Novel therapeutic evaluation biomarkers of lipid metabolism targets in uncomplicated pulmonary tuberculosis patients

NIR-II AIE Luminogen-Based Erythrocyte-Like Nanoparticles with Granuloma-Targeting and Self-Oxygenation Characteristics for Combined Phototherapy of Tuberculosis

Tuberculosis, a fatal infectious disease caused by Mycobacterium tuberculosis (M.tb), is difficult to treat with antibiotics due to drug resistance and short drug half-life. Phototherapy represents a promising alternative to antibiotics in combating M.tb. Exploring an intelligent material allowing effective tuberculosis treatment is definitely appealing, yet a significantly challenging task. Herein, an all-in-one biomimetic therapeutic nanoparticle featured by aggregation-induced second near-infrared emission, granuloma-targeting, and self-oxygenation is constructed, which can serve for prominent fluorescence imaging-navigated combined phototherapy toward tuberculosis. After camouflaging the biomimetic erythrocyte membrane, the nanoparticles show significantly prolonged blood circulation and increased selective accumulation in tuberculosis granuloma. Upon laser irradiation, the loading photosensitizer of aggregation-induced emission photosensitizer elevates the production of reactive oxygen species (ROS), causing M.tb damage and death. The delivery of oxygen to relieve the hypoxic granuloma microenvironment supports ROS generation during photodynamic therapy. Meanwhile, the photothermal agent, Prussian blue nanoparticles, plays the role of good photothermal killing effect on M.tb. Moreover, the growth and proliferation of granuloma and M.tb colonies are effectively inhibited in the nanoparticle-treated tuberculous granuloma model mice, suggesting the combined therapeutic effects of enhancing photodynamic therapy and photothermal therapy.

Individualized lipid profile in urine-derived extracellular vesicles from clinical patients with Mycobacterium tuberculosis infections

Background

Lipids are a key nutrient source for the growth and reproduction of Mycobacterium tuberculosis (Mtb). Urine-derived extracellular vesicles (EVs), because of its non-invasive sampling, lipid enrichment, and specific sorting character, have been recognized as a promising research target for biomarker discovery and pathogenesis elucidation in tuberculosis (TB). We aim to profile lipidome of Mtb-infected individuals, offer novel lipid signatures for the development of urine-based TB testing, and provide new insights into the lipid metabolism after Mtb infection.

Methods

Urine-derived extracellular vesicles from 41 participants (including healthy, pulmonary tuberculosis, latent tuberculosis patients, and other lung disease groups) were isolated and individually detected using targeted lipidomics and proteomics technology platforms. Biomarkers were screened by multivariate and univariate statistical analysis and evaluated by SPSS software. Correlation analyses were performed on lipids and proteins using the R Hmisc package.

Results

Overall, we identified 226 lipids belonging to 14 classes. Of these, 7 potential lipid biomarkers for TB and 6 for latent TB infection (LTBI) were identified, all of which were classified into diacylglycerol (DAG), monoacylglycerol (MAG), free fatty acid (FFA), and cholesteryl ester (CE). Among them, FFA (20:1) was the most promising biomarker target in diagnosing TB/LTBI from other compared groups and also have great diagnostic performance in distinguishing TB from LTBI with AUC of 0.952. In addition, enhanced lipolysis happened as early as individuals got latent Mtb infection, and ratio of raft lipids was gradually elevated along TB progression.

Conclusion

This study demonstrated individualized lipid profile of urinary EVs in patients with Mtb infection, revealed novel potential lipid biomarkers for TB/LTBI diagnosis, and explored mechanisms by which EV lipid raft-dependent bio-processes might affect pathogenesis. It lays a solid foundation for the subsequent diagnosis and therapeutic intervention of TB.

Plasma metabolomic analysis reveals the metabolic characteristics and potential diagnostic biomarkers of spinal tuberculosis

Objectives

This study aimed to conduct a non-targeted metabolomic analysis of plasma from patients with spinal tuberculosis (STB) to systematically elucidate the metabolomic alterations associated with STB, and explore potential diagnostic biomarkers for STB.

