Metabolomics: Applications and Promise in Mycobacterial Disease

Amino acid profiling as a screening and prognostic biomarker in active tuberculosis patients

BACKGROUND

Tuberculosis (TB) is one of the world's most deadly chronic infectious diseases; early diagnosis contributes to reducing disease transmission among populations. However, discovering novel diagnostic and prognostic biomarkers is still an important topic in the field of TB. Amino acid is the basic unit of protein composition, and its structure and physicochemical characteristics are more stable. Therefore, it is a potential target for TB diagnosis and the prediction of TB development.

METHODS

In this study, the blood of healthy people (HC), TB patients (TB), cured TB (RxTB), and other non-TB pneumonia patients (PN) were collected to detect the levels of amino acids in whole blood and plasma using ultra-high performance liquid chromatography coupled with mass spectrometry.

RESULTS

We detected that the amino acid levels correlated with participants status (TB, HC, RxTB, or PN) and the degree of lung damage. The results showed that phenylalanine had a good effect on the screening of TB (AUC = 0.924). We then built a TB prediction model. The model, which was based on the ratio of plasma amino acid content to whole blood amino acid content, showed good performance for the screening of TB, with 84% (95% CI = 60-97) sensitivity and 97% (95% CI = 83-100) specificity. The result of correlation between the HRCT score and amino acid level indicated that the glutamine content of plasma was significantly inversely associated with disease severity. Additionally, ornithine levels in the plasma of RxTB group reduced and four amino acids of which the ratio in plasma to whole blood showed significantly changed.

CONCLUSIONS

Taken together, amino acid profiling can be used for TB screening, and a multiparameter profiling model is better. The profiling can also reflect the severity of lung damage. Moreover, the amino acid profile is useful for reflecting the efficacy of TB treatment.

Artefact Profiling: Panomics Approaches for Understanding the Materiality of Written Artefacts

This review explains the strategies behind genomics, proteomics, metabolomics, metallomics and isotopolomics approaches and their applicability to written artefacts. The respective sub-chapters give an insight into the analytical procedure and the conclusions drawn from such analyses. A distinction is made between information that can be obtained from the materials used in the respective manuscript and meta-information that cannot be obtained from the manuscript itself, but from residues of organisms such as bacteria or the authors and readers. In addition, various sampling techniques are discussed in particular, which pose a special challenge in manuscripts. The focus is on high-resolution, non-targeted strategies that can be used to extract the maximum amount of information about ancient objects. The combination of the various omics disciplines (panomics) especially offers potential added value in terms of the best possible interpretations of the data received. The information obtained can be used to understand the production of ancient artefacts, to gain impressions of former living conditions, to prove their authenticity, to assess whether there is a toxic hazard in handling the manuscripts, and to be able to determine appropriate measures for their conservation and restoration.

Therapeutic Potentials of Immunometabolomic Modulations Induced by Tuberculosis Vaccination

Metabolomics is emerging as a promising tool to understand the effect of immunometabolism for the development of novel host-directed alternative therapies. Immunometabolism can modulate both innate and adaptive immunity in response to pathogens and vaccinations. For instance, infections can affect lipid and amino acid metabolism while vaccines can trigger bile acid and carbohydrate pathways. Metabolomics as a vaccinomics tool, can provide a broader picture of vaccine-induced biochemical changes and pave a path to potentiate the vaccine efficacy. Its integration with other systems biology tools or treatment modes can enhance the cure, response rate, and control over the emergence of drug-resistant strains. Mycobacterium tuberculosis (Mtb) infection can remodel the host metabolism for its survival, while there are many biochemical pathways that the host adjusts to combat the infection. Similarly, the anti-TB vaccine, Bacillus Calmette-Guerin (BCG), was also found to affect the host metabolic pathways thus modulating immune responses. In this review, we highlight the metabolomic schema of the anti-TB vaccine and its therapeutic applications. Rewiring of immune metabolism upon BCG vaccination induces different signaling pathways which lead to epigenetic modifications underlying trained immunity. Metabolic pathways such as glycolysis, central carbon metabolism, and cholesterol synthesis play an important role in these aspects of immunity. Trained immunity and its applications are increasing day by day and it can be used to develop the next generation of vaccines to treat various other infections and orphan diseases. Our goal is to provide fresh insight into this direction and connect various dots to develop a conceptual framework.

