Decreased serum 5-oxoproline in TB patients is associated with pathological damage of the lung

Metabolic phenotyping and global functional analysis facilitate metabolic signature discovery for tuberculosis treatment monitoring

Tracking alterations in polar metabolite and lipid levels during anti-tuberculosis (TB) interventions is an emerging biomarker discovery and validation approach due to its sensitivity in capturing changes and reflecting on the host status. Here, we employed deep plasma metabolic phenotyping to explore the TB patient metabolome during three phases of treatment: at baseline, during intensive phase treatment, and upon treatment completion. Differential metabolites (DMs) in each period were determined, and the pathway-level biological alterations were explored by untargeted metabolomics-guided functional interpretations that bypassed identification. We identified 41 DMs and 39 pathways that changed during intensive phase completion. Notably, levels of certain amino acids including histidine, bile acids, and metabolites of purine metabolism were dramatically increased. The altered pathways included those involved in the metabolism of amino acids, glycerophospholipids, and purine. At the end of treatment, 44 DMs were discovered. The levels of glutamine, bile acids, and lysophosphatidylinositol significantly increased compared to baseline; the levels of carboxylates and hypotaurine declined. In addition, 37 pathways principally associated with the metabolism of amino acids, carbohydrates, and glycan altered at treatment completion. The potential of each DM for diagnosing TB was examined using a cohort consisting of TB patients, those with latent infections, and controls. Logistic regression revealed four biomarkers (taurine, methionine, glutamine, and acetyl-carnitine) that exhibited excellent performance in differential diagnosis. In conclusion, we identified metabolites that could serve as useful metabolic signatures for TB management and elucidated underlying biological processes affected by the crosstalk between host and TB pathogen during treatment.

Untargeted Metabolomics of Feces Reveals Diagnostic and Prognostic Biomarkers for Active Tuberculosis and Latent Tuberculosis Infection: Potential Application for Precise and Non-Invasive Identification

Purpose

Distinguishing latent tuberculosis infection (LTBI) from active tuberculosis (ATB) is important to control the prevalence of tuberculosis; however, there is currently no effective method. The aim of this study was to discover specific metabolites through fecal untargeted metabolomics to discriminate ATB, individuals with LTBI, and healthy controls (HC) and to probe the metabolic perturbation associated with the progression of tuberculosis.

Patients and Methods

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to comprehensively detect compounds in fecal samples from HC, LTBI, and ATB patients. Differential metabolites between the two groups were screened, and their underlying biological functions were explored. Candidate metabolites were selected and enrolled in LASSO regression analysis to construct diagnostic signatures for discriminating between HC, LTBI, and ATB. A receiver operating characteristic (ROC) curve was applied to evaluate diagnostic value. A nomogram was constructed to predict the risk of progression of LTBI.

Results

A total of 35 metabolites were found to exist differentially in HC, LTBI, and ATB, and eight biomarkers were selected. Three diagnostic signatures based on the eight biomarkers were constructed to distinguish between HC, LTBI, and ATB, demonstrating excellent discrimination performance in ROC analysis. A nomogram was successfully constructed to evaluate the risk of progression of LTBI to ATB. Moreover, 3,4-dimethylbenzoic acid has been shown to distinguish ATB patients with different responses to etiological tests.

Conclusion

This study constructed diagnostic signatures based on fecal metabolic biomarkers that effectively discriminated HC, LTBI, and ATB, and established a predictive model to evaluate the risk of progression of LTBI to ATB. The results provide scientific evidence for establishing an accurate, sensitive, and noninvasive differential diagnosis scheme for tuberculosis.

The metabolic and lipidomic profiling of the effects of tracheal occlusion in a rabbit model of congenital diaphragmatic hernia

PURPOSE

Fetal tracheal occlusion (TO) reverses the pulmonary hypoplasia associated with congenital diaphragmatic hernia (CDH), but its mechanism of action remains poorly understood. 'Omic' readouts capture metabolic and lipid processing function, which aid in understanding CDH and TO metabolic mechanisms.

