Plasma metabolomics in human pulmonary tuberculosis disease: a pilot study

Metabolomics in the Diagnosis of Bacterial Infections

One of the essential factors in the appropriate treatment of infections is accurate and timely laboratory diagnosis. The correct diagnosis of infections plays a vital role in determining desirable therapy and controlling the spread of pathogens. Traditional methods of infection diagnosis are limited by several factors such as insufficient sensitivity and specificity, being time-consuming and laborious, having a low ability to distinguish infection from non-infectious inflammatory conditions and a low potential to predict treatment outcomes. Therefore, it is necessary to find innovative strategies for detecting specific biomarkers in order to diagnose infections. The rapid advancement of metabolomics makes it possible to determine the pattern of metabolite changes in the both of pathogen and the host during an infection. Metabolomics is a method used to assess the levels and type of metabolites in an organism. Metabolites are of low-molecular-weight compounds produced as a result of metabolic processes and pathways within cells. Metabolomics provides valuable data to detect accurate biomarkers of specific biochemical features directly related to certain phenotypes or conditions. This study aimed to review the applications and progress of metabolomics as a biomarker for the diagnosis of bacterial infections.

Untargeted metabolomics of 3xTg-AD neurotoxic astrocytes

Alzheimer's disease (AD) is the most common form of dementia, affecting approximately 47 M people worldwide. Histological features and genetic risk factors, among other evidence, supported the amyloid hypothesis of the disease. This neuronocentric paradigm is currently undergoing a shift, considering evidence of the role of other cell types, such as microglia and astrocytes, in disease progression. Previously, we described a particular astrocyte subtype obtained from the 3xTg-AD murine model that displays neurotoxic properties in vitro. We continue here our exploratory analysis through the lens of metabolomics to identify potentially altered metabolites and biological pathways. Cell extracts from neurotoxic and control astrocytes were compared using high-resolution mass spectrometry-based metabolomics. Around 12 % of metabolic features demonstrated significant differences between neurotoxic and control astrocytes, including alterations in the key metabolite glutamate. Consistent with our previous transcriptomic study, the present results illustrate many homeostatic and regulatory functions of metabolites, suggesting that neurotoxic 3xTg-AD astrocytes exhibit alterations in the Krebs cycle as well as the prostaglandin pathway. This is the first metabolomic study performed in 3xTg-AD neurotoxic astrocytes. These results provide insight into metabolic alterations potentially associated with neurotoxicity and pathology progression in the 3xTg-AD mouse model and strengthen the therapeutic potential of astrocytes in AD. BIOLOGICAL SIGNIFICANCE: Our study is the first high-resolution metabolomic characterization of the novel neurotoxic 3xTg-AD astrocytes. We propose key metabolites and pathway alterations, as well as possible associations with gene expression alterations in the model. Our results are in line with recent hypotheses beyond the amyloid cascade, considering the involvement of several stress response cascades during the development of Alzheimer's disease. This work could inspire other researchers to initiate similar studies in related models. Furthermore, this work illustrates a powerful workflow for metabolite annotation and selection that can be implemented in other studies.

Integrating untargeted and targeted LC-MS-based metabolomics to identify the serum metabolite biomarkers for tuberculosis

Given the limitations of untargeted metabolomics in precise metabolite quantification, our current research employed a novel approach by integrating untargeted and targeted metabolomics utilizing ultra-high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF-MS/MS) to analyze the metabolic profile and potential biomarkers for tuberculosis (TB). A cohort of 36 TB patients and 36 healthy controls (HC) was enlisted to obtain serum samples. Multivariate pattern recognition and univariate statistical analysis were employed to screen and elucidate the differential metabolites, whereas dot plots and receiver operating characteristic (ROC) curves were established for the identification of potential biomarkers of TB. The results indicated a distinct differentiation between the two groups, identifying 99 metabolites associated with five primary metabolic pathways in relation to TB. Of these, 19 metabolites exhibited high levels of sensitivity and specificity, as evidenced by the area under curve values approaching 1. Following targeted quantitative analysis, three potential metabolites, namely, L-asparagine, L-glutamic acid, and arachidonic acid, were demonstrated excellent discriminatory ability as evidenced by the results of the ROC curve, dot plots, and random forest model. Particularly noteworthy was the enhanced diagnostic efficacy of the combination of these three metabolites compared to singular biomarkers, suggesting their potential utility as serum biomarkers for TB diagnosis.

Altered hepatic metabolic landscape and insulin sensitivity in response to pulmonary tuberculosis