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.

Metabolomics assessment of vitamin D impact in Pam3CSK4 stimulation

Mycobacterium tuberculosis, a causative agent of tuberculosis, is amongst the leading causes of mycobacterial mortality worldwide. Although several studies have proposed the possible therapeutic role of vitamin D in antimycobacterial...

Dissecting Host-Pathogen Interactions in TB Using Systems-Based Omic Approaches

Tuberculosis (TB) is a devastating infectious disease that kills over a million people every year. There is an increasing burden of multi drug resistance (MDR) and extensively drug resistance (XDR) TB. New and improved therapies are urgently needed to overcome the limitations of current treatment. The causative agent, Mycobacterium tuberculosis (Mtb) is one of the most successful pathogens that can manipulate host cell environment for adaptation, evading immune defences, virulence, and pathogenesis of TB infection. Host-pathogen interaction is important to establish infection and it involves a complex set of processes. Metabolic cross talk between the host and pathogen is a facet of TB infection and has been an important topic of research where there is growing interest in developing therapies and drugs that target these interactions and metabolism of the pathogen in the host. Mtb scavenges multiple nutrient sources from the host and has adapted its metabolism to survive in the intracellular niche. Advancements in systems-based omic technologies have been successful to unravel host-pathogen interactions in TB. In this review we discuss the application and usefulness of omics in TB research that provides promising interventions for developing anti-TB therapies.

Metabolomic Changes in Naturally MAP-Infected Holstein-Friesian Heifers Indicate Immunologically Related Biochemical Reprogramming

Johne’s disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), causes weight loss, diarrhoea, and reduced milk yields in clinically infected cattle. Asymptomatic, subclinically infected cattle shed MAP bacteria but are frequently not detected by diagnostic tests. Herein, we compare the metabolite profiles of sera from subclinically infected Holstein–Friesian heifers and antibody binding to selected MAP antigens. The study used biobanked serum samples from 10 naturally MAP-infected and 10 control heifers, sampled monthly from ~1 to 19 months of age. Sera were assessed using flow infusion electrospray–high-resolution mass spectrometry (FIE–HRMS) on a Q Exactive hybrid quadrupole–Orbitrap mass spectrometer for high-throughput, sensitive, non-targeted metabolite fingerprinting. Partial least-squares discriminant analyses (PLS-DA) and hierarchical cluster analysis (HCA) of the data discriminated between naturally MAP-infected and control heifers. In total, 33 metabolites that differentially accumulated in naturally MAP-infected heifers compared to controls were identified. Five were significantly elevated within MAP-infected heifers throughout the study, i.e., leukotriene B4, bicyclo prostaglandin E2 (bicyclo PGE2), itaconic acid, 2-hydroxyglutaric acid and N6-acetyl-L-lysine. These findings highlight the potential of metabolomics in the identification of novel MAP diagnostic markers and particular biochemical pathways, which may provide insights into the bovine immune response to MAP.