METHODS

CDH was created in fetal rabbits at 23 days, TO at 28 days and lung collection at 31 days (Term ∼32 days). Lung-body weight ratio (LBWR) and mean terminal bronchiole density (MTBD) were determined. In a cohort, left and right lungs were collected, weighed, and samples homogenized, and extracts collected for non-targeted metabolomic and lipidomic profiling via LC-MS and LC-MS/MS, respectively.

RESULTS

LBWR was significantly lower in CDH while CDH + TO was similar to controls (p = 0.003). MTBD was significantly higher in CDH fetuses and restored to control and sham levels in CDH + TO (p < 0.001). CDH and CDH + TO resulted in significant differences in metabolome and lipidome profiles compared to sham controls. A significant number of altered metabolites and lipids between the controls and CDH groups and the CDH and CDH + TO fetuses were identified. Significant changes in the ubiquinone and other terpenoid-quinone biosynthesis pathway and the tyrosine metabolism pathway were observed in CDH + TO.

CONCLUSION

CDH + TO reverses pulmonary hypoplasia in the CDH rabbit, in association with a specific metabolic and lipid signature. A synergistic untargeted 'omics' approach provides a global signature for CDH and CDH + TO, highlighting cellular mechanisms among lipids and other metabolites, enabling comprehensive network analysis to identify critical metabolic drivers in disease pathology and recovery.

TYPE OF STUDY

Basic Science, Prospective.

LEVEL OF EVIDENCE

II.

Biomarker discovery for tuberculosis using metabolomics

Tuberculosis (TB) is the leading cause of death among infectious diseases, and the ratio of cases in which its pathogen Mycobacterium tuberculosis (Mtb) is drug resistant has been increasing worldwide, whereas latent tuberculosis infection (LTBI) may develop into active TB. Thus it is important to understand the mechanism of drug resistance, find new drugs, and find biomarkers for TB diagnosis. The rapid progress of metabolomics has enabled quantitative metabolite profiling of both the host and the pathogen. In this context, we provide recent progress in the application of metabolomics toward biomarker discovery for tuberculosis. In particular, we first focus on biomarkers based on blood or other body fluids for diagnosing active TB, identifying LTBI and predicting the risk of developing active TB, as well as monitoring the effectiveness of anti-TB drugs. Then we discuss the pathogen-based biomarker research for identifying drug resistant TB. While there have been many reports of potential candidate biomarkers, validations and clinical testing as well as improved bioinformatics analysis are needed to further substantiate and select key biomarkers before they can be made clinically applicable.

Plasma microRNA and metabolic changes associated with pediatric acute respiratory distress syndrome: a prospective cohort study

Acute respiratory distress syndrome is a heterogeneous pathophysiological process responsible for significant morbidity and mortality in pediatric intensive care patients. Diagnosis is defined by clinical characteristics that identify the syndrome after development. Subphenotyping patients at risk of progression to ARDS could provide the opportunity for therapeutic intervention. microRNAs, non-coding RNAs stable in circulation, are a promising biomarker candidate. We conducted a single-center prospective cohort study to evaluate random forest classification of microarray-quantified circulating microRNAs in critically ill pediatric patients. We additionally selected a sub-cohort for parallel metabolomics profiling as a pilot study for concurrent use of miRNAs and metabolites as circulating biomarkers. In 35 patients (n = 21 acute respiratory distress, n = 14 control) 15 microRNAs were differentially expressed. Unsupervised random forest classification accurately grouped ARDS and control patients with an area under the curve of 0.762, which was improved to 0.839 when subset to only patients with bacterial infection. Nine metabolites were differentially abundant between acute respiratory distress and control patients (n = 4, both groups) and abundance was highly correlated with miRNA expression. Random forest classification of microRNAs differentiated critically ill pediatric patients who developed acute respiratory distress relative to those who do not. The differential expression of microRNAs and metabolites provides a strong foundation for further work to validate their use as a prognostic biomarker.