Chronic inflammation triggers development of metabolic disease, and pulmonary tuberculosis (TB) generates chronic systemic inflammation. Whether TB induced-inflammation impacts metabolic organs and leads to metabolic disorder is ill defined. The liver is the master regulator of metabolism and to determine the impact of pulmonary TB on this organ we undertook an unbiased mRNA and protein analyses of the liver in mice with TB and reanalysed published data on human disease. Pulmonary TB led to upregulation of genes in the liver related to immune signalling and downregulation of genes encoding metabolic processes. In liver, IFN signalling pathway genes were upregulated and this was reflected in increased biochemical evidence of IFN signalling, including nuclear location of phosphorylated Stat-1 in hepatocytes. The liver also exhibited reduced expression of genes encoding the gluconeogenesis rate-limiting enzymes Pck1 and G6pc. Phosphorylation of CREB, a transcription factor controlling gluconeogenesis was drastically reduced in the livers of mice with pulmonary TB as was phosphorylation of other glucose metabolism-related kinases, including GSK3a, AMPK, and p42. In support of the upregulated IFN signalling being linked to the downregulated metabolic functions in the liver, we found suppression of gluconeogenic gene expression and reduced CREB phosphorylation in hepatocyte cell lines treated with interferons. The impact of reduced gluconeogenic gene expression in the liver was seen when infected mice were less able to convert pyruvate, a gluconeogenesis substrate, to the same extent as uninfected mice. Infected mice also showed evidence of reduced systemic and hepatic insulin sensitivity. Similarly, in humans with TB, we found that changes in a metabolite-based signature of insulin resistance correlates temporally with successful treatment of active TB and with progression to active TB following exposure. These data support the hypothesis that TB drives interferon-mediated alteration of hepatic metabolism resulting in reduced gluconeogenesis and drives systemic reduction of insulin sensitivity.

High-Resolution Plasma Metabolomics Identifies Alterations in Fatty Acid, Energy, and Micronutrient Metabolism in Adults Across the Leprosy Spectrum

BACKGROUND

High-resolution metabolomics (HRM) is an innovative tool to study challenging infectious diseases like leprosy, where the pathogen cannot be grown with standard methods. Here, we use HRM to better understand associations between disease manifestations, nutrition, and host metabolism.

METHODS

From 2018 to 2019, adults with leprosy and controls were recruited in Minas Gerais, Brazil. Plasma metabolites were detected using an established HRM workflow and characterized by accurate mass, mass to charge ratio m/z and retention time. The mummichog informatics package compared metabolic pathways between cases and controls and between multibacillary (MB) and paucibacillary (PB) leprosy. Additionally, select individual metabolites were quantified and compared.

RESULTS

Thirty-nine cases (62% MB and 38% PB) and 25 controls were enrolled. We found differences (P < .05) in several metabolic pathways, including fatty acid metabolism, carnitine shuttle, retinol, vitamin D3, and C-21 steroid metabolism, between cases and controls with lower retinol and associated metabolites in cases. Between MB and PB, leukotrienes, prostaglandins, tryptophan, and cortisol were all found to be lower in MB (P < .05).

DISCUSSION

Metabolites associated with several nutrient-related metabolic pathways appeared differentially regulated in leprosy, especially MB versus PB. This pilot study demonstrates the metabolic interdependency of these pathways, which may play a role in the pathophysiology of disease.

ALTERATIONS IN HISTIDINE METABOLISM IS A FEATURE OF EARLY AUTOSOMAL DOMINANT POLYCYSTIC KIDNEY DISEASE (ADPKD)

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by epithelial proliferation and progressive cyst enlargement. Using a non-targeted high-resolution metabolomics approach, we analyzed biofluids from 36 ADPKD and 18 healthy controls with estimated glomerular filtration rate (eGFR) > 60 ml/min to identify features specific to ADPKD or that associate with disease severity [eGFR or height-corrected total kidney volume (htTKV)]. Multiple pathways differed between ADPKD subjects and controls, with the histidine pathway being the most highly represented. Plasma histidine, urinary N-methylhistamine, methylimidazole-acetaldehyde, and imidazole-acetaldehyde, as well as 3-methylhistidine and anserine were increased, while plasma N-acetylhistamine and urinary imidazole-acetic acid were decreased in ADPKD compared to controls. In ADPKD, urinary histidine and a histidine derivative, urocanate (a precursor of glutamate), were significantly associated. HtTKV and eGFR were inversely associated with urinary glutamine and plasma 4-imidazolone-5-propionic acid, respectively. Supernatant from cultured human ADPKD renal cystic epithelia demonstrated increased aspartate and glutamate levels at 8 and 24 hours compared to primary tubular epithelia (p < 0.001). Following exposure over 48 hours to α-fluromethylhistidine, an inhibitor of histamine production, primary human PKD1 cyst epithelia proliferation increased significantly from baseline (p < 0.01) and greater than non-cystic epithelia (p < 0.05). The histidine ammonia lyase inhibitor nitromethane reversed α-fluromethylhistidine-induced cyst epithelia proliferation indicating a role for glutamate in cyst growth. In conclusion, histidine metabolism is altered preferentially leading to glutamate production and epithelial proliferation in ADPKD and associates with disease severity.

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.

Resolvin D2 and its receptor GPR18 in cardiovascular and metabolic diseases: A promising biomarker and therapeutic target

Accumulating evidence suggests that inflammation plays an important role in the pathophysiology of the initiation and progression of cardiovascular and metabolic diseases (CVMDs). Anti-inflammation strategies and those that promote inflammation resolution have gradually become potential therapeutic approaches for CVMDs. Resolvin D2 (RvD2), a specialized pro-resolving mediator, exerts anti-inflammatory and pro-resolution effects through its receptor GPR18, a G protein-coupled receptor. Recently, the RvD2/GPR18 axis has received more attention due to its protective role in CVMDs, including atherosclerosis, hypertension, ischaemiareperfusion, and diabetes. Here, we introduce basic information about RvD2 and GPR18, summarize their roles in different immune cells, and review the therapeutic potential of the RvD2/GPR18 axis in CVMDs. In summary, RvD2 and its receptor GPR18 play an important role in the occurrence and development of CVMDs and are potential biomarkers and therapeutic targets.