Urine NMR-based TB metabolic fingerprinting for the diagnosis of TB in children

Tuberculosis (TB) is a major cause of morbidity and mortality in children, and early diagnosis and treatment are crucial to reduce long-term morbidity and mortality. In this study, we explore whether urine nuclear magnetic resonance (NMR)-based metabolomics could be used to identify differences in the metabolic response of children with different diagnostic certainty of TB. We included 62 children with signs and symptoms of TB and 55 apparently healthy children. Six of the children with presumptive TB had bacteriologically confirmed TB, 52 children with unconfirmed TB, and 4 children with unlikely TB. Urine metabolic fingerprints were identified using high- and low-field proton NMR platforms and assessed with pattern recognition techniques such as principal components analysis and partial least squares discriminant analysis. We observed differences in the metabolic fingerprint of children with bacteriologically confirmed and unconfirmed TB compared to children with unlikely TB (p = 0.041 and p = 0.013, respectively). Moreover, children with unconfirmed TB with X-rays compatible with TB showed differences in the metabolic fingerprint compared to children with non-pathological X-rays (p = 0.009). Differences in the metabolic fingerprint in children with different diagnostic certainty of TB could contribute to a more accurate characterisation of TB in the paediatric population. The use of metabolomics could be useful to improve the prediction of TB progression and diagnosis in children.

Usnic Acid Treatment Changes the Composition of Mycobacterium tuberculosis Cell Envelope and Alters Bacterial Redox Status

Mycobacterium tuberculosis developed efficient adaptation mechanisms in response to different environmental conditions. This resulted in the ability to survive in human macrophages and in resistance to numerous antibiotics. To get insight into bacterial responses to potent antimycobacterial natural compounds, we tested how usnic acid, a lichen-derived secondary metabolite, would influence mycobacteria at transcriptomic and metabolomic levels. The analysis of expression of sigma factors revealed a profound impact of usnic acid on one of the primary genetic regulatory systems of M. tuberculosis Combined liquid chromatography-mass spectrometry and nuclear magnetic resonance analyses allowed us to observe the perturbations in metabolic pathways, as well as in lipid composition, which took place within 24 h of exposure. Early bacterial response was related to redox homeostasis, lipid synthesis, and nucleic acid repair. Usnic acid treatment provoked disturbances of redox state in mycobacterial cells and increased production of structural elements of the cell wall and cell membrane. In addition, to increase the number of molecules related to restoration of redox balance, the rearrangements of the cell envelope were the first defense mechanisms observed under usnic acid treatment.IMPORTANCE The evaluation of mechanisms of mycobacterial response to natural products has been barely studied. However, it might be helpful to reveal bacterial adaptation strategies, which are eventually crucial for the discovery of new drug targets and, hence, understanding the resistance mechanisms. This study showed that the first-line mycobacterial defense against usnic acid, a potent antimicrobial agent, is the remodeling of the cell envelope and restoring redox homeostasis. Transcriptomic data correlated with metabolomics analysis. The observed metabolic changes appeared similar to those exerted by antibiotics.

Metabolomics of Withania somnifera (L.) Dunal: Advances and applications

ETHNOPHARMACOLOGICAL RELEVANCE

Withania somnifera L. (Solanaceae), commonly known as Ashwagandha or Indian ginseng, is used in Ayurveda (Indian system of traditional medicine) for vitality, cardio-protection and treating other ailments, such as neurological disorders, gout, and skin diseases.

AIM OF THE REVIEW

We present a critical overview of the information on the metabolomics of W. somnifera and highlight the significance of the technique for use in quality control of medicinal products. We have also pointed out the use of metabolomics to distinguish varieties and to identify best methods of cultivation, collection, as well as extraction.

MATERIAL AND METHODS

The relevant information on medicinal value, phytochemical studies, metabolomics of W. somnifera, and their applications were collected from a rigorous electronic search through scientific databases, including Scopus, PubMed, Web of Science and Google Scholar. Structures of selected metabolites were from the PubChem.

RESULTS

The pharmacological activities of W. somnifera were well documented. Roots are the most important parts of the plant used in Ayurvedic preparations. Stem and leaves also have a rich content of bioactive phytochemicals like steroidal lactones, alkaloids, and phenolic acids. Metabolomic studies revealed that metabolite profiles of W. somnifera depended on plant parts collected and the developmental stage of the plant, besides the season of sample collection and geographical location. The levels of withanolides were variable, depending on the morpho/chemotypes within the species of W. somnifera. Although studies on W. somnifera were initiated several years ago, the complexity of secondary metabolites was not realized due to the lack of adequate and fool-proof technology for phytochemical fingerprinting. Sophistications in chromatography coupled to mass spectrometry facilitated the discovery of several new metabolites. Mutually complementary techniques like LC-MS, GC-MS, HPTLC, and NMR were employed to obtain a comprehensive metabolomic profile. Subsequent data analyses and searches against spectral databases enabled the annotation of signals and dereplication of metabolites in several numbers without isolating them individually.