Methods

From January 2020 to January 2022, 30 patients with spinal tuberculosis (STBs) clinically diagnosed at the General Hospital of Ningxia Medical University and 30 age- and sex-matched healthy controls (HCs) were selected for this study. Using ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) based metabolomics, we analyzed the metabolic profiles of 60 plasma samples. Statistical analyses, pathway enrichment, and receiver operating characteristic (ROC) analyses were performed to screen and evaluate potential diagnostic biomarkers.

Results

Metabolomic profiling revealed distinct alterations between the STBs and HCs cohorts. A total of 1635 differential metabolites were screened, functionally clustered, and annotated. The results showed that the differential metabolites were enriched in sphingolipid metabolism, tuberculosis, cutin, suberine and wax biosynthesis, beta-alanine metabolism, methane metabolism, and other pathways. Through the random forest algorithm, LysoPE (18:1(11Z)/0:0), 8-Demethyl-8-formylriboflavin 5'-phosphate, Glutaminyl-Gamma-glutamate, (2R)-O-Phospho-3-sulfolactate, and LysoPE (P-16:0/0:0) were determined to have high independent diagnostic value.

Conclusions

STBs exhibited significantly altered metabolite profiles compared with HCs. Here, we provide a global metabolomic profile and identify potential diagnostic biomarkers of STB. Five potential independent diagnostic biomarkers with high diagnostic value were screened. This study provides novel insights into the pathogenesis, diagnosis, and treatment strategies of STB.

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

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

Genome-wide meta-analysis and fine-mapping prioritize potential causal variants and genes related to leprosy

To date, genome-wide association studies (GWASs) have discovered 35 susceptible loci of leprosy; however, the cumulative effects of these loci can only partially explain the overall risk of leprosy, and the causal variants and genes within these loci remain unknown. Here, we conducted out new GWASs in two independent cohorts of 5007 cases and 4579 controls and then a meta-analysis in these newly generated and multiple previously published (2277 cases and 3159 controls) datasets were performed. Three novel and 15 previously reported risk loci were identified from these datasets, increasing the known leprosy risk loci of explained genetic heritability from 23.0 to 38.5%. A comprehensive fine-mapping analysis was conducted, and 19 causal variants and 14 causal genes were identified. Specifically, manual checking of epigenomic information from the Epimap database revealed that the causal variants were mainly located within the immune-relevant or immune-specific regulatory elements. Furthermore, by using gene-set, tissue, and cell-type enrichment analyses, we highlighted the key roles of immune-related tissues and cells and implicated the PD-1 signaling pathways in the pathogenetic mechanism of leprosy. Collectively, our study identified candidate causal variants and elucidated the potential regulatory and coding mechanisms for genes associated with leprosy.

Characteristics of plasma exosomes in drug-resistant tuberculosis patients

BACKGROUND

Increasing prevalence of drug-resistant tuberculosis (DR-TB) poses a major challenge to the early detection and effective control of tuberculosis (TB). Exosomes carrying proteins and nucleic acid mediate intercellular communication between host and pathogen including Mycobacterium tuberculosis. However, molecular events of exosomes indicating the status and development of DR-TB remain unknown. This study determined the proteomics of exosome in DR-TB and explored the potential pathogenesis of DR-TB.

METHODS

Plasma samples were collected from 17 DR-TB patients and 33 non-drug-resistant tuberculosis (NDR-TB) patients using grouped case-control study design. After exosomes of plasma were isolated and confirmed by compositional and morphological measurement for exosomal characteristics, a label-free quantitative proteomics of exosomes was performed and differential protein components were determined via bioinformatics analysis.

RESULTS

Compared with the NDR-TB group, we identified 16 up-regulated proteins and 10 down-regulated proteins in the DR-TB group. The down-regulated proteins were mainly apolipoproteins and mainly enriched in cholesterol metabolism-related pathways. Apolipoproteins family including APOA1, APOB, APOC1 were key proteins in protein-protein interaction network.