Landscape of Metabolic Fingerprinting for Diagnosis and Risk Stratification of Sepsis

Background

Sepsis and septic shock, a subset of sepsis with higher risk stratification, are hallmarked by high mortality rates and necessitated early and accurate biomarkers.

Methods

Untargeted metabolomic analysis was performed to compare the metabolic features between the sepsis and control systemic inflammatory response syndrome (SIRS) groups in discovery cohort, and potential metabolic biomarkers were selected and quantified using multiple reaction monitoring based target metabolite detection method.

Results

Differentially expressed metabolites including 46 metabolites in positive electrospray ionization (ESI) ion mode, 22 metabolites in negative ESI ion mode, and 4 metabolites with dual mode between sepsis and SIRS were identified and revealed. Metabolites 5-Oxoproline, L-Kynurenine and Leukotriene D4 were selected based on least absolute shrinkage and selection operator regularization logistic regression and differential expressed between sepsis and septic shock group in the training and test cohorts. Respective risk scores for sepsis and septic shock based on a 3-metabolite fingerprint classifier were established to distinguish sepsis from SIRS, septic shock from sepsis. Significant relationship between developed sepsis risk scores, septic shock risk scores and Sequential (sepsis-related) Organ Failure Assessment (SOFA), procalcitonin (PCT) and lactic acid were observed.

Conclusions

Collectively, our findings demonstrated that the characteristics of plasma metabolites not only manifest phenotypic variation in sepsis onset and risk stratification of sepsis but also enable individualized treatment and improve current therapeutic strategies.

Tuberculous Granuloma: Emerging Insights From Proteomics and Metabolomics

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

Using Omics to Study Leprosy, Tuberculosis, and Other Mycobacterial Diseases

Mycobacteria are members of the Actinomycetales order, and they are classified into one family, Mycobacteriaceae. More than 20 mycobacterial species cause disease in humans. The Mycobacterium group, called the Mycobacterium tuberculosis complex (MTBC), has nine closely related species that cause tuberculosis in animals and humans. TB can be detected worldwide and one-fourth of the world's population is contaminated with tuberculosis. According to the WHO, about two million dies from it, and more than nine million people are newly infected with TB each year. Mycobacterium tuberculosis (M. tuberculosis) is the most potential causative agent of tuberculosis and prompts enormous mortality and morbidity worldwide due to the incompletely understood pathogenesis of human tuberculosis. Moreover, modern diagnostic approaches for human tuberculosis are inefficient and have many lacks, while MTBC species can modulate host immune response and escape host immune attacks to sustain in the human body. "Multi-omics" strategies such as genomics, transcriptomics, proteomics, metabolomics, and deep sequencing technologies could be a comprehensive strategy to investigate the pathogenesis of mycobacterial species in humans and offer significant discovery to find out biomarkers at the early stage of disease in the host. Thus, in this review, we attempt to understand an overview of the mission of "omics" approaches in mycobacterial pathogenesis, including tuberculosis, leprosy, and other mycobacterial diseases.

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.

Metabolomics as a Tool to Investigate HIV/TB Co-Infection

The HIV/AIDS (human immunodeficiency virus/acquired immunodeficiency syndrome) and tuberculosis (TB) pandemics are perpetuated by a significant global burden of HIV/TB co-infection. The synergy between HIV and Mycobacterium tuberculosis (Mtb) during co-infection of a host is well established. While this synergy is known to be driven by immunological deterioration, the metabolic mechanisms thereof remain poorly understood. Metabolomics has been applied to study various aspects of HIV and Mtb infection separately, yielding insights into infection- and treatment-induced metabolic adaptations experienced by the host. Despite the contributions that metabolomics has made to the field, this approach has not yet been systematically applied to characterize the HIV/TB co-infected state. Considering that limited HIV/TB co-infection metabolomics studies have been published to date, this review briefly summarizes what is known regarding the HIV/TB co-infection synergism from a conventional and metabolomics perspective. It then explores metabolomics as a tool for the improved characterization of HIV/TB co-infection in the context of previously published human-related HIV infection and TB investigations, respectively as well as for addressing the gaps in existing knowledge based on the similarities and deviating trends reported in these HIV infection and TB studies.