CONCLUSIONS

The present review provides a critical update of metabolomic data and the diverse application of the technique. The identification of parameters for standardization and quality control of herbal products is essential to facilitate mandatory checks for the purity of formulation. Such studies would enable us to identify the best geographical location of plants and the time of collection. We recommend the use of metabolomic analysis of herbal products based on W. somnifera for quality control as well as the discovery of novel bioactive compounds.

Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker

Despite efforts to improve tuberculosis (TB) detection, limitations in access, quality and timeliness of diagnostic services in low- and middle-income countries are challenging for current TB diagnostics. This study aimed to identify and characterise a metabolic profile of TB in urine by high-field nuclear magnetic resonance (NMR) spectrometry and assess whether the TB metabolic profile is also detected by a low-field benchtop NMR spectrometer. We included 189 patients with tuberculosis, 42 patients with pneumococcal pneumonia, 61 individuals infected with latent tuberculosis and 40 uninfected individuals. We acquired the urine spectra from high and low-field NMR. We characterised a TB metabolic fingerprint from the Principal Component Analysis. We developed a classification model from the Partial Least Squares-Discriminant Analysis and evaluated its performance. We identified a metabolic fingerprint of 31 chemical shift regions assigned to eight metabolites (aminoadipic acid, citrate, creatine, creatinine, glucose, mannitol, phenylalanine, and hippurate). The model developed using low-field NMR urine spectra correctly classified 87.32%, 85.21% and 100% of the TB patients compared to pneumococcal pneumonia patients, LTBI and uninfected individuals, respectively. The model validation correctly classified 84.10% of the TB patients. We have identified and characterised a metabolic profile of TB in urine from a high-field NMR spectrometer and have also detected it using a low-field benchtop NMR spectrometer. The models developed from the metabolic profile of TB identified by both NMR technologies were able to discriminate TB patients from the rest of the study groups and the results were not influenced by anti-TB treatment or TB location. This provides a new approach in the search for possible biomarkers for the diagnosis of TB.

Mycobacterium tuberculosis curli pili (MTP) deficiency is associated with alterations in cell wall biogenesis, fatty acid metabolism and amino acid synthesis

INTRODUCTION

In an effort to find alternative therapeutic interventions to combat tuberculosis, a better understanding of the pathophysiology of Mycobacterium tuberculosis is required. The Mycobacterium tuberculosis curli pili (MTP) adhesin, present on the surface of this pathogen, has previously been shown using functional genomics and global transcriptomics, to play an important role in establishing infection, bacterial aggregation, and modulating host response in vitro and in vivo.

OBJECTIVE

This investigation aimed to determine the role of MTP in modulating the metabolism of M. tuberculosis, using mtp gene-knockout mutant and complemented strains.

METHODS

Untargeted two-dimensional gas chromatography time-of-flight mass spectrometry, and bioinformatic analyses, were used to identify significant differences in the metabolite profiles among the wild-type, ∆mtp mutant and mtp-complemented strains, and validated with results generated by real-time quantitative PCR.

RESULTS

A total of 28 metabolites were found to be significantly altered when comparing the ∆mtp mutant and the wild-type strains indicating a decreased utilisation of metabolites in cell wall biogenesis, a reduced efficiency in the breakdown of fatty acids, and decreased amino acid biosynthesis in the former strain. Comparison of the wild-type to mtp-complement, and ∆mtp to mtp-complemented strains revealed 10 and 16 metabolite differences, respectively. Real-time quantitative PCR results supported the metabolomics findings. Complementation of the ∆mtp mutant resulted in a partial restoration of MTP function.

