Biomarkers of inflammation, immunosuppression and stress with active disease are revealed by metabolomic profiling of tuberculosis patients

A novel humanized mouse model for HIV and tuberculosis co-infection studies

Background

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), continues to be a major public health problem worldwide. The human immunodeficiency virus (HIV) is another equally important life-threatening pathogen. HIV infection decreases CD4+ T cell levels markedly increasing Mtb co-infections. An appropriate animal model for HIV/Mtb co-infection that can recapitulate the diversity of the immune response in humans during co-infection would facilitate basic and translational research in HIV/Mtb infections. Herein, we describe a novel humanized mouse model.

Methods

The irradiated NSG-SGM3 mice were transplanted with human CD34+ hematopoietic stem cells, and the humanization was monitored by staining various immune cell markers for flow cytometry. They were challenged with HIV and/or Mtb, and the CD4+ T cell depletion and HIV viral load were monitored over time. Before necropsy, the live mice were subjected to pulmonary function test and CT scan, and after sacrifice, the lung and spleen homogenates were used to determine Mtb load (CFU) and cytokine/chemokine levels by multiplex assay, and lung sections were analyzed for histopathology. The mouse sera were subjected to metabolomics analysis.

Results

Our humanized NSG-SGM3 mice were able to engraft human CD34+ stem cells, which then differentiated into a full-lineage of human immune cell subsets. After co-infection with HIV and Mtb, these mice showed decrease in CD4+ T cell counts overtime and elevated HIV load in the sera, similar to the infection pattern of humans. Additionally, Mtb caused infections in both lungs and spleen, and induced granulomatous lesions in the lungs. Distinct metabolomic profiles were also observed in the tissues from different mouse groups after co-infections.

Conclusion

The humanized NSG-SGM3 mice are able to recapitulate the pathogenic effects of HIV and Mtb infections and co-infection at the pathological, immunological and metabolism levels and are therefore a reproducible small animal model for studying HIV/Mtb co-infection.

L-arginine attenuates Streptococcus uberis-induced inflammation by decreasing miR155 level

L-arginine, as an essential substance of the immune system, plays a vital role in innate immunity. MiR155, a multi-functional microRNA, has gained importance as a regulator of homeostasis in immune cells. However, the immunoregulatory mechanism between L-arginine and miR155 in bacterial infections is unknown. Here, we investigated the potential role of miR155 in inflammation and the molecular regulatory mechanisms of L-arginine in Streptococcus uberis (S. uberis) infections. And we observed that miR155 was up-regulated after infection, accompanying the depletion of L-arginine, leading to metabolic disorders of amino acids and severe tissue damage. Mechanically, the upregulated miR155 mediated by the p65 protein played a pro-inflammatory role by suppressing the suppressor of cytokine signaling 6 (SOCS6)-mediated p65 ubiquitination and degradation. This culminated in a violently inflammatory response and tissue damage. Interestingly, a significant anti-inflammatory effect was revealed in L-arginine supplementation by reducing miR155 production via inhibiting p65. This work firstly uncovers the pro-inflammatory role of miR155 and an anti-inflammatory mechanism of L-arginine in S.uberis infection with a mouse mastitis model. Collectively, we provide new insights and strategies for the prevention and control of this important pathogen, which is of great significance for ensuring human food health and safety.

Urinary metabolic characterization of advanced tuberculous meningitis cases in a South African paediatric population

Tuberculous meningitis (TBM) is a severe form of tuberculosis with high neuro-morbidity and mortality, especially among the paediatric population (aged ≤12 years). Little is known of the associated metabolic changes. This study aimed to identify characteristic metabolic markers that differentiate severe cases of paediatric TBM from controls, through non-invasive urine collection. Urine samples selected for this study were from two paediatric groups. Group 1: controls (n = 44): children without meningitis, no neurological symptoms and from the same geographical region as group 2. Group 2: TBM cases (n = 13): collected from paediatric patients that were admitted to Tygerberg Hospital in South Africa on the suspicion of TBM, mostly severely ill; with a later confirmation of TBM. Untargeted 1H NMR-based metabolomics data of urine were generated, followed by statistical analyses via MetaboAnalyst (v5.0), and the identification of important metabolites. Twenty nine urinary metabolites were identified as characteristic of advanced TBM and categorized in terms of six dysregulated metabolic pathways: 1) upregulated tryptophan catabolism linked to an altered vitamin B metabolism; 2) perturbation of amino acid metabolism; 3) increased energy production-metabolic burst; 4) disrupted gut microbiota metabolism; 5) ketoacidosis; 6) increased nitrogen excretion. We also provide original biological insights into this biosignature of urinary metabolites that can be used to characterize paediatric TBM patients in a South African cohort.

Evaluation of Systemic Inflammation Before and After Standard Anti-tuberculosis Treatment in Patients With Active Pulmonary Tuberculosis and Diabetes Mellitus

Background Diabetes mellitus (DM) is a common comorbidity of active pulmonary tuberculosis (APTB) that increases the risk of treatment failure during anti-tuberculosis chemotherapy. Evaluating systemic inflammatory response could help determine differences in response to treatment between APTB patients and those with APTB and DM. Methodology To explore changes in systemic inflammation, measured by a set of inflammatory mediators in subjects with APTB and TBDM before and after six months of anti-tuberculosis chemotherapy, 30 APTB and nine TBDM subjects underwent cytokine testing, including interleukin (IL)-6, IL-8, IL-10, interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), and transforming growth factor-beta 1 (TGF-β1) by enzyme-linked immunosorbent assay, C-reactive protein by nephelometry, and sialic acid by colorimetric assay at baseline and following six months of standard anti-tuberculosis treatment. Sputum smear microscopy or molecular biology (Xpert MTB/RIF) was used for diagnosis, and sputum smear microscopy was performed monthly during the treatment of the patient with pulmonary tuberculosis to evaluate his evolution. Principal component analysis examined changes in the inflammatory status. Results Both groups showed negative sputum smear microscopy in the sixth month after starting anti-tuberculosis chemotherapy. TGF-β1 was found to be significantly higher in subjects with TBDM before treatment compared to APTB patients (p<0.001), and systemic inflammation continued only in TBDM subjects after treatment (accumulation and persistence of inflammatory mediators like IL-6, IL-8, IL-10, IFN-γ, TNF-α, TGF-β1, C-reactive protein, and sialic acid in blood). On the other hand, the mediators IFN-γ, C-reactive protein, and total sialic acid were found to be most influential in distinguishing pre- and post-treatment inflammatory response in subjects with APTB without DM. Conclusions Inflammatory mediators analyzed in combination, including IFN-γ, CRP, and total sialic acid, may be useful in evaluating the systemic inflammatory response in subjects with APTB and TBDM before and after anti-tuberculosis treatment. Determining these mediators revealed persistent systemic inflammation in TBDM subjects after six months of standard tuberculosis treatment, despite negative sputum smear microscopy results and good glycemic control. This suggests a need for inflammation-modulating therapies during tuberculosis control. Finally, monitoring sputum smear microscopy results alongside the determination of proposed inflammatory mediators (IFN-γ, CRP, and total sialic acid) are effective in evaluating the response to anti-tuberculosis treatment in APTB subjects without DM, warranting further investigation.

Metabolic alterations in urine among the patients with severe fever with thrombocytopenia syndrome

BACKGROUND

The pathogenesis of severe fever with thrombocytopenia syndrome (SFTS) remained unclear. We aimed to profile the metabolic alterations in urine of SFTS patients and provide new evidence for its pathogenesis.

METHODS

A case-control study was conducted in the 154th hospital in China. Totally 88 cases and 22 controls aged ≥ 18 years were enrolled. The cases were selected from laboratory-confirmed SFTS patients. The controls were selected among SFTSV-negative population. Those with diabetes, cancer, hepatitis and other sexually transmitted diseases were excluded in both groups. Fatal cases and survival cases were 1:1 matched. Inter-group differential metabolites and pathways were obtained, and the inter-group discrimination ability was evaluated.

RESULTS

Tryptophan metabolism and phenylalanine metabolism were the top one important metabolism pathway in differentiating the control and case groups, and the survival and fatal groups, respectively. The significant increase of differential metabolites in tryptophan metabolism, including 5-hydroxyindoleacetate (5-HIAA), L-kynurenine (KYN), 5-hydroxy-L-tryptophan (5-HTP), 3-hydroxyanthranilic acid (3-HAA), and the increase of phenylpyruvic acid and decrease of hippuric acid in phenylalanine metabolism indicated the potential metabolic alterations in SFTSV infection. The increase of 5-HIAA, KYN, 5-HTP, phenylpyruvic acid and hippuric acid were involved in the fatal progress of SFTS patients.