Discovery of serum biomarkers for diagnosis of tuberculosis by NMR metabolomics including cross-validation with a second cohort

Background

Tuberculosis (TB) is a disease with worldwide presence and a major cause of death in several developing countries. Current diagnostic methodologies often lack specificity and sensitivity, whereas a long time is needed to obtain a conclusive result.

Methods

In an effort to develop better diagnostic methods, this study aimed at the discovery of a biomarker signature for TB diagnosis using a Nuclear Magnetic Resonance based metabolomics approach. In this study, we acquired ¹H NMR spectra of blood serum samples of groups of healthy subjects, individuals with latent TB and of patients with pulmonary and extra-pulmonary TB. The resulting data were treated with uni- and multivariate statistical analysis.

Results

Six metabolites (inosine, hypoxanthine, mannose, asparagine, aspartate and glutamate) were validated by an independent cohort, all of them related with metabolic processes described as associated with TB infection.

Conclusion

The findings of the study are according with the WHO Target Product Profile recommendations for a triage test to rule-out active TB.

Human tuberculosis and Mycobacterium tuberculosis complex: A review on genetic diversity, pathogenesis and omics approaches in host biomarkers discovery

Mycobacterium tuberculosis complex (MTBC) refers to a group of mycobacteria encompassing nine members of closely related species that causes tuberculosis in animals and humans. Among the nine members, Mycobacterium tuberculosis (M. tuberculosis) remains the main causative agent for human tuberculosis that results in high mortality and morbidity globally. In general, MTBC species are low in diversity but exhibit distinctive biological differences and phenotypes among different MTBC lineages. MTBC species are likely to have evolved from a common ancestor through insertions/deletions processes resulting in species speciation with different degrees of pathogenicity. The pathogenesis of human tuberculosis is complex and remains poorly understood. It involves multi-interactions or evolutionary co-options between host factors and bacterial determinants for survival of the MTBC. Granuloma formation as a protection or survival mechanism in hosts by MTBC remains controversial. Additionally, MTBC species are capable of modulating host immune response and have adopted several mechanisms to evade from host immune attack in order to survive in humans. On the other hand, current diagnostic tools for human tuberculosis are inadequate and have several shortcomings. Numerous studies have suggested the potential of host biomarkers in early diagnosis of tuberculosis, in disease differentiation and in treatment monitoring. "Multi-omics" approaches provide holistic views to dissect the association of MTBC species with humans and offer great advantages in host biomarkers discovery. Thus, in this review, we seek to understand how the genetic variations in MTBC lead to species speciation with different pathogenicity. Furthermore, we also discuss how the host and bacterial players contribute to the pathogenesis of human tuberculosis. Lastly, we provide an overview of the journey of "omics" approaches in host biomarkers discovery in human tuberculosis and provide some interesting insights on the challenges and directions of "omics" approaches in host biomarkers innovation and clinical implementation.

