing to significant morbidity and mortality worldwide. Although a fully functional immune system is essential for the control of Mycobacterium tuberculosis infection, the underlying mechanisms and reasons for failure in part of the infected population remain enigmatic. Here, whole-blood microarray gene expression analyses were performed in TB patients and in latently as well as uninfected healthy controls to define biomarkers predictive of susceptibility and resistance. Fc gamma receptor 1B (FCGRIB)was identified as the most differentially expressed gene, and, in combination with four other markers, produced a high degree of accuracy in discriminating TB patients and latently infected donors. We determined differentially expressed genes unique for active disease and identified profiles that correlated with susceptibility and resistance to TB. Elevated expression of innate immune-related genes in active TB and higher expression of particular gene clusters involved in apoptosis and natural killer cell activity in latently infected donors are likely to be the major distinctive factors determining failure or success in controlling M. tuberculosis infection. The gene expression profiles defined in this study provide valuable clues for better understanding of progression from latent infection to active disease and pave the way for defining predictive correlates of protection in TB.

Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

Background

For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.

Results

Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach.

Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.

Conclusions

The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.

Identification of major factors influencing ELISpot-based monitoring of cellular responses to antigens from Mycobacterium tuberculosis

A number of different interferon-γ ELISpot protocols are in use in laboratories studying antigen-specific immune responses. It is therefore unclear how results from different assays compare, and what factors most significantly influence assay outcome. One such difference is that some laboratories use a short in vitro stimulation period of cells before they are transferred to the ELISpot plate; this is commonly done in the case of frozen cells, in order to enhance assay sensitivity. Other differences that may be significant include antibody coating of plates, the use of media with or without serum, the serum source and the number of cells added to the wells. The aim of this paper was to identify which components of the different ELISpot protocols influenced assay sensitivity and inter-laboratory variation. Four laboratories provided protocols for quantifying numbers of interferon-γ spot forming cells in human peripheral blood mononuclear cells stimulated with Mycobacterium tuberculosis derived antigens. The differences in the protocols were compared directly. We found that several sources of variation in assay protocols can be eliminated, for example by avoiding serum supplementation and using AIM-V serum free medium. In addition, the number of cells added to ELISpot wells should also be standardised. Importantly, delays in peripheral blood mononuclear cell processing before stimulation had a marked effect on the number of detectable spot forming cells; processing delay thus should be minimised as well as standardised. Finally, a pre-stimulation culture period improved the sensitivity of the assay, however this effect may be both antigen and donor dependent. In conclusion, small differences in ELISpot protocols in routine use can affect the results obtained and care should be given to conditions selected for use in a given study. A pre-stimulation step may improve the sensitivity of the assay, particularly when cells have been previously frozen.

Exploring the immune response against Mycobacterium tuberculosis for a better diagnosis of the infection

Tuberculosis (TB) still represents a monumental problem, with more than two million deaths every year worldwide. The current diagnostics for TB offer sub-optimal accuracy both for the active and the latent form of infection and are often based on technologies unaffordable in low-income settings. The tuberculin skin test was the first diagnostic based on an acquired immune response towards Mycobacterium tuberculosis (MTB). Advances in molecular and cellular biology and the elucidation of the mechanisms governing the relation between MTB and the human immune system form the basis for new and more accurate assays, potentially able to fill the gaps and limits of classical diagnostics. However, the process of validating new tests is still complex and hampered by specific questions regarding TB immunology and natural history. We present here a summary of the current approaches to validate new diagnostics based on the detection of immunological biomarkers of TB infection.

Gene expression profiling of the host response to Mycobacterium bovis infection in cattle

Bovine tuberculosis (BTB), caused by Mycobacterium bovis, continues to pose a threat to livestock worldwide and, as a zoonotic infection, also has serious implications for human health. The implementation of comprehensive surveillance programmes to detect BTB has been successful in reducing the incidence of infection in many countries, yet BTB has remained recalcitrant to eradication in several EU states, particularly in Ireland and the UK. There are well-recognized limitations in the use of the current diagnostics to detect all infected animals and this has led to renewed efforts to uncover novel diagnostic biomarkers that may serve to enhance the performance of the tests. Studies of single immunological parameters have so far been unable to unlock the complexities of the immune response to mycobacterial infection. However, the development of high-throughput methods including pan-genomic gene expression technologies such as DNA microarrays has facilitated the simultaneous identification and analysis of thousands of genes and their interactions during the immune response. In addition, the application of these new genomic technologies to BTB has identified pathogen-associated immune response signatures of host infection. The objective of these investigations is to understand the changing profile of immune responses throughout the course of infection and to identify biomarkers for sensitive diagnosis, particularly during the early stages of infection. Transcriptional profiling via microarray and more recently via next-generation sequencing technologies may lead to the development of specific and sensitive diagnostics for M. bovis infection and will enhance the prospect of eradication of tuberculosis from cattle populations.

Identification of T-cell antigens specific for latent mycobacterium tuberculosis infection

Background

T-cell responses against dormancy-, resuscitation-, and reactivation-associated antigens of Mycobacterium tuberculosis are candidate biomarkers of latent infection in humans.

Methodology/Principal Findings

We established an assay based on two rounds of in vitro restimulation and intracellular cytokine analysis that detects T-cell responses to antigens expressed during latent M. tuberculosis infection. Comparison between active pulmonary tuberculosis (TB) patients and healthy latently M. tuberculosis-infected donors (LTBI) revealed significantly higher T-cell responses against 7 of 35 tested M. tuberculosis latency-associated antigens in LTBI. Notably, T cells specific for Rv3407 were exclusively detected in LTBI but not in TB patients. The T-cell IFNγ response against Rv3407 in individual donors was the most influential factor in discrimination analysis that classified TB patients and LTBI with 83% accuracy using cross-validation. Rv3407 peptide pool stimulations revealed distinct candidate epitopes in four LTBI.

Conclusions

Our findings further support the hypothesis that the latency-associated antigens can be exploited as biomarkers for LTBI.

Tuberculosis in Africa: learning from pathogenesis for biomarker identification

In Africa, more than 4 million people suffer from active tuberculosis (TB) resulting in an estimated 650,000 deaths every year. The etiologic agent of TB, Mycobacterium tuberculosis, survives in resting macrophages, which control the pathogen after activation by specific T lymphocytes. Here, we describe the basic mechanisms underlying the host response to TB with an emphasis on immunity and discuss diagnostics, drugs, and vaccines for TB. Moreover, we outline our attempts to develop biomarkers, which could help the monitoring of TB clinical trials, provide the basis for new diagnostics, and allow prognosis of outcome of infection and of drug treatment.