CONCLUSIONS

Tryptophan metabolism and phenylalanine metabolism might be involved in the pathogenesis of SFTSV infection. These findings provided new evidence for the pathogenesis and treatment of SFTS.

Identifying the Interaction Between Tuberculosis and SARS-CoV-2 Infections via Bioinformatics Analysis and Machine Learning

The number of patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 is still increasing. In the case of COVID-19 and tuberculosis (TB), the presence of one disease affects the infectious status of the other. Meanwhile, coinfection may result in complications that make treatment more difficult. However, the molecular mechanisms underpinning the interaction between TB and COVID-19 are unclear. Accordingly, transcriptome analysis was used to detect the shared pathways and molecular biomarkers in TB and COVID-19, allowing us to determine the complex relationship between COVID-19 and TB. Two RNA-seq datasets (GSE114192 and GSE163151) from the Gene Expression Omnibus were used to find concerted differentially expressed genes (DEGs) between TB and COVID-19 to identify the common pathogenic mechanisms. A total of 124 common DEGs were detected and used to find shared pathways and drug targets. Several enterprising bioinformatics tools were applied to perform pathway analysis, enrichment analysis and networks analysis. Protein-protein interaction analysis and machine learning was used to identify hub genes (GAS6, OAS3 and PDCD1LG2) and datasets GSE171110, GSE54992 and GSE79362 were used for verification. The mechanism of protein-drug interactions may have reference value in the treatment of coinfection of COVID-19 and TB.

Clinical metabolomics by NMR revealed serum metabolic signatures for differentiating sarcoidosis from tuberculosis

BACKGROUND

Pulmonary sarcoidosis (SAR) and tuberculosis (TB) are two granulomatous lung-diseases and often pose a diagnostic challenge to a treating physicians.

OBJECTIVE

The present study aims to explore the diagnostic potential of NMR based serum metabolomics approach to differentiate SAR from TB.

MATERIALS AND METHOD

The blood samples were obtained from three study groups: SAR (N = 35), TB (N = 28) and healthy normal subjects (NC, N = 56) and their serum metabolic profiles were measured using 1D 1H CPMG (Carr-Purcell-Meiboom-Gill) NMR spectra recorded at 800 MHz NMR spectrometer. The quantitative metabolic profiles were compared employing a combination of univariate and multivariate statistical analysis methods and evaluated for their diagnostic potential using receiver operating characteristic (ROC) curve analysis.

RESULTS

Compared to SAR, the sera of TB patients were characterized by (a) elevated levels of lactate, acetate, 3-hydroxybutyrate (3HB), glutamate and succinate (b) decreased levels of glucose, citrate, pyruvate, glutamine, and several lipid and membrane metabolites (such as very-low/low density lipoproteins (VLDL/LDL), polyunsaturated fatty acids, etc.).

CONCLUSION

The metabolic disturbances not only found to be well in concordance with various previous reports, these further demonstrated very high sensitivity and specificity to distinguish SAR from TB patients suggesting serum metabolomics analysis can serve as surrogate method in the diagnosis and clinical management of SAR.

Plasma metabolome of healthy and Rhodococcus equi-infected foals over time

BACKGROUND

Foals that develop pulmonary ultrasonographic lesions on Rhodococcus equi (R. equi) endemic farms are treated with antibiotics because those at risk of developing clinical pneumonia (~20%) cannot be recognised early. Candidate biomarkers identified using metabolomics may aid targeted treatment strategies against R. equi.

OBJECTIVES

(1) To describe how foal ageing affects their plasma metabolome (birth to 8 weeks) and (2) to establish the effects that experimental infection with Rhodococcus equi (R. equi) has on foal metabolome.

STUDY DESIGN

Experimental study.

METHODS

Nine healthy newborn foals were experimentally infected with R. equi as described in a previous study. Foals were treated with oral antibiotics if they developed clinical pneumonia (n = 4, clinical group) or remained untreated if they showed no signs of disease (n = 5, subclinical group). A group of unchallenged foals (n = 4) was also included in the study. By the end of the study period (8 weeks), all foals were free of disease. This status was confirmed with transtracheal wash fluid evaluation and culture as well as thoracic ultrasonography. Plasma metabolomics was determined by GC-MS weekly for the study duration (8 weeks).

RESULTS

Foals' plasma metabolome was altered by ageing (birth to 8 weeks) and experimental infection with R. equi as demonstrated using multivariate statistical analysis. The intensities of 25 and 28 metabolites were altered by ageing and infection (p < 0.05) respectively. Furthermore, 20 metabolites changed by more than 2-fold between clinical and subclinical groups.

MAIN LIMITATIONS

The number of foals is limited. Foals were experimentally infected with R. equi.

CONCLUSIONS

Ageing and R. equi infection induced changes in the plasma metabolome of foals. These results provide an initial description of foal's plasma metabolome and serve as background for future identification of R. equi pneumonia biomarkers.

The metabolic consequences of HIV/TB co-infection

BACKGROUND

The synergy between the human immunodeficiency virus (HIV) and Mycobacterium tuberculosis during co-infection of a host is well known. While this synergy is known to be driven by immunological deterioration, the metabolic mechanisms that contribute to the associated disease burden experienced during HIV/tuberculosis (TB) co-infection remain poorly understood. Furthermore, while anti-HIV treatments suppress viral replication, these therapeutics give rise to host metabolic disruption and adaptations beyond that induced by only infection or disease.

METHODS

In this study, the serum metabolic profiles of healthy controls, untreated HIV-negative TB-positive patients, untreated HIV/TB co-infected patients, and HIV/TB co-infected patients on antiretroviral therapy (ART), were measured using two-dimensional gas chromatography time-of-flight mass spectrometry. Since no global metabolic profile for HIV/TB co-infection and the effect of ART has been published to date, this pilot study aimed to elucidate the general areas of metabolism affected during such conditions.

RESULTS

HIV/TB co-infection induced significant changes to the host's lipid and protein metabolism, with additional microbial product translocation from the gut to the blood. The results suggest that HIV augments TB synergistically, at least in part, contributing to increased inflammation, oxidative stress, ART-induced mitochondrial damage, and its detrimental effects on gut health, which in turn, affects energy availability. ART reverses these trends to some extent in HIV/TB co-infected patients but not to that of healthy controls.

CONCLUSION

This study generated several new hypotheses that could direct future metabolic studies, which could be combined with other research techniques or methodologies to further elucidate the underlying mechanisms of these changes.

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.

The cause-effect relation of tuberculosis on incidence of diabetes mellitus

Tuberculosis (TB) is one of the oldest human diseases and is one of the major causes of mortality and morbidity across the Globe. Mycobacterium tuberculosis (Mtb), the causal agent of TB is one of the most successful pathogens known to mankind. Malnutrition, smoking, co-infection with other pathogens like human immunodeficiency virus (HIV), or conditions like diabetes further aggravate the tuberculosis pathogenesis. The association between type 2 diabetes mellitus (DM) and tuberculosis is well known and the immune-metabolic changes during diabetes are known to cause increased susceptibility to tuberculosis. Many epidemiological studies suggest the occurrence of hyperglycemia during active TB leading to impaired glucose tolerance and insulin resistance. However, the mechanisms underlying these effects is not well understood. In this review, we have described possible causal factors like inflammation, host metabolic changes triggered by tuberculosis that could contribute to the development of insulin resistance and type 2 diabetes. We have also discussed therapeutic management of type 2 diabetes during TB, which may help in designing future strategies to cope with TB-DM cases.

Exploration of Lipid Metabolism Alterations in Children with Active Tuberculosis Using UHPLC-MS/MS

Metabolic profiling using nonsputum samples has demonstrated excellent performance in diagnosing infectious diseases. But little is known about the lipid metabolism alternation in children with tuberculosis (TB). Therefore, the study was performed to explore lipid metabolic changes caused by Mycobacterium tuberculosis infection and identify specific lipids as diagnostic biomarkers in children with TB using UHPLC-MS/MS. Plasma samples obtained from 70 active TB children, 21 non-TB infectious disease children, and 21 healthy controls were analyzed by a partial least-squares discriminant analysis model in the training set, and 12 metabolites were identified that can separate children with TB from non-TB controls. In the independent testing cohort with 49 subjects, three of the markers, PC (15:0/17:1), PC (17:1/18:2), and PE (18:1/20:3), presented with high diagnostic values. The areas under the curve of the three metabolites were 0.904, 0.833, and 0.895, respectively. The levels of the altered lipid metabolites were found to be associated with the severity of the TB disease. Taken together, plasma lipid metabolites are potentially useful for diagnosis of active TB in children and would provide insights into the pathogenesis of the disease.