Integration of metabolomics and transcriptomics reveals novel biomarkers in the blood for tuberculosis diagnosis in children

Pediatric tuberculosis (TB) remains a major global health problem. Improved pediatric diagnostics using readily available biosources are urgently needed. We used liquid chromatography-mass spectrometry to analyze plasma metabolite profiles of Indian children with active TB (n = 16) and age- and sex-matched, Mycobacterium tuberculosis-exposed but uninfected household contacts (n = 32). Metabolomic data were integrated with whole blood transcriptomic data for each participant at diagnosis and throughout treatment for drug-susceptible TB. A decision tree algorithm identified 3 metabolites that correctly identified TB status at distinct times during treatment. N-acetylneuraminate achieved an area under the receiver operating characteristic curve (AUC) of 0.66 at diagnosis. Quinolinate achieved an AUC of 0.77 after 1 month of treatment, and pyridoxate achieved an AUC of 0.87 after successful treatment completion. A set of 4 metabolites (gamma-glutamylalanine, gamma-glutamylglycine, glutamine, and pyridoxate) identified treatment response with an AUC of 0.86. Pathway enrichment analyses of these metabolites and corresponding transcriptional data correlated N-acetylneuraminate with immunoregulatory interactions between lymphoid and non-lymphoid cells, and correlated pyridoxate with p53-regulated metabolic genes and mitochondrial translation. Our findings shed new light on metabolic dysregulation in children with TB and pave the way for new diagnostic and treatment response markers in pediatric TB.

Tuberculosis causes highly conserved metabolic changes in human patients, mycobacteria-infected mice and zebrafish larvae

Tuberculosis is a highly infectious and potentially fatal disease accompanied by wasting symptoms, which cause severe metabolic changes in infected people. In this study we have compared the effect of mycobacteria infection on the level of metabolites in blood of humans and mice and whole zebrafish larvae using one highly standardized mass spectrometry pipeline, ensuring technical comparability of the results. Quantification of a range of circulating small amines showed that the levels of the majority of these compounds were significantly decreased in all three groups of infected organisms. Ten of these metabolites were common between the three different organisms comprising: methionine, asparagine, cysteine, threonine, serine, tryptophan, leucine, citrulline, ethanolamine and phenylalanine. The metabolomic changes of zebrafish larvae after infection were confirmed by nuclear magnetic resonance spectroscopy. Our study identified common biomarkers for tuberculosis disease in humans, mice and zebrafish, showing across species conservation of metabolic reprogramming processes as a result of disease. Apparently, the mechanisms underlying these processes are independent of environmental, developmental and vertebrate evolutionary factors. The zebrafish larval model is highly suited to further investigate the mechanism of metabolic reprogramming and the connection with wasting syndrome due to infection by mycobacteria.

The Echo of Pulmonary Tuberculosis: Mechanisms of Clinical Symptoms and Other Disease-Induced Systemic Complications

Clinical symptoms of active tuberculosis (TB) can range from a simple cough to more severe reactions, such as irreversible lung damage and, eventually, death, depending on disease progression. In addition to its clinical presentation, TB has been associated with several other disease-induced systemic complications, such as hyponatremia and glucose intolerance. Here, we provide an overview of the known, although ill-described, underlying biochemical mechanisms responsible for the clinical and systemic presentations associated with this disease and discuss novel hypotheses recently generated by various omics technologies. This summative update can assist clinicians to improve the tentative diagnosis of TB based on a patient's clinical presentation and aid in the development of improved treatment protocols specifically aimed at restoring the disease-induced imbalance for overall homeostasis while simultaneously eradicating the pathogen. Furthermore, future applications of this knowledge could be applied to personalized diagnostic and therapeutic options, bettering the treatment outcome and quality of life of TB patients.

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.

Identification of serum biomarkers for active pulmonary tuberculosis using a targeted metabolomics approach

Although tuberculosis (TB) is a severe health problem worldwide, the current diagnostic methods are far from optimal. Metabolomics is increasingly being used in the study of infectious diseases. We performed metabolome profiling to identify potential biomarkers in patients with active TB. Serum samples from 21 patients with active pulmonary TB, 20 subjects with latent TB infection (LTBI), and 28 healthy controls were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by multivariate and univariate analyses. Metabolic profiles indicated higher serum levels of glutamate, sulfoxy methionine, and aspartate and lower serum levels of glutamine, methionine, and asparagine in active TB patients than in LTBI subjects or healthy controls. The ratios between metabolically related partners (glutamate/glutamine, sulfoxy methionine/methionine, and aspartate/asparagine) were also elevated in the active TB group. There was no significant difference in the serum concentration of these metabolites according to the disease extent or risk of relapse in active TB patients. Novel serum biomarkers such as glutamate, sulfoxy methionine, aspartate, glutamine, methionine, and asparagine are potentially useful for adjunctive, rapid, and noninvasive pulmonary TB diagnosis.