Complex Mixtures and Multiple Stressors: Evaluating Combined Chemical Exposures and Cumulative Toxicity

The problem of chemical mixtures in the environment encompasses biological, analytical, logistical, and regulatory challenges, among others [...].

Evaluation of extraction methods for untargeted metabolomic studies for future applications in zebrafish larvae infection models

Sample preparation in untargeted metabolomics should allow reproducible extractions of as many molecules as possible. Thus, optimizing sample preparation is crucial. This study compared six different extraction procedures to find the most suitable for extracting zebrafish larvae in the context of an infection model. Two one-phase extractions employing methanol (I) and a single miscible phase of methanol/acetonitrile/water (II) and two two-phase methods using phase separation between chloroform and methanol/water combinations (III and IV) were tested. Additional bead homogenization was used for methods III and IV (III_B and IV_B). Nine internal standards and 59 molecules of interest (MoInt) related to mycobacterial infection were used for method evaluation. Two-phase methods (III and IV) led to a lower feature count, higher peak areas of MoInt, especially amino acids, and higher coefficients of variation in comparison to one-phase extractions. Adding bead homogenization increased feature count, peak areas, and CVs. Extraction I showed higher peak areas and lower CVs than extraction II, thus being the most suited one-phase method. Extraction III and IV showed similar results, with III being easier to execute and less prone to imprecisions. Thus, for future applications in zebrafish larvae metabolomics and infection models, extractions I and III might be chosen.

Small molecule bio-signature in childhood intra-thoracic tuberculosis identified by metabolomics

The diagnosis of pediatric tuberculosis (TB) remains a major challenge, hence the evaluation of new tools for improved diagnostics is urgently required. We investigated the serum metabolic profile of children with culture-confirmed intra-thoracic TB (ITTB) (n = 23) and compared it with those of non-TB controls (NTCs) (n = 13) using proton NMR spectroscopy-based targeted and untargeted metabolomics approaches. In targeted metabolic profiling, five metabolites (histidine, glycerophosphocholine, creatine/phosphocreatine, acetate, and choline) differentiated TB children from NTCs. Additionally, seven discriminatory metabolites (N-α-acetyl-lysine, polyunsaturated fatty acids, phenylalanine, lysine, lipids, glutamate + glutamine, and dimethylglycine) were identified in untargeted metabolic profiling. The pathway analysis revealed alterations in six metabolic pathways. The altered metabolites were associated with impaired protein synthesis, hindered anti-inflammatory and cytoprotective mechanisms, abnormalities in energy generation processes and membrane metabolism, and deregulated fatty acid and lipid metabolisms in children with ITTB. The diagnostic significance of the classification models obtained from significantly distinguishing metabolites showed sensitivity, specificity, and area under the curve of 78.2%, 84.6%, and 0.86, respectively, in the targeted profiling and 92.3%, 100%, and 0.99, respectively, in the untargeted profiling. Our findings highlight detectable metabolic changes in childhood ITTB; however, further validation is warranted in a large cohort of the pediatric population.

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.

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.

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.

Untargeted metabolomics of pulmonary tuberculosis patient serum reveals potential prognostic markers of both latent infection and outcome

Currently, there are no particularly effective biomarkers to distinguish between latent tuberculosis infection (LTBI) and active pulmonary tuberculosis (PTB) and evaluate the outcome of TB treatment. In this study, we have characterized the changes in the serum metabolic profiles caused by Mycobacterium tuberculosis (Mtb) infection and standard anti-TB treatment with isoniazid-rifampin-pyrazinamide-ethambutol (HRZE) using GC-MS and LC-MS/MS. Seven metabolites, including 3-oxopalmitic acid, akeboside ste, sulfolithocholic acid, 2-decylfuran (4,8,8-trimethyldecahydro-1,4-methanoazulen-9-yl)methanol, d-(+)-camphor, and 2-methylaminoadenosine, were identified to have significantly higher levels in LTBI and untreated PTB patients (T0) than those in uninfected healthy controls (Un). Among them, akeboside Ste and sulfolithocholic acid were significantly decreased in PTB patients with 2-month HRZE (T2) and cured PTB patients with 2-month HRZE followed by 4-month isoniazid-rifampin (HR) (T6). Receiver operator characteristic curve analysis revealed that the combined diagnostic model showed excellent performance for distinguishing LT from T0 and Un. By analyzing the biochemical and disease-related pathways, we observed that the differential metabolites in the serum of LTBI or TB patients, compared to healthy controls, were mainly involved in glutathione metabolism, ascorbate and aldarate metabolism, and porphyrin and chlorophyll metabolism. The metabolites with significant differences between the T0 group and the T6 group were mainly enriched in niacin and nicotinamide metabolism. Our study provided more detailed experimental data for developing laboratory standards for evaluating LTBI and cured PTB.

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.