Diagnosis and biomarkers for ocular tuberculosis: From the present into the future

Tuberculosis is an airborne disease caused by Mycobacterium tuberculosis (Mtb) and can manifest both pulmonary and extrapulmonary disease, including ocular tuberculosis (OTB). Accurate diagnosis and swift optimal treatment initiation for OTB is faced by many challenges combined with the lack of standardized treatment regimens this results in uncertain OTB outcomes. The purpose of this study is to summarize existing diagnostic approaches and recently discovered biomarkers that may contribute to establishing OTB diagnosis, choice of anti-tubercular therapy (ATT) regimen, and treatment monitoring. The keywords ocular tuberculosis, tuberculosis, Mycobacterium, biomarkers, molecular diagnosis, multi-omics, proteomics, genomics, transcriptomics, metabolomics, T-lymphocytes profiling were searched on PubMed and MEDLINE databases. Articles and books published with at least one of the keywords were included and screened for relevance. There was no time limit for study inclusion. More emphasis was placed on recent publications that contributed new information about the pathogenesis, diagnosis, or treatment of OTB. We excluded abstracts and articles that were not written in the English language. References cited within the identified articles were used to further supplement the search. We found 10 studies evaluating the sensitivity and specificity of interferon-gamma release assay (IGRA), and 6 studies evaluating that of tuberculin skin test (TST) in OTB patients. IGRA (Sp = 71-100%, Se = 36-100%) achieves overall better sensitivity and specificity than TST (Sp = 51.1-85.7%; Se = 70.9-98.5%). For nuclear acid amplification tests (NAAT), we found 7 studies on uniplex polymerase chain reaction (PCR) with different Mtb targets, 7 studies on DNA-based multiplex PCR, 1 study on mRNA-based multiplex PCR, 4 studies on loop-mediated isothermal amplification (LAMP) assay with different Mtb targets, 3 studies on GeneXpert assay, 1 study on GeneXpert Ultra assay and 1 study for MTBDRplus assay for OTB. Specificity is overall improved but sensitivity is highly variable for NAATs (excluding uniplex PCR, Sp = 50-100%; Se = 10.5-98%) as compared to IGRA. We also found 3 transcriptomic studies, 6 proteomic studies, 2 studies on stimulation assays, 1 study on intraocular protein analysis and 1 study on T-lymphocyte profiling in OTB patients. All except 1 study evaluated novel, previously undiscovered biomarkers. Only 1 study has been externally validated by a large independent cohort. Future theranostic marker discovery by a multi-omics approach is essential to deepen pathophysiological understanding of OTB. Combined these might result in swift, optimal and personalized treatment regimens to modulate the heterogeneous mechanisms of OTB. Eventually, these studies could improve the current cumbersome diagnosis and management of OTB.

Sex and Gender Differences in Tuberculosis Pathogenesis and Treatment Outcomes

Tuberculosis remains a daunting public health concern in many countries of the world. A consistent observation in the global epidemiology of tuberculosis is an excess of cases of active pulmonary tuberculosis among males compared with females. Data from both humans and animals also suggest that males are more susceptible than females to develop active pulmonary disease. Similarly, male sex has been associated with poor treatment outcomes. Despite this growing body of evidence, little is known about the mechanisms driving sex bias in tuberculosis disease. Two dominant hypotheses have been proposed to explain the predominance of active pulmonary tuberculosis among males. The first is based on the contribution of biological factors, such as sex hormones and genetic factors, on host immunity during tuberculosis. The second is focused on non-biological factors such as smoking, professional exposure, and health-seeking behaviors, known to be influenced by gender. In this chapter, we review the literature regarding these two prevailing hypotheses by presenting human but also experimental animal studies. In addition, we presented studies aiming at examining the impact of sex and gender on other clinical forms of tuberculosis such as latent tuberculosis infection and extrapulmonary tuberculosis, which both appear to have their own specificities in relation to sex. We also highlighted potential intersections between sex and gender in the context of tuberculosis and shared future directions that could guide in elucidating mechanisms of sex-based differences in tuberculosis pathogenesis and treatment outcomes.

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.

Mass spectrometry-based identification of new serum biomarkers in patients with latent infection pulmonary tuberculosis

Noninvasive and simple indicators for diagnosing latent tuberculosis (TB) infection (LTBI) and tracking progression from latent infection to active TB infection are still desperately needed. The aim of this study was to screen and identify possible biomarkers for diagnosing LTBI and monitoring the progression from latent infection to active TB infection, as well as to investigate the underlying processes and functions. To assess changes in metabolite composition associated with active tuberculosis infection in humans, whole blood supernatants were collected from patients with LTBI, drug-susceptible TB patients, drug-resistant TB patients, and healthy controls. The metabolites in all serum samples were extracted by oscillatory, deproteinization, and then detected by liquid chromatography-tandem mass spectrometry/MS analysis. Normalization by Pareto-scaling method, the difference analysis was carried out by Metaboanalyst 4.0 software, and 1-way analysis of variance analysis among groups showed that P-value < 0.05 was regarded as a different metabolite. To clarify the dynamic changes and functions of differential metabolites with disease progression, and explore its significance and mechanism as a marker by further cluster analysis, functional enrichment analysis, and relative content change analysis of differential metabolites. 65 metabolites were substantially different in four groups. Differential metabolites such as Inosine and Prostaglandin E1 may be important blood indicators for diagnosing mycobacterium tuberculosis latent infection, which were all tightly connected to amino acid metabolism, Biosynthesis of various secondary metabolites, Nucleotide metabolism, Endocrine system, Immune system, Lipid metabolism, and Nervous system. This study screened and identified Inosine, 16, 16-dimethyl-6-keto Prostaglandin E1, Theophylline, and Cotinine as potential serum biomarkers for diagnosing latent TB infection, and Cotinine as potential biomarkers for monitoring disease progression from healthy population to LTBI and then to active TB including drug-resistant TB infection and sensitive TB infection. Furthermore, this research provides a preliminary experimental basis to further investigate the development of metabolomics-based diagnosis of LTBI and monitoring the progress from latent infection to active TB infection.

In-depth systems biological evaluation of bovine alveolar macrophages suggests novel insights into molecular mechanisms underlying Mycobacterium bovis infection

OBJECTIVE

Bovine tuberculosis (bTB) is a chronic respiratory infectious disease of domestic livestock caused by intracellular Mycobacterium bovis infection, which causes ~$3 billion in annual losses to global agriculture. Providing novel tools for bTB managements requires a comprehensive understanding of the molecular regulatory mechanisms underlying the M. bovis infection. Nevertheless, a combination of different bioinformatics and systems biology methods was used in this study in order to clearly understand the molecular regulatory mechanisms of bTB, especially the immunomodulatory mechanisms of M. bovis infection.

METHODS

RNA-seq data were retrieved and processed from 78 (39 non-infected control vs. 39 M. bovis-infected samples) bovine alveolar macrophages (bAMs). Next, weighted gene co-expression network analysis (WGCNA) was performed to identify the co-expression modules in non-infected control bAMs as reference set. The WGCNA module preservation approach was then used to identify non-preserved modules between non-infected controls and M. bovis-infected samples (test set). Additionally, functional enrichment analysis was used to investigate the biological behavior of the non-preserved modules and to identify bTB-specific non-preserved modules. Co-expressed hub genes were identified based on module membership (MM) criteria of WGCNA in the non-preserved modules and then integrated with protein-protein interaction (PPI) networks to identify co-expressed hub genes/transcription factors (TFs) with the highest maximal clique centrality (MCC) score (hub-central genes).