The application of metabolomics toward pulmonary tuberculosis research

In the quest to identify novel biomarkers for pulmonary tuberculosis (TB), high-throughput systems biology approaches such as metabolomics has become increasingly widespread. Such biomarkers have not only successfully been used for better disease characterization, but have also provided new insights toward the future development of improved diagnostic and therapeutic approaches. In this review, we give a summary of the metabolomics studies done to date, with a specific focus on those investigating various aspects of pulmonary TB, and the infectious agent responsible, Mycobacterium tuberculosis. These studies, done on a variety of sample matrices, including bacteriological culture, sputum, blood, urine, tissue, and breath, are discussed in terms of their intended research outcomes or future clinical applications. Additionally, a summary of the research model, sample cohort, analytical apparatus and statistical methods used for biomarker identification in each of these studies, is provided.

Potential role for Rv2026c- and Rv2421c- specific antibody responses in diagnosing active tuberculosis

The current diagnostic methods for tuberculosis (TB) have several limitations. Although commercial serological tests based on antibody detection are available, their variable accuracies limit their roles in the clinic. The aim of this study was to discover the improved biomarkers for TB disease by investigating the serum profiles of IgG and IgM antibodies against nearly all Mycobacterium tuberculosis (MTB) antigens in 36 active TB patients and 18 healthy controls (HCs) using proteome microarrays. Our results revealed that multiple antigens could induce stronger serum IgG or IgM responses in TB patients compared to HCs, among them, Rv2026c and Rv2421c were further validated by ELISA with sera from 221 samples and showed the moderate performance in diagnosing TB by receiver operating characteristic analysis. Moreover, logistic regression analysis was performed to establish a combined panel that provided better sensitivity and specificity at 82.5% and 88.12%, respectively, than single antigens in the diagnosis of active TB. Furthermore, the antibody reactivity against Rv2026c and Rv2421c was correlated with clinical backgrounds. These results suggest that the combination of different antigens and classes of antibodies could provide promise and encouragement in developing an efficient serological test for the diagnosis of active TB.

Metabolomics applied to the discovery of tuberculosis and diabetes mellitus biomarkers

Tuberculosis (TB) and diabetes mellitus Type 2 (DM2) are two diseases as ancient as they are harmful to human health. The outcome for both diseases in part depends on immune and metabolic individual responses. DM2 is increasing yearly, mainly due to environmental, genetic and lifestyle habits. There are multiple evidence that DM2 is one of the most important risk factor of becoming infected with TB or reactivating latent TB. Mass spectrometry-based metabolomics is an important tool for elucidating the metabolites and metabolic pathways that influence the immune responses to M. tuberculosis infection during diabetes. We provide an up-to-date review highlighting the importance and benefit of metabolomics for identifying biomarkers as candidate molecules for diagnosis, disease activity or prognosis.