CONCLUSION

The lack of the MTP adhesin resulted in various bacterial cell wall alterations and related metabolic changes. This study highlights the importance of MTP as a virulence factor and further substantiates its potential use as a suitable biomarker for the development of diagnostic tools and intervention therapeutics against TB.

Insights into the Inhibition of Aeromonas hydrophila d-Alanine-d-Alanine Ligase by Integration of Kinetics and Structural Analysis

Aeromonas hydrophila, a pathogenic bacterium, is harmful to humans, domestic animals, and fishes and, moreover, of public health concern due to the emergence of multiple drug-resistant strains. The cell wall has been discovered as a novel and efficient drug target against bacteria, and d-alanine-d-alanine ligase (Ddl) is considered as an essential enzyme in bacterial cell wall biosynthesis. Herein, we studied the A. hydrophila HBNUAh01 Ddl (AhDdl) enzyme activity and kinetics and determined the crystal structure of AhDdl/d-Ala complex at 2.7 Å resolution. An enzymatic assay showed that AhDdl exhibited higher affinity to ATP (K_m: 54.1 ± 9.1 μM) compared to d-alanine (K_m: 1.01 ± 0.19 mM). The kinetic studies indicated a competitive inhibition of AhDdl by d-cycloserine (DCS), with an inhibition constant (K_i) of 120 μM and the 50% inhibitory concentrations (IC₅₀) value of 0.5 mM. Meanwhile, structural analysis indicated that the AhDdl/d-Ala complex structure adopted a semi-closed conformation form, and the active site was extremely conserved. Noteworthy is that the substrate d-Ala occupied the second d-Ala position, not the first d-Ala position. These results provided more insights for understanding the details of the catalytic mechanism and resources for the development of novel drugs against the diseases caused by A. hydrophila.

Comprehensive Examination of the Mouse Lung Metabolome Following Mycobacterium tuberculosis Infection Using a Multiplatform Mass Spectrometry Approach

The mechanisms whereby Mycobacterium tuberculosis (Mtb) rewires the host metabolism in vivo are surprisingly unexplored. Here, we used three high-resolution mass spectrometry platforms to track altered lung metabolic changes associated with Mtb infection of mice. The multiplatform data sets were merged using consensus orthogonal partial least squares-discriminant analysis (cOPLS-DA), an algorithm that allows for the joint interpretation of the results from a single multivariate analysis. We show that Mtb infection triggers a temporal and progressive catabolic state to satisfy the continuously changing energy demand to control infection. This causes dysregulation of metabolic and oxido-reductive pathways culminating in Mtb-associated wasting. Notably, high abundances of trimethylamine-N-oxide (TMAO), produced by the host from the bacterial metabolite trimethylamine upon infection, suggest that Mtb could exploit TMAO as an electron acceptor under anaerobic conditions. Overall, these new pathway alterations advance our understanding of the link between Mtb pathogenesis and metabolic dysregulation and could serve as a foundation for new therapeutic intervention strategies. Mass spectrometry data has been deposited in the Metabolomics Workbench repository (data-set identifier: ST001328).

A High-Performing Plasma Metabolite Panel for Early-Stage Lung Cancer Detection

The objective of this research is to use metabolomic techniques to discover and validate plasma metabolite biomarkers for the diagnosis of early-stage non-small cell lung cancer (NSCLC). The study included plasma samples from 156 patients with biopsy-confirmed NSCLC along with age and gender-matched plasma samples from 60 healthy controls. A fully quantitative targeted mass spectrometry (MS) analysis (targeting 138 metabolites) was performed on all samples. The sample set was split into a discovery set and validation set. Metabolite concentration data, clinical data, and smoking history were used to determine optimal sets of biomarkers and optimal regression models for identifying different stages of NSCLC using the discovery sets. The same biomarkers and regression models were used and assessed on the validation models. Univariate and multivariate statistical analysis identified β-hydroxybutyric acid, LysoPC 20:3, PC ae C40:6, citric acid, and fumaric acid as being significantly different between healthy controls and stage I/II NSCLC. Robust predictive models with areas under the curve (AUC) > 0.9 were developed and validated using these metabolites and other, easily measured clinical data for detecting different stages of NSCLC. This study successfully identified and validated a simple, high-performing, metabolite-based test for detecting early stage (I/II) NSCLC patients in plasma. While promising, further validation on larger and more diverse cohorts is still required.