RESULTS

As result, WGCNA analysis led to the identification of 21 modules in the non-infected control bAMs (reference set), among which the topological properties of 14 modules were altered in the M. bovis-infected bAMs (test set). Interestingly, 7 of the 14 non-preserved modules were directly related to the molecular mechanisms underlying the host immune response, immunosuppressive mechanisms of M. bovis, and bTB development. Moreover, among the co-expressed hub genes and TFs of the bTB-specific non-preserved modules, 260 genes/TFs had double centrality in both co-expression and PPI networks and played a crucial role in bAMs-M. bovis interactions. Some of these hub-central genes/TFs, including PSMC4, SRC, BCL2L1, VPS11, MDM2, IRF1, CDKN1A, NLRP3, TLR2, MMP9, ZAP70, LCK, TNF, CCL4, MMP1, CTLA4, ITK, IL6, IL1A, IL1B, CCL20, CD3E, NFKB1, EDN1, STAT1, TIMP1, PTGS2, TNFAIP3, BIRC3, MAPK8, VEGFA, VPS18, ICAM1, TBK1, CTSS, IL10, ACAA1, VPS33B, and HIF1A, had potential targets for inducing immunomodulatory mechanisms by M. bovis to evade the host defense response.

CONCLUSION

The present study provides an in-depth insight into the molecular regulatory mechanisms behind M. bovis infection through biological investigation of the candidate non-preserved modules directly related to bTB development. Furthermore, several hub-central genes/TFs were identified that were significant in determining the fate of M. bovis infection and could be promising targets for developing novel anti-bTB therapies and diagnosis strategies.

Metabolites enhance innate resistance to human Mycobacterium tuberculosis infection

To determine the mechanisms that mediate resistance to Mycobacterium tuberculosis (M. tuberculosis) infection in household contacts (HHCs) of patients with tuberculosis (TB), we followed 452 latent TB infection-negative (LTBI-) HHCs for 2 years. Those who remained LTBI- throughout the study were identified as nonconverters. At baseline, nonconverters had a higher percentage of CD14+ and CD3-CD56+CD27+CCR7+ memory-like natural killer (NK) cells. Using a whole-transcriptome and metabolomic approach, we identified deoxycorticosterone acetate as a metabolite with elevated concentrations in the plasma of nonconverters, and further studies showed that this metabolite enhanced glycolytic ATP flux in macrophages and restricted M. tuberculosis growth by enhancing antimicrobial peptide production through the expression of the surface receptor sialic acid binding Ig-like lectin-14. Another metabolite, 4-hydroxypyridine, from the plasma of nonconverters significantly enhanced the expansion of memory-like NK cells. Our findings demonstrate that increased levels of specific metabolites can regulate innate resistance against M. tuberculosis infection in HHCs of patients with TB who never develop LTBI or active TB.

Metabolic biological markers for diagnosing and monitoring the course of tuberculosis

The international biomedical community has been currently facing a need to find a simple and most accessible type of analysis that helps to diagnose tuberculosis (TB) with the maximum reliability even before the onset of clinical manifestations. Tuberculosis results in more deaths than any other pathogen, second only to pneumonia caused by the SARS-CoV-2 virus, but the majority of infected people remain asymptomatic. In addition, it is important to develop methods to distinguish various forms of tuberculosis infection course at early stages and to reliably stratify patients into appropriate groups (persons with a rapidly progressing infection, chronic course, latent infection carriers). Immunometabolism investigates a relationship between bioenergetic pathways and specific functions of immune cells that has recently become increasingly important in scientific research. The host anti-mycobacteria immune response in tuberculosis is regulated by a number of metabolic networks that can interact both cooperatively and antagonistically, influencing an outcome of the disease. The balance between inflammatory and immune reactions limits the spread of mycobacteria in vivo and protects from developing tuberculosis. Cytokines are essential for host defense, but if uncontrolled, some mediators may contribute to developing disease and pathology. Differences in plasma levels of metabolites between individuals with advanced infection, LTBI and healthy individuals can be detected long before the onset of the major related clinical signs. Changes in amino acid and cortisol level may be detected as early as 12 months before the onset of the disease and become more prominent at verifying clinical diagnosis. Assessing serum level of certain amino acids and their ratios may be used as additional diagnostic markers of active pulmonary TB. Metabolites, including serum fatty acids, amino acids and lipids may contribute to detecting active TB. Metabolic profiles indicate about increased indolamine 2.3-dioxygenase 1 (IDO1) activity, decreased phospholipase activity, increased adenosine metabolite level, and fibrous lesions in active vs. latent infection. TB treatment can be adjusted based on individual patient metabolism and biomarker profiles. Thus, exploring immunometabolism in tuberculosis is necessary for development of new therapeutic strategies.

Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature

Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into three experimental groups—healthy controls (controls), latent TB infection (LTBI), and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate, and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between controls and TB patients. The AUC, specificity, and sensitivity, determined by ROC statistical analysis of the model composed of four of these proteins considering both proteomic sets, were 0.96, 93%, and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine, and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes were submitted to ROC analysis. An AUC = 1 was determined, with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling one protein and four metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature correctly assigned the 12 controls and 12 patients used only for prediction (AUC = 1, specificity = 100%, and sensitivity = 100%). This multiomics approach revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.

The Role of Amino Acids in Tuberculosis Infection: A Literature Review

Recently, there was an abundance of studies being conducted on the metabolomic profiling of tuberculosis patients. Amino acids are critical metabolites for the immune system, as they might contribute to providing nutrients for the host intracellular pathway. In tuberculosis, several amino acids play important roles in both the mycobacteria infection mechanism and the host. Individual studies showed how the dynamics of metabolite products that result from interactions between Mycobacterium tuberculosis (Mtb) and the host play important roles in different stages of infection. In this review, we focus on the dynamics of amino-acid metabolism and identify the prominent roles of amino acids in the diagnostics and treatment of tuberculosis infection. Online resources, including PubMed, ScienceDirect, Scopus, and Clinical Key, were used to search for articles with combination keywords of amino acids and TB. The inclusion criteria were full-text articles in English published in the last 10 years. Most amino acids were decreased in patients with active TB compared with those with latent TB and healthy controls. However, some amino acids, including leucine, isoleucine, valine, phenylalanine, aspartate, and glutamate, were found to be at higher levels in TB patients. Additionally, the biomarkers of Mtb infection included the ratios of kynurenine to tryptophan, phenylalanine to histidine, and citrulline to arginine. Most amino acids were present at different levels in different stages of infection and disease progression. The search for additional roles played by those metabolomic biomarkers in each stage of infection might facilitate diagnostic tools for staging TB infection.

Development and Validation of a Parsimonious Tuberculosis Gene Signature Using the digital NanoString nCounter Platform

BACKGROUND

Blood-based biomarkers for diagnosing active tuberculosis (TB), monitoring treatment response, and predicting risk of progression to TB disease have been reported. However, validation of the biomarkers across multiple independent cohorts is scarce. A robust platform to validate TB biomarkers in different populations with clinical end points is essential to the development of a point-of-care clinical test. NanoString nCounter technology is an amplification-free digital detection platform that directly measures mRNA transcripts with high specificity. Here, we determined whether NanoString could serve as a platform for extensive validation of candidate TB biomarkers.

METHODS

The NanoString platform was used for performance evaluation of existing TB gene signatures in a cohort in which signatures were previously evaluated on an RNA-seq dataset. A NanoString codeset that probes 107 genes comprising 12 TB signatures and 6 housekeeping genes (NS-TB107) was developed and applied to total RNA derived from whole blood samples of TB patients and individuals with latent TB infection (LTBI) from South India. The TBSignatureProfiler tool was used to score samples for each signature. An ensemble of machine learning algorithms was used to derive a parsimonious biomarker.

RESULTS

Gene signatures present in NS-TB107 had statistically significant discriminative power for segregating TB from LTBI. Further analysis of the data yielded a NanoString 6-gene set (NANO6) that when tested on 10 published datasets was highly diagnostic for active TB.

CONCLUSIONS

The NanoString nCounter system provides a robust platform for validating existing TB biomarkers and deriving a parsimonious gene signature with enhanced diagnostic performance.

Untargeted metabolomic analysis of thoracic blood from badgers indicate changes linked to infection with bovine tuberculosis (Mycobacterium bovis): a pilot study

INTRODUCTION

Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB) in cattle, represents a major disease burden to UK cattle farming, with considerable costs associated with its control. The European badger (Meles meles) is a known wildlife reservoir for bTB and better knowledge of the epidemiology of bTB through testing wildlife is required for disease control. Current tests available for the diagnosis of bTB in badgers are limited by cost, processing time or sensitivities.

MATERIALS AND METHODS

We assessed the ability of flow infusion electrospray-high-resolution mass spectrometry (FIE-HRMS) to determine potential differences between infected and non-infected badgers based on thoracic blood samples obtained from badgers found dead in Wales. Thoracic blood samples were autoclaved for handling in a containment level 2 (CL2) hazard laboratory.