First-line anti-tuberculosis drugs induce hepatotoxicity: A novel mechanism based on a urinary metabolomics platform

Tuberculosis (TB) has become a global public health and social threat. As clinical first-line drugs, rifampicin and isoniazid used in combination with pyrazinamide and ethambutol (the HRZE regimen) usually induce hepatotoxicity. However, the mechanisms underlying this phenomenon remain unclear, and studying the metabolic impact of co-treating TB patients with the HRZE regimen can provide new hepatotoxicity evidence. In this study, urine metabolites from TB patients were profiled using a high-resolution ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) platform. The tricarboxylic acid circulation, arginine and proline metabolism and purine metabolic pathways were found to be affected by anti-TB drugs. The levels of pyroglutamate, isocitrate, citrate, and xanthine were significantly decreased after the administration of HRZE. The above mentioned pathways were also different between drug-induced liver injury (DILI) and non-DILI patients. Urate and cis-4-octenedioic acid levels in the DILI group were significantly increased compared to those in the non-DILI group, while the cis-aconitate and hypoxanthine levels were significantly decreased. These results highlight that superoxide generation can aggravate the hepatotoxic effects of the HRZE regimen. In addition, our metabolomic approach had the ability to predict hepatotoxicity for clinical applications.

Th1 cytokines, true functional signatures for protective immunity against TB?

The lack of an effective preventative vaccine against tuberculosis (TB) presents a great challenge to TB control. Since it takes an extremely long time to accurately determine the protective efficacy of TB vaccines, there is a great need to identify the surrogate signatures of protection to facilitate vaccine development. Unfortunately, antigen-specific Th1 cytokines that are currently used to evaluate the protective efficacy of the TB vaccine, do not align with the protection and failure of TB vaccine candidates in clinical trials. In this review, we discuss the limitation of current Th1 cytokines as surrogates of protection and address the potential elements that should be considered to finalize the true functional signatures of protective immunity against TB.

Metabolomics biomarkers for tuberculosis diagnostics: current status and future objectives

Numerous studies have contributed to our current understanding of the complex biology of pulmonary tuberculosis and subsequently provided solutions to its control or eradication. Metabolomics, a newcomer to the Omics research domain, has significantly contributed to this understanding by identifying biomarkers originating from the disease-associated metabolome adaptations of both the microbe and host. These biomarkers have shed light on previously unknown disease mechanisms, many of which have been implemented toward the development of improved diagnostic strategies. In this review, we will discuss the role that metabolomics has played in tuberculosis research to date, with a specific focus on new biomarker identification, and how these have contributed to improved disease characterization and diagnostics, and their potential clinical applications.

A 52-week safety study in cynomolgus macaques for genetically modified rice expressing Cry1Ab/1Ac protein

A 52-week feeding study in cynomolgus macaques was carried out to evaluate the safety of Bt rice Huahui 1 (HH1), a transgenic rice line expressing Cry1Ab/1Ac protein. Monkeys were fed a diet with 20% or 60% HH1 rice, 20% or 60% parental rice (Minghui 63, MH63), normal diet, normal diet spiked with purified recombinant Cry1Ab/1Ac fusion protein or bovine serum albumin (BSA) respectively. During the feeding trail, clinical observations were conducted daily, and multiple parameters, including body weight, body temperature, electrocardiogram, hematology, blood biochemistry, serum metabolome and gut microbiome were examined at regular intervals. Upon sacrifice, the organs were weighted, and the macroscopic, microscopic and electron microscopic examinations were performed. The results show no adverse or toxic effects of Bt rice HH1 or Cry1Ab/1Ac fusion protein on monkeys. Therefore, the present 52-week primate feeding study suggests that the transgenic rice containing Cry 1Ab/1Ac is equivalent to its parental rice line MH63.

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.

Neglected diseases prioritized in Brazil under the perspective of metabolomics: A review

This review article compiles in a critical manner literature publications regarding seven neglected diseases (ND) prioritized in Brazil (Chagas disease, dengue, leishmaniasis, leprosy, malaria, schistosomiasis, and tuberculosis) under the perspective of metabolomics. Both strategies, targeted and untargeted metabolomics, were considered in the compilation. The majority of studies focused on biomarker discovery for diagnostic purposes, and on the search of novel or alternative therapies against the ND under consideration, although temporal progression of the infection at metabolic level was also addressed. Tuberculosis, followed by schistosomiasis, malaria and leishmaniasis are the diseases that received larger attention in terms of number of publications. Dengue and leprosy were the least studied and Chagas disease received intermediate attention. NMR and HPLC-MS technologies continue to predominate among the analytical platforms of choice in the metabolomic studies of ND. A plethora of metabolites were identified in the compiled studies, with expressive predominancy of amino acids, organic acids, carbohydrates, nucleosides, lipids, fatty acids, and derivatives.