CONCLUSION

Differentially expressed proteins in the exosomes may indicate the status of DR-TB from NDR-TB. Apolipoproteins family including APOA1, APOB, APOC1 may be involved in the pathogenesis of DR-TB by regulating cholesterol metabolism via exosomes.

Tuberculosis is associated with sputum metabolome variations, irrespective of patient sex or HIV status: an untargeted GCxGC-TOFMS study

INTRODUCTION

Various studies have identified TB-induced metabolome variations. However, in most of these studies, a large degree of variation exists between individual patients.

OBJECTIVES

To identify differential metabolites for TB, independent of patients' sex or HIV status.

METHODS

Untargeted GCxGC/TOF-MS analyses were applied to the sputum of 31 TB + and 197 TB- individuals. Univariate statistics were used to identify metabolites which are significantly different between TB + and TB- individuals (a) irrespective of HIV status, and (b) with a HIV + status. Comparisons a and b were repeated for (i) all participants, (ii) males only and (iii) females only.

RESULTS

Twenty-one compounds were significantly different between the TB + and TB- individuals within the female subgroup (11% lipids; 10% carbohydrates; 1% amino acids, 5% other and 73% unannotated), and 6 within the male subgroup (20% lipids; 40% carbohydrates; 6% amino acids, 7% other and 27% unannotated). For the HIV + patients (TB + vs. TB-), a total of 125 compounds were significant within the female subgroup (16% lipids; 8% carbohydrates; 12% amino acids, 6% organic acids, 8% other and 50% unannotated), and 44 within the male subgroup (17% lipids; 2% carbohydrates; 14% amino acids related, 8% organic acids, 9% other and 50% unannotated). Only one annotated compound, 1-oleoyl lysophosphaditic acid, was consistently identified as a differential metabolite for TB, irrespective of sex or HIV status. The potential clinical application of this compound should be evaluated further.

CONCLUSIONS

Our findings highlight the importance of considering confounders in metabolomics studies in order to identify unambiguous disease biomarkers.

Comprehensive lipid profiles investigation reveals host metabolic and immune alterations during anti-tuberculosis treatment: Implications for therapeutic monitoring

In this study, we investigated the lipidome of tuberculosis patients during standard chemotherapy to discover biosignatures that could aid therapeutic monitoring. UPLC-QToF MS was used to analyze 82 baseline and treatment plasma samples of patients with pulmonary tuberculosis. Subsequently, a data-driven and knowledge-based workflow, including robust annotation, statistical analysis, and functional analysis, was applied to assess lipid profiles during treatment. Overall, the lipids species from 17 lipid subclasses were significantly altered by anti-tuberculosis chemotherapy. Cholesterol ester (CE), monoacylglycerols, and phosphatidylcholine (PC) were upregulated, whereas triacylglycerols, sphingomyelin, and ether-linked phosphatidylethanolamines (PE O-) were downregulated. Notably, PCs demonstrated a clear upward expression pattern during tuberculosis treatment. Several lipid species were identified as potential biomarkers for therapeutic monitoring, such as PC(42:6), PE(O-40:5), CE(24:6), and dihexosylceramide Hex2Cer(34:2;2 O). Functional and lipid gene enrichment analysis revealed alterations in pathways related to lipid metabolism and host immune responses. In conclusion, this study provides a foundation for the use of lipids as biomarkers for clinical management of tuberculosis.

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.

ALB, HP, OAF and RBP4 as novel protein biomarkers for identifying cured patients with pulmonary tuberculosis by DIA

BACKGROUND

Pulmonary tuberculosis (TB) is a serious infectious disease that lacks robust blood-based biomarkers to identify cured TB. Some discharged patients are not fully cured and may relapse or even develop multidrug-resistant TB. This study is committed to finding proteomic-based plasma biomarkers to support establishing laboratory standards for clinical TB cure.

METHODS

Data-independent acquisition (DIA) was used to obtain the plasma protein expression profiles of TB patients at different treatment stages compared with healthy controls. Multivariate statistical methods and bioinformatics were used to analyze the data.