RESULTS

Here we show the major differences associated with with M. bovis infection were changes to folate, pyrimidine, histidine, glycerophospholipid and phosphonate metabolism.

CONCLUSIONS

Our studies have indicated differences in the metabolomic signature of badgers found dead in relation to their infection status, suggesting metabolomics could hold potential for developing novel diagnostics for bTB in badgers. As well as highlighting a potential way to handle samples containing a highly pathogenic agent at CL2 for metabolomics studies.

Identifying potential biomarkers and therapeutic targets for dogs with sepsis using metabolomics and lipidomics analyses

Sepsis is a diagnostic and therapeutic challenge and is associated with morbidity and a high risk of death. Metabolomic and lipidomic profiling in sepsis can identify alterations in metabolism and might provide useful insights into the dysregulated host response to infection, but investigations in dogs are limited. We aimed to use untargeted metabolomics and lipidomics to characterize metabolic pathways in dogs with sepsis to identify therapeutic targets and potential diagnostic and prognostic biomarkers. In this prospective observational cohort study, we examined the plasma metabolomes and lipidomes of 20 healthy control dogs and compared them with those of 21 client-owned dogs with sepsis. Patient data including signalment, physical exam findings, clinicopathologic data and clinical outcome were recorded. Metabolites were identified using an untargeted mass spectrometry approach and pathway analysis identified multiple enriched metabolic pathways including pyruvaldehyde degradation; ketone body metabolism; the glucose-alanine cycle; vitamin-K metabolism; arginine and betaine metabolism; the biosynthesis of various amino acid classes including the aromatic amino acids; branched chain amino acids; and metabolism of glutamine/glutamate and the glycerophospholipid phosphatidylethanolamine. Metabolites were identified with high discriminant abilities between groups which could serve as potential biomarkers of sepsis including 13,14-Dihydro-15-keto Prostaglandin A₂; 12(13)-DiHOME (12,13-dihydroxy-9Z-octadecenoic acid); and 9-HpODE (9-Hydroxyoctadecadienoic acid). Metabolites with higher abundance in samples from nonsurvivors than survivors included 3-(2-hydroxyethyl) indole, indoxyl sulfate and xanthurenic acid. Untargeted lipidomic profiling revealed multiple sphingomyelin species (SM(d34:0)+H; SM(d36:0)+H; SM(d34:0)+HCOO; and SM(d34:1D3)+HCOO); lysophosphatidylcholine molecules (LPC(18:2)+H) and lipophosphoserine molecules (LPS(20:4)+H) that were discriminating for dogs with sepsis. These biomarkers could aid in the diagnosis of dogs with sepsis, provide prognostic information, or act as potential therapeutic targets.

Non-volatile organic compounds in exhaled breath particles correspond to active tuberculosis

Human breath contains trace amounts of non-volatile organic compounds (NOCs) which might provide non-invasive methods for evaluating individual health. In previous work, we demonstrated that lipids detected in exhaled breath aerosol (EBA) could be used as markers of active tuberculosis (TB). Here, we advanced our analytical platform for characterizing small metabolites and lipids in EBA samples collected from participants enrolled in clinical trials designed to identify molecular signatures of active TB. EBA samples from 26 participants with active TB and 73 healthy participants were processed using a dual-phase extraction method, and metabolites and lipids were identified via mass spectrometry database matching. In total, 13 metabolite and 9 lipid markers were identified with statistically different optimized relative standard deviation values between individuals diagnosed with active TB and the healthy controls. Importantly, EBA lipid profiles can be used to separate the two sample types, indicating the diagnostic potential of the identified molecules. A feature ranking algorithm reduced this number to 10 molecules, with the membrane glycerophospholipid, phosphatidylinositol 24:4, emerging as the top driver of segregation between the two groups. These results support the use of this approach to identify consistent NOC signatures from EBA samples in active TB cases. This suggests the potential to apply this method to other human diseases which alter respiratory NOC release.

Targeted metabolomics analysis of serum and Mycobacterium tuberculosis antigen-stimulated blood cultures of pediatric patients with active and latent tuberculosis

Profound tuberculosis (TB)-induced metabolic changes reflected in the blood metabolomic profile may provide an opportunity to identify specific markers of Mycobacterium tuberculosis infection. Using targeted liquid chromatography tandem mass spectrometry, we compared the levels of 30 small metabolites, including amino acids and derivatives, and small organic compounds in serum and M.tb antigen-stimulated whole blood cultures of active TB children, latent TB (LTBI) children, nonmycobacterial pneumonia (NMP) children, and healthy controls (HCs) to assess their potential as biomarkers of childhood TB. We found elevated levels of leucine and kynurenine combined with reduced concentrations of citrulline and glutamine in serum and blood cultures of TB and LTBI groups. LTBI status was additionally associated with a decrease in valine levels in blood cultures. The NMP metabolite profile was characterized by an increase in citrulline and glutamine and a decrease in leucine, kynurenine and valine concentrations. The highest discriminatory potential for identifying M.tb infection was observed for leucine detected in serum and kynurenine in stimulated blood cultures. The use of targeted metabolomics may reveal metabolic changes in M.tb-infected children, and the obtained results are a proof of principle of the usefulness of metabolites in the auxiliary diagnosis of TB in children.

Molecular perturbations in pulmonary tuberculosis patients identified by pathway-level analysis of plasma metabolic features

Insight into the metabolic biosignature of tuberculosis (TB) may inform clinical care, reduce adverse effects, and facilitate metabolism-informed therapeutic development. However, studies often yield inconsistent findings regarding the metabolic profiles of TB. Herein, we conducted an untargeted metabolomics study using plasma from 63 Korean TB patients and 50 controls. Metabolic features were integrated with the data of another cohort from China (35 TB patients and 35 controls) for a global functional meta-analysis. Specifically, all features were matched to a known biological network to identify potential endogenous metabolites. Next, a pathway-level gene set enrichment analysis-based analysis was conducted for each study and the resulting p-values from the pathways of two studies were combined. The meta-analysis revealed both known metabolic alterations and novel processes. For instance, retinol metabolism and cholecalciferol metabolism, which are associated with TB risk and outcome, were altered in plasma from TB patients; proinflammatory lipid mediators were significantly enriched. Furthermore, metabolic processes linked to the innate immune responses and possible interactions between the host and the bacillus showed altered signals. In conclusion, our proof-of-concept study indicated that a pathway-level meta-analysis directly from metabolic features enables accurate interpretation of TB molecular profiles.

A virtual host model of Mycobacterium tuberculosis infection identifies early immune events as predictive of infection outcomes

Tuberculosis (TB), caused by infection with Mycobacterium tuberculosis (Mtb), is one of the world's deadliest infectious diseases and remains a significant global health burden. TB disease and pathology can present clinically across a spectrum of outcomes, ranging from total sterilization of infection to active disease. Much remains unknown about the biology that drives an individual towards various clinical outcomes as it is challenging to experimentally address specific mechanisms driving clinical outcomes. Furthermore, it is unknown whether numbers of immune cells in the blood accurately reflect ongoing events during infection within human lungs. Herein, we utilize a systems biology approach by developing a whole-host model of the immune response to Mtb across multiple physiologic and time scales. This model, called HostSim, tracks events at the cellular, granuloma, organ, and host scale and represents the first whole-host, multi-scale model of the immune response following Mtb infection. We show that this model can capture various aspects of human and non-human primate TB disease and predict that biomarkers in the blood may only faithfully represent events in the lung at early time points after infection. We posit that HostSim, as a first step toward personalized digital twins in TB research, offers a powerful computational tool that can be used in concert with experimental approaches to understand and predict events about various aspects of TB disease and therapeutics.

Host lipidome and tuberculosis treatment failure

INTRODUCTION

Host lipids play important roles in tuberculosis (TB) pathogenesis. Whether host lipids at TB treatment initiation (baseline) affect subsequent treatment outcomes has not been well characterised. We used unbiased lipidomics to study the prospective association of host lipids with TB treatment failure.

METHODS

A case-control study (n=192), nested within a prospective cohort study, was used to investigate the association of baseline plasma lipids with TB treatment failure among adults with pulmonary TB. Cases (n=46) were defined as TB treatment failure, while controls (n=146) were those without failure. Complex lipids and inflammatory lipid mediators were measured using liquid chromatography mass spectrometry techniques. Adjusted least-square regression was used to assess differences in groups. In addition, machine learning identified lipids with highest area under the curve (AUC) to classify cases and controls.