Combining metabolome and clinical indicators with machine learning provides some promising diagnostic markers to precisely detect smear-positive/negative pulmonary tuberculosis

Background

Tuberculosis (TB) had been the leading lethal infectious disease worldwide for a long time (2014–2019) until the COVID-19 global pandemic, and it is still one of the top 10 death causes worldwide. One important reason why there are so many TB patients and death cases in the world is because of the difficulties in precise diagnosis of TB using common detection methods, especially for some smear-negative pulmonary tuberculosis (SNPT) cases. The rapid development of metabolome and machine learning offers a great opportunity for precision diagnosis of TB. However, the metabolite biomarkers for the precision diagnosis of smear-positive and smear-negative pulmonary tuberculosis (SPPT/SNPT) remain to be uncovered. In this study, we combined metabolomics and clinical indicators with machine learning to screen out newly diagnostic biomarkers for the precise identification of SPPT and SNPT patients.

Methods

Untargeted plasma metabolomic profiling was performed for 27 SPPT patients, 37 SNPT patients and controls. The orthogonal partial least squares-discriminant analysis (OPLS-DA) was then conducted to screen differential metabolites among the three groups. Metabolite enriched pathways, random forest (RF), support vector machines (SVM) and multilayer perceptron neural network (MLP) were performed using Metaboanalyst 5.0, “caret” R package, “e1071” R package and “Tensorflow” Python package, respectively.

Results

Metabolomic analysis revealed significant enrichment of fatty acid and amino acid metabolites in the plasma of SPPT and SNPT patients, where SPPT samples showed a more serious dysfunction in fatty acid and amino acid metabolisms. Further RF analysis revealed four optimized diagnostic biomarker combinations including ten features (two lipid/lipid-like molecules and seven organic acids/derivatives, and one clinical indicator) for the identification of SPPT, SNPT patients and controls with high accuracy (83–93%), which were further verified by SVM and MLP. Among them, MLP displayed the best classification performance on simultaneously precise identification of the three groups (94.74%), suggesting the advantage of MLP over RF/SVM to some extent.

Conclusions

Our findings reveal plasma metabolomic characteristics of SPPT and SNPT patients, provide some novel promising diagnostic markers for precision diagnosis of various types of TB, and show the potential of machine learning in screening out biomarkers from big data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07694-8.

Pathological and protective roles of dendritic cells in Mycobacterium tuberculosis infection: Interaction between host immune responses and pathogen evasion

Dendritic cells (DCs) are principal defense components that play multifactorial roles in translating innate immune responses to adaptive immunity in Mycobacterium tuberculosis (Mtb) infections. The heterogeneous nature of DC subsets follows their altered functions by interacting with other immune cells, Mtb, and its products, enhancing host defense mechanisms or facilitating pathogen evasion. Thus, a better understanding of the immune responses initiated, promoted, and amplified or inhibited by DCs in Mtb infection is an essential step in developing anti-tuberculosis (TB) control measures, such as host-directed adjunctive therapy and anti-TB vaccines. This review summarizes the recent advances in salient DC subsets, including their phenotypic classification, cytokine profiles, functional alterations according to disease stages and environments, and consequent TB outcomes. A comprehensive overview of the role of DCs from various perspectives enables a deeper understanding of TB pathogenesis and could be useful in developing DC-based vaccines and immunotherapies.

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.

Crosstalk between Host Genome and Metabolome among People with HIV in South Africa

Genome-wide association studies (GWAS) of circulating metabolites have revealed the role of genetic regulation on the human metabolome. Most previous investigations focused on European ancestry, and few studies have been conducted among populations of African descent living in Africa, where the infectious disease burden is high (e.g., human immunodeficiency virus (HIV)). It is important to understand the genetic associations of the metabolome in diverse at-risk populations including people with HIV (PWH) living in Africa. After a thorough literature review, the reported significant gene−metabolite associations were tested among 490 PWH in South Africa. Linear regression was used to test associations between the candidate metabolites and genetic variants. GWAS of 154 plasma metabolites were performed to identify novel genetic associations. Among the 29 gene−metabolite associations identified in the literature, we replicated 10 in South Africans with HIV. The UGT1A cluster was associated with plasma levels of biliverdin and bilirubin; SLC16A9 and CPS1 were associated with carnitine and creatine, respectively. We also identified 22 genetic associations with metabolites using a genome-wide significance threshold (p-value < 5 × 10−8). In a GWAS of plasma metabolites in South African PWH, we replicated reported genetic associations across ancestries, and identified novel genetic associations using a metabolomics approach.

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.

Targeting the Annexin A1-FPR2/ALX pathway for host-directed therapy in dengue disease

Host immune responses contribute to dengue's pathogenesis and severity, yet the possibility that failure in endogenous inflammation resolution pathways could characterise the disease has not been contemplated. The pro-resolving protein Annexin A1 (AnxA1) is known to counterbalance overexuberant inflammation and mast cell (MC) activation. We hypothesised that inadequate AnxA1 engagement underlies the cytokine storm and vascular pathologies associated with dengue disease. Levels of AnxA1 were examined in the plasma of dengue patients and infected mice. Immunocompetent, interferon (alpha and beta) receptor one knockout (KO), AnxA1 KO, and formyl peptide receptor 2 (FPR2) KO mice were infected with dengue virus (DENV) and treated with the AnxA1 mimetic peptide Ac_2-26 for analysis. In addition, the effect of Ac_2-26 on DENV-induced MC degranulation was assessed in vitro and in vivo. We observed that circulating levels of AnxA1 were reduced in dengue patients and DENV-infected mice. Whilst the absence of AnxA1 or its receptor FPR2 aggravated illness in infected mice, treatment with AnxA1 agonistic peptide attenuated disease manifestationsatteanuated the symptoms of the disease. Both clinical outcomes were attributed to modulation of DENV-mediated viral load-independent MC degranulation. We have thereby identified that altered levels of the pro-resolving mediator AnxA1 are of pathological relevance in DENV infection, suggesting FPR2/ALX agonists as a therapeutic target for dengue disease.