RESULTS

Bioinformatic analysis suggests coagulation dysfunction and vitamin and lipid metabolism disturbances in TB. Albumin (ALB), haptoglobin (HP), out at first protein homolog (OAF), and retinol-binding protein 4 (RBP4) can be used to establish a diagnostic model for the efficacy evaluation of TB with an area under the curve of 0.963, which could effectively distinguish untreated TB patients from cured patients.

CONCLUSIONS

Our research demonstrated that ALB, HP, OAF and RBP4 can be potential biomarkers for evaluating the efficacy of TB. These findings may provide experimental data for establishing the laboratory indicators of clinical TB cure and providing clinicians with new targets for exploring the underlying mechanisms of TB pathogenesis.

Comprehensive lipid and lipid-related gene investigations of host immune responses to characterize metabolism-centric biomarkers for pulmonary tuberculosis

Despite remarkable success in the prevention and treatment of tuberculosis (TB), it remains one of the most devastating infectious diseases worldwide. Management of TB requires an efficient and timely diagnostic strategy. In this study, we comprehensively characterized the plasma lipidome of TB patients, then selected candidate lipid and lipid-related gene biomarkers using a data-driven, knowledge-based framework. Among 93 lipids that were identified as potential biomarker candidates, ether-linked phosphatidylcholine (PC O–) and phosphatidylcholine (PC) were generally upregulated, while free fatty acids and triglycerides with longer fatty acyl chains were downregulated in the TB group. Lipid-related gene enrichment analysis revealed significantly altered metabolic pathways (e.g., ether lipid, linolenic acid, and cholesterol) and immune response signaling pathways. Based on these potential biomarkers, TB patients could be differentiated from controls in the internal validation (random forest model, area under the curve [AUC] 0.936, 95% confidence interval [CI] 0.865–0.992). PC(O-40:4), PC(O-42:5), PC(36:0), and PC(34:4) were robust biomarkers able to distinguish TB patients from individuals with latent infection and healthy controls, as shown in the external validation. Small changes in expression were identified for 162 significant lipid-related genes in the comparison of TB patients vs. controls; in the random forest model, their utilities were demonstrated by AUCs that ranged from 0.829 to 0.956 in three cohorts. In conclusion, this study introduced a potential framework that can be used to identify and validate metabolism-centric biomarkers.

Targeted Lipidomics Reveal the Effect of Perchlorate on Lipid Profiles in Liver of High-Fat Diet Mice

Perchlorate, commonly available in drinking water and food, acts on the iodine uptake by the thyroid affecting lipid metabolism. High-fat diets leading to various health problems continually raise public concern. In the present study, liver lipid metabolism profiles and metabolic pathways were investigated in C57BL/6J mice chronically exposed to perchlorate using targeted metabolomics. Mice were fed a high-fat diet and treated orally with perchlorate at 0.1 mg/kg bw (body weight), 1 mg/kg bw and 10 mg/kg bw daily for 12 weeks. Perchlorate induced disorders of lipid metabolism in vivo and hepatic lipid accumulation confirmed by serum biochemical parameters and histopathological examination. There were 34 kinds of lipid in liver detected by UHPLC-MS/MS and key metabolites were identified by multivariate statistical analysis evaluated with VIP > 1, p-value < 0.05, fold change > 1.2 or < 0.8. Perchlorate low, medium and high dose groups were identified with 11, 7 and 8 significantly altered lipid metabolites compared to the control group, respectively. The results of the metabolic pathway analysis revealed that the differential metabolites classified into different experimental groups contribute to the glycerophospholipid metabolic pathway. These findings provide insights into the effects of perchlorate on lipid metabolism during long-term exposure to high-fat diets and contribute to the evaluation of perchlorate liver toxic mechanisms and health effects.