RESULTS

Baseline levels of 32 lipids differed between controls and those with treatment failure after false discovery rate adjustment. Treatment failure was associated with lower baseline levels of cholesteryl esters and oxylipin, and higher baseline levels of ceramides and triglycerides compared to controls. Two cholesteryl ester lipids combined in a unique classifier model provided an AUC of 0.79 (95% CI 0.65-0.93) in the test dataset for prediction of TB treatment failure.

CONCLUSIONS

We identified lipids, some with known roles in TB pathogenesis, associated with TB treatment failure. In addition, a lipid signature with prognostic accuracy for TB treatment failure was identified. These lipids could be potential targets for risk-stratification, adjunct therapy and treatment monitoring.

Arginine-mediated gut microbiome remodeling promotes host pulmonary immune defense against nontuberculous mycobacterial infection

Nontuberculous mycobacterial pulmonary diseases (NTM-PDs) are emerging as global health threats with issues of antibiotic resistance. Accumulating evidence suggests that the gut-lung axis may provide novel candidates for host-directed therapeutics against various infectious diseases. However, little is known about the gut-lung axis in the context of host protective immunity to identify new therapeutics for NTM-PDs. This study was performed to identify gut microbes and metabolites capable of conferring pulmonary immunity to NTM-PDs. Using metabolomics analysis of sera from NTM-PD patients and mouse models, we showed that the levels of l-arginine were decreased in sera from NTM-PD patients and NTM-infected mice. Oral administration of l-arginine significantly enhanced pulmonary antimicrobial activities with the expansion of IFN-γ-producing effector T cells and a shift to microbicidal (M1) macrophages in the lungs of NTM-PD model mice. Mice that received fecal microbiota transplants from l-arginine-treated mice showed increased protective host defense in the lungs against NTM-PD, whereas l-arginine-induced pulmonary host defense was attenuated in mice treated with antibiotics. Using 16S rRNA sequencing, we further showed that l-arginine administration resulted in enrichment of the gut microbiota composition with Bifidobacterium species. Notably, oral treatment with either Bifidobacterium pseudolongum or inosine enhanced antimicrobial pulmonary immune defense against NTM infection, even with multidrug-resistant clinical NTM strains. Our findings indicate that l-arginine-induced gut microbiota remodeling with enrichment of B. pseudolongum boosts pulmonary immune defense against NTM infection by driving the protective gut-lung axis in vivo.

Imaging mass spectrometry differentiates the effects of doxorubicin formulations on non-targeted tissues

Imaging mass spectrometry indicated a wide range of chemical disturbances in a model of non-targeted organs of rats treated with different formulations of doxorubicin and enabled the differentiation of drug formulation-specific effects.

Metabolomics Strategy Assisted by Transcriptomics Analysis to Identify Potential Biomarkers Associated with Tuberculosis

Purpose

To investigate the dysregulated pathways and identify reliable diagnostic biomarkers for tuberculosis using integrated analysis of metabolomics and transcriptomics.

Methods

Three groups of samples, untargeted metabolomics analysis of healthy controls (HC), latent tuberculosis infection patients (LTBI), and active tuberculosis patients (TB), were analyzed using gas chromatography time-of-flight mass spectrometry (GC-TOF MS) and ultra-high performance liquid chromatography-quantitative mass spectrometry (UHPLC-QE-MS). Both univariate and multivariate and statistical analyses were used to select differential metabolites (DMs) among group comparison, and LASSO regression analysis was employed to discover potential diagnostic biomarkers. Metabolite set enrichment analysis was performed to identify the altered metabolic pathways specifically in patients with TB. Meanwhile, a transcriptomic dataset GSEG4992 was downloaded from the GEO database to explore the differentially expressed genes (DEGs) between TB and HC identified in significantly enriched pathways. Finally, an integrative analysis of DMs and DEGs was performed to investigate the possible molecular mechanisms of TB.

Results

Thirty-three specific metabolites were significantly different between TB and HC, of which 7 (5-hydroxyindoleacetic acid, isoleucyl-isoleucine, heptadecanoic acid, indole acetaldehyde, 5-ethyl-2,4-dimethyloxazole, and 2-hydroxycaproic acid, unknown 71) were chosen as combinational potential biomarkers for TB. The area under the curve (AUC) value of these biomarkers was 0.97 (95% CI: 0.92–1.00). Metabolites set enrichment analysis (MSEA) displayed that there were 3 significantly enriched pathways among all. The genes in 3 significantly enriched pathways were further analyzed, of which 9(ALDH3B1, BCAT1, BCAT2, GLYAT, GOT1, IL4I1, MIF, SDS, SDSL) were expressed differentially. The area under the curve (AUC) values of these DEGs enriched in pathways mostly were greater than 0.8. As a result, a connected network of metabolites and genes in the pathways were established, which provides insights into the credibility of selected metabolites.

Conclusion

The newly identified metabolic biomarkers display a high potential to be developed into a promising tool for TB screening, diagnosis, and therapeutic effect monitoring.

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.

Benchtop nuclear magnetic resonance-based metabolomic approach for the diagnosis of bovine tuberculosis

Even though enormous efforts and control strategies have been implemented, bovine tuberculosis (TB) remains a significant source of health and socioeconomic concern. The standard method used in TB eradication programs for in vivo detection is the tuberculin skin test. However, the specificity of the tuberculin skin test is affected by infection with non-tuberculous mycobacteria or by vaccination. Thus, some animals are not correctly diagnosed. This study aimed first to identify a plasma metabolic TB profile by high-field (HF) nuclear magnetic resonance (NMR) spectroscopy and second measure this characteristic TB metabolic profile using low-field benchtop (LF) NMR as an affordable molecular technology for TB diagnosis. Plasma samples from cattle diagnosed with TB (derivation set, n = 11), diagnosed with paratuberculosis (PTB, n = 10), PTB-vaccinated healthy control (n = 10) and healthy PTB-unvaccinated control (n = 10) were analyzed by NMR. Unsupervised Principal Component Analysis (PCA) was used to identify metabolic differences between groups. We identified 14 metabolites significantly different between TB and control animals. The second group of TB animals was used to validate the results (validation set, n = 14). Predictive models based on metabolic fingerprint acquired by both HF and LF NMR spectroscopy successfully identified TB versus control subjects (Area under the curve of Receiver Operating Characteristic over 0.92, in both models; Confidence Interval 0.77-1). In summary, plasma fingerprinting using HF and LF-NMR differentiated TB subjects from uninfected animals, and PTB and PTB-vaccinated subjects who may provide a TB-false positive, highlighting the use of LF-NMR-based metabolomics as a complementary or alternative diagnostic tool to the current diagnostic methods.

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.

Murine Norovirus Infection Results in Anti-inflammatory Response Downstream of Amino Acid Depletion in Macrophages

Murine norovirus (MNV) infection results in a late translation shutoff that is proposed to contribute to the attenuated and delayed innate immune response observed both in vitro and in vivo. Recently, we further demonstrated the activation of the α subunit of eukaryotic initiation factor 2 (eIF2α) kinase GCN2 during MNV infection, which has been previously linked to immunomodulation and resistance to inflammatory signaling during metabolic stress. While viral infection is usually associated with activation of double-stranded RNA (dsRNA) binding pattern recognition receptor PKR, we hypothesized that the establishment of a metabolic stress in infected cells is a proviral event, exploited by MNV to promote replication through weakening the activation of the innate immune response. In this study, we used multi-omics approaches to characterize cellular responses during MNV replication. We demonstrate the activation of pathways related to the integrated stress response, a known driver of anti-inflammatory phenotypes in macrophages. In particular, MNV infection causes an amino acid imbalance that is associated with GCN2 and ATF2 signaling. Importantly, this reprogramming lacks the features of a typical innate immune response, with the ATF/CHOP target GDF15 contributing to the lack of antiviral responses. We propose that MNV-induced metabolic stress supports the establishment of host tolerance to viral replication and propagation. IMPORTANCE During viral infection, host defenses are typically characterized by the secretion of proinflammatory autocrine and paracrine cytokines, potentiation of the interferon (IFN) response, and induction of the antiviral response via activation of JAK and Stat signaling. To avoid these and propagate, viruses have evolved strategies to evade or counteract host sensing. In this study, we demonstrate that murine norovirus controls the antiviral response by activating a metabolic stress response that activates the amino acid response and impairs inflammatory signaling. This highlights novel tools in the viral countermeasures arsenal and demonstrates the importance of the currently poorly understood metabolic reprogramming occurring during viral infections.