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.

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.

Plasma Metabolomics of Intermediate and Neovascular Age-Related Macular Degeneration Patients

To characterize metabolites and metabolic pathways altered in intermediate and neovascular age-related macular degeneration (IAMD and NVAMD), high resolution untargeted metabolomics was performed via liquid chromatography-mass spectrometry on plasma samples obtained from 91 IAMD patients, 100 NVAMD patients, and 195 controls. Plasma metabolite levels were compared between: AMD patients and controls, IAMD patients and controls, and NVAMD and IAMD patients. Partial least-squares discriminant analysis and linear regression were used to identify discriminatory metabolites. Pathway analysis was performed to determine metabolic pathways altered in AMD. Among the comparisons, we identified 435 unique discriminatory metabolic features. Using computational methods and tandem mass spectrometry, we identified 11 metabolic features whose molecular identities had been previously verified and confirmed the molecular identities of three additional discriminatory features. Included among the discriminatory metabolites were acylcarnitines, phospholipids, amino acids, and steroid metabolites. Pathway analysis revealed that lipid, amino acid, and vitamin metabolism pathways were altered in NVAMD, IAMD, or AMD in general, including the carnitine shuttle pathway which was significantly altered in all comparisons. Finally, few discriminatory features were identified between IAMD patients and controls, suggesting that plasma metabolic profiles of IAMD patients are more similar to controls than to NVAMD patients.

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.

Specialized pro-resolving mediators: biosynthesis and biological role in bacterial infections

Acute inflammation caused by bacterial infections is an essential biological defence mechanism of the host in order to neutralize and clear the invaders and to return to homeostasis. Despite its protective function, inflammation may become persistent and uncontrolled, resulting in chronic diseases and tissue destruction as consequence of the unresolved inflammatory process. Therefore, spatiotemporal induction of endogenous inflammation resolution programs that govern bacterial clearance as well as tissue repair and regeneration, are of major importance in order to enable tissues to restore functions. Lipid mediators that are de-novo biosynthesized from polyunsaturated fatty acids (PUFAs) mainly by lipoxygenases and cyclooxygenases, critically regulate the initiation, the maintenance but also the resolution of infectious inflammation and tissue regeneration. The discovery of specialized pro-resolving mediators (SPMs) generated from omega-3 PUFAs stimulated intensive research in inflammation resolution, especially in infectious inflammation elicited by bacteria. SPMs are immunoresolvents that actively terminate inflammation by limiting neutrophil influx, stimulating phagocytosis, bacterial killing and clearance as well as efferocytosis of apoptotic neutrophils and cellular debris by macrophages. Moreover, SPMs prevent collateral tissue damage, promote tissue repair and regeneration and lower antibiotic requirement. Here, we review the biosynthesis of SPMs in bacterial infections and cover specific mechanisms of SPMs that govern the resolution of bacteria-initiated inflammation.

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.

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

Background

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

Methods

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

Results

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

Conclusion

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

Metabolomics in infectious diseases and drug discovery

Metabolomics has emerged as an invaluable tool that can be used along with genomics, transcriptomics and proteomics to understand host-pathogen interactions at small-molecule levels. Metabolomics has been used to study a variety of infectious diseases and applications. The most common application of metabolomics is for prognostic and diagnostic purposes, specifically the screening of disease-specific biomarkers by either NMR-based or mass spectrometry-based metabolomics. In addition, metabolomics is of great significance for the discovery of druggable metabolic enzymes and/or metabolic regulators through the use of state-of-the-art flux analysis, for example, via the elucidation of metabolic mechanisms. This review discusses the application of metabolomics technologies to biomarker screening, the discovery of drug targets in infectious diseases such as viral, bacterial and parasite infections and immunometabolomics, highlights the challenges associated with accessing metabolite compartmentalization and discusses the available tools for determining local metabolite concentrations.