Mycobacterium abscessus-Bronchial Epithelial Cells Cross-Talk Through Type I Interferon Signaling

Introduction: Mycobacteria are aerobic non-motile organisms with lipid rich, hydrophobic cell walls that render them resistant to antibiotics. While there are over 150 different species of NTM, Mycobacterium avium complex (MAC) and Mycobacterium abscessus (MAB) are two of the most common culprits of pulmonary infection. MAB has been found to be most common in southeastern United States (Florida to Texas) and the third most rapidly growing NTM infection. It is responsible for chronic lung infections. Mycobacterial cell wall components initiate the interaction between bacteria and host. The reaction between bronchial epithelia and components in the envelope of mycobacterial cell wall is poorly understood. Methods: A lung-on-membrane model was developed with normal human bronchial epithelial (NHBE) cells re-differentiated at the air-liquid interface (ALI) and human endothelial cells on a transwell^® polyester membrane. Microparticles from MAB cell walls were developed by an inhouse protocol and added to the ALI side of lung model. NHBE cells were harvested at day 3. RNA was isolated and analyzed with RNASeq. NHBE cells were lysed and protein assay was performed with western blot. We tested whether lung INF-alpha expression would increase in mice treated with intratracheal MAB cell wall particles. A paired t-test is used to compare two population means using GraphPad Prism 7 software. Results: RNAseq analysis identified 1759 differentially expressed genes between NHBE cells challenged with and without MAB microparticles with FDR < 0.5. 410 genes had a 2.5-fold change (FC) or greater. NHBE cells exposure to MAB microparticles significantly enriched the IFN I signaling pathway. Protein overexpression of IFN I family (2'-5'-Oligoadenylate Synthetase 1, Interferon-induced GTP-binding protein Mx1, Interferon-stimulated gene 15) was found in bronchial epithelial cells following exposure to MAB cell wall microparticles. IFN-α protein and gene expressions were significantly increased in mice lung challenged with microparticles in comparison with controls. Conclusion: These data strongly support the role of Type I IFN in cross-talk between NHBE cells and MAB. They also suggest that initiating immune response by NHBE cells may play a central role in innate immunity. Furthermore, this study underscores the importance of mycobacterial cell wall in initiating innate immune response.

Application of model systems to study adaptive responses of Mycobacterium tuberculosis during infection and disease

Tuberculosis (TB) claims more human lives than any other infectious organism. The lethal synergy between TB-HIV infection and the rapid emergence of drug resistant strains has created a global public health threat that requires urgent attention. Mycobacterium tuberculosis, the causative agent of TB is an exquisitely well-adapted human pathogen, displaying the ability to promptly remodel metabolism when encountering stressful environments during pathogenesis. A careful study of the mechanisms that enable this adaptation will enhance the understanding of key aspects related to the microbiology of TB disease. However, these efforts require microbiological model systems that mimic host conditions in the laboratory. Herein, we describe several in vitro model systems that generate non-replicating and differentially culturable mycobacteria. The changes that occur in the metabolism of M. tuberculosis in some of these models and how these relate to those reported for human TB disease are discussed. We describe mechanisms that tubercle bacteria use to resuscitate from these non-replicating conditions, together with phenotypic heterogeneity in terms of culturabiliy of M. tuberculosis in sputum. Transcriptional changes in M. tuberculosis that allow for adaptation of the organism to the lung environment are also summarized. Finally, given the emerging importance of the microbiome in various infectious diseases, we provide a description of how the lung and gut microbiome affect susceptibility to TB infection and response to treatment. Consideration of these collective aspects will enhance the understanding of basic metabolism, physiology, drug tolerance and persistence in M. tuberculosis to enable development of new therapeutic interventions.