Self-Reported Medication Use and Urinary Drug Metabolites in the German Chronic Kidney Disease (GCKD) Study

BACKGROUND

Polypharmacy is common among patients with CKD, but little is known about the urinary excretion of many drugs and their metabolites among patients with CKD.

METHODS

To evaluate self-reported medication use in relation to urine drug metabolite levels in a large cohort of patients with CKD, the German Chronic Kidney Disease study, we ascertained self-reported use of 158 substances and 41 medication groups, and coded active ingredients according to the Anatomical Therapeutic Chemical Classification System. We used a nontargeted mass spectrometry-based approach to quantify metabolites in urine; calculated specificity, sensitivity, and accuracy of medication use and corresponding metabolite measurements; and used multivariable regression models to evaluate associations and prescription patterns.

RESULTS

Among 4885 participants, there were 108 medication-drug metabolite pairs on the basis of reported medication use and 78 drug metabolites. Accuracy was excellent for measurements of 36 individual substances in which the unchanged drug was measured in urine (median, 98.5%; range, 61.1%-100%). For 66 pairs of substances and their related drug metabolites, median measurement-based specificity and sensitivity were 99.2% (range, 84.0%-100%) and 71.7% (range, 1.2%-100%), respectively. Commonly prescribed medications for hypertension and cardiovascular risk reduction-including angiotensin II receptor blockers, calcium channel blockers, and metoprolol-showed high sensitivity and specificity. Although self-reported use of prescribed analgesics (acetaminophen, ibuprofen) was <3% each, drug metabolite levels indicated higher usage (acetaminophen, 10%-26%; ibuprofen, 10%-18%).

CONCLUSIONS

This comprehensive screen of associations between urine drug metabolite levels and self-reported medication use supports the use of pharmacometabolomics to assess medication adherence and prescription patterns in persons with CKD, and indicates under-reported use of medications available over the counter, such as analgesics.

Evolutionary Views of Tuberculosis: Indoleamine 2,3-Dioxygenase Catalyzed Nicotinamide Synthesis Reflects Shifts in Macrophage Metabolism: Indoleamine 2,3-Dioxygenase Reflects Altered Macrophage Metabolism During Tuberculosis Pathogenesis

Indoleamine 2,3-dioxygenase (IDO) is the rate-limiting enzyme in conversion of tryptophan to kynurenines, feeding de novo nicotinamide synthesis. IDO orchestrates materno-foetal tolerance, increasing human reproductive fitness. IDO mediates immune suppression through depletion of tryptophan required by T lymphocytes and other mechanisms. IDO is expressed by alternatively activated macrophages, suspected to play a key role in tuberculosis (TB) pathogenesis. Unlike its human host, Mycobacterium tuberculosis can synthesize tryptophan, suggesting possible benefit to the host from infection with the microbe. Intriguingly, nicotinamide analogues are used to treat TB. In reviewing this field, it is postulated that flux through the nicotinamide synthesis pathway reflects switching between aerobic glycolysis and oxidative phosphorylation in M. tuberculosis-infected macrophages. The evolutionary cause of such shifts may be ancient mitochondrial behavior related to reproductive fitness. Evolutionary perspectives on the IDO pathway may elucidate why, after centuries of co-existence with the Tubercle bacillus, humans still remain susceptible to TB disease.

Monocyte metabolic transcriptional programs associate with resistance to tuberculin skin test/interferon-γ release assay conversion

After extensive exposure to Mycobacterium tuberculosis (Mtb), most individuals acquire latent Mtb infection (LTBI) defined by a positive tuberculin skin test (TST) or interferon-γ release assay (IGRA). To identify mechanisms of resistance to Mtb infection, we compared transcriptional profiles from highly exposed contacts who resist TST/IGRA conversion (resisters, RSTRs) and controls with LTBI using RNAseq. Gene sets related to carbon metabolism and free fatty acid (FFA) transcriptional responses enriched across 2 independent cohorts suggesting RSTR and LTBI monocytes have distinct activation states. We compared intracellular Mtb replication in macrophages treated with FFAs and found that palmitic acid (PA), but not oleic acid (OA), enhanced Mtb intracellular growth. This PA activity correlated with its inhibition of proinflammatory cytokines in Mtb-infected cells. Mtb growth restriction in PA-treated macrophages was restored by activation of AMP kinase (AMPK), a central host metabolic regulator known to be inhibited by PA. Finally, we genotyped AMPK variants and found 7 SNPs in PRKAG2, which encodes the AMPK-γ subunit, that strongly associated with RSTR status. Taken together, RSTR and LTBI phenotypes are distinguished by FFA transcriptional programs and by genetic variation in a central metabolic regulator, which suggests immunometabolic pathways regulate TST/IGRA conversion.

Abnormal Tryptophan Metabolism in HIV and Mycobacterium tuberculosis Infection

Host metabolism has recently gained more attention for its roles in physiological functions and pathologic conditions. Of these, metabolic tryptophan disorders generate a pattern of abnormal metabolites that are implicated in various diseases. Here, we briefly highlight the recent advances regarding abnormal tryptophan metabolism in HIV and Mycobacterium tuberculosis infection and discuss its potential impact on immune regulation, disease progression, and neurological disorders. Finally, we also discuss the potential for metabolic tryptophan interventions toward these infectious diseases.

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.

Perspectives for systems biology in the management of tuberculosis

Standardised management of tuberculosis may soon be replaced by individualised, precision medicine-guided therapies informed with knowledge provided by the field of systems biology. Systems biology is a rapidly expanding field of computational and mathematical analysis and modelling of complex biological systems that can provide insights into mechanisms underlying tuberculosis, identify novel biomarkers, and help to optimise prevention, diagnosis and treatment of disease. These advances are critically important in the context of the evolving epidemic of drug-resistant tuberculosis. Here, we review the available evidence on the role of systems biology approaches - human and mycobacterial genomics and transcriptomics, proteomics, lipidomics/metabolomics, immunophenotyping, systems pharmacology and gut microbiomes - in the management of tuberculosis including prediction of risk for disease progression, severity of mycobacterial virulence and drug resistance, adverse events, comorbidities, response to therapy and treatment outcomes. Application of the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach demonstrated that at present most of the studies provide "very low" certainty of evidence for answering clinically relevant questions. Further studies in large prospective cohorts of patients, including randomised clinical trials, are necessary to assess the applicability of the findings in tuberculosis prevention and more efficient clinical management of patients.

Application of Volatilome Analysis to the Diagnosis of Mycobacteria Infection in Livestock

Volatile organic compounds (VOCs) are small molecular mass metabolites which compose the volatilome, whose analysis has been widely employed in different areas. This innovative approach has emerged in research as a diagnostic alternative to different diseases in human and veterinary medicine, which still present constraints regarding analytical and diagnostic sensitivity. Such is the case of the infection by mycobacteria responsible for tuberculosis and paratuberculosis in livestock. Although eradication and control programs have been partly managed with success in many countries worldwide, the often low sensitivity of the current diagnostic techniques against Mycobacterium bovis (as well as other mycobacteria from Mycobacterium tuberculosis complex) and Mycobacterium avium subsp. paratuberculosis together with other hurdles such as low mycobacteria loads in samples, a tedious process of microbiological culture, inhibition by many variables, or intermittent shedding of the mycobacteria highlight the importance of evaluating new techniques that open different options and complement the diagnostic paradigm. In this sense, volatilome analysis stands as a potential option because it fulfills part of the mycobacterial diagnosis requirements. The aim of the present review is to compile the information related to the diagnosis of tuberculosis and paratuberculosis in livestock through the analysis of VOCs by using different biological matrices. The analytical techniques used for the evaluation of VOCs are discussed focusing on the advantages and drawbacks offered compared with the routine diagnostic tools. In addition, the differences described in the literature among in vivo and in vitro assays, natural and experimental infections, and the use of specific VOCs (targeted analysis) and complete VOC pattern (non-targeted analysis) are highlighted. This review emphasizes how this methodology could be useful in the problematic diagnosis of tuberculosis and paratuberculosis in livestock and poses challenges to be addressed in future research.

Differential Expression of Activation Markers by Mycobacterium tuberculosis-specific CD4+ T Cell Distinguishes Extrapulmonary From Pulmonary Tuberculosis and Latent Infection

BACKGROUND

Diagnosis of active tuberculosis (ATB) currently relies on detection of Mycobacterium tuberculosis (Mtb). Identifying patients with extrapulmonary TB (EPTB) remains challenging because microbiological confirmation is often not possible. Highly accurate blood-based tests could improve diagnosis of both EPTB and pulmonary TB (PTB) and timely initiation of anti-TB therapy.