Novel Potential Diagnostic Serum Biomarkers of Metabolomics in Osteoarticular Tuberculosis Patients: A Preliminary Study

Osteoarticular tuberculosis is one of the extrapulmonary tuberculosis, which is mainly caused by direct infection of Mycobacterium tuberculosis or secondary infection of tuberculosis in other parts. Due to the low specificity of the current detection method, it is leading to a high misdiagnosis rate and subsequently affecting the follow-up treatment and prognosis. Metabolomics is mainly used to study the changes of the body’s metabolites in different states, so it can serve as an important means in the discovery of disease-related metabolic biomarkers and the corresponding mechanism research. Liquid chromatography tandem mass spectrometry (LC-MS/MS) was used to detect and analyze metabolites in the serum with osteoarticular tuberculosis patients, disease controls, and healthy controls to find novel metabolic biomarkers that could be used in the diagnosis of osteoarticular tuberculosis. Our results showed that 68 differential metabolites (p<0.05, fold change>1.0) were obtained in osteoarticular tuberculosis serum after statistical analysis. Then, through the evaluation of diagnostic efficacy, PC[o-16:1(9Z)/18:0], PC[20:4(8Z,11Z,14Z,17Z)/18:0], PC[18:0/22:5(4Z,7Z,10Z,13Z,16Z)], SM(d18:1/20:0), and SM[d18:1/18:1(11Z)] were found as potential biomarkers with high diagnostic efficacy. Using bioinformatics analysis, we further found that these metabolites share many lipid metabolic signaling pathways, such as choline metabolism, sphingolipid signaling, retrograde endocannabinoid signaling, and sphingolipid and glycerophospholipid metabolism; these results suggest that lipid metabolism plays an important role in the pathological process of tuberculosis. This study can provide certain reference value for the study of metabolic biomarkers of osteoarticular tuberculosis and the mechanism of lipid metabolism in osteoarticular tuberculosis and even other tuberculosis diseases.

The binding mechanism of NHWD-870 to bromodomain-containing protein 4 based on molecular dynamics simulations and free energy calculation

Bromodomain and extra-terminal (BET) proteins (BRD2, BRD3, BRD4, and BRDT) are epigenetic readers with tandem bromodomains.

Lipid Droplets, the Central Hub Integrating Cell Metabolism and the Immune System

Lipid droplets (LDs) are commonly found in various biological cells and are organelles related to cell metabolism. LDs, the number and size of which are heterogeneous across cell type, are primarily composed of polar lipids and proteins on the surface with neutral lipids in the core. Neutral lipids stored in LDs can be degraded by lipolysis and lipophagocytosis, which are regulated by various proteins. The process of LD formation can be summarized in four steps. In addition to energy production, LDs play an extremely pivotal role in a variety of physiological and pathological processes, such as endoplasmic reticulum stress, lipid toxicity, storage of fat-soluble vitamins, regulation of oxidative stress, and reprogramming of cell metabolism. Interestingly, LDs, the hub of integration between metabolism and the immune system, are involved in antitumor immunity, anti-infective immunity (viruses, bacteria, parasites, etc.) and some metabolic immune diseases. Herein, we summarize the role of LDs in several major immune cells as elucidated in recent years, including T cells, dendritic cells, macrophages, mast cells, and neutrophils. Additionally, we analyze the role of the interaction between LDs and immune cells in two typical metabolic immune diseases: atherosclerosis and Mycobacterium tuberculosis infection.

Mesenchymal Stem Cells and Tuberculosis: Clinical Challenges and Opportunities

Tuberculosis (TB) is one of the communicable diseases caused by Mycobacterium tuberculosis (Mtb) infection, affecting nearly one-third of the world's population. However, because the pathogenesis of TB is still not fully understood and the development of anti-TB drug is slow, TB remains a global public health problem. In recent years, with the gradual discovery and confirmation of the immunomodulatory properties of mesenchymal stem cells (MSCs), more and more studies, including our team's research, have shown that MSCs seem to be closely related to the growth status of Mtb and the occurrence and development of TB, which is expected to bring new hope for the clinical treatment of TB. This article reviews the relationship between MSCs and the occurrence and development of TB and the potential application of MSCs in the treatment of TB.