Harnessing Biological Insight to Accelerate Tuberculosis Drug Discovery

Tuberculosis (TB) is the leading cause of mortality globally resulting from an infectious disease, killing almost 1.6 million people annually and accounting for approximately 30% of deaths attributed to antimicrobial resistance (AMR). This despite the widespread administration of a neonatal vaccine, and the availability of an effective combination drug therapy against the causative agent, Mycobacterium tuberculosis (Mtb). Instead, TB prevalence worldwide is characterized by high-burden regions in which co-epidemics, such as HIV, and social and economic factors, undermine efforts to control TB. These elements additionally ensure conditions that favor the emergence of drug-resistant Mtb strains, which further threaten prospects for future TB control. To address this challenge, significant resources have been invested in developing a TB drug pipeline, an initiative given impetus by the recent regulatory approval of two new anti-TB drugs. However, both drugs have been reserved for drug-resistant disease, and the seeming inevitability of new resistance plus the recognized need to shorten the duration of chemotherapy demands continual replenishment of the pipeline with high-quality "hits" with novel mechanisms of action. This represents a massive challenge, which has been undermined by key gaps in our understanding of Mtb physiology and metabolism, especially during host infection. Whereas drug discovery for other bacterial infections can rely on predictive in vitro assays and animal models, for Mtb, inherent metabolic flexibility and uncertainties about the nutrients available to infecting bacilli in different host (micro)environments instead requires educated predictions or demonstrations of efficacy in animal models of arguable relevance to human disease. Even microbiological methods for enumeration of viable mycobacterial cells are fraught with complication. Our research has focused on elucidating those aspects of mycobacterial metabolism that contribute to the robustness of the bacillus to host immunological defenses and applied antibiotics and that, possibly, drive the emergence of drug resistance. This work has identified a handful of metabolic pathways that appear vulnerable to antibiotic targeting. Those highlighted, here, include the inter-related functions of pantothenate and coenzyme A biosynthesis and recycling and nucleotide metabolism-the last of which reinforces our view that DNA metabolism constitutes an under-explored area for new TB drug development. Although nonessential functions have traditionally been deprioritized for antibiotic development, a common theme emerging from this work is that these very functions might represent attractive targets because of the potential to cripple mechanisms critical to bacillary survival under stress (for example, the Rel_Mtb-dependent stringent response) or to adaptability under unfavorable, potentially lethal, conditions including antibiotic therapy (for example, DnaE2-dependent SOS mutagenesis). The bar, however, is high: demonstrating convincingly the likely efficacy of this strategy will require innovative models of human TB disease. In the concluding section, we focus on the need for improved techniques to elucidate mycobacterial metabolism during infection and its impact on disease outcomes. Here, we argue that developments in other fields suggest the potential to break through this barrier by harnessing chemical-biology approaches in tandem with the most advanced technologies. As researchers based in a high-burden country, we are impelled to continue participating in this important endeavor.

Recent Trends in System-Scale Integrative Approaches for Discovering Protective Antigens Against Mycobacterial Pathogens

Mycobacterial infections are one of the deadliest infectious diseases still posing a major health burden worldwide. The battle against these pathogens needs to focus on novel approaches and key interventions. In recent times, availability of genome scale data has revolutionized the fields of computational biology and immunoproteomics. Here, we summarize the cutting-edge ‘omics’ technologies and innovative system scale strategies exploited to mine the available data. These may be targeted using high-throughput technologies to expedite the identification of novel antigenic candidates for the rational next generation vaccines and serodiagnostic development against mycobacterial pathogens for which traditional methods have been failing.