Integrative Multi-Omics Reveals Serum Markers of Tuberculosis in Advanced HIV

Tuberculosis (TB) accounts for disproportionate morbidity and mortality among persons living with HIV (PLWH). Conventional methods of TB diagnosis, including smear microscopy and Xpert MTB/RIF, have lower sensitivity in PLWH. Novel high-throughput approaches, such as miRNAomics and metabolomics, may advance our ability to recognize subclinical and difficult-to-diagnose TB, especially in very advanced HIV. We conducted a case-control study leveraging REMEMBER, a multi-country, open-label randomized controlled trial comparing 4-drug empiric standard TB treatment with isoniazid preventive therapy in PLWH initiating antiretroviral therapy (ART) with CD4 cell counts <50 cells/μL. Twenty-three cases of incident TB were site-matched with 32 controls to identify microRNAs (miRNAs), metabolites, and cytokines/chemokines, associated with the development of newly diagnosed TB in PLWH. Differentially expressed miRNA analysis revealed 11 altered miRNAs with a fold change higher than 1.4 or lower than -1.4 in cases relative to controls (p<0.05). Our analysis revealed no differentially abundant metabolites between cases and controls. We found higher TNFα and IP-10/CXCL10 in cases (p=0.011, p=0.0005), and higher MDC/CCL22 in controls (p=0.0072). A decision-tree algorithm identified gamma-glutamylthreonine and hsa-miR-215-5p as the optimal variables to classify incident TB cases (AUC 0.965; 95% CI 0.925-1.000). hsa-miR-215-5p, which targets genes in the TGF-β signaling pathway, was downregulated in cases. Gamma-glutamylthreonine, a breakdown product of protein catabolism, was less abundant in cases. To our knowledge, this is one of the first uses of a multi-omics approach to identify incident TB in severely immunosuppressed PLWH.

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.

MS2Compound: A User-Friendly Compound Identification Tool for LC-MS/MS-Based Metabolomics Data

Metabolomics is a leading frontier of systems science and biomedical innovation. However, metabolite identification in mass spectrometry (MS)-based global metabolomics investigations remains a formidable challenge. Moreover, lack of comprehensive spectral databases hinders accurate identification of compounds in global MS-based metabolomics. Creating experiment-derived metabolite spectral libraries tailored to each experiment is labor-intensive. Therefore, predicted spectral libraries could serve as a better alternative. User-friendly tools are much needed, as the currently available metabolomic analysis tools do not offer adequate provision for users to create or choose context-specific databases. Here, we introduce the MS2Compound, a metabolite identification tool, which can be used to generate a custom database of predicted spectra using the Competitive Fragmentation Modeling-ID (CFM-ID) algorithm, and identify metabolites or compounds from the generated database. The database generator can create databases of the model/context/species used in the metabolomics study. The MS2Compound is also powered with mS-score, a scoring function for matching raw fragment spectra to a predicted spectra database. We demonstrated that mS-score is robust in par with dot product and hypergeometric score in identifying metabolites using benchmarking datasets. We evaluated and highlight here the unique features of the MS2Compound by a re-analysis of a publicly available metabolomic dataset (MassIVE id: MSV000086784) for a complex traditional drug formulation called Triphala. In conclusion, we believe that the omics systems science and biomedical research and innovation community in the field of metabolomics will find the MS2Compound as a user-friendly analysis tool of choice to accelerate future metabolomic analyses.

Understanding Metabolic Regulation Between Host and Pathogens: New Opportunities for the Development of Improved Therapeutic Strategies Against Mycobacterium tuberculosis Infection

Mycobacterium tuberculosis (Mtb) causes chronic granulomatous lung disease in humans. Recently, novel strategies such as host-directed therapeutics and adjunctive therapies that enhance the effect of existing antibiotics have emerged to better control Mtb infection. Recent advances in understanding the metabolic interplay between host immune cells and pathogens have provided new insights into how their interactions ultimately influence disease outcomes and antibiotic-treatment efficacy. In this review, we describe how metabolic cascades in immune environments and relevant metabolites produced from immune cells during Mtb infection play critical roles in the progression of diseases and induction of anti-Mtb protective immunity. In addition, we introduce how metabolic alterations in Mtb itself can lead to the development of persister cells that are resistant to host immunity and can eventually evade antibiotic attacks. Further understanding of the metabolic link between host cells and Mtb may contribute to not only the prevention of Mtb persister development but also the optimization of host anti-Mtb immunity together with enhanced efficacy of existing antibiotics. Overall, this review highlights novel approaches to improve and develop host-mediated therapeutic strategies against Mtb infection by restoring and switching pathogen-favoring metabolic conditions with host-favoring conditions.

The Manipulation of the Lipid Mediator Metabolism as Adjunct Host-Directed Therapy in Tuberculosis

Host-directed therapies (HDTs) enhance the host response to tuberculosis (TB) infection to reduce disease severity. For instance, the manipulation of lipid mediator production diminishes the hyperactive immune response which is a known pathological feature of TB that generates lung tissue damage. Non-steroidal anti-inflammatory drugs (NSAIDs) and omega-3 long-chain polyunsaturated fatty acids (n-3 LCPUFA) are examples of such HDTs. In this mini-review, we recapitulate the literature available on the effects of NSAIDs and n-3 LCPUFA in TB as well as the immunological pathways underpinning these effects. Many NSAIDs have a great deal of data describing their effects and safety and in many jurisdictions are inexpensive, and sold over the counter in neighborhood convenience stores and supermarkets. The potential benefits of NSAIDs in TB are well-documented in pre-clinical studies. The reduction of pro-inflammatory lipid mediator production by inhibiting cyclooxygenase (COX) pathways with NSAIDs has been found to improve lung histopathology, bacterial control, and survival. Additionally, n-3 LCPUFA and its novel bioactive metabolites produced by COX and lipoxygenase (LOX) have been identified as safe and effective pro-resolving and antibacterial pharmaconutrients. Nevertheless, heterogeneous results have been reported in pre-clinical TB studies. Recently, the importance of the correct timing of NSAIDs and n-3 LCPUFA administration in TB has also been highlighted. This mini-review will provide a better understanding of the potential contribution of these therapies toward reducing inflammatory lung damage and improving bactericidal activity, especially during later stages of TB infection. It further highlights that clinical trials are required to confirm benefit and safety in TB patients.