METHODS

A case-control study was performed using discriminant analyses to validate an approach using Mtb-specific CD4+T-cell activation markers in blood to discriminate PTB and EPTB from latent TB infection (LTBI) as well as EPTB from PTB in 270 Brazilian individuals. We further tested the effect of human immunodeficiency virus (HIV) coinfection on diagnostic performance. Frequencies of interferon-γ +CD4+T cells expressing CD38, HLADR, and/or Ki67 were assessed by flow cytometry.

RESULTS

EPTB and PTB were associated with higher frequencies of CD4+T cells expressing CD38, HLADR, or Ki67 compared with LTBI (all P values < .001). Moreover, frequencies of HLADR+ (P = .03) or Ki67+ (P < .001) cells accurately distinguished EPTB from PTB. HIV infection did not affect the capacity of these markers to distinguish ATB from LTBI or EPTB from PTB.

CONCLUSIONS

Cell activation markers in Mtb-specific CD4+T cells distinguished ATB from LTBI and EPTB from PTB, regardless of HIV infection status. These parameters provide an attractive approach for developing blood-based diagnostic tests for both active and latent TB.

Metabolic alterations in a rat model of Takotsubo syndrome

AIMS

Cardiac energetic impairment is a major finding in takotsubo patients. We investigate specific metabolic adaptations to direct future therapies.

METHODS AND RESULTS

An isoprenaline-injection female rat model (versus sham) was studied at day-3; recovery assessed at day-7. Substrate uptake, metabolism, inflammation and remodelling were investigated by 18F-FDG-PET, metabolomics, qPCR and WB. Isolated cardiomyocytes were patch-clamped during stress protocols for redox states of NAD(P)H/FAD or [Ca2+]c, [Ca2+]m and sarcomere length. Mitochondrial respiration was assessed by seahorse/Clark electrode (glycolytic and β-oxidation substrates).Cardiac 18F-FDG metabolic rate was increased in takotsubo (p = 0.006), as were expression of GLUT4-RNA/GLUT1/HK2-RNA and HK activity (all p < 0.05), with concomitant accumulation of glucose- and fructose-6-phosphates (p > 0.0001). Both lactate and pyruvate were lower (p < 0.05) despite increases in LDH-RNA and PDH (p < 0.05 both). β-oxidation enzymes CPT1b-RNA and 3KAT were increased (p < 0.01) but malonyl-CoA (CPT-1 regulator) was upregulated (p = 0.01) with decreased fatty acids and acyl-carnitines levels (p = 0.0001-0.02). Krebs cycle intermediates α-ketoglutarate and succinyl-carnitine were reduced (p < 0.05) as was cellular ATP reporter dihydroorotate (p = 0.003). Mitochondrial Ca2+ uptake during high workload was impaired on day-3 (p < 0.0001), inducing oxidation of NAD(P)H and FAD (p = 0.03) but resolved by day-7. There were no differences in mitochondrial respiratory function, sarcomere shortening or [Ca2+] transients of isolated cardiomyocytes, implying preserved integrity of both mitochondria and cardiomyocyte. Inflammation and remodelling were upregulated - increased CD68-RNA, collagen RNA/protein and skeletal actin RNA (all p < 0.05).

CONCLUSION

Dys-regulation of glucose and lipid metabolic pathways with decreases in final glycolytic and β-oxidation metabolites and reduced availability of Krebs intermediates characterises takotsubo myocardium. The energetic deficit accompanies defective Ca2+ handling, inflammation and upregulation of remodelling pathways, with preservation of sarcomeric and mitochondrial integrity.

TRANSLATIONAL PERSPECTIVE

The simultaneous dysregulation in the glycolytic and beta-oxidation pathways which underlies the energetic deficit of the takotsubo heart supports further testing of currently available metabolic modulators as possible candidates for successful therapy, as well as targeting the inflammatory and remodelling pathways.

Metabolic Regulation of Immune Responses to Mycobacterium tuberculosis: A Spotlight on L-Arginine and L-Tryptophan Metabolism

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), is a leading cause of death worldwide. Despite decades of research, there is still much to be uncovered regarding the immune response to Mtb infection. Here, we summarize the current knowledge on anti-Mtb immunity, with a spotlight on immune cell amino acid metabolism. Specifically, we discuss L-arginine and L-tryptophan, focusing on their requirements, regulatory roles, and potential use as adjunctive therapy in TB patients. By continuing to uncover the immune cell contribution during Mtb infection and how amino acid utilization regulates their functions, it is anticipated that novel host-directed therapies may be developed and/or refined, helping to eradicate TB.

Caloric Restriction Promotes Immunometabolic Reprogramming Leading to Protection from Tuberculosis

There is a strong relationship between metabolic state and susceptibility to Mycobacterium tuberculosis (MTB) infection, with energy metabolism setting the basis for an exaggerated immuno-inflammatory response, which concurs with MTB pathogenesis. Herein, we show that controlled caloric restriction (CR), not leading to malnutrition, protects susceptible DBA/2 mice against pulmonary MTB infection by reducing bacterial load, lung immunopathology, and generation of foam cells, an MTB reservoir in lung granulomas. Mechanistically, CR induced a metabolic shift toward glycolysis, and decreased both fatty acid oxidation and mTOR activity associated with induction of autophagy in immune cells. An integrated multi-omics approach revealed a specific CR-induced metabolomic, transcriptomic, and proteomic signature leading to reduced lung damage and protective remodeling of lung interstitial tightness able to limit MTB spreading. Our data propose CR as a feasible immunometabolic manipulation to control MTB infection, and this approach offers an unexpected strategy to boost immunity against MTB.

Differences between infected and noninfected synovial fluid

AIMS

The diagnosis of joint infections is an inexact science using combinations of blood inflammatory markers and microscopy, culture, and sensitivity of synovial fluid (SF). There is potential for small molecule metabolites in infected SF to act as infection markers that could improve accuracy and speed of detection. The objective of this study was to use nuclear magnetic resonance (NMR) spectroscopy to identify small molecule differences between infected and noninfected human SF.

METHODS

In all, 16 SF samples (eight infected native and prosthetic joints plus eight noninfected joints requiring arthroplasty for end-stage osteoarthritis) were collected from patients. NMR spectroscopy was used to analyze the metabolites present in each sample. Principal component analysis and univariate statistical analysis were undertaken to investigate metabolic differences between the two groups.

RESULTS

A total of 16 metabolites were found in significantly different concentrations between the groups. Three were in higher relative concentrations (lipids, cholesterol, and N-acetylated molecules) and 13 in lower relative concentrations in the infected group (citrate, glycine, glycosaminoglycans, creatinine, histidine, lysine, formate, glucose, proline, valine, dimethylsulfone, mannose, and glutamine).

CONCLUSION

Metabolites found in significantly greater concentrations in the infected cohort are markers of inflammation and infection. They play a role in lipid metabolism and the inflammatory response. Those found in significantly reduced concentrations were involved in carbohydrate metabolism, nucleoside metabolism, the glutamate metabolic pathway, increased oxidative stress in the diseased state, and reduced articular cartilage breakdown. This is the first study to demonstrate differences in the metabolic profile of infected and noninfected human SF, using a noninfected matched cohort, and may represent putative biomarkers that form the basis of new diagnostic tests for infected SF. Cite this article: Bone Joint Res 2021;10(1):85-95.

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.

Integrative Metabolomics to Identify Molecular Signatures of Responses to Vaccines and Infections

Approaches to the identification of metabolites have progressed from early biochemical pathway evaluation to modern high-dimensional metabolomics, a powerful tool to identify and characterize biomarkers of health and disease. In addition to its relevance to classic metabolic diseases, metabolomics has been key to the emergence of immunometabolism, an important area of study, as leukocytes generate and are impacted by key metabolites important to innate and adaptive immunity. Herein, we discuss the metabolomic signatures and pathways perturbed by the activation of the human immune system during infection and vaccination. For example, infection induces changes in lipid (e.g., free fatty acids, sphingolipids, and lysophosphatidylcholines) and amino acid pathways (e.g., tryptophan, serine, and threonine), while vaccination can trigger changes in carbohydrate and bile acid pathways. Amino acid, carbohydrate, lipid, and nucleotide metabolism is relevant to immunity and is perturbed by both infections and vaccinations. Metabolomics holds substantial promise to provide fresh insight into the molecular mechanisms underlying the host immune response. Its integration with other systems biology platforms will enhance studies of human health and disease.