Mass spectrometry-based metabolomics for tuberculosis meningitis

Tuberculosis meningitis (TBM) is a prevalent form of extra-pulmonary tuberculosis that causes substantial morbidity and mortality. Diagnosis of TBM is difficult because of the limited sensitivity of existing laboratory techniques. A metabolomics approach can be used to investigate the sets of metabolites of both bacteria and host, and has been used to clarify the mechanisms underlying disease development, and identify metabolic changes, leadings to improved methods for diagnosis, treatment, and prognostication. Mass spectrometry (MS) is a major analysis platform used in metabolomics, and MS-based metabolomics provides wide metabolite coverage, because of its high sensitivity, and is useful for the investigation of Mycobacterium tuberculosis (Mtb) and related diseases. It has been used to investigate TBM diagnosis; however, the processes involved in the MS-based metabolomics approach are complex and flexible, and often consist of several steps, and small changes in the methods used can have a huge impact on the final results. Here, the process of MS-based metabolomics is summarized and its applications in Mtb and Mtb-related diseases discussed. Moreover, the current status of TBM metabolomics is described.

The crucial role of multiomic approach in cancer research and clinically relevant outcomes

Cancer with heavily economic and social burden is the hot point in the field of medical research. Some remarkable achievements have been made; however, the exact mechanisms of tumor initiation and development remain unclear. Cancer is a complex, whole-body disease that involves multiple abnormalities in the levels of DNA, RNA, protein, metabolite and medical imaging. Biological omics including genomics, transcriptomics, proteomics, metabolomics and radiomics aims to systematically understand carcinogenesis in different biological levels, which is driving the shift of cancer research paradigm from single parameter model to multi-parameter systematical model. The rapid development of various omics technologies is driving one to conveniently get multi-omics data, which accelerates predictive, preventive and personalized medicine (PPPM) practice allowing prediction of response with substantially increased accuracy, stratification of particular patients and eventual personalization of medicine. This review article describes the methodology, advances, and clinically relevant outcomes of different "omics" technologies in cancer research, and especially emphasizes the importance and scientific merit of integrating multi-omics in cancer research and clinically relevant outcomes.

Livestock metabolomics and the livestock metabolome: A systematic review

Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

UPLC-MS for metabolomics: a giant step forward in support of pharmaceutical research

Metabolomics is a relatively new and rapidly growing area of post-genomic biological research. As use of metabolomics technology grows throughout the spectrum of drug discovery and development, and its applications broaden, its impact is expanding dramatically. This review seeks to provide the reader with a brief history of the development of metabolomics, its significance and strategies for conducting metabolomics studies. The most widely used analytical tools for metabolomics: NMR, LC-MS and GC-MS, are discussed along with considerations for their use. Herein, we will show how metabolomics can assist in pharmaceutical research studies, such as pharmacology and toxicology, and discuss some examples of the importance of metabolomics analysis in research and development.

Individualizing management of extensively drug-resistant tuberculosis: diagnostics, treatment, and biomarkers

INTRODUCTION

Success rates for treatment of extensively drug resistant tuberculosis (XDR-TB) are low due to limited treatment options, delayed diagnosis and inadequate health care infrastructure. Areas covered: This review analyses existing programmes of prevention, diagnosis and treatment of XDR-TB. Improved diagnostic procedures and rapid molecular tests help to select appropriate drugs and dosages. Drugs dosages can be further tailored to the specific conditions of the patient based on quantitative susceptibility testing of the M. tuberculosis isolate and use of therapeutic drug monitoring. Pharmacovigilance is important for preserving activity of the novel drugs bedaquiline and delamanid. Furthermore, biomarkers of treatment response must be developed and validated to guide therapeutic decisions. Expert commentary: Given the currently poor treatment outcomes and the association of XDR-TB with HIV in endemic regions, a more patient oriented approach regarding diagnostics, drug selection and tailoring and treatment evaluation will improve treatment outcome. The different areas of expertise should be covered by a multidisciplinary team and may involve the transition of patients from hospitalized to home or community-based treatment.