Deregulated tyrosine-phenylalanine metabolism in pulmonary tuberculosis patients

Metabolic profiling of biofluids from tuberculosis (TB) patients would help us in understanding the disease pathophysiology and may also be useful for the development of novel diagnostics and host-directed therapy. In this pilot study we have compared the urine metabolic profiles of two groups of subjects having similar TB symptoms and categorized as active TB (ATB, n = 21) and non-TB (NTB, n = 21) based on GeneXpert test results. Silylation, gas chromatography mass spectrometry, and standard chemometric methods were employed to identify the important molecules and deregulated metabolic pathways. Eleven active TB patients were followed up on longitudinally for comparative urine metabolic profiling with healthy controls (n = 11). A set of 42 features qualified to have a variable importance parameter score of > 1.5 of a partial least-squares discriminate analysis model and fold change of > 1.5 at p value < 0.05 between ATB and NTB. Using these variables, a receiver operating characteristics curve was plotted and the area under the curve was calculated to be 0.85 (95% CI: 0.72-0.96). Several of these variables that represent norepinephrine, gentisic acid, 4-hydroxybenzoic acid, hydroquinone, and 4-hydroxyhippuric acid are part of the tyrosine-phenylalanine metabolic pathway. In the longitudinal study we observed a treatment-dependent trend in the urine metabolome of follow-up samples, and subjects declared as clinically cured showed similar metabolic profile as those of asymptomatic healthy subjects. The deregulated tyrosine-phenylalanine axis reveals a potential target for diagnostics and intervention in TB.

Plasma metabolomics in human pulmonary tuberculosis disease: a pilot study

We aimed to characterize metabolites during tuberculosis (TB) disease and identify new pathophysiologic pathways involved in infection as well as biomarkers of TB onset, progression and resolution. Such data may inform development of new anti-tuberculosis drugs. Plasma samples from adults with newly diagnosed pulmonary TB disease and their matched, asymptomatic, sputum culture-negative household contacts were analyzed using liquid chromatography high-resolution mass spectrometry (LC-MS) to identify metabolites. Statistical and bioinformatics methods were used to select accurate mass/charge (m/z) ions that were significantly different between the two groups at a false discovery rate (FDR) of q<0.05. Two-way hierarchical cluster analysis (HCA) was used to identify clusters of ions contributing to separation of cases and controls, and metabolomics databases were used to match these ions to known metabolites. Identity of specific D-series resolvins, glutamate and Mycobacterium tuberculosis (Mtb)-derived trehalose-6-mycolate was confirmed using LC-MS/MS analysis. Over 23,000 metabolites were detected in untargeted metabolomic analysis and 61 metabolites were significantly different between the two groups. HCA revealed 8 metabolite clusters containing metabolites largely upregulated in patients with TB disease, including anti-TB drugs, glutamate, choline derivatives, Mycobacterium tuberculosis-derived cell wall glycolipids (trehalose-6-mycolate and phosphatidylinositol) and pro-resolving lipid mediators of inflammation, known to stimulate resolution, efferocytosis and microbial killing. The resolvins were confirmed to be RvD1, aspirin-triggered RvD1, and RvD2. This study shows that high-resolution metabolomic analysis can differentiate patients with active TB disease from their asymptomatic household contacts. Specific metabolites upregulated in the plasma of patients with active TB disease, including Mtb-derived glycolipids and resolvins, have potential as biomarkers and may reveal pathways involved in TB disease pathogenesis and resolution.