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

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

Specialized proresolving mediators in infection and lung injury

Specialized proresolving mediators (SPMs) are endogenous lipid metabolites of long-chain polyunsaturated fatty acids that are involved in promoting the resolution of inflammation. Many disease conditions characterized by excessive inflammation have impaired or altered SPM biosynthesis, which may lead to chronic, unresolved inflammation. Exogenous administration of SPMs in infectious conditions has been shown to be effective at improving infection clearance and survival in preclinical models. SPMs have also shown tremendous promise in the context of inflammatory lung conditions, such as acute respiratory distress syndrome and chronic obstructive pulmonary disease, mostly in preclinical settings. To date, SPMs have not been studied in the context of the novel Coronavirus, severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2), however their preclinical efficacy in combatting infections and improving acute respiratory distress suggest they may be a valuable resource in the fight against Coronavirus disease-19 (COVID-19). Overall, while the research on SPMs is still evolving, they may offer a novel therapeutic option for inflammatory conditions.

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.

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

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

Pediatric Tuberculosis: The Impact of "Omics" on Diagnostics Development

Tuberculosis (TB) is a major public health concern for all ages. However, the disease presents a larger challenge in pediatric populations, partially owing to the lack of reliable diagnostic standards for the early identification of infection. Currently, there are no biomarkers that have been clinically validated for use in pediatric TB diagnosis. Identification and validation of biomarkers could provide critical information on prognosis of disease, and response to treatment. In this review, we discuss how the “omics” approach has influenced biomarker discovery and the advancement of a next generation rapid point-of-care diagnostic for TB, with special emphasis on pediatric disease. Limitations of current published studies and the barriers to their implementation into the field will be thoroughly reviewed within this article in hopes of highlighting future avenues and needs for combating the problem of pediatric tuberculosis.

HIV and the tuberculosis "set point": how HIV impairs alveolar macrophage responses to tuberculosis and sets the stage for progressive disease

As HIV has fueled a global resurgence of tuberculosis over the last several decades, there is a growing awareness that HIV-mediated impairments in both innate and adaptive immunity contribute to the heightened risk of tuberculosis in people with HIV. Since early immune responses to Mycobacterium tuberculosis (Mtb) set the stage for subsequent control or progression to active tuberculosis disease, early host-pathogen interactions following Mtb infection can be thought of as establishing a mycobacterial "set point," which we define as the mycobacterial burden at the point of adaptive immune activation. This early immune response is impaired in the context of HIV coinfection, allowing for a higher mycobacterial set point and greater likelihood of progression to active disease with greater bacterial burden. Alveolar macrophages, as the first cells to encounter Mtb in the lungs, play a critical role in containing Mtb growth and establishing the mycobacterial set point. However, a number of key macrophage functions, ranging from pathogen recognition and uptake to phagocytosis and microbial killing, are blunted in HIV coinfection. To date, research evaluating the effects of HIV on the alveolar macrophage response to Mtb has been relatively limited, particularly with regard to the critical early events that help to dictate the mycobacterial set point. A greater understanding of alveolar macrophage functions impacted by HIV coinfection will improve our understanding of protective immunity to Mtb and may reveal novel pathways amenable to intervention to improve both early immune control of Mtb and clinical outcomes for the millions of people worldwide infected with HIV.

Untargeted high-resolution plasma metabolomic profiling predicts outcomes in patients with coronary artery disease

Objective

Patients with CAD have substantial residual risk of mortality, and whether hitherto unknown small-molecule metabolites and metabolic pathways contribute to this risk is unclear. We sought to determine the predictive value of plasma metabolomic profiling in patients with CAD.

Approach and results

Untargeted high-resolution plasma metabolomic profiling of subjects undergoing coronary angiography was performed using liquid chromatography/mass spectrometry. Metabolic features and pathways associated with mortality were identified in 454 subjects using metabolome-wide association studies and Mummichog, respectively, and validated in 322 subjects. A metabolomic risk score comprising of log-transformed HR estimates of metabolites that associated with mortality and passed LASSO regression was created and its performance validated. In 776 subjects (66.8 years, 64% male, 17% Black), 433 and 357 features associated with mortality (FDR-adjusted q<0.20); and clustered into 21 and 9 metabolic pathways in first and second cohorts, respectively. Six pathways (urea cycle/amino group, tryptophan, aspartate/asparagine, lysine, tyrosine, and carnitine shuttle) were common. A metabolomic risk score comprising of 7 metabolites independently predicted mortality in the second cohort (HR per 1-unit increase 2.14, 95%CI 1.62, 2.83). Adding the score to a model of clinical predictors improved risk discrimination (delta C-statistic 0.039, 95%CI -0.006, 0.086; and Integrated Discrimination Index 0.084, 95%CI 0.030, 0.151) and reclassification (continuous Net Reclassification Index 23.3%, 95%CI 7.9%, 38.2%).

Conclusions

Differential regulation of six metabolic pathways involved in myocardial energetics and systemic inflammation is independently associated with mortality in patients with CAD. A novel risk score consisting of representative metabolites is highly predictive of mortality.

Untargeted metabolomics reveal dysregulations in sugar, methionine, and tyrosine pathways in the prodromal state of AD

INTRODUCTION

Altered metabolism may occur years before clinical manifestations of Alzheimer's disease (AD). We used untargeted metabolomics on the cerebrospinal fluid of patients with mild cognitive impairment (MCI) to uncover metabolomic derangements.

METHODS

CSF from 92 normal controls and 93 MCI underwent untargeted metabolomics using high-resolution mass spectrometry with liquid chromatography. Partial least squares discriminant analysis was used followed by metabolite annotation and pathway enrichment analysis (PES). Significant features were correlated with disease phenotypes.

RESULTS

We identified 294 features differentially expressed between the two groups and 94 were annotated. PES showed that sugar regulation (N-glycan, P = .0007; sialic acid, P = .0014; aminosugars, P = .0042; galactose, P = .0054), methionine regulation (P = .0081), and tyrosine metabolism (P = .019) pathways were differentially activated and significant features within these pathways correlated with multiple disease phenotypes.

CONCLUSION

There is a metabolic signature characterized by impairments in sugars, methionine, and tyrosine regulation in MCI. Targeting these pathways may offer new therapeutic approaches to AD.

Systemic lipid dysregulation is a risk factor for macular neurodegenerative disease

Macular Telangiectasia type 2 (MacTel) is an uncommon bilateral retinal disease, in which glial cell and photoreceptor degeneration leads to central vision loss. The causative disease mechanism is largely unknown, and no treatment is currently available. A previous study found variants in genes associated with glycine-serine metabolism (PSPH, PHGDH and CPS1) to be associated with MacTel, and showed low levels of glycine and serine in the serum of MacTel patients. Recently, a causative role of deoxysphingolipids in MacTel disease has been established. However, little is known about possible other metabolic dysregulation. Here we used a global metabolomics platform in a case-control study to comprehensively profile serum from 60 MacTel patients and 58 controls. Analysis of the data, using innovative computational approaches, revealed a detailed, disease-associated metabolic profile with broad changes in multiple metabolic pathways. This included alterations in the levels of several metabolites that are directly or indirectly linked to glycine-serine metabolism, further validating our previous genetic findings. We also found changes unrelated to PSPH, PHGDH and CPS1 activity. Most pronounced, levels of several lipid groups were altered, with increased phosphatidylethanolamines being the most affected lipid group. Assessing correlations between different metabolites across our samples revealed putative functional connections. Correlations between phosphatidylethanolamines and sphingomyelin, and glycine-serine and sphingomyelin, observed in controls, were reduced in MacTel patients, suggesting metabolic re-wiring of sphingomyelin metabolism in MacTel patients. Our findings provide novel insights into metabolic changes associated with MacTel and implicate altered lipid metabolism as a contributor to this retinal neurodegenerative disease.

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

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

Performance of metabonomic serum analysis for diagnostics in paediatric tuberculosis

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

Design and Rationale of the Biomarker Center of the Household Air Pollution Intervention Network (HAPIN) Trial

BACKGROUND

Biomarkers of exposure, susceptibility, and effect are fundamental for understanding environmental exposures, mechanistic pathways of effect, and monitoring early adverse outcomes. To date, no study has comprehensively evaluated a large suite and variety of biomarkers in household air pollution (HAP) studies in concert with exposure and outcome data. The Household Air Pollution Intervention Network (HAPIN) trial is a liquified petroleum gas (LPG) fuel/stove randomized intervention trial enrolling 800 pregnant women in each of four countries (i.e., Peru, Guatemala, Rwanda, and India). Their offspring will be followed from birth through 12 months of age to evaluate the role of pre- and postnatal exposure to HAP from biomass burning cookstoves in the control arm and LPG stoves in the intervention arm on growth and respiratory outcomes. In addition, up to 200 older adult women per site are being recruited in the same households to evaluate indicators of cardiopulmonary, metabolic, and cancer outcomes.

OBJECTIVES

Here we describe the rationale and ultimate design of a comprehensive biomarker plan to enable us to explore more fully how exposure is related to disease outcome.

METHODS

HAPIN enrollment and data collection began in May 2018 and will continue through August 2021. As a part of data collection, dried blood spot (DBS) and urine samples are being collected three times during pregnancy in pregnant women and older adult women. DBS are collected at birth for the child. DBS and urine samples are being collected from the older adult women and children three times throughout the child's first year of life. Exposure biomarkers that will be longitudinally measured in all participants include urinary hydroxy-polycyclic aromatic hydrocarbons, volatile organic chemical metabolites, metals/metalloids, levoglucosan, and cotinine. Biomarkers of effect, including inflammation, endothelial and oxidative stress biomarkers, lung cancer markers, and other clinically relevant measures will be analyzed in urine, DBS, or blood products from the older adult women. Similarly, genomic/epigenetic markers, microbiome, and metabolomics will be measured in older adult women samples.

DISCUSSION

Our study design will yield a wealth of biomarker data to evaluate, in great detail, the link between exposures and health outcomes. In addition, our design is comprehensive and innovative by including cutting-edge measures such as metabolomics and epigenetics. https://doi.org/10.1289/EHP5751.